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_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_6_turbines_in_row():
n_wt = 6
x = [0] * n_wt
y = - np.arange(n_wt) * 40 * 2
wake_model = NOJ(NibeA0)
site = UniformSite([1], .1)
WD_ilk, WS_ilk, _, _ = site.local_wind(x_i=x, y_i=y, wd=[0], ws=[11])
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] * n_wt, wd_il=WD_ilk.mean(2))
WS_eff_ilk = wake_model.calc_wake(WS_ilk, TI_ilk, dw_iil, cw_iil, dh_iil, dw_order_indices_l, [0] * n_wt)[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)))
