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)
aep = AEPCalculator(wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z) # , np.arange(2, 10, .01))
plt.colorbar(c)
windTurbines.plot(x, y)
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)
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 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 main():
if __name__ == '__main__':
from py_wake.aep_calculator import AEPCalculator
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
# setup site, turbines and wakemodel
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
from py_wake.tests.test_files import tfp
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'
wake_model = Fuga(path, site, windTurbines)
# calculate AEP
aep_calculator = AEPCalculator(wake_model)
aep = aep_calculator.calculate_AEP(x, y)[0].sum()
# 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__':
from py_wake.aep_calculator import AEPCalculator
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
# setup site, turbines and wakemodel
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(windTurbines)
# calculate AEP
aep_calculator = AEPCalculator(site, windTurbines, wake_model)
aep = aep_calculator.calculate_AEP(x, y)[0].sum()
# plot wake mape
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 test_distance_over_rectangle():
x, y = [-100, 50], [200, -100]
windTurbines = IEA37_WindTurbines()
site = Rectangle(height=200, width=100, distance_resolution=100)
wake_model = NOJ(site, windTurbines)
aep = AEPCalculator(wake_model)
x_j = np.linspace(-100, 500, 100)
y_j = np.linspace(-200, 300, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[270], ws=[9])
my = np.argmin(np.abs(Y[:, 0] - 200))
my2 = np.argmin(np.abs(Y[:, 0] + 100))
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z, cmap='Blues_r',
levels=100) # , np.arange(2, 10, .01))
plt.colorbar(c)
windTurbines.plot(x, y)
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_aep_map():
site = IEA37Site(16)
x = [0, 0]
y = [0, 200]
windTurbines = IEA37_WindTurbines()
wake_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
aep = AEPCalculator(wake_model)
# print(aep.calculate_AEP([0], [0]).sum())
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, x, y, wd=[0], ws=np.arange(3, 25))
m = 17
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z, 100) # , np.arange(2, 10, .01))
plt.colorbar(c)
windTurbines.plot(x, y)
plt.plot(X[m], Y[m], '.-r')
plt.show()
# print(np.round(Z[m], 2).tolist()) # ref
ref = [
21.5, 21.4, 21.02, 20.34, 18.95, 16.54, 13.17, 10.17, 10.17, 13.17,
16.54, 18.95, 20.34, 21.02, 21.4
]
npt.assert_array_almost_equal(Z[m].squeeze('h'), ref, 2)
def test_twotype_windturbines():
from py_wake.wind_turbines import WindTurbines
v80 = V80()
def power(ws, types):
power = v80.power(ws)
# add 10% type 1 turbines
power[types == 1] *= 1.1
return power
wts = WindTurbines(names=['V80', 'V88'],
diameters=[80, 88],
hub_heights=[70, 77],
ct_funcs=[v80.ct_funcs[0], v80.ct_funcs[0]],
power_funcs=[v80.power, lambda ws: v80.power(ws) * 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)
aep_calculator = AEPCalculator(NOJ(Hornsrev1Site(), wts))
npt.assert_almost_equal(
aep_calculator.calculate_AEP(wt9_x, wt9_y, type_i=types0).sum(),
81.2066072392765)
npt.assert_almost_equal(
aep_calculator.calculate_AEP(wt9_x, wt9_y, type_i=types1).sum(),
83.72420504573488)
npt.assert_almost_equal(
aep_calculator.calculate_AEP(wt9_x, wt9_y, type_i=types2).sum(),
88.87227386796884)
if 0:
plt.show()
def run_NOJ():
windTurbines = IEA37_WindTurbines()
site = IEA37Site(64)
wake_model = NOJ(windTurbines)
aep_calculator = AEPCalculator(site, windTurbines, wake_model)
x, y = site.initial_position.T
print(aep_calculator.calculate_AEP(x, y).sum())
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 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_aep_map_no_turbines():
site = IEA37Site(16)
windTurbines = IEA37_WindTurbines()
wake_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
aep = AEPCalculator(wake_model)
x_j = np.arange(-150, 150, 20)
y_j = np.arange(-250, 250, 20)
_, _, 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)
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_stf(WakeModel, ref_ti):
# setup site, turbines and wakemodel
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wake_model = WakeModel(site, windTurbines)
aep_calculator = AEPCalculator(wake_model)
aep_calculator.calculate_AEP(x, y)
# print(np.round(aep_calculator.TI_eff_ilk[:, 0, 0], 3).tolist())
npt.assert_array_almost_equal(aep_calculator.TI_eff_ilk[:, 0, 0], ref_ti, 3)
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)
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(site, wt, NOJ(wt))
npt.assert_almost_equal(aep.calculate_AEP_no_wake_loss(x, y).sum() / 80, 8.260757098)
cap_factor = aep.calculate_AEP(x, y).sum() / aep.calculate_AEP_no_wake_loss(x, y).sum()
# print(cap_factor)
npt.assert_almost_equal(cap_factor, 0.947175839142014)
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
wake_model = NOJ(windTurbines)
site = UniformSite([1], 0.1)
aep = AEPCalculator(site, windTurbines, wake_model)
_, _, WS_eff_yx = aep.wake_map(x_j=[0], y_j=[0, -40, -100], h=50, wt_x=[0], wt_y=[0], wd=[0], ws=[8.1])
npt.assert_array_almost_equal(WS_eff_yx[:, 0], [8.1, 4.35, 5.7])
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 test_aep_map_no_turbines():
_, _, 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 = IEA37SimpleBastankhahGaussian(windTurbines)
aep = AEPCalculator(site, windTurbines, 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])
npt.assert_array_almost_equal(Z, 21.89, 2)
def main():
if __name__ == '__main__':
site = WaspGridSiteBase.from_wasp_grd(ParqueFicticio_path, speedup_using_pickle=False)
site.initial_position = np.array([
[263655.0, 6506601.0],
[263891.1, 6506394.0],
[264022.2, 6506124.0],
[264058.9, 6505891.0],
[264095.6, 6505585.0],
[264022.2, 6505365.0],
[264022.2, 6505145.0],
[263936.5, 6504802.0],
])
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site, windTurbines)
x, y = site.initial_position.T
aep_calculator = AEPCalculator(wake_model)
print(aep_calculator.calculate_AEP(x, y).sum())
def main():
if __name__ == '__main__':
try:
import matplotlib.pyplot as plt
plt.gcf()
plot_comp = XYPlotComp()
plot = True
except RuntimeError:
plot_comp = NoPlot()
plot = False
n_wt = 16
site = IEA37Site(n_wt)
windTurbines = IEA37_WindTurbines()
wake_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
Drotor_vector = [windTurbines.diameter()] * n_wt
power_rated_vector = [float(windTurbines.power(20) / 1000)] * n_wt
hub_height_vector = [windTurbines.hub_height()] * n_wt
AEPCalc = AEPCalculator(wake_model)
def aep_func(x, y, **kwargs):
return AEPCalc.calculate_AEP(x_i=x, y_i=y).sum(-1).sum(-1) * 10**6
def irr_func(aep, **kwargs):
my_irr = economic_evaluation(Drotor_vector, power_rated_vector,
hub_height_vector,
aep).calculate_irr()
print(my_irr)
return my_irr
aep_comp = CostModelComponent(input_keys=['x', 'y'],
n_wt=n_wt,
cost_function=aep_func,
output_key="aep",
output_unit="GWh",
objective=False,
output_val=np.zeros(n_wt))
irr_comp = CostModelComponent(input_keys=['aep'],
n_wt=n_wt,
cost_function=irr_func,
output_key="irr",
output_unit="%",
objective=True,
income_model=True)
group = TopFarmGroup([aep_comp, irr_comp])
problem = TopFarmProblem(
design_vars=dict(zip('xy', site.initial_position.T)),
cost_comp=group,
driver=EasyRandomSearchDriver(
randomize_func=RandomizeTurbinePosition_Circle(), max_iter=50),
constraints=[
SpacingConstraint(200),
CircleBoundaryConstraint([0, 0], 1300.1)
],
plot_comp=plot_comp)
cost, state, recorder = problem.optimize()
def test_IEA37SimpleBastankhahGaussian_ex16():
_, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
n_wt = 16
x, y, aep_ref = read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)
if 0:
import matplotlib.pyplot as plt
plt.plot(x, y, '2k')
for i, (x_, y_) in enumerate(zip(x, y)):
plt.annotate(i, (x_, y_))
plt.axis('equal')
plt.show()
site = UniformSite(freq, ti=0.75)
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = IEA37SimpleBastankhahGaussian(windTurbines)
aep = AEPCalculator(site, windTurbines, wake_model)
aep_ilk = aep.calculate_AEP(x, y, wd=np.arange(0, 360, 22.5), ws=[9.8])
aep_MW_l = aep_ilk.sum((0, 2)) * 1000
# test that the result is equal to results provided for IEA task 37
npt.assert_almost_equal(aep_ref[0], aep_MW_l.sum(), 5)
npt.assert_array_almost_equal(aep_ref[1], aep_MW_l, 5)
def test_BastankhahGaussian_ex16():
site = IEA37_Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = BastankhahGaussian(windTurbines)
if 0:
import matplotlib.pyplot as plt
windTurbines.plot(x, y)
plt.show()
aep = AEPCalculator(site, windTurbines, wake_model)
aep_ilk = aep.calculate_AEP(x, y, wd=np.arange(0, 360, 22.5), ws=[9.8])
aep_MW_l = aep_ilk.sum((0, 2)) * 1000
# test that the result is equal to last run (no evidens that these number are correct)
aep_ref = (355971.9717035484, [
9143.74048, 8156.71681, 11311.92915, 13955.06316, 19807.65346,
25196.64182, 39006.65223, 41463.31044, 23042.22602, 12978.30551,
14899.26913, 32320.21637, 67039.04091, 17912.40907, 12225.04134,
7513.75582
])
npt.assert_almost_equal(aep_MW_l.sum(), aep_ref[0], 5)
npt.assert_array_almost_equal(aep_MW_l, aep_ref[1], 5)
def test_IEA37SimpleBastankhahGaussian_wake_map():
site = IEA37_Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = IEA37SimpleBastankhahGaussian(windTurbines)
aep = AEPCalculator(site, windTurbines, wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
# test that the result is equal to last run (no evidens that these number are correct)
ref = [
3.32, 4.86, 7.0, 8.1, 7.8, 7.23, 6.86, 6.9, 7.3, 7.82, 8.11, 8.04,
7.87, 7.79, 7.85, 8.04, 8.28
]
npt.assert_array_almost_equal(Z[49, 100:133:2], ref, 2)
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z, np.arange(2, 9.1, .01))
plt.colorbar(c)
site.plot_windturbines(x, y)
plt.plot(X[49, 100:133:2], Y[49, 100:133:2], '-.')
plt.show()
def test_wake_map():
_, _, 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 = NOJ(windTurbines)
aep = AEPCalculator(site, windTurbines, wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z) # , np.arange(2, 10, .01))
plt.colorbar(c)
site.plot_windturbines(x, y)
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)
def test_BastankhahGaussian_wake_map():
site = IEA37_Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = BastankhahGaussian(windTurbines)
aep = AEPCalculator(site, windTurbines, wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
# test that the result is equal to last run (no evidens that these number are correct)
ref = [
0.18, 3.6, 7.27, 8.32, 7.61, 6.64, 5.96, 6.04, 6.8, 7.69, 8.08, 7.87,
7.59, 7.46, 7.55, 7.84, 8.19
]
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z, np.arange(-.25, 9.1, .01))
plt.colorbar(c)
windTurbines.plot(x, y)
plt.show()
npt.assert_array_almost_equal(Z[49, 100:133:2], ref, 2)
def test_wake_map():
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
wake_model = NOJ(site, windTurbines)
aep = AEPCalculator(wake_model)
x_j = np.linspace(-1500, 1500, 200)
y_j = np.linspace(-1500, 1500, 100)
X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9])
m = 49, slice(100, 133, 2)
# print(np.round(Z[m], 2).tolist()) # ref
if 0:
import matplotlib.pyplot as plt
c = plt.contourf(X, Y, Z) # , np.arange(2, 10, .01))
plt.colorbar(c)
windTurbines.plot(x, y)
plt.plot(X[m], Y[m], '.-r')
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[m], ref, 2)
def main():
if __name__ == '__main__':
plot_comp = XYPlotComp()
site = get_site()
n_wt = len(site.initial_position)
windTurbines = DTU10MW()
min_spacing = 2 * windTurbines.diameter(0)
wake_model = IEA37SimpleBastankhahGaussian(site, windTurbines)
Drotor_vector = [windTurbines.diameter()] * n_wt
power_rated_vector = [float(windTurbines.power(20) / 1000)] * n_wt
hub_height_vector = [windTurbines.hub_height()] * n_wt
AEPCalc = AEPCalculator(wake_model)
def aep_func(x, y, **kwargs):
return AEPCalc.calculate_AEP(x_i=x, y_i=y).sum(-1).sum(-1) * 10**6
def irr_func(aep, **kwargs):
return economic_evaluation(Drotor_vector, power_rated_vector,
hub_height_vector, aep).calculate_irr()
aep_comp = CostModelComponent(input_keys=['x', 'y'],
n_wt=n_wt,
cost_function=aep_func,
output_key="aep",
output_unit="GWh",
objective=False,
output_val=np.zeros(n_wt))
irr_comp = CostModelComponent(input_keys=['aep'],
n_wt=n_wt,
cost_function=irr_func,
output_key="irr",
output_unit="%",
objective=True,
income_model=True)
group = TopFarmGroup([aep_comp, irr_comp])
problem = TopFarmProblem(
design_vars=dict(zip('xy', site.initial_position.T)),
cost_comp=group,
driver=EasyRandomSearchDriver(
randomize_func=RandomizeTurbinePosition_Circle(), max_iter=50),
constraints=[
SpacingConstraint(min_spacing),
XYBoundaryConstraint(site.boundary),
],
plot_comp=plot_comp)
cost, state, recorder = problem.optimize()
def test_aep_no_wake():
site = UniformWeibullSite([1], [10], [2], .75)
V80 = hornsrev1.V80()
aep = AEPCalculator(NOJ(site, V80))
npt.assert_almost_equal(
aep.calculate_AEP([0], [0], ws=np.arange(3, 25)).sum(), 8.260757098, 9)
