from py_wake.flow_map import HorizontalGrid, YZGrid, Points, XYGrid
from py_wake.tests import npt
import matplotlib.pyplot as plt
from py_wake import np
from py_wake.examples.data.ParqueFicticio._parque_ficticio import ParqueFicticioSite
from py_wake.site.distance import StraightDistance
from py_wake.examples.data.iea37 import IEA37Site, IEA37_WindTurbines
import pytest
from py_wake.deflection_models.jimenez import JimenezWakeDeflection
from py_wake.wind_turbines._wind_turbines import WindTurbines, WindTurbine
from py_wake.examples.data import wtg_path, hornsrev1
from py_wake.utils.profiling import timeit
from py_wake.wind_turbines.power_ct_functions import PowerCtTabular
from py_wake.examples.data.hornsrev1 import V80
from py_wake.literature.iea37_case_study1 import IEA37CaseStudy1
from py_wake.deficit_models.gaussian import IEA37SimpleBastankhahGaussianDeficit
from py_wake.wind_farm_models.engineering_models import PropagateDownwind
from py_wake.superposition_models import SquaredSum
@pytest.fixture(autouse=True)
def close_plots():
yield
try:
plt.close('all')
except Exception:
pass
def test_power_xylk():
wind_farm_model = IEA37CaseStudy1(16)
x, y = wind_farm_model.site.initial_position.T
simulation_result = wind_farm_model(x, y)
fm = simulation_result.flow_map(grid=HorizontalGrid(resolution=3))
npt.assert_array_almost_equal(fm.power_xylk(with_wake_loss=False)[:, :, 0, 0] * 1e-6, 3.35)
fm = simulation_result.flow_map(grid=Points(
[-1820., 0., 1820., -1820., 0., 1820., -1820., 0., 1820.],
[-1730.9229, -1730.9229, -1730.9229, 0., 0., 0., 1730.9229, 1730.9229, 1730.9229],
[110., 110., 110., 110., 110., 110., 110., 110., 110.]))
npt.assert_array_almost_equal(fm.power_xylk(with_wake_loss=False)[:, 0, 0] * 1e-6, 3.35)
def test_power_xylk_wt_args():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = WindTurbines.from_WAsP_wtg(wtg_path + "Vestas V112-3.0 MW.wtg", default_mode=None)
wind_farm_model = PropagateDownwind(site, windTurbines,
wake_deficitModel=IEA37SimpleBastankhahGaussianDeficit(),
superpositionModel=SquaredSum())
simulation_result = wind_farm_model(x, y, wd=[0, 270], ws=[6, 8, 10], mode=0)
fm = simulation_result.flow_map(XYGrid(resolution=3))
npt.assert_array_almost_equal(fm.power_xylk(mode=1).sum(['wd', 'ws']).isel(h=0),
[[7030000., 6378864., 7029974.],
[7030000., 6144918., 4902029.],
[7030000., 7030000., 7029974.]], 0)
npt.assert_array_almost_equal(fm.power_xylk(mode=8).sum(['wd', 'ws']).isel(h=0),
[[8330000., 7577910., 8329970.],
[8330000., 7304188., 5837139.],
[8330000., 8330000., 8329970.]], 0)
# print(np.round(fm.power_xylk(mode=8).sum(['wd', 'ws']).squeeze()))
npt.assert_array_almost_equal(fm.aep_xylk(mode=1).sum(['x', 'y']).isel(h=0),
[[10., 24., 47.],
[75., 191., 375.]], 0)
npt.assert_array_almost_equal(fm.aep_xy(mode=1).isel(h=0),
[[88., 86., 88.],
[88., 68., 40.],
[88., 88., 88.]], 0)
def test_YZGrid_perpendicular():
wind_farm_model = IEA37CaseStudy1(16)
x, y = wind_farm_model.site.initial_position.T
m = x < -1000
simulation_result = wind_farm_model(x[m], y[m], wd=270)
fm = simulation_result.flow_map(grid=YZGrid(-1000, z=110, resolution=20))
if 0:
simulation_result.flow_map(grid=YZGrid(-1000)).plot_wake_map()
plt.plot(fm.X[0], fm.Y[0], '.')
print(np.round(fm.WS_eff_xylk[:, 0, 0, 0], 2).data.tolist())
plt.plot(fm.X[0], fm.WS_eff_xylk[:, 0, 0, 0] * 100, label='ws*100')
plt.legend()
plt.show()
npt.assert_array_almost_equal(fm.WS_eff_xylk[:, 0, 0, 0],
[9.8, 9.8, 8.42, 5.24, 9.74, 9.8, 9.8, 9.8, 9.76, 7.61, 7.61,
9.76, 9.8, 9.8, 9.8, 9.74, 5.24, 8.42, 9.8, 9.8], 2)
def test_YZGrid_parallel():
wind_farm_model = IEA37CaseStudy1(16)
x, y = wind_farm_model.site.initial_position.T
m = x < -1000
simulation_result = wind_farm_model(x[m], y[m], wd=0)
fm = simulation_result.flow_map(grid=YZGrid(-1000, z=110, resolution=20))
if 0:
simulation_result.flow_map(grid=YZGrid(-1000)).plot_wake_map()
plt.plot(fm.X[0], fm.Y[0], '.')
print(np.round(fm.WS_eff_xylk[:, 0, 0, 0], 2).data.tolist())
plt.plot(fm.X[0], fm.WS_eff_xylk[:, 0, 0, 0] * 100, label='ws*100')
plt.legend()
plt.show()
npt.assert_array_almost_equal(fm.WS_eff_xylk[:, 0, 0, 0],
[7.32, 7.02, 6.63, 8.86, 8.79, 8.71, 8.63, 8.53, 8.42, 8.3, 8.16,
7.99, 7.81, 7.59, 7.33, 7.0, 6.52, 9.8, 9.8, 9.8], 2)
def test_YZGrid_plot_wake_map_perpendicular():
wfm = IEA37CaseStudy1(16)
x, y = wfm.site.initial_position.T
sim_res = wfm(x, y)
sim_res.flow_map(grid=YZGrid(x=-100, y=None, resolution=100, extend=.1), wd=270, ws=None).plot_wake_map()
if 0:
plt.show()
plt.close('all')
def test_YZGrid_variables():
wfm = IEA37CaseStudy1(16)
x, y = [0], [0]
sim_res = wfm(x, y)
fm = sim_res.flow_map(grid=YZGrid(x=100, y=None, resolution=100, extend=.1), wd=270, ws=None)
fm.WS_eff.plot()
plt.plot(fm.y[::10], fm.y[::10] * 0 + 110, '.')
if 0:
print(np.round(fm.WS_eff.interp(h=110)[::10].squeeze().values, 4))
plt.show()
plt.close('all')
npt.assert_array_almost_equal(fm.WS_eff.interp(h=110)[::10].squeeze(),
[9.1461, 8.4157, 7.3239, 6.058, 5.022, 4.6455, 5.1019, 6.182, 7.446, 8.506], 4)
def test_YZGrid_plot_wake_map_parallel():
wfm = IEA37CaseStudy1(16)
x, y = wfm.site.initial_position.T
sim_res = wfm(x, y)
sim_res.flow_map(wd=0, ws=None).plot_wake_map()
plt.axvline(-450, ls='--')
plt.figure()
sim_res.flow_map(grid=YZGrid(x=-450, y=None, resolution=100, extend=.1), wd=0, ws=None).plot_wake_map()
if 0:
plt.show()
plt.close('all')
def test_YZGrid_terrain_perpendicular():
site = ParqueFicticioSite(distance=StraightDistance())
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wfm = PropagateDownwind(site, windTurbines,
wake_deficitModel=IEA37SimpleBastankhahGaussianDeficit(),
superpositionModel=SquaredSum())
simulation_result = wfm(x, y, wd=270, ws=10)
x = x.max() + 10
fm = simulation_result.flow_map(grid=YZGrid(x, z=110, resolution=20, extend=0))
y = fm.X[0]
x = np.zeros_like(y) + x
z = site.elevation(x, y)
simulation_result.flow_map(XYGrid(extend=.005)).plot_wake_map()
plt.plot(x, y, '.')
plt.figure()
simulation_result.flow_map(grid=YZGrid(fm.x.item(), y=fm.y,
z=np.arange(30, 210, 10))).plot_wake_map()
plt.plot(y, z + 110, '.')
plt.plot(y, fm.WS_eff_xylk[:, 0, 0, 0] * 100, label="ws*100")
plt.legend()
if 0:
print(np.round(fm.WS_eff_xylk[:, 0, 0, 0], 2).values.tolist())
plt.show()
plt.close('all')
npt.assert_array_almost_equal(fm.WS_eff_xylk[:, 0, 0, 0],
[5.39, 8.48, 8.42, 6.42, 5.55, 11.02, 4.99, 11.47, 5.32, 10.22, 13.39, 8.79,
8.51, 12.4, 5.47, 10.78, 10.12, 6.54, 10.91, 7.18], 2)
def test_YZGrid_terrain_parallel():
site = ParqueFicticioSite(distance=StraightDistance())
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wfm = PropagateDownwind(site, windTurbines,
wake_deficitModel=IEA37SimpleBastankhahGaussianDeficit(),
superpositionModel=SquaredSum())
simulation_result = wfm(x, y, wd=0, ws=10)
x = 264000
fm = simulation_result.flow_map(grid=YZGrid(x, z=110, resolution=20, extend=0))
if 0:
y = fm.X[0]
x = np.zeros_like(y) + x
z = site.elevation(x, y)
simulation_result.flow_map(XYGrid(extend=0.005)).plot_wake_map()
plt.plot(x, y, '.')
plt.figure()
simulation_result.flow_map(grid=YZGrid(fm.x.item(), fm.y, z=np.arange(30, 210, 10))).plot_wake_map()
plt.plot(y, z + 110, '.')
plt.plot(y, fm.WS_eff_xylk[:, 0, 0, 0] * 100, label="ws*100")
plt.legend()
print(np.round(fm.WS_eff_xylk[:, 0, 0, 0], 2).values.tolist())
plt.show()
plt.close('all')
npt.assert_array_almost_equal(fm.WS_eff_xylk[:, 0, 0, 0],
[4.55, 3.89, 3.15, 2.31, 4.41, 4.3, 7.41, 7.2, 7.03, 7.23, 7.32, 6.77, 6.83,
5.58, 11.01, 11.51, 11.93, 12.17, 11.03, 9.89], 2)
def test_Points():
wfm = IEA37CaseStudy1(16)
x, y = wfm.site.initial_position.T
sim_res = wfm(x, y)
flow_map = sim_res.flow_map(Points(x, y, x * 0 + wfm.windTurbines.hub_height()), wd=0, ws=None)
if 0:
flow_map.WS_eff.plot()
plt.show()
plt.close('all')
def test_not_implemented_plane():
wfm = IEA37CaseStudy1(16)
x, y = wfm.site.initial_position.T
sim_res = wfm(x, y)
grid = YZGrid(x=-100, y=None, resolution=100, extend=.1)
grid = grid(x, y, wfm.windTurbines.hub_height(x * 0), wfm.windTurbines.hub_height(x * 0))
with pytest.raises(NotImplementedError):
sim_res.flow_map(grid=grid, wd=270, ws=None).plot_wake_map()
def test_FlowBox():
wfm = IEA37CaseStudy1(16)
x, y = wfm.site.initial_position.T
sim_res = wfm(x, y)
sim_res.flow_box(x=np.arange(0, 100, 10), y=np.arange(0, 100, 10), h=np.arange(0, 100, 10))
def test_min_ws_eff_line():
wfm = IEA37CaseStudy1(16, deflectionModel=JimenezWakeDeflection())
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
yaw_ilk = np.reshape([-30, 30, 0], (3, 1, 1))
plt.figure(figsize=(14, 3))
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()
if 0:
fm.plot_wake_map()
min_ws_line.plot()
print(np.round(min_ws_line[::10], 2))
plt.show()
plt.close('all')
npt.assert_array_almost_equal(min_ws_line[::10],
[np.nan, np.nan, 11.6, 21.64, 30.42, 38.17, 45.09, 51.27,
-8.65, -18.66, -27.51, -35.37, -42.38, -48.58, -1.09, -1.34,
-1.59, -1.83, -2.07, -2.31, -2.56], 2)
def test_plot_windturbines_with_wd_ws_dependent_yaw():
wfm = IEA37CaseStudy1(16, deflectionModel=JimenezWakeDeflection())
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
yaw_ilk = np.broadcast_to(np.reshape([-30, 30, 0], (3, 1, 1)), (3, 4, 2))
plt.figure(figsize=(14, 3))
fm = wfm(x, y, yaw=yaw_ilk, wd=[0, 90, 180, 270], ws=[9, 10]).flow_map(
XYGrid(x=np.arange(-100, 2000, 10), y=np.arange(-500, 500, 10)))
fm.plot_windturbines()
if 0:
plt.show()
plt.close('all')
def flow_map_j_wd_chunks():
# demonstrate that wd chunkification is more efficient than j chunkification
wfm = IEA37CaseStudy1(16, deflectionModel=JimenezWakeDeflection())
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
yaw_ilk = np.reshape([-30, 30, 0], (3, 1, 1))
sim_res = wfm(x, y, yaw=yaw_ilk, wd=np.arange(320), ws=10)
t_all = timeit(sim_res.flow_map, verbose=1)(XYGrid(x=np.linspace(-100, 2000, 64), y=np.linspace(-500, 500, 100)))
t_j = timeit(sim_res.flow_map, verbose=1)(XYGrid(x=np.linspace(-100, 2000, 2), y=np.linspace(-500, 500, 100)))
t_wd = timeit(sim_res.flow_map, verbose=1)(XYGrid(x=np.linspace(-100, 2000, 64), y=np.linspace(-500, 500, 100)),
wd=np.arange(10))
print(np.mean(t_all[1]) / np.mean(t_j[1]))
print(np.mean(t_all[1]) / np.mean(t_wd[1]))
def test_aep_map():
wfm = IEA37CaseStudy1(16)
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
sim_res = wfm(x, y)
grid = XYGrid(x=np.linspace(-100, 2000, 50), y=np.linspace(-500, 500, 25))
aep_map = sim_res.aep_map(grid, normalize_probabilities=True)
fm = sim_res.flow_map(grid)
npt.assert_array_almost_equal(fm.aep_xy(normalize_probabilities=True).sel(h=110), aep_map)
grid = Points(x=np.linspace(-100, 2000, 50), y=np.full(50, -500), h=np.full(50, wfm.windTurbines.hub_height()))
aep_line = sim_res.aep_map(grid, normalize_probabilities=True)
npt.assert_array_almost_equal(aep_map[0], aep_line)
def test_aep_map_type():
site = IEA37Site(16)
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
v80 = V80()
v120 = WindTurbine('V80_low_induc', 80, 70, powerCtFunction=PowerCtTabular(
hornsrev1.power_curve[:, 0], hornsrev1.power_curve[:, 1] * 1.5, 'w', hornsrev1.ct_curve[:, 1]))
windTurbines = WindTurbines.from_WindTurbine_lst([v80, v120])
wfm = PropagateDownwind(site, windTurbines,
wake_deficitModel=IEA37SimpleBastankhahGaussianDeficit(),
superpositionModel=SquaredSum())
sim_res = wfm(x, y)
grid = XYGrid(x=np.linspace(-100, 2000, 50), y=np.linspace(-500, 500, 25))
aep_map0 = sim_res.aep_map(grid, normalize_probabilities=True)
aep_map1 = sim_res.aep_map(grid, type=1, normalize_probabilities=True)
npt.assert_array_almost_equal(aep_map0 * 1.5, aep_map1)
def test_aep_map_parallel():
wfm = IEA37CaseStudy1(16)
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
sim_res = wfm(x, y)
grid = XYGrid(x=np.linspace(-100, 2000, 50), y=np.linspace(-500, 500, 25))
aep_map = sim_res.aep_map(grid, normalize_probabilities=True, n_cpu=2)
fm = sim_res.flow_map(grid)
npt.assert_array_almost_equal(fm.aep_xy(normalize_probabilities=True).sel(h=110), aep_map)
fm = sim_res.flow_map(grid, wd=[0])
aep_map = sim_res.aep_map(grid, normalize_probabilities=True, wd=[0], n_cpu=2)
npt.assert_array_almost_equal(fm.aep_xy(normalize_probabilities=True).sel(h=110), aep_map)
def test_aep_map_smartstart_griddedsite_terrainfollowingdistance():
site = ParqueFicticioSite()
x, y = site.initial_position[:3].T
windTurbines = IEA37_WindTurbines()
wfm = PropagateDownwind(site, windTurbines,
wake_deficitModel=IEA37SimpleBastankhahGaussianDeficit(),
superpositionModel=SquaredSum())
for i in range(3):
sim_res = wfm(x[:i], y[:i], wd=[0, 1])
grid = XYGrid(x=site.ds.x, y=site.ds.y)
sim_res.aep_map(grid, normalize_probabilities=True)
def test_wd_dependent_flow_map():
wfm = IEA37CaseStudy1(16)
sim_res = wfm(x=[0], y=[0], wd=[0, 90, 180])
for wd in [[0], [0, 90], None]:
fm = sim_res.flow_map(wd=wd)
fm.plot_wake_map()
if 0:
plt.show()
plt.close('all')
def test_ws_dependent_flow_map():
wfm = IEA37CaseStudy1(16)
sim_res = wfm(x=[0], y=[0], ws=[8, 9, 10], wd=270)
for ws in [[8], [8, 9], None]:
fm = sim_res.flow_map(ws=ws)
fm.plot_wake_map()
if 0:
plt.show()
plt.close('all')
def test_time_dependent_flow_map():
wfm = IEA37CaseStudy1(16)
sim_res = wfm(x=[0], y=[0], wd=[0, 90, 180], ws=[8, 9, 10], time=True)
for t in [[0], [0, 1], None]:
fm = sim_res.flow_map(time=t)
fm.plot_wake_map()
if 0:
plt.show()
plt.close('all')
def test_i_dependent_flow_map():
wfm = IEA37CaseStudy1(16)
sim_res = wfm(x=[0], y=[0], wd=[0, 90, 180])
X, Y = np.meshgrid(np.linspace(-2000, 2000, 50), np.linspace(-2000, 2000, 50))
fm = sim_res.flow_map(Points(x=X.flatten(), y=Y.flatten(), h=X.flatten() * 0 + 110))
with pytest.raises(NotImplementedError, match="Plot not supported for FlowMaps based on Points. Use XYGrid, YZGrid or XZGrid instead"):
fm.plot_wake_map()