def test_twotype_windturbines():
v80 = V80()
def power(ws, types):
power = v80.power(ws)
# add 10% type 1 turbines
power[types == 1] *= 1.1
return power
power_curve = hornsrev1.power_curve
wts = WindTurbines(names=['V80', 'V88'],
diameters=[80, 88],
hub_heights=[70, 77],
ct_funcs=[v80.ct_funcs[0],
v80.ct_funcs[0]],
power_funcs=[lambda ws, yaw: np.interp(ws, power_curve[:, 0], power_curve[:, 1]),
lambda ws, yaw: np.interp(ws, power_curve[:, 0], power_curve[:, 1]) * 1.1],
power_unit='w'
)
import matplotlib.pyplot as plt
types0 = [0] * 9
types1 = [0, 0, 0, 1, 1, 1, 0, 0, 0]
types2 = [1] * 9
wts.plot(wt9_x, wt9_y, types1)
wfm = NOJ(Hornsrev1Site(), wts)
npt.assert_array_equal(wts.types(), [0, 1])
npt.assert_almost_equal(wfm.aep(wt9_x, wt9_y, type=types0), 81.2066072392765)
npt.assert_almost_equal(wfm.aep(wt9_x, wt9_y, type=types1), 83.72420504573488)
npt.assert_almost_equal(wfm.aep(wt9_x, wt9_y, type=types2), 88.87227386796884)
if 0:
plt.show()
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37._iea37 import IEA37Site
from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
from py_wake import NOJ
# setup site, turbines and flow model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
import matplotlib.pyplot as plt
_, (ax1, ax2) = plt.subplots(1, 2)
for ax, wf_model, lbl in [
(ax1,
NOJ(site, windTurbines,
turbulenceModel=STF2005TurbulenceModel()), 'STF2005'),
(ax2,
NOJ(site, windTurbines,
turbulenceModel=STF2017TurbulenceModel()), 'STF2017')
]:
sim_res = wf_model(x, y)
print(sim_res.TI_eff_ilk[:, 0])
# plot wake map
flow_map = sim_res.flow_map(wd=0, ws=9.8)
c = flow_map.plot_ti_map(ax=ax)
ax.set_title('Turbulence intensity calculated by %s' % lbl)
plt.show()
def test_superposition_models(superpositionModel, res):
site = UniformSite([1], 0.1)
wake_model = NOJ(site, NibeA0, superpositionModel=superpositionModel)
x_i = [0, 0, 0]
y_i = [0, -40, -100]
h_i = [50, 50, 50]
WS_eff_ilk = wake_model.calc_wt_interaction(x_i, y_i, h_i, [0, 0, 1], 0.0,
8.1)[0]
npt.assert_array_almost_equal(WS_eff_ilk[-1, 0, 0], res)
def test_NOJ_Nibe_result():
# Replicate result from: Jensen, Niels Otto. "A note on wind generator interaction." (1983).
site = UniformSite([1], 0.1)
wake_model = NOJ(site, NibeA0)
x_i = [0, 0, 0]
y_i = [0, -40, -100]
h_i = [50, 50, 50]
WS_eff_ilk = wake_model.calc_wt_interaction(x_i, y_i, h_i, [0, 1, 1], 0.0,
8.1)[0]
npt.assert_array_almost_equal(WS_eff_ilk[:, 0, 0], [8.1, 4.35, 5.7])
def test_NOJ_6_turbines_in_row():
n_wt = 6
x = [0] * n_wt
y = -np.arange(n_wt) * 40 * 2
site = UniformSite([1], 0.1)
wake_model = NOJ(site, NibeA0)
WS_eff_ilk = wake_model.calc_wt_interaction(x, y, [50] * n_wt,
[0.0] * n_wt, 0.0, 11.0)[0]
np.testing.assert_array_almost_equal(
WS_eff_ilk[1:, 0, 0], 11 - np.sqrt(
np.cumsum(
((11 * 2 / 3 * 20**2)**2) / (20 + 8 * np.arange(1, 6))**4)))
def test_NOJ_two_turbines_in_row(wdir, x, y):
# Two turbines in a row, North-South
# Replicate result from: Jensen, Niels Otto. "A note on wind generator interaction." (1983).
windTurbines = NibeA0
site = UniformSite([1], 0.1)
wfm = NOJ(site, windTurbines)
wfm.verbose = False
h_i = [50, 50, 50]
WS_eff_ilk = wfm.calc_wt_interaction(x, y, h_i, [0, 0, 0], wdir, 8.1)[0]
ws_wt3 = 8.1 - np.hypot(8.1 * 2 / 3 * (20 / 26)**2, 8.1 * 2 / 3 *
(20 / 30)**2)
npt.assert_array_almost_equal(WS_eff_ilk[:, 0, 0], [8.1, 4.35, ws_wt3])
def test_aep():
site = UniformSite([1], ti=0)
windTurbines = IEA37_WindTurbines()
wfm = NOJ(site, windTurbines)
sim_res = wfm([0], [0], wd=270)
npt.assert_almost_equal(sim_res.aep().sum(), 3.35 * 24 * 365 / 1000)
npt.assert_almost_equal(sim_res.aep(normalize_probabilities=True).sum(), 3.35 * 24 * 365 / 1000)
npt.assert_equal(sim_res.aep().data.sum(), wfm.aep([0], [0], wd=270))
npt.assert_almost_equal(sim_res.aep(normalize_probabilities=True).sum(),
wfm.aep([0], [0], wd=270, normalize_probabilities=True))
npt.assert_almost_equal(sim_res.aep(with_wake_loss=False).sum(), wfm.aep([0], [0], wd=270, with_wake_loss=False))
def test_time_series_operating_wrong_shape():
from py_wake.wind_turbines.power_ct_functions import PowerCtFunctionList, PowerCtTabular
d = np.load(os.path.dirname(examples.__file__) + "/data/time_series.npz")
wd, ws, ws_std = [d[k][:6 * 24] for k in ['wd', 'ws', 'ws_std']]
ws += 3
t = np.arange(6 * 24)
wt = V80()
site = Hornsrev1Site()
# replace powerCtFunction
wt.powerCtFunction = PowerCtFunctionList(
key='operating',
powerCtFunction_lst=[
PowerCtTabular(ws=[0, 100],
power=[0, 0],
power_unit='w',
ct=[0, 0]), # 0=No power and ct
wt.powerCtFunction
], # 1=Normal operation
default_value=1)
wfm = NOJ(site, wt)
x, y = site.initial_position.T
operating = (t < 48) | (t > 72)
with pytest.raises(
ValueError,
match=
r"Argument, operating\(shape=\(1, 144\)\), has unsupported shape."
):
wfm(x, y, ws=ws, wd=wd, time=t, operating=[operating])
def test_time_series_operating():
from py_wake.wind_turbines.power_ct_functions import PowerCtFunctionList, PowerCtTabular
d = np.load(os.path.dirname(examples.__file__) + "/data/time_series.npz")
wd, ws, ws_std = [d[k][:6 * 24] for k in ['wd', 'ws', 'ws_std']]
ws += 3
t = np.arange(6 * 24)
wt = V80()
site = Hornsrev1Site()
# replace powerCtFunction
wt.powerCtFunction = PowerCtFunctionList(
key='operating',
powerCtFunction_lst=[
PowerCtTabular(ws=[0, 100],
power=[0, 0],
power_unit='w',
ct=[0, 0]), # 0=No power and ct
wt.powerCtFunction
], # 1=Normal operation
default_value=1)
wfm = NOJ(site, wt)
x, y = site.initial_position.T
operating = (t < 48) | (t > 72)
sim_res = wfm(x, y, ws=ws, wd=wd, time=t, operating=operating)
npt.assert_array_equal(sim_res.operating[0], operating)
npt.assert_array_equal(sim_res.Power[:, operating == 0], 0)
npt.assert_array_equal(sim_res.Power[:, operating != 0] > 0, True)
operating = np.ones((80, 6 * 24))
operating[1] = (t < 48) | (t > 72)
sim_res = wfm(x, y, ws=ws, wd=wd, time=t, operating=operating)
npt.assert_array_equal(sim_res.operating, operating)
npt.assert_array_equal(sim_res.Power.values[operating == 0], 0)
npt.assert_array_equal(sim_res.Power.values[operating != 0] > 0, True)
def test_distance_over_rectangle():
x, y = [-100, 50], [200, -100]
windTurbines = IEA37_WindTurbines()
site = Rectangle(height=200, width=100, distance_resolution=100)
wf_model = NOJ(site, windTurbines)
sim_res = wf_model(x, y, wd=[270], ws=[9])
x_j = np.linspace(-100, 500, 100)
y_j = np.linspace(-200, 300, 100)
flow_map = sim_res.flow_map(HorizontalGrid(x_j, y_j))
Z = flow_map.WS_eff_xylk[:, :, 0, 0]
X, Y = flow_map.X, flow_map.Y
my = np.argmin(np.abs(Y[:, 0] - 200))
my2 = np.argmin(np.abs(Y[:, 0] + 100))
if 0:
import matplotlib.pyplot as plt
flow_map.plot_wake_map()
H = site.elevation(X, Y)
plt.plot(X[my], Z[my] * 10, label='wsp*10')
plt.plot(X[my2], Z[my2] * 10, label='wsp*10')
plt.contour(X, Y, H)
plt.plot(X[my, :50:4], Z[my, :50:4] * 10, '.')
plt.plot(x_j, site.elevation(x_j, x_j * 0), label='terrain level')
plt.legend()
plt.show()
ref = [
9., 3.42, 3.8, 6.02, 6.17, 6.31, 6.43, 7.29, 7.35, 7.41, 7.47, 7.53,
7.58
]
npt.assert_array_almost_equal(Z[my, :50:4], ref, 2)
def test_ti_map():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site,
windTurbines,
turbulenceModel=STF2017TurbulenceModel())
aep = AEPCalculator(wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.ti_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
m = 49, slice(100, 133, 2)
if 0:
print(np.round(Z[m], 2).tolist()) # ref
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z, np.arange(.075, .50, .001))
plt.colorbar(c)
windTurbines.plot(x, y)
plt.plot(X[m], Y[m], '.-r')
plt.show()
ref = [
0.48, 0.08, 0.08, 0.13, 0.16, 0.18, 0.19, 0.19, 0.2, 0.18, 0.17, 0.12,
0.13, 0.13, 0.13, 0.12, 0.12
]
npt.assert_array_almost_equal(Z[m], ref, 2)
def test_wake_model():
site = IEA37Site(16)
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site, windTurbines)
with pytest.raises(ValueError, match="Turbines 0 and 1 are at the same position"):
wake_model([0, 0], [0, 0], wd=np.arange(0, 360, 22.5), ws=[9.8])
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37._iea37 import IEA37Site
from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
from py_wake import NOJ
import matplotlib.pyplot as plt
# setup site, turbines and wakemodel
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wf_model = NOJ(site,
windTurbines,
turbulenceModel=GCLTurbulenceModel())
# calculate AEP
sim_res = wf_model(x, y)
print(sim_res.TI_eff_ilk.flatten())
# plot wake mape
aep = sim_res.aep()
flow_map = sim_res.flow_map(wd=0, ws=9.8)
flow_map.plot_ti_map()
plt.title('AEP: %.2f GWh' % aep)
plt.show()
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37 import iea37_path
from py_wake.examples.data.iea37._iea37 import IEA37Site
from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
from py_wake import NOJ
# setup site, turbines and flow model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = NOJ(site, windTurbines)
# calculate AEP
aep_calculator = AEPCalculator(wake_model)
aep = aep_calculator.calculate_AEP(x, y)[0].sum()
print(aep_calculator.WS_eff_ilk.shape)
# plot wake map
import matplotlib.pyplot as plt
aep_calculator.plot_wake_map(wt_x=x, wt_y=y, wd=[0], ws=[9])
plt.title('AEP: %.2f GWh' % aep)
windTurbines.plot(x, y)
plt.show()
def main():
if __name__ == '__main__':
site = ParqueFicticioSite()
windTurbines = IEA37_WindTurbines()
wf_model = NOJ(site, windTurbines)
x, y = site.initial_position.T
print(wf_model(x, y).aep)
def test_aep():
site = UniformSite([1], ti=0)
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site, windTurbines)
sim_res = wake_model([0], [0], wd=270)
npt.assert_almost_equal(sim_res.aep(), 3.35 * 24 * 365 / 360 / 1000)
npt.assert_almost_equal(sim_res.aep(normalize_probabilities=True),
3.35 * 24 * 365 / 1000)
def main():
if __name__ == '__main__':
import matplotlib.pyplot as plt
wt = HornsrevV80()
site = Hornsrev1Site()
wt.plot(wt_x, wt_y)
wf_model = NOJ(site, wt)
aep = wf_model(wt_x, wt_y).aep()
plt.title('AEP: %.1fGWh' % aep.sum())
plt.show()
def test_time_series_aep():
d = np.load(os.path.dirname(examples.__file__) + "/data/time_series.npz")
wd, ws = [d[k][::100] for k in ['wd', 'ws']]
wt = V80()
site = Hornsrev1Site()
x, y = site.initial_position.T
wfm = NOJ(site, wt)
sim_res = wfm(x, y, ws=ws, wd=wd, time=True, verbose=False)
npt.assert_allclose(sim_res.aep().sum(), 545, atol=1)
def test_aep_mixed_type():
site = UniformSite([1], ti=0)
wt = WindTurbines.from_WindTurbines(
[IEA37_WindTurbines(), IEA37_WindTurbines()])
wfm = NOJ(site, wt)
sim_res = wfm([0, 500], [0, 0], type=[0, 1], wd=270)
npt.assert_almost_equal(
sim_res.aep(with_wake_loss=False).sum(),
2 * wfm([0], [0], wd=270).aep(with_wake_loss=False).sum())
def test_aep_no_wake_loss_hornsrev():
wt = hornsrev1.V80()
x, y = hornsrev1.wt_x, hornsrev1.wt_y
site = UniformWeibullSite([1], [10], [2], .75)
site.default_ws = np.arange(3, 25)
aep = AEPCalculator(NOJ(site, wt))
aep_nowake = aep.calculate_AEP_no_wake_loss(x, y).sum()
npt.assert_almost_equal(aep_nowake / 80, 8.260757098)
cap_factor = aep.calculate_AEP(x, y).sum() / aep_nowake
# print(cap_factor)
npt.assert_almost_equal(cap_factor, 0.947175839142014)
def test_huge_flow_map(deflectionModel):
site = IEA37Site(16)
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site,
windTurbines,
deflectionModel=deflectionModel,
turbulenceModel=STF2005TurbulenceModel())
n_wt = 2
flow_map = wake_model(*site.initial_position[:n_wt].T,
wd=0).flow_map(HorizontalGrid(resolution=1000))
# check that deficit matrix > 10MB (i.e. it enters the memory saving loop)
assert (np.prod(flow_map.WS_eff_xylk.shape) * n_wt * 8 / 1024**2) > 10
assert flow_map.WS_eff_xylk.shape == (1000, 1000, 1, 1)
def test_time_series_override_WD():
d = np.load(os.path.dirname(examples.__file__) + "/data/time_series.npz")
wd, ws = [d[k][:6 * 24] for k in ['wd', 'ws']]
t = pd.date_range("2000-01-01", freq="10T", periods=24 * 6)
WD_it = (np.arange(80) / 100)[:, na] + wd[na]
wt = V80()
site = Hornsrev1Site()
x, y = site.initial_position.T
wfm = NOJ(site, wt)
sim_res = wfm(x, y, ws=ws, wd=wd, time=t, WD=WD_it, verbose=False)
npt.assert_array_equal(sim_res.WS, ws)
npt.assert_array_equal(sim_res.WD, WD_it)
npt.assert_array_equal(sim_res.time, t)
def test_DeprecatedWindTurbines():
for wts in [
V80Deprecated(),
WindTurbines(
names=['V80'],
diameters=[80],
hub_heights=[70],
ct_funcs=[
lambda ws: np.interp(ws, hornsrev1.ct_curve[:, 0],
hornsrev1.ct_curve[:, 1])
],
power_funcs=[
lambda ws: np.interp(ws, hornsrev1.power_curve[:, 0],
hornsrev1.power_curve[:, 1])
],
power_unit='w')
]:
types0 = [0] * 9
wfm = NOJ(Hornsrev1Site(), wts)
npt.assert_array_equal(wts.types(), [0])
npt.assert_almost_equal(wfm.aep(wt9_x, wt9_y, type=types0),
81.2066072392765)
def test_time_series_override_TI():
d = np.load(os.path.dirname(examples.__file__) + "/data/time_series.npz")
wd, ws, ws_std = [d[k][:6 * 24] for k in ['wd', 'ws', 'ws_std']]
ti = np.minimum(ws_std / ws, .5)
t = pd.date_range("2000-01-01", freq="10T", periods=24 * 6)
wt = V80()
site = Hornsrev1Site()
x, y = site.initial_position.T
wfm = NOJ(site, wt)
sim_res = wfm(x, y, ws=ws, wd=wd, time=t, TI=ti, verbose=False)
npt.assert_array_equal(sim_res.WS, ws)
npt.assert_array_equal(sim_res.WD, wd)
npt.assert_array_equal(sim_res.time, t)
npt.assert_array_equal(sim_res.TI[0], ti)
def test_NOJ_Nibe_result_wake_map():
# Replicate result from: Jensen, Niels Otto. "A note on wind generator interaction." (1983).
def ct_func(_):
return 8 / 9
def power_func(*_):
return 0
windTurbines = NibeA0
site = UniformSite([1], 0.1)
wake_model = NOJ(site, windTurbines)
sim_res = wake_model(x=[0], y=[0], wd=[0], ws=[8.1])
WS_eff_xy = sim_res.flow_map(HorizontalGrid(
x=[0], y=[0, -40, -100], h=50)).WS_eff_xylk.mean(['wd', 'ws'])
npt.assert_array_almost_equal(WS_eff_xy[:, 0], [8.1, 4.35, 5.7])
def test_time_series_values():
wt = V80()
site = Hornsrev1Site()
x, y = site.initial_position.T
wfm = NOJ(site, wt)
wd = np.arange(350, 360)
ws = np.arange(5, 10)
wd_t, ws_t = [v.flatten() for v in np.meshgrid(wd, ws)]
sim_res_t = wfm(x, y, ws=ws_t, wd=wd_t, time=True, verbose=False)
sim_res = wfm(x, y, wd=wd, ws=ws)
for k in ['WS_eff', 'TI_eff', 'Power', 'CT']:
npt.assert_array_equal(
np.moveaxis(sim_res_t[k].values.reshape((80, 5, 10)), 1, 2),
sim_res[k].values)
def test_two_wt_aep():
site = Hornsrev1Site()
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site, windTurbines)
sim_res1 = wake_model([0], [0], wd=270)
sim_res2 = wake_model([0, 0], [0, 500], wd=270)
# one wt, wind from west ~ 5845 hours of full load
npt.assert_almost_equal(sim_res1.aep(normalize_probabilities=True).sum(), 3.35 * 5.845, 2)
# No wake, two wt = 2 x one wt
npt.assert_almost_equal(sim_res1.aep().sum() * 2, sim_res2.aep().sum())
# same for normalized propabilities
npt.assert_almost_equal(sim_res1.aep(normalize_probabilities=True).sum() * 2,
sim_res2.aep(normalize_probabilities=True).sum())
def test_stf(turbulence_model, ref_ti):
# setup site, turbines and wind farm model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
for wake_model in [
NOJ(site, windTurbines, turbulenceModel=turbulence_model),
All2AllIterative(site,
windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum(),
turbulenceModel=turbulence_model)
]:
res = wake_model(x, y)
# print(np.round(res.TI_eff_ilk[:, 0, 0], 3).tolist())
npt.assert_array_almost_equal(res.TI_eff_ilk[:, 0, 0], ref_ti, 3)
def test_models_with_noj(turbulence_model, ref_ti):
# setup site, turbines and wind farm model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
for wake_model in [NOJ(site, windTurbines, turbulenceModel=turbulence_model),
All2AllIterative(site, windTurbines,
wake_deficitModel=NOJDeficit(),
superpositionModel=SquaredSum(),
turbulenceModel=turbulence_model),
]:
res = wake_model(x, y)
# print(turbulence_model.__class__.__name__, np.round(res.TI_eff_ilk[:, 0, 0], 3).tolist())
if 0:
res.flow_map(wd=0).plot_ti_map()
plt.show()
npt.assert_array_almost_equal(res.TI_eff_ilk[:, 0, 0], ref_ti, 3)
def test_wake_map():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = NOJ(site, windTurbines)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
flow_map = wake_model(x, y, wd=[0],
ws=[9]).flow_map(HorizontalGrid(x_j, y_j, 110))
Z = flow_map.WS_eff_xylk.mean((2, 3))
if 0:
flow_map.plot_wake_map()
plt.show()
ref = [
3.27, 3.27, 9.0, 7.46, 7.46, 7.46, 7.46, 7.31, 7.31, 7.31, 7.31, 8.3,
8.3, 8.3, 8.3, 8.3, 8.3
]
npt.assert_array_almost_equal(Z[49, 100:133:2], ref, 2)