import numpy as np
from foxes.models.wake_models.top_hat import TopHatWakeModel
from foxes.utils.two_circles import calc_area
import foxes.variables as FV
import foxes.constants as FC
from .centre import PartialCentre
[docs]
class PartialTopHat(PartialCentre):
"""
Partial wakes for top-hat models.
The wake effect is weighted by the overlap of
the wake circle and the rotor disc circle.
Attributes
----------
rotor_model: foxes.core.RotorModel
The rotor model, default is the one from the algorithm
:group: models.partial_wakes
"""
[docs]
def __init__(self, rotor_model=None):
"""
Constructor.
Parameters
----------
rotor_model: foxes.core.RotorModel, optional
The rotor model, default is the one from the algorithm
"""
super().__init__()
self.rotor_model = rotor_model
[docs]
def initialize(self, algo, verbosity=0):
"""
Initializes the model.
Parameters
----------
algo: foxes.core.Algorithm
The calculation algorithm
verbosity: int
The verbosity level, 0 = silent
"""
if self.rotor_model is None:
self.rotor_model = algo.rotor_model
super().initialize(algo, verbosity)
self.WCOOS_ID = self.var("WCOOS_ID")
self.WCOOS_X = self.var("WCOOS_X")
self.WCOOS_R = self.var("WCOOS_R")
[docs]
def sub_models(self):
"""
List of all sub-models
Returns
-------
smdls: list of foxes.core.Model
Names of all sub models
"""
return super().sub_models() + [self.rotor_model]
[docs]
def contribute(
self,
algo,
mdata,
fdata,
tdata,
downwind_index,
wake_deltas,
wmodel,
):
"""
Modifies wake deltas at target points by
contributions from the specified wake source turbines.
Parameters
----------
algo: foxes.core.Algorithm
The calculation algorithm
mdata: foxes.core.MData
The model data
fdata: foxes.core.FData
The farm data
tdata: foxes.core.TData
The target point data
downwind_index: int
The index of the wake causing turbine
in the downwnd order
wake_deltas: dict
The wake deltas. Key: variable name,
value: numpy.ndarray with shape
(n_states, n_targets, n_tpoints, ...)
wmodel: foxes.core.WakeModel
The wake model
"""
if not isinstance(wmodel, TopHatWakeModel):
raise TypeError(
f"Partial wakes '{self.name}': Cannot be applied to wake model '{wmodel.name}', since not a TopHatWakeModel"
)
wcoos = algo.wake_frame.get_wake_coos(algo, mdata, fdata, tdata, downwind_index)
x = wcoos[:, :, 0, 0]
yz = wcoos[:, :, 0, 1:3]
del wcoos
ct = self.get_data(
FV.CT,
FC.STATE_TARGET,
lookup="w",
fdata=fdata,
tdata=tdata,
downwind_index=downwind_index,
algo=algo,
upcast=True,
)
sel0 = (ct > 0) & (x > 0)
if np.any(sel0):
R = np.linalg.norm(yz, axis=-1)
del yz
D = self.get_data(
FV.D,
FC.STATE_TARGET,
lookup="w",
fdata=fdata,
tdata=tdata,
downwind_index=downwind_index,
algo=algo,
upcast=True,
)
wr = wmodel.calc_wake_radius(
algo, mdata, fdata, tdata, downwind_index, x, ct
)
st_sel = sel0 & (wr > R - D / 2)
if np.any(st_sel):
x = x[st_sel]
ct = ct[st_sel]
wr = wr[st_sel]
R = R[st_sel]
D = D[st_sel]
clw = wmodel.calc_centreline(
algo, mdata, fdata, tdata, downwind_index, st_sel, x, wr, ct
)
weights = calc_area(D / 2, wr, R) / (np.pi * (D / 2) ** 2)
for v, d in clw.items():
try:
superp = wmodel.superp[v]
except KeyError:
raise KeyError(
f"Model '{self.name}': Missing wake superposition entry for variable '{v}' in wake model '{wmodel.name}', found {sorted(list(wmodel.superp.keys()))}"
)
wake_deltas[v] = superp.add_wake(
algo,
mdata,
fdata,
tdata,
downwind_index,
st_sel,
v,
wake_deltas[v],
weights[:, None] * d[:, None],
)