{ "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+00/'\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": [ "119 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": [ "1.14 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+00/'\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 0x229f1ba8250>" ] }, "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 0x229f1f4c220>" ] }, "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 0x229f2096460>" ] }, "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 0x229f24526d0>" ] }, "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 0x229f2583c10>" ] }, "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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\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 0x229f25242b0>" ] }, "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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XD3ANRFOUxYsXEx4eTmxsbJHTFbbW0LlzZ9auXcv69eu57bbbGDBgAKGhoQQHB9O/f38A4uLiCAkJoVKlSsTFxbF9+3bA1bJ7165dNG3alCNHjrBt2zbuv/9+rrrqKvr161dkFn82eeVuHvk6mc5NavLRsA6EB/vXubpeS6uq60XkJeBH4DiQDBTc2LgCaKyqx0XkSmAycNanp6qOBkaDq9eQtzKXhqvi6jFnYwqv/riJoMAA7undzOlIpWPAvx152NP7CFJTUxk4cCDvvPMOt912m0fzajF9tPI3qcvv/vvv5+GHH2bQoEHMnj2bZ599FnBtmtqyZQspKSlMnjyZv//974Br087ChQvzPvDP9Rivv/46F110EcnJyeTm5hIaGlpkTlWlTZs2LFxY/IBABY0bN67YzULZ2dlMnDgxr4NrQa1btyYiIoI1a9bQoUMHKlWqlLepKCAgIK/VdkBAQN5+hHnz5uV1Ta1RowbJycn88MMPvPPOO3z99dd8/PHHJf5bfN30NXt5+Oskvy0C4OWdxar6kaq2U9WewGFgc4H7j6nqcff1aUAlEfHrDmdBgQG8MjSBQQn1eWn6Bsb88qvTkcqFatWq8eabbzJy5EjCw8OpUaMG8+bNA+Dzzz/PWzvI3+q5VatWbN++Pa+ddP7pipKamkqDBq6W5J9++mne7SLC4MGDefjhh2ndujU1a7pGjOrXrx9vv/123nTn6vefmppKvXr1CAgI4PPPP8/bSd29e3e++eYbcnNz2b9/P7NnzwagZcuWpKSk5BWCrKws1q49a4X5LLm5uYwfP54bb7yxyOlmzpxJq1atiIqKyrvt119/zftQ37FjBxs3biQ6OrrYxzxt+vTpDBgwAICDBw+Sm5vLtddemzeaW3kUH1WdIe2i/LYIgPePGqrj/tkIGAJ8WeD+uuL+iiEindx5DnkzU1kIDBBevT6BfjEX8ey36/hq6W9ORyoX2rZtS0JCAuPGjePTTz/lscceIz4+nqSkpLxhJIcNG8aIESNITExEVfnkk08YOnQocXFxBAQEFLtJBVw7eYcOHUqPHj3O6rx6ww038MUXX5yxWenNN99k2bJlxMfHExMTw6hRowpd7r333sunn35Kly5d2LRpU97awrXXXktUVBSxsbEMHz6czp07U61aNYKDg5kwYQKPP/44CQkJJCYm5u1gHjVq1DkfZ+7cuURFReWNdnbanXfeecboboWtNcyfPz/vsQYPHsy7775bou6zs2fPziu2u3fvpnfv3iQmJjJs2DBefPFFj5fjD9bvPUZurlK/ehgjhyb4bREAvLez2L26Ow9Yh2uzUB/3bSOAEe7r9wFr3fcvAroVt0xf31mc38msbL31o8Ua/cR3OnnlLqfjlNgZO4uNV6Wlpamq6sGDB7Vp06a6d+9ehxOV3M6dO7V///4lmsdfdxbvOHhCW/xtmr7+40ano3gMh3YWo6pnDZ2kqqPyXX8beLvgNOVFSFAg79/SnmGfLOGRr5OpER5Mzxa1nY5lfNDAgQM5evQomZmZPPXUU9StW9fpSCUWFRXF999/73SMMtGoZjjP/K4N/WP973UqjB+vy/iH0EqBfHBrB65/fxHPTF3Lj3/uSVCgndBtznR6v4Dxbb8ePEFGZg4x9avy+86+fQRjSVghKANVQisx5vaOZGbnWhEwxk8dOn6K2z5eQoDAzId7lav/5fLzl/i4i6qG0jAynNxc5b3ZWzl8ouL2YTHG35zMyuHuz5ez/9hJXrshsVwVAbBCUOa2HTzOGzM3MXHFLqejGGM8kJurPDo+meU7jvDa9Ym0a1TD6UilzjYNlbGL61Rh+kM9ia7pJz1IjKngXvtxE9+t2ssTA1pxVXw9p+N4ha0ROKBJrQhEhI370hi3xM4xKIo/t6GePHnyGa0nSsNvv/1Gv379aN26NTExMXmtHfLbsWMHffr0IT4+nt69e7Nr1/+vfX766ac0b96c5s2bn3GyXEn0798/r/lfeffN8l28PWsLN3VqyPCeTYufwU9ZIXDQB/O28eSk1fy8Yb/TUUpFTm4Oc3bOYVTyKObsnENO7oW3d/bnNtTnUwiKa/l866238thjj7F+/XqWLFlCnTp1zprm0Ucf5dZbb2XVqlU8/fTTPPnkkwAcPnyY5557jsWLF7NkyRKee+45jhw5UqJ8GRkZHD58OO/M6/IseedRnpy0mq5Na/L81bFndGItb6wQOOgfV8fSpn5VHvgyiU3705yOc0FycnMY/uNw/jL3L7yb9C5/mfsXhv84vFSKwWll1YZ6//79DB48mISEBBISEvLO5v3iiy/o1KkTiYmJDB8+PK+AVK5cmb/97W8kJCTQpUsX9u/fz4IFC5g6dSqPPfYYiYmJbN26la1bt9K/f3/at29Pjx492LBhA+A6G/rhhx/m0ksv5fHHHz/n379u3Tqys7PzmtBVrlyZ8PCzNzGuW7eOPn36AHDppZcyZcoUAH744Qf69u1LZGQkNWrUoG/fvkyfPj3v+fjrX/9K165d6dChAytWrOCKK66gWbNmZ5zBPHv2bHr37g3AE088QUxMDPHx8Tz66KMleCV93/FT2Yz4Yjm1K4fwzs3tqFTOdg4XVL7/Oh8XFuw6xyAsOJARny8n7WSW05HO2/zd81l9cDXp2ekoSnp2OqsOrmL+7vmlsvycnBx++uknBg0aBLi+Gb/00kusWrWKuLg4nnvuOa677jo6dOjA2LFjSUpKQkQYNmwYX331FatXryY7O5v33nsvb5mhoaHMnz//rJ48DzzwAL169SI5OZkVK1bQpk0b1q9fz1dffcUvv/yS1z107NixAJw4cYIuXbqQnJxMz549+eCDD+jWrRuDBg3ilVdeISkpiWbNmnH33Xfz1ltvsXz5ckaOHMm9996b95ibNm1i5syZvPrqq0ydOjWvZUZ+mzZtonr16gwZMoS2bdvy2GOPFbo2k5CQwDfffAPApEmTSEtL49ChQ+zevZuGDRvmTRcVFXXGJp6GDRuycOFCevTowbBhw5gwYQKLFi06I8vpsQYOHz7MpEmTWLt2LatWrcprwFdeVA4J4s99WzD61vY+O85wabJC4LB61cJ45/ft2HE4ncfGryq2Y6avWn94PRnZGWfcdjL7JBsOb7ig5Z5uQ12zZk0OHz58zjbUc+fOPWvewtpQ55/uXG2of/75Z+655x7AtY+iWrVq/PTTTyxfvpyOHTuSmJjITz/9xLZt2wAIDg5m4MCBgGuIxsK22x8/fpwFCxYwdOjQvDWK/IPMDB06lMDAQMDVuvr5588eoyk7O5t58+YxcuRIli5dyrZt2xgzZsxZ040cOZI5c+bQtm1b5syZQ4MGDQgKCir0vZV/c8fpIhsXF0fnzp2pUqUKtWvXJjQ0NG/fzC+//EL37t2pWrUqoaGh3HnnnUycOLHQNRN/tTfV9T6+vkND2tSv5nCasmGFwAd0ahLJkwNaMX3tPkbP3eZ0nPPSOrI1YUFntmEODQqlVWSrC1ru6X0EO3bsIDMzs9h9BPkVV1TP1Yb6XMu67bbb8oZ33LhxY1576vztmQMDAwvdzp+bm0v16tXz5k9KSmL9+vUlyhIVFUXbtm1p2rQpQUFBXHPNNYV29Kxfvz4TJ05k5cqVvPDCC4Cre2tUVBQ7d+7Mm27Xrl3Ur18/7/f8baVPXz/9e3Z2Ntu2baNhw4YEBwcTFBTEkiVLuPbaa5k8eXLeOAX+bkrSbi4dOZs1u1OdjlKmrBD4iD92b8KVcXV5afoGFm71vwas3Rt0J65WHGFBYQhCWFAY8bXi6d6ge6ksvyzbUPfp0ydvE1JOTg7Hjh2jT58+TJgwgQMHDgCuHa87duwocjn5s1StWpUmTZrk7Y9QVZKTk0v0HHTs2JEjR46QkpICuNZcYmJizprudPtngBdffJE77rgDgCuuuIIZM2Zw5MgRjhw5wowZM7jiiis8fvzTm4XAtYaTmprKlVdeyRtvvHHO1tv+pmuzmtzWLZpWdas4HaVMWSHwESLCy9cl0KRWBPd/uYLUdP/aXxAYEMj7fd/nlZ6v8KfEP/FKz1d4v+/7BAYEltpjlFUb6v/85z/MmjWLuLg42rdvz9q1a4mJieGf//wn/fr1Iz4+nr59+xY7fvCNN97IK6+8Qtu2bdm6dStjx47lo48+IiEhgTZt2uTtxC3oXPsIAgMDGTlyJH369CEuLg5V5a677gLg6aefzhs3ePbs2bRs2ZIWLVqwf/9+/va3vwEQGRnJU089lTe28tNPP01kZGSxz8dp06dPzysEaWlpDBw4kPj4eHr16uX34xGfzMohJ1epUyWUJwe0LndnDhdH/G2bdIcOHTR/T/XyZsuBNFbtSmVIu6jiJ/aypUuX0qRJkxL1ozfl06lTp7jkkkso7f+9pUuXsnbtWoYNG1aqyy0JVeWRr5PZn3aSz+7oTGBA+TxMVESWq2qHwu6rWGXPD1xcp0peEfC3tQJTfoWEhJR6EfAVXy/bycSVu+kYHVlui0BxrBD4qAVbDnLJSz+zbPthp6MYU25t3p/G01PW0v3iWtx/2VnDpVcYVgh8VFxUNa6Kq0cjh3sS+dumQ+M/nH5vncrO4YFxSVQOCeK1GxIq7NoAWCHwWVVCK/HSdfHUqRJKbq468k+TkZFBWlqa4/+wpvxRVQ4dOkRGRkbxE3vJyB82sn7vMV52/59VZNZ91MelZmQx/PNlDGkbxfUdGxY/Qyk6fXjk6bYMxpSm0NDQYg/B9Zb5mw/ywbxfuaVLY/q0vsiRDL7ECoGPqxIShCA89+1aujarScPIsttUlJOTw7Zt2+jZs2eZPaapWObMmVPmj3nkRCYPf53ExXUq89crW5f54/si2zTk4wIChJHXJxAgwiNfJ5OTa5tpjLkQYxZs50h6Jv+5MZGw4NI7z8WfWSHwAw2qh/HsoDYs2X6YD+f5ZwsKY3zFA32a8/XwrhWmj5AnrBD4iSHtGtC/TV1enbGJ9XuPOR3HGL+TknaKlLRTBAYIbcvhcJMXwgqBnxARXhgcS9WwSvz5qyQys3OdjmSMX3l6yhqufns+p7K9MxCRP7NC4EdqVg7hxSFxbNiXxnuztzodxxi/8ki/Fvz1qtaEBNl+gYKsEPiZvjEXMSihPm/P2syWA8edjmOMzzuZ5VoDuLhOFQbG1y9m6orJq4VARB4UkTUislZEHirkfhGRN0Vki4isEpF23sxTXjw7qA1PDmhNtMNnHRvj61SV4Z8v5/EJq5yO4tO8VghEJBa4C+gEJAADRaRgM48BQHP35W7gPUyxIiOCuaN7E4ICA8jKsX0FxpzL1OQ9zNmUQssKNr5ASXlzjaA1sEhV01U1G5gDDC4wzdXAZ+qyCKguIvW8mKlcWfLrYXq9PIutKbaJyJiCjqZn8vy360iIqsZt3aKdjuPTvFkI1gA9RaSmiIQDVwIFeyQ0AHbm+32X+7YziMjdIrJMRJadHp3JQHStcJrVqYy1AjLmbP+atp6jGVm8OCS+QjeU84TXWkyo6noReQn4ETgOJAMFB3Mt7NU562NNVUcDo8E1ME0pR/VbdaqE8vkfOzsdwxifs2DrQb5etosRvZoRU7+q03F8nld3FqvqR6raTlV7AoeBzQUm2cWZawlRwB5vZiqPDh0/xd8nr+bQcWsOZ8zJrBz+NmkNjSLDebBPxR1joCS8fdRQHffPRsAQ4MsCk0wFbnUfPdQFSFXVogeCNWc5fCKTcUt28uL3G5yOYozj3pm1hV8PnuCFwbHWS8hD59w0JCLF9TEQYK+qtihimm9EpCaQBfxJVY+IyAgAVR0FTMO172ALkA7cXpLwxqX5RVW4u2dT3p29levaR9GlaU2nIxnjiE37XSdbDm7bgB7Nazsdx28UtY9gq6q2LWpmEVlZ1P2q2qOQ20blu67An4oLaYp3/2XN+XbVHv4+eQ3THuhBcJCdK2gqnoY1wrmndzOG2VFCJVLUp8W1HszvyTSmDIQFB/L8oFi2HDjOB9ah1FRQYcGBPNKvJTUrhzgdxa+csxCo6jYAEYkQkQD39RYiMkhEKuWfxviGS1vV4cq4urz502Z+O5TudBxjysyRE5kMefcXlu844nQUv+TJ9oO5QKiINAB+wrUdf4w3Q5nz9/TANlQKDOCpKWtsrGFTYew7dpK0k9lUDrFBF8+HJ4VAVDUd11E/b6nqYCDGu7HM+apbLZRH+rVgzqYUvl+zz+k4xpSJ1vWq8sNDPa2VxHnyqBCISFfgZuB/7tus7PqwW7tGEx9VzbqTmnIvN1f5dMF2TpzKJsDOHj5vnnygPwQ8CUxS1bUi0hSY5dVU5oIEBggTRnSzI4dMuffNil08M3Ut1cIqcU3bs7rTGA8VdR7Bk8B0VZ2Dq2EckLeD+IEyyGYuwOkisGz7YepWCyWqhrWsNuVLakYWL03fQLtG1RmUYOMMXIiivjL+CjwoIitFZIyI3CAiNtCnH0lNz+LWj5fwziwbzcyUP2/M3MShE5k8f3WsbRa6QOdcI1DVccA4ABFpC/QHJopIIDAT19rCkjJJac5LtfBKfHRbRxIaVnM6ijGlasO+Y3y2cAe/79SI2Ab2/r5QHu30VdWVwErgRRGpCvQF7gSsEPi4rs1c7SZOZecQKEJQoO03MP5NVXlmylqqhAbxaL+WTscpF4otBO41gKuA6PzTq+rd3otlSlNK2imGjlrAH7s34Zau0U7HMeaCTFu9j8W/Huaf18RSIyLY6TjlgidfD78FhgE1gSruS2UvZjKlrFblYOpVC+PVHzdxND3T6TjGnLeTWTn8e/p6WtWtwk2dGjkdp9zwZNNQlKrGez2J8RoR4ZlBMVz5n3m89uMmnr861ulIxpyXWRsOsPNwBl/8sbONOlaKPFkj+F5E+nk9ifGqVnWrckuXxnyxaAcb96U5HceY8zIgrh7/e6A73ZvXcjpKueJJIVgETBKRDBE5JiJpHoxVYHzQn/u2oHJIEC9+v97pKMaU2JETrs2aberbUUKlzZNC8CrQFQhX1aqqWkVVbRBQP1Q9PJgH+jRn9sYU5m1OcTqOMR7bvD+Nrv/+ielrbABDb/CkEGwG1qi1siwXbunamIaRYbzwv/Xk5NpLavxD9fBgbujQkE5NbPQ9b/CkEOwFZovIkyLy8OmLt4MZ7wgJCuTx/q3YsC+Nb1bscjqOMR6pXSWE566OJdIOF/UKTwrBr7jGIQjm/w8ftV6vfuyquHoMSqhPrcr2T2V8W3ZOLo+OT2b1rlSno5RrxR4+qqrPlUUQU3ZEhDdvKnI4amN8wtfLdjFh+S4ua1WHuCjbSewt51wjEJFni5vZk2mM78rIzOGdWVs4kHbS6SjGnOX4qWxe+3EjHaNrMCC2rtNxyrWi1gjuLOYwUQFuBJ4t1USmzOw7dpI3Zm6ialglbunS2Ok4xpzhg7nbOHg8kw9u7YCInTzmTUUVgg8ofl/AB6WYxZSxJrUi+PmR3jSMtLEKjG9JSTvFB/O2cWVcXdo2su733lZUG2rbN1ABnC4Ce1MzqFctzOE0xri89fNmTmXnWnfRMmI9iQ3zNx+kx0uzWLj1kNNRjOHXgyf47+LfuKlTQ5rWtv6WZcGrhUBE/iwia0VkjYh8KSKhBe7vLSKpIpLkvjztzTymcB2ia1Crcggv/7ABO2/QOG3kjI1UCgzggT7NnY5SYXitEIhIA1xjG3dQ1VggENfO5YLmqWqi+/K8t/KYcwutFMhDlzdn5W9HmbFuv9NxTAV25EQmv2w5yF09mlCnSmjxM5hSUdTg9W8B5/x6qKqeDGAfBISJSBYQDuwpcUJTJq5rH8Xoedt45YeNXN76ImvxaxxRIyKYOY9dSpC9/8pUUWsEy4DlQCjQDlfPoc1AIpBT3IJVdTcwEvgNV5uKVFWdUcikXUUkWUS+F5E2hS1LRO4WkWUisiwlxZqleUNQYACP9WvJlgPHmWitJ4wD9h87SU6uUi2sEhEhHo2ia0rJOQuBqn6qqp8CzYFLVfUtVX0L6IOrGBRJRGoAVwNNgPpAhIj8ocBkK4DGqpoAvAVMPkeW0araQVU71K5du/i/ypyX/rF1iY+qxhszN3Myq9hab0ypyclVbvt4Cfd8sdzpKBWSJ/sI6nPm+QSV3bcV53LgV1VNUdUsYCLQLf8EqnpMVY+7r08DKomIjTjhEBHh8f6t2H00gy8W7XA6jqlABLj30ou5sVNDp6NUSJ6sf/0bWCkis9y/98Kzs4l/A7qISDiQgWtNYln+CUSkLrBfVVVEOuEqTHYMo4MuubgW3S+uxTuztjC8gRAaaEcRGe8LCBAGJXjy/dJ4Q7FrBKr6CdAZmOS+dHVvMipuvsXABFybf1a7H2u0iIwQkRHuya4D1ohIMvAmcKONe+C8x/u34rJWF5Fjr4QpAyuPhvDOrC02PoaDii0E4mrycTmQoKpTgGD3t/diqeozqtpKVWNV9RZVPaWqo1R1lPv+t1W1jaomqGoXVV1wQX+NKRVxUdV49foEIoLsH9N4V2Yu/JQSwZxNKdiBQs7xZB/Bu7iGqrzJ/Xsa8I7XEhmfsedkEMuO2rHcxnuWHAnjeE4gj13R0hrLOciTfQSdVbWdiKwEUNUjImIjmlQAy4+GsvF4MCezcgitFOh0HFPOHDuZxfxD4VwccYqO0ZFOx6nQPCkEWSISiPvkMhGpDeR6NZXxCX1qn6Bv7RNWBIxXfDh3GydzA7isdrrTUSo8TzYNvYlrJ/FFIvICMB/4l1dTGZ8QHqiEBio5ucqRE5lOxzHlyKHjp/ho/q/EVDlJ/dBsp+NUeJ4MVTlWRJbjOvxTgGtUdb3XkxmfoAo3jV5EldAgPhrW0ek4ppx4b/ZWMrJyuLSBrQ34Ak+bztUC0lX1beCgiDTxYibjQ0SgV8va/LThAMt3HHE6jikH9qZm8NmiHQxpF0XtEDuD3Rd4cvjoM8DjwJPumyoBX3gzlPEtw7pFU6tyMCN/2Oh0FFMOfJu8B1XlQWsz7TM8WSMYDAwCTgCo6h6KH8LSlCMRIUH86dKLWbjtEL9sOeh0HOPn7urRlOkP9bQhUn2IJ4Ug03227+mjhiK8G8n4ot93bkT9aqG8/MNGG7zGnLdjJ7MQEZrZyGM+xZNC8LWIvA9UF5G7gJnYoPUVTkhQIA9d3oLknUf50QavMedh4740Or/wE7M2HHA6iinAk15DI3H1DPoGaAE87W5HbSqYIe0a0LRWBK/O2GR9YUyJVQkN4pq2DWjbqLrTUUwBnh41tBqYB8x1XzcVUFBgAH/u24KN+9P4NtkGmzMlU796GC8OiaN6uDUm8DWeHDV0J7AEGIKrW+giEbnD28GMb7oqrh6Xt76I0EpeG+7alEOvztjImt2pTscw5+BJi4nHgLaqeghARGoCC4CPvRnM+KaAAOHD2zo4HcP4kQVbD/LWz1uoFlaJ2AbVnI5jCuHJ17pduDqOnpYG7PROHOMvTmbl8PmiHTakpSmSqjLyh43UrRrKH7o0djqOOQdP1gh2A4tFZAquQ0ivBpaIyMMAqvqaF/MZH5W88yhPTV5DtbBKNrKUOaefNxxgxW9H+dfgOGte6MM8KQRb3ZfTprh/2kllFVjnpjWZet8lxEdVdzqK8VG5ucrIGZtoFBnO0A5RTscxRfCk6dxzp6+LSABQWVWPeTWV8Quni4CNV2AKM23NXtbvPcbrNyRQKdAOLvBlnhw19F8Rqeo+o3gdsFFEHvN+NOMPJizfRfeXfrY21eYM2Tm5vPbjJprXqcyghAZOxzHF8KRMx7jXAK4BpgGNgFu8Gcr4j/ioahw6kcmouVuLn9hUGJOT9rAt5QSP9GtBoA1G7PM8KQSVRKQSrkIwRVWzcPcdMqbFRVUYnNiATxdsZ/+xk07HMT5AVflw3jZiG1TlijZ1nY5jPOBJIXgf2A5EAHNFpDFg+whMnocub0F2jvL2z1ucjmJ8gIjwxZ2deXVoog1I7yc86TX0pqo2UNUr3V1IfwMu9X404y8a1Qznho4NGbf0N3YethGnKrLsnFxUlVqVQ2hZ1w4s9Bcl3pWvLjbIqDnD/Zc1J0CEN2ZudjqKcdCYBdsZ/O4Cjp+yjwh/Ysd0mVJRt1oot3WLZtLKXWzen1b8DKZcqlM1lOZ1KlM5xJNTlIyv8GohEJE/i8haEVkjIl+KSGiB+0VE3hSRLSKySkTaeTOP8a4RvZoRHhzEaz9ucjqKccighPq8MjTB6RimhM5ZtkVkSFEzqurEou4XkQbAA7gOP80Qka+BG4Ex+SYbADR3XzoD77l/Gj8UGRHMnT2asPnAcbJycu0kogokNT2LyUm7ubFTQ0KC7ORCf1PU+tvv3D/rAN2An92/XwrMBoosBPmWHyYiWUA4ULCJ/dXAZ+6d0ItEpLqI1FPVvR7mNz7mwT7N7UiRCmj0vK28M2srnZpE0rpeVafjmBI651c2Vb1dVW/Hdc5AjKpeq6rXAm08WbCq7gZG4jrKaC+QqqozCkzWgDM7me5y33YGEblbRJaJyLKUlBRPHt445HQR2Lw/jfV77SjjiuDg8VN88st2BsbXsyLgpzxZd48u8A19P64hK4skIjVwfeNvAtQHIkTkDwUnK2TWs05WU9XRqtpBVTvUrl3bg8jGSdk5udz68RL+/f0Gp6OYMvDe7K2czMrhz32L/VgwPsqTXfuzReQH4EtcH9I3ArM8mO9y4FdVTQEQkYm4NjF9kW+aXUDDfL9HcfbmI+NnggIDePv3bWlSq7LTUYyX7U3N4PNFO7i2XRTNatvr7a886T56n3vHcQ/3TaNVdZIHy/4N6CIi4UAG0AdYVmCaqcB9IjIO107iVNs/UD60bxwJuNoNALbfoJx66+ctqCoP9GnudBRzATw62Nd9hJAnO4fzz7NYRCYAK4BsYCUwWkRGuO8fhauJ3ZXAFiAduL0kj2F82/5jJ7nrs2WM6NWMK+PqOR3HlLLfDqXz9dKd3NSpEQ0jw52OYy5AsYXAvTbwEq6jh8R9UVUtdq+Qqj4DPFPg5lH57lfgTyUJbPxHrcohZGTm8OqMjfSLuYggO5y0XHnjp00EBgj3XXax01HMBfLkP/NlYJCqVlPVqqpaxZMiYExggPBIvxZsTTnBpJW7nY5jStH2gyeYvHI3t3WL5qKqocXPYHyaJ4Vgv6qu93oSUy5d0aYucQ2q8cbMzZzKtoHuy4vGNcN57w/tGd6zqdNRTCnwpBAsE5GvROQmERly+uL1ZKZcEBEeu6Ilu49m8NXSncXPYPyCiHBFm7rUrBzidBRTCjwpBFVx7cjth+ts498BA70ZypQvPZrXolOTSN78aQvpmdaV0t/d/+VKPpi7zekYphR5cvioHcljLsjptYKhoxby6YId3NO7mdORzHk6lZ1DTm4uOWqDFJYnRTWd+4uqviwib1H42b4PeDWZKVc6RkdyacvajJqzld93bkS1sEpORzLnISQokHdvbp93fogpH4raNHR6B/EyYHkhF2NK5JF+LQkOCmDLgeNORzHnYcVvR9hywDXWhJ0gWL4UtWmomYh0BMbaiGSmNMQ2qMYvj19GcJCdT+BvcnKVxyesAmDGn3taIShnivqPjAL+AxwQkdki8i8RuUpEIssomymHgoMCyMrJZcVvR5yOYkrgmxW72HzgOA/3bWFFoBwqqg31o6raDagL/BU4DNwBrBGRdWWUz5RDI2ds5MbRizhw7KTTUYwHTmbl8MaPm0hoWJ3+sXWdjmO8wJNeQ2G4DiGt5r7sAVZ7M5Qp327tGk2HxpHUrmLHoPuDzxfuYE/qSUZen2BrA+VUUUcNjcY1CE0asBhYALymqrZOby5Ig+phNKge5nQM44FjJ7N4Z/YWejSvRbdmtZyOY7ykqDWCRkAIsBnYjWvsgKNlkMn4iE6HJhKZuRs+Ge+V5e8+msGp7Bya2rgFPiv1SDqjsjOIy64Gn3jUrLhE+u/bx+HgBsCwUl+28dw5X1lV7S+u9cA2uAaUeQSIFZHDwEJ3Z1FjzltOrnIg7RR1q4YSHlz6HzLmwmTm5LI39SQ1I4KJsNenXCvy1XW3iV4jIkeBVPdlINCJs9tLm3JmSU1XS6lhw4Z5ZflV0zO56uVZdAyJ5ONhHb3yGOb8/XPKGv677Tdm/rEX1IrwymNMHzMGgBivLN146pxHDYnIAyIyTkR2AnNxFYCNwBDADiE1F6x6eDB/uvRift5wgF+2HHQ6jing3t4X8+r1CUR7qQgY31HUeQTRwASgk6o2VdVbVPVdVU1W1dyyiWfKu2HdomlQPYx//m89ObnWtsBXqCp1q4VydWIDp6OYMlDUeQQPq+oEG0PYeFNopUAeH9CK9XuP8c2KXU7HMcC8zSncOHoR+1LtPI+Kws71N477XXw9EhtWZ+QPG61NtQ84fjKbU9m51IiwxoAVhRUC4zgR4amBrTmQdorR1ufecQPi6jHp3m6EBAU6HcWUESsExie0bxzJlXF12ZpywlocO+TEqWy+Wvob2Tm5dgZxBWMHBxuf8foNifYt1EHvz93Gmz9tplXdqiQ0rO50HFOGbI3A+IzTRWDHoRNsS7ExC8rSvtSTjJ67lavi61kRqICsEBifkpmdy9BRC/nXtPXFT2xKzcgZG8nNhSf6t3I6inGAbRoyPiU4KIDXb0ikeR3rP1RW1uxO5ZsVu7irR1MaRoY7Hcc4wGtrBCLSUkSS8l2OichDBabpLSKp+aZ52lt5jP+45OJa1KkaiqqSnWPnLnqTqvLs1LVEus/yNhWT19YIVHUjkAggIoG4OphOKmTSeao60Fs5jH9Kz8zmto+XcGmrOtzb2z6gvGVy0m6W7TjCy9fGUy3MzhuoqMpqH0EfYKuq7iijxzN+Ljw4iOrhwbz98xY7w9VLjp/K5sVpG0iIqsZ17aOcjmMcVFaF4Ebgy3Pc11VEkkXkexFpU9gEInK3iCwTkWUpKSneS2l8ylNXxZCdq7bj2EvGL9vJgbRTPDuoDQEBdt5AReb1QiAiwcAgoLDRTVYAjVU1AXgLmFzYMlR1tKp2UNUOtWvX9lpW41sa1QxnRM+mTE3ew+Jth5yOU+7c1jWar4d3pW2jGk5HMQ4rizWCAcAKVd1f8A5VPaaqx93XpwGVRMTGwzN57ul9MfWrhfLM1LW247iUqCqp6VkEBAidmlhHeVM2heAmzrFZSETqukdBQ0Q6ufPYVz+TJyw4kL8PjGHDvjQ+W2i7mErD9DX76P7yz6zdk+p0FOMjvFoIRCQc6AtMzHfbCBEZ4f71OlwjoCUDbwI3qjWaMQUMiK1Lrxa1eXXGRvamZjgdx++1rFuFqxPr0/KiKk5HMT7Cq4VAVdNVtaaqpua7bZSqjnJff1tV26hqgqp2UdUF3sxj/JOI8I+rY8nOdR3zbi5M09qV+ec1cQQFWmMB42LvBOMXGtUM5/H+rejStKZ1Jz1Pq3elcs8Xy0lJO+V0FONjrMWE8Rt3dG/idAS/lZ2Ty5OTVrH/2ClCKtn3P3Mme0cYvzNxxS7e/nmz0zH8ymcLd7Bm9zGe+V0MVUPtDGJzJisExu8s+fUwczcftMHuPbTzcDqvzthIrxa1uSquntNxjA+yTUPG7zzzuzYEBwUQaGfDFktVeWLiKgBeGBxrI4+ZQtkagfE7YcGBBAYIKWmn+DZ5j9NxfNp/l/zGL1sO8derWhNVw1pMm8LZGoHxW2/9vJmxi38jumYEcVHVnI7jc3YdSedf/1tP94tr8ftOjZyOY3yYrREYv/VI35bUqhzMo+OTycy29hP5qSpPfLMagBeHxNkmIVMkKwTGb1ULr8SLQ+LYuD+Nt+woojPk5CqJDavz94ExNuqYKZZtGjJ+7bJWF3FtuyjembWFXi1q0yHamqgBBAUG8OgVLZ2OYfyErREYv/fsoBiiaoTz4LgkUjOynI7jqMzsXO78dCkLt1rvRuM5KwTG71UJrcR/bkxk37GT/G3S6grdguJA2kl+PXiCtJMVuyCakrFCYMqFto1q8HDfFny3ai/jl+9yOo5jomqEM/2hnvRrU9fpKMaPWCEw5caIXs245OKaHDhW8cY4Pnj8FC/8bx3pmdlUsq6ipoRsZ7EpNwIDhE9v71Th2itn5+Ty0Lgklmw/zHXtG9Kyro0zYEqmYv3HmHLvdBFYuPUQz05dWyH2F7wyYyPztxzkn1fHWhEw58UKgSmXVvx2hHmbUziaXr53mn63ag/vz9nGH7o04vqODZ2OY/yUbRoy5dK9vZsxrFs0ESHl9y2+Yd8xHhu/ivaNa/D0wDZOxzF+zNYITLkkIkSEBHEyK4dnpqxh15F0pyOVqtT0LIZ/vpwqoUG8d3M7goPsX9mcP3v3mHJtX+pJJq7Yze2fLCW1nGwmOpmVw12fL2PP0Qze+0M76lQNdTqS8XNWCEy5Fl0rgvdvbc+OQ+nc+dlSTmblOB3pgr398xaW/HqYV69PpH1ja6lhLpwVAlPudWtWi9duSGDZjiM88OVKvx/Z7J7ezXj/lvYMSqjvdBRTTlghMBXCwPj6PD0whhnr9vP0lDV+eVjp1OQ9HD+VTURIEFfYmcOmFFkhMBXG7Zc0YUSvZoxd/Bsvfr/Br4rBzsPpPPxVEh/O2+Z0FFMOld9j64wpxOP9W5Kemc3oudvIyMzhuUFtCPCDsY8bRoYz9s7OtG1Uw+kophyyQmAqFBHhuUFtCKsUyIKth8jIyvHZcw1UlddnbqZ13SoMiKtH56Y1nY5kyimvbRoSkZYikpTvckxEHiowjYjImyKyRURWiUg7b+Ux5jQR4YkBrfh6eFciQoI4cSrb54a6zM1VXvjfet78aTMLbGwB42Ve+yqkqhuBRAARCQR2A5MKTDYAaO6+dAbec/80xqtEhLDgQFSV+/67gqwc5bM7OvnEZqKMzBweGZ/EtNX7GNYtmmd+F+N0JFPOldU6cR9gq6ruKHD71cBn6tprt0hEqotIPVXdW0a5TAUnIlyd2ICTWTk+UQR2Hk7nnrHLWbvnGH+/qjV/7N7EBp43XldWheBG4MtCbm8A7Mz3+y73bWcUAhG5G7gboFGjRl6KaCqqa9o2yLs+bfVeUjOyuLFjwzL/AP5h7T4eG5+MAh/e2oE+rS8q08c3FZfXDx8VkWBgEDC+sLsLue2sY/pUdbSqdlDVDrVr1y7tiMbkmZq0hycnrubOT5eV2QA3qRlZPPJ1MsM/X07jmhH87/4eVgRMmSqL8wgGACtUdX8h9+0C8vfOjQL2lEEmYwr17s3teGpgDPO3HKTPa3P4eP6vZOV4d0dyStpJvl+zl/svu5hv7ulGo5rhXn08Ywoqi0JwE4VvFgKYCtzqPnqoC5Bq+weMkwIChD92b8L3D/YgsWF1nv9uHVe8MZcpSbtLtTXFvM0p/OO7dQBcXKcKvzx+GY/0a2ldRI0jvPquE5FwoC8wMd9tI0RkhPvXacA2YAvwAXCvN/MY46mmtSvz2R2d+ODWDgQHBvDguCR6j5zFe7O3nrMg5OTmMGfnHEYlj2LOzjnk5J7Z4C41PYtT2a7b1u05xox1+/I6otaICPbuH2RMEby6s1hV04GaBW4ble+6An/yZgZjzpeI0DfmIvq0qsOMdfv45Jft/LB2H/f0bgbA18t20qpuFeKjqpOTm8PwH4ez+uBqMrIzCAsKo3WNNtzT+iVW7DjGgq0HWbj1EC9fF8+QdlEMuySaO7o3sYHmjU/wzVMqjfEhAQFC/9h69I+tR0am6xt9dk4uz0xZy82dGxEfVZ0Z22ezeM9KCMgEID07nWX7kvn9ik/JOd6aZrUjuKtnU+IaVAMgJCjQsb/HmIKsEBhTAmHBrg/woMAAFv21T94ZyZuObISAMwe+kcAsrusi/KXL5dSsHFLmWY3xlBUCY85TtbBKedcT67QhPCiM9Oz/HxIzLCiUK1t2sCJgfJ5toDSmFHRv0J24WnGEBYUhCGFBYcTXiqd7g+5ORzOmWLZGYEwpCAwI5P2+7zN/93w2HN5Aq8hWdG/QncAA2xdgfJ8VAmNKSWBAIL0a9qJXw15ORzGmRGzTkDHGVHBWCIwxpoKzQmCMMRWcFQJjjKngrBAYY0wFJ652P/5DRFKAgiOdeaoWcLAU45QmX81muUrOV7NZrpLx1Vxwftkaq2qhA7r4XSG4ECKyTFU7OJ2jML6azXKVnK9ms1wl46u5oPSz2aYhY4yp4KwQGGNMBVfRCsFopwMUwVezWa6S89VslqtkfDUXlHK2CrWPwBhjzNkq2hqBMcaYAqwQGGNMBVfuCoGIDBWRtSKSKyLnPLxKRPqLyEYR2SIiT+S7PVJEfhSRze6fNUopV7HLFZGWIpKU73JMRB5y3/esiOzOd9+VpZHL02zu6baLyGr34y8r6fzeyCUiDUVkloisd7/uD+a7r1Sfs3O9Z/LdLyLypvv+VSLSztN5vZzrZneeVSKyQEQS8t1X6Gtahtl6i0hqvtfoaU/n9XKux/JlWiMiOSIS6b7Pa8+ZiHwsIgdEZM057vfOe0xVy9UFaA20BGYDHc4xTSCwFWgKBAPJQIz7vpeBJ9zXnwBeKqVcJVquO+M+XCeBADwLPOql58yjbMB2oNaF/m2lmQuoB7RzX68CbMr3Wpbac1bUeybfNFcC3wMCdAEWezqvl3N1A2q4rw84nauo17QMs/UGvjufeb2Zq8D0vwN+LqPnrCfQDlhzjvu98h4rd2sEqrpeVTcWM1knYIuqblPVTGAccLX7vquBT93XPwWuKaVoJV1uH2Crqp7vWdQlcaF/s2PPmaruVdUV7utpwHqgQSk9fn5FvWfy5/1MXRYB1UWknofzei2Xqi5Q1SPuXxcBUaX02BeczUvzlvaybwK+LKXHLpKqzgUOFzGJV95j5a4QeKgBsDPf77v4/w+Pi1R1L7g+ZIA6pfSYJV3ujZz95rvPvTr4cWltfilhNgVmiMhyEbn7POb3Vi4ARCQaaAsszndzaT1nRb1nipvGk3m9mSu/P+L6RnnauV7TsszWVUSSReR7EWlTwnm9mQsRCQf6A9/ku9mbz1lxvPIe88sRykRkJlC3kLv+pqpTPFlEIbdd8HG0ReUq4XKCgUHAk/lufg/4B66c/wBeBe4o42yXqOoeEakD/CgiG9zfYM5bKT5nlXH9sz6kqsfcN1/Qc1bwIQq5reB75lzTeOX9Vsxjnj2hyKW4CkH+gZRL/TUtYbYVuDZ/Hnfvw5kMNPdwXm/mOu13wC+qmv9bujefs+J45T3ml4VAVS+/wEXsAhrm+z0K2OO+vl9E6qnqXvcq14HSyCUiJVnuAGCFqu7Pt+y86yLyAfCdp7lKK5uq7nH/PCAik3Ctjs7F4edMRCrhKgJjVXVivmVf0HNWQFHvmeKmCfZgXm/mQkTigQ+BAap66PTtRbymZZItX9FGVaeJyLsiUsuTeb2ZK5+z1sy9/JwVxyvvsYq6aWgp0FxEmri/fd8ITHXfNxW4zX39NsCTNQxPlGS5Z22TdH8QnjYYKPSoAm9lE5EIEaly+jrQL18Gx54zERHgI2C9qr5W4L7SfM6Kes/kz3ur+8iOLkCqe5OWJ/N6LZeINAImAreo6qZ8txf1mpZVtrru1xAR6YTrM+mQJ/N6M5c7TzWgF/ned2XwnBXHO+8xb+z5dvKC6x9+F3AK2A/84L69PjAt33RX4jrCZCuuTUqnb68J/ARsdv+MLKVchS63kFzhuP4RqhWY/3NgNbDK/QLXK8XnrNhsuI5GSHZf1vrKc4ZrM4e6n5ck9+VKbzxnhb1ngBHACPd1Ad5x37+afEetnev9VkrPU3G5PgSO5Ht+lhX3mpZhtvvcj52Ma0d2N194zty/DwPGFZjPq88Zri+Ae4EsXJ9jfyyL95i1mDDGmAquom4aMsYY42aFwBhjKjgrBMYYU8FZITDGmArOCoExxlRwVgiMKQUiMl1EGojIbHcHyFUiskFE3haR6k7nM6YoVgiMuUAiEobrHIfd7ptuVtV4IB7X+SyldYKdMV7hly0mjHGCiPwDOKiq/3H//gKukxY342p7fgZVzRSRvwBbRCRBVZPLMq8xnrI1AmM89xHulhciEoDrNP6xuHpDTS9sBlXNwXUWaqsyymhMiVkhMMZDqrodOCQibXH1mFmprgZulwDzi5i1sM6QxvgM2zRkTMl8iKsHTV3gYxFpCuxU12AgZxGRQCAO14A5xvgkWyMwpmQm4RqopCPwA0VsFnK3x34RV6FYVWYJjSkhWyMwpgTcO4BnAUdVNUdE+gP3F5hsrIicAkKAmZTeEIvGeIUVAmNKwL2TuAswVERCcLW23n76flXt7VA0Y86bbRoyxkMiEgNsAX5S1c2qekpVOzidy5gLZeMRGGNMBWdrBMYYU8FZITDGmArOCoExxlRwVgiMMaaCs0JgjDEV3P8Bkp0Btb2yZacAAAAASUVORK5CYII=\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 0x22980d52b50>" ] }, "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(r'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, Á., 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 0x22980f59520>" ] }, "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. 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 0x22982eacf10>" ] }, "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 0x22982f3ac40>" ] }, "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 0x229f26edd90>" ] }, "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 }