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 test_fuga_wriggles():
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+00/'
site = hornsrev1.Hornsrev1Site()
fuga = PropagateDownwind(site, wts, FugaDeficit(path,
remove_wriggles=True))
D = 80
flow_map_cw = fuga([0], [0], wd=270, ws=10).flow_map(
HorizontalGrid([0], np.arange(-20 * D, 20 * D)))
y = np.linspace(-5 * D, 5 * D, 100)
dw_lst = range(10)
flow_map_cw_lst = np.array([
fuga([0], [0], wd=270,
ws=10).flow_map(HorizontalGrid([dw * D], y)).WS_eff.squeeze()
for dw in dw_lst
])
if 0:
for flow_map_cw, dw in zip(flow_map_cw_lst, dw_lst):
plt.plot(y, flow_map_cw, label="%dD" % dw)
plt.xlabel('y [m]')
plt.ylabel('ws [m/s')
plt.ylim([9.9, 10.1])
plt.grid()
plt.legend(loc=1)
plt.show()
assert np.all(flow_map_cw_lst > 0)
def test_fuga_table_edges():
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+00/'
site = hornsrev1.Hornsrev1Site()
fuga = FugaBlockage(path, site, wts)
D = 80
flow_map_dw = fuga([0], [0], wd=270, ws=10).flow_map(
HorizontalGrid(np.arange(-200 * D, 450 * D), y=[0]))
flow_map_cw = fuga([0], [0], wd=270, ws=10).flow_map(
HorizontalGrid([0], np.arange(-20 * D, 20 * D)))
flow_map = fuga([0], [0], wd=270, ws=10).flow_map(
HorizontalGrid(np.arange(-150, 400) * D,
np.arange(-20, 21) * D))
if 0:
plt.plot(flow_map_dw.x / D, flow_map_dw.WS_eff.squeeze())
plt.grid()
plt.ylim([9.9, 10.1])
plt.figure()
plt.plot(flow_map_cw.y / D, flow_map_cw.WS_eff.squeeze())
plt.grid()
plt.ylim([9.9, 10.1])
plt.figure()
flow_map.WS_eff.plot()
plt.show()
npt.assert_array_equal(flow_map.WS_eff.squeeze()[[0, -1], :], 10)
npt.assert_array_equal(flow_map.WS_eff.squeeze()[:, [0, -1]], 10)
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 check_speed_Hornsrev(WFModel):
assert getattr(sys, 'gettrace')() is None, "Skipping speed check, In debug mode!!!"
wt = HornsrevV80()
site = Hornsrev1Site()
wf_model = WFModel(site, wt)
aep, t_lst = timeit(lambda x, y: wf_model(x, y).aep().sum())(wt_x, wt_y)
fn = tfp + "speed_check/%s.txt" % WFModel.__name__
if os.path.isfile(fn):
with open(fn) as fid:
lines = fid.readlines()
# check aep
npt.assert_almost_equal(float(lines[-1].split(";")[1]), aep)
timings = np.array([(np.mean(eval(l.split(";")[2])), np.std(eval(l.split(";")[2]))) for l in lines])
dates = [np.datetime64(l.split(";")[0]) for l in lines]
dates = np.r_[dates, datetime.now()]
y = np.r_[timings[:, 0], np.mean(t_lst)]
error = np.r_[timings[:, 1], np.std(t_lst)]
fig, axes = plt.subplots(2, 1)
fig.suptitle(WFModel.__name__)
for x, ax in zip([dates, np.arange(len(dates))], axes):
ax.fill_between(x, y - 2 * error, y + 2 * error)
ax.plot(x, y, '.-k')
ax.axhline(y[:-1].mean() + 2 * error[:-1].mean(), ls='--', color='gray')
if y[-1] > (y[:-1].mean() + 2 * error[:-1].mean()):
raise Exception("Simulation time too slow, %f > %f" % (y[-1], (y[:-1].mean() + 2 * error[:-1].mean())))
if getattr(sys, 'gettrace')() is None:
with open(fn, 'a') as fid:
fid.write("%s;%.10f;%s\n" % (datetime.now(), aep, t_lst))
def test_fuga_blockage_wt_row():
wts = HornsrevV80()
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+00/'
site = hornsrev1.Hornsrev1Site()
fuga_pdw = Fuga(path, site, wts)
fuga_a2a = FugaBlockage(path, site, wts)
x, y = [
np.asarray(xy)[np.arange(0, 73, 8)]
for xy in (hornsrev1.wt_x, hornsrev1.wt_y)
]
sim_res_pdw = fuga_pdw(x, y, wd=[270])
aep = sim_res_pdw.aep_ilk()[:, 0, :]
sim_res_a2a = fuga_a2a(x, y, wd=[270])
aep_blockage = sim_res_a2a.aep_ilk()[:, 0, :]
# blockage reduce aep(wd=270) by .24%
npt.assert_almost_equal((aep.sum() - aep_blockage.sum()) / aep.sum() * 100,
0.2433161515321294)
if 0:
plt.plot(
(sim_res_pdw.WS_eff_ilk[:, 0, 7] - sim_res_a2a.WS_eff_ilk[:, 0, 7])
/ sim_res_pdw.WS_eff_ilk[:, 0, 7] * 100)
plt.grid()
plt.show()
def main():
if __name__ == '__main__':
import matplotlib.pyplot as plt
wt = HornsrevV80()
wt.plot(wt_x, wt_y)
aep_calculator = AEPCalculator(Hornsrev1Site(), wt, NOJ(wt))
print('AEP', aep_calculator.calculate_AEP(wt_x, wt_y)[0].sum())
plt.show()
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_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_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 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 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_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=0.075)
wake_model = Fuga(path, site, wts)
res, _ = timeit(wake_model.__call__, verbose=0, line_profile=0,
profile_funcs=[FugaDeficit.interpolate, LUTInterpolator.__call__, GridInterpolator.__call__])(x=wt_x, y=wt_y, wd=[30], ws=[10])
npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(),
[10.002683492812844, 10.0, 8.413483643142389, 10.036952526815286,
9.371203842245153, 8.437429367715435, 8.012759083790058], 8)
npt.assert_array_almost_equal(res.ct_ilk.flatten(), [0.79285509, 0.793, 0.80641348, 0.79100456,
0.80180315, 0.80643743, 0.80601276], 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.data[140, 100:400:10], 4)))
print(list(np.round(Z73.data[140, 100:400:10], 4)))
plt.legend()
plt.show()
npt.assert_array_almost_equal(
Z70[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(
Z73[140, 100:400:10],
[10.0463, 10.0468, 10.0688, 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, 10.018, 10.0183, 10.019, 10.0138], 4)
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=0.75)
wake_model = Fuga(LUT_path_2MW_z0_0_03, wts)
aep = AEPCalculator(site, wts, wake_model)
x_j = np.linspace(-1500, 1500, 500)
y_j = np.linspace(-1500, 1500, 300)
_, _, Z_wec1 = aep.wake_map(x_j, y_j, 70, wt_x, wt_y, wt_height=70, wd=[30], ws=[10])
aep.wake_model.wec = 2
X, Y, Z_wec2 = aep.wake_map(x_j, y_j, 70, wt_x, wt_y, wt_height=70, wd=[30], ws=[10])
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z_wec1, np.arange(6, 10.5, .1))
plt.colorbar(c)
plt.plot(X[0], Y[140])
wts.plot(wt_x, wt_y)
plt.figure()
c = plt.contourf(X, Y, Z_wec2, 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], 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],
[10.0547, 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(
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 main():
if __name__ == '__main__':
from py_wake import NOJ
from py_wake import IEA37SimpleBastankhahGaussian, Fuga
import py_wake
import os
import matplotlib.pyplot as plt
from py_wake.examples.data.hornsrev1 import HornsrevV80, Hornsrev1Site
from py_wake.examples.data.iea37._iea37 import IEA37Site
LUT_path = os.path.dirname(
py_wake.__file__
) + '/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+00/'
wt_x, wt_y = IEA37Site(16).initial_position.T
windTurbines = HornsrevV80()
site = Hornsrev1Site()
wake_models = [
NOJ(site, windTurbines),
IEA37SimpleBastankhahGaussian(site, windTurbines),
Fuga(LUT_path, site, windTurbines)
]
for wake_model in wake_models:
# Calculate AEP
sim_res = wake_model(wt_x, wt_y)
# Plot wake map
plt.figure(wake_model.__class__.__name__)
plt.title('AEP: %.2f GWh' % sim_res.aep().sum())
flow_map = sim_res.flow_map(wd=[0], ws=[9])
flow_map.plot_wake_map()
flow_map.plot_windturbines()
plt.show()
def main():
if __name__ == '__main__':
site = UniformSite(p_wd=[1], ti=.1) # Dummy site (flat and uniform)
# Validation cases:
SingleWakecases = [{
'name': 'Wieringermeer-West',
'U0': 10.7,
'CT': 0.63,
'TItot': 0.08,
'D': 80.0,
'zH': 80.0,
'xDown': np.array([2.5, 3.5, 7.5]),
'location': 'onshore'
}, {
'name': 'Wieringermeer-East',
'U0': 10.9,
'CT': 0.63,
'TItot': 0.06,
'D': 80.0,
'zH': 80.0,
'xDown': np.array([2.5, 3.5, 7.5]),
'location': 'onshore'
}, {
'name': 'Nibe',
'U0': 8.5,
'CT': 0.89,
'TItot': 0.08,
'D': 40.0,
'zH': 45.0,
'xDown': np.array([2.5, 4, 7.5]),
'location': 'onshore'
}, {
'name': 'Nordtank-500',
'U0': 7.45,
'CT': 0.70,
'TItot': 0.112,
'D': 41.0,
'zH': 36.0,
'xDown': np.array([2, 5, 7.5]),
'location': 'onshore'
}, {
'name': 'NREL-5MW_TIlow',
'U0': 8.0,
'CT': 0.79,
'TItot': 0.04,
'D': 126.0,
'zH': 90.0,
'xDown': np.array([2.5, 5, 7.5]),
'location': 'offshore'
}, {
'name': 'NREL-5MW_TIhigh',
'U0': 8.0,
'CT': 0.79,
'TItot': 0.128,
'D': 126.0,
'zH': 90.0,
'xDown': np.array([2.5, 5, 7.5]),
'location': 'onshore'
}]
# If missing wind turbines need to be included in the plot, one should write np.nan in the wts list.
hr_inner_rows = np.linspace(0, 79, 80).reshape(10, 8)[:, 1:7].flatten(
).tolist() # WTs representing the inner rows of Horns Rev 1
WFcases = [{
'name':
'Wieringermeer',
'U0':
8.35,
'TItot':
0.096,
'wt':
N80(),
'wt_x':
wt_x_w,
'wt_y':
wt_y_w,
'site':
site,
'location':
'onshore',
'plots': [{
'name': 'Row',
'wd': 275.0,
'wts': [0, 1, 2, 3, 4]
}]
}, {
'name':
'Lillgrund',
'U0':
9.0,
'TItot':
0.048,
'wt':
SWT2p3_93_65(),
'wt_x':
wt_x_l,
'wt_y':
wt_y_l,
'site':
LillgrundSite(),
'location':
'offshore',
'plots': [{
'name': 'RowB',
'wd': 222.0,
'wts': [14, 13, 12, 11, 10, 9, 8, 7]
}, {
'name': 'RowD',
'wd': 222.0,
'wts': [29, 28, 27, np.nan, 26, 25, 24, 23]
}, {
'name': 'RowB',
'wd': 207.0,
'wts': [14, 13, 12, 11, 10, 9, 8, 7]
}, {
'name': 'RowD',
'wd': 207.0,
'wts': [29, 28, 27, np.nan, 26, 25, 24, 23]
}, {
'name': 'Row6',
'wd': 120.0,
'wts': [2, 9, 17, 25, 32, 37, 42, 46]
}, {
'name': 'Row4',
'wd': 120.0,
'wts': [4, 11, 19, np.nan, np.nan, 39, 44]
}, {
'name': 'Row6',
'wd': 105.0,
'wts': [2, 9, 17, 25, 32, 37, 42, 46]
}, {
'name': 'Row4',
'wd': 105.0,
'wts': [4, 11, 19, np.nan, np.nan, 39, 44]
}, {
'name': 'WFeff'
}]
}, {
'name':
'Hornsrev1',
'U0':
8.0,
'TItot':
0.056,
'wt':
HornsrevV80(),
'wt_x':
wt_x_hr,
'wt_y':
wt_y_hr,
'site':
Hornsrev1Site(),
'location':
'offshore',
'plots': [{
'name': 'InnerRowMean',
'wd': 270.0,
'wts': hr_inner_rows
}]
}]
# Revert back to old default style:
mpl.style.use('classic')
# Latex font
plt.rcParams['font.family'] = 'STIXGeneral'
linewidth = 1.5
cLES = 'c'
cRANS = 'g'
colors = ['r', 'b']
# Plot velocity deficit of single wake cases and calculate integrated velocity deficit
UdefCases = deficitPlotSingleWakeCases(SingleWakecases, site,
linewidth, cLES, cRANS, colors)
# Plot bar plot of integrated velocity deficit of single wake cases
barPlotSingleWakeCases(SingleWakecases, UdefCases, cLES, cRANS, colors)
# Plot power deficit in a row of wind turbine or plot wind farm efficiency
deficitPlotWFCases(WFcases, linewidth, cLES, cRANS, colors)
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=0.075)
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(), [
10.002683492812844, 10.0, 8.413483643142389, 10.036952526815286,
9.371203842245153, 8.437429367715435, 8.012759083790058
], 8)
npt.assert_array_almost_equal(res.ct_ilk.flatten(), [
0.79285509, 0.793, 0.80641348, 0.79100456, 0.80180315, 0.80643743,
0.80601276
], 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:
import matplotlib.pyplot as plt
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[140, 100:400:10], 4)))
print(list(np.round(Z73[140, 100:400:10], 4)))
plt.legend()
plt.show()
# npt.assert_array_almost_equal(
# Z70[140, 100:400:10],
# [10.0547, 10.0519, 10.0741, 10.0099, 9.6774, 7.8538, 6.8484, 9.2134, 9.9749, 10.0232, 10.0658, 10.0189, 10.0187,
# 9.1496, 7.2077, 9.1154, 10.0183, 10.0008, 10.0146, 9.8838, 9.2848, 7.9681, 6.7412, 8.3149, 9.9114, 10.0119,
# 10.0011, 9.9979, 10.0002, 9.9981], 4)
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_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+00/'
site = UniformSite([1, 0, 0, 0], ti=0.075)
wake_model = Fuga(path, site, wts)
res, _ = timeit(wake_model.__call__,
verbose=0,
line_profile=0,
profile_funcs=[
FugaDeficit.interpolate, LUTInterpolator.__call__,
GridInterpolator.__call__
])(x=wt_x, y=wt_y, wd=[30], ws=[10])
npt.assert_array_almost_equal(res.WS_eff_ilk.flatten(), [
10.00669629, 10., 8.47606501, 10.03143097, 9.37288077, 8.49301941,
8.07462708
], 8)
npt.assert_array_almost_equal(res.ct_ilk.flatten(), [
0.7926384, 0.793, 0.80647607, 0.79130273, 0.80177967, 0.80649302,
0.80607463
], 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.data[140, 100:400:10], 4)))
print(list(np.round(Z73.data[140, 100:400:10], 4)))
plt.legend()
plt.show()
npt.assert_array_almost_equal(Z70[140, 100:400:10], [
10.0407, 10.0438, 10.0438, 10.013, 9.6847, 7.8787, 6.9561, 9.2251,
9.9686, 10.0382, 10.0498, 10.0569, 10.0325, 9.1787, 7.4004, 9.1384,
10.0329, 10.0297, 10.0232, 9.9265, 9.3163, 8.0768, 6.8858, 8.3754,
9.9592, 10.0197, 10.0118, 10.0141, 10.0118, 10.0095
], 4)
npt.assert_array_almost_equal(Z73[140, 100:400:10], [
10.0404, 10.0435, 10.0433, 10.0113, 9.6836, 7.9206, 7.0218, 9.2326,
9.9665, 10.0376, 10.0494, 10.0563, 10.0304, 9.1896, 7.4515, 9.15,
10.0317, 10.0294, 10.0226, 9.9245, 9.3252, 8.1192, 6.9462, 8.3988,
9.9574, 10.0194, 10.0117, 10.014, 10.0117, 10.0094
], 4)
def __init__(self):
self.windFarmModel_dict = {}
# single wake cases
swc = {
'Wieringermeer-West': {'U0': 10.7, 'CT': 0.63, 'TItot': 0.08, 'D': 80.0, 'zH': 80.0,
'xDown': np.array([2.5, 3.5, 7.5]), 'sDown': 80.0, 'location': 'onshore'},
'Wieringermeer-East': {'U0': 10.9, 'CT': 0.63, 'TItot': 0.06, 'D': 80.0, 'zH': 80.0,
'xDown': np.array([2.5, 3.5, 7.5]), 'sDown': 80.0, 'location': 'onshore'},
'Nibe': {'U0': 8.5, 'CT': 0.89, 'TItot': 0.08, 'D': 40.0, 'zH': 45.0,
'xDown': np.array([2.5, 4, 7.5]), 'sDown': 40.0, 'location': 'onshore'},
'Nordtank-500': {'U0': 7.45, 'CT': 0.70, 'TItot': 0.112, 'D': 41.0, 'zH': 36.0,
'xDown': np.array([2, 5, 7.5]), 'sDown': 40.0, 'location': 'onshore'},
'NREL-5MW_TIlow': {'U0': 8.0, 'CT': 0.79, 'TItot': 0.04, 'D': 126.0, 'zH': 90.0,
'xDown': np.array([2.5, 5, 7.5]), 'sDown': 126.0, 'location': 'offshore'},
'NREL-5MW_TIhigh': {'U0': 8.0, 'CT': 0.79, 'TItot': 0.128, 'D': 126.0, 'zH': 90.0,
'xDown': np.array([2.5, 5, 7.5]), 'sDown': 126.0, 'location': 'onshore'}
}
self.single_wake_cases = [SingleWakeValidationCase.from_case_dict(k, v) for k, v in swc.items()]
# multiwake cases
from py_wake.examples.data.hornsrev1 import wt_x as wt_x_hr
from py_wake.examples.data.hornsrev1 import wt_y as wt_y_hr
from py_wake.validation.ecn_wieringermeer import wt_x as wt_x_w
from py_wake.validation.ecn_wieringermeer import wt_y as wt_y_w
from py_wake.validation.lillgrund import wt_x as wt_x_l
from py_wake.validation.lillgrund import wt_y as wt_y_l
def get_site(ti, ws, wt_x, wt_y):
return UniformSite(p_wd=[1], ti=ti, ws=ws, initial_position=np.array([wt_x, wt_y]).T)
hr_inner_rows = np.arange(80).reshape(10, 8)[:, 1:7].flatten().tolist()
self.multi_wake_cases = [MultiWakeValidationCase('Wieringermeer',
site=get_site(
ti=0.096 / 0.8, ws=8.35, wt_x=wt_x_w, wt_y=wt_y_w),
windTurbines=N80(),
sigma=2.5 * np.ones(len(wt_x_w)),
plots=[RowPlot(name='Row', wd=275.0, wts=[0, 1, 2, 3, 4])]),
MultiWakeValidationCase('Lillgrund',
site=get_site(ti=0.048, ws=9, wt_x=wt_x_l, wt_y=wt_y_l),
windTurbines=SWT2p3_93_65(),
sigma=3.3 * np.ones(len(wt_x_l)),
plots=[RowPlot('RowB', 222.0, [14, 13, 12, 11, 10, 9, 8, 7]),
RowPlot('RowD', 222.0, [
29, 28, 27, np.nan, 26, 25, 24, 23]),
RowPlot('RowB', 207.0, [14, 13, 12, 11, 10, 9, 8, 7]),
RowPlot('RowD', 207.0, [
29, 28, 27, np.nan, 26, 25, 24, 23]),
RowPlot('Row6', 120.0, [2, 9, 17, 25, 32, 37, 42, 46]),
RowPlot('Row4', 120.0, [
4, 11, 19, np.nan, np.nan, 39, 44]),
RowPlot('Row6', 105.0, [2, 9, 17, 25, 32, 37, 42, 46]),
RowPlot('Row4', 105.0, [
4, 11, 19, np.nan, np.nan, 39, 44]),
WindRosePlot(),
]),
MultiWakeValidationCase('Hornsrev1',
site=get_site(ti=0.056, ws=8, wt_x=wt_x_hr, wt_y=wt_y_hr),
windTurbines=HornsrevV80(),
sigma=sigma_hornsrev('vanderLaan', wt_x_hr, wt_y_hr),
plots=[RowPlot('InnerRowMean', 270.0, hr_inner_rows),
WindRosePlot(),
])
]