import os import struct import numpy as np from py_wake.wake_model import LinearSum, WakeModel from numpy import newaxis as na class FugaWakeModel(WakeModel, LinearSum): ams = 5 invL = 0 args4deficit = ['WS_lk', 'WS_eff_lk', 'dw_jl', 'cw_jl', 'ct_lk'] def __init__(self, LUT_path, windTurbines): WakeModel.__init__(self, windTurbines) self.load(LUT_path) def load(self, path): with open(path + 'CaseData.bin', 'rb') as fid: case_name = struct.unpack('127s', fid.read(127))[0] r = struct.unpack('d', fid.read(8))[0] zhub = struct.unpack('d', fid.read(8))[0] lo_level = struct.unpack('I', fid.read(4))[0] hi_level = struct.unpack('I', fid.read(4))[0] z0 = struct.unpack('d', fid.read(8))[0] zi = struct.unpack('d', fid.read(8))[0] ds = struct.unpack('d', fid.read(8))[0] closure = struct.unpack('I', fid.read(4))[0] zeta0 = struct.unpack('d', fid.read(8))[0] def psim(zeta): return self.ams * zeta if not zeta0 >= 0: raise NotImplementedError # See Colonel.u2b.psim factor = 1 / (1 - (psim(zhub * self.invL) - psim(zeta0)) / np.log(zhub / z0)) f = [f for f in os.listdir(path) if f.endswith("input.par")][0] # z0_zi_zeta0 = os.path.split(os.path.dirname(path))[1] # z0, zi, zeta0 = re.match('Z0=(\d+.\d+)Zi=(\d+)Zeta0=(\d+.\d+E\+\d+)', z0_zi_zeta0).groups() with open(path + f) as fid: lines = fid.readlines() prefix = lines[0].strip() nxW, nyW = map(int, lines[2:4]) dx, dy, sigmax, sigmay = map(float, lines[4:8]) self.lo_level, self.hi_level = map(int, lines[11:13]) self.dsAll = ds zlevels = np.arange(self.lo_level, self.hi_level + 1) mdu = [np.fromfile(path + prefix + '%04dUL.dat' % j, np.dtype('<f'), -1) for j in zlevels] self.du = -np.array(mdu, dtype=np.float32).reshape((len(mdu), nyW // 2, nxW)) * factor self.z0 = z0 self.x0 = nxW // 4 self.dx = dx self.x = np.arange(-self.x0, nxW * 3 / 4) * dx self.y = np.arange(nyW // 2) * dy self.dy = dy self.z = z0 * np.exp(zlevels * self.dsAll) self.lut_interpolator = LUTInterpolator(self.x, self.y, self.z, self.du) def interpolate(self, x, y, z): x = np.maximum(np.minimum(x, self.x[-1]), self.x[0]) y = np.maximum(np.minimum(y, self.y[-1]), self.y[0]) z = np.maximum(np.minimum(z, self.z[-1]), self.z[0]) return self.lut_interpolator((x, y, z)) def calc_deficit(self, WS_lk, WS_eff_lk, dw_jl, cw_jl, ct_lk): mdu_jl = self.interpolate(dw_jl, cw_jl, 70) deficit_jlk = mdu_jl[:, :, na] * (ct_lk * WS_eff_lk**2 / WS_lk) return deficit_jlk class LUTInterpolator(object): # Faster than scipy.interpolate.interpolate.RegularGridInterpolator def __init__(self, x, y, z, V): self.x = x self.y = y self.z = z self.V = V self.nx = nx = len(x) self.ny = ny = len(y) self.nz = nz = len(z) assert V.shape == (nz, ny, nx) self.dx, self.dy = [xy[1] - xy[0] for xy in [x, y]] self.x0 = x[0] self.y0 = y[0] Ve = np.concatenate((V, V[-1:]), 0) Ve = np.concatenate((Ve, Ve[:, -1:]), 1) Ve = np.concatenate((Ve, Ve[:, :, -1:]), 2) self.V000 = np.array([V, Ve[:-1, :-1, 1:], Ve[:-1, 1:, :-1], Ve[:-1, 1:, 1:], Ve[1:, :-1, :-1], Ve[1:, :-1, 1:], Ve[1:, 1:, :-1], Ve[1:, 1:, 1:]]).reshape((8, nz * ny * nx)) def __call__(self, xyz): xp, yp, zp = xyz def i0f2(_i): _if, _i0 = np.modf(_i) _i0 = _i0.astype(np.int) return _i0, _if def i0f(_i): _i0 = np.asarray(_i).astype(np.int) _if = _i - _i0 return _i0, _if xi0, xif = i0f((xp - self.x0) / self.dx) yi0, yif = i0f((yp - self.y0) / self.dy) zi0, zif = i0f(np.interp(zp, self.z, np.arange(self.nz))) nx, ny = self.nx, self.ny v000, v001, v010, v011, v100, v101, v110, v111 = self.V000[:, zi0 * nx * ny + yi0 * nx + xi0] v_00 = v000 + (v100 - v000) * zif v_01 = v001 + (v101 - v001) * zif v_10 = v010 + (v110 - v010) * zif v_11 = v011 + (v111 - v011) * zif v__0 = v_00 + (v_10 - v_00) * yif v__1 = v_01 + (v_11 - v_01) * yif return (v__0 + (v__1 - v__0) * xif) # # Slightly slower # xif1, yif1, zif1 = 1 - xif, 1 - yif, 1 - zif # w = np.array([xif1 * yif1 * zif1, # xif * yif1 * zif1, # xif1 * yif * zif1, # xif * yif * zif1, # xif1 * yif1 * zif, # xif * yif1 * zif, # xif1 * yif * zif, # xif * yif * zif]) # # return np.sum(w * self.V01[:, zi0, yi0, xi0], 0) def main(): if __name__ == '__main__': from py_wake.aep._aep import AEP from py_wake.examples.data.iea37 import iea37_path from py_wake.examples.data.iea37.iea37_reader import read_iea37_windrose,\ read_iea37_windfarm from py_wake.site._site import UniformSite from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines _, _, 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') import matplotlib.pyplot as plt x_j = np.linspace(-1500, 1500, 500) y_j = np.linspace(-1500, 1500, 300) from py_wake.tests.test_files import tfp path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/' wake_model = FugaWakeModel(path, windTurbines) aep = AEP(site, windTurbines, wake_model) X, Y, Z = aep.wake_map(x_j, y_j, 110, x, y, wd=[0], ws=[9]) plt.figure() c = plt.contourf(X, Y, Z, 100) plt.colorbar(c) plt.plot(x, y, '2k') for i, (x_, y_) in enumerate(zip(x, y)): plt.annotate(i, (x_, y_)) plt.axis('equal') plt.show() main()