def test_own_deficit_is_zero():
for deficitModel in get_models(WakeDeficitModel):
site = Hornsrev1Site()
windTurbines = IEA37_WindTurbines()
wf_model = All2AllIterative(site,
windTurbines,
wake_deficitModel=deficitModel(),
turbulenceModel=STF2017TurbulenceModel())
sim_res = wf_model([0], [0])
npt.assert_array_equal(sim_res.WS_eff,
sim_res.WS.broadcast_like(sim_res.WS_eff))
def test_with_all_deficit_models(WFM):
site = IEA37Site(16)
windTurbines = IEA37_WindTurbines()
for deficitModel in get_models(WakeDeficitModel):
wfm = WFM(site, windTurbines, wake_deficitModel=deficitModel(),
rotorAvgModel=RotorCenter(),
superpositionModel=LinearSum(),
deflectionModel=None, turbulenceModel=STF2017TurbulenceModel())
wfm2 = WFM(site, windTurbines, wake_deficitModel=deficitModel(),
rotorAvgModel=EqGridRotorAvg(1),
superpositionModel=LinearSum(),
deflectionModel=None, turbulenceModel=STF2017TurbulenceModel())
kwargs = {'x': [0, 0, 500, 500], 'y': [0, 500, 0, 500], 'wd': [0], 'ws': [8]}
npt.assert_equal(wfm.aep(**kwargs), wfm2.aep(**kwargs))
def test_get_models():
assert cls_in(FugaDeficit, get_models(BlockageDeficitModel))
assert cls_in(SelfSimilarityDeficit, get_models(BlockageDeficitModel))
assert [n.__name__ for n in get_models(SuperpositionModel)
] == ['LinearSum', 'SquaredSum', 'MaxSum', 'WeightedSum']
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
min_WS_line = fm.min_WS_eff()
if 0:
plt.figure(figsize=(14, 3))
fm.plot_wake_map()
min_WS_line.plot()
plt.plot(10 * D, dy10d * D, '.', label="Ref, 10D")
plt.legend()
plt.show()
npt.assert_almost_equal(min_WS_line.interp(x=10 * D).item() / D, dy10d)
@pytest.mark.parametrize(
'deflectionModel',
[m for m in get_models(DeflectionModel) if m is not None])
def test_plot_deflection_grid(deflectionModel):
site = IEA37Site(16)
x, y = [0], [0]
windTurbines = V80()
D = windTurbines.diameter()
wfm = IEA37SimpleBastankhahGaussian(site,
windTurbines,
deflectionModel=deflectionModel())
yaw_ilk = np.reshape([-30], (1, 1, 1))
sim_res = wfm(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10)
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
plt.figure(figsize=(14, 3))
sim_res = wfm(x, y, yaw=yaw_ilk, wd=270, ws=10)
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
min_WS_line = fm.min_WS_eff()
if 0:
plt.figure(figsize=(14, 3))
fm.plot_wake_map()
min_WS_line.plot()
plt.plot(10 * D, dy10d * D, '.', label="Ref, 10D")
plt.legend()
plt.show()
npt.assert_almost_equal(min_WS_line.interp(x=10 * D).item() / D, dy10d)
@pytest.mark.parametrize('deflectionModel', [m for m in get_models(DeflectionModel) if m is not None])
def test_plot_deflection_grid(deflectionModel):
site = IEA37Site(16)
x, y = [0], [0]
windTurbines = V80()
D = windTurbines.diameter()
wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=deflectionModel())
yaw_ilk = np.reshape([-30], (1, 1, 1))
sim_res = wfm(x, y, yaw=yaw_ilk, wd=270, ws=10)
fm = sim_res.flow_map(XYGrid(x=np.arange(-D, 10 * D + 10, 10)))
plt.figure(figsize=(14, 3))
fm.plot_wake_map()
fm.plot_deflection_grid()