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import warnings
from py_wake.flow_map import HorizontalGrid
def __init__(self, wake_model):
"""Initialize AEPCalculator
Parameters
----------
site : py_wake.site.Site
windTurbines : WindTurbines
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flow_model : FlowModel
warnings.simplefilter('default', DeprecationWarning)
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warnings.warn("""AEPCalculator(wake_model) is deprecated;
wake_model(x_i, y_i, ...) returns a flowModelResult with same functionality as AEPCalculator.""",
DeprecationWarning, stacklevel=2)
self.site = wake_model.site
self.windTurbines = wake_model.windTurbines
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def _set_flowModelResult(self, flowModelResult):
for n in ['WS_eff_ilk', 'TI_eff_ilk', 'power_ilk', 'ct_ilk']:
setattr(self, n, getattr(flowModelResult, n))
for n in ['WD_ilk', 'WS_ilk', 'TI_ilk', 'P_ilk']:
setattr(self, n, getattr(flowModelResult, n))
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def calculate_AEP(self, x_i, y_i, h_i=None, type_i=0, wd=None, ws=None):
"""Calculate AEP
In addition effective wind speed, turbulence intensity, and the
power, ct and probability is calculated
Parameters
----------
x_i : array_like
X position of wind turbines
y_i : array_like
Y position of wind turbines
h_i : array_like or None, optional
Hub height of wind turbines\n
If None, default, the standard hub height is used
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type_i int, array_like, optional, default is 0
Wind turbine types\n
wd : int, float, array_like or None
Wind directions(s)\n
If None, default, the wake is calculated for site.default_wd
ws : int, float, array_like or None
Wind speed(s)\n
If None, default, the wake is calculated for site.default_ws
Returns
-------
AEP_GWh_ilk : array_like
AEP in GWh
"""
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flowModelResult = self.wake_model(x=x_i, y=y_i, h=h_i, type=type_i, wd=wd, ws=ws)
self._set_flowModelResult(flowModelResult)
return flowModelResult.aep_ilk()
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def calculate_AEP_no_wake_loss(self, x_i, y_i, h_i=None, type_i=0, wd=None, ws=None):
"""Calculate AEP without wake loss(GWh). Same input as calculate_AEP"""
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flowModelResult = self.wake_model(x=x_i, y=y_i, h=h_i, type=type_i, wd=wd, ws=ws)
self._set_flowModelResult(flowModelResult)
return flowModelResult.aep_ilk(with_wake_loss=False)
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def wake_map(self, x_j=None, y_j=None, height_level=None, wt_x=[],
wt_y=[], wt_type=0, wt_height=None, wd=None, ws=None):
"""Calculate wake(effective wind speed) map
Parameters
----------
x_j : array_like or None, optional
X position map points
y_j : array_like
Y position of map points
height_level : int, float or None, optional
Height of wake map\n
If None, default, the mean hub height is used
wt_x : array_like, optional
X position of wind turbines
wt_y : array_like, optional
Y position of wind turbines
wt_type : array_like or None, optional
Type of the wind turbines
wt_height : array_like or None, optional
Hub height of the wind turbines\n
If None, default, the standard hub height is used
wd : int, float, array_like or None
Wind directions(s)\n
If None, default, the wake is calculated for site.default_wd
ws : int, float, array_like or None
Wind speed(s)\n
If None, default, the wake is calculated for site.default_ws
Returns
-------
X_j : array_like
2d array of map x positions
Y_j : array_like
2d array of map y positions
WS_eff_avg : array_like
2d array of average effective local wind speed taking into account
the probability of wind direction and speed
See Also
--------
plot_wake_map
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sim_res = self.wake_model(x=wt_x, y=wt_y, type=wt_type, h=wt_height, wd=wd, ws=ws)
flow_map = sim_res.flow_map(HorizontalGrid(x=x_j, y=y_j, h=height_level))
X, Y = flow_map.XY
return X, Y, flow_map.WS_eff_xylk.mean(['wd', 'ws'])
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def ti_map(self, x_j=None, y_j=None, height_level=None, wt_x=[],
wt_y=[], wt_type=0, wt_height=None, wd=None, ws=None):
"""Calculate turbulence intensity map
Parameters
----------
x_j : array_like or None, optional
X position map points
y_j : array_like
Y position of map points
height_level : int, float or None, optional
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Height of wake map\n
If None, default, the mean hub height is used
wt_x : array_like, optional
X position of wind turbines
wt_y : array_like, optional
Y position of wind turbines
wt_type : array_like or None, optional
Type of the wind turbines
wt_height : array_like or None, optional
Hub height of the wind turbines\n
If None, default, the standard hub height is used
wd : int, float, array_like or None
Wind directions(s)\n
If None, default, the wake is calculated for site.default_wd
ws : int, float, array_like or None
Wind speed(s)\n
If None, default, the wake is calculated for site.default_ws
Returns
-------
X_j : array_like
2d array of map x positions
Y_j : array_like
2d array of map y positions
WS_eff_avg : array_like
2d array of average effective local wind speed taking into account
the probability of wind direction and speed
See Also
--------
plot_wake_map
"""
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sim_res = self.wake_model(x=wt_x, y=wt_y, type=wt_type, h=wt_height, wd=wd, ws=ws)
flow_map = sim_res.flow_map(HorizontalGrid(x=x_j, y=y_j, h=height_level))
X, Y = flow_map.XY
return X, Y, flow_map.TI_eff_xylk.mean(['wd', 'ws'])
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def plot_wake_map(self, x_j=None, y_j=None, h=None, wt_x=[], wt_y=[], wt_type=0, wt_height=None,
wd=None, ws=None, ax=None, levels=100):
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"""Plot wake(effective wind speed) map
Parameters
----------
x_j : array_like or None, optional
X position map points
y_j : array_like
Y position of map points
h : int, float or None, optional
Height of wake map\n
If None, default, the mean hub height is used
wt_x : array_like, optional
X position of wind turbines
wt_y : array_like, optional
Y position of wind turbines
wt_type : array_like or None, optional
Type of the wind turbines
wt_height : array_like or None, optional
Hub height of the wind turbines\n
If None, default, the standard hub height is used
wd : int, float, array_like or None
Wind directions(s)\n
If None, default, the wake is calculated for site.default_wd
ws : int, float, array_like or None
Wind speed(s)\n
If None, default, the wake is calculated for site.default_ws
ax : pyplot or matplotlib axes object, default None
Axes to plot on
levels : int or array_like
levels for pyplot.contourf
"""
import matplotlib.pyplot as plt
if ax is None:
ax = plt.gca()
X, Y, Z = self.wake_map(x_j, y_j, h, wt_x, wt_y, wt_type, wt_height, wd, ws)
c = ax.contourf(X, Y, Z, levels, cmap='Blues_r')
plt.colorbar(c, label='wind speed [m/s]')
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def aep_map(self, x_j=None, y_j=None, type_j=None, wt_x=[], wt_y=[], wt_type=0, wt_height=None, wd=None, ws=None):
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"""Calculate AEP map
The map represents the of AEP produced by a new turbine at the specified positions
Parameters
----------
x_j : array_like or None, optional
X position map points (potential turbine positions)
y_j : array_like
Y position of map points (potential turbine positions)
type_j : int, float or None, optional
Type of potential turbine positions\n
If None, default, first turbine type(0) is used
wt_x : array_like, optional
X position of the current wind turbines
wt_y : array_like, optional
Y position of the current wind turbines
wt_type : array_like or None, optional
Type of the current wind turbines
wt_height : array_like or None, optional
Hub height of the current wind turbines\n
If None, default, the standard hub height is used
wd : int, float, array_like or None
Wind directions(s)\n
If None, default, the wake is calculated for site.default_wd
ws : int, float, array_like or None
Wind speed(s)\n
If None, default, the wake is calculated for site.default_ws
Returns
-------
X_j : array_like
2d array of map x positions
Y_j : array_like
2d array of map y positions
WS_eff_avg : array_like
2d array of average effective local wind speed taking into account
the probability of wind direction and speed
"""
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h_j = self.windTurbines.hub_height(type_j)
sim_res = self.wake_model(x=wt_x, y=wt_y, type=wt_type, h=wt_height, wd=wd, ws=ws)
flow_map = sim_res.flow_map(HorizontalGrid(x=x_j, y=y_j, h=h_j))
X, Y = flow_map.XY
aep_xy = flow_map.aep_xy(normalize_probabilities=True)
return X, Y, aep_xy
if __name__ == '__main__':
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
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from py_wake import NOJ
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# setup site, turbines and flow model
site = IEA37Site(16)
x, y = site.initial_position.T
windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
wake_model = NOJ(site, windTurbines)
# calculate AEP
aep_calculator = AEPCalculator(wake_model)
aep = aep_calculator.calculate_AEP(x, y)[0].sum()
print(aep_calculator.WS_eff_ilk.shape)
# 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()