import numpy as np
class WindTurbines():
"""Set of wind turbines"""
def __init__(self, names, diameters, hub_heights, ct_funcs, power_funcs, power_unit):
"""Initialize WindTurbines
Parameters
----------
names : array_like
Wind turbine names
diameters : array_like
Diameter of wind turbines
hub_heights : array_like
Hub height of wind turbines
ct_funcs : list of functions
Wind turbine ct functions; func(ws) -> ct
power_funcs : list of functions
Wind turbine power functions; func(ws) -> power
power_unit : {'W', 'kW', 'MW', 'GW'}
Unit of power_func output (case insensitive)
"""
self._names = names
self._diameters = np.array(diameters)
self._hub_heights = np.array(hub_heights)
self.ct_funcs = ct_funcs
self.power_scale = {'w': 1, 'kw': 1e3, 'mw': 1e6, 'gw': 1e9}[power_unit.lower()]
if self.power_scale != 1:
self.power_funcs = list([lambda ws, f=f: f(ws) * self.power_scale for f in power_funcs])
else:
self.power_funcs = power_funcs
def _info(self, var, types):
return var[np.asarray(types, np.int)]
def hub_height(self, types=0):
"""Hub height of the specified type(s) of wind turbines
"""
return self._info(self._hub_heights, types)
def diameter(self, types=0):
"""Rotor diameter of the specified type(s) of wind turbines
"""
return self._info(self._diameters, types)
def name(self, types=0):
"""Name of the specified type(s) of wind turbines
"""
return self._info(self._names, types)
def power(self, ws_i, type_i=0):
"""Power in watt
Parameters
----------
ws_i : array_like, shape (i,...)
Wind speed
type_i : int or array_like, shape (i,)
wind turbine type
Returns
-------
power : array_like
Power production for the specified wind turbine type(s) and wind speed
"""
return self._ct_power(ws_i, type_i)[1]
def ct(self, ws_i, type_i=0):
"""Trust coefficient
Parameters
----------
ws_i : array_like, shape (i,...)
Wind speed
type_i : int or array_like, shape (i,)
wind turbine type
Returns
-------
ct : array_like
Trust coefficient for the specified wind turbine type(s) and wind speed
"""
return self._ct_power(ws_i, type_i)[0]
def _ct_power(self, ws_i, type_i=0):
if np.any(type_i != 0):
CT = np.zeros_like(ws_i)
P = np.zeros_like(ws_i)
for t in np.unique(type_i):
m = type_i == t
CT[m] = self.ct_funcs[t](ws_i[m])
P[m] = self.power_funcs[t](ws_i[m])
return CT, P
else:
return self.ct_funcs[0](ws_i), self.power_funcs[0](ws_i)
def plot(self, x, y, types=None, ax=None):
"""Plot wind farm layout including type name and diameter
Parameters
----------
x : array_like
x position of wind turbines
y : array_like
y position of wind turbines
types : int or array_like
type of the wind turbines
ax : pyplot or matplotlib axes object, default None
"""
import matplotlib.pyplot as plt
if types is None:
types = np.zeros_like(x)
if ax is None:
ax = plt.gca()
markers = np.array(list("213v^<>o48spP*hH+xXDd|_"))
from matplotlib.patches import Circle
assert len(x) == len(y)
types = np.zeros_like(x) + types # ensure same length as x
for i, (x_, y_, d) in enumerate(zip(x, y, self.diameter(types))):
circle = Circle((x_, y_), d / 2, color='gray', alpha=.5)
ax.add_artist(circle)
for t, m in zip(np.unique(types), markers):
ax.plot(np.asarray(x)[types == t], np.asarray(y)[types == t], '%sk' % m, label=self._names[int(t)])
for i, (x_, y_, d) in enumerate(zip(x, y, self.diameter(types))):
ax.annotate(i, (x_ + d / 2, y_ + d / 2), fontsize=7)
ax.legend(loc=1)
ax.axis('equal')
class OneTypeWindTurbines(WindTurbines):
def __init__(self, name, diameter, hub_height, ct_func, power_func, power_unit):
"""Initialize OneTypeWindTurbine
Parameters
----------
name : str
Wind turbine name
diameter : int or float
Diameter of wind turbine
hub_height : int or float
Hub height of wind turbine
ct_func : function
Wind turbine ct function; func(ws) -> ct
power_func : function
Wind turbine power function; func(ws) -> power
power_unit : {'W', 'kW', 'MW', 'GW'}
Unit of power_func output (case insensitive)
"""
WindTurbines.__init__(self, [name], [diameter], [hub_height],
[lambda ws: ct_func(ws)],
[lambda ws: power_func(ws)],
power_unit)
def cube_power(ws_cut_in, ws_cut_out, ws_rated, power_rated):
def power_func(ws):
ws = np.asarray(ws)
power = np.zeros_like(ws, dtype=np.float)
m = (ws > ws_cut_in) & (ws < ws_rated)
power[m] = power_rated * ((ws[m] - ws_cut_in) / (ws_rated - ws_cut_in))**3
power[(ws >= ws_rated) & (ws <= ws_cut_out)] = power_rated
return power
return power_func
def main():
if __name__ == '__main__':
wts = WindTurbines(names=['tb1', 'tb2'],
diameters=[80, 120],
hub_heights=[70, 110],
ct_funcs=[lambda _: 8 / 9,
lambda _: 8 / 9],
power_funcs=[cube_power(ws_cut_in=3, ws_cut_out=25, ws_rated=12, power_rated=2000),
cube_power(ws_cut_in=3, ws_cut_out=25, ws_rated=12, power_rated=3000)],
power_unit='kW')
ws = np.arange(25)
import matplotlib.pyplot as plt
power = wts.power(ws)
plt.plot(ws, power, label=wts.name(0))
plt.legend()
plt.show()
wts.plot([0, 100], [0, 100], [0, 1])
plt.xlim([-50, 150])
plt.ylim([-50, 150])
plt.show()
main()