def __init__(self,
f=[
3.597152, 3.948682, 5.167395, 7.000154, 8.364547, 6.43485,
8.643194, 11.77051, 15.15757, 14.73792, 10.01205, 5.165975
],
mean_wsp=8):
UniformSite.__init__(self, p_wd=f, ti=0.1, ws=mean_wsp)
def test_uniform_site_probability():
"""check that the uniform site recovers probability"""
p_wd = np.array([0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1])
wd_l = np.linspace(0, 360, p_wd.size, endpoint=False)
ws_k = np.array([12])
site = UniformSite(p_wd, ti=1)
actual = site.probability(0, 0, 0, wd_l[na, :, na], ws_k[na, na], 360 / p_wd.size, None)
npt.assert_array_almost_equal(actual.squeeze(), p_wd)
def __init__(self, n_wt, ti=.075, shear=None):
assert n_wt in [9, 16, 36, 64]
from py_wake.examples.data.iea37.iea37_reader import \
read_iea37_windfarm, read_iea37_windrose
_, wsp, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
UniformSite.__init__(self, freq, ti, ws=wsp, shear=shear)
self.initial_position = np.array(read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)[:2]).T
def test_smart_start_aep_map_PyWakeAEP():
site = IEA37Site(16)
n_wt = 4
x, y = site.initial_position[:n_wt].T
wd_lst = np.arange(0, 360, 45)
ws_lst = [10]
turbines = hornsrev1.HornsrevV80()
site = UniformSite([1], .75)
site.default_ws = ws_lst
site.default_wd = wd_lst
aep = PyWakeAEP(wake_model=NOJ(site, turbines))
aep_1wt = aep.calculate_AEP([0], [0]).sum()
tf = TopFarmProblem(design_vars={
'x': x,
'y': y
},
cost_comp=aep.get_TopFarm_cost_component(n_wt),
driver=EasyScipyOptimizeDriver(),
constraints=[
SpacingConstraint(160),
CircleBoundaryConstraint((0, 0), 500)
])
x = np.arange(-500, 500, 10)
y = np.arange(-500, 500, 10)
XX, YY = np.meshgrid(x, y)
tf.smart_start(XX,
YY,
aep.get_aep4smart_start(wd=wd_lst, ws=ws_lst),
radius=40,
seed=1)
tf.evaluate()
if 0:
wt_x, wt_y = tf['x'], tf['y']
for i, _ in enumerate(wt_x, 1):
print(aep.calculate_AEP(wt_x[:i], wt_y[:i]).sum((1, 2)))
X_j, Y_j, aep_map = aep.aep_map(x,
y,
0,
wt_x,
wt_y,
ws=ws_lst,
wd=wd_lst)
print(tf.evaluate())
import matplotlib.pyplot as plt
c = plt.contourf(X_j, Y_j, aep_map, 100)
plt.colorbar(c)
plt.plot(wt_x, wt_y, '2r')
for c in tf.model.constraint_components:
c.plot()
plt.axis('equal')
plt.show()
npt.assert_almost_equal(aep_1wt * n_wt, tf['AEP'], 5)
def test_uniform_site_probability():
"""check that the uniform site recovers probability"""
p_wd = np.array([0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1])
site = UniformSite(p_wd, ti=1)
lw = site.local_wind(0,
0,
0,
wd=np.linspace(0, 360, p_wd.size, endpoint=False),
ws=12)
npt.assert_array_almost_equal(lw.P, p_wd)
def test_NOJ_Nibe_result():
# Replicate result from: Jensen, Niels Otto. "A note on wind generator interaction." (1983).
wake_model = NOJ(NibeA0)
WS_ilk = np.array([[[8.1]], [[8.1]], [[8.1]]])
TI_ilk = np.zeros_like(WS_ilk)
site = UniformSite([1], 0.1)
dw_iil, cw_iil, dh_iil, dw_order_indices_l = site.wt2wt_distances(
x_i=[0, 0, 0], y_i=[0, -40, -100], h_i=[50, 50, 50], wd_il=[[0]])
WS_eff_ilk = wake_model.calc_wake(WS_ilk, TI_ilk, dw_iil, cw_iil, dh_iil, dw_order_indices_l, [0, 1, 1])[0]
npt.assert_array_almost_equal(WS_eff_ilk[:, 0, 0], [8.1, 4.35, 5.7])
def __init__(self, n_wt, ti=.75):
assert n_wt in [16, 36, 64]
from py_wake.examples.data.iea37.iea37_reader import read_iea37_windfarm,\
read_iea37_windrose
_, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
self.initial_position = np.array(
read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)[:2]).T
UniformSite.__init__(self, freq, ti)
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
wake_model = NOJ(windTurbines)
WS_ilk = np.array([[[8.1]], [[8.1]], [[8.1]]])
TI_ilk = np.zeros_like(WS_ilk)
site = UniformSite([1], 0.1)
dw_iil, cw_iil, dh_iil, dw_order_indices_l = site.wt2wt_distances(x_i=x, y_i=y, h_i=[50, 50, 50], wd_il=[[wdir]])
WS_eff_ilk = wake_model.calc_wake(WS_ilk, TI_ilk, dw_iil, cw_iil, dh_iil, dw_order_indices_l, [0, 0, 0])[0]
ws_wt3 = 8.1 - np.sqrt((8.1 * 2 / 3 * (20 / 26)**2)**2 + (8.1 * 2 / 3 * (20 / 30)**2)**2)
npt.assert_array_almost_equal(WS_eff_ilk[:, 0, 0], [8.1, 4.35, ws_wt3])
def test_smart_start_aep_map(seed, radius, resolution, tol):
site = IEA37Site(16)
n_wt = 4
x, y = site.initial_position[:n_wt].T
wd_lst = np.arange(0, 360, 45)
ws_lst = [10]
turbines = hornsrev1.HornsrevV80()
site = UniformSite([1], .75)
site.default_ws = ws_lst
site.default_wd = wd_lst
wfm = NOJ(site, turbines)
aep_comp = PyWakeAEPCostModelComponent(wfm, n_wt=n_wt)
aep_1wt = wfm([0], [0]).aep().sum()
tf = TopFarmProblem(design_vars={
'x': x,
'y': y
},
cost_comp=aep_comp,
driver=EasyScipyOptimizeDriver(),
constraints=[
SpacingConstraint(160),
CircleBoundaryConstraint((0, 0), radius)
])
x = np.arange(-radius, radius, resolution)
y = np.arange(-radius, radius, resolution)
XX, YY = np.meshgrid(x, y)
tf.smart_start(XX,
YY,
aep_comp.get_aep4smart_start(wd=wd_lst, ws=ws_lst),
radius=40,
plot=0,
seed=seed)
tf.evaluate()
if 0:
wt_x, wt_y = tf['x'], tf['y']
for i, _ in enumerate(wt_x, 1):
print(wfm(wt_x[:i], wt_y[:i]).aep().sum(['wd', 'ws']))
aep_comp.windFarmModel(wt_x, wt_y, ws=ws_lst,
wd=wd_lst).flow_map().aep_xy().plot()
print(tf.evaluate())
import matplotlib.pyplot as plt
plt.plot(wt_x, wt_y, '2r')
for c in tf.model.constraint_components:
c.plot()
plt.axis('equal')
plt.show()
npt.assert_almost_equal(aep_1wt * n_wt, tf['AEP'], tol)
def from_case_dict(name, case_dict):
site = UniformSite(p_wd=[1],
ti=case_dict['TItot'] / 0.8,
ws=case_dict['U0'])
site.default_wd = np.linspace(-30, 30, 61) % 360
windTurbines = WindTurbine(name="",
diameter=case_dict['D'],
hub_height=case_dict['zH'],
powerCtFunction=PowerCtFunction(
input_keys=['ws'],
power_ct_func=lambda ws, run_only, ct=case_dict['CT']: ws * 0 + ct,
power_unit='w'))
xD = case_dict['xDown']
x = xD * case_dict['sDown']
return SingleWakeValidationCase(name, site, windTurbines, xD, x)
def from_case_dict(name, case_dict):
site = UniformSite(p_wd=[1],
ti=case_dict['TItot'] / 0.8,
ws=case_dict['U0'])
site.default_wd = np.linspace(-30, 30, 61) % 360
windTurbines = OneTypeWindTurbines(
name="",
diameter=case_dict['D'],
hub_height=case_dict['zH'],
ct_func=lambda ws, ct=case_dict['CT']: ws * 0 + ct,
power_func=lambda ws: ws * 0 + 1,
power_unit='W')
xD = case_dict['xDown']
x = xD * case_dict['sDown']
return SingleWakeValidationCase(name, site, windTurbines, xD, x)
def test_Mirror_flow_map(wfm_cls, groundModel, superpositionModel):
site = UniformSite([1], ti=0.1)
wt = V80()
wfm = NOJ(site, wt, k=.5, superpositionModel=superpositionModel)
fm_ref = wfm([0, 0 + 1e-20], [0, 0 + 1e-20], wd=0, h=[50, -50]).flow_map(
YZGrid(x=0, y=np.arange(-100, 100, 1) + .1, z=np.arange(1, 100)))
fm_ref.plot_wake_map()
plt.title("Underground WT added manually")
plt.figure()
wfm = wfm_cls(site,
wt,
NOJDeficit(k=.5),
groundModel=groundModel,
superpositionModel=superpositionModel)
fm_res = wfm([0], [0], wd=0, h=[50]).flow_map(
YZGrid(x=0, y=np.arange(-100, 100, 1) + .1, z=np.arange(1, 100)))
fm_res.plot_wake_map()
plt.title("With Mirror GroundModel")
if 0:
plt.show()
plt.close()
npt.assert_array_equal(fm_ref.WS_eff, fm_res.WS_eff)
def test_Mirror(wfm_cls):
# Compare points in flow map with ws of WT at same position. All2Alliterative failing with NOJ and WT.diameter=0
# and therefore this cannot be tested above
site = UniformSite([1], ti=0.1)
wt = V80()
wfm = wfm_cls(site,
wt,
ZongGaussianDeficit(a=[0, 1]),
turbulenceModel=STF2017TurbulenceModel(),
groundModel=Mirror())
sim_res = wfm(
[0],
[0],
h=[50],
wd=0,
)
fm_ref = sim_res.flow_map(YZGrid(x=0, y=np.arange(-70, 0, 20), z=10))
ref = fm_ref.WS_eff_xylk[:, 0, 0, 0].values
res = np.array([
wfm([0, 0], [0, y], [50, 10], wd=0).WS_eff.sel(wt=1).item()
for y in fm_ref.X[0]
])
if 0:
fm_res = sim_res.flow_map(YZGrid(x=0, y=np.arange(-100, 10, 1)))
fm_res.plot_wake_map()
plt.plot(fm_ref.X[0], fm_ref.Y[0], '.')
plt.plot(fm_ref.X[0], ref * 10, label='ref, WS*10')
plt.plot(fm_ref.X[0], res * 10, label='Res, WS*10')
plt.legend()
plt.show()
plt.close()
npt.assert_array_equal(res, ref)
def test_Mirror_NOJ():
# Compare points in flow map with ws of WT at same position
site = UniformSite([1], ti=0.1)
V80_D0 = V80()
V80_D0._diameters = [0]
wt = WindTurbines.from_WindTurbines([V80(), V80_D0])
wfm = NOJ(site, wt, k=.5, groundModel=Mirror())
sim_res = wfm([0], [0], h=[50], wd=0)
fm_ref = sim_res.flow_map(YZGrid(x=0, y=np.arange(-70, 0, 20), z=10))
ref = fm_ref.WS_eff_xylk[:, 0, 0, 0].values
res = np.array([
wfm([0, 0], [0, y], [50, 10], type=[0, 1],
wd=0).WS_eff.sel(wt=1).item() for y in fm_ref.X[0]
])
if 0:
fm_res = sim_res.flow_map(YZGrid(x=0, y=np.arange(-100, 10, 1)))
fm_res.plot_wake_map()
plt.plot(fm_ref.X[0], fm_ref.Y[0], '.')
plt.plot(fm_ref.X[0], ref * 10, label='ref, WS*10')
plt.plot(fm_ref.X[0], res * 10, label='Res, WS*10')
plt.legend()
plt.show()
plt.close()
npt.assert_array_equal(res, ref)
def local_wind(self, x_i=None, y_i=None, h_i=None, wd=None,
ws=None, time=False, wd_bin_size=None, ws_bins=None):
lw = UniformSite.local_wind(self, x_i=x_i, y_i=y_i, h_i=h_i, wd=wd, ws=ws,
wd_bin_size=wd_bin_size, ws_bins=ws_bins)
lw['TI'] = xr.DataArray(lw.TI_ilk + np.arange(len(x_i))[:, np.newaxis, np.newaxis] * .1,
[('wt', [0, 1, 2]), ('wd', np.atleast_1d(wd)), ('ws', np.atleast_1d(ws))])
return lw
def test_interpolation():
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
plot = 0
if plot:
ax1 = plt.gca()
ax2 = plt.twinx()
for wdm, n_d_values in (
(FugaDeficit(path, method='linear'), 4),
(FugaDeficit(path, method='spline'), 20),
(FugaYawDeficit(path, method='linear'), 4),
(FugaYawDeficit(path, method='spline'), 20),
):
wfm = PropagateDownwind(site, wts, wdm)
sim_res = wfm(x=[0], y=[0], wd=[270], ws=[10], yaw=[[[10]]])
fm = sim_res.flow_map(XYGrid(x=[200], y=np.arange(-10, 11)))
fm = sim_res.flow_map(
XYGrid(x=np.arange(-100, 800, 10), y=np.arange(-10, 11)))
# linear has 4 line segments with same gradient, while spline has 20 different gradient values
npt.assert_equal(
len(np.unique(np.round(np.diff(fm.WS_eff.sel(x=500).squeeze()),
6))), n_d_values)
if plot:
ax1.plot(fm.y, fm.WS_eff.sel(x=500).squeeze())
ax2.plot(fm.y[:-1], np.diff(fm.WS_eff.sel(x=500).squeeze()), '--')
if plot:
plt.show()
plt.close('all')
def test_fuga_downwind():
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wfm_UL = Fuga(path, site, wts)
wfm_ULT = PropagateDownwind(site, wts, FugaYawDeficit(path))
(ax1, ax2), (ax3, ax4) = plt.subplots(2, 2)[1]
def plot(wfm, yaw, ax, min_ws):
levels = np.arange(6.5, 10.5, .5)
sim_res = wfm([0], [0], wd=270, ws=10, yaw=[[[yaw]]])
fm = sim_res.flow_map(XYGrid(x=np.arange(-100, 500, 5)))
npt.assert_almost_equal(fm.WS_eff.min(), min_ws)
fm.plot_wake_map(ax=ax, levels=levels)
fm.min_WS_eff(fm.x, 70).plot(ax=ax, color='r')
plt.axhline(0, color='k')
plot(wfm_UL, 0, ax1, 7.15853738)
plot(wfm_UL, 30, ax2, 7.83219266)
plot(wfm_ULT, 0, ax3, 7.15853738)
plot(wfm_ULT, 30, ax4, 8.12261872)
if 0:
plt.show()
plt.close('all')
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37 import iea37_path
from py_wake.examples.data.iea37.iea37_reader import read_iea37_windfarm,\
read_iea37_windrose
from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
from py_wake.site._site import UniformSite
from py_wake.aep_calculator import AEPCalculator
class MyWakeModel(SquaredSum, WakeModel):
args4deficit = ['WS_lk', 'dw_jl']
def calc_deficit(self, WS_lk, dw_jl):
# 10% deficit downstream
return (WS_lk * .1)[na] * (dw_jl > 0)[:, :, na]
_, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
n_wt = 16
x, y, _ = read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)
site = UniformSite(freq, ti=0.75)
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = MyWakeModel(windTurbines)
aep_calculator = AEPCalculator(site, windTurbines, wake_model)
import matplotlib.pyplot as plt
aep_calculator.plot_wake_map(wt_x=x,
wt_y=y,
wd=[0, 30],
ws=[9],
levels=np.linspace(5, 9, 100))
windTurbines.plot(x, y)
plt.show()
def test_fuga_downwind_vs_notebook():
powerCtFunction = PowerCtTabular([0, 100], [0, 0], 'w',
[0.850877, 0.850877])
wt = WindTurbine(name='',
diameter=80,
hub_height=70,
powerCtFunction=powerCtFunction)
path = tfp + 'fuga/2MW/Z0=0.00001000Zi=00400Zeta0=0.00E+00'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wfm_ULT = PropagateDownwind(site, wt, FugaYawDeficit(path))
WS = 10
p = Path(tfp) / "fuga/v80_wake_4d_y_no_deflection.csv"
y, notebook_deficit_4d = np.array(
[v.split(",") for v in p.read_text().strip().split("\n")],
dtype=float).T
sim_res = wfm_ULT([0], [0], wd=270, ws=WS, yaw=[[[17.4493]]])
fm = sim_res.flow_map(XYGrid(4 * wt.diameter(), y=y))
npt.assert_allclose(fm.WS_eff.squeeze() - WS,
notebook_deficit_4d,
atol=1e-6)
if 0:
plt.plot(y, notebook_deficit_4d, label='Notebook deficit 4d')
plt.plot(y, fm.WS_eff.squeeze() - WS)
plt.show()
plt.close('all')
def test_wake_model():
_, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
site = UniformSite(freq, ti=0.75)
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = NOJ(windTurbines)
aep = AEPCalculator(site, windTurbines, wake_model)
with pytest.raises(ValueError, match="Turbines 0 and 1 are at the same position"):
aep.calculate_AEP([0, 0], [0, 0], wd=np.arange(0, 360, 22.5), ws=[9.8])
def test_fuga():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'
site = UniformSite([1, 0, 0, 0], ti=0.75)
wake_model = Fuga(path, wts)
aep = AEPCalculator(site, wts, wake_model)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
_, _, Z70 = aep.wake_map(x_j,
y_j,
70,
wt_x,
wt_y,
wt_height=70,
wd=[30],
ws=[10])
X, Y, Z73 = aep.wake_map(x_j,
y_j,
73,
wt_x,
wt_y,
wt_height=70,
wd=[30],
ws=[10])
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z70, np.arange(6, 10.5, .1))
plt.colorbar(c)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
plt.plot(X[0], Z70[140, :], label="Z=70m")
plt.plot(X[0], Z73[140, :], label="Z=73m")
plt.plot(X[0, 100:400:10], Z70[140, 100:400:10], '.')
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z70[140, 100:400:10], [
10.0547, 10.0519, 10.0718, 10.0093, 9.6786, 7.8589, 6.8539, 9.2199,
9.9837, 10.036, 10.0796, 10.0469, 10.0439, 9.1866, 7.2552, 9.1518,
10.0449, 10.0261, 10.0353, 9.9256, 9.319, 8.0062, 6.789, 8.3578,
9.9393, 10.0332, 10.0191, 10.0186, 10.0191, 10.0139
], 4)
npt.assert_array_almost_equal(Z73[140, 100:400:10], [
10.0542, 10.0514, 10.0706, 10.0075, 9.6778, 7.9006, 6.9218, 9.228,
9.9808, 10.0354, 10.0786, 10.0464, 10.0414, 9.1973, 7.3099, 9.1629,
10.0432, 10.0257, 10.0344, 9.9236, 9.3274, 8.0502, 6.8512, 8.3813,
9.9379, 10.0325, 10.0188, 10.0183, 10.019, 10.0138
], 4)
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_fuga_new_format():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.00014617Zi=00399Zeta0=0.00E+0/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wake_model = Fuga(path, site, wts)
res = wake_model(x=wt_x, y=wt_y, wd=[30], ws=[10])
npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(), [
10.00725165, 10., 7.92176401, 10.02054952, 9.40501317, 7.92609363,
7.52384558
], 8)
npt.assert_array_almost_equal(res.ct_ilk.flatten(), [
0.79260841, 0.793, 0.80592176, 0.79189033, 0.80132982, 0.80592609,
0.80552385
], 8)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
wake_model = Fuga(path, site, wts)
sim_res = wake_model(wt_x, wt_y, wd=[30], ws=[10])
flow_map70 = sim_res.flow_map(HorizontalGrid(x_j, y_j, h=70))
flow_map73 = sim_res.flow_map(HorizontalGrid(x_j, y_j, h=73))
X, Y = flow_map70.XY
Z70 = flow_map70.WS_eff_xylk[:, :, 0, 0]
Z73 = flow_map73.WS_eff_xylk[:, :, 0, 0]
if 0:
flow_map70.plot_wake_map(levels=np.arange(6, 10.5, .1))
plt.plot(X[0], Y[140])
plt.figure()
plt.plot(X[0], Z70[140, :], label="Z=70m")
plt.plot(X[0], Z73[140, :], label="Z=73m")
plt.plot(X[0, 100:400:10], Z70[140, 100:400:10], '.')
print(list(np.round(Z70.values[140, 100:400:10], 4)))
print(list(np.round(Z73.values[140, 100:400:10], 4)))
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z70[140, 100:400:10], [
10.0458, 10.0309, 10.065, 10.0374, 9.7865, 7.7119, 6.4956, 9.2753,
10.0047, 10.0689, 10.0444, 10.0752, 10.0699, 9.1852, 6.9783, 9.152,
10.0707, 10.0477, 10.0365, 9.9884, 9.2867, 7.5714, 6.4451, 8.3276,
9.9976, 10.0251, 10.0264, 10.023, 10.0154, 9.9996
], 4)
npt.assert_array_almost_equal(Z73[140, 100:400:10], [
10.0458, 10.0309, 10.065, 10.0374, 9.7865, 7.7119, 6.4956, 9.2753,
10.0047, 10.0689, 10.0444, 10.0752, 10.0699, 9.1852, 6.9783, 9.152,
10.0707, 10.0477, 10.0365, 9.9884, 9.2867, 7.5714, 6.4451, 8.3276,
9.9976, 10.0251, 10.0264, 10.023, 10.0154, 9.9996
], 4)
def test_fuga_new_format():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.00408599Zi=00400Zeta0=0.00E+00/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wake_model = Fuga(path, site, wts)
res = wake_model(x=wt_x, y=wt_y, wd=[30], ws=[10])
npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(), [
10.00647891, 10., 8.21713928, 10.03038884, 9.36889964, 8.23084088,
7.80662141
], 8)
npt.assert_array_almost_equal(res.ct_ilk.flatten(), [
0.79265014, 0.793, 0.80621714, 0.791359, 0.80183541, 0.80623084,
0.80580662
], 8)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
wake_model = Fuga(path, site, wts)
sim_res = wake_model(wt_x, wt_y, wd=[30], ws=[10])
flow_map70 = sim_res.flow_map(HorizontalGrid(x_j, y_j, h=70))
flow_map73 = sim_res.flow_map(HorizontalGrid(x_j, y_j, h=73))
X, Y = flow_map70.XY
Z70 = flow_map70.WS_eff_xylk[:, :, 0, 0]
Z73 = flow_map73.WS_eff_xylk[:, :, 0, 0]
if 0:
flow_map70.plot_wake_map(levels=np.arange(6, 10.5, .1))
plt.plot(X[0], Y[140])
plt.figure()
plt.plot(X[0], Z70[140, :], label="Z=70m")
plt.plot(X[0], Z73[140, :], label="Z=73m")
plt.plot(X[0, 100:400:10], Z70[140, 100:400:10], '.')
print(list(np.round(Z70.values[140, 100:400:10], 4)))
print(list(np.round(Z73.values[140, 100:400:10], 4)))
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z70[140, 100:400:10], [
10.0384, 10.042, 10.044, 10.0253, 9.7194, 7.7561, 6.7421, 9.2308,
9.9894, 10.0413, 10.0499, 10.0579, 10.0437, 9.1626, 7.2334, 9.1208,
10.0396, 10.0322, 10.0276, 9.9504, 9.2861, 7.8375, 6.6608, 8.3343,
9.9756, 10.0229, 10.0136, 10.0142, 10.0118, 10.0094
], 4)
npt.assert_array_almost_equal(Z73[140, 100:400:10], [
10.0384, 10.042, 10.044, 10.0253, 9.7194, 7.7561, 6.7421, 9.2308,
9.9894, 10.0413, 10.0499, 10.0579, 10.0437, 9.1626, 7.2334, 9.1208,
10.0396, 10.0322, 10.0276, 9.9504, 9.2861, 7.8375, 6.6608, 8.3343,
9.9756, 10.0229, 10.0136, 10.0142, 10.0118, 10.0094
], 4)
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 test_wec():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
site = UniformSite([1, 0, 0, 0], ti=0.075)
wake_model = Fuga(LUT_path_2MW_z0_0_03, site, wts)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
flow_map_wec1 = wake_model(wt_x, wt_y, 70, wd=[30],
ws=[10]).flow_map(HorizontalGrid(x_j, y_j))
Z_wec1 = flow_map_wec1.WS_eff_xylk[:, :, 0, 0]
wake_model.wec = 2
flow_map_wec2 = wake_model(wt_x, wt_y, 70, wd=[30],
ws=[10]).flow_map(HorizontalGrid(x_j, y_j))
X, Y = flow_map_wec1.XY
Z_wec2 = flow_map_wec2.WS_eff_xylk[:, :, 0, 0]
if 0:
print(list(np.round(Z_wec1[140, 100:400:10].values, 4)))
print(list(np.round(Z_wec2[140, 100:400:10].values, 4)))
flow_map_wec1.plot_wake_map(levels=np.arange(6, 10.5, .1),
plot_colorbar=False)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
c = flow_map_wec2.plot_wake_map(levels=np.arange(6, 10.5, .1),
plot_colorbar=False)
plt.colorbar(c)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
plt.plot(X[0], Z_wec1[140, :], label="Z=70m")
plt.plot(X[0], Z_wec2[140, :], label="Z=70m")
plt.plot(X[0, 100:400:10], Z_wec1[140, 100:400:10], '.')
plt.plot(X[0, 100:400:10], Z_wec2[140, 100:400:10], '.')
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z_wec1[140, 100:400:10], [
10.0467, 10.0473, 10.0699, 10.0093, 9.6786, 7.8589, 6.8539, 9.2199,
9.9837, 10.036, 10.0796, 10.0469, 10.0439, 9.1866, 7.2552, 9.1518,
10.0449, 10.0261, 10.0353, 9.9256, 9.319, 8.0062, 6.789, 8.3578,
9.9393, 10.0332, 10.0183, 10.0186, 10.0191, 10.0139
], 4)
npt.assert_array_almost_equal(Z_wec2[140, 100:400:10], [
10.0297, 9.9626, 9.7579, 9.2434, 8.2318, 7.008, 6.7039, 7.7303, 9.0101,
9.6877, 9.9068, 9.7497, 9.1127, 7.9505, 7.26, 7.9551, 9.2104, 9.7458,
9.6637, 9.1425, 8.2403, 7.1034, 6.5109, 7.2764, 8.7653, 9.7139, 9.9718,
10.01, 10.0252, 10.0357
], 4)
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_wake(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 cmp_fuga_with_colonel():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
xy, Z = [
v for _, v in np.load(tfp + "fuga/U_XY_70m_.txt_30deg.npz").items()
]
x_min, x_max, x_step, y_min, y_max, y_step = xy
x_j = np.arange(
x_min,
np.round((x_max - x_min) / x_step) * x_step + x_min + x_step, x_step)
y_j = np.arange(
y_min,
np.round((y_max - y_min) / y_step) * y_step + y_min + y_step, y_step)
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'
site = UniformSite([1, 0, 0, 0], ti=0.75)
wake_model = Fuga(path, wts)
aep = AEPCalculator(site, wts, wake_model)
X, Y, Z2 = aep.wake_map(x_j, y_j, 70, wt_x, wt_y, h_i=70, wd=[30], ws=[10])
print(x_j)
print(y_j)
m = (X == 500) & (Y == -880)
print(Z[m])
print(Z2[m])
if 1:
import matplotlib.pyplot as plt
plt.clf()
c = plt.contourf(X, Y, Z, np.arange(6, 10.5, .1))
plt.colorbar(c, label="m/s")
plt.axis('equal')
plt.tight_layout()
wts.plot(wt_x, wt_y)
plt.figure()
c = plt.contourf(X, Y, Z2, np.arange(6, 10.5, .1))
plt.colorbar(c)
wts.plot(wt_x, wt_y)
plt.figure()
c = plt.contourf(X, Y, Z2 - Z, np.arange(-.01, .01, .001))
plt.colorbar(c, label="m/s")
wts.plot(wt_x, wt_y)
plt.show()
npt.assert_array_almost_equal(Z, Z2, 2)
def test_wec():
# move turbine 1 600 300
wt_x = [-250, 600, -500, 0, 500, -250, 250]
wt_y = [433, 300, 0, 0, 0, -433, -433]
wts = HornsrevV80()
site = UniformSite([1, 0, 0, 0], ti=0.075)
wfm = BastankhahGaussian(site, wts)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
flow_map_wec1 = wfm(wt_x, wt_y, 70, wd=[30],
ws=[10]).flow_map(HorizontalGrid(x_j, y_j))
Z_wec1 = flow_map_wec1.WS_eff_xylk[:, :, 0, 0]
wfm.wec = 2
flow_map_wec2 = wfm(wt_x, wt_y, 70, wd=[30],
ws=[10]).flow_map(HorizontalGrid(x_j, y_j))
X, Y = flow_map_wec1.XY
Z_wec2 = flow_map_wec2.WS_eff_xylk[:, :, 0, 0]
if 0:
print(list(np.round(Z_wec1[140, 100:400:10].values, 2)))
print(list(np.round(Z_wec2[140, 100:400:10].values, 2)))
flow_map_wec1.plot_wake_map(levels=np.arange(6, 10.5, .1),
plot_colorbar=False)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
c = flow_map_wec2.plot_wake_map(levels=np.arange(6, 10.5, .1),
plot_colorbar=False)
plt.colorbar(c)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
plt.plot(X[0], Z_wec1[140, :], label="Z=70m")
plt.plot(X[0], Z_wec2[140, :], label="Z=70m")
plt.plot(X[0, 100:400:10], Z_wec1[140, 100:400:10], '.')
plt.plot(X[0, 100:400:10], Z_wec2[140, 100:400:10], '.')
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z_wec1[140, 100:400:10], [
10.0, 10.0, 10.0, 9.99, 9.8, 6.52, 1.47, 9.44, 9.98, 10.0, 10.0, 10.0,
10.0, 9.05, 0.03, 9.11, 10.0, 10.0, 10.0, 9.97, 9.25, 7.03, 2.35, 6.51,
9.99, 10.0, 10.0, 10.0, 10.0, 10.0
], 2)
npt.assert_array_almost_equal(Z_wec2[140, 100:400:10], [
9.99, 9.96, 9.84, 9.47, 7.82, 2.24, 0.21, 6.21, 9.22, 9.82, 9.98, 9.92,
9.05, 4.45, 0.01, 4.53, 9.35, 9.95, 9.75, 9.13, 7.92, 5.14, 0.32, 2.2,
8.38, 9.94, 10.0, 10.0, 10.0, 10.0
], 2)
def test_aep_map_no_turbines():
_, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
site = UniformSite(freq, ti=0.075)
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
aep = AEPCalculator(wake_model)
x_j = np.arange(-150, 150, 20)
y_j = np.arange(-250, 250, 20)
X, Y, Z = aep.aep_map(x_j, y_j, 0, [], [], wd=[0])
expect = (3.35 * 1e6) * 24 * 365 * (1e-9)
npt.assert_array_almost_equal(Z, expect, 2)
