def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37 import IEA37Site, IEA37_WindTurbines
from py_wake.deficit_models.selfsimilarity import SelfSimilarityDeficit
import matplotlib.pyplot as plt
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
from py_wake.deficit_models.noj import NOJDeficit
from py_wake.superposition_models import SquaredSum
# NOJ wake model
noj = PropagateDownwind(site,
windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum())
# NOJ wake and selfsimilarity blockage
noj_ss = All2AllIterative(
site,
windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum(),
blockage_deficitModel=SelfSimilarityDeficit())
for wm in [noj, noj_ss]:
plt.figure()
wm(x=x, y=y, wd=[30], ws=[9]).flow_map().plot_wake_map()
plt.show()
def test_iea37_distances():
from py_wake.examples.data.iea37 import IEA37Site
n_wt = 16 # must be 9, 16, 36, 64
site = IEA37Site(n_wt)
x, y = site.initial_position.T
lw = site.local_wind(x_i=x, y_i=y,
wd=site.default_wd,
ws=site.default_ws)
dw_iil, hcw_iil, _, _ = site.wt2wt_distances(
x_i=x, y_i=y,
h_i=np.zeros_like(x),
wd_il=lw.WD_ilk.mean(2))
# Wind direction.
wdir = np.rad2deg(np.arctan2(hcw_iil, dw_iil))
npt.assert_allclose(
wdir[:, 0, 0],
[180, -90, -18, 54, 126, -162, -90, -54, -18, 18, 54, 90, 126, 162, -162, -126],
atol=1e-4)
if 0:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.scatter(x, y)
for i, txt in enumerate(np.arange(len(x))):
ax.annotate(txt, (x[i], y[i]), fontsize='large')
def test_min_ws_eff_line():
site = IEA37Site(16)
x, y = [0, 600, 1200], [0, 0, 0] # site.initial_position[:2].T
windTurbines = IEA37_WindTurbines()
wfm = IEA37SimpleBastankhahGaussian(
site, windTurbines, deflectionModel=JimenezWakeDeflection())
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()
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_FlowBox():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wf_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
sim_res = wf_model(x, y)
flow_box = sim_res.flow_box(x=np.arange(0, 100, 10), y=np.arange(0, 100, 10), h=np.arange(0, 100, 10))
def test_plot_ws_distribution_iea37():
from py_wake.examples.data.iea37 import IEA37Site
n_wt = 16 # must be 16, 32 or 64
site = IEA37Site(n_wt)
site.plot_ws_distribution(wd=[0])
if 0:
import matplotlib.pyplot as plt
plt.show()
def test_power_xylk():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
# NOJ wake model
wind_farm_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
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)
def test_not_implemented_plane():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wf_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
sim_res = wf_model(x, y)
grid = YZGrid(x=-100, y=None, resolution=100, extend=.1)
grid = grid(x, y, windTurbines.hub_height(x * 0), windTurbines.hub_height(x * 0))
with pytest.raises(NotImplementedError):
sim_res.flow_map(grid=grid, wd=270, ws=None).plot_wake_map()
def test_YZGrid_plot_wake_map():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wf_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
sim_res = wf_model(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()
def test_plot_ws_distribution_iea37():
from py_wake.examples.data.iea37 import IEA37Site
n_wt = 16 # must be 16, 32 or 64
site = IEA37Site(n_wt)
p = site.plot_ws_distribution(wd=[0])
npt.assert_almost_equal(p, [1 / 300] * 300)
if 0:
import matplotlib.pyplot as plt
plt.show()
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37 import IEA37Site, IEA37_WindTurbines
from py_wake.deficit_models.selfsimilarity import SelfSimilarityDeficit
from py_wake.deficit_models.gaussian import ZongGaussianDeficit
from py_wake.turbulence_models.stf import STF2017TurbulenceModel
from py_wake.flow_map import XYGrid
import matplotlib.pyplot as plt
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
from py_wake.deficit_models.noj import NOJDeficit
from py_wake.superposition_models import SquaredSum
# NOJ wake model
noj = PropagateDownwind(site,
windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum())
# NOJ wake and selfsimilarity blockage
noj_ss = All2AllIterative(
site,
windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum(),
blockage_deficitModel=SelfSimilarityDeficit())
# Zong convection superposition
zongp_ss = PropagateDownwind(site,
windTurbines,
wake_deficitModel=ZongGaussianDeficit(),
superpositionModel=WeightedSum(),
turbulenceModel=STF2017TurbulenceModel())
# Zong convection superposition
zong_ss = All2AllIterative(
site,
windTurbines,
wake_deficitModel=ZongGaussianDeficit(),
superpositionModel=WeightedSum(),
blockage_deficitModel=SelfSimilarityDeficit(),
turbulenceModel=STF2017TurbulenceModel())
for wm in [noj, noj_ss, zongp_ss, zong_ss]:
sim = wm(x=x, y=y, wd=[30], ws=[9])
plt.figure()
sim.flow_map(XYGrid(resolution=200)).plot_wake_map()
plt.title(' AEP: %.3f GWh' % sim.aep().sum())
plt.show()
def test_Points():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wf_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
sim_res = wf_model(x, y)
flow_map = sim_res.flow_map(Points(x, y,
x * 0 + windTurbines.hub_height()),
wd=0,
ws=None)
if 0:
flow_map.WS_eff.plot()
plt.show()
plt.close('all')
def test_YZGrid():
site = IEA37Site(16)
x, y = site.initial_position.T
m = x < -1000
windTurbines = IEA37_WindTurbines()
wind_farm_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
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.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():
site = IEA37Site(16)
x, y = site.initial_position.T
m = x < -1000
windTurbines = IEA37_WindTurbines()
wind_farm_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
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 main():
if __name__ == '__main__':
from py_wake.examples.data.iea37 import IEA37Site, IEA37_WindTurbines
from py_wake import IEA37SimpleBastankhahGaussian
import matplotlib.pyplot as plt
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wind_farm_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
simulation_result = wind_farm_model(x, y)
fm = simulation_result.flow_map(wd=30)
fm.plot_wake_map()
plt.figure()
fm.plot(fm.power_xylk().sum(['wd', 'ws']) * 1e-3, "Power [kW]")
fm = simulation_result.flow_map(grid=HorizontalGrid(resolution=50))
plt.figure()
fm.plot(fm.aep_xy(), "AEP [GWh]")
plt.show()
def test_YZGrid_variables():
site = IEA37Site(16)
x, y = [0], [0]
windTurbines = IEA37_WindTurbines()
wf_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
sim_res = wf_model(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)