import os
import struct
from numpy import newaxis as na
import numpy as np
from py_wake.deficit_models.deficit_model import DeficitModel
from py_wake.superposition_models import LinearSum
from py_wake.wind_farm_models.engineering_models import PropagateDownwind, All2AllIterative
from py_wake.rotor_avg_models.rotor_avg_model import RotorCenter
from py_wake.tests.test_files import tfp
from py_wake.utils.grid_interpolator import GridInterpolator
from pathlib import Path
class FugaUtils():
def __init__(self, path, on_mismatch='raise'):
"""
Parameters
----------
path : string
Path to folder containing 'CaseData.bin', input parameter file (*.par) and loop-up tables
on_mismatch : {'raise', 'casedata','input_par'}
Determines how to handle mismatch between info from CaseData.in and input.par.
If 'raise' a ValueError exception is raised in case of mismatch\n
If 'casedata', the values from CaseData.bin is used\n
If 'input_par' the values from the input parameter file (*.par) is used
"""
self.path = Path(path)
with open(self.path / 'CaseData.bin', 'rb') as fid:
case_name = struct.unpack('127s', fid.read(127))[0] # @UnusedVariable
self.r = struct.unpack('d', fid.read(8))[0] # @UnusedVariable
self.zHub = struct.unpack('d', fid.read(8))[0]
self.low_level = struct.unpack('I', fid.read(4))[0]
self.high_level = struct.unpack('I', fid.read(4))[0]
self.z0 = struct.unpack('d', fid.read(8))[0]
zi = struct.unpack('d', fid.read(8))[0] # @UnusedVariable
self.ds = struct.unpack('d', fid.read(8))[0]
closure = struct.unpack('I', fid.read(4))[0]
if os.path.getsize(self.path / 'CaseData.bin') == 187:
self.zeta0 = struct.unpack('d', fid.read(8))[0]
else:
# with open(path + 'CaseData.bin', 'rb') as fid2:
# info = fid2.read(127).decode()
# zeta0 = float(info[info.index('Zeta0'):].replace("Zeta0=", ""))
if 'Zeta0' in self.path.name:
self.zeta0 = float(self.path.name[self.path.name.index(
'Zeta0'):].replace("Zeta0=", "").replace("/", ""))
f = [f for f in os.listdir(self.path) if f.endswith('.par')][0]
lines = (self.path / f).read_text().split("\n")
self.prefix = lines[0].strip()
self.nx, self.ny = map(int, lines[2:4])
self.dx, self.dy = map(float, lines[4:6]) # @UnusedVariable
self.sigmax, self.sigmay = map(float, lines[6:8]) # @UnusedVariable
def set_Value(n, v):
if on_mismatch == 'raise' and getattr(self, n) != v:
raise ValueError("Mismatch between CaseData.bin and %s: %s %s!=%s" % (f, n, getattr(self, n), v))
elif on_mismatch == 'input_par':
setattr(self, n, v)
set_Value('low_level', int(lines[11]))
set_Value('high_level', int(lines[12]))
set_Value('z0', float(lines[8])) # roughness level
set_Value('zHub', float(lines[10])) # hub height
self.nx0 = self.nx // 4
self.ny0 = self.ny // 2
self.x = np.arange(-self.nx0, self.nx * 3 / 4) * self.dx # rotor is located 1/4 downstream
self.y = np.arange(self.ny // 2) * self.dy
self.zlevels = np.arange(self.low_level, self.high_level + 1)
if self.low_level == self.high_level == 9999:
self.z = [self.zHub]
else:
self.z = self.z0 * np.exp(self.zlevels * self.ds)
def mirror(self, x, anti_symmetric=False):
x = np.asarray(x)
return np.concatenate([((1, -1)[anti_symmetric]) * x[::-1], x[1:]])
def load_luts(self, UVLT=['UL', 'UT', 'VL', 'VT'], zlevels=None):
luts = np.array([[np.fromfile(str(self.path / (self.prefix + '%04d%s.dat' % (j, uvlt))), np.dtype('<f'), -1)
for j in (zlevels or self.zlevels)] for uvlt in UVLT]).astype(np.float)
return luts.reshape((len(UVLT), len(zlevels or self.zlevels), self.ny // 2, self.nx))
class FugaDeficit(DeficitModel, FugaUtils):
ams = 5
invL = 0
args4deficit = ['WS_ilk', 'WS_eff_ilk', 'dw_ijlk', 'hcw_ijlk', 'dh_ijl', 'h_il', 'ct_ilk', 'D_src_il']
def __init__(self, LUT_path=tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/', remove_wriggles=False):
"""
Parameters
----------
LUT_path : str
Path to folder containing 'CaseData.bin', input parameter file (*.par) and loop-up tables
remove_wriggles : bool
The current Fuga loop-up tables have significan wriggles.
If True, all deficit values after the first zero crossing (when going from the center line
and out in the lateral direction) is set to zero.
This means that all speed-up regions are also removed
"""
FugaUtils.__init__(self, LUT_path, on_mismatch='input_par')
self.remove_wriggles = remove_wriggles
self.lut_interpolator = LUTInterpolator(*self.load())
def load(self):
def psim(zeta):
return self.ams * zeta
if not self.zeta0 >= 0: # pragma: no cover
# See Colonel.u2b.psim
raise NotImplementedError
factor = 1 / (1 - (psim(self.zHub * self.invL) - psim(self.zeta0)) / np.log(self.zHub / self.z0))
mdu = self.load_luts(['UL'])[0]
du = -np.array(mdu, dtype=np.float32).reshape((len(mdu), self.ny // 2, self.nx)) * factor
if self.remove_wriggles:
# remove all positive and negative deficits after first zero crossing in lateral direction
du *= (np.cumsum(du < 0, 1) == 0)
# smooth edges to zero
n = 250
du[:, :, :n] = du[:, :, n][:, :, na] * np.arange(n) / n
du[:, :, -n:] = du[:, :, -n][:, :, na] * np.arange(n)[::-1] / n
n = 50
du[:, -n:, :] = du[:, -n, :][:, na, :] * np.arange(n)[::-1][na, :, na] / n
return self.x, self.y, self.z, du
def interpolate(self, x, y, z):
# self.grid_interplator(np.array([zyx.flatten() for zyx in [z, y, x]]).T, check_bounds=False).reshape(x.shape)
return self.lut_interpolator((x, y, z))
def _calc_layout_terms(self, dw_ijlk, hcw_ijlk, h_il, dh_ijl, D_src_il, **_):
self.mdu_ijlk = self.interpolate(dw_ijlk, np.abs(hcw_ijlk), (h_il[:, na] + dh_ijl)[:, :, :, na]) * \
~((dw_ijlk == 0) & (hcw_ijlk <= D_src_il[:, na, :, na]) # avoid wake on itself
)
def calc_deficit(self, WS_ilk, WS_eff_ilk, dw_ijlk, hcw_ijlk, dh_ijl, h_il, ct_ilk, D_src_il, **kwargs):
if not self.deficit_initalized:
self._calc_layout_terms(dw_ijlk, hcw_ijlk, h_il, dh_ijl, D_src_il, **kwargs)
return self.mdu_ijlk * (ct_ilk * WS_eff_ilk**2 / WS_ilk)[:, na]
def wake_radius(self, D_src_il, dw_ijlk, **_):
# Set at twice the source radius for now
return np.zeros_like(dw_ijlk) + D_src_il[:, na, :, na]
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
xp = np.maximum(np.minimum(xp, self.x[-1]), self.x[0])
yp = np.maximum(np.minimum(yp, self.y[-1]), self.y[0])
# zp = np.maximum(np.minimum(zp, self.z[-1]), self.z[0])
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)
class Fuga(PropagateDownwind):
def __init__(self, LUT_path, site, windTurbines,
rotorAvgModel=RotorCenter(), deflectionModel=None, turbulenceModel=None, remove_wriggles=False):
"""
Parameters
----------
LUT_path : str
path to look up tables
site : Site
Site object
windTurbines : WindTurbines
WindTurbines object representing the wake generating wind turbines
rotorAvgModel : RotorAvgModel
Model defining one or more points at the down stream rotors to
calculate the rotor average wind speeds from.\n
Defaults to RotorCenter that uses the rotor center wind speed (i.e. one point) only
deflectionModel : DeflectionModel
Model describing the deflection of the wake due to yaw misalignment, sheared inflow, etc.
turbulenceModel : TurbulenceModel
Model describing the amount of added turbulence in the wake
"""
PropagateDownwind.__init__(self, site, windTurbines,
wake_deficitModel=FugaDeficit(LUT_path, remove_wriggles=remove_wriggles),
rotorAvgModel=rotorAvgModel, superpositionModel=LinearSum(),
deflectionModel=deflectionModel, turbulenceModel=turbulenceModel)
class FugaBlockage(All2AllIterative):
def __init__(self, LUT_path, site, windTurbines,
rotorAvgModel=RotorCenter(),
deflectionModel=None, turbulenceModel=None, convergence_tolerance=1e-6, remove_wriggles=False):
"""
Parameters
----------
LUT_path : str
path to look up tables
site : Site
Site object
windTurbines : WindTurbines
WindTurbines object representing the wake generating wind turbines
rotorAvgModel : RotorAvgModel
Model defining one or more points at the down stream rotors to
calculate the rotor average wind speeds from.\n
Defaults to RotorCenter that uses the rotor center wind speed (i.e. one point) only
deflectionModel : DeflectionModel
Model describing the deflection of the wake due to yaw misalignment, sheared inflow, etc.
turbulenceModel : TurbulenceModel
Model describing the amount of added turbulence in the wake
"""
fuga_deficit = FugaDeficit(LUT_path, remove_wriggles=remove_wriggles)
All2AllIterative.__init__(self, site, windTurbines, wake_deficitModel=fuga_deficit,
rotorAvgModel=rotorAvgModel, superpositionModel=LinearSum(),
deflectionModel=deflectionModel, blockage_deficitModel=fuga_deficit,
turbulenceModel=turbulenceModel, convergence_tolerance=convergence_tolerance)
def main():
if __name__ == '__main__':
from py_wake.examples.data.iea37._iea37 import IEA37Site
from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
import matplotlib.pyplot as plt
# setup site, turbines and wind farm model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines()
path = tfp + 'fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'
for wf_model in [Fuga(path, site, windTurbines),
FugaBlockage(path, site, windTurbines)]:
plt.figure()
print(wf_model)
# run wind farm simulation
sim_res = wf_model(x, y)
# calculate AEP
aep = sim_res.aep().sum()
# plot wake map
flow_map = sim_res.flow_map(wd=30, ws=9.8)
flow_map.plot_wake_map()
flow_map.plot_windturbines()
plt.title('AEP: %.2f GWh' % aep)
plt.show()
plt.show()
main()