From 7042090889663d8893d1eaf3c9eb96e7a0046877 Mon Sep 17 00:00:00 2001
From: "Mads M. Pedersen" <mmpe@dtu.dk>
Date: Fri, 28 May 2021 06:39:20 +0000
Subject: [PATCH] Yaw etc (see description)
---
docs/_static/wt_in_yaw.svg | 3575 ++++++------
.../notebooks/EngineeringWindFarmModels.ipynb | 4844 +++++++++--------
docs/notebooks/YawMisalignment.ipynb | 196 +-
docs/notebooks/exercises/WakeDeflection.ipynb | 288 +-
py_wake/deficit_models/fuga.py | 5 +-
py_wake/deflection_models/fuga_deflection.py | 154 +-
py_wake/deflection_models/jimenez.py | 11 +-
.../data/iea34_130rwt/_iea34_130rwt.py | 5 +-
py_wake/examples/data/lillgrund.py | 3 +-
py_wake/flow_map.py | 4 +-
.../test_deficit_models.py | 24 +-
.../tests/test_deficit_models/test_fuga.py | 42 +-
.../test_deflection_models.py | 9 +-
.../test_fuga_deflection.py | 99 +
.../D080.0000_zH070.0000_FIT9999UL.dat | 2 +-
.../D080.0000_zH070.0000_FIT9999UT.dat | 2 +-
.../D080.0000_zH070.0000_FIT9999VL.dat | 2 +-
.../D080.0000_zH070.0000_FIT9999VT.dat | 2 +-
.../inputfile.par | 10 +-
.../2MW_FIT9999UL.dat | 3 -
.../2MW_FIT9999UT.dat | 3 -
.../2MW_FIT9999VL.dat | 3 -
.../2MW_FIT9999VT.dat | 3 -
.../CaseData.bin | Bin 179 -> 0 bytes
.../inputfile.par | 17 -
.../CaseData.bin | Bin 0 -> 179 bytes
.../D080.0000_zH070.0000_FIT9999UL.dat | 3 +
.../D080.0000_zH070.0000_FIT9999UT.dat | 3 +
.../D080.0000_zH070.0000_FIT9999VL.dat | 3 +
.../D080.0000_zH070.0000_FIT9999VT.dat | 3 +
.../inputfile.par | 18 +
.../test_files/fuga/v80_deflection_x.csv | 80 +-
.../fuga/v80_wake_4d_y_no_deflection.csv | 10 +-
.../test_files/fuga/v80_wake_center_x.csv | 82 +-
py_wake/tests/test_flow_map.py | 2 +-
.../test_iea34_surrogates.py | 34 +
py_wake/tests/test_utils/test_model_utils.py | 1 -
.../test_simulation_result.py | 28 +
.../test_wind_farm_model.py | 12 +
.../test_windturbines/test_power_ct_curves.py | 13 +-
.../test_power_ct_wind_turbines.py | 2 +-
.../test_windturbines/test_windturbines.py | 10 +-
py_wake/utils/model_utils.py | 21 +-
py_wake/utils/xarray_utils.py | 30 +-
.../wind_farm_models/engineering_models.py | 4 +-
py_wake/wind_farm_models/wind_farm_model.py | 65 +-
py_wake/wind_turbines/_wind_turbines.py | 12 +-
py_wake/wind_turbines/power_ct_functions.py | 10 +-
.../wind_turbines/wind_turbine_functions.py | 10 +-
49 files changed, 5044 insertions(+), 4718 deletions(-)
create mode 100644 py_wake/tests/test_deflection_models/test_fuga_deflection.py
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UL.dat
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UT.dat
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999VL.dat
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999VT.dat
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/CaseData.bin
delete mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/inputfile.par
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/CaseData.bin
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UL.dat
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UT.dat
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VL.dat
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VT.dat
create mode 100644 py_wake/tests/test_files/fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/inputfile.par
create mode 100644 py_wake/tests/test_wind_farm_models/test_simulation_result.py
create mode 100644 py_wake/tests/test_wind_farm_models/test_wind_farm_model.py
diff --git a/docs/_static/wt_in_yaw.svg b/docs/_static/wt_in_yaw.svg
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diff --git a/docs/notebooks/EngineeringWindFarmModels.ipynb b/docs/notebooks/EngineeringWindFarmModels.ipynb
index ba9e3e9ef..96f29404e 100644
--- a/docs/notebooks/EngineeringWindFarmModels.ipynb
+++ b/docs/notebooks/EngineeringWindFarmModels.ipynb
@@ -1,2423 +1,2425 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Engineering WindFarmModels"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "All Wind farms models take a `Site` and a `WindTurbines` object as input"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Install PyWake if needed\n",
- "try:\n",
- " import py_wake\n",
- "except ModuleNotFoundError:\n",
- " !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake.git"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "# import and setup site and windTurbines\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import os\n",
- "import py_wake\n",
- "from py_wake.examples.data.hornsrev1 import V80, Hornsrev1Site\n",
- "\n",
- "site = Hornsrev1Site()\n",
- "windTurbines = V80()\n",
- "wt_x, wt_y = site.initial_position.T"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Model overview\n",
- "\n",
- "\n",
- "The engineering wind farms models in PyWake are composed of one of two wind farms models in combination with a wake deficit model, a superposition model and optionally a blockage deficit and a turbulence model.\n",
- "\n",
- "- `WindFarmModel`: Defines the proceedure that detemines how wake and blockage deficits propagates in the wind farm. \n",
- "Two models are available:\n",
- " - [PropagateDownwind](#PropagateDownwind) (fast, but blockage is neglected)\n",
- " - [All2AllIterative](#All2AllIterative) (slower but supports blockage).\n",
- "- Wake `DeficitModel`: Calculate wake deficit from one wind turbine to downstream wind turbines or sites in the wind farm. Several common models are available: \n",
- " - [NOJDeficit](#NOJDeficit)\n",
- " - [FugaDeficit](#FugaDeficit)\n",
- " - [BastankhahGaussianDeficit](#BastankhahGaussianDeficit)\n",
- " - [NiayifarGaussianDeficit](#NiayifarGaussianDeficit)\n",
- " - [ZongGaussianDeficit](#ZongGaussianDeficit)\n",
- " - [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit)\n",
- " - [GCLDeficit](#GCLDEficit)\n",
- "- `SuperpositionModel`: Defines how deficits from multiple sources sums up. Available models are:\n",
- " - [LinearSum](#LinearSum): Deficits sum up linearly\n",
- " - [SquaredSum](#SquaredSum): Deficits sum as root-sum-square\n",
- " - [MaxSum](#MaxSum): Only the largest deficit is considered\n",
- "- Blockage `DeficitModel`: Calculate blockage deficit from one wind turbine to other wind turbines or sites in the wind farm. Some models, model upstream effects only while other also models downstream speed-up effects. Available models are:\n",
- " - [SelfSimilarityDeficit](#SelfSimilarityDeficit)\n",
- " - [SelfSimilarityDeficit2020](#SelfSimilarityDeficit2020)\n",
- " - [FugaDeficit](#FugaDeficit)\n",
- " - [VortexCylinder](#VortexCylinder)\n",
- " - [VortexDipole](#VortexDipole)\n",
- " - [RankineHalfBody](#RankineHalfBody)\n",
- " - [HybridInduction](#HybridInduction)\n",
- " - [Rathmann](#Rathmann) \n",
- "- `RotorAvgModel`: Defines one or more points at the rotor to calculate a (weighted) rotor-average deficit from\n",
- " - [RotorCenter](#RotorCenter): One point at the center of the rotor\n",
- " - [GridRotorAvg](#GridRotorAvg): Custom grid in Cartesian coordinates\n",
- " - [EqGridRotorAvg](#EqGridRotorAvg): Equidistant N x N Cartesian grid covering the rotor\n",
- " - [GQGridRotorAvg](#GQGridRotorAvg): M x N cartesian grid using Gaussian quadrature coordinates and weights\n",
- " - [PolarGridRotorAvg](#PolarGridRotorAvg): Custom grid in polar coordinates \n",
- " - [CGIRotorAVG](#CGIRotorAvg): Circular Gauss Integration\n",
- "- `DeflectionModel`: Calculate deflected downwind and crosswind distances due to yaw misalignment, shear etc. Available models are:\n",
- " - [JimenezWakeDeflection](#JimenezWakeDeflection)\n",
- "- `TurbulenceModel`: Calculate added turbulence in the wake from one wind turbine to downstream wind turbines or sites in the wind farm. Available models are:\n",
- " - [STF2005TurbulenceModel](#STF2005TurbulenceModel): Steen Frandsen, from IEC 2005 standard\n",
- " - [STF2017TurbulenceModel](#STF2017TurbulenceModel): Steen Frandsen, from IEC 2017 standard\n",
- " - [GCLTurbulence](#GCLTurbulence): Gunner Chr. Larsen\n",
- " - [CrespoHernandez](#CrespoHernandez): A. Crespo and J. Hern\u00e1ndez\n",
- "- `GroundModel`: Model effects of ground:\n",
- " - [Mirror](#Mirror): The ground acts as a mirror on the wake\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Predefined WindFarmModels\n",
- "The deficit models comprise:\n",
- "\n",
- "| Name | WindFarmModel | Wake DeficitModel | Blockage DeficitModel | SuperpositionModel |\n",
- "| :--- | :--- | :--- | :--- | :--- | \n",
- "| NOJ | [PropagateDownwind](#PropagateDownwind) | [NOJDeficit](#NOJDeficit) | - | [SquaredSum](#SquaredSum) |\n",
- "| Fuga | [PropagateDownwind](#PropagateDownwind) | [FugaDeficit](#FugaDeficit) | - | [LinearSum](#LinearSum) |\n",
- "| FugaBlockage | [All2AllIterative](#All2AllIterative) | [FugaDeficit](#FugaDeficit) | [FugaDeficit](#FugaDeficit) | [LinearSum](#LinearSum) |\n",
- "| BastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [BastankhahGaussianDeficit](#BastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
- "| IEA37SimpleBastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
- "\n",
- "- Default rotor-average model: `RotorCenter`\n",
- "- Default turbulence model: `None`"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "from py_wake import NOJ\n",
- "from py_wake import Fuga\n",
- "from py_wake import FugaBlockage\n",
- "from py_wake import BastankhahGaussian\n",
- "from py_wake import IEA37SimpleBastankhahGaussian\n",
- "\n",
- "# Path to Fuga look-up tables\n",
- "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
- "\n",
- "models = {'NOJ': NOJ(site,windTurbines), \n",
- " 'Fuga': Fuga(lut_path,site,windTurbines),\n",
- " 'FugaBlockage': FugaBlockage(lut_path,site,windTurbines), \n",
- " 'BGaus': BastankhahGaussian(site,windTurbines),\n",
- " 'IEA37BGaus': IEA37SimpleBastankhahGaussian(site,windTurbines)\n",
- " }"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "These models can easily be combined with other models, e.g. NOJ with linear sum superposition:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [],
- "source": [
- "from py_wake.superposition_models import LinearSum\n",
- "models['NOJLinear'] = NOJ(site,windTurbines,superpositionModel=LinearSum())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "or models can be combined in custom ways, e.g. NOJDeficit for the wake, LinearSum superposition and SelfSimilarityDeficit for the blockage:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "from py_wake.wind_farm_models import All2AllIterative\n",
- "from py_wake.deficit_models import NOJDeficit, SelfSimilarityDeficit\n",
- "models['NOJ_ss'] = All2AllIterative(site,windTurbines,\n",
- " wake_deficitModel=NOJDeficit(),\n",
- " superpositionModel=LinearSum(), \n",
- " blockage_deficitModel=SelfSimilarityDeficit() )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "NOJ: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
- "Fuga: Fuga(PropagateDownwind, FugaDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
- "FugaBlockage: FugaBlockage(All2AllIterative, FugaDeficit-wake, FugaDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n",
- "BGaus: BastankhahGaussian(PropagateDownwind, BastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
- "IEA37BGaus: IEA37SimpleBastankhahGaussian(PropagateDownwind, IEA37SimpleBastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
- "NOJLinear: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
- "NOJ_ss: All2AllIterative(EngineeringWindFarmModel, NOJDeficit-wake, SelfSimilarityDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n"
- ]
- }
- ],
- "source": [
- "for name, model in models.items():\n",
- " print (\"%s: %s\"%(name, model))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Engineering WindFarmModel base classes\n",
- "\n",
- "### PropagateDownwind\n",
- "The `PropagateDownwind` wind farm model is very fast as it only performs a minimum of deficit calculations. It iterates over all turbines in downstream order. In each iteration it calculates the effective wind speed at the current wind turbine as the free stream wind speed minus the sum up the deficit from upstream sources. Based on this effective wind speed, it calculates the deficit caused by the current turbine on all downstream destinations. Note, that this procedure neglects upstream blockage effects.\n",
- "\n",
- "```python\n",
- "\n",
- "for wt in wind turbines in downstream order:\n",
- " ws_eff[wt] = ws[wt] - superposition(deficit[from_upstream_src,to_wt])\n",
- " ct = windTurbines.ct(ws_eff[wt])\n",
- " deficit[from_wt,to_downstream_dst] = wakeDeficitModel(ct, distances[from_wt,to_downstream_dst], ...)\n",
- "```\n",
- "\n",
- "The proceedure is illustrated in the animation below:\n",
- "- Iteration 1: WT0 sees the free wind (10m/s). Its deficit on WT1 and WT2 is calculated.\n",
- "- Iteration 2: WT1 sees the free wind minus the deficit from WT0. Its deficit on WT2 is calculated and the effective wind speed at WT2 is updated"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- ""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "95.2 ms \u00b1 0 ns per loop (mean \u00b1 std. dev. of 1 run, 10 loops each)\n"
- ]
- }
- ],
- "source": [
- "%%timeit -r1\n",
- "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
- "models['Fuga'](wt_x[:20],wt_y[:20])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### All2AllIterative\n",
- "The `All2AllIterative` wind farm model is slower but is capable of handling blockage effects. <br/> \n",
- "It iterates until the effective wind speed converge (i.e. less than or equal to the maximum number of turbines that affect each other in the wind farm. The converge tolerance is an input parameter).<br/> \n",
- "In each iteration it sums up the deficit from all wind turbine sources and calculates the deficit caused by the all wind turbines turbine on all wind turbines.\n",
- "\n",
- "```python\n",
- "\n",
- "while ws_eff not converged:\n",
- " ws_eff[all] = ws[all] - superposition(deficit[from_all,to_all])\n",
- " ct[all] = windTurbines.ct(ws_eff[all])\n",
- " deficit[from_all,to_all] = wakeDeficitModel(ct[all], distances[from_all,to_all], ...)\n",
- "```\n",
- "\n",
- "The proceedure is illustrated in the animation below:\n",
- "- Iteration 1: All three WT see the free wind (10m/s) and their CT values and resulting deficits are therefore equal\n",
- "- Iteration 2: The local effective wind speeds are updated taking into account the wake and blockage effects of the other WT. Based on these wind speeds the CT and deficits are recalculated\n",
- "- Iteration 3: Repeat after which the flow field has converged"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- ""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "2.22 s \u00b1 0 ns per loop (mean \u00b1 std. dev. of 1 run, 1 loop each)\n"
- ]
- }
- ],
- "source": [
- "%%timeit -r1\n",
- "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
- "models['FugaBlockage'](wt_x[:20],wt_y[:20])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Wake deficit models\n",
- "The wake deficit models compute the wake deficit caused by a single wind turbine. \n",
- "\n",
- "**Variable suffixes**\n",
- "\n",
- "The implementation of the deficit models is highly vectorized and therefore suffixes are used to indicate the dimension of variables. The suffixes used in this context are:\n",
- "\n",
- "- i: source wind turbines\n",
- "- j: destination wind turbines\n",
- "- k: wind speeds\n",
- "- l: wind directions\n",
- "\n",
- "This means that `deficit_ijlk[0,1,2,3]` holds the deficit caused by the first turbine on the second turbine for the third wind direction and fourth wind speed"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [],
- "source": [
- "# methods to plot deficit map, used below to visualize and compare the deficit models\n",
- "\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "from matplotlib import cm\n",
- "from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
- "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
- "D = 80\n",
- "def _map(f, xy=None):\n",
- " X, Y = np.meshgrid(*xy)\n",
- " x_j, y_j = X.flatten(), Y.flatten()\n",
- " downwind_distance_ijlk = x_j.reshape((1, -1, 1, 1))\n",
- " crosswind_distance_ijlk = np.abs(y_j.reshape((1, -1, 1, 1)))\n",
- " ws = 10\n",
- " res_ijlk = f(\n",
- " # specify arguments for all models\n",
- " WS_ilk=np.array([[[ws]]]), # wind speed at source turbine\n",
- " D_src_il=np.array([[D]]), # diameter of source turbine\n",
- " D_dst_ijl=None, # diameter of destination turbine\n",
- " h_il=np.array([[67]]), # source turbine hub height\n",
- " dw_ijlk=downwind_distance_ijlk, # down wind distance\n",
- " hcw_ijlk=crosswind_distance_ijlk, # horizontal cross wind distance\n",
- " dh_ijlk=np.zeros_like(crosswind_distance_ijlk),\n",
- " # height difference(vertical cross wind distance) between source and destination turbine\n",
- " cw_ijlk=crosswind_distance_ijlk, # cross wind distance (both horizontal and vertical)\n",
- " ct_ilk=np.array([[[8 / 9]]]), # thrust coefficient\n",
- " WS_eff_ilk=np.array([[[ws]]]), # effective wind speed at source turbine\n",
- " TI_ilk=np.array([[[0.1]]]),\n",
- " TI_eff_ilk=np.array([[[0.1]]]),\n",
- " wake_radius_ijlk=BastankhahGaussianDeficit().wake_radius(dw_ijlk=downwind_distance_ijlk, \n",
- " D_src_il=np.array([[D]]), \n",
- " ct_ilk=np.array([[[8 / 9]]])),\n",
- " )\n",
- " return X / D, Y / D, res_ijlk[0, :, 0, 0].reshape(X.shape)\n",
- "\n",
- " \n",
- "def plot_deficit_map(model, cmap='Blues', levels=np.linspace(0,10,55)):\n",
- " xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
- " X,Y,deficit = _map(model.calc_deficit, xy)\n",
- " c = plt.contourf(X,Y,deficit, levels=levels, cmap=cmap)\n",
- " plt.colorbar(c, label=\"Deficit [m/s]\")\n",
- " plt.plot([0,0],[-1/2,1/2],'k')\n",
- " plt.ylabel(\"Crosswind distance [y/D]\")\n",
- " plt.xlabel(\"downwind distance [x/D]\")\n",
- "\n",
- "def plot_wake_deficit_map(model):\n",
- " cmap = np.r_[[[1,1,1,1],[1,1,1,1]],cm.Blues(np.linspace(-0,1,128))] # ensure zero deficit is white\n",
- " plot_deficit_map(model,cmap=ListedColormap(cmap))\n",
- "\n",
- "def plot_blockage_deficit_map(model):\n",
- " from matplotlib import cm\n",
- " from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
- " cmap = np.r_[cm.Reds_r(np.linspace(-0,1,127)),[[1,1,1,1],[1,1,1,1]],cm.Blues(np.linspace(-0,1,128))] # ensure zero deficit is white\n",
- " plot_deficit_map(model,cmap=ListedColormap(cmap), levels=np.linspace(-3.5,3.5,113))\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### NOJDeficit\n",
- "\n",
- "The NOJDeficit model is implemented according to Niels Otto Jensen, \"A note on wind generator interaction.\" (1983), i.e. a top-hat wake, only valid in the far wake\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import NOJDeficit\n",
- "plot_wake_deficit_map(NOJDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### FugaDeficit\n",
- "\n",
- "The FugaDeficit model calculates the wake deficit based on a set op look-up tables computed by a linearized RANS solver. The look-up tables be created in advance using the [Fuga GUI](https://orbit.dtu.dk/en/publications/developments-of-the-offshore-wind-turbine-wake-model-fuga)\n",
- "\n",
- "The fugaDeficit models both near wake, far wake and blockage deficit"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "import os\n",
- "import py_wake\n",
- "from py_wake.deficit_models import FugaDeficit\n",
- "\n",
- "# Path to Fuga look-up tables\n",
- "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
- "\n",
- "plot_wake_deficit_map(FugaDeficit(lut_path))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### BastankhahGaussianDeficit\n",
- "\n",
- "The `BastankhahGaussianDeficit` model is implemented according to Bastankhah M and Port\u00e9-Agel F. \"A new analytical model for wind-turbine wakes\" J. Renew. Energy. 2014;70:116-23. The model is valid in the far wake only."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
- "plot_wake_deficit_map(BastankhahGaussianDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### IEA37SimpleBastankhahGaussianDeficit\n",
- "\n",
- "The `IEA37SimpleBastankhahGaussian` model is implemented according to the [IEA task 37 documentation](https://github.com/byuflowlab/iea37-wflo-casestudies/blob/master/cs1-2/iea37-wakemodel.pdf) and is equivalent to BastankhahGaussian for $beta=1/\\sqrt{8} \\sim ct=0.9637188$. The model is valid in the far wake only."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import IEA37SimpleBastankhahGaussianDeficit\n",
- "plot_wake_deficit_map(IEA37SimpleBastankhahGaussianDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### GCLDeficit\n",
- "\n",
- " Implemented according to:\n",
- " Larsen, G. C. (2009). A simple stationary semi-analytical wake model.\n",
- " Risoe National Laboratory for Sustainable Energy,\n",
- " Technical University of Denmark. Denmark.\n",
- " Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
- "\n",
- " Description:\n",
- " based on an analytical solution of the thin shear layer approximation of the NS equations.\n",
- " The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields\n",
- " are consistently assumed uniform.\n",
- " The effect of expansion is approximately accounted for by imposing suitable\n",
- " empirical downstream boundary conditions on the wake expansion that depend\n",
- " on the rotor thrust and the ambient turbulence conditions, respectively."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import GCLDeficit\n",
- "plot_wake_deficit_map(GCLDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### NiayifarGaussianDeficit\n",
- " \n",
- " Implemented according to:\n",
- " Amin Niayifar and Fernando Port\u00e9-Agel\n",
- " Analytical Modeling of Wind Farms: A New Approach for Power Prediction\n",
- " Energies 2016, 9, 741; doi:10.3390/en9090741\n",
- "\n",
- " Features:\n",
- " - Wake expansion function of local turbulence intensity\n",
- "\n",
- " Description:\n",
- " The expansion rate 'k' varies linearly with local turbluence\n",
- " intensity: k = a1 I + a2. The default constants are set\n",
- " according to publications by Porte-Agel's group, which are based\n",
- " on LES simulations. Lidar field measurements by Fuertes et al. (2018)\n",
- " indicate that a = [0.35, 0.0] is also a valid selection."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import NiayifarGaussianDeficit\n",
- "plot_wake_deficit_map(NiayifarGaussianDeficit(a=[0.38, 4e-3]))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### ZongGaussianDeficit\n",
- " \n",
- " Implemented according to:\n",
- " Haohua Zong and Fernando Port\u00e9-Agel\n",
- " A momentum-conserving wake superposition method for\n",
- " wind farm power prediction\n",
- " J. Fluid Mech. (2020), vol. 889, A8; doi:10.1017/jfm.2020.77\n",
- "\n",
- " Features:\n",
- " - Wake expansion function of local turbulence intensity\n",
- " - New wake width expression following the approach by\n",
- " Shapiro et al. (2018)\n",
- "\n",
- " Description:\n",
- " Extension of the Niayifar et al. (2016) implementation with Shapirio\n",
- " wake width expression, which uses the near-wake length estimation by\n",
- " Vermeulen (1980)."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import ZongGaussianDeficit\n",
- "plot_wake_deficit_map(ZongGaussianDeficit(a=[0.38, 4e-3]))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### GCLDeficit\n",
- "\n",
- " Implemented according to:\n",
- " Larsen, G. C. (2009). A simple stationary semi-analytical wake model. \n",
- " Ris\u00f8 National Laboratory for Sustainable Energy, \n",
- " Technical University of Denmark. Denmark. \n",
- " Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
- "\n",
- " Description:\n",
- " based on an analytical solution of the thin shear layer approximation of the NS equations. \n",
- " The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields \n",
- " are consistently assumed uniform.\n",
- " The effect of expansion is approximately accounted for by imposing suitable \n",
- " empirical downstream boundary conditions on the wake expansion that depend \n",
- " on the rotor thrust and the ambient turbulence conditions, respectively. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import GCLDeficit\n",
- "plot_wake_deficit_map(GCLDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compare deficit models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {},
- "outputs": [],
- "source": [
- "deficitModels = [NOJDeficit(),\n",
- " FugaDeficit(lut_path),\n",
- " BastankhahGaussianDeficit(),\n",
- " IEA37SimpleBastankhahGaussianDeficit(),\n",
- " NiayifarGaussianDeficit(),\n",
- " ZongGaussianDeficit(),\n",
- " GCLDeficit()]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Deficit along center line**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x171852aceb0>"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=((10,6)))\n",
- "for deficitModel in deficitModels:\n",
- " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(np.linspace(-200,500,300), 0))\n",
- " plt.plot(X[0], deficit[0], label=deficitModel.__class__.__name__)\n",
- "plt.title(\"Center line deficit\")\n",
- "plt.xlabel('x/D')\n",
- "plt.ylabel('Deficit [m/s]')\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Deficit profile 2D downstream**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x17185317580>"
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=((10,6)))\n",
- "for deficitModel in deficitModels:\n",
- " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(2*D, np.linspace(-200,200,300)))\n",
- " plt.plot(Y[:,], deficit[:,0], label=deficitModel.__class__.__name__)\n",
- "\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Implement your own deficit models\n",
- "Deficit models must subclass `DeficitModel`and thus must implement the `calc_deficit` method and a class variable, `args4deficit` specifying the arguments required by its `calc_deficit` method\n",
- "\n",
- "```python \n",
- "class DeficitModel(ABC):\n",
- " args4deficit = ['WS_ilk', 'dw_ijlk']\n",
- "\n",
- " @abstractmethod\n",
- " def calc_deficit(self):\n",
- " \"\"\"Calculate wake deficit caused by the x'th most upstream wind turbines\n",
- " for all wind directions(l) and wind speeds(k) on a set of points(j)\n",
- "\n",
- " This method must be overridden by subclass\n",
- "\n",
- " Arguments required by this method must be added to the class list\n",
- " args4deficit\n",
- "\n",
- " See class documentation for examples and available arguments\n",
- "\n",
- " Returns\n",
- " -------\n",
- " deficit_ijlk : array_like\n",
- " \"\"\"\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import WakeDeficitModel\n",
- "from numpy import newaxis as na\n",
- "class MyDeficitModel(WakeDeficitModel):\n",
- " args4deficit = ['WS_ilk', 'dw_ijlk', 'cw_ijlk']\n",
- "\n",
- " def calc_deficit(self, WS_ilk, dw_ijlk, cw_ijlk,**_):\n",
- " # 10% deficit in downstream triangle\n",
- " ws_10pct_ijlk = 0.1*WS_ilk[:,na]\n",
- " triangle_ijlk = ((.2*dw_ijlk) >cw_ijlk)\n",
- " return ws_10pct_ijlk *triangle_ijlk\n",
- "\n",
- "plot_wake_deficit_map(MyDeficitModel())\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Superposition models\n",
- "The super position models calculates the effective wind speed given the local wind speed and deficits (typically from multiple sources)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### LinearSum"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.contour.QuadContourSet at 0x17182cf51c0>"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "linear_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=LinearSum())\n",
- "plt.figure(figsize=(10,4))\n",
- "linear_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### SquaredSum"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.contour.QuadContourSet at 0x17182fbdbe0>"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.superposition_models import SquaredSum\n",
- "squared_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
- "plt.figure(figsize=(10,4))\n",
- "squared_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### MaxSum"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.contour.QuadContourSet at 0x17182f84dc0>"
- ]
- },
- "execution_count": 24,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.superposition_models import MaxSum\n",
- "max_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=MaxSum())\n",
- "plt.figure(figsize=(10,4))\n",
- "max_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Blockage deficit models\n",
- "\n",
- "The blockage deficit models compute the blockage effects caused by a single wind turbine. Their structure are quite similar to the [wake deficit models](#Wake-deficit-models). They model upstream blockage effects (wind speed reduction) and in addition, some models also models downstream speed-up effects."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### SelfSimilarityDeficit\n",
- "Simple inductionmodel model, described in [N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016](https://onlinelibrary.wiley.com/doi/full/10.1002/we.2137)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import SelfSimilarityDeficit\n",
- "plot_blockage_deficit_map(SelfSimilarityDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### SelfSimilarityDeficit2020\n",
- "\n",
- "This is an updated version of [N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016](https://onlinelibrary.wiley.com/doi/full/10.1002/we.2137). The new features are found in the radial and axial functions:\n",
- "\n",
- "1. Radially Eq. (13) is replaced by a linear fit, which ensures the induction half width, `r12`, to continue to diminish approaching the rotor. This avoids unphysically large lateral induction tails, which could negatively influence wind farm simulations.\n",
- "2. The value of gamma in Eq. (8) is revisited. Now gamma is a function of CT and axial coordinate to force the axial induction to match the simulated results more closely. The fit is valid over a larger range of thrust coefficients and the results of the constantly loaded rotor are excluded in the fit."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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7ugkabyR5nOIE27+VtAeQa/rutkEjbZD5EPAHkifBBZik4WQi9Go+70bvG2U9rQJG9tiZSoMH8yukDyM5XUIII+AKYM/05ryGJDD8Vf1Okh4PbAf8NLNuO2Bd2mi9FDgQ+NdOCpFO0X0ecKHtv6+tt/1b4F/ynCNPpvF24HG27+ykkOOuV43N9YGiVcCoBYu5avNqNke8CKFrojeZRtp+8DbgfJKH506zfb2kjwIrbNe60R4BnGlv8i/4z4DPS6qSdF46sYsmgi8CLwT+QdIsycPaP0jHFMwl1zAiwL2dlW8ytXsuY+N+rdtWmgWMWrCoXScbPEqFAnOVChU7AkcII8T2ucC5des+WPf5ww2O+wnwhB6V4WfAz4APS3oEcAjwLkn7AFeSBJBvtDpHnqBxM3CJpHOA9ZmLf7zjkg/RfBvBe91ttdXghI3aK+qro+aq1U2Cxfq6Kqr1lQqLisUIGiH0yLg+95TWHn0tXZC0P3Bou+PyBI3/TZfpdAk90Cx4NesplQ0YtcxifaXCXLr/bCbbmEszE0ebRgihgXSUj9cDu5OJA9l2jmbydLn9SBdlG2uNBxhsXjWVJ8uAzaulslVSNbWAMVut8tDsptseokq5GplGCN2StMkUBGPkXOBy4Fo2DlqXS57eU9sD7wX+HFhcW2/7OfMrY2inXYCpZRn1AWN9pcpsuS5YOfKMEEJTi23/QycH5qmeOgP4OvBikn69RwF3dHKxkJjPCLb11VLZgHHPQ2Vmy2bdXJXZNDuZLSfnLlejB1UI3epV76kR9BVJfwN8n03bqu9qd2CeoPEI21+U9HbbPwJ+JOmKzss6PMNuBM9z/lZDhLQKGLPlKjPlKjOzaXfcchVH1AghNDYLnAQcz8YHugw8pt2BeYLGXPp6u6QXkUzgkWf2p7HW6ZAgefdt1vhdq5KqBYwH1lc2BIu5SpW5cpWZueR9NYJGCF3p1Si3I+hdwGPT+ZLmJU/Q+Jikh6UX+RSwDfCO+V5oEsx3GHTIPxBhtqfU+kp1Q4YxU65y/0NzzJWr3D+TvAJUq9GmEUJoahWwrpMD8wSNu23fS/KA38EAkg7s5GKh8ThTWQ0bwBtkGRuqpGYrGwLGupkys7MVyuUq5UqVSmQaIXRFglK+UW4XmgeBqyRdzKZtGt13uSXJLp6UY13okfqqKWDzLKNc5Z51c6xbX94QMNatm2Pdulnm5qrMzUX1VAihqe+my7w1DRqSngY8HdheUrZr1jYkY6eEHmnX3lF76rv+eYy5Stp+Ua5uCBgPPVRmZt16KpVKjHQbQg+MY5uG7dM7PbbVUyvTwFYkgWXrzHIfyURMIade9sKqVU3NlJNG71rjd7lc3RAwHrzvQaoxc18IoU46ym1X+zTNNDLda79k+3fpyQrAVrbvm29hJ818b9jNGsGz7Rnr0/aQ2bqutevWzTE7W2ZutszszCyzM7NUK5VoCA+hS0Ljlmm8TFKrOcDFxgn3GsrTpvHPko4hmUvjCmAbSZ+0fVL+coZG2gWWRr2x1s1trKKqVU3VsozZmVlm1s1QXXcfVCu5poUNIUyU9+TY57JWG/MEjb1s3yfpNSSTdxwLrCR5MKQrkg4FPknSRnKq7RO7PedC1nQI9YZDijSYvKlcoVKuwMwDUCn3vHwhTJqk91Rvxp5qd7+TtAj4MrA/cCfwatu3pNuOA95E8uP9722f30kZumnLqMnz1yhJKgEvA862PUcPpoSTVAQ+QzIhyF7AkZL26va8vTLs9oBWEyzNlGvzaVSZna1sqJoCqM7OwPp14Or8RiELIfRNzvvdm0gecXgs8AnSmfTS/Y4gGf/vUOCz6fmGIk/Q+DxwC7AlcKmk3Ugaw7t1ALDK9s22Z4EzgcN7cN6JNTc7t8nnGEYkhO7Uxp5qt+SQ5353OFDLBL4FPFeS0vVn2l6fTsu6Kj3fULQNGrZPtr2T7cOc+B1tGkpy2olkVsCa1em6TUg6WtIKSSvWro1xEkMII2lp7T6VLkfXbc9zv9uwj+0yyQPVj8h57LxI+ss86xpp9ZzGa21/te4ZjayBzNxnezmwHOBJ+y+Ln87zkPxICSF0SoLFeVp+Ya3tZX0uTi8dB3wzx7rNtPpzbJm+bt1hodpZA+yS+bxzum4kFAsaartGba7vRhZPFbifpIFuerrI9HTyn7E0XWJ2ejHVRUtAYzlxTAgLVZ77XW2f1ZKmgIeRNIj37F4p6YXAYcBOkk7ObNoGyNV7ptVzGp9PX/s1c98VwJ6S9iD5AxwB/FWfrrUgNAtUpYKoexh8sx4dpekpZqeKFKeKVBdvBcWpXA1WIYQWqhV48O5enCnP/e5skvmKfkryAPVFti3pbOA/JX0ceDSwJ/DzDstxG7ACeClJL9ia+4F35jlBq+qpk5ttg3wDW7U5vizpbcD5JF3QTrN9fTfnXGjaZTOlophr0QVqcanIuqkCU+lSTINGZck2UChSiKgRQndchfJs96dpcr+T9FFghe2zgS+STI60CriLJLCQ7vcN4AaSbOCtthtXQ7Qvx9XA1ZLOSNtN5q1V9VQtCh1I0kXs6+nnvyQpfNdsn0syV+3YmW/11lRRDR/GKxUKrK9UmC4UWFQssKSUDCOyeLrIuvVlSmnA2HLLacrlavKcBrC+UKQYbRohjIxG9zvbH8y8nyG5vzY69gTghG7LIOkbtl8F/ELSZjcc2/u0O0er6qnT04v8HfCMWlSS9DnaPDEYNtXr9pHpdKjm0lSBUrHAlktKlMtVtthiClhCcarIg1OFcRv+IITBM9CkbXGBenv6+uJOT5CnX8B2JI0ktbljt0rXhR5pF1QWFYvMVctsMV1Ih0ZPGsNnigUWl4rMVaosWVLasP/UVIE7i0UiZIQQsmzfnr4tALen2Q2StgB2yHOOPEHjRJJU5mKSZ12eBXx43qUNuRULYvGG0eerzFU3NobXV1HNVapsvbi0yfHlcjVp44hMI4QuGY/nkDzfJJn6oqaSrntyuwPbBg3b/yHpPOAp6ar32f59J6UMSa+nuUq1aXbRaH22XeMhqkxPiemiWDxVgC1K3P/Q3IbAUZoqMFeuUiwWUOQaIYTGptIn0wGwPStpOteBeXZKg8T3OixcaCEbJJo1hkNSRQUVtpguwCwsKWX2ywSOmbkKLErONZ6zVIYwQDZUuu89NYLukPTStNcWkg4H1uY5MN+zjmEzDTOCohoOZ95s/1bb66uoYGO2wTTp3BqZPrVblJiZrbBkUfqgX7FAIXpPhRAaOwY4Q9KnSZodbgVen+fAiQoataqhvLrt9dTp8c2Oq2UbkHS/rQUTgOmpQlJdlZoqKoYRCaFrHrfeUwDY/g3wVElbpZ8fyHtsq4f7Ht7mone12h6aq2/XaFZF1SjbADb0pGJ24/olJVg3p8w1RMSMEEJWszEFaz8wbbcdU7Ddw30mSV12Be5O328L/C+wR0elDk1lg0erLKVUEFBgenGB2WqVh9IxRqanNkaJoqIZPISu2eM2odmS9LXjMQVbPdy3B4CkLwBnpU8z1ga8elmnFxwnedo12gWCTrONpJqK5HPa52GLTBvHVCEyjRDCZv4kfb3BdtsRbRvJMzrRU2sBA8D2eWzavzd0oNkUkrVnK6aKm07usrhYpFQoUCqKUqHAVqUSi4pFSgWx5VRxs6VYUHS5DaFbNszOtF8WjsPSiZ2O6/QEeRrCb5P0AeCr6efXkIyUOBEGMUR6o2wjuw2S6WcXFzMP/FVMqcmIhKVCIameipgRQtjUD0iaGraSdB9Jk0OtGcK2t2l3gjyZxpHA9sBZ6fLIdN2C1KtJ4ltfY9O7dTZjyL7Pk23UPtfWbZJxFMWSUpElpWTdhvfFyDFC6Akbl2fbLguF7ffY3hY4x/Y2trfOvuY5R54nwu9i4yBXoU6vMpH6bKP2Wt++sWnGsVEpE38WF9PqqYgcIYQGbB8uaTdgT9sXpmNPTdm+v92xbYOGpD8F3g3snt3f9nM6L/LkadYg3ujZkUaBo97GxvHNr5NQuoQQOuYqzK3v+2XSRxy+TnKfvQV4le276/Y5GPhEZtXjgSNsf1fSl4Bnk8wrDvAG21e1uN7fAEcDDydpHN8Z+Bzw3HZlzdOm8c30ZKeyscvOROkkm2j1dHie6zTLOLLrm50DiCwjhIXlWOC/bZ8o6dj08/uyO9i+GNgXNgSZVcAPM7u8x/a3cl7vrcABwM/Sc/9a0iPzHJgnaJRtn5KzIAvCfJ8MbydvUMmTbeQNHM3Uel3ttfc+LC41zkZCCDnZMDeQNovDgYPS96cDl1AXNOq8EjjP9roOr7c+HaQQgHRO8ly/cvMEjf+S9BaSRvANeVo8Ed5eu2yj08DRSq3R/AMfO4ltl5Ra7htC6JmlklZkPi+3vXwex++Qmevi97Sf2+IIoP7p7RMkfRD4b+BY263q1X4k6f3AFpKeD7wF+K88Bc0TNI5KX9+TWWfgMXkuMC7mO+BgJ/vlCRw1zbrmNuupFULogKuw/qE8e661vazVDpIuBB7VYNPxm1zSdqOpWDPn2RF4Asl84zXHkQSbaWA5SZby0RbFORZ4E3At8Lck09Ce2qr8NXl6T43lcCG9rqJqfp382UZ9ueoDB7DZ5/pz1dYPomtxCCE/289rtk3SHyTtaPv2NCj8scWpXkUySsdc5ty1LGW9pP8g6bzUqixVSd8Fvmv7jtxfgtYDFj7H9kWSXtHkot+Zz4XGQb+yjXaBA1oHi+x5asdHlhFCD6TPaQzA2SS1Oiemr63mLzqSuie6MwFHJMM8XdfowHT7h4C3kT6nJ6kCfMp2q8xkg1aZxrOBi4CXNNhmYOKCRqcaZRvzCRy17bB5tVR2W+24WsYRgSOEBeNE4BuS3gT8jiSbQNIy4Bjbb04/7w7sAvyo7vgzJG1P0s/+KpL5Mhp5J3Ag8GTbv03P+RjgFEnvtP2JJsdt0GrAwg+lr29sd5KFqpMqqk6zjU4DB9AweGx+/kLL7SGEDgyo95TtO2nwjITtFcCbM59vAXZqsF/e5+ZeBzzf9oZZ+mzfLOm1JN13Ow8aNZJ+A1wOXAZcZvv6nIULObQLHNA4eNRvqx1be60fyiSEEIBSNmDU2L5DUq7ulnl6T+0FPAV4JnCSpMcB19h++byKOkZ6mW002r9ZVVSrxu1GvaeiMTyELlUr8NCDwy5FL7VKm3KlVHmCRgWYS1+rJK36rVr2F5R+9aLqNnDU1tU0C1KNutiWitGeEUJo6Inp6Lb1BCzOc4I8QeM+kr68Hwe+kNa9TbxuBiqcT+DIbmtXntq5Qwg9MrgnwgfCdtfDROQdGv1SkicGz5T0EUltB7VaSPpVjdPqRt/s5j7fXk+bPpuxeRVVCCH0Up6H+74HfE/S44EXAu8A3gts0d+ijb482UbrJ8CbP/hXf+NvVXVVO1d2fQSOEHpgzDKNXmj7E1vStyWtAj4JbAm8Htiu3wUbtE6zjTw353YZR54qpeyzF80CRggh9FueNo1/Bn5heyKHRe+VdllJJ0Op147LXiP7GkLokg1zc+33myB5gsYewC+B+9O5wp8EfMz2lX0t2RB02pOqF4MVJtffeLNvF0BaTSnbal0IYR6qVZjJNWDhxMhTJ/OPtu+X9AzgecAXgbGaX6MX8t6g8+5Xq7ZqtjQ7ZwxYGELopzx3llq11ItIxog/h2T43bHUzc2214FjvueKzCKEHqs1hLdbJkieO+QaSZ8HXg2cK2lRzuOakvSXkq6XVE0H5Bopg/iV3osBBduNQxVCCL2W5+7yKpLJPl5g+x6Sicjf0/KI9q4DXkHy/MdYmW8g6CR4NDomsowQ+iAyjc3kaQjfETjH9npJBwH7AF/u5qK2bwSozU87iroZXqSTp8W7uenHeFMhhEHJc4f5NlCR9FiSaQR3Af6zr6UaEYNo3+hWZBgh9JGrMDPTfpkgee6KVdtlkuqkT9l+D0n20ZKkCyVd12A5fD4FlHS0pBWSVqxdO69ZCYeu3xMhbf6QX2QZISxEedt5Jd0i6VpJV0lakVn/cEkXSPp1+tq3B7DzVE/NSTqS5Enw2ix+bcddbzUf7nzYXk6S4fCk/Zd1NkJgF3oxCm43gxu2Omc320MIOQzu4b5aO+/nc+x7cIM5MY4F/tv2iZKOTT+/r8dlBPJlGm8EngacYPu3kvYAvtKPwoyqXvyC72XW0eg8kWWEsHDZvtH2L7s4xeHA6en700nmCe+Ltnca2zcA7waulbQ3sNr2v3RzUUkvl7SaJBidI+n8bs43CL26KXfb4N3tWFchhHmoZRrtFlhaq0ZPl6P7VSLgh5JW1l1jB9u3p+9/D+zQp+vnmu71IJLIdQvJRB27SDrKdsfdZW2fBZw13+OGfSvs1YRNeSZXarRvq3KFEIZqre2Wz5xJuhB4VINNx6ejiefxDNtrJD0SuEDSTfX3YtuW1Leq/DxtGv8GHFJLnST9KfA1YP9+FWqSdJsVRMAIoX9cNV6/vjfn6kE7r+016esfJZ0FHEDyvNsfJO1o+3ZJO9LH2VXz3HFK2bo2278iR0N4vwy76mWUbtKNyjLsv08IoT8kbSlp69p74BCSBnSAs4Gj0vdHAXkzl3nLcwdcKelUSQelyxeAFW2PGmOjFDhCCH2Uv02jK83aeSU9WtK56W47AD+WdDXwc5KHrn+QbjsReL6kX5MMLHti14VqIk/11DHAW4G/Tz9fBny2XwXKox9dWOerFjh60cbRzfWzIssIYWFq1s5r+zbgsPT9zcATmxx/JzCQabhbBg1JReBq248HPj6IAuU1CoEDetc4Pt9rhhAGICZh2kzLu086W98vJe06oPIsSIO6iZeKhQgYIYShylM9tR1wvaSfAw/WVtp+ad9KldOoZBvQ/+qqdsEiqqZC6IPINDaTJ2j8Y99L0YVRChzQn+qqyC5CCKOiadBIR7XdwfaP6tY/A7i98VEBepd15A0WkWWE0CfVKtUHe/OcxrhodVf6d+C+BuvvTbeNjFG9adbaIOaTKXRyTAghDEqr6qkdbF9bv9L2tZJ271+ROjNq1VT1+hUERjVghjAWbKpz5WGXYqS0upNt22LbFj0uRwghhAWgVdBYIelv6ldKejOwsn9F6tyk/eqetO8bwqDZ4Nly22WStKqeegdwlqTXsDFILAOmgZf3uVwdG/Vqql6JgBFCGIamQcP2H4CnSzoY2DtdfY7tiwZSsi5MSuAIIfRZ1VQeiuc0sto+p2H7YuDiAZSlp8Y5cESWEUIYljwP94UQwmSyJ67Nop2xfhhgHH+Rj+N3CiEsHGMdNGC8brLj9F1CWAhcNdXZctulW5JOknSTpGsknSVp2wb77CLpYkk3SLpe0tsz2z4saY2kq9LlsK4L1cTYBw0Yj5vtOHyHEEJTFwB7294H+BVwXIN9ysC7bO8FPBV4q6S9Mts/YXvfdDm3wfE9MTFtGgu5YTwCRghDYlOdrQzgMv5h5uPlwCsb7HM76bh/tu+XdCOwE3BD3wuYMRGZRk2xoLgBhxByqxpmZyttF2CppBWZ5eguLvvXwHmtdkiHctoP+Flm9dvS6q3TJG3XxfVbmphMI2shZR0R5EJYENbaXtZqB0kXAo9qsOl4299L9zmepBrqjBbn2Qr4NvAO27VBZU8B/glw+vpvJMGn5yYyaMDCCBwRMEIYLtvMzfVmfhzbz2u1XdIbgBcDz7Xd8OYkqUQSMM6w/Z3Muf+Q2ecLwPd7UeZGJqp6qt4o35RHuWwhhN6SdCjwXuClttc12UfAF4EbbX+8btuOmY8vB67rV1knNtOoqd2cRynriIARwmiwYa7cnymc63waWARckMQGLrd9jKRHA6faPgw4EHgdcK2kq9Lj3p/2lPpXSfuSVE/dAvxtvwo68UGjZhSqqyJYhDCZbD+2yfrbgMPS9z8GGt4kbL+uf6XbVASNjGFmHREwQhg9tpld3/8utwtJBI0GBhk8IliEEBaSCBot9Dt4RMAIYbQNsE1jwYigkUP25t5tAIlAEUJYyCJozFP9Tb9dEIkgEcLCZUO5PDo9K0dBBI0uRVAIIUySCBohhNCEbWbmovdU1kQ/ER5CCGF+hpJpSDoJeAkwC/wGeKPte4ZRlhBCaMbAXONhoCbWsDKNPBOOhBBCGDFDyTTyTDgSQgjDFpnG5kahTaPlhCOSjq5NbHLH2jsGWKwQQgj1+pZp9GrCEdvLgeUA+++/LEJ+CGFgItPYXN+CRi8mHAkhhDBahlI9lWfCkRBCGLaqzfpq+6Vbkv4pnd/7Kkk/TOfRaLTfUZJ+nS5HZdbvL+laSasknZxO2NQXw2rT+DSwNcmEI1dJ+tyQyhFCCKPgJNv72N6XZKrWD9bvIOnhwIeApwAHAB+StF26+RTgb4A90+XQfhV0WL2nGk44EkIIo2RQbRq278t83DK9dL0XABfYvgtA0gXAoZIuAbaxfXm6/svAy2jRwagbMYxICCF0b6mkFZnPy9NOPLlJOgF4PXAvcHCDXXYCbs18Xp2u2yl9X7++LyJohBBCC+V8mcZa28ta7dCuR6nt44HjJR0HvI2kKmrkRNAIIYQBaNejNOMM4Fw2DxprgIMyn3cGLknX71y3fk1HhcxhFB7uCyGEkVQxPFiptl26JWnPzMfDgZsa7HY+cIik7dIG8EOA823fDtwn6alpr6nXA9/rulBNRKYRQgjDd6KkxwFV4HfAMQCSlgHH2H6z7bsk/RNwRXrMR2uN4sBbgC8BW5A0gPelERwiaIQQQlOmN89htL2O/RdN1q8A3pz5fBpwWpP99u5bATOieiqEEEJukWmEEEITVcPMADKNhSQyjRBCCLlFphFCCE0YmInxVDcRQSOEEJqoAA9UImhkRfVUCCGE3CLTCCGEJmwG0uV2IYlMI4QQQm6RaYQQQhNVHF1u60SmEUIIITctpOm5Jd1BMi5LJ5YCa3tYnIVgEr8zTOb3ju+8ud1sb9/NBST9IL1OO2tt9222vFGyoIJGNyStaDfe/biZxO8Mk/m94zuHQYnqqRBCCLlF0AghhJDbJAWNec3XOyYm8TvDZH7v+M5hICamTSOEEEL3JinTCCGE0KUIGiGEEHKbqKAh6SRJN0m6RtJZkrYddpn6RdKhkn4paZWkY4ddnn6TtIukiyXdIOl6SW8fdpkGRVJR0i8kfX/YZRkUSdtK+lb67/lGSU8bdpkmxUQFDeACYG/b+wC/Ao4bcnn6QlIR+AzwQmAv4EhJew23VH1XBt5ley/gqcBbJ+A717wduHHYhRiwTwI/sP144IlM3vcfmokKGrZ/aLucfrwc2HmY5emjA4BVtm+2PQucCRw+5DL1le3bbV+Zvr+f5Cay03BL1X+SdgZeBJw67LIMiqSHAc8Cvghge9b2PUMt1ASZqKBR56+B84ZdiD7ZCbg183k1E3ADrZG0O7Af8LMhF2UQ/h14L1AdcjkGaQ/gDuA/0mq5UyVtOexCTYqxCxqSLpR0XYPl8Mw+x5NUZ5wxvJKGfpC0FfBt4B227xt2efpJ0ouBP9peOeyyDNgU8CTgFNv7AQ8CY99uNyrGbmh0289rtV3SG4AXA8/1+D6ksgbYJfN553TdWJNUIgkYZ9j+zrDLMwAHAi+VdBiwGNhG0ldtv3bI5eq31cBq27VM8ltE0BiYscs0WpF0KEkq/1Lb64Zdnj66AthT0h6SpoEjgLOHXKa+kiSSOu4bbX982OUZBNvH2d7Z9u4k/40vmoCAge3fA7dKely66rnADUMs0kQZu0yjjU8Di4ALknsMl9s+ZrhF6j3bZUlvA84HisBptq8fcrH67UDgdcC1kq5K173f9rnDK1Loo/8DnJH+KLoZeOOQyzMxYhiREEIIuU1U9VQIIYTuRNAIIYSQWwSNEEIIuUXQCCGEkFsEjRBCCLlF0AghhJBbBI0xJunDkt49xOv/ZJ77H5RneG9Jl0halr4/t9UQ95LeIWnJfMrRK2k5fynppTn2PULS8ZLeIOmOdEylX0s6X9LTM/udJOn3w/zvGiZbBI3QN7af3n6vrq9xWJsRTt8BDCVopF5jO8/T+C8EfpC+/7rt/WzvCZwIfEfSnwHYfg/wuf4UNYT2ImiMmfTX6q8k/Rh4XGb9vpIuz0xAtZ2kR0pamW5/oiRL2jX9/BtJSyR9SdLJkn4i6WZJr0y3f6b2Czo932np+7+WdEL6/oH09aD0V3dt0pwz0mE/apNF3STpSuAVTb7TFpLOTCfbOQvYIrPtFklLJW0p6RxJV6cDVL5a0t8DjwYulnRxuv8pklakEzV9pO48H5F0paRrJT0+Xb+VpP9I110j6S/S9YdI+mm6/zfTgRJb/XeZknSFpIPSz/+c+TsJ2Be4sv442xcDy4GjW50/hEGJoDFGJO1PMgbRvsBhwJMzm78MvC+dgOpa4EO2/wgslrQN8ExgBfBMSbuRjJ5aG59rR+AZJAM9npiuuyw9BpJh12sTHj0TuLRB8fYj+dW/F/AY4EBJi4EvAC8B9gce1eSr/R2wzvafAR9K9613KHCb7Sfa3ptkgp6TgduAg20fnO53vO1lwD7AsyXtkznHWttPAk4BatU//wjca/sJ6d/uIklLgQ8Az0v3XwH8Q5OyA8nQLsAbgFMkPS8tby1o7Qdc3WIAzSuBx7c6fwiDEkFjvDwTOMv2unRY8LNhw6Q129r+Ubrf6SST2AD8hGTcpmcB/zd9fSZJUKj5ru2q7RuAHdJ1l5EEmL1IBov7g6Qdgael56z3c9urbVeBq4DdSW6Ev7X96/SG+dUm3+tZtW22rwGuabDPtcDzJf2LpGfavrfJuV6VZjW/AP6cjcEOoDYy7sq0fADPI5kFkfT6d5PMDLgX8D/pOFdHAbs1ud4G6fhfXwG+D/x1OkEWJAGk1dwuanfuEAZl0gYsDJu7lCRI7AZ8D3gfYOCczD7rM+8FYHtN2gB9aHqOhwOvAh5IZ86rlz1HhR7/v2f7V5KeRJJhfUzSf9v+aHYfSXuQZBBPtn23pC+RDCleX8Z25RNwge0jOyjqE4B7gEdm1h0C/EWLY/YjpjMNIyIyjfFyKfCytA1ga5JqH9Jf3XdLqlUnvQ6oZR2XAa8Ffp1mAXeR3Hh/nON6l5NUOV2anufdbJqhtHMTsLukP0k/N7sJXwr8FYCkvUmqljYh6dEkVVhfBU4imaQH4H5g6/T9NiQT9twraQeSxud2LgDemrnOdiTf+0BJj03XbSnpT9udSNIrSILrs4BPSdo2zQKnbN/Z5Jhnk7RnfCFHWUPou8g0xojtKyV9Hbga+CPJvBo1RwGfU9L9dMNQ0rZvSRtia+0QPwZ2Tqth2rkMOMT2Kkm/I7kh5g4atmckHQ2cI2ldeuzWDXY9hWRqzxtJfnE3mqnuCcBJkqrAHEk7CCSNyD+QdJvtgyX9giRY3Qr8T45ifgz4jKTrSDKQj9j+jpLJvL4maVG63weAXzU7SdoOciLJ5F+3Svo08Engv4AL63Z/taRnkPT6+i3wF7Yj0wgjIYZGD6FPJF0CvNv2ihb7nAqcavvyeZz3wyTVgP+v60KGME9RPRVC/9wFfEktHu6z/eZ5BoyTSKoTH+xB+UKYt8g0Qggh5BaZRgghhNwiaIQQQsgtgkYIIYTcImiEEELI7f8D5hBlzATaCYwAAAAASUVORK5CYII=\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import SelfSimilarityDeficit2020\n",
- "plot_blockage_deficit_map(SelfSimilarityDeficit2020())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### FugaDeficit\n",
- "\n",
- "The FugaDeficit model calculates the wake deficit based on a set op look-up tables computed by a linearized RANS solver. The look-up tables be created in advance using the [Fuga GUI](https://orbit.dtu.dk/en/publications/developments-of-the-offshore-wind-turbine-wake-model-fuga)\n",
- "\n",
- "The fugaDeficit models both near wake, far wake and blockage deficit.\n",
- "\n",
- "Note, the present look-up table generator introduces some unphysical wriggles in the blockage deficit/speed-up"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import FugaDeficit\n",
- "plot_blockage_deficit_map(FugaDeficit())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### VortexCylinder\n",
- "\n",
- "Induced velocity from a semi-infinite cylinder of tangential vorticity, extending along the z axis.\n",
- "\n",
- "This model is an adapted version of the one published by Emmanuel Branlard at https://github.com/ebranlard/wiz/blob/master/wiz/VortexCylinder.py\n",
- "\n",
- "References:\n",
- "\n",
- "- E. Branlard, M. Gaunaa, Cylindrical vortex wake model: right cylinder, Wind Energy, 2014, https://onlinelibrary.wiley.com/doi/full/10.1002/we.1800\n",
- "- E. Branlard, Wind Turbine Aerodynamics and Vorticity Based Method, Springer, 2017\n",
- "- E. Branlard, A. Meyer Forsting, Using a cylindrical vortex model to assess the induction zone in front of aligned and yawed rotors, in Proceedings of EWEA Offshore Conference, 2015, https://orbit.dtu.dk/en/publications/using-a-cylindrical-vortex-model-to-assess-the-induction-zone-inf"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import VortexCylinder\n",
- "plot_blockage_deficit_map(VortexCylinder())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### VortexDipole\n",
- "\n",
- "The vorticity originating from a wind turbine can be represented by a vortex dipole line (see Appendix B in [2]). The induction estimated by such a representation is very similar to the results given by the more complex vortex cylinder model in the far-field r/R > 6 [1,2]. The implementation follows the relationships given in [1,2]. This model is an adapted version of the one published by Emmanuel Branlard: https://github.com/ebranlard/wiz/blob/master/wiz/VortexDoublet.py\n",
- "\n",
- "References:\n",
- "- [1] Emmanuel Branlard et al 2020 J. Phys.: Conf. Ser. 1618 062036\n",
- "- [2] Branlard, E, Meyer Forsting, AR. Wind Energy. 2020; 23: 2068\u2013 2086. https://doi.org/10.1002/we.2546"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import VortexDipole\n",
- "plot_blockage_deficit_map(VortexDipole())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### RankineHalfBody\n",
- "\n",
- "A simple induction model using a Rankine Half Body to represent the induction introduced by a wind turbine. The source strength is determined enforcing 1D momentum balance at the rotor disc.\n",
- "\n",
- "References:\n",
- "\n",
- "- B Gribben, G Hawkes - A potential flow model for wind turbine induction and wind farm blockage - Technical Paper, Frazer-Nash Consultancy, 2019"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import RankineHalfBody\n",
- "plot_blockage_deficit_map(RankineHalfBody())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### HybridInduction\n",
- "The idea behind this model originates from [2,3], which advocates to combine near-rotor and farfield approximations of a rotor's induced velocities. Whereas in [1,2] the motivation is to reduce the computational effort, here the already very fast self-similar model [1] is combined with the vortex dipole approximation in the far-field, as the self-similar one is optimized for the near-field (r/R > 6, x/R < 1) and misses the acceleration around the wake for x/R > 0. The combination of both allows capturing the redistribution of energy by blockage. Location at which to switch from near-rotor to far-field can be altered though by setting switch_radius.\n",
- "\n",
- "References:\n",
- "1. N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016\n",
- "2. Emmanuel Branlard et al 2020 J. Phys.: Conf. Ser. 1618 062036\n",
- "3. Branlard, E, Meyer Forsting, AR. Wind Energy. 2020; 23: 2068\u2013 2086. https://doi.org/10.1002/we.2546"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import HybridInduction\n",
- "plot_blockage_deficit_map(HybridInduction())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Rathmann\n",
- "\n",
- "Ole Sten Rathmann (DTU) developed in 2020 an approximation to the vortex cylinder solution (E. Branlard and M. Gaunaa, 2014). In speed it is comparable to the vortex dipole method, whilst giving a flow-field nearly identical to the vortex cylinder model for x/R < -1. Its centreline deficit is identical to the vortex cylinder model, whilst using a radial shape function that depends on the opening of the vortex cylinder seen from a point upstream. To simulate the speed-up downstream the deficit is mirrored in the rotor plane with a sign change."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deficit_models import Rathmann\n",
- "plot_blockage_deficit_map(Rathmann())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compare blokage deficit models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {},
- "outputs": [],
- "source": [
- "blockagedeficitModels = [SelfSimilarityDeficit(),\n",
- " SelfSimilarityDeficit2020(),\n",
- " FugaDeficit(),\n",
- " VortexCylinder(),\n",
- " VortexDipole(),\n",
- " RankineHalfBody(),\n",
- " HybridInduction(),\n",
- " Rathmann()]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Deficit along center line**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x17182cfac70>"
- ]
- },
- "execution_count": 34,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=((10,6)))\n",
- "for deficitModel in blockagedeficitModels:\n",
- " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(np.linspace(-200,100,300), 0))\n",
- " plt.plot(X[0], deficit[0], label=deficitModel.__class__.__name__)\n",
- "plt.title(\"Center line deficit\")\n",
- "plt.xlabel('x/D')\n",
- "plt.ylabel('Deficit [m/s]')\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Deficit profile 1 up- and downstream**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "for d in [-1,1]:\n",
- " plt.figure(figsize=((10,6)))\n",
- " for deficitModel in blockagedeficitModels:\n",
- " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(d*D, np.linspace(-200,200,300)))\n",
- " plt.plot(Y[:,], deficit[:,0], label=deficitModel.__class__.__name__)\n",
- " plt.title(\"%sD %sstream\"%(abs(d),('down','up')[d<0]))\n",
- " plt.ylim([-.5,.5])\n",
- " plt.xlabel('y/D')\n",
- " plt.ylabel('Deficit [m/s]')\n",
- " plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Rotor-average models\n",
- "\n",
- "In the plots below, it is clearly seen that the wind speed varies over the rotor, and that the the rotor-average wind speed is not well-defined by the wind sped at the rotor center.\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Text(0, 0.5, 'Wind speed [m/s]')"
- ]
- },
- "execution_count": 36,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x288 with 3 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.superposition_models import SquaredSum\n",
- "from py_wake.flow_map import HorizontalGrid, YZGrid\n",
- "R = D/2\n",
- "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
- "sim_res = wfm([0,200],[0,0],wd=270,ws=10)\n",
- "fig,(ax1,ax2) = plt.subplots(1,2, figsize=(10,4))\n",
- "ax1.set_xlabel(\"x [m]\"), ax1.set_ylabel(\"y [m]\")\n",
- "sim_res.flow_map(HorizontalGrid(extend=.1)).plot_wake_map(10, ax=ax1, plot_colorbar=False)\n",
- "sim_res.flow_map(YZGrid(x=200)).plot_wake_map(10, ax=ax2)\n",
- "ax2.plot([-100,100],[70,70],'-.')\n",
- "ax2.set_xlabel(\"y [m]\"), ax1.set_ylabel(\"z [m]\")\n",
- "\n",
- "plt.figure()\n",
- "flow_map = sim_res.flow_map(HorizontalGrid(x=[200], y=np.arange(-80, 80)))\n",
- "\n",
- "for x in [-.5,.5]:\n",
- " plt.gca().axvline(x,color='grey')\n",
- "plt.plot(flow_map.Y[:, 0]/D, flow_map.WS_eff_xylk[:, 0, 0, 0], '-.', label='Hub-height profile')\n",
- "plt.plot([-.5,.5],[7.73,7.73],label='Rotor average: 7.73m/s')\n",
- "rc_ws = flow_map.WS_eff_xylk[80, 0, 0, 0]\n",
- "plt.plot(flow_map.Y[80, 0]/D, rc_ws,'.', ms=10, label='Rotor center: %.2fm/s'%rc_ws)\n",
- "plt.legend()\n",
- "plt.xlabel(\"y/D\")\n",
- "plt.ylabel('Wind speed [m/s]')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A better estimate of the rotor-average wind speed can be obtained by a (weighted) mean of the wind speed at a number of points covering the rotor. Here is a some model examples."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {},
- "outputs": [],
- "source": [
- "from py_wake.rotor_avg_models import RotorCenter, GridRotorAvg, EqGridRotorAvg, GQGridRotorAvg, CGIRotorAvg, PolarGridRotorAvg,polar_gauss_quadrature\n",
- "from py_wake.flow_map import HorizontalGrid\n",
- "R=D/2\n",
- "def plot_rotor_avg_model(rotorAvgModel, name):\n",
- " plt.figure()\n",
- " m = rotorAvgModel\n",
- " wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=m)\n",
- " ws_eff = wfm([0, 200], [0, 0], wd=270, ws=10).WS_eff_ilk[1,0,0]\n",
- " plt.title(name)\n",
- " c = plt.scatter(m.nodes_x, m.nodes_y,c=m.nodes_weight,label=\"%.2fm/s\"%(ws_eff))\n",
- " plt.colorbar(c,label='weight')\n",
- " plt.gca().add_artist(plt.Circle((0,0),1,fill=False))\n",
- " plt.axis('equal')\n",
- " plt.xlabel(\"y/R [m]\"); plt.ylabel('z/R [m]')\n",
- " plt.xlim([-1.5,1.5])\n",
- " plt.ylim([-1.5,1.5])\n",
- " plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### RotorCenter\n",
- "The `RotorCenter` model determines the rotor average wind speed from the rotor center point"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_rotor_avg_model(RotorCenter(), 'RotorCenter')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### GridRotorAvg\n",
- "\n",
- "The `GridRotorAvg` defines a set of points in cartesian coordinates"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "x = y = np.array([-.6, 0,.6])\n",
- "plot_rotor_avg_model(GridRotorAvg(x,y,nodes_weight = [0.25,.5,.25]), 'Grid_4')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### EqGridRotorAvg\n",
- "\n",
- "The `EqGridRotorAvg` defines a NxN equidistant cartesian grid of points and discards points outside the rotor"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_rotor_avg_model(EqGridRotorAvg(4), 'Grid_4')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### GQGridRotorAvg\n",
- "\n",
- "The `GQGridRotorAvg` defines a grid of M x N cartesian grid points using Gaussian quadrature coordinates and weights"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_rotor_avg_model(GQGridRotorAvg(4,3), 'GQGrid_4,3')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### PolarGridRotorAvg\n",
- "\n",
- "The `PolarGridRotorAvg` defines a grid in polar coordinates."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "theta = np.linspace(-np.pi,np.pi,6, endpoint=False)\n",
- "r = 2/3\n",
- "plot_rotor_avg_model(PolarGridRotorAvg(nodes_r =r, nodes_theta=theta, nodes_weight=None), 'PolarGrid_6')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The polar grid can be combined with Gaussian Quadrature. This is similar to the implementation in FusedWake (https://gitlab.windenergy.dtu.dk/TOPFARM/FUSED-Wake/-/blob/master/fusedwake/gcl/fortran/GCL.f)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plot_rotor_avg_model(PolarGridRotorAvg(*polar_gauss_quadrature(4,10)), 'PolarGrid_4,10')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### CGIRotorAvg\n",
- "Circular Gauss integration with 4,7,9 or 21 points as defined in Abramowitz M and Stegun A. Handbook of Mathematical Functions. Dover: New York, 1970."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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2RFNK2X48j0NVP8LTTe+77m8+t3sU8tyteAbYy5S1OEypqSozZ86kZcuWPPvss9x22238/PPPPPTQQxFfNPJKTEzklVdeYcuWLSQmJnLdddfRq1evoDuhzTinCNlEOVrCRfi8E+OKxYsX0759ex5//HGeffZZvvjiCwYNGhTQw2dDUfXq1bnrrrv4/vvvGTBgAJdffjmDBw9m06ZNbkczJZCjUY6WcBE+78QEVGpqKj179mTUqFGMGzeO1NRUevXqZecTFFNsbCyjRo1i06ZNJCQkcOGFFzJq1CgyMuyo81DhmeTQWhzGFOiHH37g6quvJjk5mYEDB/Ldd99xzTXXEBVl/5RKo1KlStx3331s3LiRSpUq0apVK+677z4XrmZniksRMrWcoyVc2P/txpHMzEwefvhhunTpQtu2bdm0aRMjR460Lik/q1mzJpMnT2bNmjX88ssvtGjRglmzZrkdyxRCFbI1ytESLuyoKlOkb775hptuuom6deuyZs0a6tULjxlWg9nZZ5/NK6+8wtKlS7n55puZOXMmzz77LLVq1XI7mjmN+PMEwJAQPiXQ+F1uK6Nnz57ccccdfPDBB1Y0AqxLly6sWbOGunXrkpCQYK2PIKREXosjfN6J8atvvvmGDh06sHz5clavXs1NN91kA98uqVixIk899RQzZ87k3nvvZciQIezdu9ftWMaHDY6biJaZmclDDz1Ejx49uP322/nwww+tlREkclsf8fHxtG7d2lofQUJxdr3xcLrmuI1xmJP27dvHoEGDiI6OZvXq1XbyXhCqWLEi//znPxk4cCA33HADy5YtY+LEiTb/lYsUyPTfXFUhwVocBoBvv/2WDh060L59e+bPn29FI8h16dKFr7/+mlWrVnH55ZfbYbuuErIdLuHCCodh7ty5dO/enYceeognnnjCfr2GiJo1a7JgwQKaNWtGx44d2bhxo9uRIpJiZ46bCKKqPPbYY4wZM4aPPvqI66/P7wqUJpjFxMQwZcoU7r77brp27cqCBQvcjhSRIq3FEVkdc+akI0eOcPPNN7N161ZWrFhB3bp13Y5kSmH48OE0b96cq6++mrvvvpuxY8faUXABoiph1ZpwIrLerQFg165d/OlPfyIuLo7PP//cikaY6Nq1K8uXL+fNN99k6NChZGVluR0pIngGx23KERPGduzYQbdu3ejfvz+vvfYa5cuXdzuS8aOGDRvy5ZdfkpGRweDBgzlx4oTbkSKA2AmAJnxt3bqVbt26ccstt/Dggw9aV0aYqlSpEnPnzuXEiRNcddVVHDt2zO1IYc0zOB5Z53FY4YgQW7ZsoVu3btxxxx3cc889bscxZSwuLo733nuPuLg4rrjiCiseZczOHDdh5+eff+aSSy7h3nvv5fbbb3c7jgmQ2NhYZsyYQbVq1Rg4cKB1W5WRSDxz3ApHmNu5cyeXXnopd955J6NGjXI7jgmw6Oho3njjDeLi4hg8eDCZmZluRwpLOUQ5WsJF+LwTc5rdu3fTo0cPhg0bxp133ul2HOOSmJgYZsyYwfHjx7nhhhvIzs52O1JYUYXMnChHS7gIn3diTnH8+HEGDBjAgAEDuPfee92OY1wWFxfH+++/T3p6OhMmTHA7TljxdFVF1pnjdgJgGFJVRo8eTZ06dXj00UfdjmOCRPny5Xnvvffo0KEDrVu3ZsiQIW5HChvhdFa4E1Y4wtCzzz7LypUr+eqrr+xa4OYUtWvXZu7cuVx66aU0a9aMpKQktyOFvNzDcSOJfauEmcWLF/OPf/yDuXPnUrlyZbfjmCCUkJDASy+9xJVXXsmuXbvcjhMGrKvKhLDNmzdz3XXX8e6779K4cWO345ggNmDAANatW8eAAQNYsmQJcXFxbkcKaXbNcROSfvvtN5KTk3nooYe4+OKL3Y5jQsADDzxA/fr1GTlyJKrqdpyQ5TmqqpyjJVxY4QgDqsr111/PxRdfzMiRI92OY0JEVFQUr776KqtXr2bKlCluxwlZkXgCoHVVhYFp06aRkZHB+++/73YUE2IqVarE7Nmz6dChAz179uT88893O1JIsq4qE1K2bdvGfffdx6uvvkpMTIzbcUwIaty4MY888gg33XSTTcVeAjbJoQkpqsqwYcMYO3YsLVu2dDuOCWEjRoygSpUqPPXUU25HCUl2VJUJGdOmTePXX39l3LhxbkcxIU5EeOWVV2jfvj39+vWzLqtiUBWywqgoOBFZ7zaM+HZRRUcHtv4fycwkKycnoPuMNMezsjge4G6jRo0aWZdVCVlXVQCJSG8R2Sgim0XktAmVROQmEdkjImu8yzA3cgYbt7qolm7bxiWvTeeCF56j9dTn+NtnnwT8yy3cpR86xF9mvUerqc/SauqzXPf+THb+9lvA9j9ixAjOOOMM67IqBhvjCCARKQc8D/QBzgeGiEh+7eN3VbWNd5kW0JBB6uWXXw54F9V3e3Zz67w5bD1wgGxVjmdn8d536xm3aEHAMoS741lZDHx3Bst3bCdblWxVvt65gyvfncGxrMBMhy4iTJs2jcmTJ/Pdd98FZJ/hwJ+Fw8EP6rEi8p2IrBWRT0Skoc9jDUTkYxHZ4N2mkf/e5R/cbHF0ADar6hZVPQG8A/R3MU9IOHDgAA888AD/+c9/AtpF9WLq1xzPMx33sawsFv34I3t+/z1gOcLZoi0/cvjEcbJ9TsbLVuVI5gkWbN4csByNGjXiwQcf5I477gjYPkOZP8/jcPiDejWQpKoJwHvAkz6PvQ5MUtUWeL5jd/vhLZ7GzcJRD9juc3+Hd11eA72V9T0ROTu/FxKRW0UkVURS9+zZUxZZg8YTTzxBcnIyrVq1Cuh+N+/fT04+ZxfHlivHzkOB60oJZz8fOMDRfLr+fs/M5OcDBwKaZcSIEWzdupXFixcHdL+hKgdxtDhQ5A9qVf1MVY947y4H6gN4C0y0qi7ybnfYZzu/CvbB8XlAI29lXQS8lt9GqvqSqiapalLt2rUDGjCQ0tPTeemll/j73/8e8H0n1DmLcnL6P/wT2dk0qlYt4HnCUfNatamQTyuyUkwMzWvVCmiWmJgYHn30UcaPH2/TkRRBFbJyohwtDjj9QZ3rFmC+9/a5wAERmSUiq0VkkrcF43duFo6dgG8Lor533Umquk9Vj3vvTgMSA5QtKD388MPccsst1K9fP+D7HpnUnrg8X2oVoqMZ0jqBauUrBDxPOLq4USPqVjmDGJ+p8GOioqhTuTKXNmka8DyDBg0iJyfHZiRwoBhdVbVye0e8y60l3aeIXA8kAZO8q6KBrsDdQHugCXBTqd5YAdwsHCuBZiLSWERigcFAiu8GIhLvczcZ2BDAfEHlhx9+4P3333ftan6NqlXnvasH86cGDagYHUN85cr8X+cuPHDRxa7kCUfloqKYefU1XN2yFVXj4jgjLo6rzm/J+1cPIdqF66pERUXx+OOPc//999vhuYUo5hjH3tzeEe/yUp6XK/IHNYCI9ADuB5J9flzvANZ4u7mygDlAOz+/XcDFEwBVNUtExgALgXLAdFVdLyIPA6mqmgLcLiLJQBawnzKqnqFgwoQJjB07lho1ariWoXmt2rw+4CrX9h8JzogrzyOX9OCRS3q4HQWAnj17Ur9+faZPn86tt5b4x3HYU/8danvyBzWegjEYuNZ3AxFpC/wb6K2qu/M8t5qI1FbVPcAlQKq/gvly9cxxVf0I+CjPur/53B4PjA90rmCTlpbGl19+yfTp092OYiKMiPD4448zYMAArr/+eipWrOh2pKDkr0kOHf6gngRUBmaKZ9xxm6omq2q2iNwNfCKeB9KAl/0SLA+bciQE3HfffUyYMIFKlSq5HcVEoA4dOnDhhRfy3HPPcc8997gdJ+io+vfSsQ5+UBfYHPUeUZXgtzAFCPajqiLe+vXrWbduHUOHDnU7iolgEyZMYMqUKTbWkS8hOyfK0RIuwuedhKkXXniB4cOHExsb63YUE8EuuOACGjVqxLx589yOEpRUxdESLqxwBLFDhw7x9ttvM3z4cLejGMPo0aOZOnWq2zGCjs1VZYLKm2++Sffu3V05b8OYvAYOHMjatWvZuHGj21GCi3rGOZws4cIKR5BSVaZOncro0aPdjmIMAHFxcdxyyy28+OKLbkcJOn6cciQkWOEIUl9++SWZmZlccsklbkcx5qQRI0bw+uuv87tNbHmS2uC4CRZTp05l1KhRSD7zQxnjloYNG9KlSxfeeecdt6MEFeuqMq7bvXs3CxYs4MYbb3Q7ijGnsUHy09lRVcZ1c+bMoU+fPlSzWWdNEOrVqxfp6elsDuA1QoKZpzVhhcO4LCUlhf797ZpWJjhFRUXRr18/O6fDhx2Oa1z1+++/88UXX9C7d2+3oxhToOTkZFJSUoreMELYGIdx1aJFi+jYsSNVq1Z1O4oxBbr00ktZtWoV+/fvdzuK6xQhJyfK0RIuwuedhImUlBT69evndgxjClWhQgUuvvhi5s+fX/TGEUAdLuHCCkcQyc7O5oMPPrDCYUJCcnKyjXOA98xxGxw3LlmxYgVnnXUWjRs3djuKMUW6/PLLWbhwISdOnHA7ivsirMlhhSOIpKSkkJyc7HYMYxypU6cOzZs354svvnA7iuusxWFcs2jRIvr06eN2DGMc69OnDx9//LHbMVylQE6OOFrChRWOIHH8+HE2bNhAu3Zlcm15Y8pEhw4dSEtLczuGuxRQcbaECbt0bJBYt24d55xzDhUqVHA7ijGOJSYmsmrVKlQ1oudVC6dzNJywFkeQSEtLIzEx0e0YxhRL7dq1qVKlClu2bHE7irtscNy4IS0tjaSkJLdjGFNsiYmJEd5d5Wxg3AbHjd+lpqZai8OEpMTERFJTU92O4a4Ia3EUOsYhIk5GajNVdZ2f8kSk48eP8/3333PBBRe4HcWYYktMTGTy5Mlux3CPgobREVNOFDU4/jmwEgq95mFjoJG/AkUiGxg3ocwGyKHwr8jwU1ThWKmqhV67VEQ+9WOeiLRq1SrrpjIh68wzz6Ry5cps2bKFpk2buh3HHSHYDSUid6jqM0Wty0+hYxxFFQ2n25jC/fjjj5x77rluxzCmxM4999zIPrIqNMc48rvE6E1Onuj4PA4RScDTJXXyOao6y+nzTcEyMjJo0aKF2zGMKbH4+HgyMjLcjuGO3BMAQ4SIDAGuBRqLiO9FVaoAjubJd1Q4RGQ6kACsB3K8qxWwwuEH6enp1K1b1+0YxpRY3bp1SU9PdzuGa0LsBMCvgAygFvCUz/pDwFonL+C0xdFJVc8vXjbjVEZGBvHx8W7HMKbE4uPj2bp1q9sx3BNCR1Wp6s/Az8CFJX0Np+dxLBMRKxxlxAqHCXV169aN3K4qQNTZEkxE5EoR2SQiB0XkNxE5JCK/OXmu0xbH63iKxy7gOJ5jz1RVE0qY2XgdPXqU33//nZo1a7odxZgSi4+Pj9yuquAc+HbiSaCfqm4o7hOdFo5XgL8A6/hjjMP4wa5duzjrrLMi+Ph3Ew4iu8URsjPf/lKSogHOC8ceVU0pejNTXOnp6dZNZUJebosjYk8CDKEWh4hc6b2ZKiLvAnPw9CQBzo6WdVo4VovI28C84u7AFO6XX37hrLPOcjuGMaVSqVIlYmJi+O2336hatarbcQIvtPph+vncPgL08rnv6GhZp4WjAp6CUewdmMIdO3aMihUruh3DmFKrUKECx44di7zCEWLncajqzaV9DUeFwx87yo+I9AaeAcoB01R1Yp7H4/AMzCcC+4BrVHVrWWRxS2ZmJtHRdj0tE/qio6PJyspyO4Yr/HnElIPvxbHAMCAL2AMM9R5ii4hk4xmLBtimqsmF7GdKPqsPAqmqOrewjIUejisitxb2uNNtCnheOeB5oA9wPjAkn0N+bwF+VdVzgH8BT5RkX8EsKyuLmJgYt2MYU2qRXDj8NeWIw+/F1UCS96jW9/AcHZXrqKq28S4FFg2v8kAbYJN3SQDqA7eIyNOFPbGon7r3isjeQh4X4A7gpSJeJz8dgM2qugVARN4B+gPf+WzTH/i79/Z7wHMiIqohdp5mIbKysqzFYcJCRBcO/ynye1FVP/PZfjlwfQn3lQB0UdVs775eAP4H/Ik/Wi35cjKter8itlnkMGRe9YDtPvd3AB0L2kZVs0TkIFATOKWYeVs9twI0aNCghHHcEUY10EQ4ESEnJ7RGif2lGF1VtUTE96pXL6mq7w9vJ9+Lvm4B5vvcL+99/SxgoqrOKeS51YHKeLqnACoBNVQ1W0SOF/y0IgpHWY1t+Jv3g38JICkpKaS+ie1XmgkXEdvtqhRnypG9quqXa0SLyPVAEtDNZ3VDVd0pIk2AT0Vknar+WMBLPAmsEZEleHqPLgL+ISKVgMWF7dvNPpKdwNk+9+t71+W3zQ4RiQaq4hkkDxsxMTFWOExYiOhuV//9XHXyvYiI9ADuB7qpqu8pEju9f7d4C0JbIN/CoaqviMhHeLrHAO5T1dzT/8cVFtLNa46vBJqJSGMRiQUGA3lPMkzhjznjrwI+DafxDbAWhwkfkXyEoB/nqirye1FE2gL/BpJVdbfP+ureI1ERkVpAF04dM87drrn3bzsgHk/X2HbgLIeXC3evxeEdsxgDLMRz2Nl0VV0vIg/jORwsBc9UJ2+IyGY888QPditvWYmNjeXYsWNuxzCm1I4fP05sbKzbMdzhp5+zDr8XJ+EZm5jpPUs/97DbFsC/RSQHT6NgoqqeVjiAsXjGhJ/K5zEFirw4X5GFw3t4WHVV3eu9H4vnKlF3qWqprj6kqh8BH+VZ9zef28eAQaXZR7A788wz+eWXX9yOYUypHDt2jKNHj1K9enW3o7jDj/0gDr4XexTwvK+A1g5e/1bv3+4lzVjUeRyD8fzSXysin4tIL2ALnmOMryvpTs0fIntyOBMuInmyTqfdVEE4rXpFEXlARF7y3m8mIpc7eW5RLY4HgERV3ezt+1oGXKWq80oX2eTKveRmxE4OZ8JCxE/WGUIXcvLxHyAN6Oy9vxOYCXxQ1BOLGhw/oaqbAVR1FbDJioZ/Va5cmXLlynHw4MGiNzYmSEX6xchCscUBNFXVJ4FMAFU9guew3CIV1eI40zsvSq5qvvdV9Z/FTWpOl9tdVa1aNbejGFMi6enp1K1b1+0Y7gm+ouDECRGpgDe9iDTFZ/bzwhTV4ngZqOKz5L1v/CC3u8qYUBXRLY4QHeMAHgQWAGeLyFvAJ8A9Tp5YVIvjB+BjVQ2rk+6CTd26dSP3spsmLKSnp3PRRRe5HcM9wVcUnLgR+BDPPIBbgDtyj54tSlGFowGeY4Vj8FSj+cDX4XYSntusxWFCXUS3OAAJzSm6XgG6Aj2Bpngu2PeFqj5T1BML7apS1SdU9RKgL/ANMBRYJSJvi8gNIlKn9NlNw4YN+fHHgqaTMSb4bdmyhYYNG7odwxSDd5bdx4AJeIYhkoBRTp7raMoRVT2kqrNVdYSqtgUeBWrjuciSKaV27dqxatUqt2MYUyIHDx4kIyOD8847z+0o7vHT9TgCSUQ+AZYC1wAbgfaq2tzJcx0VDhH5RET65t73nsZ+nqpeVoK8Jo82bdqwfv16MjMz3Y5iTLGtWrWKCy64gHLlyrkdxR2hOzi+FjgBtMJzbY5W3qOsiuR0ksPGwP8TkQd91vllamDjOZejYcOGrF+/3u0oxhRbWloaiYmJbsdwVwi2OFT1LlW9CLgSz6zj/wEOOHmu08JxALgUqCMi80Qkwq5GX/YSExNJS0tzO4YxxWaFg5AsHCIyRkTexXMp2v7AdDzTSRXJaeEQVc1S1dHA+8CXwJklCWvyl5SURGpqatEbGhNk0tLSSEqK3A4IwXNUlZMlyJQH/gk0V9UeqvqQqn7q5IlOC8eLuTdU9VU8s+N+XMyQphDW4jChKHdgvHlzR2Oq4SlExzhUdbKqrlDVYl8QyOlRVf/Ocz9NVYcWd2emYDZAbkLR6tWrSUhIiNyB8Vwh2FVVGm5eAdD4yB0g//bbb92OYoxjqampNr4BVjiMey655BI+/th6AE3o+Pjjj7nkkiIvGBf2QrGrqjSscASR5ORkUlLyXnbdmOB08OBBli9fTs+ePd2O4j5rcRi3dOvWjfXr17N79+6iNzbGZQsXLqRr165UqlTJ7Sju0pA9qqrErHAEkbi4OHr27MmHH37odhRjipSSkkJycrLbMYKDtTiMm6y7yoSCzMxM5s+fz+WXO7pEddizMQ7jqr59+/LJJ59w9OhRt6MYU6ClS5fSpEkT6tWr53aU4GAtDuOmmjVr0rZtWz791NEJnMa4IiUlhX79+rkdIzg4LRpWOExZsu4qE8xU1cY3fAjWVWWCwJVXXsmsWbOsu8oEpa+//hpV5YILLnA7StCwwmFc17hxY5KSkpg5c6bbUYw5zdSpUxk1ahQi4naU4GFdVSYYjB49mqlTp7odw5hT7N27l5SUFG6++Wa3owQXKxwmGPTt25eMjAybMdcElf/85z/079+fmjVruh0leDjsprKuKlPmypUrx8iRI3nhhRfcjmIMADk5ObzwwguMHj3a7SjBx1ocJljccsstvP/++/z6669uRzGGhQsXUqNGDdq3b+92lKBjU46YoHHmmWfSt29fXnvtNbejGMPUqVMZPXq0DYrnw7qqTFDJHSTPyQmjnysm5Pz0008sW7aMwYMHux0l+NgJgCbYdO7cmSpVqjB79my3o5gINmnSJIYOHUrFihXdjhKcIqxwRLsdwBRORHjssce488476d+/P9HR9p/MBNbmzZv573//y8aNG92OEpRyzxyPJNbiCAGXXXYZ8fHxNtZhXDFhwgTuuusuOwS3EJKjjhZHryXSW0Q2ishmEbk3n8fHish3IrJWRD4RkYZ5Hj9DRHaIyHN+enunsZ+vIUBEePzxxxk0aBDXXnstFSpUcCXH3iNHmJaWypKff+LMSpUZ3i6Rrg0buZIlXGXl5PDut+uY+d23qMKg81tyTavWxJQr50qeVatW8fnnnzNt2jRX9h8S/NgNJSLlgOeBnsAOYKWIpKjqdz6brQaSVPWIiIwCngSu8Xn8EeAL/yTKnyuFQ0RqAO8CjYCtwNWqetoxpyKSDazz3t2mqhE7q1qnTp1o3749zz33HOPGjQv4/vceOULft17n4LFjZObk8MO+faSl72Rclz9xU5t2Ac8TjlSV4Slz+HrnDo5mZQGwef8+Pv5xM68NGOjK0Uzjx4/ngQcesKv8FcGPXVUdgM2qugVARN4B+gMnC4eqfuaz/XLg+pM5RBKBOsACIMlvqfJwq6vqXuATVW0GfOK9n5+jqtrGu0Rs0cj12GOPMWnSJA4cOBDwfb+yKpXfvEUj19GsLCYtXcrRzMyA5wlHqenprEzfebJogOczXrUrg+U7tgc8z6effsrmzZsZNmxYwPcdcvw3OF4P8P2PvcO7riC3APMBRCQKeAq4u1jZS8CtwtEfyO2wfw24wqUcIaVFixYkJyfz5JNPBnzfn/+8lRP5HBJcLkr4Yd/egOcJRyvTd3Lcp2jkOpqZycr0nQHNoqqMHz+eRx99lNjY2IDuOxQV4zyOWiKS6rPcWuJ9ilyPp1UxybtqNPCRqu4o9RsqgltjHHVUNcN7exeeplV+yotIKpAFTFTVOflt5P3wbwVo0KCBn6MGlwcffJA2bdpw2223BfTqa3UqVeb7vacXiMzsbGraIZp+UatiReLKRXMk69QWXPnoaGpVDGxX0fvvv8+JEye45pprit7YFGeMY6+qFtaFtBM42+d+fe+6U4hID+B+oJuqHveuvhDoKiKjgcpArIgcVtWCenRKrMxaHCKyWES+zWfp77udqhbWiGvo/ZCvBZ4Wkab5baSqL6lqkqom1a5d279vJMicffbZ/PWvf2XkyJF4PrrAGJ6YRIU8hwLHREWRUOcs6p9RNWA5wlmfc5oRFXX6OEY5ieLyc88NWI5ff/2VO++8k6effpqoKDvwskjq1ylHVgLNRKSxiMQCg4FTruomIm2BfwPJqrr7ZAzV61S1gao2wtNd9XpZFA0ow8Khqj1UtVU+y1zgFxGJB/D+3V3Aa+z0/t0CLAHallXeUHLfffexbds23njjjYDts/PZDRjftRsVY2KoHBtLXLlo2pwVzwuXR/zQk99UiYvjjQFXEV+5ChVjYqgYE8NZlSvz2oArOSOufMBy3HHHHQwYMIBu3boFbJ+hzJ9XAFTVLGAMsBDYAPxXVdeLyMMikvs/2yQ8LYqZIrJGRAJ+uVAJ5K/WkzsVmQTsU9WJ3uOUa6jqPXm2qQ4cUdXjIlILWAb0z3NY2mmSkpI0NTW1zLIHi9WrV3PZZZexZs0a6tatG7D9HsvK5Id9+6hZoSL1zjgjYPuNJKrKD/v2oSjn1awV0KOp5s2bx5133snatWsj4kgqEUkrouuoSJVrnq2tet/paNsVb99d6v0FA7faoROBniKyCejhvY+IJIlI7gHjLYBUEfkG+AzPGEehRSOStG3bllGjRjFixIiAdlmVj44hoc5ZVjTKkIhwXq1aNK9VO6BF49dff2XUqFFMnz49IoqGP9kkhwGgqvtU9VJVbebt0trvXZ+qqsO8t79S1daqeoH37ytuZA1m999/P9u3bw9ol5UJX9ZFVUIROMmhnTkewmJjY3n11Vfp1asXPXr0CGiXlQkv8+bNY+nSpaxdu9btKCEpnK614YQdMhHi2rRpw+jRo7n11lsD2mVlwsf+/fsZOXKkdVGVgl3IyYSc++67j127djF58mS3o5gQk52dzXXXXcc111xjXVQlpYCqsyVMWFdVGIiNjWX27Nl06tSJli1b0rdvX7cjmRAxfvx4MjMzXZmNIJyE08C3E9biCBNnn302M2fO5KabbuL77793O44JAW+88QazZs3i3Xffteu8lFaEDY5b4QgjnTt3ZuLEiSQnJ/Prr6dNNmzMSStWrGDs2LHMnTvXrrNRSv48ATBUWOEIM0OHDuXPf/4z11xzDVn5TJhnzM6dOxk4cCDTp0+nZcuWbscJfersIk5OL+QUCqxwhKFJkzyTZd5zzz1FbGkizdGjRxkwYACjR4+mX79+bscJH9ZVZUJddHQ077zzDvPmzWP69OluxzFBIicnh+HDh9OkSRPGjx/vdpywEmldVTYiFqZq1KjBvHnz6N69O1WqVGHQoEFuRzIuUlVuv/12fvrpJxYtWuTK1QTDlgJh1A3lhBWOMNa8eXMWLFhAr169iIuLIznZZrKNRKrKuHHjWLFiBYsXL6aiXT/F/yKrblhXVbi74IIL+OCDDxg2bBgLFixwO44JMFXlb3/7G4sXL2bhwoVUrWrXTikLkdZVZYUjArRv3545c+Zwww038OGHH7odxwSIqnL//fcze/ZsFi1aRI0aNdyOFLbsqCoTljp37kxKSgpDhw5l9uzZbscxZUxV+b//+z/mz5/PkiVLCPcrY7rKZsc14axTp07Mnz+fvn37cuzYMYYMGeJ2JFMGcnJyGDNmDKmpqXz66adUr17d7UhhzXMCYBhVBQescESYdu3asXjxYnr37s1PP/3E+PHj7QibMHLo0CH+8pe/sH//fhYvXswZdsGtwAijmW+dsK6qCNSqVStWrFjBnDlzGDJkCEeOHHE7kvGDLVu2cOGFF1KrVi0rGgEmqo6WcGGFI0LVq1ePzz//nJiYGLp27cr27dvdjmRK4bPPPqNz586MGDGCl19+mdjYWLcjRY4IHOOwwhHBKlSowOuvv87gwYPp1KkTX331lduRTDGpKlOnTmXw4MG89dZb/PWvf7Wux4CLvLmqbIwjwokI48aNo2XLllxxxRU88cQT3HzzzW7HMg6cOHGC22+/nf/973989dVXNG3a1O1IkSuMuqGcsBaHAaBv3758/vnnPP744/z1r3+1cY8gt23bNnr06EF6ejrLli2zouEmtUvHmgjWokULVqxYwb59+2jTpg1Lly51O5LJQ1V5+eWXSUxMpE+fPsyZM8cGwYOBXTrWRLLq1avz9ttvM3v2bAYNGsSQIUN45JFHbH6jILBt2zaGDRvGr7/+ymeffUarVq3cjmRyhU9NcMRaHCZfAwYMYN26dWRkZFjrw2W+rYzu3buzbNkyKxpBRnJyHC3hwlocpkA1a9a01ofLrJURAhQ7AdCYvPK2PmbPno2GUX9tMDp69CiTJk2yVkYIEJyd/GcnAJqIk9v6mDJlCg899BAXXnghS5YscTtW2MnKymLatGmce+65LFu2jP/973+MHz+e6GjrHAhqETY4boXDFEvv3r1ZtWoVt99+O0OHDqVPnz6sXr3a7VghT1WZNWsWrVu35q233uK9995j1qxZNG/e3O1oxgkrHMYULioqimuvvZbvv/+eP//5z/Tt25drr72WH3/80e1oIemzzz6jU6dOPPLII/zrX//i008/pWPHjm7HMk7ljnE4WcKEFQ5TYrGxsYwZM4ZNmzbRokULOnbsyK233sq6devcjhb0cnJymD9/Pr169WLYsGHceeedpKWl0bt3b5syJARF2lFVVjhMqVWuXJkJEyawYcMG6tWrR58+fejatSszZszgxIkTbscLKvv27WPSpEk0a9aMBx54gMGDB7NhwwaGDBlCVJT97xiaHHZTWVeVMaerXbs2Dz74ID/99BN33XUXr7zyCg0aNOD+++9n27Ztbsdzjary9ddfc9NNN3HOOeewfv16ZsyYQWpqKkOHDrWZbEOdYoXDmNKKiYnhyiuvZPHixSxZsoTff/+dtm3b0r9/fz744AOOHTvmdsSA2LdvH9OmTaN9+/YMGTKEVq1asXnzZl599VU6dOhgXVLhxMY4jPGf5s2b8/TTT7Nt2zb69evHxIkTqVOnDgMHDuS1115jz549bkf0qx9++IHJkyfTrVs3mjRpwvz583n00UfZtGkTd999NzVr1nQ7oikD/jyPQ0R6i8hGEdksIvfm8/hYEflORNaKyCci0tC7vqGIrBKRNSKyXkRG+vlt/pEh3E7kSkpK0tTUVLdjmELs2bOHjz76iHnz5rFo0SJat25NcnIyycnJnHfeeSH1SzwrK4tly5Yxb948UlJSOHToEP369SM5OZlLLrmE8uXLux3RFEJE0lQ1qTSvUbVCvHZudJOjbRd8P7HQ/YlIOeAHoCewA1gJDFHV73y26Q6sUNUjIjIKuFhVrxGRWDzf6cdFpDLwLdBZVdNL+t4K4spZRSIyCPg70ALooKr5ftOLSG/gGaAcME1VJwYspCkztWvX5sYbb+TGG2/k2LFjLFmyhJSUFHr06EH58uXp3LkziYmJJCUl0aZNGypVquR25JN2795NWlrayeXLL7+kfv36JCcn89Zbb9GuXbuQKnzGD1Qh22/9UB2Azaq6BUBE3gH6AycLh6p+5rP9cuB673rfI1HiKMMeJbdOR/0WuBL4d0EbeCvv8/hUXhFJ8a28JvSVL1+e3r1707t3b55//nnWrVvH119/TVpaGm+++Sbr16+ncePGJCYmniwmrVq14owzzijTL+icnBx2797N6tWrTykUhw4dol27diQmJjJ48GCmTJnC2WefXWY5TIhw3nNTS0R8fyi/pKov+dyvB/hex3kHUNhJPbcA83PviMjZwIfAOcC4smhtgEuFQ1U3AEX9j19k5TXhRURISEggISGBYcOGAZ6r3K1fv/7kF/dbb73Fd999h6oSHx9P3bp1iY+PP+121apViY6OJjo6mpiYGKKiosjKyjq5ZGZmsm/fPtLT08nIyCAjI+OU27t27aJq1aokJCScLBKTJ0+mSZMm1qIwp3NeOPaWtmssl4hcDyQB3f6IoduBBBGpC8wRkfdU9Rd/7M9XME+A47jyisitwK0ADRo0KPtkJmBiY2Np27Ytbdu2PVlMAA4dOnTKl33u32+++Yb09HQOHz58skBkZWWRnZ19SiGJjo6mRo0aJwvO+eefT48ePU7eP+uss4iLi3PxnZuQoYD/rie+E/Btwtb3rjuFiPQA7ge6qerx0yKppovIt0BX4D1/hctVZoVDRBYDZ+Xz0P2qOtef+/I29V4Cz+C4P1/bBKcqVapQpUoVzj33XLejmIinoH4b41gJNBORxngKxmDgWt8NRKQtnm7+3qq622d9fWCfqh4VkerAn4B/+SuYrzIrHKrao5Qv4ajyGmOMqxS/DY6rapaIjAEW4jkoaLqqrheRh4FUVU0BJgGVgZnebtNtqpqM52Cjp0REAQEmq2qZzP8TzF1VRVZeY4wJCn48rUFVPwI+yrPubz638/1RrqqLgAS/BSmEKycAisgAEdkBXAh8KCILvevrishH4Km8QG7l3QD8V1XXu5HXGGMKFWFTjrh1VNVsYHY+69OBvj73T6u8xhgTXMKrKDgRzF1VxhgT/BQIoynTnbDCYYwxpWUtDmOMMc75dcqRkGCFwxhjSkNB/XceR0iwwmGMMaXlvzPHQ4IVDmOMKS0b4zDGGOOYqh1VZYwxppisxWGMMcY5RbOz3Q4RUFY4jDGmNPw7rXpIsMJhjDGlZYfjGmOMcUoBtRaHMcYYx9SvF3IKCVY4jDGmlCJtcFw0zA4jE5FDwEa3cxRTLWCv2yGKKdQyh1pesMyBcJ6qVinNC4jIAjzv24m9qtq7NPsLBuFYOFJVNcntHMVhmcteqOUFyxwIoZY3WLhyBUBjjDGhywqHMcaYYgnHwvGS2wFKwDKXvVDLC5Y5EEItb1AIuzEOY4wxZSscWxzGGGPKkBUOY4wxxRLyhUNEBonIehHJEZECD6sTka0isk5E1ohIaiAz5pPFaebeIrJRRDaLyL2BzJhPlhoiskhENnn/Vi9gu2zvZ7xGRFJcyFnoZyYicSLyrvfxFSLSKNAZ88lUVOabRGSPz+c6zI2cPnmmi8huEfm2gMdFRKZ4389aEWkX6Ix58hSV92IROejz+f4t0BlDjqqG9AK0AM4DlgBJhWy3Fajldl6nmYFywI9AEyAW+AY438XMTwL3em/fCzxRwHaHXcxY5GcGjAZe9N4eDLzr8r8FJ5lvAp5zM2eePBcB7YBvC3i8LzAfEKATsCLI814MfOD25xpKS8i3OFR1g6qG1JniDjN3ADar6hZVPQG8A/Qv+3QF6g+85r39GnCFe1EK5OQz830f7wGXiogEMGNewfbfuUiq+gWwv5BN+gOvq8dyoJqIxAcm3ekc5DXFFPKFoxgU+FhE0kTkVrfDOFAP2O5zf4d3nVvqqGqG9/YuoE4B25UXkVQRWS4iVwQm2klOPrOT26hqFnAQqBmQdPlz+t95oLfb5z0ROTsw0Uos2P7tOnGhiHwjIvNFpKXbYYJdSExyKCKLgbPyeeh+VZ3r8GX+pKo7ReRMYJGIfO/9JVIm/JQ5oArL7HtHVVVECjqOu6H3c24CfCoi61T1R39njTDzgBmqelxERuBpMV3icqZwsgrPv9vDItIXmAM0czdScAuJwqGqPfzwGju9f3eLyGw8XQRlVjj8kHkn4PvLsr53XZkpLLOI/CIi8aqa4e122F3Aa+R+zltEZAnQFk8ffiA4+cxyt9khItFAVWBfYOLlq8jMquqbbxqe8aZgFvB/u6Whqr/53P5IRKaKSC1VDaXJGgMqIrqqRKSSiFTJvQ30AvI9wiKIrASaiUhjEYnFM5Ab8KOUfKQAN3pv3wic1moSkeoiEue9XQvoAnwXsITOPjPf93EV8Kl6R0hdUmTmPOMDycCGAOYriRTgBu/RVZ2Agz7dnEFHRM7KHecSkQ54vhfd/DER/NwenS/tAgzA04d6HPgFWOhdXxf4yHu7CZ6jVb4B1uPpLgrqzN77fYEf8PxidztzTeATYBOwGKjhXZ8ETPPe7gys837O64BbXMh52mcGPAwke2+XB2YCm4GvgSZufq4OMz/u/Xf7DfAZ0NzlvDOADCDT++/4FmAkMNL7uADPe9/POgo52jFI8o7x+XyXA53d/jcR7ItNOWKMMaZYIqKryhhjjP9Y4TDGGFMsVjiMMcYUixUOY4wxxWKFwxhjTLFY4TAhzTtFRH0RWeKdYfYbEVkpIm0K2D53luQCZyXO5zlNvbOmHvZbcGNCmBUOE7JEpAJQU1V3eFddp6oXAFOBSYU8tbuqOp5aX1V/VNU2JU9qTHixwmGCmog8LCJ3+tx/TETu8N69GM/U9Hktw+Gket4WyOPeFkWqiLQTkYUi8qOIjCxlfGPCkhUOE+ymAzcAiEgUnik53vQ+1gdYkM9zeuOZqM6pbd4Wxf+AV/FMRdIJeKgkgY0JdyExyaGJXKq6VUT2iUhbPFO5r9Y/Jv3rAtzts/lb3vmeKgNtirGb3Lmh1gGVVfUQcEhEjotINVU9UKo3YUyYsRaHCQXT8FwF72Y8LRC807ZvV8/Fj3Jdh2desteAZ4vx+se9f3N8bufetx9XxuRhhcOEgtl4up/aAwu96/LtplLP5GsTgE4i0jxgCY2JIFY4TNDztio+A/6rqtne1b3Jf3wDVT0KPAWMC0xCYyKLzY5rgp53UHwVMEhVN3mv+bFUVR2fi+HzWlvxTPNd7Iv0iMhhVa1c3OcZE26sxWGCmoicj+faGZ+o6iYAVT1ekqLhtQf4pCQnAOK5dooxEc9aHMYYY4rFWhzGGGOKxQqHMcaYYrHCYYwxpliscBhjjCkWKxzGGGOK5f8DDWFH9I9f90YAAAAASUVORK5CYII=\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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FZdI4U1hYGB07duS5555j165dDB06lKeeeorGjRszceJE9u3bV/RJTEDI6Rz3ZAkWwXMlxnGZmZl8+OGHdO/enV69elGtWjU2bNjAxx9/zBVXXBGyHbjlypXjpptuYuXKlXz88cds27aNiy66iBtvvJEVK1Y4HZ7xgSwVj5ZgYYnDlJiqMmPGDFq0aMELL7zAnXfeyc8//8xjjz3m7AN2/FBcXByvvfYaO3bsIC4ujhtuuIHevXuzZs0ap0MzxaQIWYR5tASL4LkS44hFixbRvn17nn76aV544QW++uorrr322jIdPhuIqlSpwn333ceWLVsYNGgQ/fv3Z8iQIWzbts3p0EwxZGuYR0uwCJ4rMWUqKSmJXr16MWrUKMaPH09SUhK9e/cO2eao4oqKimLUqFFs27aN1q1bc8kllzBq1ChSU21WnUDhmuTQahzGFOiHH37gz3/+MwkJCQwePJjvv/+e6667jrAw+1UqidjYWB544AG2bt1KbGwsLVu25IEHHijjJ9mZ4lCEDA33aAkW9r/deCQjI4PHH3+cLl260LZtW7Zt28bIkSOtScrHqlWrxnPPPce6dev49ddfadasGTNnznQ6LFMIVcjSMI+WYBFag49Nsaxfv55hw4ZRu3Zt1q1bR506wTHDqj+rV68er732GsuXL+eWW25hxowZvPDCC1SvXt3p0MxZJORuAAyeFGh8LqeW0atXL+655x7mzJljSaOMdenShXXr1lG7dm1at25ttQ8/pIRejSN4rsT41Pr16+nQoQMrV65k7dq1DBs2zDq+HVK+fHn++c9/MmPGDO6//36GDh3KgQMHij7QlBnrHDchLSMjg8cee4yePXty991389lnn1ktw0/k1D5q1apFq1atrPbhJxTPnjfuxcOe/J71cZhcBw8e5NprryUiIoK1a9fazXt+qHz58vzrX/9i8ODB3HTTTaxYsYKJEyfa/FcOUiDD5qoyoei7776jQ4cOtG/fnnnz5lnS8HNdunRh9erVrFmzhv79+9uwXUcJWR4uwcISh+HTTz+lR48ePPbYYzzzzDP27TVAVKtWjfnz59OkSRM6duzI1q1bnQ4pJCl257gJIarKU089xZgxY5g7dy433nij0yEZL0VGRjJ58mTGjRtH165dmT9/vtMhhaRQq3GEVsOcyXXixAluueUWdu7cyapVq6hdu7bTIZkSuO2222jatCl//vOfGTduHGPHjrVRcGVEVYKqNuEJSxwhaO/evfTr14+WLVvy5Zdf+vRZzFtWb2P5J6uJjI7k8qGXUvdCS0h5qSrrl25i9by1VKwSyxU3dOXc82v45Nxdu3Zl5cqVXHXVVXz33Xe8+uqrRETYf/HS5uocD63mXfutCjG7d+/miiuu4Prrr+eRRx7x2bdSVeWlu6cx//UvSD+ZTlh4GB88+yl3PHcTCaOu9EkZgS47O5vHr/0nyZ+vJ+34KSKiInj3yY/529t30/Xqjj4po379+ixbtozBgwczZMgQ3nvvPaKionxyblMQCaqb+zwRWlcb4nbu3Em3bt249dZbefTRR33alPH9ih+Y//oXnDpxClUlKzOL9JPp/O//3uS3vYd8Vk4g+/rjVblJAyAzPZNTJ9N59uYXSDtxymflxMbG8umnn5Kens4111xDWlqaz85tzubqHA+t+zgscYSIHTt20K1bN+655x7++te/+vz8X320gvST6WetDwsPY/XctT4vLxAtfver3KSRV1h4GBu/+t6nZUVHR/PRRx8RHR3NVVddZcmjlNmd4ybo/Pzzz1x++eXcf//93H333aVSRkREOPlVYESE8IjQav8tSERkwS3D4YVsK66oqCimT59O5cqVGTx4MOnpZyd2U3KheOe4JY4gt2fPHq644gruvfdeRo0aVWrl9Lj+UiKjz55iPTsrm04D4kqt3EDSZ/jlxMRGn7U+LCyMVl2blkqZERERvP3220RHRzNkyBAyMjJKpZxQl02YR0uwCJ4rMWfZt28fPXv2ZMSIEdx7772lWtYFbRpy4yPXEBUTSVS5KGJio4mKieJvb99NxSoVSrXsQNG+TxuuvKUHUeWiiIqJpFyFGMpViOGxT/5KZFTpPdckMjKS6dOnc+rUKW666SaysrJKraxQpAoZ2WEeLcFCVNXpGHwqPj5ek5KSnA7DcadOneLyyy+nW7du/OMf/yizcn/9eT+rPltDRFQEXa5qT6Xq55RZ2YFi15Y9rFm4gdhK5ekyqAPlK5Yrk3LT0tK48sor6dKlS5n+TvgzEUlW1fiSnOPc5tX0unf6eLTvi3HvFVmeiPQB/gOEA1NVdeIZ28cCI4BMYD8wXFV/FpE2wH+Bc4As4ClV/cDLy/GIDccNQqrK6NGjqVmzJk8++WSZll2zfg0SRtvw28Kc37QO5zct+xmHY2Ji+Oijj+jQoQOtWrVi6NChZR5DsPLVXeEiEg68BPQCdgPfikiiquYdPbEWiFfVEyIyCngWuA44AdykqttEpDaQLCILVPWwT4LLwxJHEHrhhRf49ttv+eabb+xZ4OY0NWrU4NNPP+WKK66gSZMmxMeX6Mu24Y/huD7SAdiuqjsAROR9YCCQmzhU9Ys8+68EbnSv/yHPPikisg+oARz2VXA57K9KkFm0aBH/+Mc/+PTTT6lQwfoWzNlat27NK6+8wtVXX83evXudDicIiC8nOawD/JLn/W73uoLcCsw7KyKRDkAU8KMXF+Ixq3EEke3bt3PDDTfwwQcf0LBhQ6fDMX5s0KBBbNy4kUGDBrF06VKio88e7WU858Uzx6uLSN5O2FdU9ZXilCkiNwLxQLcz1tcC3gZuVtXs4py7KFbjCBK///47CQkJPPbYY3Tv3t3pcEwAeOihh6hbty4jR44k2AbJlCXXqKpwjxbggKrG51nOTBp7gHp53td1rzuNiPQEHgQSVPVUnvXnAJ8BD6rqSl9faw5LHEFAVbnxxhvp3r07I0eOdDocEyDCwsJ44403WLt2LZMnT3Y6nIDl4xsAvwWaiEhDEYkChgCJeXcQkbbA/3AljX151kcBs4C3VPUjn11gPqypKghMnTqV1NRUPv74Y6dDMQEmNjaWWbNm0aFDB3r16kXz5s2dDikgedFUVShVzRSRMcACXMNxp6nqJhF5HEhS1URgElABmOGeb26XqiYAfwYuA6qJyDD3KYep6jqfBJeHJY4At2vXLh544AGWLl1KZGTp3URmglfDhg154oknGDZsGN98841Nxe4lH4+qQlXnAnPPWPdIntc9CzjuHeAdnwVSCGuqCmCqyogRIxg7diwtWrRwOhwTwO644w4qVqzIP//5T6dDCUih9uhY+2oRwKZOncqhQ4cYP36806GYACcivPbaa7Rv354BAwZYk5UXVIXMIEoKngitqw0iOU1Ub7zxhjUtGJ9o0KBBbpNVZmam0+EEFJsdtwyJSB8R2Soi20Xk/ny2DxOR/SKyzr2McCJOf2NNVKa03HHHHZxzzjnWZOWFUHyQk2NfVT2ckwXgA1UdU+YB+rFXX33VmqhMqRARpk6dak1WXgqmpOAJJ2scuXOyqGo6kDMniynE4cOHeeihh3j99deticqUigYNGvDoo49yzz33OB1KQLAHOZUtT+dkGSwiG0TkIxGpl892ROR2EUkSkaT9+/eXRqx+45lnniEhIYGWLVs6HYoJYnfccQc7d+5k0aJFTocSELIRj5Zg4e+d47OBBqraGlgIvJnfTqr6Ss4t/DVq1CjTAMtSSkoKr7zyCn//+9+dDsUEucjISJ588kkmTJhg05EUQRUys8M8WoKFk1dS5JwsqnowzzwsU4GQfgbp448/zq233krdunWdDsWEgGuvvZbs7GybkcADodZU5WQjee6cLLgSxhDg+rw7iEgtVU11v00ANpdtiP7jhx9+4OOPP2br1q1Oh2JCRFhYGE8//TR33XUXV111lfWpFSCnjyOUOFbjUNVMIGdOls3AhzlzsohIgnu3u0Vkk4isB+4GhjkTrfMefvhhxo4dS9WqVZ0OxYSQXr16UbduXaZNm+Z0KH5NVTxagoWjXyE8mJNlAjChrOPyN8nJySxbtsz+85oyJyI8/fTTDBo0iBtvvJHy5cs7HZJfCqaOb08ET29NEHvggQd4+OGHiY2NdToUE4I6dOjAJZdcwosvvuh0KH5JNfT6OCxx+LlNmzaxceNGhg8f7nQoJoQ9/PDDTJ482aYiyZeQlR3m0RIsgudKgtR///tfbrvtNqKiopwOxYSwiy++mAYNGjB79mynQ/FLodbHYYnDjx09epT33nuP2267zelQjGH06NFMmTLF6TD8TijOVWWJw4+988479OjRw+7bMH5h8ODBbNiwwYaEn0ld/RyeLMHCEoefUlWmTJnC6NGjnQ7FGACio6O59dZbefnll50Oxe/YlCPGLyxbtoyMjAwuv/xyp0MxJtcdd9zBW2+9xfHjx50OxW+odY4bfzFlyhRGjRqF+2H0xviF+vXr06VLF95//32nQ/Er1lRlHLdv3z7mz5/PzTff7HQoxpzFOsnPZqOqjOM++eQT+vbtS+XKlZ0OxZiz9O7dm5SUFLZv3+50KH7BVZuwxGEclpiYyMCB9kwr45/CwsIYMGCA3dORhw3HNY46fvw4X331FX369HE6FGMKlJCQQGJiotNh+A3r4zCOWrhwIR07dqRSpUpOh2JMga644grWrFnDb7/95nQojlOE7Owwj5ZgETxXEiQSExMZMGCA02EYU6hy5crRvXt35s2b53QofkE9XIKFJQ4/kpWVxZw5cyxxmICQkJBg/RzgvnPcd53jItJHRLaKyHYRuT+f7WNF5HsR2SAii0Wkfp5tN4vINvdSasMyLXH4kVWrVnHeeefRsGFDp0Mxpkj9+/dnwYIFpKenOx2K83xU5RCRcOAloC/QHBgqIs3P2G0tEK+qrYGPgGfdx1YFHgU6Ah2AR0WkSgmvLF+WOPxIYmIiCQkJRe9ojB+oWbMmTZs25auvvnI6FMf5sMbRAdiuqjtUNR14HzhtiKWqfqGqJ9xvVwI5k9ldCSxU1d9U9RCwECiVUTaWOPzIwoUL6du3r9NhGOOxvn378vnnnzsdhqMUyM4Wjxaguogk5VluP+N0dYBf8rzf7V5XkFuBnI4mb48tNnv6vJ84deoUmzdvpl27dk6HYozHOnTowKRJk5wOw1kKeH6PxgFVjfdFsSJyIxAPdPPF+bxhNQ4/sXHjRi644ALKlSvndCjGeCwuLo41a9agwXSTQjH48D6OPUC9PO/rutedRkR6Ag8CCap6yptjfcESh59ITk4mLi7O6TCM8UqNGjWoWLEiO3bscDoUZ/luPO63QBMRaSgiUcAQ4LQ7LUWkLfA/XEljX55NC4DeIlLF3Sne273O5yxx+Ink5GTi431SgzWmTMXFxZGcnOx0GA7yrGPck85xVc0ExuD6g78Z+FBVN4nI4yKSM3JmElABmCEi60Qk0X3sb8ATuJLPt8Dj7nU+Z30cfiIpKYnhw4c7HYYxXouLiyMpKYk///nPTofiHB+21KnqXGDuGeseyfO6ZyHHTgOm+S6a/BWaOETEk57aDFXd6KN4QtKpU6fYsmULF198sdOhGOO1uLg4nnvuOafDcI6CZgfPBIaeKKrG8SWuKk9hn0pDoIGvAgpF1jFuAlneDvLQffBYaF13UYnjW1Ut9NmlIrLEh/GEpDVr1ljHuAlY5557LhUqVGDHjh00btzY6XCcEYCDykTkHlX9T1Hr8lNo53hRScPTfUzhfvzxRy688EKnwzCm2C688MLQHlkVmLMc5jeX1TBPDvS4c1xEWuNqkso9RlVnenq8KVhqairNmjVzOgxjiq1WrVqkpqY6HYYzvLsB0HEiMhS4HmiYMyLLrSLg0SgsjxKHiEwDWgObgGz3agUscfhASkoKtWvXdjoMY4qtdu3apKSkOB2GYwLs/sdvgFSgOvDPPOuPAhs8OYGnNY5OqnrmDI3GR1JTU6lVq5bTYRhTbLVq1WLnzp1Oh+GcABpVpao/Az8DlxT3HJ7eALgin6l9jY9Y4jCBrnbt2qHbVAWIerb4ExG52v3cjiMi8ruIHBWR3z051tMax1u4ksde4BSusWfqng/elMDJkyc5fvw41apVczoUY4qtVq1aodtU5Z8d3554Fhigqpu9PdDTxPEa8BdgI3/0cRgf2Lt3L+edd14Ij383wSC0axwSUJ3jefxanKQBnieO/aqaWPRuxlspKSnWTGUCXk6NI2RvAgygGoeIXO1+mSQiHwCf4GpJAjwbLetp4lgrIu8Bs70twBTu119/5bzzznM6DGNKJDY2lsjISH7//XcqVarkdDhlL7DaYQbkeX0C1yy6OTwaLetp4iiHK2F4XYApXFpaGuXLly/WsdnZ2axfuondP6TSoEU9Wl7aNDS/7RVCNRPSl0FWKkS2QiJbOh2S30k/lcHquWs4vO93Wl3WjPrN6hZ9UD7KlStHWlpa6CWOALuPQ1VvKek5PEocvigoPyLSB/gPEA5MVdWJZ2yPxtUxHwccBK5T1Z2lEYtTMjIyiIjwfpLi3387yv91f5Rfd+4nOysbCQ/j/KZ1mLT4UcpXtDmvADQrBT04FPR30CxA0Kj2SJUpuB51YH76bhfjLv87macyyMrKBoXL/nwJ414bTViYd09diIiIIDMzs3QC9XP+NmLKEyIyOZ/VR4AkVf20sGML/c3I53m4xdqngOPCgZeAvkBzYGg+Q35vBQ6p6gXAv4FnilOWP8vMzCQyMtLr4164cyq7t6Zw8lgap06mk3YsjZ82/syrf327FKIMTHp4LGT/CnocSANOQvpq9PjrTofmF1SVRwY+w+8HjnLiaBqnTqRz6mQ6X3+0ki+mL/f6fKGcOAJ0ypEYoA2wzb20xvXUwFtF5PnCDizqK8X97rG+BS2DgXuKGXQHYLuq7lDVdOB9YOAZ+wwE3nS//gi4QoKsLSYzM9PrGkd2djbLZq4mMyPrtPUZpzJZ8t4yX4YXsDT7EGTkNwgwDU5+6ERIfmfnpl84vO/IWevTjp/is1cWen2+kE4cgak10ENVX1DVF4CeQFNgEKd3S5zFk2nVBxSxj/e/YS51gF/yvN8NdCxoH1XNFJEjQDXgQN6d3LWe2wHOP//8YobjjOI8q1lVyc7OvzcuMzMr3/UhRzMpcKprzSjTUPxVxqkMJCz/zyg9zfvPSEQK/L0MdoHYVAVUwfUkwZxvD7FAVVXNEpFTBR9WROIorb4NX1PVV4BXAOLj4wPqn7A439LCw8O5uHsL1n3xHZr9x+WGhYfRsV9bX4cYkCS8BhpeF7LOnLE1CmL6OhKTv2l8cQMioyI5Sdpp66PLR3HFDZd6fb7iNrsGPCWgphzJ41lgnYgsxfUt6zLgHyISCywq7EAnnzm+B6iX531d97p89xGRCKASrk7yoBEZGVms6v29L99OxaoViCkfDUBMbDSVa5zDqH8HRK4vE1L5OZBYINq9ojyE10Yq3OloXP4iPCKcB967h+jy0URGu75DxlSIoWGr+vzp9l5en684za5BIwD7OFT1NaAzrvs4ZgGXqupUVT2uquMLO9bJf+VvgSYi0hBXghiCa6rfvBJxzRm/ArgGWKLFadvxY8VtF67d+Dze2vYCi979mp0bd9G4TUOuuOFSylWwEVU5JLIl1FiMnpgJWb8gUe0gpq+NqMojrtfFvL7lP3z+xhccSDlEu56t6ZwQT3hEuNfnKu4IwWAQSE1VItJUVbfkeTR4TpfBeSJynqquKeocjv0ru/ssxgALcA3Hnaaqm0TkcVzDwRJxTXXytohsxzVP/BCn4i0tUVFRpKWlFb1jPmIrxTJwdB8fRxRcJKwqUmGE02H4tRp1q3HDQ9eU+DynTp0iKipEk3IAJQ5gLK4+4X/ms02BIh/OV2TicA+braKqB9zvo3A9Jeo+VS3R04dUdS4w94x1j+R5nQZcW5Iy/N25557Lr7/+6nQYxpRIWloaJ0+epEqVKk6H4owAShyqerv7Z4/inqOo+ziG4Pqmv0FEvhSR3sAOXPde3FDcQs0fQntyOBMsQnmyTk+nVPe35iwRKS8iD4nIK+73TUSkvyfHFlXjeAiIU9Xt7vawFcA1qjq7ZCGbHDmP3AzZyeFMUAj5yToDc1TV60Ayrg5ycPU1zwDmFHVgUaOq0lV1O4C7w2SbJQ3fqlChAuHh4Rw5cvaNWMYEilB/GFkg1jiAxqr6LJABoKonKPDmp9MVVeM4V0TG5nlfOe97Vf2Xt5Gas+U0V1WuXNnpUIwplpSUFGrXru10GM7xv6TgiXQRKYc7ehFpTJ7ZzwtTVI3jVaBinuXM98YHcpqrjAlUIV3j8HEfh4j0EZGtIrJdRO7PZ/tlIrJGRDJF5Joztj0rIptEZLOITC5iiqZHgflAPRF5F1gM/NWTGIuqcfwAfK6qQXXTnb+pXbt26D520wSFlJQULrvsMqfDcI6Pahx5Jn/thWsapm9FJFFVv8+z2y5cI1vHnXFsZ6ALrjmoAJYB3YClBRR3M/AZrnkAdwD35IyeLUpRieN8YIaIROLKRvOA1cF2E57TrMZhAl1I1zgA8d0UXbmTvwKISM7kr7mJI+fREiJnlaq4ZryNwtVXEQkUNtb/NaArriTVGNcD+75S1f8UFWShTVWq+oyqXg70A9YDw4E1IvKeiNwkIjWLKsAUrX79+vz4449Oh2FMse3YsYP69es7HUYgqC4iSXmWMx9Lkd/kr3U8ObGqrgC+AFLdy4LCnimuql8ATwEP4+qGiAdGeVKWpw9yOoprLpNZAO7nZvTF9ZClKz05hylYu3bteOedd5wOw5hiOXLkCKmpqVx00UVOh+Icz9tgDqhqfGmEICIXAM1wzfsHsFBEuqrq1wXsvxjXjLgrgK+B9qq6z5OyPJrkUEQWi0i/nPfu9raLVNWShg+0adOGTZs2kZFh032bwLNmzRouvvhiwsO9n98qKPi2c9yTyV8LMghYqarHVPUYrq6FSwrZfwOQDrTE1S/S0j3Kqkiezo7bEPibiDyaZ12pZM1QVKFCBerXr8+mTZucDsUYryUnJxMXF+d0GM7y3ey4uZO/uqd3GoJrsldP7AK6iUiEu1+6G1BYU9V9qnoZcDWuWcdfBw57UpCnieMwcAVQU0Rmi0iIPY2+9MXFxZGcnOx0GMZ4zRIHPkscqpoJ5Ez+uhn4MGfyVxFJABCR9iKyG9c8fv8TkZxvnB8BPwIbcfVJry/shm0RGSMiHwBrcXXAT8PVBVEkT2fHFfcFjRaRYbiGeYXobGalIz4+nqSkJG699VanQzHGK8nJyTz00ENOh+EYwaejqjyZ/PVb/ujHyLtPFnCHF0XFAP8Ckt1/3z3maY3j5ZwXqvoGrjHEn3tTkCmc1ThMIMrpGG/atKnToTgnQCc5VNXnVHWVt0kDPEwcqvq/M94nq+pwbwszBbMOchOI1q5dS+vWrUO3YzxHAD4BsCScfHSsySOng/y7775zOhRjPJaUlGT9G2CJwzjn8ssv5/PPrQXQBI7PP/+cyy8v8oFxQS8Qm6pKwhKHH0lISCAx0dORd8Y468iRI6xcuZJevXo5HYrzrMZhnNKtWzc2bdrEvn0e3bxpjKMWLFhA165diY2NdToUZ6lrVJUnS7CwxOFHoqOj6dWrF5999pnToRhTpMTERBISEpwOwz9YjcM4yZqrTCDIyMhg3rx59O/v0SOqg571cRhH9evXj8WLF3Py5EmnQzGmQMuXL6dRo0bUqePRxK3Bz2ocxknVqlWjbdu2LFmyxOlQjClQYmIiAwYMcDoM/+Bp0rDEYUqTNVcZf6aq1r+Rh2BNVcYPXH311cycOdOaq4xfWr16NarKxRdf7HQofsMSh3Fcw4YNiY+PZ8aMGU6HYsxZpkyZwqhRoxARp0PxH9ZUZfzB6NGjmTJlitNhGHOaAwcOkJiYyC233OJ0KP7FEofxB/369SM1NdVmzDV+5fXXX2fgwIFUq1bN6VD8h4fNVNZUZUpdeHg4I0eO5L///a/ToRgDQHZ2Nv/9738ZPXq006H4H6txGH9x66238vHHH3Po0CGnQzGGBQsWULVqVdq3b+90KH7HphwxfuPcc8+lX79+vPnmm06HYgxTpkxh9OjR1imeD2uqMn4lp5M8OzuIvq6YgPPTTz+xYsUKhgwZ4nQo/sduADT+pnPnzlSsWJFZs2Y5HYoJYZMmTWL48OGUL1/e6VD8U4gljginAzCFExGeeuop7r33XgYOHEhEhP2TmbK1fft2PvzwQ7Zu3ep0KH4p587xUGI1jgBw5ZVXUqtWLevrMI54+OGHue+++2wIbiEkWz1agoUljgAgIjz99NP8/e9/t2lITJlas2YNX375Jffee6/Tofgv6+MoGyJSVUQWisg2988qBeyXJSLr3EtIz/rXqVMn2rdvz4svvuh0KCaETJgwgYceesie8lcEG1VVNu4HFqtqE2Cx+31+TqpqG/cS8lNxPvXUU0yaNInDhw87HYoJAUuWLGH79u2MGDHC6VD8n9U4ysRAIKfB/k3gKofiCCjNmjUjISGBZ5991ulQTJBTVSZMmMCTTz5JVFSU0+H4PatxlI2aqprqfr0XqFnAfjEikiQiK0XkqoJOJiK3u/dL2r9/v69j9SuPPvoo//vf/9izZ4/ToZgg9vHHH5Oens51113ndCiBwYc1DhHpIyJbRWS7iJzVGiMil4nIGhHJFJFrzth2voh8LiKbReR7EWlQkssqSKklDhFZJCLf5bMMzLufqhb2kdZX1XjgeuB5EWmc306q+oqqxqtqfI0aNXx7IX6mXr163HXXXYwcORLXR2eMbx06dIh7772X559/nrAwGz9TJPXdlCMiEg68BPQFmgNDRaT5GbvtAoYB7+VzireASaraDOgA7Cv+hRWs1H4rVLWnqrbMZ/kU+FVEagG4f+Z7caq6x/1zB7AUaFta8QaSBx54gF27dvH22287HYoJQvfccw+DBg2iW7duTocSEHz8BMAOwHZV3aGq6cD7uJr2c6nqTlXdAJyWitwJJkJVF7r3O6aqJ3xwiWdx6utEInCz+/XNwKdn7iAiVUQk2v26OtAF+L7MIvRjUVFRvPHGG4wbN46UlBSnwzFBZPbs2SxfvpyJEyc6HUpgUfVsgeo5zeru5fYzzlQH+CXP+93udZ64EDgsIjNFZK2ITHLXYHzOqcQxEeglItuAnu73iEi8iEx179MMSBKR9cAXwERVtcTh1rZtW0aNGsUdd9xhTVbGJw4dOsSoUaOYNm2aDb/1khc1jgM5zeru5RUfhhEBdAXGAe2BRriatHzOkcShqgdV9QpVbeJu0vrNvT5JVUe4X3+jqq1U9WL3z9eciNWfPfjgg/zyyy/WZGV8wpqoism3NwDuAerleV/Xvc4Tu4F17mauTOAToJ2Hx3rFJj4KYDlNVr1796Znz57Url3b6ZBMgMppotqwYYPToQQkHz5r41ugiYg0xJUwhuAaHOTpsZVFpIaq7gcuB5J8FlkeNmQiwLVp04bRo0dz++23W5OVKZbffvuNkSNHWhNVCfhqVJW7pjAGWABsBj5U1U0i8riIJACISHsR2Q1cC/xPRDa5j83C1Uy1WEQ24uq3f7U0rtdqHEHggQceoHPnzjz33HOMHz/e6XBMAMnKyuKGG27guuuusyaq4lJyOr59czrVucDcM9Y9kuf1t7iasPI7diHQ2mfBFMASRxCIiopi1qxZdOrUiRYtWtCvXz+nQzIBYsKECWRkZNhsBCUUTHeFe8KaqoJEvXr1mDFjBsOGDWPLli1Oh2MCwNtvv83MmTP54IMP7DkvJWVzVZlA1blzZyZOnEhCQgKHDh1yOhzjx1atWsXYsWP59NNP7TkbJeTjGwADgiWOIDN8+HD+9Kc/cd1115GZmel0OMYP7dmzh8GDBzNt2jRatGjhdDiBTz17iJM9yMn4tUmTJgHw17/+1eFIjL85efIkgwYNYvTo0QwYMMDpcIKHNVWZQBcREcH777/P7NmzmTZtWpmWnZ6WzrovvuO75VvIysoq07IDxYmjJ1mzaANbv91epkOos7Ozue2222jUqBETJkwos3JDQag1VVmPWJCqWrUqs2fPpkePHlSsWJFrr7221MtcNmsVzw57EREBhahyUTw5+34uan9BqZcdKOa8spCX73uD8MhwNFupVOMcnp73IHUvLN2bN1WVu+++m59++omFCxe6/o2MbygQRM1QnrAaRxBr2rQp8+fPZ8yYMSQmlu6Td1N/+pWJN07m5NE0Tvx+khNHT3J43xH+1vsJTp08VaplB4otq7fx8tg3OHUynRO/n+TksTR+3bmfv/V+guxs3916fCZVZfz48axatYq5c+dSvnz5UisrZFlTlQkmF198MXPmzGHEiBHMnz+/1Mr5/M2l+TZNZWcrK+esKbVyA0nilAWkn8w4bZ2qcvTQMb5f8UOplKmqPPLIIyxatIgFCxZQqVKlUikn1IVaU5UljhDQvn17PvnkE2666SY+++yzUinjyIGjZKbnkziysjj627FSKTPQHN7/e759GiLCsUPHfV6eqvLggw8ya9YsFi5cSNWqVX1ehnGxUVUmKHXu3JnExESGDx/OrFmzfH7+jn3bElMh5qz1mq20vaKlz8sLRJ0T2hNTPvqs9ZnpmTTvfKFPy1JV/u///o958+axdOlSgv3JmI7y7ey4AcESRwjp1KkT8+bNY9SoUUyfPt2n527fty3NOjUhJvaPP4wxsdH0u60ndS6o5dOyAlWvmy6jdpPziM6TPKLLR3PTY9dxTtWKPisnOzubO++8k2XLlrFkyRKqV6/us3Obs7luAFSPlmBho6pCTLt27Vi0aBF9+vThp59+YsKECT4ZYRMWFsbTcx9k8btfs/jdr4kqF8mfbutFxz+VyuMAAlJ0uWgmf/MUC15fylcfr6BStYokjO7Dxd19dxPe0aNH+ctf/sJvv/3GokWLOOecc3x2blOI0hvb4Jck2Kbijo+P16SkUpmCPqjs2bOHQYMG0ahRI6ZNm2YjbYLAjh07SEhIoFOnTkyZMoWoqCinQ/J7IpKsqvElOcc559TV9vF3erTvki8eKHF5/sCaqkJUnTp1+PLLL4mMjKRr16788ssvRR9k/NYXX3xB586dueOOO3j11VctaZQl6+MwoaRcuXK89dZbDBkyhE6dOvHNN984HZLxkqoyZcoUhgwZwrvvvstdd91lN/eVudCbq8r6OEKciDB+/HhatGjBVVddxTPPPMMtt9zidFjGA+np6dx99918/fXXfPPNNzRu3NjpkEJXkDX5F8VqHAaAfv368eWXX/L0009z1113ceLECadDMoXYtWsXPXv2JCUlhRUrVljScJL67tGxgcISh8nVrFkzVq1axcGDB2nTpg3Lly93OiRzBlXl1VdfJS4ujr59+/LJJ5/YyCl/oOrZEiSsqcqcpkqVKrz33nvMmjWLa6+9lqFDh/LEE0/YqCs/sGvXLkaMGMGhQ4f44osvaNnSbqz0G8GTEzxiNQ6Tr0GDBrFx40ZSU1Ot9uGwvLWMHj16sGLFCksafkaysz1agoXVOEyBqlWrZrUPh1ktIwAoIXcDoNU4TJHOrH3MmjWrTB9AFIpOnjzJpEmTrJYRAATPphsJpilHLHEYj+TUPiZPnsxjjz3GJZdcwtKlS50OK+hkZmYydepULrzwQlasWMHXX3/NhAkTiIiwxgG/FmKd45Y4jFf69OnDmjVruPvuuxk+fDh9+/Zl7dq1TocV8FSVmTNn0qpVK959910++ugjZs6cSdOmTZ0OzXjCEocxhQsLC+P6669ny5Yt/OlPf6Jfv35cf/31/Pjjj06HFpC++OILOnXqxBNPPMG///1vlixZQseOHZ0Oy3gqp4/DkyVIWOIwxRYVFcWYMWPYtm0bzZo1o2PHjtx+++1s3LjR6dD8XnZ2NvPmzaN3796MGDGCe++9l+TkZPr06WNThgQgX46qEpE+IrJVRLaLyP35bL9MRNaISKaIXJPP9nNEZLeIvOiDS8uXJQ5TYhUqVODhhx9m8+bN1KlTh759+9K1a1emT59Oenq60+H5lYMHDzJp0iSaNGnCQw89xJAhQ9i8eTNDhw4lLMz+OwYmD5upPGiqEpFw4CWgL9AcGCoizc/YbRcwDHivgNM8AXxV7MvxgP2mGp+pUaMGjz76KD/99BP33Xcfr732Gueffz4PPvggu3btcjo8x6gqq1evZtiwYVxwwQVs2rSJ6dOnk5SUxPDhw20m20Cn+LKPowOwXVV3qGo68D4w8LTiVHeq6gbyafwSkTigJvB5ia+rEJY4jM9FRkZy9dVXs2jRIpYuXcrx48dp27YtAwcOZM6cOaSlpTkdYpk4ePAgU6dOpX379gwdOpSWLVuyfft23njjDTp06GBNUsHE8z6O6iKSlGe5/Ywz1QHyPuNgt3tdkUQkDPgnMK74F+IZSxymVDVt2pTnn3+eXbt2MWDAACZOnEjNmjUZPHgwb775Jvv373c6RJ/64YcfeO655+jWrRuNGjVi3rx5PPnkk2zbto1x48ZRrVo1p0M0pcCL+zgOqGp8nuUVH4YxGpirqrt9eM582eBwUyZiY2MZMWIEI0aMYP/+/cydO5fZs2dz991306pVKxISEkhISOCiiy4KqG/imZmZrFixgtmzZ5OYmMjRo0cZMGAAf/vb37j88suJiYlxOkRTFnw31HYPUC/P+7rudZ64BOgqIqOBCkCUiBxT1bM62EvKkcQhItcCfweaAR1UNd9nvYpIH+A/QDgwVVUnllmQptTUqFGDm2++mZtvvpm0tDSWLl1KYmIiPXv2JCYmhs6dOxMXF0d8fDxt2rQhNjbW6ZBz7du3j+Tk5Nxl2bJl1K1bl4SEBN59913atWsXUInP+IAqZPlsrO23QBMRaYgrYQwBrvcsDL0h57WIDAPiSyNpgHM1ju+Aq4H/FbRDntEFvXC1830rIomq+n3ZhGjKQkxMDH369KFPnz689NJLbNy4kdWrV5OcnMw777zDpk2baNiwIXFxcbnJpGXLlpxzzjml+gc6Ozubffv2sXbt2tMSxdGjR2nXrh1xcXEMGTKEyZMnU69evaJPaIKbj2ocqpopImOABbi+ME9T1U0i8jiQpKqJItIemAVUAQaIyGOq2sInAXhInJxzSESWAuPyq3GIyCXA31X1Svf7CQCq+nRh54yPj9ekpHwrMCYApaens2nTptP+eH///feoKrVq1aJ27drUqlXrrNeVKlUiIiKCiIgIIiMjCQsLIzMzM3fJyMjg4MGDpKSkkJqaSmpq6mmv9+7dS6VKlWjduvVpSatRo0ZWowgiIpKsqvElOUelmPO0c92/eLTv/B+fK3F5/sCf+zjyG12Q7+207pEJtwOcf/75pR+ZKTNRUVG0bduWtm3bMmLEiNz1R48ePe2Pfc7P9evXk5KSwrFjx3ITRGZmJllZWaclkoiICKpWrZqbcJo3b07Pnj1z35933nlER0c7eOUmYCgQRM8T90SpJQ4RWQScl8+mB1X1U1+W5R6Z8Aq4ahy+PLfxTxUrVqRixYpceOGFTodiQp6CBtF8Ih4otcShqj1LeIqSjC4wxpiyofiyczwg+PN9HLmjC0QkCtfogkSHYzLGmLPZ7LilT0QGichuXOOOPxORBe71tUVkLrhGFwA5ows2Ax+q6iYn4jXGmEKFWOJwpHNcVWfhGk525voUoF+e93OBuWUYmjHGeCm4koIn/HlUlTHG+D8FPJwyPVhY4jDGmJKyGocxxhjP+XTKkYBgicMYY0pCQe0+DmOMMV6xO8eNMcZ4xfo4jDHGeEzVRlUZY4zxktU4jDHGeE7RrCyngyhTljiMMaYkbFp1Y4wxXrPhuMYYYzylgFqNwxhjjMfUHuRkjDHGS6HWOS4aZMPIROQosNXpOLxUHTjgdBBeCrSYAy1esJjLwkWqWrEkJxCR+biu2xMHVLVPScrzB8GYOJJUNd7pOLxhMZe+QIsXLOayEGjx+gt/fnSsMcYYP2SJwxhjjFeCMXG84nQAxWAxl75Aixcs5rIQaPH6haDr4zDGGFO6grHGYYwxphRZ4jDGGOOVgE8cInKtiGwSkWwRKXBYnYjsFJGNIrJORJLKMsZ8YvE05j4islVEtovI/WUZYz6xVBWRhSKyzf2zSgH7Zbk/43UikuhAnIV+ZiISLSIfuLevEpEGZR1jPjEVFfMwEdmf53Md4USceeKZJiL7ROS7AraLiEx2X88GEWlX1jGeEU9R8XYXkSN5Pt9HyjrGgKOqAb0AzYCLgKVAfCH77QSqOx2vpzED4cCPQCMgClgPNHcw5meB+92v7weeKWC/Yw7GWORnBowGXna/HgJ84PDvgicxDwNedDLOM+K5DGgHfFfA9n7APECATsAqP4+3OzDH6c81kJaAr3Go6mZVDag7xT2MuQOwXVV3qGo68D4wsPSjK9BA4E336zeBq5wLpUCefGZ5r+Mj4AoRkTKM8Uz+9u9cJFX9CvitkF0GAm+py0qgsojUKpvozuZBvMZLAZ84vKDA5yKSLCK3Ox2MB+oAv+R5v9u9zik1VTXV/XovULOA/WJEJElEVorIVWUTWi5PPrPcfVQ1EzgCVCuT6PLn6b/zYHezz0ciUq9sQis2f/vd9cQlIrJeROaJSAung/F3ATHJoYgsAs7LZ9ODqvqph6e5VFX3iMi5wEIR2eL+JlIqfBRzmSos5rxvVFVFpKBx3PXdn3MjYImIbFTVH30da4iZDUxX1VMicgeuGtPlDscUTNbg+r09JiL9gE+AJs6G5N8CInGoak8fnGOP++c+EZmFq4mg1BKHD2LeA+T9ZlnXva7UFBaziPwqIrVUNdXd7LCvgHPkfM47RGQp0BZXG35Z8OQzy9lnt4hEAJWAg2UTXr6KjFlV88Y3FVd/kz8r89/dklDV3/O8nisiU0SkuqoG0mSNZSokmqpEJFZEKua8BnoD+Y6w8CPfAk1EpKGIROHqyC3zUUp5JAI3u1/fDJxVaxKRKiIS7X5dHegCfF9mEXr2meW9jmuAJeruIXVIkTGf0T+QAGwuw/iKIxG4yT26qhNwJE8zp98RkfNy+rlEpAOuv4tOfpnwf073zpd0AQbhakM9BfwKLHCvrw3Mdb9uhGu0ynpgE67mIr+O2f2+H/ADrm/sTsdcDVgMbAMWAVXd6+OBqe7XnYGN7s95I3CrA3Ge9ZkBjwMJ7tcxwAxgO7AaaOTk5+phzE+7f2/XA18ATR2OdzqQCmS4f49vBUYCI93bBXjJfT0bKWS0o5/EOybP57sS6Oz074S/LzbliDHGGK+ERFOVMcYY37HEYYwxxiuWOIwxxnjFEocxxhivWOIwxhjjFUscJqC5p4ioKyJL3TPMrheRb0WkTQH758ySXOCsxPkc09g9a+oxnwVuTACzxGECloiUA6qp6m73qhtU9WJgCjCpkEN7qKrHU+ur6o+q2qb4kRoTXCxxGL8mIo+LyL153j8lIve433bHNTX9mVbg4aR67hrI0+4aRZKItBORBSLyo4iMLGH4xgQlSxzG300DbgIQkTBcU3K8497WF5ifzzF9cE1U56ld7hrF18AbuKYi6QQ8VpyAjQl2ATHJoQldqrpTRA6KSFtcU7mv1T8m/esCjMuz+7vu+Z4qAG28KCZnbqiNQAVVPQocFZFTIlJZVQ+X6CKMCTJW4zCBYCqup+DdgqsGgnva9l/U9fCjHDfgmpfsTeAFL85/yv0zO8/rnPf25cqYM1jiMIFgFq7mp/bAAve6fJup1DX52sNAJxFpWmYRGhNCLHEYv+euVXwBfKiqWe7Vfci/fwNVPQn8ExhfNhEaE1psdlzj99yd4muAa1V1m/uZH8tV1eN7MfKcayeuab69fkiPiBxT1QreHmdMsLEah/FrItIc17MzFqvqNgBVPVWcpOG2H1hcnBsAcT07xZiQZzUOY4wxXrEahzHGGK9Y4jDGGOMVSxzGGGO8YonDGGOMVyxxGGOM8cr/A+/6Wo03Fb7FAAAAAElFTkSuQmCC\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "for n in [4,7,9,21]:\n",
- " plot_rotor_avg_model(CGIRotorAvg(n), 'CGIRotorAvg_%d'%n)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compare rotor-average models\n",
- "In general, the compuational cost and the accuracy of the estimate increases with the number of points, but the distribution of the points also has an impact.\n",
- "\n",
- "The plot below shows the absolute error of the estimated rotor-average wind speed for the wind directions \n",
- "270$\\pm$30$^\\circ$ (i.e. wind directions with more than 1% deficit) for a number of different rotor-average models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x17186cfb280>"
- ]
- },
- "execution_count": 45,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "grid_models = [EqGridRotorAvg(i) for i in range(1,10)]\n",
- "wd_lst = np.arange(240,301)\n",
- "\n",
- "def get_ws_eff(rotorAvgModel):\n",
- " wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=rotorAvgModel)\n",
- " return wfm([0, 200], [0, 0], wd=wd_lst, ws=10).WS_eff_ilk[1,:,0]\n",
- "\n",
- "ws_ref = get_ws_eff(EqGridRotorAvg(200)) # Use 200x200 points (31700 inside the rotor) to determine the reference value\n",
- "\n",
- "def get_n_err(rotorAvgModel):\n",
- " ws_mean_err = np.abs(get_ws_eff(rotorAvgModel) - ws_ref).mean()\n",
- " return len(rotorAvgModel.nodes_x), ws_mean_err\n",
- " \n",
- "\n",
- "plt.gca().axhline(0, color='grey',ls='--')\n",
- "plt.plot(*zip(*[get_n_err(m) for m in grid_models]), label='Grid_x')\n",
- "model_lst = [('RotorCenter', EqGridRotorAvg(1)),\n",
- " ('Grid_4', EqGridRotorAvg(4)), \n",
- " ('PolarGrid_4,10', PolarGridRotorAvg(*polar_gauss_quadrature(4,10))),\n",
- " ('GQGrid_4,3', GQGridRotorAvg(4, 3))] + \\\n",
- " [('CGI_%d'%n, CGIRotorAvg(n)) for n in [4,7,9,21]]\n",
- "for name, model in model_lst:\n",
- " n,err = get_n_err(model)\n",
- " plt.plot(n,err,'.',ms=10, label=\"%s (%.4f)\"%(name,err))\n",
- "plt.xlabel('Number of rotor-average points')\n",
- "plt.ylabel('Mean abs error (270$\\pm30^\\circ$) [m/s]')\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Deflection models\n",
- "The deflection models calculate the deflection of the wake due to yaw-misalignment, sheared inflow etc. \n",
- "Note, this is one of the four effects of skew inflow that is handled in PyWake, see [here](https://topfarm.pages.windenergy.dtu.dk/PyWake/notebooks/YawMisalignment.html).\n",
- "The deflection models take as input the downwind and crosswind distances between the source wind turbines and the destination wind turbines/sites and calculate a new set of deflected downwind and crosswind distances."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {},
- "outputs": [],
- "source": [
- "def plot_deflection(deflectionModel):\n",
- " from py_wake import IEA37SimpleBastankhahGaussian\n",
- " from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines\n",
- "\n",
- " site = IEA37Site(16)\n",
- " x, y = [0, 400, 800], [0, 0, 0]\n",
- " windTurbines = V80()\n",
- " wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=deflectionModel)\n",
- "\n",
- " yaw_ilk = np.reshape([-20,20,0],(3,1,1))\n",
- "\n",
- " plt.figure(figsize=(14,4))\n",
- " fm = wfm(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10).flow_map()\n",
- " fm.plot_wake_map()\n",
- " fm.min_WS_eff().plot(color='k', ls='--')\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### JimenezWakeDeflection"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The `JimenezWakeDeflection` model is implemented according to Jim\u00e9nez, \u00c1., Crespo, A. and Migoya, E. (2010), Application of a LES technique to characterize the wake deflection of a wind turbine in yaw. Wind Energ., 13: 559-572. doi:10.1002/we.380"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 47,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1008x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deflection_models import JimenezWakeDeflection\n",
- "plot_deflection(JimenezWakeDeflection())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### FugaDeflection"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 48,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1008x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deflection_models import FugaDeflection\n",
- "plot_deflection(FugaDeflection())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Implement your own deflection models\n",
- "\n",
- "Deficit models must subclass `DeficitModel` and thus must implement the `calc_deflection` method and a class variable, `args4deflection` specifying the arguments required by its calc_deflection method\n",
- "\n",
- "```python\n",
- "\n",
- "class DeflectionModel(ABC):\n",
- " args4deflection = [\"ct_ilk\"]\n",
- "\n",
- " @abstractmethod\n",
- " def calc_deflection(self, dw_ijl, hcw_ijl, **kwargs):\n",
- " \"\"\"Calculate deflection\n",
- "\n",
- " This method must be overridden by subclass\n",
- "\n",
- " Arguments required by this method must be added to the class list\n",
- " args4deflection\n",
- "\n",
- " See documentation of EngineeringWindFarmModel for a list of available input arguments\n",
- "\n",
- " Returns\n",
- " -------\n",
- " dw_ijlk : array_like\n",
- " downwind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
- " for all wind direction (l) and wind speed (k)\n",
- " hcw_ijlk : array_like\n",
- " horizontal crosswind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
- " for all wind direction (l) and wind speed (k)\n",
- " \"\"\"\n",
- "```"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 49,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.contour.QuadContourSet at 0x17186dc3ee0>"
- ]
- },
- "execution_count": 49,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.deflection_models import DeflectionModel\n",
- "from numpy import newaxis as na\n",
- "class MyDeflectionModel(DeflectionModel):\n",
- " args4deficit = ['dw_ijlk', 'cw_ijlk']\n",
- "\n",
- " def calc_deflection(self, dw_ijl, hcw_ijl, **_):\n",
- " dw_ijlk = dw_ijl[..., na] # add extra wind speed dimension\n",
- " hcw_ijlk =hcw_ijl[..., na] + .1*dw_ijlk # deflect 1/10 of the downstream distance\n",
- " dh_ijlk =np.zeros_like(hcw_ijl[..., na]) # no vertical deflection\n",
- " return dw_ijlk, hcw_ijlk, dh_ijlk\n",
- "\n",
- "iea_my_deflection = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=MyDeflectionModel())\n",
- "\n",
- "plt.figure(figsize=(10,4))\n",
- "iea_my_deflection(x, y, wd=270, ws=10).flow_map().plot_wake_map()\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Turbulence models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 50,
- "metadata": {},
- "outputs": [],
- "source": [
- "# methods to plot turbulence map, used below to visualize and compare the deficit models\n",
- " \n",
- "def plot_turb_map(turbulenceModel):\n",
- " xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
- " X,Y,deficit = _map(turbulenceModel.calc_added_turbulence, xy)\n",
- " c = plt.contourf(X,Y,deficit, levels=100, cmap='Blues')\n",
- " plt.colorbar(c, label=\"Added turbulence intensity [-]\")\n",
- " plt.plot([0,0],[-1/2,1/2],'k')\n",
- " plt.ylabel(\"Crosswind distance [y/D]\")\n",
- " plt.xlabel(\"downwind distance [x/D]\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### STF2005TurbulenceModel\n",
- "\n",
- "Steen Frandsen model implemented according to IEC61400-1, 2005 and weight according to Steen Frandsen's [thesis](https://orbit.dtu.dk/en/publications/turbulence-and-turbulence-generated-structural-loading-in-wind-tu)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.turbulence_models import STF2005TurbulenceModel\n",
- "plot_turb_map(STF2005TurbulenceModel())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### STF2017TurbulenceModel\n",
- "\n",
- "Steen Frandsen model implemented according to IEC61400-1, 2017 and weight according to Steen Frandsen's [thesis](https://orbit.dtu.dk/en/publications/turbulence-and-turbulence-generated-structural-loading-in-wind-tu)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 52,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.turbulence_models import STF2017TurbulenceModel\n",
- "plot_turb_map(STF2017TurbulenceModel())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**STF20XXTurbulenceModel with IEC-based spread angle**\n",
- "\n",
- "The `STF2005TurbulenceModel` and `STF2017TurbulenceModel` take a `weight_function` input which defaults to the bell-shaped `FrandsenWeight` defined in Steen Frandsen's thesis. As an alternative the `IECWeight` applies the full added turbulence in a 21.6$^\\circ$ spread angle up to 10 diameter downstream. \n",
- "\n",
- "Note, this is a debatable interpretation of the IEC standard which includes a 6% contribution from neighbouring wind turbines when calculating the omni-directional effective turbulence intensity. These 6% maps to a spread angle of 360$^\\circ\\cdot$ 6% = 21.6$^\\circ$.\n",
- "\n",
- "Note, the IEC standard includes more concepts which is not implemented in PyWake"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 53,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.turbulence_models import STF2017TurbulenceModel, IECWeight\n",
- "from py_wake.superposition_models import SqrMaxSum\n",
- "plot_turb_map(STF2017TurbulenceModel(addedTurbulenceSuperpositionModel=SqrMaxSum(), \n",
- " weight_function=IECWeight(distance_limit=10)))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### GCLTurbulence\n",
- "\n",
- "Gunner Chr. Larsen model implemented according to \n",
- " \n",
- " Pierik, J. T. G., Dekker, J. W. M., Braam, H., Bulder, B. H., Winkelaar, D., Larsen, G. C., Morfiadakis, E., Chaviaropoulos, P., Derrick, A., & Molly, J. P. (1999). European wind turbine standards II (EWTS-II). In E. L. Petersen, P. Hjuler Jensen, K. Rave, P. Helm, & H. Ehmann (Eds.), Wind energy for the next millennium. Proceedings (pp. 568-571). James and James Science Publishers."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 54,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.turbulence_models import GCLTurbulence\n",
- "plot_turb_map(GCLTurbulence())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### CrespoHernandez\n",
- "\n",
- " Implemented according to:\n",
- " A. Crespo and J. Hern\u00e1ndez\n",
- " Turbulence characteristics in wind-turbine wakes\n",
- " J. of Wind Eng. and Industrial Aero. 61 (1996) 71-85"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 55,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.turbulence_models import CrespoHernandez\n",
- "plot_turb_map(CrespoHernandez())"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Compare Turbulence models"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 56,
- "metadata": {},
- "outputs": [],
- "source": [
- "turbulenceModels = [STF2005TurbulenceModel(),\n",
- " STF2017TurbulenceModel(),\n",
- " STF2017TurbulenceModel(addedTurbulenceSuperpositionModel=SqrMaxSum(), weight_function=IECWeight(10)),\n",
- " GCLTurbulence(),\n",
- " CrespoHernandez()]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**turbulence intensity along center line**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 57,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x1718932c040>"
- ]
- },
- "execution_count": 57,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=((10,6)))\n",
- "for turbulenceModel in turbulenceModels:\n",
- " X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(np.linspace(-200,500,300), 0))\n",
- " l = turbulenceModel.__class__.__name__\n",
- " if l.startswith('STF'):\n",
- " l+=f\"({turbulenceModel.apply_weight.__self__.__class__.__name__})\"\n",
- " plt.plot(X[0], ti[0], label=l)\n",
- "\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Deficit profile 2D downstream**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 58,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x171893a5130>"
- ]
- },
- "execution_count": 58,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 720x432 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=((10,6)))\n",
- "for turbulenceModel in turbulenceModels:\n",
- " X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(2*D, np.linspace(-200,200,300)))\n",
- " plt.plot(Y[:,], ti[:,0], label=turbulenceModel.__class__.__name__)\n",
- "\n",
- "plt.legend()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Ground models"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Mirror\n",
- "The Mirror ground model lets the ground mirror the wake deficit. It is implemented by adding wakes from underground mirrored wind turbines"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 59,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<matplotlib.contour.QuadContourSet at 0x171895c3e50>"
- ]
- },
- "execution_count": 59,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "from py_wake.ground_models import Mirror\n",
- "wfm = NOJ(site, windTurbines, k=.5, groundModel=Mirror())\n",
- "wfm([0], [0], wd=0).flow_map(YZGrid(x=0, y=np.arange(-300, 100, 1) + .1, z=np.arange(-100, 200))).plot_wake_map()\n"
- ]
- }
- ],
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- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
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- "name": "ipython",
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- "nbconvert_exporter": "python",
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- "version": "3.8.8"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
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- "title_sidebar": "Contents",
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- "height": "calc(100% - 180px)",
- "left": "10px",
- "top": "150px",
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- },
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- "toc_window_display": true
- }
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Engineering WindFarmModels"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "All Wind farms models take a `Site` and a `WindTurbines` object as input"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Install PyWake if needed\n",
+ "try:\n",
+ " import py_wake\n",
+ "except ModuleNotFoundError:\n",
+ " !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake.git"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# import and setup site and windTurbines\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import os\n",
+ "import py_wake\n",
+ "from py_wake.examples.data.hornsrev1 import V80, Hornsrev1Site\n",
+ "\n",
+ "site = Hornsrev1Site()\n",
+ "windTurbines = V80()\n",
+ "wt_x, wt_y = site.initial_position.T"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Model overview\n",
+ "\n",
+ "\n",
+ "The engineering wind farms models in PyWake are composed of one of two wind farms models in combination with a wake deficit model, a superposition model and optionally a blockage deficit and a turbulence model.\n",
+ "\n",
+ "- `WindFarmModel`: Defines the proceedure that detemines how wake and blockage deficits propagates in the wind farm. \n",
+ "Two models are available:\n",
+ " - [PropagateDownwind](#PropagateDownwind) (fast, but blockage is neglected)\n",
+ " - [All2AllIterative](#All2AllIterative) (slower but supports blockage).\n",
+ "- Wake `DeficitModel`: Calculate wake deficit from one wind turbine to downstream wind turbines or sites in the wind farm. Several common models are available: \n",
+ " - [NOJDeficit](#NOJDeficit)\n",
+ " - [FugaDeficit](#FugaDeficit)\n",
+ " - [BastankhahGaussianDeficit](#BastankhahGaussianDeficit)\n",
+ " - [NiayifarGaussianDeficit](#NiayifarGaussianDeficit)\n",
+ " - [ZongGaussianDeficit](#ZongGaussianDeficit)\n",
+ " - [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit)\n",
+ " - [GCLDeficit](#GCLDEficit)\n",
+ "- `SuperpositionModel`: Defines how deficits from multiple sources sums up. Available models are:\n",
+ " - [LinearSum](#LinearSum): Deficits sum up linearly\n",
+ " - [SquaredSum](#SquaredSum): Deficits sum as root-sum-square\n",
+ " - [MaxSum](#MaxSum): Only the largest deficit is considered\n",
+ "- Blockage `DeficitModel`: Calculate blockage deficit from one wind turbine to other wind turbines or sites in the wind farm. Some models, model upstream effects only while other also models downstream speed-up effects. Available models are:\n",
+ " - [SelfSimilarityDeficit](#SelfSimilarityDeficit)\n",
+ " - [SelfSimilarityDeficit2020](#SelfSimilarityDeficit2020)\n",
+ " - [FugaDeficit](#FugaDeficit)\n",
+ " - [VortexCylinder](#VortexCylinder)\n",
+ " - [VortexDipole](#VortexDipole)\n",
+ " - [RankineHalfBody](#RankineHalfBody)\n",
+ " - [HybridInduction](#HybridInduction)\n",
+ " - [Rathmann](#Rathmann) \n",
+ "- `RotorAvgModel`: Defines one or more points at the rotor to calculate a (weighted) rotor-average deficit from\n",
+ " - [RotorCenter](#RotorCenter): One point at the center of the rotor\n",
+ " - [GridRotorAvg](#GridRotorAvg): Custom grid in Cartesian coordinates\n",
+ " - [EqGridRotorAvg](#EqGridRotorAvg): Equidistant N x N Cartesian grid covering the rotor\n",
+ " - [GQGridRotorAvg](#GQGridRotorAvg): M x N cartesian grid using Gaussian quadrature coordinates and weights\n",
+ " - [PolarGridRotorAvg](#PolarGridRotorAvg): Custom grid in polar coordinates \n",
+ " - [CGIRotorAVG](#CGIRotorAvg): Circular Gauss Integration\n",
+ "- `DeflectionModel`: Calculate deflected downwind and crosswind distances due to yaw misalignment, shear etc. Available models are:\n",
+ " - [JimenezWakeDeflection](#JimenezWakeDeflection)\n",
+ "- `TurbulenceModel`: Calculate added turbulence in the wake from one wind turbine to downstream wind turbines or sites in the wind farm. Available models are:\n",
+ " - [STF2005TurbulenceModel](#STF2005TurbulenceModel): Steen Frandsen, from IEC 2005 standard\n",
+ " - [STF2017TurbulenceModel](#STF2017TurbulenceModel): Steen Frandsen, from IEC 2017 standard\n",
+ " - [GCLTurbulence](#GCLTurbulence): Gunner Chr. Larsen\n",
+ " - [CrespoHernandez](#CrespoHernandez): A. Crespo and J. Hernández\n",
+ "- `GroundModel`: Model effects of ground:\n",
+ " - [Mirror](#Mirror): The ground acts as a mirror on the wake\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Predefined WindFarmModels\n",
+ "The deficit models comprise:\n",
+ "\n",
+ "| Name | WindFarmModel | Wake DeficitModel | Blockage DeficitModel | SuperpositionModel |\n",
+ "| :--- | :--- | :--- | :--- | :--- | \n",
+ "| NOJ | [PropagateDownwind](#PropagateDownwind) | [NOJDeficit](#NOJDeficit) | - | [SquaredSum](#SquaredSum) |\n",
+ "| Fuga | [PropagateDownwind](#PropagateDownwind) | [FugaDeficit](#FugaDeficit) | - | [LinearSum](#LinearSum) |\n",
+ "| FugaBlockage | [All2AllIterative](#All2AllIterative) | [FugaDeficit](#FugaDeficit) | [FugaDeficit](#FugaDeficit) | [LinearSum](#LinearSum) |\n",
+ "| BastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [BastankhahGaussianDeficit](#BastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
+ "| IEA37SimpleBastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
+ "\n",
+ "- Default rotor-average model: `RotorCenter`\n",
+ "- Default turbulence model: `None`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from py_wake import NOJ\n",
+ "from py_wake import Fuga\n",
+ "from py_wake import FugaBlockage\n",
+ "from py_wake import BastankhahGaussian\n",
+ "from py_wake import IEA37SimpleBastankhahGaussian\n",
+ "\n",
+ "# Path to Fuga look-up tables\n",
+ "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
+ "\n",
+ "models = {'NOJ': NOJ(site,windTurbines), \n",
+ " 'Fuga': Fuga(lut_path,site,windTurbines),\n",
+ " 'FugaBlockage': FugaBlockage(lut_path,site,windTurbines), \n",
+ " 'BGaus': BastankhahGaussian(site,windTurbines),\n",
+ " 'IEA37BGaus': IEA37SimpleBastankhahGaussian(site,windTurbines)\n",
+ " }"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "These models can easily be combined with other models, e.g. NOJ with linear sum superposition:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from py_wake.superposition_models import LinearSum\n",
+ "models['NOJLinear'] = NOJ(site,windTurbines,superpositionModel=LinearSum())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "or models can be combined in custom ways, e.g. NOJDeficit for the wake, LinearSum superposition and SelfSimilarityDeficit for the blockage:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from py_wake.wind_farm_models import All2AllIterative\n",
+ "from py_wake.deficit_models import NOJDeficit, SelfSimilarityDeficit\n",
+ "models['NOJ_ss'] = All2AllIterative(site,windTurbines,\n",
+ " wake_deficitModel=NOJDeficit(),\n",
+ " superpositionModel=LinearSum(), \n",
+ " blockage_deficitModel=SelfSimilarityDeficit() )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "NOJ: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
+ "Fuga: Fuga(PropagateDownwind, FugaDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
+ "FugaBlockage: FugaBlockage(All2AllIterative, FugaDeficit-wake, FugaDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n",
+ "BGaus: BastankhahGaussian(PropagateDownwind, BastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
+ "IEA37BGaus: IEA37SimpleBastankhahGaussian(PropagateDownwind, IEA37SimpleBastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
+ "NOJLinear: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
+ "NOJ_ss: All2AllIterative(EngineeringWindFarmModel, NOJDeficit-wake, SelfSimilarityDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n"
+ ]
+ }
+ ],
+ "source": [
+ "for name, model in models.items():\n",
+ " print (\"%s: %s\"%(name, model))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Engineering WindFarmModel base classes\n",
+ "\n",
+ "### PropagateDownwind\n",
+ "The `PropagateDownwind` wind farm model is very fast as it only performs a minimum of deficit calculations. It iterates over all turbines in downstream order. In each iteration it calculates the effective wind speed at the current wind turbine as the free stream wind speed minus the sum up the deficit from upstream sources. Based on this effective wind speed, it calculates the deficit caused by the current turbine on all downstream destinations. Note, that this procedure neglects upstream blockage effects.\n",
+ "\n",
+ "```python\n",
+ "\n",
+ "for wt in wind turbines in downstream order:\n",
+ " ws_eff[wt] = ws[wt] - superposition(deficit[from_upstream_src,to_wt])\n",
+ " ct = windTurbines.ct(ws_eff[wt])\n",
+ " deficit[from_wt,to_downstream_dst] = wakeDeficitModel(ct, distances[from_wt,to_downstream_dst], ...)\n",
+ "```\n",
+ "\n",
+ "The proceedure is illustrated in the animation below:\n",
+ "- Iteration 1: WT0 sees the free wind (10m/s). Its deficit on WT1 and WT2 is calculated.\n",
+ "- Iteration 2: WT1 sees the free wind minus the deficit from WT0. Its deficit on WT2 is calculated and the effective wind speed at WT2 is updated"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "125 ms ± 0 ns per loop (mean ± std. dev. of 1 run, 10 loops each)\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%timeit -r1\n",
+ "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
+ "models['Fuga'](wt_x[:20],wt_y[:20])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### All2AllIterative\n",
+ "The `All2AllIterative` wind farm model is slower but is capable of handling blockage effects. <br/> \n",
+ "It iterates until the effective wind speed converge (i.e. less than or equal to the maximum number of turbines that affect each other in the wind farm. The converge tolerance is an input parameter).<br/> \n",
+ "In each iteration it sums up the deficit from all wind turbine sources and calculates the deficit caused by the all wind turbines turbine on all wind turbines.\n",
+ "\n",
+ "```python\n",
+ "\n",
+ "while ws_eff not converged:\n",
+ " ws_eff[all] = ws[all] - superposition(deficit[from_all,to_all])\n",
+ " ct[all] = windTurbines.ct(ws_eff[all])\n",
+ " deficit[from_all,to_all] = wakeDeficitModel(ct[all], distances[from_all,to_all], ...)\n",
+ "```\n",
+ "\n",
+ "The proceedure is illustrated in the animation below:\n",
+ "- Iteration 1: All three WT see the free wind (10m/s) and their CT values and resulting deficits are therefore equal\n",
+ "- Iteration 2: The local effective wind speeds are updated taking into account the wake and blockage effects of the other WT. Based on these wind speeds the CT and deficits are recalculated\n",
+ "- Iteration 3: Repeat after which the flow field has converged"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2.38 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%timeit -r1\n",
+ "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
+ "models['FugaBlockage'](wt_x[:20],wt_y[:20])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Wake deficit models\n",
+ "The wake deficit models compute the wake deficit caused by a single wind turbine. \n",
+ "\n",
+ "**Variable suffixes**\n",
+ "\n",
+ "The implementation of the deficit models is highly vectorized and therefore suffixes are used to indicate the dimension of variables. The suffixes used in this context are:\n",
+ "\n",
+ "- i: source wind turbines\n",
+ "- j: destination wind turbines\n",
+ "- k: wind speeds\n",
+ "- l: wind directions\n",
+ "\n",
+ "This means that `deficit_ijlk[0,1,2,3]` holds the deficit caused by the first turbine on the second turbine for the third wind direction and fourth wind speed"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# methods to plot deficit map, used below to visualize and compare the deficit models\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from matplotlib import cm\n",
+ "from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
+ "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
+ "D = 80\n",
+ "def _map(f, xy=None):\n",
+ " X, Y = np.meshgrid(*xy)\n",
+ " x_j, y_j = X.flatten(), Y.flatten()\n",
+ " downwind_distance_ijlk = x_j.reshape((1, -1, 1, 1))\n",
+ " crosswind_distance_ijlk = np.abs(y_j.reshape((1, -1, 1, 1)))\n",
+ " ws = 10\n",
+ " res_ijlk = f(\n",
+ " # specify arguments for all models\n",
+ " WS_ilk=np.array([[[ws]]]), # wind speed at source turbine\n",
+ " D_src_il=np.array([[D]]), # diameter of source turbine\n",
+ " D_dst_ijl=None, # diameter of destination turbine\n",
+ " h_il=np.array([[67]]), # source turbine hub height\n",
+ " dw_ijlk=downwind_distance_ijlk, # down wind distance\n",
+ " hcw_ijlk=crosswind_distance_ijlk, # horizontal cross wind distance\n",
+ " dh_ijlk=np.zeros_like(crosswind_distance_ijlk),\n",
+ " # height difference(vertical cross wind distance) between source and destination turbine\n",
+ " cw_ijlk=crosswind_distance_ijlk, # cross wind distance (both horizontal and vertical)\n",
+ " ct_ilk=np.array([[[8 / 9]]]), # thrust coefficient\n",
+ " WS_eff_ilk=np.array([[[ws]]]), # effective wind speed at source turbine\n",
+ " TI_ilk=np.array([[[0.1]]]),\n",
+ " TI_eff_ilk=np.array([[[0.1]]]),\n",
+ " wake_radius_ijlk=BastankhahGaussianDeficit().wake_radius(dw_ijlk=downwind_distance_ijlk, \n",
+ " D_src_il=np.array([[D]]), \n",
+ " ct_ilk=np.array([[[8 / 9]]])),\n",
+ " )\n",
+ " return X / D, Y / D, res_ijlk[0, :, 0, 0].reshape(X.shape)\n",
+ "\n",
+ " \n",
+ "def plot_deficit_map(model, cmap='Blues', levels=np.linspace(0,10,55)):\n",
+ " xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
+ " X,Y,deficit = _map(model.calc_deficit, xy)\n",
+ " c = plt.contourf(X,Y,deficit, levels=levels, cmap=cmap)\n",
+ " plt.colorbar(c, label=\"Deficit [m/s]\")\n",
+ " plt.plot([0,0],[-1/2,1/2],'k')\n",
+ " plt.ylabel(\"Crosswind distance [y/D]\")\n",
+ " plt.xlabel(\"downwind distance [x/D]\")\n",
+ "\n",
+ "def plot_wake_deficit_map(model):\n",
+ " cmap = np.r_[[[1,1,1,1],[1,1,1,1]],cm.Blues(np.linspace(-0,1,128))] # ensure zero deficit is white\n",
+ " plot_deficit_map(model,cmap=ListedColormap(cmap))\n",
+ "\n",
+ "def plot_blockage_deficit_map(model):\n",
+ " from matplotlib import cm\n",
+ " from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
+ " cmap = np.r_[cm.Reds_r(np.linspace(-0,1,127)),[[1,1,1,1],[1,1,1,1]],cm.Blues(np.linspace(-0,1,128))] # ensure zero deficit is white\n",
+ " plot_deficit_map(model,cmap=ListedColormap(cmap), levels=np.linspace(-3.5,3.5,113))\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### NOJDeficit\n",
+ "\n",
+ "The NOJDeficit model is implemented according to Niels Otto Jensen, \"A note on wind generator interaction.\" (1983), i.e. a top-hat wake, only valid in the far wake\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import NOJDeficit\n",
+ "plot_wake_deficit_map(NOJDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### FugaDeficit\n",
+ "\n",
+ "The FugaDeficit model calculates the wake deficit based on a set op look-up tables computed by a linearized RANS solver. The look-up tables be created in advance using the [Fuga GUI](https://orbit.dtu.dk/en/publications/developments-of-the-offshore-wind-turbine-wake-model-fuga)\n",
+ "\n",
+ "The fugaDeficit models both near wake, far wake and blockage deficit"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import os\n",
+ "import py_wake\n",
+ "from py_wake.deficit_models import FugaDeficit\n",
+ "\n",
+ "# Path to Fuga look-up tables\n",
+ "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
+ "\n",
+ "plot_wake_deficit_map(FugaDeficit(lut_path))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### BastankhahGaussianDeficit\n",
+ "\n",
+ "The `BastankhahGaussianDeficit` model is implemented according to Bastankhah M and Porté-Agel F. \"A new analytical model for wind-turbine wakes\" J. Renew. Energy. 2014;70:116-23. The model is valid in the far wake only."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
+ "plot_wake_deficit_map(BastankhahGaussianDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### IEA37SimpleBastankhahGaussianDeficit\n",
+ "\n",
+ "The `IEA37SimpleBastankhahGaussian` model is implemented according to the [IEA task 37 documentation](https://github.com/byuflowlab/iea37-wflo-casestudies/blob/master/cs1-2/iea37-wakemodel.pdf) and is equivalent to BastankhahGaussian for $beta=1/\\sqrt{8} \\sim ct=0.9637188$. The model is valid in the far wake only."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import IEA37SimpleBastankhahGaussianDeficit\n",
+ "plot_wake_deficit_map(IEA37SimpleBastankhahGaussianDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GCLDeficit\n",
+ "\n",
+ " Implemented according to:\n",
+ " Larsen, G. C. (2009). A simple stationary semi-analytical wake model.\n",
+ " Risoe National Laboratory for Sustainable Energy,\n",
+ " Technical University of Denmark. Denmark.\n",
+ " Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
+ "\n",
+ " Description:\n",
+ " based on an analytical solution of the thin shear layer approximation of the NS equations.\n",
+ " The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields\n",
+ " are consistently assumed uniform.\n",
+ " The effect of expansion is approximately accounted for by imposing suitable\n",
+ " empirical downstream boundary conditions on the wake expansion that depend\n",
+ " on the rotor thrust and the ambient turbulence conditions, respectively."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import GCLDeficit\n",
+ "plot_wake_deficit_map(GCLDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### NiayifarGaussianDeficit\n",
+ " \n",
+ " Implemented according to:\n",
+ " Amin Niayifar and Fernando Porté-Agel\n",
+ " Analytical Modeling of Wind Farms: A New Approach for Power Prediction\n",
+ " Energies 2016, 9, 741; doi:10.3390/en9090741\n",
+ "\n",
+ " Features:\n",
+ " - Wake expansion function of local turbulence intensity\n",
+ "\n",
+ " Description:\n",
+ " The expansion rate 'k' varies linearly with local turbluence\n",
+ " intensity: k = a1 I + a2. The default constants are set\n",
+ " according to publications by Porte-Agel's group, which are based\n",
+ " on LES simulations. Lidar field measurements by Fuertes et al. (2018)\n",
+ " indicate that a = [0.35, 0.0] is also a valid selection."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import NiayifarGaussianDeficit\n",
+ "plot_wake_deficit_map(NiayifarGaussianDeficit(a=[0.38, 4e-3]))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### ZongGaussianDeficit\n",
+ " \n",
+ " Implemented according to:\n",
+ " Haohua Zong and Fernando Porté-Agel\n",
+ " A momentum-conserving wake superposition method for\n",
+ " wind farm power prediction\n",
+ " J. Fluid Mech. (2020), vol. 889, A8; doi:10.1017/jfm.2020.77\n",
+ "\n",
+ " Features:\n",
+ " - Wake expansion function of local turbulence intensity\n",
+ " - New wake width expression following the approach by\n",
+ " Shapiro et al. (2018)\n",
+ "\n",
+ " Description:\n",
+ " Extension of the Niayifar et al. (2016) implementation with Shapirio\n",
+ " wake width expression, which uses the near-wake length estimation by\n",
+ " Vermeulen (1980)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import ZongGaussianDeficit\n",
+ "plot_wake_deficit_map(ZongGaussianDeficit(a=[0.38, 4e-3]))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GCLDeficit\n",
+ "\n",
+ " Implemented according to:\n",
+ " Larsen, G. C. (2009). A simple stationary semi-analytical wake model. \n",
+ " Risø National Laboratory for Sustainable Energy, \n",
+ " Technical University of Denmark. Denmark. \n",
+ " Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
+ "\n",
+ " Description:\n",
+ " based on an analytical solution of the thin shear layer approximation of the NS equations. \n",
+ " The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields \n",
+ " are consistently assumed uniform.\n",
+ " The effect of expansion is approximately accounted for by imposing suitable \n",
+ " empirical downstream boundary conditions on the wake expansion that depend \n",
+ " on the rotor thrust and the ambient turbulence conditions, respectively. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import GCLDeficit\n",
+ "plot_wake_deficit_map(GCLDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Compare deficit models"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "deficitModels = [NOJDeficit(),\n",
+ " FugaDeficit(lut_path),\n",
+ " BastankhahGaussianDeficit(),\n",
+ " IEA37SimpleBastankhahGaussianDeficit(),\n",
+ " NiayifarGaussianDeficit(),\n",
+ " ZongGaussianDeficit(),\n",
+ " GCLDeficit()]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Deficit along center line**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b6e46131f0>"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
},
- "nbformat": 4,
- "nbformat_minor": 2
-}
\ No newline at end of file
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=((10,6)))\n",
+ "for deficitModel in deficitModels:\n",
+ " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(np.linspace(-200,500,300), 0))\n",
+ " plt.plot(X[0], deficit[0], label=deficitModel.__class__.__name__)\n",
+ "plt.title(\"Center line deficit\")\n",
+ "plt.xlabel('x/D')\n",
+ "plt.ylabel('Deficit [m/s]')\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Deficit profile 2D downstream**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b6e42d32e0>"
+ ]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=((10,6)))\n",
+ "for deficitModel in deficitModels:\n",
+ " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(2*D, np.linspace(-200,200,300)))\n",
+ " plt.plot(Y[:,], deficit[:,0], label=deficitModel.__class__.__name__)\n",
+ "\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Implement your own deficit models\n",
+ "Deficit models must subclass `DeficitModel`and thus must implement the `calc_deficit` method and a class variable, `args4deficit` specifying the arguments required by its `calc_deficit` method\n",
+ "\n",
+ "```python \n",
+ "class DeficitModel(ABC):\n",
+ " args4deficit = ['WS_ilk', 'dw_ijlk']\n",
+ "\n",
+ " @abstractmethod\n",
+ " def calc_deficit(self):\n",
+ " \"\"\"Calculate wake deficit caused by the x'th most upstream wind turbines\n",
+ " for all wind directions(l) and wind speeds(k) on a set of points(j)\n",
+ "\n",
+ " This method must be overridden by subclass\n",
+ "\n",
+ " Arguments required by this method must be added to the class list\n",
+ " args4deficit\n",
+ "\n",
+ " See class documentation for examples and available arguments\n",
+ "\n",
+ " Returns\n",
+ " -------\n",
+ " deficit_ijlk : array_like\n",
+ " \"\"\"\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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vdJJDzEQvLYuzNnKD7VeNsv/TFOMKryuXipg3zs+fa/tvxtOxym2oC4H/Al5F8XzuCcDq8XxYRL36khpJDhGjk7Qj8GLgzQC2HwceH+fp/kPSXwBfY8sx6IdadaySLJ5o+xxJJ9u+DrhO0nXjDDRmsZTUiOlGUtXaUPMlLat7v9T20hFtDFwlycBnRzkO8HxJt1CsPXGK7TuAZ1D8gf55SQcAy4GTbT821u9DkWROAz5UxlOL6xmtOlZJFrXZTA9IeiXFl9h9HEHGLFW7gkhyiBlszcgxiFEcYvt+SU8CrpZ0p+3r646vAJ5u+1FJRwFfBfai+D39bOCdtm+S9Gng/cDfjSPOvwGe2eJW2KiqpMx/krQT8B7gFIpBlsVj/aCYXQYGzcCgWf3oEA8PDCZRxKxn+/7y54PApcDBI46vs/1o+foKoF/SfIoVSlfZvqlsejFF8hiPO4CB8XSscmWx1vbDFBPzXgog6ZDxfFjMfKsfHcp8h4gRJG0H9Nh+pHz9cuAfRrR5CvAr25Z0MMUf878u398naW/bPwIOA8ZbzHUYuFnSNWw5ZjHxR2eBf2PrLDbavpiFkhxiJusRk1Ub6snApZKg+L37n7a/IekkANtLgNcBfyVpCPgt8HrbtXGFdwIXlk9C3U1REHA8vlpuY9YwWUh6PvACYIGk+ketdqRY2DtmobUDw3lqKWKMbN8NHDDK/iV1r88EzmzQ/2ag1ZhIlTjOH2/fZmMWc4DtKRLKDnXbOooMGLPA2oFhVj86tGlLooiYfsqqsxNq0/DKou4x2fNs/7w8WQ+wve11Yw02pofUW4qYkV4jqdka26Ick26kypjFP5f31YYpnu/dSdKnbJ9WPc6YqupLaqRia8SWxjDPYqp7b4U2NzQ7WCVZ7Gt7naQ3UNQVeR9F0phwspB0JMU09l7gbNuVFuGIiRkYNBsGi6SQ20oRM99ExipqqiSLfkn9wGuAM20PljMQJ0RSL/AZ4AiK54i/L+nyrO/dHvV1lzLnISLGqsr11WeBnwHbAddLejrFIPdEHQzcZfvustbJF4FjJuG8McLagWEe2zC0aYuIGKuWycL2GbZ3s32UCz+nxUBIRbtRrMJXs6rctwVJJ0paJmnZ6tWpXxgRndMj2G5Ob8ttupD0x1X2jabZPIvjbV8wYo5FvYmulKdR9m11e6sstrUUYNGiRRO+/TUbbdO/5d8EGaeImLU+AHy5wr6tNBuz2K78ucM4g2plFfC0uve7UxQpjEk2r1/Mq5uFum69GN7oTY/I5gmoiJlN0iuAo4DdJJ1Rd2hHoNK96WbzLD5b/mzXSnnfB/aStCfwC+D1wJ+16bOizo5zt7zSWLd+IxuGioSRxBExI90PLAOOpniateYR4N1VTtDsNtQZjY5BtcJTLfoPSXoH8E2KR2fPLWu3R4cVyaNIIKsf3fxHRhJHzHYC5vSOdsd8erF9C3CLpAttj+spl2a3oWrZ5xBgX4rV8gD+mC0z07iVZXivmIxzxeRYsP2W/0mkUGDE9CfpS7b/BPjBaFMfbO/f6hzNbkOdX37ImynWjR0s3y8Brhpv0DG9JHlEzAgnlz9HW9+7kiqT8p5KMchdW6N1+3JfzEJJHhHTj+0Hypc9wAO21wNI2paifHpLVZLFxykuXa4p378E+MjYQo2ZasH2fVusrf3wwGCT1hHTS0+PmDdnRtSGqvkyxdITNcPlvue26lhlUt7ngT+gWAbwUuD5k1FnJGaO4tHcYtt1pznsNK9/0xYRm0nqlfQDSV9r0ua5koYlvW6sfSvoKytmAFC+nlOpY5VGtn8JXDa+2GK2mde/+emReTvNSV2qiM1OBlZSzG/YSlkz7xMUT4mOqW9FqyUdbfvy8vOOAdZU6Tijrq9iatpxbs+mbded5rDdNn2TtVRlxLQhaXfglcDZTZq9E/gK8OA4+lZxEvBBSfdKuo+iivhfVulY6coiYjLVJgXWZpLXpAxJTDXFPItKf1PPl7Ss7v3SslRRvdOBv6VBVQxJuwHHAi9j6zGEpn2rsv1T4HmStgdk+5GqfZtNyntCiw99qNnxiFa2nkmuLMQU09Ua2w3XyJb0KuBB28slHdqg2enA+2wPS5tv5Vbs21SjWn+1z7HdstZfq0l5pkiuewBry9c7A/cCe44n6IhGRiaPLPEaM8ghwNGSjgLmAjtKusD28XVtFgFfLH+BzweOkjRE8YBRq76tzCt/jvvKpNmkvD1h0yS8y8vZ1rWCVIeP9wMjqtpl3pbjGkkeMV3Z/gBFdVfKq4NTRv6yr/3OLducB3zN9leBr7bqW8HvlD9/aLtlhdnRVLkZ99xaogCwfSXFXIuIjtplXi8Ltu/btM3t76Wv2v3kiHHpEWzTp5bbeEk6SdJJkxhyI0eVK55+YLwnqDLAvUbSh4ELKG5LHQ/8erwfGDFZRl55ZDZ5TAe2rwWuLV8vadDmza36jtE3KB6R3U7SOoohhdowg223fBy3yp9lxwELKCbkfRV4UrkvYkpZsH0fu+40Z9OWq46Igu332t4J+LrtHW3vUP+zyjlaXlmUTz2d3KpdxFRTq2O1bv3GTAaMAGwfI+npwF62v1XWhuqr8ghty2Qh6XeBU4CF9e1tv2z8IUd0zo5ze+jr3Vx6ZGjYSR5RSY/Etv0z5wpV0l8AJwJPoBj03h1YAhzWqm+VMYsvlyc7m6LoVMS0U1+ChH4lecRs9XbgYOAmANs/kfSkKh2rJIsh22dNILjoggMPPLDbIUxpoyWPoeHisdzhjc5s8pipNth+vDYZT1IfxUB3S1WSxX9L+muKAe4NtZ2ZwT21nX766d0OYVqZ1y+oSyDr1m9+neQRM8h1kj4IbCvpCOCvgf+u0rFKsjih/Pneun0GnjGmECOmkWalSCB1rGYLqXJtqOni/cDbgNsoCgheQcXihFWehkpZj5j1kjxiJrC9UdJXga/aXj2Wvs0KCb7M9rclvbbBh14ytjAjZo6t61il+GFMXSoGKU4F3kExEU+ShoF/s/0PVc7R7MriJcC3gVePcsxAkkVEqX42+epHNz9ZleQRU8RiimKGz7V9D4CkZwBnSXq37X9tdYJmhQRPLX++ZXJijZgdapMBAQYGzWMbhpM0pqkexNyZMWbxJuAI25tWxbN9t6TjgauA8SeLGkk/BW4EbgCut/3D8ccbMbsUa5NvmTweHhjsYkQxS/XXJ4oa26vLAoMtVXkaal+KeuovAj4paR/gFtvHjinUiCiSx05zNr1P8ogOeXycxzapkiyGgcHy50bgV4xYHzYixqeWPAYGNz9ZleQRbXBAWW12JFEsqNRSlWSxjuKZ3E8Bn7Od8uQRk2yLGeXzUopkqpCgv2f6j1nY7m3dqrkqyeI44IUUM/3+XNJ3KcYu/meiHx4RW0sdq5lH0lzgemAbit+7F9ceIqprcwzwjxR3cIaAxba/U6VvJ1SZlHcZcFk5VvEKikew/hbYtr2hRQQ0rmO1YWhjnrKaPjYAL7P9aDmg/B1JV9q+sa7N/1AsYW1J+wNfAvap2LftqjwN9RXgQOAu4DsUj2Dd1N6wIqKRzXWseli3fnOySPKYumwbeLR8219uHtHm0bq329WOV+nbCVVuQ30cWGE79QwippgtZ5L3sHZg8/+mmVE+caLymMV8Scvq3i+1vXSLc0m9wHLgmcBnbG/1R7ekY4F/pliR9JVj6dtuVf4pLATmAUj6sKRLJD27rVFFxLjsMq9307Zg+z7m9vdu2qKt1theVLctHdnA9rDtAykWHDpY0n6jtLnU9j7AayjGLyr3bbcqyeLvbD8i6YXAHwLnA1nfImIaqE8etXXJa1t0h+3fANcCRzZpcz3wO5Lmj7Vvu1T5L6Z2XftK4KxywHtOk/YRMUUt2L5v05bk0TmSFkjauXy9LXA4cOeINs8sC/5R3r2ZA/y6St9OqDJm8QtJn6UI8BOStqFakmlI0h8DHwGeBRxse1nzHhHRDvV1rKAogphxjs0ksU3fpCTSXYHzy7GHHuBLtr8m6SQA20uAPwLeJGkQ+C3wp+WTUaP2nYygxqJKsvgTikueT9r+TRn4e1v0aeV24LXAZyd4noiYRCOLIGY2+eSwfStw0Cj7l9S9/gTwiap9O61KstgV+LrtDZIOBfYHvjCRD7W9EoqsHRFTU30dq3XrN2Yy4CxX5frqK8CwpGcC5wB7Av/Z1qgiYkrZcW4PO83r37Tl6arZp8qVxUbbQ+WKeafb/jdJP2jVSdK3gKeMcuhD5SB5JZJOBE4E2GOPPap2i4hJVj+TfF5/LwODm//W3DC4cUYuLTuGeRYzXpVkMSjpOIqZ27VV81rWP7d9+EQCqzvPUmApwKJFizo+azEiRjcyeaxbv/n98EbPyOQxm1VJFm8BTgI+ZvseSXsCF7Q3rIiYbkauS16fPFKKZPpreX1Vrox3CnBbOWtwle2PT+RDJR0raRXwfODrkr45kfNFxNSz49yeTduC7fvYbpvNM8ozr2P6qVJI8FCKWds/o7iF9zRJJ5QzDMfF9qXApePtHxHTz8grj+lQx6pHYm5vBvOh2m2ofwFebvtHAJJ+F7gIeE47A4uImW2XeVv+Eq4lj4x1TE1VkkV/LVEA2P5x1QW+IyKqqiWPgcEeHttQd9UxBa84ZqMqyWK5pHOA/yjfv4GiVG5ExKSb1y/m9W85kzzJo/uqJIuTgLcD76IYs7ge+Pd2BhURUTMyeXR6NnlvTypNQItkIakHWG57P+BTnQkpIqKx4gmrzYWvU4qkM5omC9sbJd0iaQ/b93YqqIiIqpI8OqNqIcE7JP0f8Fhtp+2j2xZVRMQ4jUweMTmqJIuPtj2KiIgpSMqYRU3DaZTlqk2H2L6ufgMMrOpciBER05ukp0m6RtJKSXdIOnmUNm+QdGu5fVfSAVX7dkKzOfenA4+Msn+gPBYREdUMAe+x/SzgecDbJe07os09wEts7w/8I2UB1Yp9265ZslhYrtC0hXIJ1IVtiygiYoax/YDtFeXrR4CVwG4j2nzX9try7Y3A7lX7dkKzMYu5TY5tO9mBRERMNUL09VYas5gvaVnd+6Xl8gpbn1NaSLFM6k1Nzvc24Mpx9m2LZsni+5L+wvbn6ndKehuZwR0RUW+N7UWtGknanmL10cW21zVo81KKZPHCsfZtp2bJYjFwqaT68h6LgDnAsW2OKyJiRilr6n0FuND2JQ3a7A+cDbzC9q/H0rfdGiYL278CXlBmuf3K3V+3/e2ORBYRMUNIEnAOsNL2qNUwJO0BXAK80faPx9K3E1rOs7B9DXBNB2KJiJipDgHeSLGI3M3lvg8CewDYXgL8PfBE4N+L/MBQeWtr1L62r+hY9FSblBcRMTtN0qQ8298pzta0zZ8Dfz6evp2QtQ0jIqKlJIuIiGgpySIiIlrKmEVERAMC+nvzNzXkyiIiIipIsoiIiJaSLCIioqWMWURENJDFjzbLlUVERLSUZBERES0lWUREREsZs4iIaEgZsyjlyiIiIlpKsoiIiJaSLCIioqUki4iIBiTo71XLrdq5dK6kByXd3uD4PpK+J2mDpFPG0rcTkiwiIjrjPODIJscfAt4FfHIcfdsuySIiogNsX0+REBodf9D294HBsfbthK4kC0mnSbpT0q2SLpW0czfiiIiIarp1ZXE1sJ/t/YEfAx/oUhwREQ2JojZUqw2YL2lZ3XZil0OfdF2ZlGf7qrq3NwKv60YcERGTZI3tRd0Oop2mwpjFW4ErGx2UdGItW69evbqDYUVERE3briwkfQt4yiiHPmT7srLNh4Ah4MJG57G9FFgKsGjRIrch1IiItpN0EXAoxS2rVcCpQD+A7SWSngIsA3YENkpaDOxre91ofW2f08n425YsbB/e7LikE4BXAYfZThKIiClHgr5JWoPb9nEtjv8S2H08fTuhK2MWko4E3ge8xPZAN2KIiIjqujVmcSawA3C1pJslLelSHBERUUG3noZ6Zjc+NyIixifrWURENCBEX9azAKbGo7MRETHFJVlERERLSRYREdFSxiwiIhoRWYO7lCuLiIhoKckiIiJaSrKIiIiWMmYREdGAgL6Ka2zPdLmyiIiIlpIsIiKipSSLiIhoKWMWEREN9Ajm9WfMAnJlERHREZKOlPQjSXdJev8oxyXpjPL4rZKeXbVvJyRZRES0maRe4DPAK4B9geMk7Tui2SuAvcrtROCsMfRtuySLiIj2Oxi4y/bdth8HvggcM6LNMcAXXLgR2FnSrhX7tt20GrNYvnz5Gkk/H2f3+cCayYxnGpiN3xlm5/fOd97a0yf6AcuXL/+mpPkVms6VtKzu/VLbS+ve7wbcV/d+FfAHI84xWpvdKvZtu2mVLGwvGG9fSctsL5rMeKa62fidYXZ+73zn9rB95CSdarRRcldsU6Vv202rZBERMU2tAp5W93534P6KbeZU6Nt2GbOIiGi/7wN7SdpT0hzg9cDlI9pcDrypfCrqecDDth+o2LftZtOVxdLWTWac2fidYXZ+73znKcz2kKR3AN8EeoFzbd8h6aTy+BLgCuAo4C5gAHhLs76d/g6yO37rKyIippnchoqIiJaSLCIioqVZlSwknSbpznIq/aWSdu52TO0yFcoDdJKkp0m6RtJKSXdIOrnbMXWKpF5JP5D0tW7H0imSdpZ0cfn/80pJz+92TDPdrEoWwNXAfrb3B34MfKDL8bTFVCkP0GFDwHtsPwt4HvD2WfCda04GVnY7iA77NPAN2/sABzD7vn/HzapkYfsq20Pl2xspnleeiaZEeYBOsv2A7RXl60cofnns1t2o2k/S7sArgbO7HUunSNoReDFwDoDtx23/pqtBzQKzKlmM8Fbgym4H0SaNygbMCpIWAgcBN3U5lE44HfhbYGOX4+ikZwCrgc+Xt9/OlrRdt4Oa6WZcspD0LUm3j7IdU9fmQxS3LS7sXqRtNSXKA3SDpO2BrwCLba/rdjztJOlVwIO2l3c7lg7rA54NnGX7IOAxYMaPy3XbjJuUZ/vwZsclnQC8CjjMM3eSSZXSAjOOpH6KRHGh7Uu6HU8HHAIcLekoYC6wo6QLbB/f5bjabRWwynbtyvFikizabsZdWTQj6UjgfcDRtge6HU8bTYnyAJ0kSRT3sFfa/lS34+kE2x+wvbvthRT/jr89CxIFtn8J3Cdp73LXYcAPuxjSrDDjrixaOBPYBri6+N3CjbZP6m5Ik2+qlAfosEOANwK3Sbq53PdB21d0L6Roo3cCF5Z/DN1NWRoj2iflPiIioqVZdRsqIiLGJ8kiIiJaSrKIiIiWkiwiIqKlJIuIiGgpySIiIlpKspjBJH1E0ild/PzvjrH9oVXKbEu6VtKi8vUVzUrNS1osad5Y4pgsZZw/knR0hbbHSfqQpDdLWl3WPPqJpG9KekFdu9Mk/bKb/15jdkqyiLax/YLWrSb8GUe1qDi6GOhKsii9wXaV2fNHAt8oX/+X7YNs7wV8HLhE0rMAbL8XWNKeUCMaS7KYYcq/Tn8k6VvA3nX7D5R0Y93CT7tIepKk5eXxAyRZ0h7l+59KmifpPElnSPqupLslva48/u+1v5jL851bvn6bpH8qXz9a/jy0/Cu7tljNhWV5jtoiTXdK+g7w2gbfaVtJXyxj/y9g27pjP5M0X9J2kr4u6ZaycOSfSnoX8FTgGknXlO3PkrSsXCDpoyPO81FJKyTdJmmfcv/2kj5f7rtV0h+V+18u6Xtl+y+XBQyb/Xvpk/R9SYeW7/9Z0sfK1wIOBFaM7Gf7GmApcGKz80e0W5LFDCLpORQ1gg6i+MX73LrDXwDeVy78dBtwqu0Hgbkq1gd4EbAMeJGkp1NUM63Vz9oVeCFFAcaPl/uuL/tAUf68ttDQC4EbRgnvIIq/8velKDF9iKS5wOeAV5fnekqDr/ZXwEAZ+8eA54zS5kjgftsH2N6PYmGcMygKKL7U9kvLdh+yvQjYH3iJpP3rzrHG9rOBs4DabZ6/Ax62/fvl539b0nzgw8DhZftlwN80iB0oSrAAbwbOknREGW8tWR0E3NKksOUKYJ9m549otySLmeVFwKW2B8ry3JcDSNoJ2Nn2dWW78ykWjwH4LkVdpRcD/6/8+SK2/IX/Vdsbbf8QeHK57waKxLIvRRG3X0naFXh+ec6R/s/2KtsbgZuBhRS/AO+x/ZPyF+UFDb7Xi2vHbN8K3DpKm9uAwyV9QtKLbD/c4Fx/ImkF8APg99ic5ABqlWqXl/EBHE6x6iDl56+lWIlvX+B/yzpUJwBPb/B5m5T1uf4D+G/greXCVFAkjmZrq4xWcj6io2ZbIcHZYKzFvm6gSA5PBy6jqMproH6geUPdawHY/oWkXSh+0V0PPAH4E+DRcqW6kerPMczm//aqxtu0ne0fl1dWRwH/LOkq2/9Q30bSnhRXDM+1vVbSeRSlvUfGWB+fRvlsAVfbPq5i7PV+H/gNm5MuwMuBP2rS5yCybGh0Wa4sZpbrgWPLe/w7UNzeofwre62k2m2jNwLX1fU5HvhJ+Vf/QxS/cP+3wud9j+LW0vUUSecURr8F1cidwJ6Sfqd83+iX7/XAGwAk7UdxC2kLkp5KcavqAuCTFIvjADwC7FC+3pFioZyHJT2ZYo3yVq4C3lH3ObtQLMl7iKRnlvvmSfrdVieS9FrgiRRXSmdI2rm86uuz/esGfV5CMV7xuQqxRrRNrixmENsrygHgm4Gfs+Uv7hOAJSoeI91U0tn2z8qx5uvLdt8Bdi9vt7RyA/By23dJ+jnF1UXlZGF7vaQTga9LWlN+9n6jND2LYgnNW8vv9n+jtPl94DRJG4FBinEOKAaHr5T0gO2XSvoBcAfFP4MqCfGfgM9Iup3iiuOjti+R9GbgIknblO0+DPy40UnKcY6PUyy6dZ+kM4FPU9yS+taI5n8q6YUUT3HdA/yR7VxZRFelRHlEm0i6FjjF9rImbc4GzrZ94xjO+xGK232fnHCQERXlNlRE+zwEnKcmk/Js//kYE8VpFLcNH5uE+CIqy5VFRES0lCuLiIhoKckiIiJaSrKIiIiWkiwiIqKl/w8vCKqHYoOLjwAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import WakeDeficitModel\n",
+ "from numpy import newaxis as na\n",
+ "class MyDeficitModel(WakeDeficitModel):\n",
+ " args4deficit = ['WS_ilk', 'dw_ijlk', 'cw_ijlk']\n",
+ "\n",
+ " def calc_deficit(self, WS_ilk, dw_ijlk, cw_ijlk,**_):\n",
+ " # 10% deficit in downstream triangle\n",
+ " ws_10pct_ijlk = 0.1*WS_ilk[:,na]\n",
+ " triangle_ijlk = ((.2*dw_ijlk) >cw_ijlk)\n",
+ " return ws_10pct_ijlk *triangle_ijlk\n",
+ "\n",
+ "plot_wake_deficit_map(MyDeficitModel())\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Superposition models\n",
+ "The super position models calculates the effective wind speed given the local wind speed and deficits (typically from multiple sources)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### LinearSum"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.contour.QuadContourSet at 0x2b6e47be2b0>"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "linear_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=LinearSum())\n",
+ "plt.figure(figsize=(10,4))\n",
+ "linear_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### SquaredSum"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.contour.QuadContourSet at 0x2b6e4a7d550>"
+ ]
+ },
+ "execution_count": 23,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.superposition_models import SquaredSum\n",
+ "squared_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
+ "plt.figure(figsize=(10,4))\n",
+ "squared_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### MaxSum"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.contour.QuadContourSet at 0x2b6e46457f0>"
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.superposition_models import MaxSum\n",
+ "max_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=MaxSum())\n",
+ "plt.figure(figsize=(10,4))\n",
+ "max_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Blockage deficit models\n",
+ "\n",
+ "The blockage deficit models compute the blockage effects caused by a single wind turbine. Their structure are quite similar to the [wake deficit models](#Wake-deficit-models). They model upstream blockage effects (wind speed reduction) and in addition, some models also models downstream speed-up effects."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### SelfSimilarityDeficit\n",
+ "Simple inductionmodel model, described in [N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016](https://onlinelibrary.wiley.com/doi/full/10.1002/we.2137)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import SelfSimilarityDeficit\n",
+ "plot_blockage_deficit_map(SelfSimilarityDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### SelfSimilarityDeficit2020\n",
+ "\n",
+ "This is an updated version of [N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016](https://onlinelibrary.wiley.com/doi/full/10.1002/we.2137). The new features are found in the radial and axial functions:\n",
+ "\n",
+ "1. Radially Eq. (13) is replaced by a linear fit, which ensures the induction half width, `r12`, to continue to diminish approaching the rotor. This avoids unphysically large lateral induction tails, which could negatively influence wind farm simulations.\n",
+ "2. The value of gamma in Eq. (8) is revisited. Now gamma is a function of CT and axial coordinate to force the axial induction to match the simulated results more closely. The fit is valid over a larger range of thrust coefficients and the results of the constantly loaded rotor are excluded in the fit."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import SelfSimilarityDeficit2020\n",
+ "plot_blockage_deficit_map(SelfSimilarityDeficit2020())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### FugaDeficit\n",
+ "\n",
+ "The FugaDeficit model calculates the wake deficit based on a set op look-up tables computed by a linearized RANS solver. The look-up tables be created in advance using the [Fuga GUI](https://orbit.dtu.dk/en/publications/developments-of-the-offshore-wind-turbine-wake-model-fuga)\n",
+ "\n",
+ "The fugaDeficit models both near wake, far wake and blockage deficit.\n",
+ "\n",
+ "Note, the present look-up table generator introduces some unphysical wriggles in the blockage deficit/speed-up"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import FugaDeficit\n",
+ "plot_blockage_deficit_map(FugaDeficit())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### VortexCylinder\n",
+ "\n",
+ "Induced velocity from a semi-infinite cylinder of tangential vorticity, extending along the z axis.\n",
+ "\n",
+ "This model is an adapted version of the one published by Emmanuel Branlard at https://github.com/ebranlard/wiz/blob/master/wiz/VortexCylinder.py\n",
+ "\n",
+ "References:\n",
+ "\n",
+ "- E. Branlard, M. Gaunaa, Cylindrical vortex wake model: right cylinder, Wind Energy, 2014, https://onlinelibrary.wiley.com/doi/full/10.1002/we.1800\n",
+ "- E. Branlard, Wind Turbine Aerodynamics and Vorticity Based Method, Springer, 2017\n",
+ "- E. Branlard, A. Meyer Forsting, Using a cylindrical vortex model to assess the induction zone in front of aligned and yawed rotors, in Proceedings of EWEA Offshore Conference, 2015, https://orbit.dtu.dk/en/publications/using-a-cylindrical-vortex-model-to-assess-the-induction-zone-inf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import VortexCylinder\n",
+ "plot_blockage_deficit_map(VortexCylinder())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### VortexDipole\n",
+ "\n",
+ "The vorticity originating from a wind turbine can be represented by a vortex dipole line (see Appendix B in [2]). The induction estimated by such a representation is very similar to the results given by the more complex vortex cylinder model in the far-field r/R > 6 [1,2]. The implementation follows the relationships given in [1,2]. This model is an adapted version of the one published by Emmanuel Branlard: https://github.com/ebranlard/wiz/blob/master/wiz/VortexDoublet.py\n",
+ "\n",
+ "References:\n",
+ "- [1] Emmanuel Branlard et al 2020 J. Phys.: Conf. Ser. 1618 062036\n",
+ "- [2] Branlard, E, Meyer Forsting, AR. Wind Energy. 2020; 23: 2068– 2086. https://doi.org/10.1002/we.2546"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import VortexDipole\n",
+ "plot_blockage_deficit_map(VortexDipole())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### RankineHalfBody\n",
+ "\n",
+ "A simple induction model using a Rankine Half Body to represent the induction introduced by a wind turbine. The source strength is determined enforcing 1D momentum balance at the rotor disc.\n",
+ "\n",
+ "References:\n",
+ "\n",
+ "- B Gribben, G Hawkes - A potential flow model for wind turbine induction and wind farm blockage - Technical Paper, Frazer-Nash Consultancy, 2019"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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1in8WZR7R8YPXdftFWUY8YFQrmwPG1OTsx8x+lS2DSsaMI3U4r2cbbm45FLjbzO4xsyngm8BxKeVPAL7Rw/p8D6hK2hs4D9gL+HqWHbNc/D8J/FrSd8P3Lwc+1k4tR0mrWUZawKgPFlnPE4jKb47/xYJ477vfQbEgzjrzM+HGIiIKvA2alOYtbHz4Rp3WdVlFakaRtdO725mE91G4LhBiLNsd4Yvrmo2WhktVR3YB7ou9Xw48teE5pfnA0cDJsc0GXCbJgC/WHbsdNTOrSHox8Bkz+1yzvoxIlo7wr0q6jmDtDAEviadUrrl2AkZSmWQ1oDAz9Pbmm25g5t6a2AV0pLr0nBscK83skJTPG/3XS/qP/ULgV3VNU4eFS2w/Brhc0h1mdlW7lQWmJZ0AnBieD6CUZceszUx3AKui8pJ2N7M/t1rLQdZK01Q3+jLSzl/fyd3sfJvbXGszr82C9ljnXAe61KdBkFnsFnu/K8HQ10aOp65pysxWhM8PSrqIoLmrk6DxOoLbKT5mZn+UtBfwtSw7Ng0akv4F+ADwAMGd4FErx/5tV3cOyZJlZAkYleqW+7UyXbpzLlfXAvuEF+e/EASGf6gvJGlr4DnAq2LbFgAFM1sbvj4K+HA7lZC0FPgxcIWZvTXabmZ/BE7PcowsmcbbgCeY2cPtVHIuaeXO8KRhttFzfbBolHVs3iaKBTFeKjA5XfWg4VyXiO5kGmH/wcnApQQ3z51vZrdKelP4+Tlh0RcDl9XNKL4jcFHY3DwGfN3MftJmVc4n6C95h6Qpgpu1f2JmN2Y9QKZpRIBH26vf6Gml+SnLnFLxEVDRczxgxLdPhiOOpmuzm9JKhcLMVAdR4HDODRYzuwS4pG7bOXXvvwx8uW7bPcABXarDNcA1wAclbU+QtbxT0v7A9QQB5Ntpx8gSNO4Bfi7pR8Cm2Mk/1XbNB0w3htq2k2VkCRj1wSIKRPHAUSoY07UaW4X9WMWCqBnIhmvKFecG0ahm7mHr0TfCB5IOJshCUmUJGn8OH+Xw4XogHlTqA0YULKZrNTZVq0w3CFClcDqR7SbK4RBBw8dKOecaCWf5eA2wJ7E4EO/nSJJlyO2HOqjbSOlG01RSlhG9bhYw1leqbJyqsakuOxovFpieiDrIx6nVYER/IDnXN5JaX0J5OFxC0Ex1M5tv9soky+ipHYB/Bf4GmIi2m9nftlbHuStL01XDGwJjAWPddIWpWo3VGytMVYzVk1WmKrP/rheOF9lzu2BbzTzTcK5T3eoIH0ATZvaOdnbM0jx1AfAt4AUE43pPBB5q52SjqtV5phplGdCgWSoWMB6drLCpWmP1xirrNlVZvWGaDZsqszq9t5pXYqpqsEMQNIZsFnnnXP/8t6R/BH7I7L7qR5J3CWQJGtub2XmS3mZmvwB+IekX7dd1sPRivqlWVuJrFHBmmqXCJqmpWtAc9eC6CmsmKzyydhNrJ6fZMFlhw4ZpKmHGMTZW4JF1m5iqLGKqapTHPGo414luTVg4gKYIJkc8jc13phvwuGY7Zgka0+Hz/ZKeT3AX465tVHJOSspC0voyIAg8UR/G6o0VVm+szgSMR9Zt4tE1m3j44Q2sX7OBaqXK9NQ0pXKJh7fbiulKjclKlfml0VlxzDnXVe8A9m5n1twsQeOj4V2K7wQ+BywCTmn1RMOu0xUDG9393Ug8y5iuGRunakxVjHWbqqzdOM0j6zbx8CMbWfnQOlY9uIrpNatgcl2wL7B2eZn1ax4Hm6psPeGZhnOdkJhZ4GzE3ApsaGfHLEFjlZk9SnCD3xEAkg5r52SjqJNgUr+YUn2WETVLrZ4M+jCiDGPlQ+tYuWIltTUrZ63IB0BlitV330Fh/RSPWegjpJ1zDVWBGyRdyew+jc6H3BJkF0/OsM21KT6vVPymvSjLmKrU2LCpwobJCo8+OsmqB1dR27Bmy4ARs3HNGtZuO5H4uXMumxHt0/h++GhZYtCQ9HTgGcAOkuJDsxYRzJ3iGphuMLFgvaTts+78DstsmK6xesM0ayenWbNmE+vWbJzVJJWm1v0+fufcCDCzr7S7b9pdK2VgIUFg2Sr2WAO8rN0TumyipqmparAK33Slxvr1U6xfsz41w3DOdY8IJgNt9hgW4Sy3HZVJzDRiw2u/bGZ/Cg9WABaa2ZpWK+tmS1rqNerPAGaapqYrNdZvmGbjhikm1/gfvXOubS+SlLYGuAj7rpNk6dP4eDh9bxW4Dtha0qfCRdBdC5JGTqV1pk9WakxOV6lUakxNTgXNUp5pONcXweipkZpG5N0Zylyd9mGWoLGvma2R9EqC+UreQxA8Og4ako4GPkvQR3KumWVaBGTYpPVtpHWCb5gO3k9Xa1QqNaqVqgcM54ZUs+udggUzPgssIRgO+1ozuz7Lvll10pcRyRJCS5JKwIuAH5jZNMlr22YmqQh8HjgG2Bc4QdK+nR531ExOhU1VU5Wca+Lc3BPNPdVpn0bG690xwD7h4yTg7Bb27ZssQeOLwL3AAuAqSXsQdIZ36lDgbjO7x8ymgG8Cx3XhuEOv0dTnANNT0w23O+cGXpbr3XHAVy1wDbCNpJ0y7ts3TYOGmZ1pZruY2ZLwy/yJJh0lGe1CsCpgZHm4bRZJJ0laJmnZypU+T6Jzrn8kmBhr/gAWR9ep8HFS3aGyXO+SymS6Vrb2vfTyLNsaSbtP41Vm9rW6ezTiOl25r1FOt8VPbDNbCiwFePLBh8zpeTFK5RJpwx6cc7lZaWaHpHye5XqXVCbTtbJF7wW+k2HbFtI6wheEz1u1WalmlgO7xd7vSjAZ4pxXirWRTpSD+yjL5SxjFpxzXVWrwvpV3ThSlutdUplyhn0zkXQMQUf7LpLOjH20CMjUcZp2n8YXw+derdx3LbCPpL2AvwDHA//Qo3PlqlhQwxFUUQda9FmpUGC6unl9jPmloPWwVCwwNlagOFaEsbKPoHJu+GS53l0MnCzpm8BTgUfN7H5JD2XYN6sVwDLgWIJRsJG1wNuzHCCteerMpM8g28RWTfavSDoZuJRgGNn5ZnZrJ8ccdKVioeG9Go2CyrxygbWbqkyMFZgoFRkbK1CeKMPEQr9Xw7l+sVpX/q8lXe/Ce+Aws3MIbmlYAtxNMOT2dWn7tlmPG4EbJV1gZm0NyUxr84ii0GEEw7y+Fb5/ObMjVNvM7BKCP6g5pz5QFAuCajAN83ityPpKlfKYKI8VKI0VKJeLzJtfpjR/AdMZ5p1yzg2WRte7MFhErw14S9Z92yHp22b2CuB3khr1Ie/f7BhpzVNfCU/yWuCI8P4MJJ0DXNZupV025UKB8WKBcjFY2H7+xBgLFpRZsGgBq9d4E5VzfWFArMl4BLwtfH5BuwfIcp/GzszuDF8YbnMNxBdsSbrpJ2n7RDHo9C4VCjOd4fNLBbaZX2KriRITE2MsWDSf0qJtg74N55xrgZndH74sAA+Y2Z/C2ygepPEorS1kGZJzOkEqc2X4/jnAB1usq8so3hk+r1xgU7VGeazA/PExtlk0zuRkhckNi3h4w3pYl7wGfHnBQrYa9xFXznXGsOpIzsbwHYKlLyLVcNtTmu3Y9KpiZv8l6ccEvfkAp5rZ/7VTy1GUNDKqlf1nifVrTNeM8WKBbSaKTFVKbNhUYXq7eeGUIjux6sGJhqv3Tey8J6UV45RHa6I151z3jIV3lwNgZlOSMjVfZPopGgaJH7RZuZHQjeBQrdmsEVSNjrm5icooFTSTbSwcL7LdVuMATC+uUS6PURwrsnHRAqanpqlWqhTHiixYtIA99tqeB24dw2OGcx0yg+pI9h8+JOlYM7sYQNJxwMosO3r7RU7qA8ZYse6ejVi2sc28MaYqxqKJMSanquy4zTxKYwUmJsaYnFw4M5lhuTzG9tvNY++dFnH1WHGoFodxzvXVm4ALJJ1F0JdxH/CaLDvO+aCRdO9EZ8fUzLKvzTKU+hv8igUxweZsY2FpjHXTFbYaj1bYHWfNZJHSWIHpheOsndw8ieFWEyV23nYej99+gt8URcZ+LedcIhu10VMAmNkfgKdJWgjIzNZm3Tft5r7tmpw0uRd2jsnadFXfRJWUbQAzfRsQjKTaOpwVrTwmykWxaGKMqUqNyUrQZDUxVmDheJEdF5bYc+v5FCQ80XDOxSXNKRgs5QFm1nROwWY390WTZe0OrApfbwP8GdirrVq7LdRnG7C5bwNqLKQ0s0DTVK3GeDHo55iqbC5fHhPbzBtju/Ey202UKcgjhnMdM4PRGj01P3xue07BtJv79oKZm/kuDu9IjCa8el67JxxmrXSGJzVRpWUb9X0QUTMV1IACC0tjbKpWKReCHu6pMJCUw/s6xotFth4vMX+8iBRM6+ycczGPD59vM7OmM9o2kmV8zVOigAFgZj8muFfDdVE8YIwVN68INlEsBjf7FcX8UpGFpRILS2MsLIVZxXg5fF9i6/ESi8ZLlMcKM+mmc64DZjA12fwxPJaEK7G+t90DZOkIXynp/cDXCJqrXgU83O4JB1E3OsOzdHg3yzbizVTx/o0JikwUi0xWq0CN0kzTVVj/QoGJYjBaarxUmDmOBw7nXJ2fEAytXSBpDUGXQ9QNYWa2qNkBsgSNE4APABeF768Kt81J7TZRtXLc6PWsjnE2B49G+xYLmslQJkpF7wR3rhvMsBGa583M3g28W9IPzKytJWOz3BH+CJsnuXIpOsk26ss0ChyNjh9lFWPFYEbciZLfn+Fc11gNpjflXYuuM7PjJO0B7GNmV0iaR3CXeNOht037NCT9laSlki6T9LPo0Y2KzwWlYvMLeCm8dTu62EeZQzyDiB7jpcKsR7StPFaYKe+cGy6StpN0uaS7wudtG5R5gqQbYo81kk4JP/ugpL/EPlvS5Hz/CHwX+GK4aVfg+1nqmqV56jvAOcC5BJNajaRW+jXSMop2so34+eP9GvV9HWnHLBY0E3xKRfnIKee6wQym+9I8dSrwUzM7XdKp4fv3zK6K3QkcCCCpSLCK30WxIp82s09kPN9bgEOB34THvkvSY7LsmCVoVMzs7IwVcQ3U9200Cxzx7VkyhyhgxLOTJ+1/4OZ916/aPKlhtTp71s60eXWKW85fpmLKP5kG/S1b6OaU7gu2+DHm3LA6Djg8fP0V4OfUBY06zwX+EE5r3o5N4SSFAEgaI+gQbypL0PgfSW8miGgzjXtz/Y7wVrONVgIHMCvriCTdzxEPGFFz2MfP+BQTpdhFPAoW1anN0yJEwaPRkMHyBLG/7rDSY5v/VTUKEFmCTHVjrHyGIBNpFGzWr8q+fzMegFwjVoNNG5uXg8WSlsXeLzWzpS2cacdorYtwXfBmv/qPB75Rt+1kSa8hWAP8nWaW9h/kF5LeB8yTdCTwZuB/slQ0S9A4MXx+d2ybAY/LcoJu6nWLSy/moUrT6Ma+RsEjXj4u3heS9NnmnYszY+sgDBzFsSBwlCeaVLTun0m7AcO50bXSzA5JKyDpCuCxDT46rZUThVOYH8vsey3OBj5C8F/8I8AngdenHOZU4A3AzcA/ESwle26W82cZPeXThSToNNtoVK7+/RYX/7p964+fqTO8WGZW4IjEm62SLvgZA0ZTrWQZzuWli0NuzSxxJg1JD0jaKcwydiJYSS/JMcD1ZvZA7NgzryV9Cfhhk7rUJH0f+L6ZPZT1O0D6hIV/a2Y/k/SShJNe2MqJhkU3s41OAkckaYht/fsso7Qg+PVv1crmwAGbm6va6a9ICBgd933E+dK2bvRdTNCqc3r4nLZ+0QnUNU1FASd8+2LglkY7KujE+ABwMkHjjSRVgc+Z2YezVDQt03gO8DPghQ0+M2Akg0ar2lmcKSlwQPMg0eizKGA0zTKKxdnTPBfLQR9HcXbfx6zyadoJGIPI+zNckv6Nnjod+LakNxBMCPtyAEk7A+ea2ZLw/XzgSIImpbj/lHQgwbX53gafR04BDiOYHuqP4TEfB5wt6e1m9ulmFU2bsPAD4fPrmh2knzpdQa/fkuobXeiTggdsGUDqP48fJ769YZPWWHlmBNVMtgGbA8fMCTJkASnNUU0DhmcZzm3BzB4mGBFVv30FsCT2fgOwfYNyr854qtcAR5rZzCp9ZnaPpFcBlwHtB42IpD8A1wBXA1eZ2W0ZKze0Wm2iauXejC3PlTzVSLO+ifomqUw39oXZxhaBA5ova9mk76LrAcO5vNWqsHF93rXoplI8YETM7KFwIsOmssxyuy/BXYPbA5+QdI+ki5rsM+dkuQEvSamozH0Sjco3OvasbQnNL1tc5Ivl9EeKnjRJeZbhXLel/TLM1A6X5X96FZgOn2vAA6T37PdcP5qoejH8tlm9Wwkc8WPGn9NGW800UcX6NmZlHG3IHCwGNcvw/gyXpn99Gv1yQDi7bT0BTcbeB7L8j19DMJb3U8CXwrY310CWYJbU4d3OuTo7wOzAAbQcPHoaMDzLcK7rzKzjX29Zp0Z/JsEdg2+U9GuCvo2fdnryQddOttHKeuHQXvBIGnabSaxDvH40VZbg0XIz1CAHDM8yXDOjl2l0LMvNfT8AfiDpiQQ3lZwC/Cswr7dVS9evUVS9DBxRWWgePJICQ9NRU00rUDcMly72Twxqk5Rzrm1ZRk99j2BmxbuBXxIM2fpNb6s1/FoNau00N2UJJDMWbLt5rqZ4tgENA0fH2g0Y3izlBokZTE/nXYuBkuUn5ekEt6yP7LTozbTbKd6t/ou0Y0fayjJmHbBLgaOT7KKfAcObppxrS5YrzZ7AfABJ75d0oaQn97RWGfVzwaFOLsrdrmdXjtfoAt3JBb9Y9OYoN3pqNZjc2Pwxh2S5Ev6bma2V9Ezg7wjmevf1NVrUjVX1ko7RcZYx6yTF1gJAt4KFZxnODYUsV5uozeL5wNlhx/jANDwPS7YRaSd4pO1TX6fUY9dfLJtdqOMBJOnRDd6P4QZVNHqq2WMOyXIV/IukLwKvAC6RNJ5xv0SSXi7pVkk1Salz0A+abv2qr18HPO3RU3lfsPM+v3OuJVmugK8ALgWONrPVwHbMXpCpHbcALwGu6vA4QH+zDehyc1AHulaPvC7ceZzXm6ZcKzzT2EKW0VM7AT8ys02SDgf2B77ayUnN7HaAaH3aYdTvVf4anb8t8aG3cfXDcHvNMwznhlKWK8/3gKqkvYHzgL2Ar/e0Vm3od7YB+WUcSeft+M+gXxfyvAKGZxmuVVaDycnmjzkky1WvZmYVguakz5jZ2wmyj1SSrpB0S4PHca1UUNJJkpZJWvbQypZWJeyLUrHQ1+DR83P18oI+VvaA4VwDWft5Jd0r6WZJN0haFtu+naTLJd0VPvfsH3yW5qlpSScQ3AkereLXdN71tPVwW2FmS4GlAAcffEjqXXJ5LtDUj+aqrgWMpCaqSC+aqrw5yg2j/t0RHvXzfjFD2SMarIlxKvBTMztd0qnh+/d0uY5AtkzjdcDTgY+Z2R8l7QV8rReVGXa9yjqyHLfrzXPdygryzC4inmW4AWdmt5vZnR0c4jiCe+gIn1/UcaUSNL3ChSv1vQu4WdJ+wHIzO72Tk0p6saTlBMHoR5Iu7eR4cXn0bdTrZvDoWXNU1gtpdNFv5cLfzj7ODaIo02j2gMVRM3r4OKlXNQIuk3Rd3Tl2NLP7gyrb/cBjenT+TBMWHk4Que4lWKhjN0knmlnbw2XN7CJg5Ff/iy74rTZbtRoo+hYohzEIeJbh+mOlmaXecybpCuCxDT46LbxpOovDzGyFpMcAl0u6o5NrcTuy9Gl8EjgqSp0k/RXwDeDgXlasE3n2bTQyKPd1bKFZ38aw84DhOmQ1wzZt6s6xutDPa2YrwucHw2W3DyW43+0BSTuZ2f2SdqKHq6tmuZqV4m1tZvZ7MnSE520Qmqn6Ya58T+fmOkkLJG0VvQaOIuhAB7gYODF8fSKQNXNpWZagcZ2k8yQdHj6+BFzXqwq5PhvVX+Oj+r1cf2Xv0+hIUj+vpJ0lXRIW2xH4paQbgd8S3HT9k/Cz04EjJd0FHBm+74kszVNvAt4CvJWgT+Mq4Au9qlA3DVozVbd5lpHAA4brlj4NuU3q5w2bo5aEr+8BDkjY/2Hgub2sYyQ1aEgqANeZ2X7Ap/pRoW4b9cDRFaPUt+EBw7meSg0aZlaTdKOk3c3sz/2qVLeNYuDwLMO5PvDlXreQdcLCWyX9FlgfbTSzY3tWK5eqJwFjFLINzzKc67ksQeNDPa9FH4xittF1wxw4PGC4XqjVqK3vzpDbUZEYNMJZbXc0s1/UbX828JdeV6wXRiFw9LxZahgDhwcM5/ombcjtZ4C1DbZvCD8bSsPcFzDMde8ZDxiul8yoTVeaPuaStKCxp5ndVL/RzJYBe/asRn0wjBffvtZ5WC7Ew1JP50ZIWp/GRMpn87pdkX4bpqaqXILcoDdTecBwfWAGNjW3Molm0jKNayX9Y/1GSW9gRO4IH4aMI9c6DuKFecG2g1kv5+aItEzjFOAiSa9kc5A4BCgDL+5xvfomuigPYtYxEEEtukAPQtbhwcL1W82obvT7NOISg4aZPQA8Q9IRwH7h5h+Z2c/6UrM+G7TmqoEIGHF5N1d5wHBuIDS9T8PMrgSu7ENdcjcoWcfABYxIHoHDg4XLk5n3adTJcnPfnJNX1jGwwSKuX81VHiycG0geNBL0O+sYioAR16vg4cHCDRCrGTXPNGYZ0CXlBkexoJ5e0Ht9/J6LRjN1crHvxjGcG2KSzpB0h6SbJF0kaZsGZXaTdKWk2yXdKultsc8+KOkvkm4IH0t6VVfPNDKKX9g7zT6GOkikaXTRr89EPDC4YWJGbarajzNdDrzXzCqS/gN4L/CeujIV4J1mdn24gt91ki43s9vCzz9tZp/odUU9aLQh6aJfH0xGNji0woOEc02Z2WWxt9cAL2tQ5n7g/vD1Wkm3A7sAt9WX7SUPGl3kQcK50VIzmMqWaSyWtCz2fqmZLW3ztK8HvpVWQNKewEHAb2KbT5b0GmAZQUbSk9EqHjScc65zK83skLQCkq4AHtvgo9PM7AdhmdMImqEuSDnOQuB7wClmtibcfDbwEcDC508SBJ+u86DhnHMJzIzp6Vq3jvW8tM8lnQi8AHiumTXsOJVUIggYF5jZhbFjPxAr8yXgh12pdAM+eso553Im6WiCju9jzWxDQhkB5wG3m9mn6j7bKfb2xcAtvaqrZxrOOZfADKYr3ck0mjgLGAcuD2ID15jZmyTtDJxrZkuAw4BXAzdLuiHc731mdgnwn5IOJGieuhf4p15V1IOGc87lzMz2Tti+AlgSvv4l0HC0jZm9une1m82DhnPOJTAzpjb15T6NoeF9Gs455zLzTMM55xL0sU9jaHim4ZxzLjPPNJxzLoEZVCqDszjbIPBMwznnXGaeaTjnXAIzY3LaR0/FeabhnHMus1wyDUlnAC8EpoA/AK8zs9V51MU555IYMN14Gqg5K69M43JgPzPbH/g9wYIjzjnnBlwumUaWBUeccy5vnmlsaRA6wlMXHJF0EnASwG67796vOjnnnAeNBnoWNLq14Ei4+tVSgIMPPsT/9pxzLkc9CxrdWHDEOefyVDNjU80vT3G5dIRnWXDEOefmCkkfkXSTpBskXRauo9Go3NGS7pR0t6RTY9u3k3S5pLvC5217Vde8Rk+dBWxFsODIDZLOyakezjmXKOrTaPbogjPMbH8zO5BgqdZ/ry8gqQh8HjgG2Bc4QdK+4cenAj81s32An4bveyKv0VMNFxxxzrm5yMzWxN4uIIhX9Q4F7jazewAkfRM4DrgtfD48LPcV4OcErTldNwijp5xzbmBVsmUSiyUti71fGg7iyUzSx4DXAI8CRzQosgtwX+z9cuCp4esdzex+ADO7X9JjWjl3KzxoOOdc51aa2SFpBZqNKDWz04DTJL0XOBn4QP0hGuzb9156DxrOOZegarC+2p1FmJqNKI35OvAjtgway4HdYu93BVaErx+QtFOYZewEPNhRZVP4hIXOOZczSfvE3h4L3NGg2LXAPpL2klQGjgcuDj+7GDgxfH0i8INe1dUzDeecS2D07T6N0yU9AagBfwLeBBAOvT3XzJaYWUXSycClQBE438xujfYHvi3pDcCfgZf3qqIeNJxzLmdm9tKE7SuAJbH3lwCXNCj3MPDcnlUwxoOGc84lqBlM+h3hs3ifhnPOucw803DOuQQGTPrUeLN4puGccy4zzzSccy5BFVhX9UwjzjMN55xzmXmm4ZxzCczw9TTqeKbhnHMuM880nHMuQQ3z+zTqeKbhnHMuMw3T8tySHiKYl6Udi4GVXazOMJiL3xnm5vf277ylPcxsh05OIOkn4XmaWWlmR3dyrmExVEGjE5KWNZvvftTMxe8Mc/N7+3d2/eLNU8455zLzoOGccy6zuRQ0Wlqvd0TMxe8Mc/N7+3d2fTFn+jScc851bi5lGs455zrkQcM551xmcypoSDpD0h2SbpJ0kaRt8q5Tr0g6WtKdku6WdGre9ek1SbtJulLS7ZJulfS2vOvUL5KKkn4n6Yd516VfJG0j6bvh/+fbJT097zrNFXMqaACXA/uZ2f7A74H35lyfnpBUBD4PHAPsC5wgad98a9VzFeCdZvbXwNOAt8yB7xx5G3B73pXos88CPzGzJwIHMPe+f27mVNAws8vMrBK+vQbYNc/69NChwN1mdo+ZTQHfBI7LuU49ZWb3m9n14eu1BBeRXfKtVe9J2hV4PnBu3nXpF0mLgGcD5wGY2ZSZrc61UnPInAoadV4P/DjvSvTILsB9sffLmQMX0IikPYGDgN/kXJV++Azwr0At53r00+OAh4D/CpvlzpW0IO9KzRUjFzQkXSHplgaP42JlTiNozrggv5r2lBpsmxNjqyUtBL4HnGJma/KuTy9JegHwoJldl3dd+mwMeDJwtpkdBKwHRr7fblCM3NToZva8tM8lnQi8AHiuje5NKsuB3WLvdwVW5FSXvpFUIggYF5jZhXnXpw8OA46VtASYABZJ+pqZvSrnevXacmC5mUWZ5HfxoNE3I5dppJF0NPAe4Fgz25B3fXroWmAfSXtJKgPHAxfnXKeekiSCNu7bzexTedenH8zsvWa2q5ntSfB3/LM5EDAws/8D7pP0hHDTc4HbcqzSnDJymUYTZwHjwOXBNYZrzOxN+Vap+8ysIulk4FKgCJxvZrfmXK1eOwx4NXCzpBvCbe8zs0vyq5LroX8BLgh/FN0DvC7n+swZPo2Ic865zOZU85RzzrnOeNBwzjmXmQcN55xzmXnQcM45l5kHDeecc5l50HDOOZeZB40RJumDkt6V4/l/3WL5w7NM7y3p55IOCV9fkjbFvaRTJM1vpR7dEtbzTknHZih7gqTTJL1W0kPhnEp3SbpU0jNi5c6Q9H95/r26uc2DhusZM3tG81Idn2NJkxlOTwFyCRqhV5pZlrvxjwZ+Er7+lpkdZGb7AKcDF0r6awAzezdwTm+q6lxzHjRGTPhr9U5JVwBPiG0/UNI1sQWotpX0GEnXhZ8fIMkk7R6+/4Ok+ZK+LOlMSb+WdI+kl4WffyH6BR0e7/zw9RskfTR8vS58Pjz81R0tmnNBOO1HtFjUHZJ+Cbwk4TvNk/TNsO7fAubFPrtX0mJJCyT9SNKN4QSVfy/prcDOwJWSrgzLny1pWbhQ04fqjvMhSddLulnSE8PtCyX9V7jtJkkvDbcfJel/w/LfCSdKTPt7GZN0raTDw/cfl/Sx8LWAA4Hr6/czsyuBpcBJacd3rl88aIwQSQcTzEF0EMEF+Cmxj78KvCdcgOpm4ANm9iAwoWB9gmcBy4BnSdqDYPbUaH6unYBnEkz0eHq47apwHwimXY8WPHomcHWD6h1E8Kt/X4KprQ+TNAF8CXhheKzHJny1fwY2hHX/GHBwgzJHAyvM7AAz249ggZ4zCSZqPMLMjgjLnWZmhwD7A8+RtH/sGCvN7MnA2UDU/PNvwKNm9qTw/D+TtBh4P/C8sPwy4B0JdQeCqV2A1wJnSzoyrG8UtA4CbkyZQPN64Ilpx3euXzxojJZnAReZ2YZwWvCLASRtDWxjZr8Iy32FYBEbgF8TzNv0bOD/hc/PYvaF//tmVjOz24Adw21XEwSYfQkmi3tA0k7A08Nj1vutmS03sxpwA7AnwYXwj2Z2V3jB/FrC93p29JmZ3QTc1KDMzcDzJP2HpGeZ2aMJx3qFpOuB3wF/w+ZgBxDNjHtdWD+A5xGsgkh4/lUEKwPuC/wqnOfqRGCPhPPNCOf/+m/gf4DXhwtkQRBA0tZ2aTTVvXO5mGsTFs4FrU4mdjVBkNgD+AHBLMAGxDukN8VeC8DM/iJpW4IL3lXAdsArgHXhynn14seosvnfXtb6ppYzs9+HmdYS4OOSLjOzD8fLSNqLIIN4ipmtkvRlginF6+sYr58anFvA5WZ2Qsa6xz0JWM3m4AtwFPDSlH0OwpczdQPCM43RchXw4rAPYCuCZh/CX92rJEXNSa8GfhHb51XAXWEW8AjBhfdXGc73vwRNTlcRBJ930bhpKskdwF6SHh++T7oIXwW8EkDSfgRNS7NI2pmgCetrwCcIFukBWAtsFb5eRLBgz6OSdiRYQ72Zy4CTY+fZlmCp4MMk7R1umy/pr5odSNJLgO0JMqczJW0TZoFjZvZwwj7PIejP+FKGujrXc55pjBAzuz7sKL4B+BOzL+AnAucoGH46M5W0md0b9klfFZb7JbBr2AzTzNXAUWZ2t6Q/EWQbmYOGmU1KOgn4kaSV4bn3a1D0bIKlPW8Kv9tvG5R5EnCGpBowTdAPAkEn8o8l3W9mR0j6HXArwZ9BlsD4UeDzkm4hyEA+ZGYXSnot8A1J42G59wO/TzpI2A9yOsHiX/dJOgv4LEFT1RV1xf9e0jMJRn39EXipmXmm4QaCT43uXI9I+jnwLjNbllLmXOBcM7umheN+kKAZ8BMdV9K5FnnzlHO98wjwZaXc3Gdmb2wxYJxB0Jy4vgv1c65lnmk455zLzDMN55xzmXnQcM45l5kHDeecc5l50HDOOZfZ/wfR8p3ALK1rpwAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import RankineHalfBody\n",
+ "plot_blockage_deficit_map(RankineHalfBody())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### HybridInduction\n",
+ "The idea behind this model originates from [2,3], which advocates to combine near-rotor and farfield approximations of a rotor's induced velocities. Whereas in [1,2] the motivation is to reduce the computational effort, here the already very fast self-similar model [1] is combined with the vortex dipole approximation in the far-field, as the self-similar one is optimized for the near-field (r/R > 6, x/R < 1) and misses the acceleration around the wake for x/R > 0. The combination of both allows capturing the redistribution of energy by blockage. Location at which to switch from near-rotor to far-field can be altered though by setting switch_radius.\n",
+ "\n",
+ "References:\n",
+ "1. N. Troldborg, A.R. Meyer Fortsing, Wind Energy, 2016\n",
+ "2. Emmanuel Branlard et al 2020 J. Phys.: Conf. Ser. 1618 062036\n",
+ "3. Branlard, E, Meyer Forsting, AR. Wind Energy. 2020; 23: 2068– 2086. https://doi.org/10.1002/we.2546"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import HybridInduction\n",
+ "plot_blockage_deficit_map(HybridInduction())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Rathmann\n",
+ "\n",
+ "Ole Sten Rathmann (DTU) developed in 2020 an approximation to the vortex cylinder solution (E. Branlard and M. Gaunaa, 2014). In speed it is comparable to the vortex dipole method, whilst giving a flow-field nearly identical to the vortex cylinder model for x/R < -1. Its centreline deficit is identical to the vortex cylinder model, whilst using a radial shape function that depends on the opening of the vortex cylinder seen from a point upstream. To simulate the speed-up downstream the deficit is mirrored in the rotor plane with a sign change."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deficit_models import Rathmann\n",
+ "plot_blockage_deficit_map(Rathmann())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Compare blokage deficit models"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "blockagedeficitModels = [SelfSimilarityDeficit(),\n",
+ " SelfSimilarityDeficit2020(),\n",
+ " FugaDeficit(),\n",
+ " VortexCylinder(),\n",
+ " VortexDipole(),\n",
+ " RankineHalfBody(),\n",
+ " HybridInduction(),\n",
+ " Rathmann()]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Deficit along center line**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b6ea130550>"
+ ]
+ },
+ "execution_count": 34,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=((10,6)))\n",
+ "for deficitModel in blockagedeficitModels:\n",
+ " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(np.linspace(-200,100,300), 0))\n",
+ " plt.plot(X[0], deficit[0], label=deficitModel.__class__.__name__)\n",
+ "plt.title(\"Center line deficit\")\n",
+ "plt.xlabel('x/D')\n",
+ "plt.ylabel('Deficit [m/s]')\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Deficit profile 1 up- and downstream**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "for d in [-1,1]:\n",
+ " plt.figure(figsize=((10,6)))\n",
+ " for deficitModel in blockagedeficitModels:\n",
+ " X, Y, deficit = _map(deficitModel.calc_deficit, xy=(d*D, np.linspace(-200,200,300)))\n",
+ " plt.plot(Y[:,], deficit[:,0], label=deficitModel.__class__.__name__)\n",
+ " plt.title(\"%sD %sstream\"%(abs(d),('down','up')[d<0]))\n",
+ " plt.ylim([-.5,.5])\n",
+ " plt.xlabel('y/D')\n",
+ " plt.ylabel('Deficit [m/s]')\n",
+ " plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Rotor-average models\n",
+ "\n",
+ "In the plots below, it is clearly seen that the wind speed varies over the rotor, and that the the rotor-average wind speed is not well-defined by the wind sped at the rotor center.\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0, 0.5, 'Wind speed [m/s]')"
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x288 with 3 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.superposition_models import SquaredSum\n",
+ "from py_wake.flow_map import HorizontalGrid, YZGrid\n",
+ "R = D/2\n",
+ "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
+ "sim_res = wfm([0,200],[0,0],wd=270,ws=10)\n",
+ "fig,(ax1,ax2) = plt.subplots(1,2, figsize=(10,4))\n",
+ "ax1.set_xlabel(\"x [m]\"), ax1.set_ylabel(\"y [m]\")\n",
+ "sim_res.flow_map(HorizontalGrid(extend=.1)).plot_wake_map(10, ax=ax1, plot_colorbar=False)\n",
+ "sim_res.flow_map(YZGrid(x=200)).plot_wake_map(10, ax=ax2)\n",
+ "ax2.plot([-100,100],[70,70],'-.')\n",
+ "ax2.set_xlabel(\"y [m]\"), ax1.set_ylabel(\"z [m]\")\n",
+ "\n",
+ "plt.figure()\n",
+ "flow_map = sim_res.flow_map(HorizontalGrid(x=[200], y=np.arange(-80, 80)))\n",
+ "\n",
+ "for x in [-.5,.5]:\n",
+ " plt.gca().axvline(x,color='grey')\n",
+ "plt.plot(flow_map.Y[:, 0]/D, flow_map.WS_eff_xylk[:, 0, 0, 0], '-.', label='Hub-height profile')\n",
+ "plt.plot([-.5,.5],[7.73,7.73],label='Rotor average: 7.73m/s')\n",
+ "rc_ws = flow_map.WS_eff_xylk[80, 0, 0, 0]\n",
+ "plt.plot(flow_map.Y[80, 0]/D, rc_ws,'.', ms=10, label='Rotor center: %.2fm/s'%rc_ws)\n",
+ "plt.legend()\n",
+ "plt.xlabel(\"y/D\")\n",
+ "plt.ylabel('Wind speed [m/s]')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "A better estimate of the rotor-average wind speed can be obtained by a (weighted) mean of the wind speed at a number of points covering the rotor. Here is a some model examples."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from py_wake.rotor_avg_models import RotorCenter, GridRotorAvg, EqGridRotorAvg, GQGridRotorAvg, CGIRotorAvg, PolarGridRotorAvg,polar_gauss_quadrature\n",
+ "from py_wake.flow_map import HorizontalGrid\n",
+ "R=D/2\n",
+ "def plot_rotor_avg_model(rotorAvgModel, name):\n",
+ " plt.figure()\n",
+ " m = rotorAvgModel\n",
+ " wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=m)\n",
+ " ws_eff = wfm([0, 200], [0, 0], wd=270, ws=10).WS_eff_ilk[1,0,0]\n",
+ " plt.title(name)\n",
+ " c = plt.scatter(m.nodes_x, m.nodes_y,c=m.nodes_weight,label=\"%.2fm/s\"%(ws_eff))\n",
+ " plt.colorbar(c,label='weight')\n",
+ " plt.gca().add_artist(plt.Circle((0,0),1,fill=False))\n",
+ " plt.axis('equal')\n",
+ " plt.xlabel(\"y/R [m]\"); plt.ylabel('z/R [m]')\n",
+ " plt.xlim([-1.5,1.5])\n",
+ " plt.ylim([-1.5,1.5])\n",
+ " plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### RotorCenter\n",
+ "The `RotorCenter` model determines the rotor average wind speed from the rotor center point"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot_rotor_avg_model(RotorCenter(), 'RotorCenter')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GridRotorAvg\n",
+ "\n",
+ "The `GridRotorAvg` defines a set of points in cartesian coordinates"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "x = y = np.array([-.6, 0,.6])\n",
+ "plot_rotor_avg_model(GridRotorAvg(x,y,nodes_weight = [0.25,.5,.25]), 'Grid_4')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### EqGridRotorAvg\n",
+ "\n",
+ "The `EqGridRotorAvg` defines a NxN equidistant cartesian grid of points and discards points outside the rotor"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot_rotor_avg_model(EqGridRotorAvg(4), 'Grid_4')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GQGridRotorAvg\n",
+ "\n",
+ "The `GQGridRotorAvg` defines a grid of M x N cartesian grid points using Gaussian quadrature coordinates and weights"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot_rotor_avg_model(GQGridRotorAvg(4,3), 'GQGrid_4,3')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### PolarGridRotorAvg\n",
+ "\n",
+ "The `PolarGridRotorAvg` defines a grid in polar coordinates."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "theta = np.linspace(-np.pi,np.pi,6, endpoint=False)\n",
+ "r = 2/3\n",
+ "plot_rotor_avg_model(PolarGridRotorAvg(nodes_r =r, nodes_theta=theta, nodes_weight=None), 'PolarGrid_6')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The polar grid can be combined with Gaussian Quadrature. This is similar to the implementation in FusedWake (https://gitlab.windenergy.dtu.dk/TOPFARM/FUSED-Wake/-/blob/master/fusedwake/gcl/fortran/GCL.f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot_rotor_avg_model(PolarGridRotorAvg(*polar_gauss_quadrature(4,10)), 'PolarGrid_4,10')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### CGIRotorAvg\n",
+ "Circular Gauss integration with 4,7,9 or 21 points as defined in Abramowitz M and Stegun A. Handbook of Mathematical Functions. Dover: New York, 1970."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "for n in [4,7,9,21]:\n",
+ " plot_rotor_avg_model(CGIRotorAvg(n), 'CGIRotorAvg_%d'%n)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Compare rotor-average models\n",
+ "In general, the compuational cost and the accuracy of the estimate increases with the number of points, but the distribution of the points also has an impact.\n",
+ "\n",
+ "The plot below shows the absolute error of the estimated rotor-average wind speed for the wind directions \n",
+ "270$\\pm$30$^\\circ$ (i.e. wind directions with more than 1% deficit) for a number of different rotor-average models"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b6ea2ada30>"
+ ]
+ },
+ "execution_count": 45,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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GOXkWd5tiMBiqgR49ejB06FD7xr2aQnZ2NmPHjq00Z1EenNmHMUCsywJuxLokdqSqngWCgMeq1jz3Ex4cQJ5FST6T4W5TDAZDNXHHHXcUu0rJnfj4+HDbbbe51QZneghTsO61+ABoCKQBqOoxVf2+Cm2rEYTbltYeMiulDAZDPafMZbWqeg+AiHTCGsdprog0AlYBy4H1qlqz+m6VSIRtaa01CGHF41MZDAZDbcXpOQhV3aWq/1LVkcAwYB0wEajTUlqhgb74e3ualVIGg6HeUy6JVlXNwLpju+KhIWs4ImJbWmv2YhgMhvqN0z0MEektIotFZIuDjGqZMaTqAq2DzF4MQ80lz5LHmiNrePu3t1lzZA15lRDe/MSJE9x88820bduWXr16MWDAABYvXlxs2aNHjzJhwoRi84YMGYIzy9vHjBlD165dS8z/6quvePbZZwHrTudJkybRvn17+vXrV2JokNjYWLp160b79u154IEHiuxAX7hwISJSwL7HH3+cqKgoOnfuXKDOihUr6NmzJzExMQwcONC+KXHZsmU89dRTZd5fXcGVZbHzgA+B8cB1DkedJyKkAYdOp2OxlC/sssFQVeRZ8rj7h7t5fO3jvBX3Fo+vfZy7f7i7Qk5DVRk7diyDBg3iwIEDxMbGsmDBgmIjsObm5tKiRQu7ZkN5+PLLL7nkkktKLfPiiy/ypz/9CbAG92vSpAn79u3j4YcfZsaMGcXWuffee3n33XfZu3cve/fuLRBlNi0tjddff51+/frZ037++WfWr19PfHw8CQkJbNq0yR4T6t5777UHV7z55pv5+9//DsDo0aNZunQp6en14welKw7jlKouVdWDqnoo/6gyy2oQrYMCyM61cCKtTkZAMdRi1iWvY1vKNtJz01GU9Nx04lPiWZe8rtxtrly5Eh8fnwK7s8PDw7n//vuBouHBExMT7b2DjIwMJk+eTHR0NJMmTSIjo/Tl6BcuXODVV1/l//7v/0oss2fPHnx9fQkJCQFgyZIl9rhWEyZMYMWKFUV6D8eOHeP8+fMMGDAAEeG2226zCxcBzJw5k8cff7xATCYRITMzk+zsbLKyssjJyeHSSy+15+WHLzl37hwtWrSwpw8ZMoRly5aVep91BVfmMJ4SkfeAFUBWfqKqflnpVtUw8oMQJqak07yRv5utMRh+Z+fpnWTkFnwpZ+Zmsuv0Lga3Kj5+U1ls376dnj17llpmw4YNxMfHExQUVGBIaM6cOQQEBBAfH098fHyZ7cycOZNHHnnErhFRHOvXry/QjmPIcS8vLxo1akRqaqrdoeSXCQsLs587hiXfunUrR44c4dprr7VHsgWr7sfQoUNp3rw5qsp9991n3wX93nvvcc011+Dv70/Dhg355Zdf7PV69+7NTz/9xI033ljqvdYFXOlh3A7EACP5fTjq2iqwqcaRH+b88Gkz8W2oWXQO6oy/V8EfMX5efnQK6lRp15g+fTrdu3enT58+9rSSwoOvXbuWP/zhDwBER0cTHR1dYrtxcXHs27ePcePGlXr9Y8eO4Si57EzI8ZLKWCwWHn74YV555ZUi+fv27WPnzp0kJSWRnJzMypUrWbt2LQD/+te/+Oabb0hKSuL222/nz3/+s71e06ZNyy1PW9twpYfRXVUrFmS/ltK8kR9eHmImvg01joEtB9ItpBvxKfFk5mbi5+VHdEg0A1sOLHebUVFRLFq0yH4+e/ZsUlJS6N379/BCJYUHh9L1IhzZsGEDsbGxREREkJuby8mTJxkyZEiBcOJgDTl+7tw5+3lYWBhHjhwhLCyM3Nxczp07V8R55Qf1yycpKYkWLVqQlpZGQkKCPUT58ePHGTNmDEuXLmXVqlX079/fPp8yatQofvnlFzp37sxvv/1mn++YNGkSI0eOtLedmZmJv3/9GHlwpYfxi4h0qTJLajBenh60MiulDDUQTw9P3hnxDi8NeonpMdN5adBLvDPiHTwrELF22LBhZGZmFlDJc3ZSd9CgQXYJ0YSEBOLjS15Iee+993L06FESExNZt24dHTp0KOIsADp37mxflQTWFVUfffQRYF3pNGzYsCJOqnnz5gQGBvLLL7+gqnz88cdcf/31NGrUiJSUFHv48P79+7N06VJ69+5N69atWbNmDbm5ueTk5LBmzRo6d+5MkyZNOHfuHHv2WFWjf/jhhwIB+/bs2VPqCq+6hCs9jIHAFBE5iHUOQwBV1ZL7nHWI1kEBHDJDUoYaiKeHJ4NbDS73nEVhRISvvvqKhx9+mBdffJHQ0FAaNGjACy+8UGbde++9l9tvv53o6GhiYmLo27dvhe0ZNGgQjzzyiF2hb9q0adx66620b9+eoKAgFixYYC8bExNDXFwcYJ1PmTp1KhkZGYwaNapY2VRHJkyYwMqVK+nWrRsiwsiRI7nuOutC0P/85z+MHz8eDw8PmjRpwgcffGCvt2rVKp5//vkK32dtwJXw5uHFpdfUlVKVFd48n6eWJPDllmTin77K6S63wVAeTHjzojz44INcd911XHnlle42pQD5+1VWrFjhblPKRZWFN3dcSlvfltUCtA5uQFpWLmfSc9xtisFQ7/jrX/9aI/c6HD58uNgJ9LpKmUNSIrJFVUtdG+dMmdpOfhDCxNSLBDXwcbM1BkPtol+/fmRlZRVI++STT+jWzbl1NJdeemkBFbuaguPKsfqAM3MYncsIASJAo0qyp8aSvxfjcGo6PVs3cbM1BkPt4tdf63SM0nqDMw7DmQXddTa8eT5hTQIQsfYwDAaDoT7ijB5GvZmnKA0/b0+aN/TjsFlaazAY6il1XpO7MgkPbmB6GAaDod5iHIYLhAcHcNhItRoMhnqKyw5DRBqISM1SR68mwoMbkHIhmwtZue42xWCwo3l5pK1axam33iJt1So0r+JTip6ensTExNC1a1cmTpxY6pLWuXPnct9997l8jY0bNzJkyBAiIyPp2bMno0ePZtu2bcWWXbp0Kf/85z+LzSsrNDrA+fPnadmyZYl2fvHFF0RFReHh4VFEv+P555+nffv2dOzYke+++67Ea0yYMIEDBw4AZWtxlNX2/Pnz6datG9HR0YwcOZKUlBQAHn74YWJiYoiJiaFDhw40btwYgEOHDtGrVy9iYmKIiori7bfftrc1efJk9u7dW+YzcgpVLfXA6lRuBr4GTgJHbH+3Ay8BkWW14dDWSGA3sA/4SzH5twDxtuNnrPGrnKpb+OjVq5dWNl/HH9XwGcs0IflspbdtMOSzY8cOp8tacnM1ccpU3dmjp+7o1Fl39uipiVOmqiU3t0I2NGjQwP755ptv1ldeeaXEsh9++KFOnz7d6bZzcnL0+PHjGh4eruvXr7en//TTT7p48eJiyztra0k88MADetNNN5Vo544dO3TXrl06ePBg3bRpkz19+/btGh0drZmZmXrgwAFt27at5hbzbBMSEnTs2LH28z59+ujPP/+sFotFR44cqd98802ROiW1nZOTo6GhoXrq1ClVVX3sscf0qaeeKlL/9ddf19tvv11VVbOysjQzM1NVVdPS0jQ8PFyTk5NVVXX16tV65513lnjfhQE2awnvVWdWSa0CfgSeABJU1QIgIkHAUOCfIrJYVT8trRFbr2Q2MAJIAjaJyFJV3eFQ7CAwWFXPiMgo4F2gn5N1q5z8pbWHUtOJalHnVxIbagEX1q4lIz4etfUAND2djPh4LqxdS+DQoZVyjSuuuIL4+HhOnz7NHXfcwYEDBwgICODdd98tEo32f//7H3//+9/Jzs4mODiYefPmcemll/L000/b40aFhITQrl07pkyZwmWXXWavO3Dg7wETp06dSlBQEFu3bqVnz55069aNzZs38+abb3Lw4EFuvvlmcnNzCwQBLInY2FhOnDjByJEjS1T/K2ln/ZIlS5g8eTK+vr60adOG9u3bs3HjRgYMGFCg3Lx587j++uuBglocgF2Lo3BokpLa7t27N6rKxYsXCQ4O5vz587Rv376IbfPnz+eZZ54BwMfn971hWVlZWCwW+/kVV1zB1KlTyc3NxcurXKrcdpwZkrpSVf+mqvH5zgJAVU+r6iJVHQ985kQ7fYF9qnpAVbOBBcD1jgVU9WdVPWM7/QUIc7ZudRBuC3NughAaagqZO3eihUSKNCODrF27KqX93Nxcvv32W7p168ZTTz1Fjx49iI+P5x//+Ae33XZbkfIDBw7kl19+YevWrUyePJkXX3zRnhcbG8uSJUv473//65Tmxp49e/jxxx+L7KR+8MEHuffee9m0aRPNmjUrtQ2LxcIjjzzCSy+95MJd/46j9gYU1NVwZP369fTq1ctepyQtDmfa9vb2Zs6cOXTr1o0WLVqwY8cOpk2bVqDuoUOHOHjwIMOGDbOnHTlyhOjoaFq1asWMGTPsIk8eHh60b9+e3377rVzPwJEyHYaqlhkLw5kyQEusw1n5JNnSSmIa8K0rdUXkLhHZLCKbT5065YRJrnGJrxfBDXw4ZFZKGWoIfp07I4VCa4u/P76dKqaHkZGRQUxMjD2K67Rp01i3bh233norYI1om5qaWiDsOFjDiF999dV069aNl156ie3bt9vzxowZU2IY8H79+tG5c2cefPBBe9rEiRPx9Cw6Xbp+/XpuuukmALs9JfHWW29xzTXXFHgxu4I6ob0BBTU7nK1TUrmcnBzmzJnD1q1bOXr0KNHR0UWCGy5YsIAJEyYUeD6tWrUiPj6effv28dFHH3HixAl7XmVpdlTnKqniIvYVOxMkIkOxOox8sV6n6qrqu6raW1V7OwquVCbhwSbMuaHmcMmgQfhHRyMBASCCBATgHx3NJYMGVahdf39/4uLiiIuL44033sDHx8epF+H999/Pfffdx7Zt23jnnXfIzPxd1thRQyMqKootW7bYz3/99Vf+9re/FXBAlaW58eabbxIREcGjjz7Kxx9/zF/+8hen6sLv2hv55OtqFMbf399+ryVpcTjbdn603Xbt2iEi3Hjjjfz8888F6i5YsMDuNAvTokULoqKi+Omnn+xplaXZUabDEJEBItK4wley9goc3XwYUMTliUg08B5wvaqmulK3OggPbmB6GIYag3h60vr992j5ysuEPnA/LV95mdbvv4cU88u8ojhqXaxevZqQkBAaNmxYoMy5c+do2dLa+c/XrCiO6dOnM3fu3AIvQmeDC15++eX2kOb59pTEvHnzOHz4MImJibz88svcdttt9tVWTzzxBIsXLy61/pgxY1iwYAFZWVkcPHiQvXv3Fhuy3VGzoyQtDmfbbtmyJTt27CB/lKSw/sbu3bs5c+ZMgXmUpKQku376mTNnWL9+PR07drTn79mzh6ioqFLv1RlKdRgi8jcgFHinwleCTUCkiLQRER9gMrC00PVaA18Ct6rqHlfqVhfhwQEcO59JZk6dj4ZiqCWIpyeBQ4cScu+9BA4dWiXOAuDpp59m8+bNREdH85e//KVYh/D0008zceJErrjiigIa24Vp1qwZn332GU888QTt27fnsssuY+HChU4tz33ttdeYPXs2ffr0KTIk5grbtm2zz4EsXryYsLAwNmzYwOjRo7n66qsBa0/oxhtvpEuXLowcOZLZs2cXO0w2evToAuJPc+bM4c4776R9+/a0a9fOPuG9dOlSZs2aVWrbLVq04KmnnmLQoEFER0cTFxfHX//6V3vb8+fPZ/LkyQV6WTt37qRfv350796dwYMH8+ijj9oDO544cQJ/f3+aN29e7mdlp6TlU/r7UtZ/AH8rrZyzB3ANsAfYDzxpS7sHuMf2+T3gDBBnOzaXVre0oyqW1aqqfrnliIbPWKZ7T5yvkvYNBleW1RrKz1VXXVVpbaWnp2u/fv2KXXLrbl599VV97733is2r1GW1qrocWF5xt2Rv7xvgm0Jpbzt8vhO409m67sBxpVT7poFutsZgMJSX0jbhuYq/vz/PPPMMycnJtG7dutLarQwaN25c5uIAZ6nYotx6SHhQvi6Gmfg2GGoK27ZtK/JS9PX1rdaw6vnDWDWN22+/vdLaMg7DRYIa+BDo68VhM/FtMNQYunXrZl9dZKg6nHIYItIJ60a5lliXsx4Flqrqziq0rUYiIrQODuCQCUJoMBjqGc4sq52BdWe1ABuxrlgSYL6IOL+guQ4REdzA7MUwGAz1Dmd6GNOAKC20m1tEXsUagLD4EJJ1mNbBAXy/4zi5eRa8PE2EeIPBUD9w5m1nAYpuU4Tmtrx6R0RwADl5yrFzmWUXNhgMhjqCMw7jIWCFiHwrIu/ajuXACuDB0qvWTVoHmSCEhpqDxaIkxqew6euDJManYLEUr73gCidOnODmm2+mbdu29OrViwEDBhTYFb1u3Tr69u1Lp06d6NixI7Nnzy5Q/9NPPyU6OpqoqCi6d+/OnXfeydmzZ4u91qxZs/jxxx+LpK9evZprr722TFs3bdqEp6cnCxcuLDZ/5MiRdO/enaioKO655x7yStAL+eqrr3j22WcBa8TXSZMm0b59e/r160diYmKxdUrSvSip/qpVq+x6FjExMfj5+fHVV18VaPP+++8voPGxbNkynnrqqTKfQ7VQ0gYNLbjhzgPoD4wHJtg+ezpT111HVW3cU1U9ejZdw2cs0082JFbZNQz1F1c27uXlWXTxq1v0nQdW65t3r9B3Hliti1/donl5lnJf32KxaP/+/XXOnDn2tMTERH399ddVVfXYsWPaqlUrjY2NVVXVU6dOac+ePfXLL79UVdVvv/1We/bsqUlJSaqqmpubq++//77u2rWryLVK2+i2atUqHT16dKm25ubm6tChQ3XUqFH6xRdfFFvm3Llz9vu64YYbdP78+cWWGzBggF2DYvbs2Xr33Xerqur8+fP1xhtvLLZOSboXztRPTU3VJk2a6MWLF+1pmzZt0j/84Q8FND4sFovGxMQUKFdZuLpxz9kB+N5AnqouAnYAlwFXVbr3qiVcGuiHj5eHkWs1uJ3DCamcTDxPTpb1V3NOVh4nE89zOCG1jJols3LlSnx8fLjnnnvsaeHh4dx///0AzJ49m6lTp9rDk4eEhPDiiy/aQ4g/99xzvPzyy/aYUp6entxxxx322EYRERE8++yzDBw4kC+++IKpU6faewfLly+nU6dODBw4kC+//LJMW9944w3Gjx9P06ZNSyyTH+8qNzeX7OzsYgMX7tmzB19fX3s4kyVLljBlyhTAqqS3YsWKIsEXHXUvRMSue+Fs/YULFzJq1CgCAqx7u/Ly8njssccKhIQH68rMIUOGsGzZsjKfR1XjzCqpp4DXgTki8jzwBnAJ8ISIPFnF9tVIPDyE8KAAElPMXgyDezl1JM3uLPLJycojJSmt3G2WpVWxfft2u/ZDPr1792bHjh1O1Qfw8/Nj3bp1TJ482Z6WmZnJH//4R/73v//x008/cfz48VLbSE5OZvHixQUcW0lcffXVNG3alMDAQCZMmFAkf/369QVsdtSq8PLyolGjRqSmFnTCpeleOFO/cMTZN998kzFjxhQb86l3794Fos+6C2d6GBOAy4FBwHRgnKo+C1wNTKpC22o04cEBpodhcDuhrQLx9i0YDM/b15OQsMoLWzN9+nS6d+9Onz59AOswtrPhxbdt20ZMTAzt2rXjs89+11mbNKnoq2PXrl20adOGyMhIRIQ//OEPpbb90EMP8cILLxQbDLAw3333HceOHSMrK4uVK1cWyXfUswDnNC1KK1NW/WPHjrFt2zb77vCjR4/yxRdf2HtxhaksPYuK4ozDyFXVPFVNB/ar6nkAVc2gnq6SAuvE96HU9GK/GAZDddG6azBNIxranYa3rydNIxrSumtwudssrFUxe/ZsVqxYYQ+3HRUVVUTqNDY2lt69exepn78De9SoUfbw21Cy1oWzjghg8+bNTJ48mYiICBYuXMif/vSnIhPIjvj5+TFmzBiWLFlSJM9RzwIKalXk5uZy7tw5goKCCtQpTfeirPqff/4548aNw9vbG4CtW7eyb98+2rdvT0REBOnp6QVkWStLz6KiOOMwskUkwPbZ3g8VkUbUY4cRERJARk4ep9Ky3G2KoR7j4SGMeTCGq6ZF0W9MG66aFsWYB2Pw8HD+xVuYYcOGkZmZyZw5c+xpjloV+VoW+aE4UlNTefLJJ5k5cyZg1Zl49NFHC7xMMwrJyBZHp06dOHjwIPv37wesYbxL4+DBgyQmJpKYmMiECRN46623GDt2LADDhw8nOTmZCxcucOzYMcD64v7mm2/oVIwaoaOeBVi1KvLDty9cuJBhw4YVcWal6V6UVX/+/PkFhqNGjx7N8ePH7fcTEBBQwJ49e/bQtWvX0h9gNeDMxr1BqpoFoA6a3oA3MKVKrKoFtHYIQti0oZ+brTHUZzw8hIjoECKiS9afcAUR4auvvuLhhx/mxRdfJDQ0lAYNGvDCCy8A1hflp59+yl133cW5c+dITExk7ty5DB48GIBrrrmGU6dOMWrUKPLy8mjcuDFdu3YtMzifn58f7777LqNHjyYkJISBAweSkJDgsv0Wi4V9+/YRFBTE+fPnGTNmDFlZWeTl5TFs2LBi5zwGDRrEI488Yh9umzZtGrfeeivt27cnKCjILtgEEBMTY3eWc+bMYerUqWRkZDBq1Ci77kVp9RMTEzly5Ij9eTnDqlWrisi0uoWSlk8VdwAjSjuvSUdVLqtVVT146oKGz1imn286XKXXMdQ/apsexptvvqldu3bV06dPu9sUVVXdtm2bPvzwwy7Xe+CBB/SHH36oAosqxvHjx3XYsGFV0nZVLavN54UyzusNLZv44+khZvOeod4zffp0tm3bRpMmTdxtCgBdu3bl1VdfdbneX//6V6dlYquTw4cP88orr7jbDKDi4c3LP1Bay/H29KBlY38TtdZgqGI+/PBDXnvttQJpl19+eZHd5RXl0ksvZcyYMZXaZmWQvzqtJuBsePMPsYY1by0iHwCo6h1VaVhtIDw4gENGF8NgqFJuv/32ShUBMpQfZ3sYc21/rwCKKr/XU8KDA/jfb8fcbYbBYDBUC045DFVdAyAiafmf87OqxKpaQnhQA85l5HA2PZvGAT7uNsdgMBiqFFcnvbPLOK9XhAdbl9aaiW+DwVAfcMlhqGr/0s7rG+HB1t2qiWYew+BGLJY89sduZMOi+eyP3YjFUnz4boOhohi5uAqQv3nvsOlhGNyExZLHoudm8fXrL/LzF//l69dfZNFzsyrsNI4fP87kyZNp164dXbp04ZprrmHPnj0A7N27l2uvvZZ27drRq1cvhg4dytq1awGYO3cu9913X5ntL1y4EBEpEmIkn4yMDAYPHmzXrvjoo4+IjIwkMjLSvoO6MKVpWIwcOZLGjRsX0deYNm0a3bt3Jzo6mgkTJnDhwoUC+YW1NrKzsxk0aBC5ubll3mNdxCmHISKdRGSGiLwuIq/ZPneuauNqOv4+nlza0NcsrTW4jYNbYzm2bzc5mZmgSk5mJsf27ubg1thyt6mqjBs3jiFDhrB//3527NjBP/7xD06cOEFmZiajR4/mrrvuYv/+/cTGxvLGG29w4MABp9tPS0vj9ddfp1+/fiWW+eCDD7jhhhvw9PTk9OnTPPPMM/z6669s3LiRZ555hjNnzhSp8/7779OkSRP27dvHww8/zIwZM+x5jz32GJ988kmROv/617/47bffiI+Pp3Xr1rz55pv2vLy8PGbMmFFgh7qPjw/Dhw8vEEixPuFMePMZwAKsey42Aptsn+eLyF+q1ryaT3hwA7O01uA2TibuJyerYDyznOwsTiU6/wIvzKpVq/D29i4QQiMmJoYrrriCefPmMWDAgAL7Fbp27crUqVOdbn/mzJk8/vjj+PmVHFJn3rx59rhM3333HSNGjCAoKIgmTZowYsQIli9fXqROaRoUw4cPJzCwaATffK0MVSUjI6NAvKeStDbGjh3LvHnznL7fuoQzPYxpQB9V/aeqfmo7/gn0teXVa8KDAsykt8FtNI1oh7evb4E0bx9fQiPalrvNhISEInoX+TijdVEaW7du5ciRI6VKr2ZnZ3PgwAEiIiKAgtoSUFB3whFnNCiK4/bbb6dZs2bs2rXLHl68NK2Nrl27smnTpjLbrYs44zAsQIti0ptTj6PV5hMR0oCTaVmkZ9fPMU2De2nToxfN23fE29cPRPD29aN5ZEfa9Cj+hV/ZjBs3jq5du3LDDTeUWdZisfDwww+XGeYiJSWFxo0b28/zewmOFBcG3dlyhfnwww85evQonTt3tg81laa14enpiY+PD2lp5Repqq04sw/jIWCFiOwFjtjSWgPtgbJnt+o49onv0+l0atbQzdYY6hseHp6Mf/JZDm6N5VTiAUIj2tKmRy88PMoWFSqJqKgo+yRvcXn5E9wAixcvZvPmzTz66KNltpuWlkZCQgJDhgwBrBPrY8aMYenSpXYtDShem2L16tX286SkJHsbjuRrUISFhZWoYVESnp6eTJo0iZdeeonbb7/drrUBVgf2zTff4OXlZQ+fnpWVVeqQWl2lzB6Gqi4HOgDPAN8B3wNPAx1teU4jIiNFZLeI7Ctu/sM2ub5BRLJE5NFCeYkisk1E4kSk+KUVbiB/L0ZiihmWMrgHDw9P2vXqS//xk2nXq2+FnAVY9TCysrL4z3/+Y0/btGkTa9as4eabb2b9+vUsXbrUnudswL5GjRqRkpJi13zo379/EWcB0KRJE/Ly8uxO4+qrr+b777/nzJkznDlzhu+//77YUOnOaFg4oqp2zQlV5X//+59dK6M0rY3U1FRCQ0Pt4kf1iTJ7GCLyAPClqv5SkQuJiCcwGxgBJAGbRGSpqu5wKHYaeAAYW0IzQ1U1pSJ2VDbhQda9GIdPm4lvQ91ARFi8eDEPPfQQ//znP/Hz8yMiIoJ///vf+Pv7s2zZMv785z/z0EMPcemllxIYGMj//d//VaoNV111FevWrePKK68kKCiImTNn2oPwzZo1y95zmDVrFr1792bMmDGlalBcccUV7Nq1iwsXLhAWFsb777/PiBEjmDJlCufPn0dV6d69ewHRqJJYtWoV11xzTaXeb62hpLjn+QdwDjgK/AT8CQgtq04J7QwAvnM4fwJ4ooSyTwOPFkpLBEKcvV5V62E40v2Z7/SJL+Or7XqGuk1t08OoCrZs2aJ/+MMf3G1GsYwbN0537drlbjMqharQwzgAhAF/wyrRukNElovIFBFxRWm+Jb/PgYC1l9HShfoKfC8isSJyV3EFROQuEdksIpvz9Yerg/DgBmbznsFQifTo0YOhQ4faN+7VFLKzsxk7diwdO3Z0tyluwRmHoapqUdXvVXUa1hVTbwEjsToTZyluMNGV4IWXq2pPYBQwXUQGFWPou6raW1V7h4aGutB0xQgPCjDhQQwGB5577jliYmIKHM8995xLbdxxxx3FrlJyJz4+Ptx2223uNsNtOLNKqsCLXlVzgKXAUhHxd+FaSUArh/MwrENdTqGqR21/T4rIYqz7QNaWXqt6iAgOYFn8UbJzLfh4mWgrBsOTTz7Jk08+6W4zDJWMM2+3SSVlqGqGC9faBESKSBsR8QEmY3U8ZSIiDfKHv0SkAXAV4Lo6fBXROrgBFoWkM2ZYymAw1F3K7GGo6p7KuJCq5orIfViX5noCH6jqdhG5x5b/tog0AzYDDQGLiDwEdAFCgMW2JXJewH/VxSW9VUlEfpjz0+m0Db3EzdYYDAZD1eCsRGsnrBPUv6rqBYf0ka68uFX1G+CbQmlvO3w+jnWoqjDnge7OXqe6aZ3vMFIuQv2cCzMYDPUAZ4IPPgAsAe4HEkTkeofsf1SVYbWJ0Et8CfDxNFFrDW5BLUrGzlTOrzhMxs5U1FKvhTANVYgzcxh/BHqp6lhgCDBTRB605ZUdqKUeICK0DgogMcWslDJUL2pRUt7fxun5uzj/wyFOz99FyvvbKuw0qkoP4+GHH7avmurQoUOBmFGOVLYeRkn1Dx48SL9+/YiMjGTSpElkZ1tFRM+cOcO4ceOIjo6mb9++JCRYp0yNHkbZeOYPQ6lqIlanMUpEXsU4DDs9w5uwfn8qR8+6sg7AYKgYmbtPk30kDc22xgHVbAvZR9LI3H263G1qFeph/Otf/yIuLo64uDjuv//+EoMWVqYeRmn1Z8yYwcMPP8zevXtp0qQJ77//PgD/+Mc/iImJIT4+no8//pgHH7T+RjZ6GGVzXERi8k9szuNarBPR3arIrlrHn4a0A4V//1gpawQMBqfIOXrR7izy0WwLOUfL39utaj2MfObPn89NN91UbF5l6mGUVF9VWblyJRMmTABgypQpfPXVVwDs2LGD4cOHA9CpUycSExM5ceIEYPQwymIKcMwxQVVzVfU2YBCAOBNDuI4T1iSAWweEszA2ib0n6l/YY4N78G7RAPEp+N9YfDzwbtGg3G1WpR5GPocOHeLgwYMMGzasSF5l62GUVD81NZXGjRvj5eVVpN3u3bvz5ZdfArBx40YOHTpEUlISYPQwyuIT4EYRae2YaNtL4SsiH2F1KvWe6UPb08DHi5e+2+1uUwz1BL+OQfi0CrQ7DfHxwKdVIH4dnQvrXVFc0cNwZMGCBUyYMKHYndyVrYfhajrAX/7yF86cOUNMTAxvvPEGPXr0sDuW+qyH4YzDGAnkYZVkPSoiO0TkALAXuAn4l6rOrUIbaw1BDXy4a1Bbvt9xgthDRcdYDYbKRjyEkGndCLqpEw1HhBN0UydCpnVDPMrf6Y+KiiI2tnhN8KioKLZs2WI/X7x4MXPnzuX0adfmTBYsWFDicFRxehhHjvwehi4pKYkWLYpqujmWc9TDKKl+SEgIZ8+etU9gO7bbsGFDPvzwQ+Li4vj44485deoUbdq0sbdh9DBKQFUzVfUtVb0cCAeGAz1VNVxV/6iqcVVtZG3ijoFtCLnElxeW7yr2F4zBUNmIh+DfOZiGw1vj3zm4Qs4Cqk4PI5/du3dz5swZBgwYUGx+ZethlFRfRBg6dKhdLOqjjz6yz5ucPXvWvmLqvffeY9CgQXb97/qsh+FS4CNVzVHVY6p6torsqfU08PXigeHt2XjwNKt3V1/EXIOhssjXw/jhhx9o164dUVFRPP3007Ro0cKuh/H222/Ttm1bBgwYwN///neX9DDmz5/P5MmTSxU3ytfDAAroYfTp06eIHka+85o2bRqpqam0b9+eV199lX/+859l1n/hhRd49dVXad++PampqUybNg2AnTt3EhUVRadOnfj222957bXX7LbVZz0Mqau/gnv37q2bN7tHmC8718KVr64hwMeTbx64Ao8K/uIz1C927txJ586d3W2GW9m6dSuvvvoqn3zyibtNKcINN9zA888/XydCnBf3XRORWFXtXVx5E1q1CvDx8uCRqzqw63gaS34ruprDYDCUjtHDqJk45TDESquySxryuS66BVEtGvLK93vIyq1ZX3qDoaoxehh1E6eCD6qqishXWBX3DE7g4SE8PrITUz7YyH9/Pcztl7cpu5LBUEcwehh1E1eGpH4RkT5VZkkdZFBkCAPaBvPmyn1cyKqfsWcMBkPdwRWHMRTYICL7RSReRLaJSHxVGVYXEBFmjOpE6sVs/rPWFTVbg8FgqHk4NSRlY1SVWVGHiWnVmFFdm/HeTwe4dUA4IZf4utskg8FgKBdO9zBU9RDQGLjOdjS2pRnK4NGrO5KZa+HNlfvcbYqhDmKxWNi9ezdr1qxh9+7dWCyWsisZDOXAaYdh08CYBzS1HZ+KyP1VZVhdol3oJdzYO4x5vx7icKoRWTJUHhaLhU8++YRFixaxatUqFi1axCeffFJhp1FVehiHDh1i+PDhREdHM2TIEHtAv8IYPYyaiStzGNOAfqo6S1VnAf2xiisZnODB4R3wEOHVH0xgQkPlsXfvXpKTk+0vuuzsbJKTk9m7d2+526xKPYxHH32U2267jfj4eGbNmsUTTzxRbDmjh1EzccVhCNYghPnkYQSUnKZZIz9uv7wNS347yo6j591tjqGOcPz4cbuzyCc7O5vjx4+Xu82q1MNw1JkYOnQoS5YsKbac0cOombjiMD4EfhWRp0XkaeAX4P0qsaqOcu/gdgT6evHid7vcbYqhjtCsWTN8fHwKpPn4+NCsWbNyt1mVehjdu3dn0aJFgDXSbVpaGqmpqQXKGD2MmovTO72BL4DbgdPAGeB2Vf131ZlW92gU4M2fhrZn9e5T/HIgtewKBkMZREZG0rJlS7vT8PHxoWXLlkRGRlbL9V3Vw3j55ZdZs2YNPXr0YM2aNbRs2dL+ws7H6GHUXFza6a2qvYAtZVYwlMjUyyKYuz6Rf367i8V/uqzUiJ0GQ1l4eHhw6623snfvXo4fP06zZs2IjIzEw6P8YeKioqLsIb+Ly8uf4AZrL2Hz5s08+uijTrXdokUL+y/3CxcusGjRIho1alSgTHF6GKtXr7afJyUlMWTIkCJt5+tehIWFFdHDKK6+ox6Gl5dXsXoYYHVEbdq0MXoYmJ3e1Y6ftycPXRlJ3JGzfLf9hLvNMdQBPDw86NixI4MHD6Zjx44VchZQtXoYKSkp9hVczz//PHfccUeRMkYPowajqk4dwA4gF9gPxAPbgHhn61f30atXL62p5OTm6bCXV+mwl1dpTm6eu80x1DB27NjhbhM0OTlZJ06cqG3bttUuXbroNddco3v27FFV1Z07d+qoUaO0TZs22r9/fx0xYoT+8MMPqqr64Ycf6vTp00ts94svvtD27dtrZGSkTps2TTMzM4std8cdd9jbVFV9//33tV27dtquXTv94IMP7OkzZ87UJUuWqKpqRkaGTpgwQdu1a6d9+vTR/fv3l1l///792qdPH23Xrp1OmDDBbs/PP/+s7du3144dO+q4ceP09OnTBe7hz3/+s9PPsiZT3HcN2KwlvFed0sOwzWFcARTZqKc1dPOeO/UwnGF5wjHu+XQLL4zvxqQ+rcuuYKg3GD0Mo4dRXVSJHobN6/xLVQ8VPipucv3k6qhmxLRqzL9+2Etmjgl/bjA4YvQwaibVOochIiNFZLeI7BORvxST30lENohIlog86krd2oaIMGNkJ46fz+SjnxPdbY7BUKkYPYy6iSvBB4cC94hIInAR66Y9VdVoZyqLiCcwGxgBJAGbRGSpqu5wKHYaeAAYW466tY4B7YIZ3CGUt1bvZ3Lf1jTyr4eTaIY6idHDqJu40sMYBbQFhmENPnit7a+z9AX2qeoBVc0GFgDXOxZQ1ZOqugnIcbVubeXxkR05l5HD22v2u9sUg8FgKBVXHMZhrBPfU2xzFwpc6kL9lsARh/MkW1ql1RWRu0Rks4hsPnXqlAumuY+oFo24PqYFH64/yInzmWVXMBgMBjfhisN4CxgA3GQ7T8M6TOQsxe1QK3uJlgt1VfVdVe2tqr1DQ0NdMM29PDKiI3kW5d8/lj9gnMFgMFQ1rjiMfqo6HcgEUNUzgE/pVQqQBLRyOA8DjlZD3RpP6+AAbu7bms83H2H/qQvuNsdQy1DNIyVlJQcPvkFKykpUK76yqKrCm7/66qt06dKF6Ohohg8fzqFDvy+0HDlyJI0bN+baa68t1baHHnrIfr2SwpMXxtXw5qrKAw88QPv27YmOjmbLFmuAiyNHjjB06FA6d+5MVFQUr732mr2tRx99lJUrV5Zqe62npA0ahQ/gV8AT2GI7DwW2ulDfCzgAtMHqaH4Dokoo+zTwaHnq5h81eeNecZw8n6mdZ36r93662d2mGNyMKxv3LJZcjd3yB121uqv+uKKdrlrdVWO3/EEtltxyX99isWj//v11zpw59rStW7fq2rVrNSMjQyMjI+2b5VRVt23bph9++KGqlr1xb+XKlXrx4kVVVX3rrbf0xhtvtOf9+OOPunTpUh09enSJ9VNTU7Vfv37284kTJ+r8+fNVVfXuu+/Wt956q9g6bdq00dTUVD19+rS2adPGvhGvpPpff/21jhw5Ui0Wi27YsEH79u2rqqpHjx7V2NhYVVU9f/68RkZG6vbt21VVNTExUUeMGFGi7TURVzfuudLDeB1YDDQVkeeAdcA/XHBMucB9wHfATuBzVd0uIveIyD0AItJMRJKAPwP/JyJJItKwpLou2F7jCQ305c4r2vLNtuP8duSsu80x1BJSU9dw/nwceXnpgJKXl87583Gkpq4pd5tVGd586NChBAQEANC/f/8CAkrDhw8nMDCw1PoLFy5k5MiRAKWGJ3ekPOHNlyxZwm233YaI0L9/f86ePcuxY8do3ry5PVpvYGAgnTt3tke4DQ8PJzU1tUKh5Ws6rki0zgMeB54HjgFjVfULVy6mqt+oagdVbaeqz9nS3lbVt22fj6tqmKo2VNXGts/nS6pb1/jjFW0IauDDC8t3FRtJ02AoTFradvLyMgqk5eVlkJZW/hXnVRne3JH333+fUaNGuVRn/fr1dttKC0/uSHnCmzsTUj0xMZGtW7fSr18/e1rPnj1Zv369S/dUm3BlHwaqugswYg5VRKCfN/cNbc+zy3bw094UBnWoPRP3BvcQGBiFp6e/rYdhxcPDj0suqZ7QIuPGjWPv3r106NDBHoXWGT799FM2b97MmjWu9YSOHTtG/oKW4n5UVUbYc2favnDhAuPHj+ff//63PSghQNOmTTl6tM5MrxahYmEtDZXOLf1bE9bEnxeW78JiMb0MQ+kEBw+mYcPueIgfIHjgR6BXBwLTwsvdS42KiiI2NrbEvPwJYLCGN587dy6nT592uv0ff/yR5557jqVLl+Lr6+uSbY6hzx3DkwMFwpM7kh/2PJ/8cqXVL6kOQE5ODuPHj+eWW24pogOSmZmJv7+/S/dUmzAOo4bh6+XJn0d0YPvR8yzbdszd5hhqOCKeRLd9gw6NHqNVg5vp0OhRujR6Cs3MxlJOgZ+qDG++detW7r77bpYuXUrTpk1dtq1z587s27cPoNTw5I6UJ7z5mDFj+Pjjj1FVfvnlFxo1akTz5s1RVaZNm0bnzp3585//XORae/bsoWvXri7fV62hpNnw2n7UtlVSjuTmWfTqf63RQS+u1KwcE/68vuFqePPsEyc0fdu2Ikf2iRPltqGqwpsPHz5cmzZtqt27d9fu3bvrddddZ88bOHCghoSEqJ+fn7Zs2VKXL19epP7atWv1lltusZ+XFJ5806ZNOm3aNHs5V8ObWywW/dOf/qRt27bVrl276qZNm1RV9aefflJAu3XrZr+Hr7/+WlVVs7OztVOnTpqTk+Paw3YjVRLeHEBEJgLLVTVNRP4P6An8XVVrpAJfTQ9vXhYrd53gjrmb+dv1Udw6IMLd5hiqEVfDm+edP092UhLYhIkA8PDAJywMT4fx9brCwIEDWbZsWQEZ15rA4sWL2bJlC3/729/cbYrTVEl4cxszbc5iIHA18BEwp9yWGkplaMem9I0I4rUV+7iYletucww1GI/AQDz8/SFfac/DAw9/fzzKWKJaW3nllVc4fPiwu80oQm5uLo888oi7zahSXHEY+dtHRwNzVHUJru30NriAiDBjVCdSLmTxwbqD7jbHUIMREXwiIvAJC8OraVN8wsLwiYhwq158ZYQ3L4l+/foRHe1UkOxqZeLEiTWu11PZuLKsNllE3sEaYvwFEfHFTJpXKb3CmzCiy6W8s/YAQzs1pWvLRu42yVBDERE8GzasMUNQJrx53cSVF/6NWHdaX6WqZ4Eg4LGqMMrwO09e05lAPy9ueOtnPt6QaDb01RPMv7OhqinPd8wVh2HBGsvpRRFZBEwG1rp8RYNLRIQ04JsHrmBgZAizlmxn+n+3cD6zsFyIoS7h5+dHamqqcRqGKkNVSU1Nxc/Pz6V6rqyS+hw4D8yzJd0ENFHViS5dsZqo7aukCmOxKO+tO8ALy3fTsrE/s2/uSbcwM0RVF8nJySEpKcm+Qc1gqAr8/PwICwvD27ug0mdpq6RccRi/qWr3stJqCnXNYeQTe+g09/93KykXsvnrNZ2Ycpl7JzcNBkPdorKW1W4Vkf4OjfYD6m6UrRpKr/Agvn7gCq6IDOHp/+3g3k+3cC7DDFEZDIaqp0yHISLbRCQe6Af8LCKJIpIIbAAGVbF9hmJo0sCH96b05slrOvPjzhNc+8ZPJiS6wWCocpxZVlu6/JXBLYgIfxzUll4RTbj/v1uZ8PbPPDGqM7dfboaoDAZD1VBmD0NVD+UfWCe9LwXCHQ6DG+nZuglfPzCQwR1CeXbZDu7+JJZz6WaIymAwVD5Oz2GIyJ1Yl9F+Bzxj+/t01ZhlcIXGAT7857be/N/ozqzcdZLRb/xEnBmiMhgMlYwrk94PAn2AQ6o6FOgBnKoSqwwuIyLceUVbvrhnAKow8e2feX/dQbOW32AwVBquOIxMVc0EEBFftarvdawaswzlpUfrJnzzwBUM6diUvy3bwV1miMpgMFQSrjiMJBFpDHwF/CAiS4C6q0VYi2kU4M27t/Zi1rVdWL37JNe8/hNbD59xt1kGg6GW4/TGvQKVRAYDjbDqY2RXulWVQF3duOcqvx05y/T/buH4uUz+MqoT0wa2MauoDAZDiVTWxj07qrpGVZfWVGdh+J3urRrz9QNXMLxzU/7+9U7++HEsZ9PNP5vBYHAdE568HtDI35u3/9CLp67rwpo9Jxn9+jq2mCEqg8HgIsZh1BNEhNsvb8PCey7DwwNufHsD/1l7wKyiMhgMTmMcRj2je6vGLLv/Cq7sfCnPfbOTOz/azJmLZojKYDCUjSvRan2B8UAEDiFFVPXZKrGsgphJ79JRVT7ecIjnvt5JyCU+vHFzD3qFB7nbLIPB4GYqa9J7CXA9kAtcdDgMtRARYcplESy69zK8PD248Z1feGfNfiwWM0RlMBiKxxVN7zBVHVmRi4nISOA1wBN4T1X/WShfbPnXAOnAVFXdYstLBNKAPCC3JA9ocI1uYY1Y9sBAnli0jee/3cUvB1J55cYYghr4uNs0g8FQw3Clh/GziHQr74VExBOYDYwCugA3iUiXQsVGAZG24y5gTqH8oaoaY5xF5dLQz5s3b+7B366PYv2+VEa//hObE0+TZ8ljzZE1vP3b26w5soY8S567TTUYDG7ElR7GQGCqiBwEsgABVFWjnazfF9inqgcARGQB1iGuHQ5lrgc+VuvEyi8i0lhEmqvqMRfsNJQDEeHWARH0aN2E6f/dwqR3fyYyej5n8vaRkZuBv5c/3UK68c6Id/D08HS3uQaDwQ240sPI//V/FXAdVp2M61yo3xI44nCeZEtztowC34tIrIjc5cJ1DS7QtWUjlt0/kD5dTpKUvov03HQUJT03nfiUeNYlr3O3iQaDwU047TAqQQ+juHgUhWdYSytzuar2xOq4potIEbU/EblLRDaLyOZTp0wg3fIS6OfNkG7ZiGfBoIUZuZnEn9pRQi2DwVDXqU49jCSglcN5GEWDF5ZYRlXz/54EFmMd4iqAqr6rqr1VtXdoaKgLphkK0zmoMwFe/gXSNM+bOd9l8OfP4li/L8WsqDIY6hnVqYexCYgUkTYi4gNMBpYWKrMUuE2s9AfOqeoxEWkgIoEAItIA67BYggvXNrjIwJYD6RbSDX8vfwTB38ufLsFdGdNhOD/sPMEt7/3KwBdW8vJ3uzlw6oK7zTUYDNWAK5PemaqaKSJ2PQwRcVoPQ1VzReQ+rD0TT+ADVd0uIvfY8t8GvsG6pHYf1mW1t9uqXwostkVZ9QL+q6rLXbDd4CKeHp68M+Id1iWvY9fpXXQK6sTAlgPx9PDk6TFd+WHHCRZtSeKt1ft4c9U+erZuzPheYVwb3YJG/t7uNr9aOHDqAtuSz9GxWSCRTQPx9DBRgA11G1d2ei/G+gJ/CBgGnAG8VfWaKrOuApid3tXDifOZfLU1mUVbkthz4gI+Xh6M6HIpE3qGcUVkCF6edSv6zPFzmSyLP8qSuKNsSz5nTw/w8aRri0Z0b9WI7q0a0z2sMWFN/E0oeUOto7Sd3kYPw1ApqCoJyedZtCWJJXHJnEnPITTQl7ExLRjfK4xOzRq628Rycy49h28TjrEk7ii/HExFFaLDGjGmewv6tw1m/6kLxB05y29HzpJw9DzZuRYAghv42J1H91aN6B7WmCZmQ6ShhlMpDsO2C/sWoK2qPisirYFmqrqx8kytPIzDcB/ZuRZW7T7JotgkVu46Sa5FiWrRkPE9w7g+pgXBl/i628QyycjOY8WuEyyJO8rq3SfJyVPahDRgTPcWXB/TgrahlxRbLzvXwp4TaXYH8lvSWfaevED+f7Pw4ACbA2lMTKtGRLVohJ+32ddiqDlUlsOYA1iAYaraWUSaAN+rap/KM7XyMA6jZpB6IYulvx1l0ZYkEpLP4+UhDO3UlPE9wxjWqSk+XjVnyCo3z8L6/aksiUvmu4TjXMzOo2mgL9fZnES3lo3KNcR0ISuXbUnn+C3J5kSOnOXouUwAPD2ETs0CbT0R63CWmQ8xuJPKchhbVLWniGxV1R62tN9UtXsl2lppGIdR89h9PI1FW5JYvDWZU2lZNAnwZkx365BVeV/GFUVV2XL4LEvjklkWf4zUi9kE+nlxTdfmXB/Tgn5tg6vk5X3yfCa/JZ2z90J+O3KW85m5gG0+pGUjYhyGs1o2NvMhhuqhshzGr8BlwCab4wjF2sPoUXmmVh7GYdRccvMs/LQvhUWxSXy/4wTZuRYim17C+F5hjOvRkksb+lW5DXtOpLEkLpklcUdJOpOBr5cHV3a+lDExLRjSMRRfr+odJrJYlMTUizbnYe2NbHeYDwm5xMc+lJXfG2kcYOZDDJVPZTmMW4BJQC9gLjABmKmqn1eSnZWKcRi1g3MZOXwdf4xFW5KIPXQGD4GBkaGM79mSq6OaVer4ftKZdP732zGWxCWz63ganh7C5e1DuL57C66KupRAv5q1HDg718Lu42nEOQxl7Tv1+3xIRHCAw6R6Y6JaNDTzIYYKU2mrpESkEzDcdrpCVXdVgn1VgnEYtY+DKRf5cksSX25JJvlsBoG+XlzbvTnje4bRK7xJuYZkTl/M5uttx1gal8ymRKuOec/Wjbk+piXXdGtOaGDNn4B3JC0zh23J56y9ENtw1jHbfIiXh9DRNh8SY3Mi7ZteYuZDDC5RIYchIoV3Y+d/+xRAVcdU2MIqwDiM2ovFovxyIJWFW5JYnnCc9Ow8IoIDuKFnGDf0bElYk4BS61/MyuWHHSdYEpfMT3tTyLUokU0vYWyPllwX3YLWwaXXr22cOJ/pMBdiHc5Kc5gP6ZY/H2I7WjTyM/MhhhKpqMM4hTWC7HzgVwoFCFTVNZVkZ6ViHEbd4GJWLt8mHGdRbBIbDqQC0L9tEON7hnFNt+Y08LUGK8jOtbB2zymW/HaUH3YcJzPHQsvG/vYVTp2aBdabl6TFohxMvWgfxopLOsfOo+fJzsufD/ElxrYvpHurxkSb+ZA6gaqy63gaq3ef4hI/L27t70ps2N+pqMPwBEYANwHRwNfAfFXdXi5rqgnjMOoeSWfSWbzFuqs8MTUdf29PRnVthq+3J98mHONseg5NArwZHd2c62Na0qt1EzzMcAwAWbl57DqWxm9JZ+17RPaf+l1huU1IA7qHNSLazIfUKtIyc1i/L5XVu0+yevcpjp+3Dk+O6tqMOX/oVa42K3MOwxer43gJeFZV3yiXRdWAcRh1F1Ul9tAZFm1JYtlvx8hT5aoul3J9TEsGRobgXcfCkVQV5zNzCu0POWd/4Xh5CJ2aB/6+MiusMREhAdW+esxQEFVl78kLrNpldRCbEk+Ta1ECfb0YGBnC0I5NGdwxtEIrDSvsMGyOYjRWZxGBNarsB6qaXG6rqhjjMOoH2bkWLKrm13Alcfxc5u8OJOks8UfOkZZlnQ8RgeYN/WgdHEB4UANaBwfQOiiAcNt5o4CatcqsrnAxK5ef96eyavdJ1uw+RfLZDAA6NQtkSMemDOkYSq/wJpX2Q6miQ1IfAV2Bb4EFqlorwoobh2EwVByLRTmQcpFtyWdJTEnn8GnrcSg1nZQLWQXKNvL3JryQE2ll+9ysoZ8ZHnQSVWX/qYv2YaaNB0+TnWehgY8nl7cPYWinpgzuEEqLxv5lN1YOKuowLED+YKdj4XxN7xoZVc44DIOharmYlWt3HodPX7T9tZ4nn80gz0Fgy8fLg1ZN/AkPbvC7QwkOoHVQA8Ka+Nf7HmJGdh4bDqSwatcpVu85yZHT1l5EZNNLGNIxlKEdm9I7IqhaQumU5jDK1MNQVTMgbDAYitDA14vOzRvSuXnR34y5eRaOns3kUAFHYv38y4FU0rPz7GVFoFlDPwdH0qBeDHUdTLH2IlbtPsUvB1LJzrXg7+3J5e2DuWtQO4Z0CKVVUM1aAu6KgJLBYDA4hZenh3WOIziAKyIL5qkqKReybcNbNoeSms6h0+ms3HWKlAtJBco38vemdVCAbe7k955JbRvqyszJ45cDqazefYrVu0+SmJoOQNuQBvyhXzhDO4XSJyKoRve2jMMwGAzViogQGuhLaKAvvcKbFMnPH+o6fDrfkVidSkLyOb5LOE5uKUNdjsNdYU0C3P7yPZyazuo9J1m16yQbDqSSmWPB18uDy9oFc/vlbRjSMZTw4AZutdEVjMMwGAw1CmeHuuwOxdY7+fVAKhfLGOpqFfR7L6UqNitm5eax8eBp+1zEAdtel/DgACb3ac2QjqH0bxvsdkdWXozDqAQsljwObo3lZOJ+mka0o02PXnh41M4vhMFQk3Ec6iqMqpJ6MbvIJPzh1HRW7T7FqbSCQ10N/bysPZMKDnUlnUm3DzOt35dKRk4ePl4e9GsTZBtqakqbkNrTiygN4zAqiMWSx6LnZnFs325ysrLw9vWlefuOjH/yWeM0DIZqREQIucSXkEuKH+pKz3ZY1eUw1LW9uKEuTw/CgvxtjqTgyq5LG/qxLekcq/ecYtWuk+w9eQGAsCb+TOgVxpCOoQxoF0yAT917vda9O6pmDm6NtTqLTOsO2ZzMTI7t3c3BrbG069XXzdYZDIZ8Any86NSsYbH68rl5Fo6dy7QNb10sMNS18eDpAkNd+Xh7Cn3bBDGpTyuGdAylXegldT5emXEYFeRk4n5ysgpuYMrJzuJU4gHjMAyGWoKXpwetggJoFRTAQEIK5Kkqpy9mc8g2vJV8NoPIppdwWfsQLvGtX6/Q+nW3VUDTiHZ4+/raexgA3j6+hEa0dbkti0U5nJDKqSNphLYKpHXX4FqzZNBgqKuICMGX+BJ8iS89Wxcd6qpPGIdRQdr06EXz9h05tnc3OdlZePv40jyyI216uBYp0mJRlr4Wx8nE8+Rk5eHt60nTiIaMeTDGOA2DwVAjMA6jgnh4eDL+yWc5uDWWU4kHCI1oW65VUocTUu3OAiAnK4+Tiec5nJBKRHRIGbUNBoOh6jEOoxLw8PCkXa++FZqzOHUkze4s8snJyiMlKc04DIPBUCMwcaJqCKGtAvH2Ldgr8fb1JCQs0E0WGQwGQ0GMw3ATalEydqZyfsVhMnam0qpLEE0jGtqdhrevJ6HhgWT6pLJmzRp2796NxWJxs9UGg6E+U61DUiIyEngN8ATeU9V/FsoXW/41QDowVVW3OFO3NqEWJeX9bWQfSUOzLYiPBz6tArnu/u4c2XGalKQ0glo24Ke4b/nyy2Sys7Px8fGhZcuW3HrrrXh41G4/r5pHauoa0tK2ExgYRXDwYKxKwAaDoSZTbQ7Dpg0+G6s+eBKwSUSWquoOh2KjgEjb0Q+YA/Rzsm6tIXP3abuzANBsC9lH0sjee4aI6BAiokPYvXs3yclWZwGQnZ1NcnIye/fupWPHju40v0Ko5rE1birnz8eRl5eBp6c/DRvG0CNmrnEaBkMNpzp7GH2Bfap6AEBEFgDXA44v/euBj9Wq6vSLiDQWkeZYZWHLqluA1NRU5s6dWyAtKiqKPn36kJOTw7x584rUiYmJISYmhvT0dD7//PMi+b1796Zr166cO3eOxYsXF8kfMGAAHTt2JCUlhWXLlhXJHzRoEG3btuXMnuNYsvMQfl8ua8nOI2XXUVp1DubIkSN8++23dmeRT3Z2NsePH8fb25u1a9cWaf/aa68lJMTqbDZs2FAkf9y4cTRq1IiEhASKE5e68cYbCQgIIC4ujri4uCL5t9xyC97e3mzatInt27cXyZ86dSoAP//8M3v27CmQ5+3tzS233EJq6hrOnIkFrJsd8/LSSU3dxFdf/Z1x454C4McffyQpqVDcn4YNueGGGwBYvnw5x48fL5AfHBzMddddB8D//vc/UlNTC+Q3a9aMkSNHAvDll19y/vz5AvlhYWFceeWVAHz++eekp6cXyG/Tpg2DBw8GYN68eeTk5BTI79ChA5dddhlAke8d1Jzv3vHjx1m+fHmR/OHDh9OqVSuOHDnCihUriuSPHDmSZs2aceDAgVr73QNYs2YNBw8eLJAfEBDAjTfeCJjvXnHfPUeqc2yjJXDE4TzJluZMGWfqIiJ3ichmEdlc+KHWKEJ9yZOCSod5ohDye/RMHx+fImEGvLy8aNasWbWYWFWkpW0HCjpCkRy8vI65xyCDweA0ZUq0VtqFRCYCV6vqnbbzW4G+qnq/Q5mvgedVdZ3tfAXwONC2rLqFqckSrSXNYYRM64bYNulZLBY++eQT+7BUXZnDSElZScL2B8nL+/1XlKdnAF2jXiMkZJgbLTMYDFBBidZKJAlo5XAeBhx1soyPE3VrDeIhhEzrRubu0+QcvYh3iwb4dQyyOwsADw8Pbr31Vvbu3cvx48dp1qwZkZGRtdpZAAQHD6Zhw5gicxjBwYPdbZrBYCiD6uxheAF7gOFAMrAJuFlVtzuUGQ3ch3WVVD/gdVXt60zdwtTkHkZ95/dVUjsIDOxiVkkZDDWIGtHDUNVcEbkP+A7r0tgPVHW7iNxjy38b+Aars9iHdVnt7aXVrS7bDZWLiCchIcPMEJTBUMuoth5GdWN6GAaDweA6pfUwaveAuMFgMBiqDeMwDAaDweAUxmEYDAaDwSmMwzAYDAaDU9TZSW8ROQUccrJ4CJBSheZUBcbmqqe22QvG5uqittnsir3hqhpaXEaddRiuICKbS1oVUFMxNlc9tc1eMDZXF7XN5sqy1wxJGQwGg8EpjMMwGAwGg1MYh2HlXXcbUA6MzVVPbbMXjM3VRW2zuVLsNXMYBoPBYHAK08MwGAwGg1MYh2EwGAwGp6j3DkNERorIbhHZJyJ/cbc9xSEiH4jISRFJcEgLEpEfRGSv7W8Td9roiIi0EpFVIrJTRLaLyIO29Jpss5+IbBSR32w2P2NLr7E2A4iIp4hsFZFltvOabm+iiGwTkTgR2WxLq+k2NxaRhSKyy/adHlCTbRaRjrbnm3+cF5GHKsPmeu0wxCrCMBsYBXQBbhKRLu61qljmAiMLpf0FWKGqkcAK23lNIRd4RFU7A/2B6bbnWpNtzgKGqWp3IAYYKSL9qdk2AzwI7HQ4r+n2AgxV1RiHfQE13ebXgOWq2gnojvV511ibVXW37fnGAL2wSkUspjJsVtV6ewADgO8czp8AnnC3XSXYGgEkOJzvBprbPjcHdrvbxlJsXwKMqC02AwHAFqwiXjXWZqzKkyuAYcCy2vC9ABKBkEJpNdZmoCFwENsCodpgcyE7rwLWV5bN9bqHAbQEjjicJ9nSagOXquoxANvfpm62p1hEJALoAfxKDbfZNrwTB5wEflDVmm7zv7Fq3lsc0mqyvQAKfC8isSJyly2tJtvcFjgFfGgb+ntPRBpQs212ZDIw3/a5wjbXd4chxaSZdcaVhIhcAiwCHlLV8+62pyxUNU+t3fgwoK+IdHWzSSUiItcCJ1U11t22uMjlqtoT6zDwdBEZ5G6DysAL6AnMUdUewEVq0PBTaYiIDzAG+KKy2qzvDiMJaOVwHgYcdZMtrnJCRJoD2P6edLM9BRARb6zOYp6qfmlLrtE256OqZ4HVWOeNaqrNlwNjRCQRWAAME5FPqbn2AqCqR21/T2IdV+9LzbY5CUiy9TYBFmJ1IDXZ5nxGAVtU9YTtvMI213eHsQmIFJE2Nm88GVjqZpucZSkwxfZ5CtZ5ghqBiAjwPrBTVV91yKrJNoeKSGPbZ3/gSmAXNdRmVX1CVcNUNQLr93alqv6BGmovgIg0EJHA/M9Yx9cTqME2q+px4IiIdLQlDQd2UINtduAmfh+Ogsqw2d2TMu4+gGuAPcB+4El321OCjfOBY0AO1l8804BgrBOee21/g9xtp4O9A7EO7cUDcbbjmhpuczSw1WZzAjDLll5jbXawfQi/T3rXWHuxzgf8Zju25/9/q8k22+yLATbbvhtfAU1qgc0BQCrQyCGtwjab0CAGg8FgcIr6PiRlMBgMBicxDsNgMBgMTmEchsFgMBicwjgMg8FgMDiFcRgGg8FgcArjMAwVQkRURF5xOH9URJ6upLbnisiEymirjOtMtEUhXVXO+jEick1l21XXEJGfnSjzkIgEVIc9BtcxDsNQUbKAG0QkxN2GOGKLROws04A/qerQcrYXg3WfidOIiJcr5cuDi8+gylHVy5wo9hDWPQSGGohxGIaKkotVL/jhwhmFewgicsH2d4iIrBGRz0Vkj4j8U0RuselRbBORdg7NXCkiP9nKXWur7ykiL4nIJhGJF5G7HdpdJSL/BbYVY89NtvYTROQFW9osrBsN3xaRlwqVL9CeWDUzPrS1sVVEhtoiBDwLTLJpD0yy6Q58ZbPtFxGJtrX3tIi8KyLfAx8XulaE7T632I7LbOmfOfZebM90vCvPwGZLrFh1Pu5yaGua7bmuFpH/iMibtvRQEVlka3uTiFxezLOcKiJLRGS5WPVknnLI+7PtGSeIyEMl/Puvlt81JuaJlQeAFsAq2z142u43wfbMi3zHDNWMu3ckmqN2H8AFrCGgE4FGwKPA07a8ucAEx7K2v0OAs1hDLPsCycAztrwHgX871F+O9YdNJNZd7n7AXcD/2cr4Yt2F28bW7kWgTTF2tgAOA6FYA8qtBMba8lYDvYupU6A94BHgQ9vnTrb2/ICpwJsO9d4AnrJ9HgbE2T4/DcQC/sVcKwDws32OBDbbPo8DPrJ99sEaXdnflWeAbUevrV4C1h2/LWz/ZkGAN/BT/j0A/wUG2j63xhripbC9U7FGHwh2aLc3Vv2FbUAD4BKsO7p7FPPvfw5r7DYPYIPD9RKxhT+3tfWDwzUbu/v7Xt+PKu8WG+o+qnpeRD4GHgAynKy2SW2hlkVkP/C9LX0b4Dg09LmqWoC9InIA64v6KiDaoffSCOtLNhvYqKoHi7leH2C1qp6yXXMeMAhrqIfScGxvIFZngKruEpFDQIdi6gwExtvKrRSRYBFpZMtbqqrFPSNv4E0RiQHyHNr9FnhdRHyxBkNcq6oZIuLKM3hARMbZPreylWsGrFHV07bn8YXDNa8EuojYgzk3FJFAVU0rZPMPqppqq/8lv4eEWayqFx3Sr8AadsWRjaqaZCsTh1XvZV2hMgeAtiLyBvA1v39HDG7COAxDZfFvrKJDHzqk5WIb9hTr28fHIS/L4bPF4dxCwe9l4dg1ijUs/f2q+p1jhogMwfrrujiKC2XvDI7tOdtGaWHz81+k44D8YZw7gWuBE1gV3TyATABVzRSR1cDVwCR+Dybn1DOwnV8JDFDVdFtbfmXci4etfFnOv6R/G2dw/PfPo5h3kaqeEZHuWO99OnAjcIeT7RuqADOHYagUbL9UP8c6gZxPItZhBYDrsf6KdpWJIuJhm9doi1U17DvgXrGGUEdEOog1+mlp/AoMFpEQsU4G3wSscdGWtcAt+dfEOlyzG0gDAksoNwRI0UJ6IKq6WG0ymqq6GWsP4ZitN3Ur4DhhvQC4Hesv9XwH4ewzaAScsTmLTlglcwE22p5HE7FOwI93qPM9cF/+ia3XUxwjbPM1/sBYYL3t3seKSIDNnnFYh7ucxf4sxbqQwkNVFwEzsYYVN7gR08MwVCav4PCiAf4DLBGRjVijY5b06780dmN9sV8K3GP7xf0e1iGMLbaeyymsL6wSUdVjIvIEsArrr+BvVNXV8M5vYZ0c34a19zRVVbPEuhz3L7ahleexzlV8KCLxWPWUp5TQXuG2F4nIRJuNjs8qf5J8qapm29KcfQbLgXtstuwGfgFQ1WQR+QdWR3oUa8juc7Y6DwCzbXW8sDqBe4ppex3wCdAe+K/N8SEic7E6JID3VLXwcFRpvAt8KyLHsK6Y+lBE8n/YPuFCO4YqwESrNRjqKSJyiapesPUwFgMfqOpiJ+tOxbpQ4L6yyhrqDmZIymCovzxt6xUlAAcpewGAoZ5jehgGg8FgcArTwzAYDAaDUxiHYTAYDAanMA7DYDAYDE5hHIbBYDAYnMI4DIPBYDA4xf8D2vn+ixTGZYIAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "grid_models = [EqGridRotorAvg(i) for i in range(1,10)]\n",
+ "wd_lst = np.arange(240,301)\n",
+ "\n",
+ "def get_ws_eff(rotorAvgModel):\n",
+ " wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=rotorAvgModel)\n",
+ " return wfm([0, 200], [0, 0], wd=wd_lst, ws=10).WS_eff_ilk[1,:,0]\n",
+ "\n",
+ "ws_ref = get_ws_eff(EqGridRotorAvg(200)) # Use 200x200 points (31700 inside the rotor) to determine the reference value\n",
+ "\n",
+ "def get_n_err(rotorAvgModel):\n",
+ " ws_mean_err = np.abs(get_ws_eff(rotorAvgModel) - ws_ref).mean()\n",
+ " return len(rotorAvgModel.nodes_x), ws_mean_err\n",
+ " \n",
+ "\n",
+ "plt.gca().axhline(0, color='grey',ls='--')\n",
+ "plt.plot(*zip(*[get_n_err(m) for m in grid_models]), label='Grid_x')\n",
+ "model_lst = [('RotorCenter', EqGridRotorAvg(1)),\n",
+ " ('Grid_4', EqGridRotorAvg(4)), \n",
+ " ('PolarGrid_4,10', PolarGridRotorAvg(*polar_gauss_quadrature(4,10))),\n",
+ " ('GQGrid_4,3', GQGridRotorAvg(4, 3))] + \\\n",
+ " [('CGI_%d'%n, CGIRotorAvg(n)) for n in [4,7,9,21]]\n",
+ "for name, model in model_lst:\n",
+ " n,err = get_n_err(model)\n",
+ " plt.plot(n,err,'.',ms=10, label=\"%s (%.4f)\"%(name,err))\n",
+ "plt.xlabel('Number of rotor-average points')\n",
+ "plt.ylabel('Mean abs error (270$\\pm30^\\circ$) [m/s]')\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Deflection models\n",
+ "The deflection models calculate the deflection of the wake due to yaw-misalignment, sheared inflow etc. \n",
+ "Note, this is one of the four effects of skew inflow that is handled in PyWake, see [here](https://topfarm.pages.windenergy.dtu.dk/PyWake/notebooks/YawMisalignment.html).\n",
+ "The deflection models take as input the downwind and crosswind distances between the source wind turbines and the destination wind turbines/sites and calculate a new set of deflected downwind and crosswind distances."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def plot_deflection(deflectionModel):\n",
+ " from py_wake import IEA37SimpleBastankhahGaussian\n",
+ " from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines\n",
+ "\n",
+ " site = IEA37Site(16)\n",
+ " x, y = [0, 400, 800], [0, 0, 0]\n",
+ " windTurbines = V80()\n",
+ " wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=deflectionModel)\n",
+ "\n",
+ " yaw = [-20,20,0]\n",
+ "\n",
+ " plt.figure(figsize=(14,4))\n",
+ " fm = wfm(x, y, yaw=yaw, wd=270, ws=10).flow_map()\n",
+ " fm.plot_wake_map()\n",
+ " fm.min_WS_eff().plot(color='k', ls='--')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### JimenezWakeDeflection"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The `JimenezWakeDeflection` model is implemented according to Jiménez, Ã., Crespo, A. and Migoya, E. (2010), Application of a LES technique to characterize the wake deflection of a wind turbine in yaw. Wind Energ., 13: 559-572. doi:10.1002/we.380"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 1008x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deflection_models import JimenezWakeDeflection\n",
+ "plot_deflection(JimenezWakeDeflection())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### FugaDeflection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 1008x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deflection_models import FugaDeflection\n",
+ "plot_deflection(FugaDeflection())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Implement your own deflection models\n",
+ "\n",
+ "Deficit models must subclass `DeficitModel` and thus must implement the `calc_deflection` method and a class variable, `args4deflection` specifying the arguments required by its calc_deflection method\n",
+ "\n",
+ "```python\n",
+ "\n",
+ "class DeflectionModel(ABC):\n",
+ " args4deflection = [\"ct_ilk\"]\n",
+ "\n",
+ " @abstractmethod\n",
+ " def calc_deflection(self, dw_ijl, hcw_ijl, **kwargs):\n",
+ " \"\"\"Calculate deflection\n",
+ "\n",
+ " This method must be overridden by subclass\n",
+ "\n",
+ " Arguments required by this method must be added to the class list\n",
+ " args4deflection\n",
+ "\n",
+ " See documentation of EngineeringWindFarmModel for a list of available input arguments\n",
+ "\n",
+ " Returns\n",
+ " -------\n",
+ " dw_ijlk : array_like\n",
+ " downwind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
+ " for all wind direction (l) and wind speed (k)\n",
+ " hcw_ijlk : array_like\n",
+ " horizontal crosswind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
+ " for all wind direction (l) and wind speed (k)\n",
+ " \"\"\"\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.contour.QuadContourSet at 0x2b6eb12eac0>"
+ ]
+ },
+ "execution_count": 49,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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vcz/mI1BlOVyZDa1/ioi/6FShyNxCDkFm1lGRMQKVOX7pj1KgyhpEuHKwsu2hzDFBgxQRHyijzgL6tWFmC1W3X4yNiL5ffbexUd5rIapHFH6ZLRaSzpG0XImLJd0q6XVF93dPkJl11Awo/QaVbr1FZQShufZItRrVHiqzEXRaRFwg6VhgD5JH6S8Bri2ys0OQmXXUzzjJSiaTDDpElXGOoufpRVmBymHKBi0CasPXk9j8C/sG4JKIuF09TLjlEGRmHTXmmIIqFZUWoGD7hKgyztPr+YpaqLfpzObZLZKuBVYD50naBSj8t8UhyMw6SsbsJO9bg0nnHed2vkp6kjIDVHK87ROi5ut8Zv0KgtqQpG1JYxFRA04HXgHcGxFPS9qdHmaXdggys45q9ekv8+yvx0qXRNQMAT0Fp9aT9CDbnrIDVHLM4QpRZiPuRknjwNXA1RHxOEBEbAG2FD3IwEOQpPuBJ4E6UIuINZKeA/wLsC9wP/BfI+I/Bt0WM+tdPYIIaP0Or9dnfkm3e4S7l+AEyZd/z8Gp9UQ9aG3TIAJUcty5H9i9Qra9DMtciWmWeAHJKvWflLQP8B3g68D1EbGtyHG2V0/QayPiscznc4HrIuKjks5NP39wO7XFzHrQGnaaWsND64DKvO/t7LE6zXvTa3CCuYWnijTnMU9QXoDq1m73CpnNFhE/BdYCayUtAX4NOA74S0mbI+KN3Y4xX7fDjgeOSt9fCnwbhyCzBakRs7+EKxKNnHDU6ct8LqEJpoNTkckCGznn6Vh/jr1OzZ6ZfgaNz2zHnA6TtmXu+5plRTA0Y4JaRcQk8K30Rdoz1NX2CEEBXCspgE9HxDpgz4h4GCAiHpb03O3QDjObg1q9MetLuqKcANTmabCpwFBvDVKdz9tvaILBBKdE76kle0trLuGpXRuH5faFLT6SdgUuAg4m+UtzWkR8L7N9N+AzwAuBren2O4rsmznGm4CPkAyvqZI8Mh8RsbxIG7dHCDoiIh5Kg843JN1VdEdJZwBnAKxatWpQ7TOzDmqN2TM6541RqeQGIGjkBIZugQl6C03tAkIzOHXLQr30NnVtTJvqc72l1W+vk1lRAbS5+z1XF5AMWj5J0lJgx5btHwI2RsSJkl4C/D1wdMF9mz4JvBX4YUTvf8kGPv1WRDyU/nwUuBI4DPi5pL0B0p+Pttl3XUSsiYg1e+yxx6CbamY5JmoNJmoNavWYerV+niprtL5i1qsRyRNnn13397xq/714xeoV/NVf/HcajaBWb8x4ZZfVyDtO89XalkZj5qten/mKIPfVPHa3ZSkm6w0m641Z52n3qtVntrfIq2k+liAx65ek5cCRwMUAETHRfIIr4yDgunT7XcC+kvYsuG/TA8AdcwlAMOCeoHQF10pEPJm+fx3wF8BVwKnAR9OfXxlkO8xs7pIv8KB5C2i6tyb9nP2nVKO1lyhm9RpV0i6jnZc/m//7gov40hc+yzVf/RLv+9DsBaHb9S4lp2rpKerwiHxrG7K9TL3elssq2tMESW9TT4ugzmGwj8cH2QKyH7AZuETSIcAtwDkR8VSmzu0kvTjfkXQY8AJgJcnT5N32bfoA8DVJ1wNTT4RFxCeKNHLQt8P2BK5MZ7AeAz4fEVdL+j5whaTTgZ8BbxtwO8xsjp6p1TNz/kx/y45NpxEgeyupNfhEblB6+KEHWf3ig7j3nrtZtfpFM+YjgiRc5Q7IbnMbrdNA7YUQmGCwoanfGbrNApisFx4YvULShszndemY36Yx4FDg7Ii4SdIFJE+C/2mmzkeBCyRtBH4I3AbUgCUF9m06H/glsAxYWrTx2UYOTETcCxySU76F6ft+ZraAPV2rdQ5BwJimU07RoLTbHnvxj3/7VzxnxZ7stMuzmag1uvQq5YeQdmEJ2gecTuONsoGp21Nc/QSmvOO3qkUUCkzJyQvWMyvHYxGxpsP2cWA8Im5KP68nCTJTIuIJ0tmd0/W+7ktfO3bbN+M5EVF41fhWnjHazDr6/voLOfD43wVgLP1GrkhM1JPtYxUxkX4DtwagifSLORuSmvUe+Nn9fPffriUaDfY74CAmGw1otA5O7tKrBFQiZ5D2dghLUDwwtZvssHn87R6YzHJEBJMldSdGxCOSHpB0QETcTdLx8aNsnfQJsKcjYgL4b8ANaTB6otu+Gd+U9LqIKLRqfCuHIDPr6unJGgBjlWyPD7PKxjLfwjMDUWNW+X8984/4rT/446nyifrsOtP7z+iq6RKUpscdzSgbYFiCufcutR63jMBktkCcDVyWPt11L/BuSWcCRMRa4EDgc5LqJCHn9E77tjnHWcAHJG0DJlmAj8ib2ZB7fGudagWgzpL0W3hJtRl+GlRzAlE2JE33CM0MSUV6k4DcHqXeglK7wJM3CSSzy2aNKUpP02HqgHbBpp/epexxvZSGlS2A4kOCChwvYiPQestsbWb794D9e9g3r94uc2+hQ5CZFfDktiQZNIPFkqqARvoTmnloSabHpxmSqpoua4ak7Hd70ZAEMEGjbfiZaOTfdsur21SNcoLSVHmJYQk6jzHqFpbMRpmkvSLikX7rOASZWVf/8XSNsTTwNHuCqpVsIGoNSLCkmk5AmMklzZC0JFPYDEljlQoTaVnRkAQwUS8WkmB2UOoWkqBoUGq3tAizyqA1wExvzx5jViAqEJachawfETBZ8myJA/Q1kifI+qrjEGRmXT2Vdsk0g0+zR2cs/QKfa0BK6pLum9eLND1WqIyQBLODUqeQlD1OXv3mtRW9hTbXoNTcv6ldWPIj8raIHCLpiQ7bBXTaDjgEmVkBTzw9CSRhpzUIVaszg89YpdI2HGXrtQtIyfuivUizQ1JrQAJKC0kAjegekuotYadIUOp26yy7/4zg06ZXyWyURUS1jOM4BJlZV08+MzkdcqrNn5WpL+OxTBDqFI6Sn8zYp7X3CPID0tb0yz4/IDXHKLUPSEDHkDTWEmbKCknZY2X3yQaldiEJ8kNO256gnLFKZkUlkyUuru5EhyAz6+rJpyeoNm9RVZQJPZUZ4WisWgHqueEIktDRLRxl98u7vbY1eVq/54CUbJ++zQZJSGoXkLJtaw1J2eBRKCRlvlfGVGFi1hNi5fQmgXuDzHrhEGRmXT399CSViqYDTLUy9URStTozCFUr02GpWTZWbT4V1pgqm1Fnjr1H2brNgJR9NL4ZkJo9S1tr9a4BCYqFpOx0AI1Zg6fbh6SaZoaWoiGplqnUPF5rbxK4N8j6EMwK36POIcjMutq6NRkT1Aw/zV6hTsEIZvcatZaVGY6aPUTZ3qOttfzeIygakCDvNhsUD0gwMyTNfupr5ucyQpLZqJP0nE7bI+IXRY7jEGRmXT311OSM8FOtzg4/7YLRdNnsHqK8XqPk59zD0Vai0K21bEBqDUdAaQEJoNbmNht07kXK214kJJnNxZCNCbqFpMkCVgH/kb7flWRh9tVFDuIQZGZdTWxNHk5XRVSrVSot4WY69LSGod6DUfJ5Zq/RRC0bjMQ2Gknd2swA1Jx1ekY4qrUPR1trs2+tNcMR0DYg1TPPpUxm7j9lj7UkU6faEoKyj7J3Ckhj0oxenyQgzbwt1rq9hu+H2eiLiNUAktYCV0XE19LPrweOKXochyAz6+qZp56hWq1OhSCASrUy6/OMcULVzsGnczBqdAxG2fLcXqOccFStim3p9cwlHAHUo3M4KtZ7tH0CklmvIoL68E029SsRcWbzQ0R8XdJHiu7sEGRmXU1snaBSrVCtVqlVkgE2nUJRbbKeG4qS9/ljiKbfFwtGE7UkGG2bnF3erdcIZoejqW19hCOAyfrscARFe48q1DOLN2UD0lilMmOR2VrLNhbZgFaz1GOS/jvwzyT/CngHsKXozg5BZtZVbds2qFTTYFOhUq1Qm6xNhaJqtQqT5IYiIPcWGmkAqVbF5GR9VuiZnGzMCEbVaoXJdPvEJH0FI4B6c9bqll6j7LZsOBprJNuy4Wgsc9us7HAEc+s9MpurACaH73+mU4A/B64kuYQb0rJCHILMrLuJZ6C6hMYkNKpjU4GokfZMNHuJgKlQpPp0AIpGzAhJzZ6iej3b69M+FE1Ozu4tatYpMxi1G2sETPUaJdc4s9coKcuM1ckJR9leqCLhaElVU7cmqpW59R6ZzSdJuwIXAQeTBJTT0pXjm9tfAlxCsr7XhyPir4vu25Q+BXaOpJ0j4pe9ttEhyMy6m9yavKpLkq6L1kDUSHqGmr1EkX55q6JZAaieBqBsSOoWigAa6TGzoaiejolprVNv9sQ0muOIkvJmOGmWtwYjmJ7xeVYwAqqNmcEIpnuNaplg0uw1Sspnnjs5/+xeIygnHE1itmBcAFwdESdJWgrs2LL9F8B7gRPmsC8Akv4LSVjaGVgl6RDg9yLiD4o00CHIzLqbSIcUV2tQHUtm5KtUoT6ZBKJG8qukkQaibA/RrEAEs3uJ0rJmb9JUmMmEomo1P/BkQ1HzFlq3UJQ38Lq5rVafHVpag1E9uwBsh2BUrYhac92ynGDUep5mOKpWxOTULNiiXpuuXyQcmc1FxPT///2StBw4EnhXcuyYgKk1kNPzxaPAo5Le2Ou+GX8DHAtclda9XdKRRds5byFI0nEkSa8KXBQRH52vtphZF5Nbk9ADUK9Ph6HqkiQQpb1D1Gs0GmM00rqdAlG1WqXWqLUNRM2ySrVCo1Fv6SViRiiqpnUqFVGvQyMNHO16ipr1oHtvUbUiamnl1t4i6DMYVSrU0jaNVfIDWGuvUV44qkrDNL+LLQ77AZuBS9LemVuAcyLiqbL3jYgHNHN+rcLzRMxLCJJUBf4e+A1gHPi+pKsi4kfz0R4z66Ke3mRp9gBNladhqHVbWt4AGvXG1KDoqfd1iEYkA6frzAhE1WoV6kloag1JlZaw07wl1qmXKPmcH4paw1O1WsncapoZSKqV6W2tYWWsWmEiDSQViVo9GKuKenqrqjX4NNvQbnu7YNQctLqkkr0lNjMYmfWj1uheJ7VC0obM53URsS7zeYxkrM/ZEXGTpAuAc4E/LXDsXvZ9IL0lFults/cCm4pexHz1BB0G3BMR9wJIuhw4HnAIMluI6s11J5bMaXGq1jA0fdwk3NTTf7hVScNQRdTr9RmBqE59qqyRluUHoua+0+Wt9RqNSD9P14PZPUXNUNTaG1RvdA5FMPMWWnZ7vVGfFXqy4ayMYGS2HTwWEWs6bB8HxiPipvTzepIgU0Qv+55Jcldpn3S/a4GzCp5n3kLQPsADmc/jwK+2VpJ0BnAGwKpVq7ZPy8ysvXQM0FQQqi5hKkFUx6Z7jJrjhVq0+0dmlaQHKRuGsp/TD9O9Q5mQVFYgAjrWhdmhaPrW2XQoao41ym5vPoU2UYvcUATToWfqMf20/cnx69PHzdSpNaYf12/2PpnNVQC1RvGuoI7HinhE0gOSDoiIu4GjKdjR0cu+EfEY8Ntzbed8haC8v6mz/gmTdq2tA1izZo3/iWO2UGRviTXl3RprhqbMtmaPUKPRoFKZHjMEBcMQUKGSWw7TA59nfia3vDUQzbiclkCU3b+1lwimQ08zEAG5vUjJz5mhKNk//xZar6HIbAE5G7gsvU11L/BuSWcCRMRaSXsBG4DlQEPS+4CDIuKJvH3zTiDpxcCFwJ4RcbCklwNviYi/LNLA+QpB48DzM59XAg/NU1vMrJvmIGiYDkDNz9XqdJ1u0nCUF4SSR+TrUwOks709rZ+b9duVN6bCQLcwlN3Wru70tk6BKCuvl6jddsgPRU3tAk+7UGQ2V2UvmxERG4HWW2ZrM9sfIfn+L7pvnn8E/gT4dLrfDyR9HljQIej7wP6SVgMPAicDvzVPbTGzbqpLuoef1pA0o+7YjG3Ts0cXX/G8lyDUPMf02J/GjHmFpppXVWaiwZnhpjojTGXlhaVOAaqX7Z17iaBYKDJbRHaMiJtbng6rFd15XkJQRNQkvQe4huQR+c9ExJ3z0RYzK2DJsuRnXq9Pux6ibL1MMGoNQNnB0s15gpTTq5FX1tQahIAZvULNIJScIzteKDMgOQ1Krb1I2bLkODEjPOXtk15psr2izNwreT1QrWYHIoBa2/HoRY5pNrIek/RC0iE1kk4CHi6687zNE5Que/+1+Tq/mfVg6Q7Jz2zA6dTj07I9r+enW/hplrUrz+7fKSC1k9dz0gxCQG54mi6bGZ6y25PrzOthapXul3nKrF0dmEsgMutda2/pEDiLZOzwSyQ9CNxHDwOlPWO0mXU31ROU08sDuYEHuoce6C34tB6nSJ3KjDrZNuQHp2wQyjPzabLMuJycANVaPnMgdXMgdGZgeKUyY/6f7FNktTRUjVUrNGLmnERmi1U61c4xknYCKhHxZC/7OwSZWXfLdp7xsV3Qad0G7YNNL9s69foUCT9JvfwA1BqGOgWgpn6DEMwOOcm2xqwny4CuYQgciKx/EeU9Ir+9SNqdZBX515BMmPgd4C8iYkuR/R2CzKyrpcuWzirLho+mTgGlyHaYHaLa9fbk1e0UfJLPxcNPux6k2dva34prF4RazRz4PDMIAbN6j5L302EImNE7ZLaIXA7cAPxm+vm3gX8Bjimys0OQmXW1w7IdcsvbjcUpEm7a7V90314CT7uyTuGm2Pbe6heVDULJ59m30Zpq9caM8ULZ3iGzXgQM46zjz4mIj2Q+/6WkE4ru7BBkZl3l9QRB9wHJeYGmKS/YQPvgkNeLUiTotNs37zxFQkyR22ddA1rL9l5neu4WhMwWkX+TdDJwRfr5JOBfi+7sEGRmXTVD0Fx6NoqMsUnqtT92523tj18k6HSuW16ggtnhB2YHoNaJFfP28/IYNggRMYzjyn4P+EPgn0hWo6gAT0n6QyAiYnmnnR2CzKyrnXZa0r1SB0WDUKsioavbsTsdYy7hqqeeqgKhZ7ru3Pd3L5AtVhGxSz/7OwSZWVc77ph/O2w+9TI7cpEQ1i1wdTpGuyUregk8vR6nXfDxwGjrx7CNKZN0BLAxIp6S9A7gUOCTEfGzIvs7BJlZVzvtlISgen24Hp9t6rUnqsg6XN1uSbULOt2O3+64nXp7HHxsEbsQOETSIcAHgItJbo39epGdHYLMrKsddyj2q6Je8hwjRccnDGqMTKcgM7tusTZ0a+tcw47HCdkiVYuIkHQ8cEFEXCzp1KI7OwSZWVe7PCt/TFCRrvPaHHqPmuFn6QL5DdVPwCg6Xqdob073HiiHIZubiLn9fZ1nT0o6D3gHcKSkKlB4EOMC+RVjZgvZ8h1n/k5pt75Q/myz04/JF52DpKwnVMoc31D2Ladeg5XDjQ0bSfcDTwJ1kh6bNS3bjwc+QrLoXQ14X0R8J922K3ARcDDJFEanRcT3ck7zduC3gNMj4hFJq4CPF22jQ5CZdfXsZyW/KvLCSa3NPxw7Tb/fLQz1sojjsE3zX9RYD7fisnoZMG6WFZT3D5CM10bEY222XQdcld7OejnJXD8vSbddAFwdESdJWgrsmNvmiEeAT2Q+/wz4XNHGOQSZWVe77DB70sPJnF+WM8PN9Jf4ZJvQ0+kXbrtwNb09qbC07Srt7do1WtxDZMMqIn6Z+bgTSQ5D0nLgSOBdab0JYGIQbXAIMrOudn1WEoLyhgvkhaHcgNTm1lRe3eRc7YNLEqraz0bdy79mu4WtfhXtqZprz49ZaSJ6+QfDCkkbMp/XRcS61iMC10oK4NM525F0IvC/gOcCb0yL9wM2A5ekT33dApwTEU8Vv5hiHILMrKtdls4MHK0ZYzInHeX1/hQNUZ3K6xEsa9POqX3a/GbrpUeoXe9VL2r1cLixUfVY6xifHEdExEOSngt8Q9JdEXFDtkJEXAlcKelIkvFBx5D8DT4UODsibpJ0AXAu8KdlX4RDkJl1tXzpEmotPTnZHo5njVXIywytvSB5uaZdgFq2ZPZtnnYPrjTDz7Kc32jtwtR0m/K3twatbsfJNTbat+JstCQLqJbXNRoRD6U/H5V0JXAYyYrveXVvkPRCSSuAcWA8Im5KN68nCUFTJP0wbXK7c7+8SBsdgsyso197+3vYWq/PetKq1pjZw5H3JFYtZtbJuzW0Q84j5Hn12mWQyXqDZWOzA1OzJ6eXMJUcr00oGutep512QatscwpqZgMgaSegEhFPpu9fB/xFS50XAT9JB0YfCiwFtqSfH5B0QETcDRwN/KjlFG9Kf56V/vyn9OdvA08XbefAQpCk/wH8Lsl9PYAPRcTX0m3nAaeTPDb33oi4ZlDtMLP+LG0zz00tZiaJWkuPRyOC1sU2igWnmHXOvFDUPF1riGrWbe3J6RSisrKBqt0tsWyw6mValX5CSpF9qzlh0KyoZJ6g0oL0niS3uSDJGp+PiKslnZmcK9YCvwm8U9Ik8Azw9oipXwpnA5elT4bdC7x7Zlvjp5AsmxERR2Q2nSvpu7QErnYG3RP0NxHx19kCSQcBJwMvBZ4HfFPSiyOiPuC2mNkc7DBWoZqZI6fZq5F9KqvWCJZmssisXqM0MGWHFuWFpuS4s+sszYyraRecmrIBqt2g5Oypd+hQPxukun035N3WazWXdU6bh13iR99tiETEvcAhOeVrM+8/Bnyszf4bgW5jjgB2kvSazPxC/4XkSbNC5uN22PHA5RGxDbhP0j0k9wnzJkEys3k2VqlQUZIAGhGMMf1l3MwMS9Iv97yAUo+YFZiAvkNTdr+84JSco3h4Ss7XW4DKaoapTk+DLaN7mMqarDem/tuaWa7Tgc9Ienb6+XHgtKI7DzoEvUfSO4ENwB9FxH8A+wA3ZuqMp2WzSDoDOANg1apVA26qmeUZqyrzxS9mfMfPCj9q+QxjLft0C0ww3cs0M9C03y97a64ZnPJCU+v+zfCUV3dppdJxxunWADV9/krXx+KLjJWuNRpUx4olIA8FsrIM20D+iLiFZAHV5YAi4j972b+vECTpm8BeOZs+TLKy60dIRm9/BPjfJOksr0839796OqfAOoA1a9YM15+M2YgYq4hGZP7aVvKCiFrKuoWlvH3mFpigv9AEvQWn6XO2rz/XAJVVZA7E5un9hIstVpJ2IBlbtC8wlo5BIiIGPyYoIo4pUk/SPwJfTT+OA8/PbF4JPNRPO8xscMaqs7/Q8zo6ZgQlmFtYKrzf7MAESWjqFpggCU35vT/t1xtrDU6QhKdeglNTpcu/thsRjFXbTwaZtMf/LrRyRQT14VtA9SvAf5JMqLit150H+XTY3hHxcPrxROCO9P1VwOclfYJkYPT+wM2DaoeZ9WesOjtsNHIWE8370p+1X8xeiLShvLE+s9vRaOScM2fffgMT5D/SXsk5P8BYbhsSecEJmBpj1U63hV9rjWBpyQu6mg2plRFx3Fx3HmQv6l9JegXJra77gd8DiIg7JV1B8sx/DTjLT4aZLVxjFVFPv2+b383ZkSqNNLHMCjcBlWprWfeglNQrFnjadagUDUzt9s8LPNU2waXTHEBzD075+00NKu/wpFi3AGXWSWPIxgQB/5+kl0XED+ey88BCUET8Todt5wPnD+rcZlaeSkXQDCqZ797ml3921fLs92+3oNT8XZsXlFqHAzcaMStkJXXze6Qq1ZyynGCRG5Zy9s+2t1W7oNOIyF3RPfnv1j7kLFX+bbDkFll+GyDb6+QeIltUXgO8S9J9JLfDBIRnjDazUlSUBJXWENAMFTP+5ZgTkiA/KOUFneR8xYJSu2Pk9ki1uX1XPCwVP8ZcjtPcJy80QffgBLQNT2ZFRTCMY4Je38/ODkFm1lHzS7ui/FstzYBSKCTBwIJSti1Jefug1HqM5nEGGXQ6HSdpZ/6x8tqa3a9dcDIbZZKWR8QTwJP9HMchyMw6qmSe1a6gtmMGeg1JzeNB+6DUOt6m+YXf7bZb0p7iQWlOx5kVotIwk9O7lBy/pX6BgDPX0GS2CHyeZP2wW0jGHmf/QgSwX5GDOASZWUez5qvpMIHNXEIS5N9uax4P+utNSo4zrdeglGzr3KvU8Vg9hqXkPPmBqdPx8o5p1osgqA/JzJsR8ab05+p+juMQZGYdzfxyj46T+DViZs/RrGOVHJI6HrNLbxIUC0pJ2+beq9R6vF7DUnIe2m/rEJjMRp2kzwH/Dvx7RNzV6/4OQWbWUUXT8+60G9QL3QNSUqdzSKLDF3g/IQnaPPqr/Efc8267TR+P3OO1CzfN9iXlLftk3vd0POWHr+Rcs9tsVkgM5SPynyV5QuzvJO0HbARuiIgLiuzsEGRmXXV6oqlbnWy9fnqRkkqd2thljpw2x+4WkmD7BqVkWzlhyWw+SaqSrB36YPP2VWbbUSSzPd+XFn2pudSFpF2Bi4CDScb3nBYRuYusR8S3JF0P/ArwWuBM4KWAQ5CZ9a+5EHvebZYiwadovb57kaCvkDSnW25QelBK2tphMHnBsGTWq6D0R+TPATYBy9ts//fWcJS6ALg6Ik6StBTYsd0JJF0H7AR8j+S22K9ExKNFG+gQZGaFVDp8ww4qIGXrdutFStrY4ZxtJlycaW4hCboHpXYzS881KEHnsGQ2nyStBN5IMjHyH/aw33LgSOBdABExAUx02OUHwKtIeo3+E3hc0vci4pki53MIMrOOqlLHpSFgcAGpaN0yepH6DUndGtIxJMGcg1Jy7KEcy2ELTW9jglZI2pD5vC4i1mU+fxL4ALBLh2McLul2kkXU/zgi7iR5tH0zcImkQ0gegT8nIp7KbXLE+wEk7Qy8G7gE2AvYochFOASZWVfVnHDQLRg1tQtI7Z5iKjsgJfXat69ILxIMPiQlJ+m8ud7h+NWq2oYkswF4LCLW5G2Q9Cbg0Yi4JR37k+dW4AUR8UtJbwC+TLKg+hhwKHB2RNwk6QLgXOBP25zrPcCvkfQG/RT4DMltsUIcgsxsTvKCUVORgNRr7xGUF5Cy9Yv0IkH3W21FztlvSOqnN8msm2SeoFLGBB0BvCUNN8uA5ZL+OSLeMXWuZLbn5vuvSfoHSSuAcWA8Im5KN68nCUHtPAv4BHBLRNR6bahDkJmVrl1A6rf3CMoJSL3UL6sXqds5EwX++/TZm2Q2aBFxHnAeTD0F9sfZAJSW7wX8PCJC0mEkd3W3pJ8fkHRARNwNHA38qMO5Pt5PWx2CzKwjqTkepf8ehn57j2B4AlJSN61XUkgqMhdT9wpm80PSmQARsRY4Cfh9STXgGeDkmP4lczZwWfpk2L0kY30GwiHIzApRmy/oMsIR9N97BL2PP4JyA1LrPgsyJJm1E5S+bEZEfBv4dvp+bab8U8Cn2uyzEcgdb1Q2hyAz68t8hSMYbO8R9B6Qet2nyK02KPN2m5llOQSZ2UAMOhzBYHuPYO4BCfq7zZbU7Xj4nkKSWRExgJ6ghc4hyMy2q/kMR7B9AhIM9jZbUr/z+c2su75mWZf0Nkl3SmpIWtOy7TxJ90i6W9KxmfJXSfphuu1v1e43opktKpJyX2WrSrmvXlUq7V9d95Xavsrcx6w3ySPyRV6jot+lZu4A3grckC2UdBBwMskiZscB/5AupAZwIXAGyaRI+6fbzcxyzXc4KjMgFdq3hIBkZsX0dTssIjZBbvf28cDlEbENuE/SPcBhku4HljdXg5X0OeAE4Ov9tMPMFp9OQajMW2tQztgj6O/2GsxtoLZZUdHbshkjYVBjgvYBbsx8Hk/LJtP3reW5JJ1B0mvEqlWrym+lmY2k7THuCMobewSDDUhmlq9rCJL0TZLFyFp9OCK+0m63nLLoUJ4rXYxtHcCaNWsWVzw1s9Jtr3AE5fUeQf8ByczydQ1BEXHMHI47Djw/83klySqx4+n71nIzs3mzEMIRlB+QzHrVGKFBz0UM6q/PVcDJknaQtJpkAPTNEfEw8KSkV6dPhb0TaNebZGY2r7bXoOymsgZmm1kxfY0JknQi8HfAHsC/StoYEcdGxJ2SriBZ9KwGnBUR9XS33wc+S7Ly69fxoGgzGzLbs+cIyu89MssTEdTr9e4VR0i/T4ddCVzZZtv5wPk55RuAg/s5r5nZQrS9wxF0Dkhm1plnjDYzG7D5CEdmcxGL7BF5D6kzM5sn23vMkdn2ImmZpJsl3Z6uLPE/c+r8iaSN6esOSXVJz0m37SppvaS7JG2SdPgg2umeIDOzBcY9RzYvotSnw7YB/1dE/FLSEuA7kr4eEVNzCEbEx4GPA0h6M/D+iPhFuvkC4OqIOEnSUmDHshqW5RBkZjYkHI5sWETyP+Uv049L0len/1FPAb4AIGk5cCTwrvRYE8DEINrp22FmZkPOt9OsDEHydFiRF7BC0obM64zW40mqStoIPAp8IyJuyjuvpB1J1hH9Ylq0H7AZuETSbZIukrTTIK7ZIcjMzMx69VhErMm81rVWiIh6RLyCZGLkwyS1ezL8zcB3M7fCxoBDgQsj4pXAU8C55V+CQ5CZmZkNUEQ8DnybpLcnz8mkt8JS48B4pudoPUkoKp1DkJmZmUEkj8gXeXUjaQ9Ju6bvnwUcA9yVU+/ZwK+TWT0iIh4BHpB0QFp0NMnky6XzwGgzMzMr297ApZKqJB0uV0TEVyWdCRARa9N6JwLXRsRTLfufDVyWPhl2L/DuQTTSIcjMzMymBkaXcqyIHwCvzClf2/L5syRLabXW2wisKaUxHfh2mJmZmS1K7gkyMzOzqTFBi4l7gszMzGxRck+QmZmZlTomaFi4J8jMzMwWJYcgMzMzW5R8O8zMzMzKXkV+KLgnyMzMzBalvkKQpLdJulNSQ9KaTPm+kp6RtDF9rc1se5WkH0q6R9Lfyksem5mZLQBBo9Eo9BoV/fYE3QG8FbghZ9tPIuIV6evMTPmFwBnA/umr3YJqZmZmZgPT15igiNgEULQzR9LewPKI+F76+XPACcDX+2mHmZmZ9Sc8JqhUqyXdJul6Sb+Wlu0DjGfqjKdluSSdIWmDpA2bN28eYFPNzMxssenaEyTpm8BeOZs+HBFfabPbw8CqiNgi6VXAlyW9FMjrMmo7R3dErAPWAaxZs2ZxzeVtZma2PSVdQfPdiu2qawiKiGN6PWhEbAO2pe9vkfQT4MUkPT8rM1VXAg/1enwzMzNbuCQ9H/gcSSdKA1gXERe01NkN+AzwQmArcFpE3JFu2xW4CDiYpLPktOZQmjIN5HaYpD0kVdP3+5EMgL43Ih4GnpT06vSpsHcC7XqTzMzMbHuq14q9uqsBfxQRBwKvBs6SdFBLnQ8BGyPi5SR5IBuSLgCujoiXAIcAm/q+thz9PiJ/oqRx4HDgXyVdk246EviBpNuB9cCZEfGLdNvvk6S7e4Cf4EHRZmZmIyUiHo6IW9P3T5KEmNYxwAcB16V17gL2lbSnpOUkOeLidNtERDw+iHb2+3TYlcCVOeVfBL7YZp8NJN1bZmZmNuIk7Qu8EripZdPtJNPsfEfSYcALSIbJ1IHNwCWSDgFuAc6JiKfKbptnjDYzM7NkYHR9stgLVjSf3k5fZ+QdUtLOJJ0i74uIJ1o2fxTYTdJG4GzgNpLbaGPAocCFEfFK4Cng3EFcstcOMzMzs149FhFrOlWQtIQkAF0WEV9q3Z6GonendQXcl752BMYjotlztB6HIDMzMxuc8h6RT0PNxcCmiPhEmzq7Ak9HxATw34Ab0mD0hKQHJB0QEXcDRwM/KqVhLRyCzMzMrGxHAL8D/DC93QXJ02CrACJiLXAg8DlJdZKQc3pm/7OByyQtBe4l7TEqm0OQmZmZTY8JKuVQ8R3yJ0jO1vkeyRQ6eds2Ah1vt5XBA6PNzMxsUXJPkJmZmQFRdCLEkeGeIDMzM1uU3BNkZmZmyQpd9cW1gKp7gszMzGxRcggyMzOzRcm3w8zMzKzUR+SHhXuCzMzMbFFyT5CZmZlR5rIZw8I9QWZmZrYouSfIzMzMPCbIzMzMbLFwT5CZmZnhZTN6JOnjku6S9ANJV0raNbPtPEn3SLpb0rGZ8ldJ+mG67W8ldVxl1szMzIaLpOdL+jdJmyTdKemcnDovkfQ9Sdsk/XHLtl0lrU8zxiZJhw+inf3eDvsGcHBEvBz4/4HzACQdBJwMvBQ4DvgHSdV0nwuBM4D909dxfbbBzMzMFpYa8EcRcSDwauCsNBtk/QJ4L/DXOftfAFwdES8BDgE2DaKRfYWgiLg2Ipp9ZzcCK9P3xwOXR8S2iLgPuAc4TNLewPKI+F5EBPA54IR+2mBmZmYlCJJH5Iu8uh0q4uGIuDV9/yRJiNmnpc6jEfF9YMZobEnLgSOBi9N6ExHxeBmX2KrMgdGnAV9P3+8DPJDZNp6W7ZO+by3PJekMSRskbdi8eXOJTTUzM7PtQdK+wCuBmwrush+wGbhE0m2SLpK00yDa1nVgtKRvAnvlbPpwRHwlrfNhkq6vy5q75dSPDuW5ImIdsC49x2ZJP82ptgJ4rO0FDK9RvS4Y3WvzdQ0XX9dwGdXrgvbX9oLt2Yh45tFrtt72dysKVl8maUPm87r0O3sGSTsDXwTeFxFPFDz2GHAocHZE3CTpAuBc4E8L7l9Y1xAUEcd02i7pVOBNwNHpLS5Ienien6m2EngoLV+ZU95VROzR5vwbImJNkWMMk1G9Lhjda/N1DRdf13AZ1euChXNtEVHqGF1JS0gC0GUR8aUedh0HxiOi2XO0niQEla7fp8OOAz4IvCUins5sugo4WdIOklaTDIC+OSIeBp6U9Or0qbB3Al/ppw1mZma2sKTf8RcDmyLiE73sGxGPAA9IOiAtOhr4UclNBPqfJ+hTwA7AN9In3W+MiDMj4k5JV5A0ugacFRHNkVS/D3wWeBbJGKKvzzqqmZmZDbMjgN8BfihpY1r2IWAVQESslbQXsAFYDjQkvQ84KL1tdjZwmaSlwL3AuwfRyL5CUES8qMO284Hzc8o3AAf3c94Ws+5BjohRvS4Y3WvzdQ0XX9dwGdXrghG8toj4DvnjgLN1HmHmEJnsto3AwG8RanoYj5mZmdni4bXDzMzMbFEauhAk6Y8lhaQVmbKhXqJD0kfSpUc2SrpW0vMy24b22kZ1WRVJb0ungW9IWtOybWivq5Wk49LruEfSQJ7MGCRJn5H0qKQ7MmXPkfQNST9Of+6W2Zb7Z7eQqM1SBMN+XQCSlkm6WdLt6bX9z7R86K8NQFJVyZw3X00/j8R1Db2IGJoXyWP31wA/BVakZQcBt5MM0F4N/ASopttuBg4nuS/5deD1830Nba5reeb9e4G1o3BtwOuAsfT9x4CPjch1HQgcAHwbWJMpH+rrarnGatr+/YCl6XUdNN/t6vEajiSZa+SOTNlfAeem788t8v/kQnoBewOHpu93IVmu6KBhv660rQJ2Tt8vIZlY79WjcG1pe/8Q+Dzw1VH4f3FUXsPWE/Q3wAeYOcHi0C/RETMnkNqJ6esb6muLEV1WJSI2RcTdOZuG+rpaHAbcExH3RsQEcDnJ9Q2NiLiBZG2irOOBS9P3lzL955D7Z7c92tmLaL8UwVBfF0Akfpl+XJK+ghG4NkkrgTcCF2WKh/66RsHQhCBJbwEejIjbWzaVskTHfJN0vqQHgN8G/iwtHolrS5W+rMoCNErX1e5aht2ekcxXRvrzuWn50F2vZi5FMBLXld4y2gg8CnwjksnyRuHaPknyD/hGpmwUrmvo9TtPUKnUYYkOkvkFXpe3W05Zz0t0DFqna4uIr0TEh4EPSzoPeA/w5wzBtXW7rrTOQJZVGaQi15W3W07ZgrquHgxjm/sxVNerlqUIOgwxG6rrimQ+uVek4wevlNRpOpWhuDZJbwIejYhbJB1VZJecsgV3XaNiQYWgaLNEh6SXkdwbvT39y74SuFXSYQxgiY5BaHdtOT4P/CtJCFrw19bturSdllUpWw9/XlkL/rp60O5aht3PJe0dEQ+ntykfTcuH5nqVvxTB0F9XVkQ8LunbwHEM/7UdAbxF0huAZcBySf/M8F/XSBiK22ER8cOIeG5E7BsR+5L8T3JoJBMtDf0SHZL2z3x8C3BX+n6or02Lb1mVUbqu7wP7S1qtZMbWk0mub9hdBZyavj+V6T+H3D+7eWhfR+n/P3lLEQz1dQFI2iPtAULSs4BjSH4XDvW1RcR5EbEy/e46GfhWRLyDIb+ukTHfI7Pn8gLuJ306LP38YZIR9HeTeeqGZLbJO9JtnyKdHHKhvUj+VXcH8APg/wX2GYVrIxnQ9wCwMX2tHZHrOpEkiG8Dfg5cMwrXlXOdbyB5+ugnJLcB571NPbb/C8DDwGT653U6sDtwHfDj9Odzuv3ZLaQX8BqSWyM/yPy9esOwX1fazpcDt6XXdgfwZ2n50F9bpr1HMf102Mhc1zC/PGO0mZmZLUpDcTvMzMzMrGwOQWZmZrYoOQSZmZnZouQQZGZmZouSQ5CZmZktSg5BZmZmtig5BJmZmdmi5BBkZmZmi9L/AcOJsnofEAxcAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 720x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.deflection_models import DeflectionModel\n",
+ "from numpy import newaxis as na\n",
+ "class MyDeflectionModel(DeflectionModel):\n",
+ " args4deficit = ['dw_ijlk', 'cw_ijlk']\n",
+ "\n",
+ " def calc_deflection(self, dw_ijl, hcw_ijl, **_):\n",
+ " dw_ijlk = dw_ijl[..., na] # add extra wind speed dimension\n",
+ " hcw_ijlk =hcw_ijl[..., na] + .1*dw_ijlk # deflect 1/10 of the downstream distance\n",
+ " dh_ijlk =np.zeros_like(hcw_ijl[..., na]) # no vertical deflection\n",
+ " return dw_ijlk, hcw_ijlk, dh_ijlk\n",
+ "\n",
+ "iea_my_deflection = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=MyDeflectionModel())\n",
+ "\n",
+ "plt.figure(figsize=(10,4))\n",
+ "iea_my_deflection(x, y, wd=270, ws=10).flow_map().plot_wake_map()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Turbulence models"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# methods to plot turbulence map, used below to visualize and compare the deficit models\n",
+ " \n",
+ "def plot_turb_map(turbulenceModel):\n",
+ " xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
+ " X,Y,deficit = _map(turbulenceModel.calc_added_turbulence, xy)\n",
+ " c = plt.contourf(X,Y,deficit, levels=100, cmap='Blues')\n",
+ " plt.colorbar(c, label=\"Added turbulence intensity [-]\")\n",
+ " plt.plot([0,0],[-1/2,1/2],'k')\n",
+ " plt.ylabel(\"Crosswind distance [y/D]\")\n",
+ " plt.xlabel(\"downwind distance [x/D]\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### STF2005TurbulenceModel\n",
+ "\n",
+ "Steen Frandsen model implemented according to IEC61400-1, 2005 and weight according to Steen Frandsen's [thesis](https://orbit.dtu.dk/en/publications/turbulence-and-turbulence-generated-structural-loading-in-wind-tu)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.turbulence_models import STF2005TurbulenceModel\n",
+ "plot_turb_map(STF2005TurbulenceModel())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### STF2017TurbulenceModel\n",
+ "\n",
+ "Steen Frandsen model implemented according to IEC61400-1, 2017 and weight according to Steen Frandsen's [thesis](https://orbit.dtu.dk/en/publications/turbulence-and-turbulence-generated-structural-loading-in-wind-tu)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.turbulence_models import STF2017TurbulenceModel\n",
+ "plot_turb_map(STF2017TurbulenceModel())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**STF20XXTurbulenceModel with IEC-based spread angle**\n",
+ "\n",
+ "The `STF2005TurbulenceModel` and `STF2017TurbulenceModel` take a `weight_function` input which defaults to the bell-shaped `FrandsenWeight` defined in Steen Frandsen's thesis. As an alternative the `IECWeight` applies the full added turbulence in a 21.6$^\\circ$ spread angle up to 10 diameter downstream. \n",
+ "\n",
+ "Note, this is a debatable interpretation of the IEC standard which includes a 6% contribution from neighbouring wind turbines when calculating the omni-directional effective turbulence intensity. These 6% maps to a spread angle of 360$^\\circ\\cdot$ 6% = 21.6$^\\circ$.\n",
+ "\n",
+ "Note, the IEC standard includes more concepts which is not implemented in PyWake"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.turbulence_models import STF2017TurbulenceModel, IECWeight\n",
+ "from py_wake.superposition_models import SqrMaxSum\n",
+ "plot_turb_map(STF2017TurbulenceModel(addedTurbulenceSuperpositionModel=SqrMaxSum(), \n",
+ " weight_function=IECWeight(distance_limit=10)))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GCLTurbulence\n",
+ "\n",
+ "Gunner Chr. Larsen model implemented according to \n",
+ " \n",
+ " Pierik, J. T. G., Dekker, J. W. M., Braam, H., Bulder, B. H., Winkelaar, D., Larsen, G. C., Morfiadakis, E., Chaviaropoulos, P., Derrick, A., & Molly, J. P. (1999). European wind turbine standards II (EWTS-II). In E. L. Petersen, P. Hjuler Jensen, K. Rave, P. Helm, & H. Ehmann (Eds.), Wind energy for the next millennium. Proceedings (pp. 568-571). James and James Science Publishers."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 54,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.turbulence_models import GCLTurbulence\n",
+ "plot_turb_map(GCLTurbulence())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### CrespoHernandez\n",
+ "\n",
+ " Implemented according to:\n",
+ " A. Crespo and J. Hernández\n",
+ " Turbulence characteristics in wind-turbine wakes\n",
+ " J. of Wind Eng. and Industrial Aero. 61 (1996) 71-85"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.turbulence_models import CrespoHernandez\n",
+ "plot_turb_map(CrespoHernandez())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Compare Turbulence models"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "turbulenceModels = [STF2005TurbulenceModel(),\n",
+ " STF2017TurbulenceModel(),\n",
+ " STF2017TurbulenceModel(addedTurbulenceSuperpositionModel=SqrMaxSum(), weight_function=IECWeight(10)),\n",
+ " GCLTurbulence(),\n",
+ " CrespoHernandez()]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**turbulence intensity along center line**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b680412eb0>"
+ ]
+ },
+ "execution_count": 57,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=((10,6)))\n",
+ "for turbulenceModel in turbulenceModels:\n",
+ " X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(np.linspace(-200,500,300), 0))\n",
+ " l = turbulenceModel.__class__.__name__\n",
+ " if l.startswith('STF'):\n",
+ " l+=f\"({turbulenceModel.apply_weight.__self__.__class__.__name__})\"\n",
+ " plt.plot(X[0], ti[0], label=l)\n",
+ "\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**Deficit profile 2D downstream**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x2b6802353d0>"
+ ]
+ },
+ "execution_count": 58,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 720x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=((10,6)))\n",
+ "for turbulenceModel in turbulenceModels:\n",
+ " X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(2*D, np.linspace(-200,200,300)))\n",
+ " plt.plot(Y[:,], ti[:,0], label=turbulenceModel.__class__.__name__)\n",
+ "\n",
+ "plt.legend()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Ground models"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Mirror\n",
+ "The Mirror ground model lets the ground mirror the wake deficit. It is implemented by adding wakes from underground mirrored wind turbines"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.contour.QuadContourSet at 0x2b6e4b1f4c0>"
+ ]
+ },
+ "execution_count": 59,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from py_wake.ground_models import Mirror\n",
+ "wfm = NOJ(site, windTurbines, k=.5, groundModel=Mirror())\n",
+ "wfm([0], [0], wd=0).flow_map(YZGrid(x=0, y=np.arange(-300, 100, 1) + .1, z=np.arange(-100, 200))).plot_wake_map()\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.8"
+ },
+ "toc": {
+ "base_numbering": 1,
+ "nav_menu": {},
+ "number_sections": true,
+ "sideBar": true,
+ "skip_h1_title": false,
+ "title_cell": "Table of Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
+ "toc_position": {
+ "height": "calc(100% - 180px)",
+ "left": "10px",
+ "top": "150px",
+ "width": "373.333px"
+ },
+ "toc_section_display": true,
+ "toc_window_display": true
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/notebooks/YawMisalignment.ipynb b/docs/notebooks/YawMisalignment.ipynb
index 008503f14..51b611e3b 100644
--- a/docs/notebooks/YawMisalignment.ipynb
+++ b/docs/notebooks/YawMisalignment.ipynb
@@ -9,7 +9,7 @@
"In case the wind turbine rotor is not perpendicular to the inflow, its operation and effects on the flow field will be different. In general it is a quite complicated process. In PyWake the effects are divided into four subeffects that are handled invididually:\n",
"\n",
"1. Change of operation due to reduced inflow wind speed\n",
- "2. Reduced deficit, <font style=\"color:red\">$deficit_{normal}$</font>, due to reduced inflow wind speed\n",
+ "2. Reduced deficit, <font style=\"color:red\">$deficit_{normal}$</font>, due to reduced inflow wind speed, ($C_{T,n} \\rightarrow C_{T,x}$)\n",
"3. Reduced deficit, <font style=\"color:#CCCC00\">$deficit_{downwind}$</font>, due to misalignment between thrust and downwind direction\n",
"4. Deflection of wake deficit, <font style=\"color:green\">$deficit_{deflected}$</font>, due to traversal thrust component reaction\n",
"\n",
@@ -40,7 +40,7 @@
"from py_wake.examples.data.hornsrev1 import V80\n",
"from py_wake.flow_map import HorizontalGrid\n",
"from py_wake.tests.test_files import tfp\n",
- "from py_wake.wind_farm_models import PropagateDownwind\n",
+ "from py_wake.wind_farm_models import PropagateDownwind, All2AllIterative\n",
"from py_wake.deficit_models import FugaYawDeficit\n",
"from py_wake.deflection_models import FugaDeflection\n",
"from py_wake.examples.data.hornsrev1 import Hornsrev1Site\n",
@@ -61,7 +61,7 @@
"\n",
"The inflow perpendicular to the rotor is reduced by $cos\\theta$.\n",
"\n",
- "This means that the pitch and rotor speed setting of the WT will be different. In PyWake the WT operation (pitch and rotor speed settings) is modeled in terms of the Power and CT curves which must be looked up for the reduced wind speed. \n",
+ "This means that the pitch and rotor speed setting of the WT will be different. In PyWake the WT operation (pitch and rotor speed settings) is modeled in terms of the Power and CT curves. If these curves are specified in terms of the the wind speed normal to the rotor, then the wind speed must be multiplied by $cos\\theta$ before looking up the power and ct. This is one of two effects modeled by the `SimpleYawModel`, which is an additional model that is applied as default to most PowerCtFunctions, see [here](#SimpleYawModel) for more details.\n",
"\n",
"Note, that below rated rotor speed, the CT curve is typically rather flat and reducing the wind speed has therefore limited effect on the CT value in this region. The power, on the other hand, is limited by the maximum power and therefore only affected in the region below rated wind speed (rated wind speed will increase with yaw misalignment)"
]
@@ -83,7 +83,7 @@
},
{
"data": {
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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1080x360 with 2 Axes>"
]
@@ -111,31 +111,62 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Furthermore, misalignemnt between the thrust force (axial induction) and the inflow leads to higher wind speed at the rotor plane which also affects the WT operation. This effect, however, is not considered in PyWake"
+ "Furthermore, misalignement between the thrust force (axial induction) and the inflow leads to higher wind speed at the rotor plane, which also affects the WT operation. This effect, however, is not considered in PyWake."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Reduced deficit due to reduced inflow wind speed\n",
+ "## Reduced deficit due to reduced inflow wind speed ($C_{T,n} \\rightarrow C_{T,x}$)\n",
"\n",
- "The wake deficit is caused by a reaction to the thrust force which slows down the inflow.\n",
+ "The wake deficit is caused by a reaction to the thrust force, which slows down the inflow.\n",
"\n",
- "In non-aligned inflow, the thrust force is reduced as the wind speed component normal to the rotor is reduced\n",
+ "The thrust force normal to the rotor plane is\n",
"\n",
"\\begin{align}\n",
- "T & =\\frac{1}{2}\\rho C_T A (U cos\\theta)^2\n",
+ "T_n & =\\frac{1}{2}\\rho C_{T,n} A (U cos\\theta)^2\n",
"\\end{align}\n",
"\n",
- "The engineering models, however, scale their deficit with the inputs, U and CT. The reduction in deficit is therefore modeled by applying a reduced $C_T$ value, $C_{T,yaw}$, that gives the same reduction in thrust, i.e. it satisfies:\n",
+ "In non-aligned inflow, the thrust force that slows down the flow, i.e. in the mean wind direction is\n",
"\n",
"\\begin{align}\n",
- "\\frac{1}{2}\\rho C_{T,yaw} A U^2 & = \\frac{1}{2}\\rho C_T A (U cos\\theta)^2 \\\\\n",
- "C_{T,yaw} & = C_T cos^2\\theta\\\\\n",
+ "T_x & =\\frac{1}{2}\\rho C_ {T,x} \\left(A cos\\theta \\right) U^2\n",
"\\end{align}\n",
"\n",
- "The `WindTurbines` object is responsible for computing the reduced $C_T$ values and the default model, just multipy the normal ct function value with $cos^2\\theta$\n"
+ "From these two equations we can find the relationship between the thrust coefficient in the rotor-normal direction, $C_{T,n}$, and the thrust coefficient in the down-wind direction, $C_{T,x}$.\n",
+ "\n",
+ "\\begin{align}\n",
+ "T_x & = T_n cos\\theta \\\\\n",
+ "\\frac{1}{2} \\rho C_{T,x} \\left(A cos\\theta \\right) U^2 & = \\frac{1}{2}\\rho C_{T,n} A (U cos\\theta)^2 cos\\theta\\\\\n",
+ "C_ {T,x} & = C_{T,n} \\cos^2\\theta\n",
+ "\\end{align}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This is the second effect modeled by the `SimpleYawModel`, which is an additional model that is applied as default to most PowerCtFunctions, see [here](#SimpleYawModel) for more details."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## SimpleYawModel\n",
+ "\n",
+ "The `SimpleYawModel` is an additional model, which as default is applied by \n",
+ "- `PowerCtFunction`\n",
+ "- `PowerCtTabular`\n",
+ "- `PowerCtNDTabular`\n",
+ "- `PowerCtXr`\n",
+ "- `CubePowerSimpleCt`\n",
+ "\n",
+ "It handles effects 1. and 2. by:\n",
+ "\n",
+ "1. Compute/look up $C_{T,n}$ based on wind speed $U\\cos\\theta$\n",
+ "2. Returns $C_{T,x} = C_{T,n} \\cos^2\\theta$\n"
]
},
{
@@ -157,35 +188,35 @@
"source": [
"### FugaYawDeficit\n",
"\n",
- "The `FugaYawDeficit` model implicitly models this effect. This model requires two sets of look-up tabels, namely `UL` and `UT`. These tables describes the normalized deficit in the downwind, `U` direction caused by a unit forcing in the longitudinal, `L` and transveral, `T` directions."
+ "The `FugaYawDeficit` model implicitly models this effect. This model requires two sets of look-up tabels, namely `UL` and `UT`. These tables describes the normalized deficit in the downwind, `U` direction caused by a unit forcing in the longitudinal, L, and transveral, T, directions."
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
- "fuga = FugaYawDeficit(tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/')\n",
+ "fuga = FugaYawDeficit(tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/')\n",
"D = 80\n",
"R = D/2\n",
"x0,x1,y = 1,10,2 #upstream, downstream and crosswind regions to load [D]\n",
"xi0 = int(512-x0/(fuga.dx/D))\n",
"xi1 = int(512+x1/(fuga.dx/D))+1\n",
"yi = int(y/(fuga.dy/D))+1\n",
- "UL, UT = [fuga.mirror(v,anti_symmetric=a) for v, a in zip(fuga.load_luts()[:2,0,:yi, xi0:xi1], (False,True))]"
+ "UL, UT = [-fuga.mirror(v,anti_symmetric=a) for v, a in zip(fuga.load_luts()[:2,0,:yi, xi0:xi1], (False,True))]"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1080x864 with 4 Axes>"
]
@@ -200,18 +231,18 @@
"axes = plt.subplots(2,1, figsize=(15,12))[1]\n",
"X, Y = np.meshgrid(fuga.x[xi0:xi1], fuga.mirror(fuga.y[:yi], anti_symmetric=True))\n",
"wtL = np.array([[0,0],[-D/2,D/2]])\n",
- "for ax, v, l in zip(axes.flatten(), [UL, UT], ['UL','UT']):\n",
+ "for ax, v, l in zip(axes.flatten(), [UL, -UT], ['UL','UT']):\n",
" c = ax.contourf(X, Y, v)\n",
- " plt.colorbar(c, ax=ax, label=r'Downwind deficit $\\left[\\frac{1}{U CT}\\right]$')\n",
+ " plt.colorbar(c, ax=ax, label=r'Downwind deficit $\\left[\\frac{1}{U^2 CT}\\right]$')\n",
" s = (slice(None,None,2),slice(None,None,5))\n",
- " ax.quiver(X[s], Y[s], v[s]*(l[0]=='U'), v[s]*(l[0]=='V'))\n",
+ " ax.quiver(X[s], Y[s], -v[s]*(l[0]=='U'), v[s]*(l[0]=='V'))\n",
" ax.plot([0,0],[-D/2,D/2],'r')\n",
" if l[1]=='L':\n",
" ax.arrow(-10,0,-20,0,color='r', width=10,head_length=30)\n",
" ax.arrow(60,0,-20,0,color='r', width=10,head_length=30)\n",
" else:\n",
- " ax.arrow(-30,-25,0,20,color='r', width=10,head_length=30)\n",
- " ax.arrow(30,-25,0,20,color='r', width=10,head_length=30)\n",
+ " ax.arrow(-30,25,0,-20,color='r', width=10,head_length=30)\n",
+ " ax.arrow(30,25,0,-20,color='r', width=10,head_length=30)\n",
" \n",
" ax.axis('equal')\n",
" ax.set_xlim([-D,10*D])\n",
@@ -232,13 +263,13 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "be319886ef544012973e2b2593a8c252",
+ "model_id": "a2ab3a7e494246568efa7de21560fb1e",
"version_major": 2,
"version_minor": 0
},
@@ -255,17 +286,17 @@
" plt.figure(figsize=(18,5))\n",
" theta = np.deg2rad(yaw)\n",
" co, si = np.cos(theta), np.sin(theta)\n",
- " deficit = co**2*(UL*co + UT*si)\n",
- " c = plt.contourf(X, Y, deficit, levels=np.arange(-.4,.1,.05))\n",
- " plt.colorbar(c, label=r'Downwind deficit $\\left[\\frac{1}{U CT}\\right]$')\n",
+ " deficit = co**2*(UL*co - UT*si)\n",
+ " c = plt.contourf(X, Y, deficit,20)#, levels=np.arange(-.4,.1,.05))\n",
+ " plt.colorbar(c, label=r'Downwind deficit $\\left[\\frac{1}{U^2 CT}\\right]$')\n",
" s = (slice(None,None,2),slice(None,None,5))\n",
- " plt.quiver(X[s], Y[s], deficit[s], deficit[s]*0, width=.002, scale=2)\n",
- " plt.plot([-si*R, si*R],[-co*R,co*R],'w',label='Rotor',lw=3)\n",
+ " plt.quiver(X[s], Y[s], -deficit[s], deficit[s]*0, width=.002, scale=2)\n",
+ " plt.plot([si*R, -si*R],[-co*R,co*R],'w',label='Rotor',lw=3)\n",
" plt.arrow(-0,0,-100*co,0,color='r', width=5,head_length=10,length_includes_head=True)\n",
- " plt.arrow(-0,-0,0,100*si,color='r', width=5,head_length=10,length_includes_head=True, zorder=32)\n",
+ " plt.arrow(-0,-0,0,-100*si,color='r', width=5,head_length=10,length_includes_head=True, zorder=32)\n",
" plt.axis('equal')\n",
" plt.xlim([-D,10*D])\n",
- " plt.ylim([-D,D])\n",
+ " plt.ylim([-D/2,D/2])\n",
" ax.set_title(l) \n",
"_ = interact(plot, yaw=IntSlider(min=-90, max=90, step=1, value=20, continuous_update=False))"
]
@@ -276,7 +307,7 @@
"source": [
"## Wake deflection due to traversal thrust component reaction\n",
"\n",
- "Wake deflection is modeled by a `DeflectionModel` which modifies the downwind, horizontal crosswind and vertical distance between wind turbines. "
+ "Wake deflection is modeled by a `DeflectionModel`, which modifies the downwind, horizontal crosswind and vertical distance between wind turbines. "
]
},
{
@@ -285,16 +316,16 @@
"source": [
"### FugaDeflection\n",
"\n",
- "FugaDeflection is capable of modeling the wake deflection if the `VL` and `VT` is present. These tables describes the normalized deficit in the crosswind, `V` direction caused by a unit forcing in the longitudinal, `L` and transveral, `T` directions."
+ "FugaDeflection is capable of modeling the wake deflection if `VL` and `VT` is known. These tables describes the normalized deficit in the crosswind, `V` direction caused by a unit forcing in the longitudinal, L, and transveral, T, directions."
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
- "fugaDeflection = FugaDeflection(tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/')\n",
+ "fugaDeflection = FugaDeflection(tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/')\n",
"D = 80\n",
"R = D/2\n",
"x0,x1,y = 1,10,2 #upstream, downstream and crosswind regions to load [D]\n",
@@ -308,12 +339,12 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1080x864 with 4 Axes>"
]
@@ -327,9 +358,9 @@
"source": [
"axes = plt.subplots(2,1, figsize=(15,12))[1]\n",
"X, Y = np.meshgrid(fugaDeflection.x[xi0:xi1], fugaDeflection.mirror(fugaDeflection.y[:yi], anti_symmetric=True))\n",
- "for ax, v, l in zip(axes.flatten(), [VL, -VT], ['VL','VT']):\n",
+ "for ax, v, l in zip(axes.flatten(), [VL, VT], ['VL','VT']):\n",
" c = ax.contourf(X, Y, v)\n",
- " plt.colorbar(c, ax=ax, label=r'$WS_{Crosswind} \\left[\\frac{1}{U CT}\\right]$')\n",
+ " plt.colorbar(c, ax=ax, label=r'$WS_{Crosswind} \\left[\\frac{1}{U^2 CT}\\right]$')\n",
" s = (slice(None,None,10),slice(None,None,1))\n",
" ax.quiver(X[s], Y[s], 0, v[s], scale=(.3,3)[l[1]=='T'])\n",
" ax.plot([0,0],[-D/2,D/2],'r')\n",
@@ -337,8 +368,8 @@
" ax.arrow(-10,0,-20,0,color='r', width=10,head_length=30)\n",
" ax.arrow(60,0,-20,0,color='r', width=10,head_length=30)\n",
" else:\n",
- " ax.arrow(-30,-25,0,20,color='r', width=10,head_length=30)\n",
- " ax.arrow(30,-25,0,20,color='r', width=10,head_length=30)\n",
+ " ax.arrow(-30,25,0,-20,color='r', width=10,head_length=30)\n",
+ " ax.arrow(30,25,0,-20,color='r', width=10,head_length=30)\n",
" \n",
" ax.axis('equal')\n",
" ax.set_xlim([-D,10*D])\n",
@@ -350,22 +381,22 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "As Fuga is a linear model, the effects in the crosswind direction can simply be calculated by the linear superposition of `VL` and `VT`:\n",
+ "As Fuga is a linear model, the effects in the crosswind direction can simply be calculated by linear superposition of `VL` and `VT`:\n",
"\n",
- "$WS_{crosswind} = cos(VL \\cdot cos\\theta + VT \\cdot sin\\theta) \\cdot U \\cdot CT$\n",
+ "$WS_{crosswind} = (VL \\cdot cos\\theta + VT \\cdot sin\\theta) \\cdot U \\cdot CT$\n",
"\n",
- "You can move the slider below to see the crosswind wind speed field for different yaw-misalignment angles. Futhermore, the integrated deflection is shown with solid lines"
+ "You can move the slider below to see the crosswind wind speed field for different yaw-misalignment angles. Furthermore, the integrated deflection is shown with solid lines"
]
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "6a14f501840e4654a59434bf1f9b4137",
+ "model_id": "81eff02cace94a50a50f8a47068a8855",
"version_major": 2,
"version_minor": 0
},
@@ -382,17 +413,20 @@
" plt.figure(figsize=(18,5))\n",
" theta = np.deg2rad(yaw)\n",
" co, si = np.cos(theta), np.sin(theta)\n",
- " deficit = co**2*(VL*co + -VT*si)\n",
+ " V = co**2*(VL*co + VT*si)\n",
" X, Y = np.meshgrid(fugaDeflection.x[xi0:xi1], fugaDeflection.mirror(fugaDeflection.y[:yi], anti_symmetric=True))\n",
- " c = plt.contourf(X, Y, deficit, levels=np.arange(-.09,.1,.01))\n",
+ " c = plt.contourf(X, Y, V)#, levels=np.arange(-.09,.1,.01))\n",
" plt.colorbar(c, label=r'$WS_{crosswind} \\left[\\frac{1}{U CT}\\right]$')\n",
" s = (slice(None,None,6),slice(None,None,1))\n",
- " plt.quiver(X[s], Y[s], deficit[s]*0, -deficit[s], width=.002, scale=2)\n",
+ " plt.quiver(X[s], Y[s], V[s]*0, V[s], width=.002, scale=2)\n",
" \n",
" # plot deflection lines\n",
" fL, fT = fugaDeflection.fLT.V.T[:,256-yi:255+yi, xi0:xi1]\n",
- " lambda1 = co**2 * (fL * co + fT * si)\n",
- " Yp = Y + lambda1\n",
+ " lambda2p = co**2 * (fL * co - fT * si)\n",
+ " y = fugaDeflection.mirror(fugaDeflection.y[:yi], anti_symmetric=True)\n",
+ " \n",
+ " lambda2 = np.array([np.interp(y, y + l2p, l2p) for l2p in lambda2p.T])\n",
+ " Yp = Y + lambda2.T\n",
" plt.plot(X[yi, :], Y[yi, :], 'grey', lw=3)\n",
" for x, y, yp in zip(X[1::4], Y[1::4], Yp[1::4]):\n",
" plt.plot(x, y, 'grey', lw=1, zorder=-32)\n",
@@ -413,18 +447,25 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Finally, all effects are put together. You can move the slider below to see the effects on the deficit behind a WT"
+ "Note, the plot above shows the wind speed in cross-wind direction (up), i.e. yellow colors corresponds to a flow towards the top of the figure, while blue corresponds to a flow towards the bottom."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Finally, all effects are put together. You can move the slider below to see the effects on the deficit behind a WT."
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "bf37131eeea54f68ac877e1a70282546",
+ "model_id": "b1675a2f71a748c09e2e18503d69171b",
"version_major": 2,
"version_minor": 0
},
@@ -437,13 +478,21 @@
}
],
"source": [
- "path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'\n",
- "wfm = PropagateDownwind(site,wt,FugaYawDeficit(path), deflectionModel=FugaDeflection(path))\n",
+ "path = tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/'\n",
+ "fugaDeficit = FugaYawDeficit(path)\n",
+ "wfm = All2AllIterative(site,wt,fugaDeficit,blockage_deficitModel=fugaDeficit, \n",
+ " deflectionModel=FugaDeflection(path)\n",
+ " )\n",
"def plot(yaw):\n",
" plt.figure(figsize=(18,5))\n",
- " fm = wfm([0],[0],ws=10,wd=270, yaw_ilk=[[[yaw]]]).flow_map(XYGrid(x=np.arange(-100,800,10), y=np.arange(-150,150,10)))\n",
- " fm.plot_wake_map()\n",
- " max_deficit_line = fm.min_WS_eff(x=np.arange(10,800,10))\n",
+ " fm = wfm([0],[0],ws=10,wd=270, yaw=[[[yaw]]]).flow_map(XYGrid(x=np.arange(-100,800,10), y=np.arange(-250,250,10)))\n",
+ " X,Y = np.meshgrid(fm.x, fm.y)\n",
+ " c1 = plt.contourf(X,Y,fm.WS_eff.squeeze(),np.arange(6.5,10.1,0.1), cmap='Blues_r')\n",
+ " c2 = plt.contourf(X,Y,fm.WS_eff.squeeze(),np.arange(10,10.2,.005), cmap='Reds')\n",
+ " plt.colorbar(c2, label='Wind speed (deficit regions) [m/s]')\n",
+ " plt.colorbar(c1, label='Wind speed (speed-up regions) [m/s]')\n",
+ " wt.plot([0],[0],wd=270,yaw=yaw)\n",
+ " max_deficit_line = fm.min_WS_eff(x=np.arange(-100,800,10))\n",
" max_deficit_line.plot(color='k', label='Max deficit line')\n",
" plt.axhline(0, label='Center line')\n",
" plt.legend()\n",
@@ -451,6 +500,20 @@
" \n",
"_ = interact(plot, yaw=IntSlider(min=-90, max=90, step=1, value=20, continuous_update=False)) "
]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Note, the scaling of wake deficit(blue) and speedup(red) does not match"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
@@ -469,7 +532,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.2"
+ "version": "3.8.8"
},
"toc": {
"base_numbering": 1,
@@ -480,9 +543,14 @@
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
- "toc_position": {},
+ "toc_position": {
+ "height": "calc(100% - 180px)",
+ "left": "10px",
+ "top": "150px",
+ "width": "165px"
+ },
"toc_section_display": true,
- "toc_window_display": true
+ "toc_window_display": false
}
},
"nbformat": 4,
diff --git a/docs/notebooks/exercises/WakeDeflection.ipynb b/docs/notebooks/exercises/WakeDeflection.ipynb
index 7f48e381d..268631552 100644
--- a/docs/notebooks/exercises/WakeDeflection.ipynb
+++ b/docs/notebooks/exercises/WakeDeflection.ipynb
@@ -1,145 +1,145 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Exercise: Combine Models\n",
- "\n",
- "In this exercise you can investigate the wake-deflection effects of yaw-misalignment"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Install PyWake if needed\n",
- "try:\n",
- " import py_wake\n",
- "except ModuleNotFoundError:\n",
- " !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake.git"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "# setup site, wind turbines and wind farm model\n",
- "from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines\n",
- "from py_wake.deficit_models.gaussian import IEA37SimpleBastankhahGaussian\n",
- "from py_wake.deflection_models.jimenez import JimenezWakeDeflection\n",
- "import numpy as np\n",
- "from ipywidgets import interact\n",
- "from ipywidgets import IntSlider\n",
- "from py_wake.flow_map import HorizontalGrid\n",
- "import matplotlib.pyplot as plt\n",
- "site = IEA37Site(16)\n",
- "x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T\n",
- "windTurbines = IEA37_WindTurbines()\n",
- "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=JimenezWakeDeflection())"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "# define function that plots the flow field and AEP history of 3 wind turbines\n",
- "def plot_flow_field_and_aep(WT0, WT1):\n",
- " \n",
- " #_, (ax1, ax2) = plt.subplots(2,1,figsize=(20,6))\n",
- " ax1 = plt.figure(figsize=(20,4)).gca()\n",
- " ax2 = plt.figure(figsize=(10,3)).gca()\n",
- " \n",
- " sim_res = wfm(x, y, yaw_ilk=np.reshape([WT0,WT1,0],(3,1,1)), wd=270, ws=10)\n",
- " sim_res.flow_map(HorizontalGrid(x = np.linspace(0,1400,200), y=np.linspace(-200,200,50))).plot_wake_map(ax=ax1)\n",
- " ax1.set_xlim([-200,1400])\n",
- " aep.append(sim_res.aep().values[:,0,0])\n",
- " aep_arr = np.array(aep) \n",
- " for i in range(3):\n",
- " ax2.plot(aep_arr[:,i], '.-', label='WT%d, %.2f'%(i,aep_arr[-1,i]))\n",
- " ax2.plot(aep_arr.sum(1), '.-', label='Total, %.2f'%aep_arr[-1].sum())\n",
- " ax2.axhline(aep_arr[0].sum(),ls='--',c='r')\n",
- " ax2.set_ylabel('AEP [GWh]')\n",
- " ax2.set_xlabel('Iteration')\n",
- " ax2.legend(loc='upper left')\n",
- " \n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "e1be6c3aa87b45ef95efe446bd8914cf",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "interactive(children=(IntSlider(value=0, continuous_update=False, description='WT0', max=50, min=-50), IntSlid\u2026"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Run the plot_flow_field_and_aep function when moving the sliders\n",
- "aep = []\n",
- "_ = interact(plot_flow_field_and_aep, \n",
- " WT0=IntSlider(min=-50, max=50, step=1, value=0, continuous_update=False),\n",
- " WT1=IntSlider(min=-50, max=50, step=1, value=0, continuous_update=False))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Move the sliders below and try to find the optimal yaw-misalignment of WT0 and WT1 with respect to total aep"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.8.2"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": true
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
\ No newline at end of file
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Exercise: Combine Models\n",
+ "\n",
+ "In this exercise you can investigate the wake-deflection effects of yaw-misalignment"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Install PyWake if needed\n",
+ "try:\n",
+ " import py_wake\n",
+ "except ModuleNotFoundError:\n",
+ " !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake.git"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# setup site, wind turbines and wind farm model\n",
+ "from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines\n",
+ "from py_wake.deficit_models.gaussian import IEA37SimpleBastankhahGaussian\n",
+ "from py_wake.deflection_models.jimenez import JimenezWakeDeflection\n",
+ "import numpy as np\n",
+ "from ipywidgets import interact\n",
+ "from ipywidgets import IntSlider\n",
+ "from py_wake.flow_map import HorizontalGrid\n",
+ "import matplotlib.pyplot as plt\n",
+ "site = IEA37Site(16)\n",
+ "x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T\n",
+ "windTurbines = IEA37_WindTurbines()\n",
+ "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=JimenezWakeDeflection())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# define function that plots the flow field and AEP history of 3 wind turbines\n",
+ "def plot_flow_field_and_aep(WT0, WT1):\n",
+ " \n",
+ " #_, (ax1, ax2) = plt.subplots(2,1,figsize=(20,6))\n",
+ " ax1 = plt.figure(figsize=(20,4)).gca()\n",
+ " ax2 = plt.figure(figsize=(10,3)).gca()\n",
+ " \n",
+ " sim_res = wfm(x, y, yaw_ilk=np.reshape([WT0,WT1,0],(3,1,1)), wd=270, ws=10)\n",
+ " sim_res.flow_map(HorizontalGrid(x = np.linspace(0,1400,200), y=np.linspace(-200,200,50))).plot_wake_map(ax=ax1)\n",
+ " ax1.set_xlim([-200,1400])\n",
+ " aep.append(sim_res.aep().values[:,0,0])\n",
+ " aep_arr = np.array(aep) \n",
+ " for i in range(3):\n",
+ " ax2.plot(aep_arr[:,i], '.-', label='WT%d, %.2f'%(i,aep_arr[-1,i]))\n",
+ " ax2.plot(aep_arr.sum(1), '.-', label='Total, %.2f'%aep_arr[-1].sum())\n",
+ " ax2.axhline(aep_arr[0].sum(),ls='--',c='r')\n",
+ " ax2.set_ylabel('AEP [GWh]')\n",
+ " ax2.set_xlabel('Iteration')\n",
+ " ax2.legend(loc='upper left')\n",
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "e1be6c3aa87b45ef95efe446bd8914cf",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "interactive(children=(IntSlider(value=0, continuous_update=False, description='WT0', max=50, min=-50), IntSlid…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Run the plot_flow_field_and_aep function when moving the sliders\n",
+ "aep = []\n",
+ "_ = interact(plot_flow_field_and_aep, \n",
+ " WT0=IntSlider(min=-50, max=50, step=1, value=0, continuous_update=False),\n",
+ " WT1=IntSlider(min=-50, max=50, step=1, value=0, continuous_update=False))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Move the sliders below and try to find the optimal yaw-misalignment of WT0 and WT1 with respect to total aep"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.8"
+ },
+ "toc": {
+ "base_numbering": 1,
+ "nav_menu": {},
+ "number_sections": true,
+ "sideBar": true,
+ "skip_h1_title": false,
+ "title_cell": "Table of Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
+ "toc_position": {},
+ "toc_section_display": true,
+ "toc_window_display": true
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/py_wake/deficit_models/fuga.py b/py_wake/deficit_models/fuga.py
index c90b72032..0f3f17db0 100644
--- a/py_wake/deficit_models/fuga.py
+++ b/py_wake/deficit_models/fuga.py
@@ -97,7 +97,7 @@ class FugaDeficit(WakeDeficitModel, BlockageDeficitModel, FugaUtils):
class FugaYawDeficit(FugaDeficit):
args4deficit = ['WS_ilk', 'WS_eff_ilk', 'dw_ijlk', 'hcw_ijlk', 'dh_ijlk', 'h_il', 'ct_ilk', 'D_src_il', 'yaw_ilk']
- def __init__(self, LUT_path=tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/',
+ def __init__(self, LUT_path=tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/',
remove_wriggles=False, method='linear'):
"""
Parameters
@@ -139,7 +139,8 @@ class FugaYawDeficit(FugaDeficit):
mdUL_ijlk, mdUT_ijlk = np.moveaxis(self.interpolate(
dw_ijlk, np.abs(hcw_ijlk), (h_il[:, na, :, na] + dh_ijlk)), -1, 0)
mdUT_ijlk[hcw_ijlk < 0] *= -1 # UT is antisymmetric
- mdu_ijlk = (mdUL_ijlk * np.cos(yaw_ilk)[:, na] - mdUT_ijlk * np.sin(yaw_ilk)[:, na])
+ theta_ilk = np.deg2rad(yaw_ilk)
+ mdu_ijlk = (mdUL_ijlk * np.cos(theta_ilk)[:, na] - mdUT_ijlk * np.sin(theta_ilk)[:, na])
mdu_ijlk *= ~((dw_ijlk == 0) & (hcw_ijlk <= D_src_il[:, na, :, na])) # avoid wake on itself
return mdu_ijlk * (ct_ilk * WS_eff_ilk**2 / WS_ilk)[:, na]
diff --git a/py_wake/deflection_models/fuga_deflection.py b/py_wake/deflection_models/fuga_deflection.py
index 3f4218773..f82befefa 100644
--- a/py_wake/deflection_models/fuga_deflection.py
+++ b/py_wake/deflection_models/fuga_deflection.py
@@ -2,18 +2,16 @@ from numpy import newaxis as na
import matplotlib.pyplot as plt
import numpy as np
from py_wake.deflection_models.deflection_model import DeflectionModel
+from py_wake.tests.test_files import tfp
from py_wake.utils.fuga_utils import FugaUtils
from py_wake.utils.grid_interpolator import GridInterpolator
-import time
-import py_wake
-import os
-tfp = os.path.dirname(py_wake.__file__).replace("\\", "/") + "/tests/test_files/"
+from scipy.interpolate.interpolate import RegularGridInterpolator
class FugaDeflection(FugaUtils, DeflectionModel):
args4deflection = ['WS_ilk', 'WS_eff_ilk', 'yaw_ilk', 'ct_ilk', 'D_src_il']
- def __init__(self, LUT_path=tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/', on_mismatch='raise'):
+ def __init__(self, LUT_path=tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00', on_mismatch='raise'):
FugaUtils.__init__(self, path=LUT_path, on_mismatch=on_mismatch)
if len(self.zlevels) == 1:
tabs = self.load_luts(['VL', 'VT']).reshape(2, -1, self.nx)
@@ -26,7 +24,7 @@ class FugaDeflection(FugaUtils, DeflectionModel):
tabs = tabs[:, 0] * (1 - t) + t * tabs[:, 1]
VL, VT = tabs
- # VL[0] *= -1 # change sign of center line to match notebook
+ self.VL, self.VT = tabs
nx0 = self.nx0
ny = self.ny // 2
@@ -35,12 +33,12 @@ class FugaDeflection(FugaUtils, DeflectionModel):
fT = np.cumsum(np.concatenate([np.zeros((ny, 1)), ((VT[:, :-1] + VT[:, 1:]) / 2)], 1), 1)
# subtract rotor center
- fL = (fL - fL[:, nx0 - 1:nx0]) * self.dx
- fT = (fT - fT[:, nx0 - 1:nx0]) * self.dx
+ fL = (fL - fL[:, nx0:nx0 + 1]) * self.dx
+ fT = (fT - fT[:, nx0:nx0 + 1]) * self.dx
self.fLtab = fL = np.concatenate([-fL[::-1], fL[1:]], 0)
self.fTtab = fT = np.concatenate([fT[::-1], fT[1:]], 0)
- self.fLT = GridInterpolator([self.x + self.dx, self.mirror(self.y, anti_symmetric=True)], np.array([fL, fT]).T)
+ self.fLT = GridInterpolator([self.x, self.mirror(self.y, anti_symmetric=True)], np.array([fL, fT]).T)
def calc_deflection(self, dw_ijl, hcw_ijl, dh_ijl, WS_ilk, WS_eff_ilk, yaw_ilk, ct_ilk, D_src_il, **_):
I, L, K = ct_ilk.shape
@@ -49,18 +47,25 @@ class FugaDeflection(FugaUtils, DeflectionModel):
WS_hub_ilk = WS_ilk
- cos_ilk, sin_ilk = np.cos(yaw_ilk), np.sin(yaw_ilk)
-
- F_ilk = ct_ilk * (WS_eff_ilk * cos_ilk)**2 / (WS_ilk * WS_hub_ilk)
-
- # For at given cross wind position in the lookup tables, lut_y, the deflection is lambda(lut_y), i.e.
- # the real position (corresponding to hcw), is y = lut_y + lambda(lut_y)
- # To find lut_y we calculate y for a range of lut_y grid points around y and interpolate
- lut_y_ijlx = (np.round(hcw_ijl[:, :, :, na] / self.dy) + np.arange(-X // 2, X // 2)[na, na, na]) * self.dy
-
- # calculate deflection, lambda(lut_y) = # F * (cos(yaw) * fT(lut_y) + sin(yaw) * fL(lut_y)
- dw_ijlx = np.repeat(dw_ijl[:, :, :, na], X, 3)
- if J < 1000:
+ theta_ilk = np.deg2rad(yaw_ilk)
+ cos_ilk, sin_ilk = np.cos(theta_ilk), np.sin(theta_ilk)
+
+ F_ilk = ct_ilk * (WS_eff_ilk)**2 / (WS_ilk * WS_hub_ilk)
+
+ """
+ For at given cross wind position in the lookup tables, yp, the deflection is lambda2p(yp), i.e.
+ the real position (corresponding to the output hcw), is yp = y - lambda2p(yp) = y - lambda2(y),
+ where y is the input hcw. I.e.:
+ lambda(y) = lambda(yp + lp(yp)) = lp(yp)
+ and
+ yp = y - lambda(y)
+ """
+
+ if 0: # J < 1000:
+ # To find lut_y we calculate y for a range of lut_y grid points around y and interpolate
+ lut_y_ijlx = (np.round(hcw_ijl[:, :, :, na] / self.dy) + np.arange(-X // 2, X // 2)[na, na, na]) * self.dy
+ dw_ijlx = np.repeat(dw_ijl[:, :, :, na], X, 3)
+ # calculate deflection, lambda(lut_y) = # F * (cos(yaw) * fT(lut_y) + sin(yaw) * fL(lut_y)
fL, fT = self.fLT(np.array([dw_ijlx.flatten(), lut_y_ijlx.flatten()]).T).T
lambda_ijlkx = F_ilk[:, na, :, :, na] * (fL.reshape(I, J, L, 1, X) * cos_ilk[:, na, :, :, na] +
@@ -68,33 +73,102 @@ class FugaDeflection(FugaUtils, DeflectionModel):
# Calcuate deflected y
y_ijlkx = lut_y_ijlx[:, :, :, na] + lambda_ijlkx
- # assert (np.all(hcw_ijl < y_ijlkx.max((3, 4))))
- # assert (np.all(hcw_ijl > y_ijlkx.min((3, 4))))
-
hcw_ijlk = np.array([[[[np.interp(hcw_ijl[i, j, l], y_ijlkx[i, j, l, k], lut_y_ijlx[i, j, l])
for k in range(K)]
for l in range(L)]
for j in range(J)]
for i in range(I)])
else:
- dw_ijl_round = np.round(dw_ijl, 10)
x, y = self.fLT.x
- def get_hcw(i, l, k):
- lambda_xy = F_ilk[i, l, k] * \
- np.sum(self.fLT.V * [np.cos(yaw_ilk[i, l, k]), np.sin(yaw_ilk[i, l, k])], -1)
+# def get_hcw_jk(i, l):
+# x_idx = (np.searchsorted(x, [dw_ijl.min(), dw_ijl.max()]) + np.array([-1, 1]))
+# m_x = len(x) - 1
+# x_slice = slice(*np.minimum([m_x, m_x], np.maximum([0, 0], x_idx)))
+#
+# y_idx = (np.searchsorted(y, [hcw_ijl.min(), hcw_ijl.max()]) + np.array([-20, 20]))
+# m_y = len(y) - 1
+# y_slice = slice(*np.minimum([m_y, m_y], np.maximum([0, 0], y_idx)))
+#
+# x_ = x[x_slice]
+# y_ = y[y_slice]
+# VLT = self.fLT.V[x_slice, y_slice]
+#
+# def get_hcw_j(i, l, k):
+# lambda2p = F_ilk[i, l, k] * \
+# np.sum(VLT * [np.cos(theta_ilk[i, l, k]), np.sin(theta_ilk[i, l, k])], -1)
+# lambda2 = RegularGridInterpolator(
+# (x_, y_), [np.interp(y_, y_ + l2p_x, l2p_x) for l2p_x in lambda2p])
+#
+# hcw_j = hcw_ijl[i, :, l].copy()
+# m = (hcw_ijl[i, :, l] > y_[0]) & (hcw_ijl[i, :, l] < y_[-1])
+# hcw_j[m] -= lambda2((dw_ijl[i, :, l][m], hcw_ijl[i, :, l][m]))
+# return hcw_j
+# return [get_hcw_j(i, l, k) for k in range(K)]
+#
+# hcw_ijlk_old = np.moveaxis([[get_hcw_jk(i, l)
+# for l in range(L)]
+# for i in range(I)], 3, 1)
+
+ hcw_ijlk = np.array([self.get_hcw_jlk(i, K, L, x, y, dw_ijl, hcw_ijl, F_ilk, theta_ilk)
+ for i in range(I)])
+# npt.assert_array_almost_equal(hcw_ijlk_old, hcw_ijlk, 4)
- hcw_j = hcw_ijl[i, :, k]
- for v in np.unique(dw_ijl_round[i, :, l]):
- xi = np.searchsorted(x, v)
- lambda_y = (v - x[xi]) / self.dx * lambda_xy[xi + 1] + (x[xi + 1] - v) / self.dx * lambda_xy[xi]
- idx = dw_ijl_round[i, :, l] == v
- hcw_j[idx] = np.interp(hcw_j[idx], y + lambda_y, y)
- return hcw_j
+ return dw_ijl[:, :, :, na], hcw_ijlk, dh_ijl[..., na]
- hcw_ijlk = np.moveaxis([[[get_hcw(i, l, k)
- for k in range(K)]
- for l in range(L)]
- for i in range(I)], -1, 1)
+ def get_hcw_jlk(self, i, K, L, x, y, dw_ijl, hcw_ijl, F_ilk, theta_ilk):
+ if (K == 1 and L > 1 and np.all(dw_ijl == dw_ijl[:1, :, :1]) and np.all(hcw_ijl == hcw_ijl[:1, :, :1]) and
+ len(np.unique(theta_ilk[i, :, 0])) < L):
+ hcw_jlk = np.zeros((dw_ijl.shape[1], L, K))
+ for theta, l in zip(*np.unique(theta_ilk[i], return_index=True)):
+ hcw_jlk[:, theta_ilk[i, :, 0] == theta] = np.array(self.get_hcw_jk(
+ i, l, K, x, y, dw_ijl, hcw_ijl, F_ilk, theta_ilk)).T[:, na]
+ return hcw_jlk
- return dw_ijl[:, :, :, na], hcw_ijlk, dh_ijl[..., na]
+ else:
+ return np.moveaxis([self.get_hcw_jk(i, l, K, x, y, dw_ijl, hcw_ijl, F_ilk, theta_ilk)
+ for l in range(L)], 2, 0)
+
+ def get_hcw_jk(self, i, l, K, x, y, dw_ijl, hcw_ijl, F_ilk, theta_ilk):
+ x_idx = (np.searchsorted(x, [dw_ijl.min(), dw_ijl.max()]) + np.array([-1, 1]))
+ m_x = len(x) + 1
+ x_slice = slice(*np.minimum([m_x, m_x], np.maximum([0, 0], x_idx)))
+
+ y_idx = (np.searchsorted(y, [hcw_ijl.min(), hcw_ijl.max()]) + np.array([-20, 20]))
+ m_y = len(y) + 1
+ y_slice = slice(*np.minimum([m_y, m_y], np.maximum([0, 0], y_idx)))
+
+ x_ = x[x_slice]
+ y_ = y[y_slice]
+ VLT = self.fLT.V[x_slice, y_slice]
+ return [self.get_hcw_j(i, l, k, F_ilk, VLT, theta_ilk, x_, y_, hcw_ijl, dw_ijl) for k in range(K)]
+
+ def get_hcw_j(self, i, l, k, F_ilk, VLT, theta_ilk, x_, y_, hcw_ijl, dw_ijl):
+ lambda2p = F_ilk[i, l, k] * \
+ np.sum(VLT * [np.cos(theta_ilk[i, l, k]), np.sin(theta_ilk[i, l, k])], -1)
+ lambda2 = RegularGridInterpolator(
+ (x_, y_), [np.interp(y_, y_ + l2p_x, l2p_x) for l2p_x in lambda2p])
+
+ hcw_j = hcw_ijl[i, :, l].copy()
+ m = (hcw_ijl[i, :, l] > y_[0]) & (hcw_ijl[i, :, l] < y_[-1])
+ hcw_j[m] -= lambda2((dw_ijl[i, :, l][m], hcw_ijl[i, :, l][m]))
+ return hcw_j
+
+
+def main():
+ if __name__ == '__main__':
+ from py_wake import Fuga
+ from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines
+ import matplotlib.pyplot as plt
+
+ site = IEA37Site(16)
+ x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
+ windTurbines = IEA37_WindTurbines()
+ path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
+ noj = Fuga(path, site, windTurbines, deflectionModel=FugaDeflection(path))
+ yaw = [-30, 30, 0]
+ noj(x, y, yaw=yaw, wd=270, ws=10).flow_map().plot_wake_map()
+ plt.show()
+
+
+main()
diff --git a/py_wake/deflection_models/jimenez.py b/py_wake/deflection_models/jimenez.py
index 78b897cc7..bb3ee673d 100644
--- a/py_wake/deflection_models/jimenez.py
+++ b/py_wake/deflection_models/jimenez.py
@@ -18,8 +18,8 @@ class JimenezWakeDeflection(DeflectionModel):
def calc_deflection(self, dw_ijl, hcw_ijl, dh_ijl, D_src_il, yaw_ilk, ct_ilk, **kwargs):
dw_lst = (np.logspace(0, 1.1, self.N) - 1) / (10**1.1 - 1)
dw_ijxl = dw_ijl[:, :, na] * dw_lst[na, na, :, na]
-
- denominator_ilk = np.cos(yaw_ilk)**2 * np.sin(yaw_ilk) * (ct_ilk / 2)
+ theta_ilk = np.deg2rad(yaw_ilk)
+ denominator_ilk = np.cos(theta_ilk)**2 * np.sin(theta_ilk) * (ct_ilk / 2)
nominator_ijxl = (1 + (self.beta / D_src_il)[:, na, na, :] * dw_ijxl)**2
alpha = denominator_ilk[:, na, na] / nominator_ijxl[..., na]
deflection_ijlk = np.trapz(np.sin(alpha), dw_ijxl[..., na], axis=2)
@@ -37,13 +37,10 @@ def main():
from py_wake.tests.test_files import tfp
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'
noj = Fuga(path, site, windTurbines, deflectionModel=JimenezWakeDeflection())
- yaw_ilk = np.zeros((len(x), 1, 1))
- yaw_ilk[:, 0, 0] = [-30, 30, 0]
- noj(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10).flow_map().plot_wake_map()
+ yaw = [-30, 30, 0]
+ noj(x, y, yaw=yaw, wd=270, ws=10).flow_map().plot_wake_map()
import matplotlib.pyplot as plt
plt.show()
- pass
-
main()
diff --git a/py_wake/examples/data/iea34_130rwt/_iea34_130rwt.py b/py_wake/examples/data/iea34_130rwt/_iea34_130rwt.py
index 306866d5d..4ba89ed3d 100644
--- a/py_wake/examples/data/iea34_130rwt/_iea34_130rwt.py
+++ b/py_wake/examples/data/iea34_130rwt/_iea34_130rwt.py
@@ -6,6 +6,7 @@ import inspect
from py_wake.wind_turbines.power_ct_functions import PowerCtSurrogate
from py_wake.wind_turbines.wind_turbine_functions import FunctionSurrogates
from py_wake.examples.data import example_data_path
+from py_wake.utils.model_utils import fix_shape
class IEA34_130_PowerCtSurrogate(PowerCtSurrogate):
@@ -26,7 +27,7 @@ class IEA34_130_PowerCtSurrogate(PowerCtSurrogate):
def _power_ct(self, ws, run_only, **kwargs):
m = (ws > self.ws_cutin) & (ws < self.ws_cutout)
- kwargs = {k: self.fix_shape(v, ws)[m] for k, v in kwargs.items()}
+ kwargs = {k: fix_shape(v, ws)[m] for k, v in kwargs.items()}
arr_m = PowerCtSurrogate._power_ct(self, ws[m], run_only=run_only, **kwargs)
if run_only == 0:
power = np.zeros_like(ws)
@@ -49,7 +50,7 @@ class ThreeRegionLoadSurrogates(FunctionSurrogates):
def __call__(self, ws, run_only=slice(None), **kwargs):
ws_flat = ws.ravel()
x = self.get_input(ws=ws, **kwargs)
- x = np.array([self.fix_shape(v, ws).ravel() for v in x]).T
+ x = np.array([fix_shape(v, ws).ravel() for v in x]).T
def predict(fs):
output = np.empty(len(x))
diff --git a/py_wake/examples/data/lillgrund.py b/py_wake/examples/data/lillgrund.py
index 11c177367..c1994ae19 100644
--- a/py_wake/examples/data/lillgrund.py
+++ b/py_wake/examples/data/lillgrund.py
@@ -91,7 +91,8 @@ LillgrundSWT23 = SWT23
class LillgrundSite(UniformWeibullSite):
def __init__(self, shear=None):
- f = [3.8, 4.5, 0.4, 2.8, 8.3, 7.5, 9.9, 14.8, 14.3, 17.0, 12.6, 4.1]
+ f = np.array([3.8, 4.5, 0.4, 2.8, 8.3, 7.5, 9.9, 14.8, 14.3, 17.0, 12.6, 4.1])
+ f /= f.sum()
a = [4.5, 4.7, 3.0, 7.2, 8.8, 8.2, 8.4, 9.5, 9.2, 9.9, 10.3, 6.7]
k = [1.69, 1.78, 1.82, 1.70, 1.97, 2.49, 2.72, 2.70, 2.88, 3.34, 2.84, 2.23]
UniformWeibullSite.__init__(self, f, a, k, .1, shear=shear)
diff --git a/py_wake/flow_map.py b/py_wake/flow_map.py
index 82cc98f08..4d2915e00 100644
--- a/py_wake/flow_map.py
+++ b/py_wake/flow_map.py
@@ -173,7 +173,7 @@ class FlowMap(FlowBox):
def plot_windturbines(self, normalize_with=1, ax=None):
fm = self.windFarmModel
- yaw = self.simulationResult.Yaw.sel(wd=self.wd[0]).mean(['ws']).data
+ yaw = self.simulationResult.yaw.sel(wd=self.wd[0]).mean(['ws']).data
if self.plane[0] == "YZ":
x_i, y_i = self.simulationResult.x.values, self.simulationResult.y.values
h_i = self.simulationResult.h.values
@@ -270,7 +270,7 @@ class FlowMap(FlowBox):
from py_wake.utils.model_utils import get_model_input
kwargs = get_model_input(self.windFarmModel, X.flatten(), Y.flatten(), ws=self.ws, wd=self.wd,
- yaw_ilk=self.simulationResult.Yaw.ilk())
+ yaw=self.simulationResult.yaw.ilk())
dw, hcw, dh = self.windFarmModel.deflectionModel.calc_deflection(**kwargs)
Yp = -hcw[0, :, 0, 0].reshape(X.shape)
ax = ax or plt.gca()
diff --git a/py_wake/tests/test_deficit_models/test_deficit_models.py b/py_wake/tests/test_deficit_models/test_deficit_models.py
index 924c221b6..7a490ea83 100644
--- a/py_wake/tests/test_deficit_models/test_deficit_models.py
+++ b/py_wake/tests/test_deficit_models/test_deficit_models.py
@@ -48,11 +48,11 @@ class GCLLocalDeficit(GCLDeficit):
14899.26913, 32320.21637, 67039.04091, 17912.40907, 12225.04134,
7513.75582])),
(IEA37SimpleBastankhahGaussianDeficit(), read_iea37_windfarm(iea37_path + 'iea37-ex16.yaml')[2]),
- (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'),
- (398938.8941139709, [9632.92248, 9733.98766, 12462.98413, 15332.30502, 22199.91899,
- 27683.32851, 42975.80734, 49481.10395, 24274.96466, 15416.63681,
- 16681.20957, 35508.27583, 75263.59612, 19679.2854, 13687.14632,
- 8925.42131])),
+ (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'),
+ (404440.47891147854, [9912.3179, 9762.02876, 12510.08811, 15396.72801, 23017.60689,
+ 27799.6478, 43138.23486, 49623.64621, 24979.0411, 15460.41439,
+ 16722.95386, 35694.269, 77968.97181, 19782.36595, 13721.39804,
+ 8950.76623])),
(GCLDeficit(), (370863.6246093183,
[9385.75387, 8768.52105, 11450.13309, 14262.42186, 21178.74926,
25751.59502, 39483.21753, 44573.31533, 23652.09976, 13924.58752,
@@ -106,7 +106,7 @@ def test_IEA37_ex16(deficitModel, aep_ref):
[0.18, 3.6, 7.27, 8.32, 7.61, 6.64, 5.96, 6.04, 6.8, 7.69, 8.08, 7.87, 7.59, 7.46, 7.55, 7.84, 8.19]),
(IEA37SimpleBastankhahGaussianDeficit(),
[3.32, 4.86, 7.0, 8.1, 7.8, 7.23, 6.86, 6.9, 7.3, 7.82, 8.11, 8.04, 7.87, 7.79, 7.85, 8.04, 8.28]),
- (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'),
+ (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'),
[6.91, 7.87, 8.77, 8.88, 8.55, 7.88, 7.24, 7.32, 8.01, 8.62, 8.72, 8.42, 8.05, 7.85, 8., 8.37, 8.69]),
(GCLDeficit(),
[2.39, 5.01, 7.74, 8.34, 7.95, 7.58, 7.29, 7.32, 7.61, 7.92, 8.11, 8.09, 7.95, 7.83, 7.92, 8.1, 8.3]),
@@ -160,7 +160,7 @@ def test_deficitModel_wake_map(deficitModel, ref):
[83.336286, 57.895893, 115.791786, 75.266662, 83.336286]),
(IEA37SimpleBastankhahGaussianDeficit(),
[83.336286, 57.895893, 115.791786, 75.266662, 83.336286]),
- (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'),
+ (FugaDeficit(LUT_path=tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'),
[100, 50, 100, 100, 100]),
(GCLDeficit(),
[156.949964, 97.763333, 195.526667, 113.225695, 111.340236]),
@@ -370,11 +370,11 @@ def test_deficitModel_wake_map_convection_all2all(deficitModel, ref):
14899.26913, 32320.21637, 67039.04091, 17912.40907, 12225.04134,
7513.75582])),
(IEA37SimpleBastankhahGaussian, read_iea37_windfarm(iea37_path + 'iea37-ex16.yaml')[2]),
- (lambda *args, **kwargs: Fuga(tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/', *args, **kwargs),
- (398938.8941139709, [9632.92248, 9733.98766, 12462.98413, 15332.30502, 22199.91899,
- 27683.32851, 42975.80734, 49481.10395, 24274.96466, 15416.63681,
- 16681.20957, 35508.27583, 75263.59612, 19679.2854, 13687.14632,
- 8925.42131])),
+ (lambda *args, **kwargs: Fuga(tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/', *args, **kwargs),
+ (404440.47891147854, [9912.3179, 9762.02876, 12510.08811, 15396.72801, 23017.60689,
+ 27799.6478, 43138.23486, 49623.64621, 24979.0411, 15460.41439,
+ 16722.95386, 35694.269, 77968.97181, 19782.36595, 13721.39804,
+ 8950.76623])),
(GCL, (370863.6246093183,
[9385.75387, 8768.52105, 11450.13309, 14262.42186, 21178.74926,
25751.59502, 39483.21753, 44573.31533, 23652.09976, 13924.58752,
diff --git a/py_wake/tests/test_deficit_models/test_fuga.py b/py_wake/tests/test_deficit_models/test_fuga.py
index 0c06c5c5a..0d254558b 100644
--- a/py_wake/tests/test_deficit_models/test_fuga.py
+++ b/py_wake/tests/test_deficit_models/test_fuga.py
@@ -102,15 +102,15 @@ def test_fuga_new_format():
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
- path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'
+ path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wake_model = Fuga(path, site, wts)
res = wake_model(x=wt_x, y=wt_y, wd=[30], ws=[10])
- npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(), [10.00725165, 10., 7.92176401, 10.02054952, 9.40501317,
- 7.92609363, 7.52384558], 8)
- npt.assert_array_almost_equal(res.ct_ilk.flatten(), [0.79260841, 0.793, 0.80592176, 0.79189033, 0.80132982,
- 0.80592609, 0.80552385], 8)
+ npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(), [10.00648185, 10., 8.21713811, 10.03039502, 9.36887205,
+ 8.23084156, 7.80661768], 8)
+ npt.assert_array_almost_equal(res.ct_ilk.flatten(), [0.79264998, 0.793, 0.80621714, 0.79135867, 0.80183579,
+ 0.80623084, 0.80580662], 8)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
@@ -138,21 +138,21 @@ def test_fuga_new_format():
npt.assert_array_almost_equal(
Z70[140, 100:400:10],
- [10.0458, 10.0309, 10.065, 10.0374, 9.7865, 7.7119, 6.4956, 9.2753, 10.0047, 10.0689,
- 10.0444, 10.0752, 10.0699, 9.1852, 6.9783, 9.152, 10.0707, 10.0477, 10.0365, 9.9884,
- 9.2867, 7.5714, 6.4451, 8.3276, 9.9976, 10.0251, 10.0264, 10.023, 10.0154, 9.9996], 4)
+ [10.0384, 10.042, 10.044, 10.0253, 9.7194, 7.7561, 6.7421, 9.2308, 9.9894, 10.0413, 10.0499,
+ 10.0579, 10.0437, 9.1626, 7.2334, 9.1208, 10.0396, 10.0322, 10.0276, 9.9504, 9.2861, 7.8375,
+ 6.6608, 8.3343, 9.9756, 10.0229, 10.0136, 10.0142, 10.0118, 10.0094], 4)
npt.assert_array_almost_equal(
Z73[140, 100:400:10],
- [10.0458, 10.0309, 10.065, 10.0374, 9.7865, 7.7119, 6.4956, 9.2753, 10.0047, 10.0689,
- 10.0444, 10.0752, 10.0699, 9.1852, 6.9783, 9.152, 10.0707, 10.0477, 10.0365, 9.9884,
- 9.2867, 7.5714, 6.4451, 8.3276, 9.9976, 10.0251, 10.0264, 10.023, 10.0154, 9.9996], 4)
+ [10.0384, 10.042, 10.044, 10.0253, 9.7194, 7.7561, 6.7421, 9.2308, 9.9894, 10.0413, 10.0499,
+ 10.0579, 10.0437, 9.1626, 7.2334, 9.1208, 10.0396, 10.0322, 10.0276, 9.9504, 9.2861, 7.8375,
+ 6.6608, 8.3343, 9.9756, 10.0229, 10.0136, 10.0142, 10.0118, 10.0094], 4)
def test_fuga_downwind():
wts = HornsrevV80()
- path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0'
+ path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wfm_UL = Fuga(path, site, wts)
@@ -162,16 +162,16 @@ def test_fuga_downwind():
def plot(wfm, yaw, ax, min_ws):
levels = np.arange(6.5, 10.5, .5)
- sim_res = wfm([0], [0], wd=270, ws=10, yaw_ilk=[[[yaw]]])
+ sim_res = wfm([0], [0], wd=270, ws=10, yaw=[[[yaw]]])
fm = sim_res.flow_map(XYGrid(x=np.arange(-100, 500, 5)))
npt.assert_almost_equal(fm.WS_eff.min(), min_ws)
fm.plot_wake_map(ax=ax, levels=levels)
fm.min_WS_eff(fm.x, 70).plot(ax=ax, color='r')
plt.axhline(0, color='k')
- plot(wfm_UL, 0, ax1, 6.89020003)
- plot(wfm_UL, 30, ax2, 7.62747285)
- plot(wfm_ULT, 0, ax3, 6.89020003)
- plot(wfm_ULT, 30, ax4, 7.94525864)
+ plot(wfm_UL, 0, ax1, 7.15850569)
+ plot(wfm_UL, 30, ax2, 7.83216849)
+ plot(wfm_ULT, 0, ax3, 7.15850569)
+ plot(wfm_ULT, 30, ax4, 8.12259776)
if 0:
plt.show()
@@ -189,7 +189,7 @@ def test_fuga_downwind_vs_notebook():
WS = 10
p = Path(tfp) / "fuga/v80_wake_4d_y_no_deflection.csv"
y, notebook_deficit_4d = np.array([v.split(",") for v in p.read_text().strip().split("\n")], dtype=float).T
- sim_res = wfm_ULT([0], [0], wd=270, ws=WS, yaw_ilk=[[[17.4493]]])
+ sim_res = wfm_ULT([0], [0], wd=270, ws=WS, yaw=[[[17.4493]]])
fm = sim_res.flow_map(XYGrid(4 * wt.diameter(), y=y))
npt.assert_allclose(fm.WS_eff.squeeze() - WS, notebook_deficit_4d, atol=1e-6)
@@ -276,7 +276,7 @@ def test_lut_exists():
assert fuga_utils.lut_exists([154]) == set([])
assert fuga_utils.lut_exists([155]) == {'UL'}
- path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'
+ path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
fuga_utils = FugaUtils(path, on_mismatch='input_par')
assert fuga_utils.lut_exists() == {'UL', 'UT', 'VL', 'VT'}
assert fuga_utils.lut_exists([154]) == set([])
@@ -286,7 +286,7 @@ def test_lut_exists():
def test_interpolation():
wts = HornsrevV80()
- path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'
+ path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
plot = 0
@@ -301,7 +301,7 @@ def test_interpolation():
):
wfm = PropagateDownwind(site, wts, wdm)
- sim_res = wfm(x=[0], y=[0], wd=[270], ws=[10], yaw_ilk=[[[10]]])
+ sim_res = wfm(x=[0], y=[0], wd=[270], ws=[10], yaw=[[[10]]])
fm = sim_res.flow_map(XYGrid(x=[200], y=np.arange(-10, 11)))
fm = sim_res.flow_map(XYGrid(x=np.arange(-100, 800, 10), y=np.arange(-10, 11)))
diff --git a/py_wake/tests/test_deflection_models/test_deflection_models.py b/py_wake/tests/test_deflection_models/test_deflection_models.py
index 0444aee84..8a7581265 100644
--- a/py_wake/tests/test_deflection_models/test_deflection_models.py
+++ b/py_wake/tests/test_deflection_models/test_deflection_models.py
@@ -15,8 +15,8 @@ from py_wake.tests.test_files import tfp
@pytest.mark.parametrize('deflectionModel,dy10d', [
(JimenezWakeDeflection, 0.5672964),
- ((lambda: FugaDeflection(tfp + 'fuga/D080.0000_zH070.0000/Z0=0.03000000Zi=00401Zeta0=0.00E+00/')), 0.2567786526168626),
- ((lambda: FugaDeflection(tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/')), 0.33216633496287334),
+ ((lambda: FugaDeflection(tfp + 'fuga/D080.0000_zH070.0000/Z0=0.03000000Zi=00401Zeta0=0.00E+00/')), 0.33771119153150087),
+ ((lambda: FugaDeflection(tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/')), 0.37719131706149484),
])
def test_deflection_model(deflectionModel, dy10d):
site = IEA37Site(16)
@@ -27,7 +27,7 @@ def test_deflection_model(deflectionModel, dy10d):
yaw_ilk = np.reshape([-30], (1, 1, 1))
- sim_res = wfm(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10)
+ sim_res = wfm(x, y, yaw=yaw_ilk, wd=270, ws=10)
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
min_WS_line = fm.min_WS_eff()
if 0:
@@ -51,7 +51,7 @@ def test_plot_deflection_grid(deflectionModel):
yaw_ilk = np.reshape([-30], (1, 1, 1))
- sim_res = wfm(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10)
+ sim_res = wfm(x, y, yaw=yaw_ilk, wd=270, ws=10)
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
plt.figure(figsize=(14, 3))
@@ -60,6 +60,7 @@ def test_plot_deflection_grid(deflectionModel):
min_WS_line = fm.min_WS_eff()
min_WS_line.plot()
plt.legend()
+ plt.title(wfm.deflectionModel)
if 0:
plt.show()
plt.close('all')
diff --git a/py_wake/tests/test_deflection_models/test_fuga_deflection.py b/py_wake/tests/test_deflection_models/test_fuga_deflection.py
new file mode 100644
index 000000000..7c6ab1b2d
--- /dev/null
+++ b/py_wake/tests/test_deflection_models/test_fuga_deflection.py
@@ -0,0 +1,99 @@
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+from py_wake.deficit_models.fuga import FugaYawDeficit
+from py_wake.flow_map import XYGrid
+from py_wake.site.xrsite import UniformSite
+from py_wake.tests.test_files import tfp
+from py_wake.wind_farm_models.engineering_models import PropagateDownwind
+from py_wake.wind_turbines._wind_turbines import WindTurbine
+from py_wake.wind_turbines.power_ct_functions import PowerCtTabular
+from py_wake.tests import npt
+from py_wake.deflection_models.fuga_deflection import FugaDeflection
+from scipy.interpolate.fitpack2 import InterpolatedUnivariateSpline
+from py_wake.examples.data.hornsrev1 import V80, Hornsrev1Site
+
+
+def test_fuga_deflection_vs_notebook():
+
+ p = Path(tfp) / "fuga/v80_deflection_x.csv"
+ x, notebook_deflection = np.array([v.split(",") for v in p.read_text().strip().split("\n")], dtype=float).T
+
+ path = tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00'
+ fuga_deflection = -FugaDeflection(path).calc_deflection(dw_ijl=np.reshape(x, (1, 41, 1)),
+ hcw_ijl=np.reshape(x * 0, (1, 41, 1)),
+ dh_ijl=np.reshape(x * 0, (1, 41, 1)),
+ WS_ilk=np.array([[[9.5]]]),
+ WS_eff_ilk=np.array([[[9.5]]]),
+ yaw_ilk=np.array([[[17.4493]]]),
+ ct_ilk=np.array([[[0.850877]]]) *
+ np.cos(0.30454774)**2,
+ D_src_il=np.array([[80]]))[1].squeeze()
+
+ if 0:
+ plt.plot(x, notebook_deflection, label='Notebook deflection')
+ plt.plot(x, fuga_deflection)
+ plt.show()
+ plt.close('all')
+ npt.assert_allclose(fuga_deflection, notebook_deflection, atol=1e-5)
+
+
+def test_fuga_wake_center_vs_notebook():
+
+ p = Path(tfp) / "fuga/v80_wake_center_x.csv"
+ x, notebook_wake_center = np.array([v.split(",") for v in p.read_text().strip().split("\n")], dtype=float).T
+
+ powerCtFunction = PowerCtTabular([0, 100], [0, 0], 'w', [0.850877, 0.850877])
+ wt = WindTurbine(name='', diameter=80, hub_height=70, powerCtFunction=powerCtFunction)
+
+ path = tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00'
+ site = UniformSite([1, 0, 0, 0], ti=0.075)
+
+ wfm = PropagateDownwind(
+ site,
+ wt,
+ wake_deficitModel=FugaYawDeficit(path),
+ deflectionModel=FugaDeflection(path, 'input_par')
+ )
+
+ WS = 10
+ sim_res = wfm([0], [0], yaw=[17.4493], wd=270, ws=[WS])
+ y = wfm.wake_deficitModel.mirror(wfm.wake_deficitModel.y, anti_symmetric=True)
+ fm = sim_res.flow_map(XYGrid(x=x[1:], y=y[240:271]))
+ fuga_wake_center = [np.interp(0, InterpolatedUnivariateSpline(ws.y, ws.values).derivative()(ws.y), ws.y)
+ for ws in fm.WS_eff.squeeze().T]
+
+ if 0:
+ plt.plot(x, notebook_wake_center, label='Notebook deflection')
+ plt.plot(x[1:], fuga_wake_center)
+ plt.show()
+ plt.close('all')
+ npt.assert_allclose(fuga_wake_center, notebook_wake_center[1:], atol=.14)
+
+
+def test_fuga_deflection_time_series_gradient_evaluation():
+
+ p = Path(tfp) / "fuga/v80_wake_center_x.csv"
+ x, notebook_wake_center = np.array([v.split(",") for v in p.read_text().strip().split("\n")], dtype=float).T
+
+ powerCtFunction = PowerCtTabular([0, 100], [0, 0], 'w', [0.850877, 0.850877])
+ wt = WindTurbine(name='', diameter=80, hub_height=70, powerCtFunction=powerCtFunction)
+
+ path = tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00'
+ site = UniformSite([1, 0, 0, 0], ti=0.075)
+
+ wfm = PropagateDownwind(
+ site,
+ wt,
+ wake_deficitModel=FugaYawDeficit(path),
+ deflectionModel=FugaDeflection(path, 'input_par')
+ )
+
+ WS = 10
+
+ yaw_ref = np.full((10, 1), 17)
+ yaw_step = np.eye(10, 10) * 1e-6 + yaw_ref
+ yaw = np.concatenate([yaw_step, yaw_ref], axis=1)
+ sim_res = wfm(np.arange(10) * wt.diameter() * 4, [0] * 10, yaw=yaw, wd=[270] * 11, ws=[WS] * 11, time=True)
+ print(sim_res)
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UL.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UL.dat
index c5493559a..277ac541b 100644
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UL.dat
+++ b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UL.dat
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:6ae9d960b6aa6e3bea5dcc8f680b45dd292e18b3a2d899027276eaa2127f5855
+oid sha256:fdc4674f54eda7a21d77f74684ad85441742c2af4820010b0a4c5fa601c3afc2
size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UT.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UT.dat
index c527f4052..22d9fc7a4 100644
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UT.dat
+++ b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999UT.dat
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:816ae6d7561d6eeed01059b689bbbd2fc95d94e507799cf2a26e15a63073b5ad
+oid sha256:fea17008dad54664802228a355e24e7ef7798bc8e4b0b7cb3cbbd0fa10a731dc
size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VL.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VL.dat
index c804e05d5..cab166bca 100644
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VL.dat
+++ b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VL.dat
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:279d592c9ba10231a4a00d4bf1f882fc90375efe0658b1c0708e17e041ef68bd
+oid sha256:2b78e10fcc7755424c9035ae397e976bfc84984c5bf51b667f70f901b81526dd
size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VT.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VT.dat
index 25eccb775..f9c5aaba2 100644
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VT.dat
+++ b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/D080.0000_zH070.0000_FIT9999VT.dat
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:1e484d482718447b3a8031dc63e9448cf96844a70876b938802186452157be74
+oid sha256:5765f83f3d0cd8e0b4476fa03ab4e97bbf58184ecb5e7283833eea2411e05718
size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/inputfile.par b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/inputfile.par
index 523c34a69..93ed00445 100644
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/inputfile.par
+++ b/py_wake/tests/test_files/fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00/inputfile.par
@@ -4,15 +4,15 @@ D080.0000_zH070.0000_FIT
512
20.0
5.0
-80.0
+80
20.0
0.00001000
-400.0
+400
70.00
9999
9999
-/builds/TOPFARM/cuttingedge/pywake/fuga/easylut/lut/
+C:\mmpe\programming\python\Topfarm\CuttingEdge\Fuga\Easylut/lut/
D080.0000_zH070.0000/Z0=0.00001000Zi=00400Zeta0=0.00E+00/
-preLUTs_Zeta0=0.00E+00/parameters.bin
-UL
+preLUTs_Zeta0=0.00E+00_32_64_0.35_9/parameters.bin
+PT
BINARY
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UL.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UL.dat
deleted file mode 100644
index acdc576ff..000000000
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UL.dat
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2f84a1f3c1573785d7cb492d8405d53ee6989d89a075d510ea0b04cdff4d4250
-size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UT.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UT.dat
deleted file mode 100644
index 574d2c093..000000000
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999UT.dat
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:bde682803af9afe0d32a8ffd9dadaaee59ef2c1bd64a491825f84e75661ba69c
-size 2097152
diff --git a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999VL.dat b/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999VL.dat
deleted file mode 100644
index 1e1432c1d..000000000
--- a/py_wake/tests/test_files/fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/2MW_FIT9999VL.dat
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
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new file mode 100644
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diff --git a/py_wake/tests/test_files/fuga/v80_deflection_x.csv b/py_wake/tests/test_files/fuga/v80_deflection_x.csv
index c6dcd4256..10dac03ad 100644
--- a/py_wake/tests/test_files/fuga/v80_deflection_x.csv
+++ b/py_wake/tests/test_files/fuga/v80_deflection_x.csv
@@ -1,41 +1,41 @@
0.,0.
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diff --git a/py_wake/tests/test_files/fuga/v80_wake_4d_y_no_deflection.csv b/py_wake/tests/test_files/fuga/v80_wake_4d_y_no_deflection.csv
index 1a478b7b8..73383dcf8 100644
--- a/py_wake/tests/test_files/fuga/v80_wake_4d_y_no_deflection.csv
+++ b/py_wake/tests/test_files/fuga/v80_wake_4d_y_no_deflection.csv
@@ -1,5 +1,5 @@
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--5.,-2.691691715215587
-0.,-2.7148103630291347
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diff --git a/py_wake/tests/test_files/fuga/v80_wake_center_x.csv b/py_wake/tests/test_files/fuga/v80_wake_center_x.csv
index e7192480a..8e0a9df62 100644
--- a/py_wake/tests/test_files/fuga/v80_wake_center_x.csv
+++ b/py_wake/tests/test_files/fuga/v80_wake_center_x.csv
@@ -1,41 +1,41 @@
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diff --git a/py_wake/tests/test_flow_map.py b/py_wake/tests/test_flow_map.py
index f45874fc8..67e085ad3 100644
--- a/py_wake/tests/test_flow_map.py
+++ b/py_wake/tests/test_flow_map.py
@@ -228,7 +228,7 @@ def test_min_ws_eff_line():
yaw_ilk = np.reshape([-30, 30, 0], (3, 1, 1))
plt.figure(figsize=(14, 3))
- fm = wfm(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10).flow_map(
+ fm = wfm(x, y, yaw=yaw_ilk, wd=270, ws=10).flow_map(
XYGrid(x=np.arange(-100, 2000, 10), y=np.arange(-500, 500, 10)))
min_ws_line = fm.min_WS_eff()
diff --git a/py_wake/tests/test_load_surrogates/test_iea34_surrogates.py b/py_wake/tests/test_load_surrogates/test_iea34_surrogates.py
index 43ef13062..e04c28c27 100644
--- a/py_wake/tests/test_load_surrogates/test_iea34_surrogates.py
+++ b/py_wake/tests/test_load_surrogates/test_iea34_surrogates.py
@@ -111,6 +111,40 @@ def test_two_turbine_case0():
npt.assert_array_almost_equal(loads.LDEL.sel(wt=0).squeeze(), (loads.DEL.sel(wt=0).squeeze()**m * f)**(1 / m))
+def test_two_turbine_case0_time_series():
+ # same as test_two_turbine_case0
+ ws, ti, shear, wdir, dist = [10.9785338191, 0.2623204277, 0.4092031776, -38.4114616871 % 360, 5.123719529]
+
+ # ref from simulation statistic (not updated yet)
+ ws_ref = 1.103937e+01
+ thrust_ref = 4.211741e+02
+ power_ref = 3.399746e+06
+ ref_dels = [4546, 5931, 11902, 7599, 2407]
+
+ wt = IEA34_130_2WT_Surrogate()
+ site = UniformSite(p_wd=[1], ti=ti, ws=ws)
+ wfm = NOJ(site, wt, turbulenceModel=STF2017TurbulenceModel())
+ sim_res = wfm([0, 0], [0, dist * 130], wd=wdir, time=True, Alpha=shear)
+ assert sim_res.dw_ijl.dims == ('wt', 'wt', 'time')
+
+ npt.assert_allclose(ws, ws_ref, rtol=.006)
+ # npt.assert_allclose(ti, ws_std_ref / ws_ref, atol=.19)
+ npt.assert_allclose(sim_res.Power.sel(wt=0), power_ref, rtol=0.002)
+ npt.assert_allclose(sim_res.CT.sel(wt=0), thrust_ref * 1e3 / (1 / 2 * 1.225 * (65**2 * np.pi) * ws_ref**2),
+ rtol=0.03)
+ sim_res['duration'] = ('time', [3600 * 24 * 365 * 20])
+ loads = sim_res.loads(method='TwoWT')
+ npt.assert_allclose(loads.DEL.sel(wt=0).squeeze(), ref_dels, rtol=.05)
+
+ f = 20 * 365 * 24 * 3600 / 1e7
+ m = loads.m.values
+ npt.assert_array_almost_equal(loads.LDEL.sel(wt=0).squeeze(), (loads.DEL.sel(wt=0).squeeze()**m * f)**(1 / m))
+
+ loads = sim_res.loads(method='TwoWT', softmax_base=100)
+ npt.assert_allclose(loads.DEL.sel(wt=0).squeeze(), ref_dels, rtol=.05)
+ npt.assert_array_almost_equal(loads.LDEL.sel(wt=0).squeeze(), (loads.DEL.sel(wt=0).squeeze()**m * f)**(1 / m))
+
+
def test_functionSurrogate():
surrogate_path = Path(example_data_path) / 'iea34_130rwt' / 'one_turbine'
load_sensors = ['del_blade_flap', 'del_blade_edge']
diff --git a/py_wake/tests/test_utils/test_model_utils.py b/py_wake/tests/test_utils/test_model_utils.py
index 541825763..79c34566c 100644
--- a/py_wake/tests/test_utils/test_model_utils.py
+++ b/py_wake/tests/test_utils/test_model_utils.py
@@ -11,7 +11,6 @@ from py_wake.deficit_models.gaussian import IEA37SimpleBastankhahGaussian
from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines
from py_wake.tests import npt
import pytest
-import re
from py_wake.ground_models.ground_models import GroundModel
diff --git a/py_wake/tests/test_wind_farm_models/test_simulation_result.py b/py_wake/tests/test_wind_farm_models/test_simulation_result.py
new file mode 100644
index 000000000..222801f08
--- /dev/null
+++ b/py_wake/tests/test_wind_farm_models/test_simulation_result.py
@@ -0,0 +1,28 @@
+from py_wake.deficit_models.noj import NOJ
+from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
+from py_wake.site._site import UniformSite
+from py_wake.tests import npt
+from py_wake.tests.test_files import tfp
+from py_wake.wind_farm_models.wind_farm_model import SimulationResult
+
+
+def test_save_load():
+ site = UniformSite([1], ti=0)
+ windTurbines = IEA37_WindTurbines()
+ wfm = NOJ(site, windTurbines)
+
+ sim_res1 = wfm([0], [0], wd=270)
+
+ sim_res1.save(tfp + "tmp.nc")
+
+ sim_res2 = SimulationResult.load(tfp + 'tmp.nc', wfm)
+ for sim_res in [sim_res1, sim_res2]:
+
+ npt.assert_almost_equal(sim_res.aep().sum(), 3.35 * 24 * 365 / 1000)
+ npt.assert_almost_equal(sim_res.aep(normalize_probabilities=True).sum(), 3.35 * 24 * 365 / 1000)
+
+ npt.assert_equal(sim_res.aep().data.sum(), wfm.aep([0], [0], wd=270))
+ npt.assert_almost_equal(sim_res.aep(normalize_probabilities=True).sum(),
+ wfm.aep([0], [0], wd=270, normalize_probabilities=True))
+ npt.assert_almost_equal(sim_res.aep(with_wake_loss=False).sum(),
+ wfm.aep([0], [0], wd=270, with_wake_loss=False))
diff --git a/py_wake/tests/test_wind_farm_models/test_wind_farm_model.py b/py_wake/tests/test_wind_farm_models/test_wind_farm_model.py
new file mode 100644
index 000000000..6a4c5ec20
--- /dev/null
+++ b/py_wake/tests/test_wind_farm_models/test_wind_farm_model.py
@@ -0,0 +1,12 @@
+from py_wake.wind_farm_models.engineering_models import PropagateDownwind
+
+from py_wake.examples.data.hornsrev1 import Hornsrev1Site, V80
+from py_wake.deficit_models.noj import NOJ
+import pytest
+
+
+def test_yaw_wrong_name():
+ wfm = NOJ(Hornsrev1Site(), V80())
+ for k in ['yaw_ilk', 'Yaw']:
+ with pytest.raises(ValueError, match=r'Custom \*yaw\*\-keyword arguments not allowed'):
+ wfm([0], [0], **{k: [[[30]]]})
diff --git a/py_wake/tests/test_windturbines/test_power_ct_curves.py b/py_wake/tests/test_windturbines/test_power_ct_curves.py
index 045454b5a..9b2f7f9e0 100644
--- a/py_wake/tests/test_windturbines/test_power_ct_curves.py
+++ b/py_wake/tests/test_windturbines/test_power_ct_curves.py
@@ -8,6 +8,7 @@ from py_wake.tests import npt
from py_wake.wind_turbines.power_ct_functions import CubePowerSimpleCt, PowerCtNDTabular, DensityScale, \
PowerCtTabular, PowerCtFunction, PowerCtFunctionList, PowerCtXr
from py_wake.wind_turbines.wind_turbine_functions import WindTurbineFunction
+from py_wake.utils.model_utils import fix_shape
@pytest.mark.parametrize('method,unit,p_scale,p_ref,ct_ref', [
@@ -202,7 +203,7 @@ def get_continuous_curve(key, optional):
def _power_ct(ws, run_only, **kwargs):
try:
- v = tab_powerct_curve.fix_shape(kwargs.pop(key), ws, True)
+ v = fix_shape(kwargs.pop(key), ws, True)
except KeyError:
if optional:
v = 1
@@ -290,9 +291,10 @@ def test_SimpleYawModel():
_, ct_c = hornsrev1.ct_curve.T
curve = PowerCtTabular(ws=u_p, power=p_c, power_unit='w', ct=ct_c, method='linear')
u = np.arange(4, 25, 1.1)
- theta = np.deg2rad(30)
+ yaw = 30
+ theta = np.deg2rad(yaw)
co = np.cos(theta)
- p, ct = curve(u, yaw=theta)
+ p, ct = curve(u, yaw=yaw)
npt.assert_array_almost_equal(p, np.interp(u * co, u_p, p_c))
npt.assert_array_almost_equal(ct, np.interp(u * co, u_p, ct_c) * co**2)
@@ -302,9 +304,10 @@ def test_DensityScaleAndSimpleYawModel():
_, ct_c = hornsrev1.ct_curve.T
curve = PowerCtTabular(ws=u_p, power=p_c, power_unit='w', ct=ct_c, method='linear')
u = np.arange(4, 25, 1.1)
- theta = np.deg2rad(30)
+ yaw = 30
+ theta = np.deg2rad(yaw)
co = np.cos(theta)
- p, ct = curve(u, yaw=theta, Air_density=1.3)
+ p, ct = curve(u, yaw=yaw, Air_density=1.3)
npt.assert_array_almost_equal(p, np.interp(u * co, u_p, p_c) * 1.3 / 1.225)
npt.assert_array_almost_equal(ct, np.interp(u * co, u_p, ct_c) * co**2 * 1.3 / 1.225)
diff --git a/py_wake/tests/test_windturbines/test_power_ct_wind_turbines.py b/py_wake/tests/test_windturbines/test_power_ct_wind_turbines.py
index b0012b1c0..1f5373faf 100644
--- a/py_wake/tests/test_windturbines/test_power_ct_wind_turbines.py
+++ b/py_wake/tests/test_windturbines/test_power_ct_wind_turbines.py
@@ -341,7 +341,7 @@ def test_DensityScaleAndSimpleYawModel():
co = np.cos(theta)
- sim_res = wfm([0], [0], wd=0, ws=u, yaw_ilk=yaw_ilk, Air_density=1.3)
+ sim_res = wfm([0], [0], wd=0, ws=u, yaw=yaw_ilk, Air_density=1.3)
p = sim_res.Power.values.squeeze()
ct = sim_res.CT.values.squeeze()
diff --git a/py_wake/tests/test_windturbines/test_windturbines.py b/py_wake/tests/test_windturbines/test_windturbines.py
index 72a147fbd..6ffcaa93c 100644
--- a/py_wake/tests/test_windturbines/test_windturbines.py
+++ b/py_wake/tests/test_windturbines/test_windturbines.py
@@ -188,22 +188,22 @@ def test_get_defaults():
def test_yaw():
v80 = V80()
- yaw = np.deg2rad(np.arange(-30, 31))
+ yaw = np.arange(-30, 31)
ws = np.zeros_like(yaw) + 8
P0 = v80.power(ws[0])
if 0:
plt.plot(yaw, v80.power(ws, yaw=yaw) / P0)
- plt.plot(yaw, np.cos(yaw)**3)
+ plt.plot(yaw, np.cos(np.deg2rad(yaw))**3)
plt.grid()
plt.figure()
plt.plot(yaw, v80.ct(ws, yaw=yaw))
- plt.plot(yaw, v80.ct(ws) * np.cos(yaw)**2)
+ plt.plot(yaw, v80.ct(ws) * np.cos(np.deg2rad(yaw))**2)
plt.grid()
plt.show()
# Power in cube region
- npt.assert_array_almost_equal(v80.power(ws, yaw=yaw) / P0, np.cos(yaw)**3, 2)
+ npt.assert_array_almost_equal(v80.power(ws, yaw=yaw) / P0, np.cos(np.deg2rad(yaw))**3, 2)
# ct in constant region
- npt.assert_array_almost_equal(v80.ct(ws, yaw=yaw), v80.ct(ws) * np.cos(yaw)**2, 3)
+ npt.assert_array_almost_equal(v80.ct(ws, yaw=yaw), v80.ct(ws) * np.cos(np.deg2rad(yaw))**2, 3)
def test_plot_yz():
diff --git a/py_wake/utils/model_utils.py b/py_wake/utils/model_utils.py
index c1ea46c54..a2f593c93 100644
--- a/py_wake/utils/model_utils.py
+++ b/py_wake/utils/model_utils.py
@@ -113,21 +113,20 @@ def get_signature(cls, kwargs={}, indent_level=0):
return "%s(%s)" % (cls.__name__, arg_str)
-def get_model_input(wfm, x, y, ws=10, wd=270, yaw_ilk=[[[0]]]):
+def get_model_input(wfm, x, y, ws=10, wd=270, yaw=[[[0]]]):
ws, wd = [np.atleast_1d(v) for v in [ws, wd]]
x, y = map(np.asarray, [x, y])
wfm.site.distance.setup(src_x_i=[0], src_y_i=[0], src_h_i=[0],
dst_xyh_j=(x, y, x * 0))
dw_ijl, hcw_ijl, dh_ijl = wfm.site.distance(wd_il=wd[na])
- sim_res = wfm([0], [0], ws=ws, wd=wd, yaw_ilk=yaw_ilk)
+ sim_res = wfm([0], [0], ws=ws, wd=wd, yaw=yaw)
args = {'dw_ijl': dw_ijl, 'hcw_ijl': hcw_ijl, 'dh_ijl': dh_ijl,
'D_src_il': np.atleast_1d(wfm.windTurbines.diameter())[na]}
- args.update({k: sim_res[n].ilk() for k, n in [('yaw_ilk', 'Yaw'),
+ args.update({k: sim_res[n].ilk() for k, n in [('yaw_ilk', 'yaw'),
('WS_ilk', 'WS'),
('WS_eff_ilk', 'WS_eff'),
('ct_ilk', 'CT')]})
- args['yaw_ilk'] = np.deg2rad(args['yaw_ilk'])
return args
@@ -147,6 +146,20 @@ def check_model(model, cls, arg_name=None, accept_None=True):
raise ValueError(s + f', but is a {model.__class__.__name__} instance')
+def fix_shape(arr, shape_or_arr_to_match, allow_number=False, allow_None=False):
+ if allow_None and arr is None:
+ return arr
+ if allow_number and isinstance(arr, (int, float)):
+ return arr
+
+ arr = np.asarray(arr)
+ if isinstance(shape_or_arr_to_match, tuple):
+ shape = shape_or_arr_to_match
+ else:
+ shape = np.asarray(shape_or_arr_to_match).shape
+ return np.broadcast_to(arr.reshape(arr.shape + (1,) * (len(shape) - len(arr.shape))), shape)
+
+
def main():
if __name__ == '__main__':
list_models()
diff --git a/py_wake/utils/xarray_utils.py b/py_wake/utils/xarray_utils.py
index 6b8321175..03aa671a1 100644
--- a/py_wake/utils/xarray_utils.py
+++ b/py_wake/utils/xarray_utils.py
@@ -37,7 +37,32 @@ class add_ilk():
def __call__(self, name, value):
dims = self.dataset.dims
if 'time' in dims:
- allowed_dims = ['i', 'wt'], ['time']
+ allowed_dims = ['i', 'wt'], ['time'], ['ws']
+ else:
+ allowed_dims = ['i', 'wt'], ['wd'], ['ws']
+
+ d = []
+ i = 0
+
+ for ad in allowed_dims:
+ for k in ad:
+ if i < len(np.shape(value)) and np.shape(value)[i] == dims.get(k, None):
+ d.append(k)
+ i += 1
+ break
+ while len(np.shape(value)) > len(d) and np.shape(value)[-1] == 1:
+ value = value[..., 0]
+ self.dataset[name] = (d, value)
+
+
+class add_ijlk():
+ def __init__(self, dataset):
+ self.dataset = dataset
+
+ def __call__(self, name, value):
+ dims = self.dataset.dims
+ if 'time' in dims:
+ allowed_dims = ['i', 'wt'], ['i', 'wt'], ['time'], ['ws']
else:
allowed_dims = ['i', 'wt'], ['i', 'wt'], ['wd'], ['ws']
@@ -50,6 +75,8 @@ class add_ilk():
d.append(k)
i += 1
break
+# while len(value.shape) > len(d) and value.shape[-1] == 1:
+# value = value[..., 0]
self.dataset[name] = (d, value)
@@ -94,6 +121,7 @@ class plot_xy_map():
if not hasattr(xr.DataArray(None), 'ilk'):
xr.register_dataarray_accessor("ilk")(ilk)
xr.register_dataset_accessor("add_ilk")(add_ilk)
+ xr.register_dataset_accessor("add_ijlk")(add_ijlk)
xr.register_dataarray_accessor("interp_all")(interp_all)
xr.register_dataarray_accessor("sel_interp_all")(sel_interp_all)
with warnings.catch_warnings():
diff --git a/py_wake/wind_farm_models/engineering_models.py b/py_wake/wind_farm_models/engineering_models.py
index f14239d62..82278dc99 100644
--- a/py_wake/wind_farm_models/engineering_models.py
+++ b/py_wake/wind_farm_models/engineering_models.py
@@ -168,8 +168,6 @@ class EngineeringWindFarmModel(WindFarmModel):
WS_eff_ilk = lw.WS.ilk((I, L, K)).copy()
TI_eff_ilk = lw.TI.ilk((I, L, K)).copy()
- if yaw_ilk is not None:
- yaw_ilk = np.zeros((I, L, K)) + np.deg2rad(yaw_ilk)
# add eps to avoid non-differentiable 0
# eps = 2 * np.finfo(float).eps ** 2 if 'autograd' in np.__name__ else 0
@@ -281,7 +279,7 @@ class EngineeringWindFarmModel(WindFarmModel):
'WS_eff_ilk': get_ilk('WS_eff'),
'TI_ilk': get_ilk('TI'),
'TI_eff_ilk': get_ilk('TI_eff'),
- 'yaw_ilk': lambda: np.deg2rad(get_ilk('Yaw')()),
+ 'yaw_ilk': get_ilk('yaw'),
'D_src_il': lambda: wt_d_i[:, na],
'D_dst_ijl': lambda: np.zeros_like(dh_ijl),
'h_il': lambda: wt_h_i.data[:, na],
diff --git a/py_wake/wind_farm_models/wind_farm_model.py b/py_wake/wind_farm_models/wind_farm_model.py
index 01f0ac5cc..6c95192f1 100644
--- a/py_wake/wind_farm_models/wind_farm_model.py
+++ b/py_wake/wind_farm_models/wind_farm_model.py
@@ -1,12 +1,12 @@
from abc import abstractmethod, ABC
-from py_wake.site._site import Site, UniformSite, UniformWeibullSite
+from py_wake.site._site import Site, UniformSite, UniformWeibullSite, LocalWind
from py_wake.wind_turbines import WindTurbines
import numpy as np
from py_wake.flow_map import FlowMap, HorizontalGrid, FlowBox, YZGrid, Grid, Points
import xarray as xr
from py_wake.utils import xarray_utils, weibull # register ilk function @UnusedImport
from numpy import newaxis as na
-from py_wake.utils.model_utils import check_model
+from py_wake.utils.model_utils import check_model, fix_shape
class WindFarmModel(ABC):
@@ -19,7 +19,7 @@ class WindFarmModel(ABC):
self.site = site
self.windTurbines = windTurbines
- def __call__(self, x, y, h=None, type=0, wd=None, ws=None, yaw_ilk=None, time=False, verbose=False, **kwargs):
+ def __call__(self, x, y, h=None, type=0, wd=None, ws=None, yaw=None, time=False, verbose=False, **kwargs):
"""Run the wind farm simulation
Parameters
@@ -47,11 +47,16 @@ class WindFarmModel(ABC):
assert len(x) == len(y)
self.verbose = verbose
h, _ = self.windTurbines.get_defaults(len(x), type, h)
+ I, L, K, = len(x), len(np.atleast_1d(wd)), (1, len(np.atleast_1d(ws)))[time is False]
+ if len([k for k in kwargs if 'yaw' in k.lower() and k != 'yaw']):
+ raise ValueError(
+ 'Custom *yaw*-keyword arguments not allowed to avoid confusion with the default "yaw" keyword')
+ yaw_ilk = fix_shape(yaw, (I, L, K), allow_None=True)
if len(x) == 0:
lw = UniformSite([1], 0.1).local_wind(x_i=[], y_i=[], h_i=[], wd=wd, ws=ws)
z = xr.DataArray(np.zeros((0, len(lw.wd), len(lw.ws))), coords=[('wt', []), ('wd', lw.wd), ('ws', lw.ws)])
- return SimulationResult(self, lw, [], yaw_ilk, z, z, z, z, kwargs)
+ return SimulationResult(self, lw, [], yaw, z, z, z, z, kwargs)
res = self.calc_wt_interaction(x_i=np.asarray(x), y_i=np.asarray(y), h_i=h, type_i=type, yaw_ilk=yaw_ilk,
wd=wd, ws=ws, time=time, **kwargs)
WS_eff_ilk, TI_eff_ilk, power_ilk, ct_ilk, localWind, wt_inputs = res
@@ -169,14 +174,17 @@ class SimulationResult(xr.Dataset):
for n in localWind:
self[n] = localWind[n]
self.attrs.update(localWind.attrs)
- for n in set(wt_inputs) - {'type', 'TI_eff'}:
- self.add_ilk(n, wt_inputs[n])
+ for n in set(wt_inputs) - {'type', 'TI_eff', 'yaw'}:
+ if '_ijl' in n:
+ self.add_ijlk(n, wt_inputs[n])
+ else:
+ self.add_ilk(n, wt_inputs[n])
if yaw_ilk is None:
- self['Yaw'] = self.Power * 0
+ self['yaw'] = self.Power * 0
else:
- self['Yaw'] = xr.DataArray(yaw_ilk, dims=['wt', 'wd', 'ws'])
- self['Yaw'].attrs['Description'] = 'Yaw misalignment [deg]'
+ self.add_ilk('yaw', yaw_ilk)
+ self['yaw'].attrs['Description'] = 'Yaw misalignment [deg]'
# for backward compatibility
for k in ['WD', 'WS', 'TI', 'P', 'WS_eff', 'TI_eff']:
@@ -261,7 +269,7 @@ class SimulationResult(xr.Dataset):
if method == 'OneWT_WDAvg': # average over wd
p_wd_ilk = P_ilk.sum((0, 2))[na, :, na]
ws_ik = (WS_eff_ilk * p_wd_ilk).sum(1)
- kwargs_ik = {k: (wt.loadFunction.fix_shape(v, WS_eff_ilk) * p_wd_ilk).sum(1) for k, v in kwargs.items()
+ kwargs_ik = {k: (fix_shape(v, WS_eff_ilk) * p_wd_ilk).sum(1) for k, v in kwargs.items()
if k != 'TI_eff' and v is not None}
kwargs_ik.update({k: v for k, v in kwargs.items() if v is None})
@@ -295,14 +303,12 @@ class SimulationResult(xr.Dataset):
I, L, K = WS_eff_ilk.shape
ws_iilk = np.broadcast_to(WS_eff_ilk[na], (I, I, L, K))
- def fix_shape(k, v):
- # if hasattr(v, 'shape') and v.shape == (I, I, L, K):
- # return v
+ def _fix_shape(k, v):
if k[-3:] == 'ijl':
- return wt.loadFunction.fix_shape(v, ws_iilk)
+ return fix_shape(v, ws_iilk)
else:
- return np.broadcast_to(wt.loadFunction.fix_shape(v, WS_eff_ilk)[na], (I, I, L, K))
- kwargs_iilk = {k: fix_shape(k, v)
+ return np.broadcast_to(fix_shape(v, WS_eff_ilk)[na], (I, I, L, K))
+ kwargs_iilk = {k: _fix_shape(k, v)
for k, v in kwargs.items()
if k in wt.loadFunction.required_inputs + wt.loadFunction.optional_inputs}
@@ -317,15 +323,20 @@ class SimulationResult(xr.Dataset):
ds = xr.DataArray(
loads_silk,
- dims=['sensor', 'wt', 'wd', 'ws'],
+ dims=['sensor', 'wt', ('wd', 'time')['time' in self.dims], 'ws'],
coords={'sensor': wt.loadFunction.output_keys,
'm': ('sensor', wt.loadFunction.wohler_exponents, {'description': 'Wohler exponents'}),
'wt': self.wt, 'wd': self.wd, 'ws': self.ws},
attrs={'description': '1Hz Damage Equivalent Load'}).to_dataset(name='DEL')
- ds['P'] = self.P
- t_flowcase = ds.P * lifetime_years * 365 * 24 * 3600
f = ds.DEL.mean() # factor used to reduce numerical errors in power
- ds['LDEL'] = ((t_flowcase * (ds.DEL / f)**ds.m).sum(('wd', 'ws')) / n_eq_lifetime)**(1 / ds.m) * f
+ if 'time' in self.dims:
+ assert 'duration' in self, "Simulation must contain a dataarray 'duration' with length of time steps in seconds"
+ t_flowcase = self.duration
+ ds['LDEL'] = ((t_flowcase * (ds.DEL / f)**ds.m).sum(('time', 'ws')) / n_eq_lifetime)**(1 / ds.m) * f
+ else:
+ ds['P'] = self.P
+ t_flowcase = ds.P * 3600 * 24 * 365 * lifetime_years
+ ds['LDEL'] = ((t_flowcase * (ds.DEL / f)**ds.m).sum(('wd', 'ws')) / n_eq_lifetime)**(1 / ds.m) * f
ds.LDEL.attrs['description'] = "Lifetime (%d years) equivalent loads, n_eq_L=%d" % (
lifetime_years, n_eq_lifetime)
@@ -393,6 +404,20 @@ class SimulationResult(xr.Dataset):
assert np.all(np.isin(ws, self.ws)), "All ws=%s not in simulation result (ws=%s)" % (ws, self.ws)
return np.atleast_1d(wd), np.atleast_1d(ws)
+ def save(self, filename):
+ self.to_netcdf(filename)
+
+ @staticmethod
+ def load(filename, wfm):
+ ds = xr.load_dataset(filename)
+ lw = LocalWind(ds.x, ds.y, ds.h, ds.wd, ds.ws, time=False, wd_bin_size=ds.attrs['wd_bin_size'],
+ WD=ds.WD, WS=ds.WS, TI=ds.TI, P=ds.P)
+ sim_res = SimulationResult(wfm, lw, type_i=ds.type.values, yaw_ilk=ds.yaw,
+ WS_eff_ilk=ds.WS_eff.ilk(), TI_eff_ilk=ds.TI_eff.ilk(), power_ilk=ds.Power, ct_ilk=ds.CT,
+ wt_inputs={})
+
+ return sim_res
+
def main():
if __name__ == '__main__':
diff --git a/py_wake/wind_turbines/_wind_turbines.py b/py_wake/wind_turbines/_wind_turbines.py
index 13d1122ee..35fdb9d70 100644
--- a/py_wake/wind_turbines/_wind_turbines.py
+++ b/py_wake/wind_turbines/_wind_turbines.py
@@ -160,23 +160,23 @@ Use WindTurbines(names, diameters, hub_heights, power_ct_funcs) instead""", Depr
yaw = np.zeros_like(x) + yaw
x, y, D = [np.asarray(v) / normalize_with for v in [x, y, self.diameter(types)]]
-
- for i, (x_, y_, d, t, yaw_) in enumerate(zip(x, y, D, types, yaw)):
+ R = D / 2
+ for i, (x_, y_, r, t, yaw_) in enumerate(zip(x, y, R, types, yaw)):
if wd is None or len(np.atleast_1d(wd)) > 1:
- circle = Circle((x_, y_), d / 2, ec=colors[t], fc="None")
+ circle = Circle((x_, y_), r, ec=colors[t], fc="None")
ax.add_artist(circle)
ax.plot(x_, y_, 'None', )
else:
for wd_ in np.atleast_1d(wd):
c, s = np.cos(np.deg2rad(90 + wd_ - yaw_)), np.sin(np.deg2rad(90 + wd_ - yaw_))
- ax.plot([x_ - s * d / 2, x_ + s * d / 2], [y_ - c * d / 2, y_ + c * d / 2], lw=1, color=colors[t])
+ ax.plot([x_ - s * r, x_ + s * r], [y_ - c * r, y_ + c * r], lw=1, color=colors[t])
for t, m, c in zip(np.unique(types), markers, colors):
# ax.plot(np.asarray(x)[types == t], np.asarray(y)[types == t], '%sk' % m, label=self._names[int(t)])
ax.plot([], [], '2', color=colors[t], label=self._names[int(t)])
- for i, (x_, y_, d) in enumerate(zip(x, y, D)):
- ax.annotate(i, (x_ + d / 2, y_ + d / 2), fontsize=7)
+ for i, (x_, y_, r) in enumerate(zip(x, y, R)):
+ ax.annotate(i, (x_ + r, y_ + r), fontsize=7)
ax.legend(loc=1)
ax.axis('equal')
diff --git a/py_wake/wind_turbines/power_ct_functions.py b/py_wake/wind_turbines/power_ct_functions.py
index 49d6f5f84..fcca9caa6 100644
--- a/py_wake/wind_turbines/power_ct_functions.py
+++ b/py_wake/wind_turbines/power_ct_functions.py
@@ -9,7 +9,7 @@ from autograd.numpy.numpy_boxes import ArrayBox
from py_wake.wind_turbines.wind_turbine_functions import WindTurbineFunction, FunctionSurrogates,\
WindTurbineFunctionList
from py_wake.utils.check_input import check_input
-from py_wake.utils.model_utils import check_model
+from py_wake.utils.model_utils import check_model, fix_shape
"""
@@ -102,7 +102,7 @@ class SimpleYawModel(AdditionalModel):
def __call__(self, f, ws, yaw=None, **kwargs):
if yaw is not None:
- co = np.cos(self.fix_shape(yaw, ws, True))
+ co = np.cos(np.deg2rad(fix_shape(yaw, ws, True)))
power_ct_arr = f(ws * co, **kwargs) # calculate for reduced ws (ws projection on rotor)
if kwargs['run_only'] == 1: # ct
# multiply ct by cos(yaw)**2 to compensate for reduced thrust
@@ -123,7 +123,7 @@ class DensityScale(AdditionalModel):
def __call__(self, f, ws, Air_density=None, **kwargs):
power_ct_arr = np.asarray(f(ws, **kwargs))
if Air_density is not None:
- power_ct_arr *= self.fix_shape(Air_density, ws, True) / self.air_density_ref
+ power_ct_arr *= fix_shape(Air_density, ws, True) / self.air_density_ref
return power_ct_arr
@@ -367,9 +367,9 @@ class PowerCtNDTabular(PowerCtFunction):
default_value_dict.keys(), additional_models)
def _power_ct(self, ws, run_only, **kwargs):
- kwargs = {**self.default_value_dict, 'ws': ws, **kwargs}
+ kwargs = {**self.default_value_dict, 'ws': ws, **{k: v for k, v in kwargs.items() if v is not None}}
- args = np.moveaxis([self.fix_shape(kwargs[k], ws)
+ args = np.moveaxis([fix_shape(kwargs[k], ws)
for k in self.input_keys], 0, -1)
try:
return self.interp[run_only](args)
diff --git a/py_wake/wind_turbines/wind_turbine_functions.py b/py_wake/wind_turbines/wind_turbine_functions.py
index fc7feee15..dda26a31b 100644
--- a/py_wake/wind_turbines/wind_turbine_functions.py
+++ b/py_wake/wind_turbines/wind_turbine_functions.py
@@ -2,6 +2,7 @@ import numpy as np
import inspect
from abc import ABC, abstractmethod
import types
+from py_wake.utils.model_utils import fix_shape
"""
sequenceDiagram
@@ -62,13 +63,6 @@ class WindTurbineFunction():
lst = [i for sub_lst in optional_inputs for i in ([sub_lst], sub_lst)[isinstance(sub_lst, (list, set))]]
self._optional_inputs |= set(lst)
- def fix_shape(self, arr, arr_to_match, allow_number=False):
- if allow_number and isinstance(arr, (int, float)):
- return arr
- arr = np.asarray(arr)
- shape = np.asarray(arr_to_match).shape
- return np.broadcast_to(arr.reshape(arr.shape + (1,) * (len(shape) - len(arr.shape))), shape)
-
class WindTurbineFunctionList(WindTurbineFunction):
"""Wraps a list of PowerCtFunction objects by adding a new discrete input argument,
@@ -163,7 +157,7 @@ class FunctionSurrogates(WindTurbineFunction, ABC):
def __call__(self, ws, run_only=slice(None), **kwargs):
x = self.get_input(ws=ws, **kwargs)
- x = np.array([self.fix_shape(v, ws).ravel() for v in x]).T
+ x = np.array([fix_shape(v, ws).ravel() for v in x]).T
if isinstance(run_only, int):
return self.function_surrogate_lst[run_only].predict_output(x).reshape(ws.shape)
else:
--
GitLab