Newer
Older
from py_wake.wind_turbines._wind_turbines import WindTurbine
from py_wake.wind_turbines.power_ct_functions import SimpleYawModel, PowerCtTabular, PowerCtNDTabular
import numpy as np
from py_wake.utils.generic_power_ct_curves import standard_power_ct_curve
class GenericWindTurbine(WindTurbine):
def __init__(self, name, diameter, hub_height, power_norm, turbulence_intensity=.1,
air_density=1.225, max_cp=.49, constant_ct=.8,
gear_loss_const=.01, gear_loss_var=.014, generator_loss=0.03, converter_loss=.03,
Mads M. Pedersen
committed
ws_lst=np.arange(.1, 30, .1), ws_cutin=None,
ws_cutout=None, power_idle=0, ct_idle=None, method='linear',
additional_models=[SimpleYawModel()]):
"""Wind turbine with generic standard power curve based on max_cp, rated power and losses.
Ct is computed from the basic 1d momentum theory
Parameters
----------
name : str
Wind turbine name
diameter : int or float
Diameter of wind turbine
power_norm : int or float
Nominal power [kW]
diameter : int or float
Rotor diameter [m]
turbulence_intensity : float
Turbulence intensity
air_density : float optional
Density of air [kg/m^3], defualt is 1.225
max_cp : float
Maximum power coefficient
constant_ct : float, optional
Ct value in constant-ct region
gear_loss_const : float
Constant gear loss [%]
gear_loss_var : float
Variable gear loss [%]
generator_loss : float
Generator loss [%]
converter_loss : float
converter loss [%]
Mads M. Pedersen
committed
ws_lst : array_like
List of wind speeds. The power/ct tabular will be calculated for these wind speeds
ws_cutin : number or None, optional
if number, then the range [0,ws_cutin[ will be set to power_idle and ct_idle
ws_cutout : number or None, optional
if number, then the range ]ws_cutout,100] will be set to power_idle and ct_idle
power_idle : number, optional
see ws_cutin and ws_cutout
ct_idle : number, optional
see ws_cutin and ws_cutout
method : {'linear', 'phip','spline}
Interpolation method:\n
- linear: fast, discontinous gradients\n
- pchip: smooth\n
- spline: smooth, closer to linear, small overshoots in transition to/from constant plateaus)
additional_models : list, optional
list of additional models.
"""
u, p, ct = standard_power_ct_curve(power_norm, diameter, turbulence_intensity, air_density, max_cp, constant_ct,
Mads M. Pedersen
committed
gear_loss_const, gear_loss_var, generator_loss, converter_loss, ws_lst)
if ws_cutin is not None:
u, p, ct = [v[u >= ws_cutin] for v in [u, p, ct]]
if ws_cutout is not None:
u, p, ct = [v[u <= ws_cutout] for v in [u, p, ct]]
if ct_idle is None:
ct_idle = ct[-1]
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
powerCtFunction = PowerCtTabular(u, p * 1000, 'w', ct, ws_cutin=ws_cutin, ws_cutout=ws_cutout,
power_idle=power_idle, ct_idle=ct_idle, method=method,
additional_models=additional_models)
WindTurbine.__init__(self, name, diameter, hub_height, powerCtFunction)
class GenericTIRhoWindTurbine(WindTurbine):
def __init__(self, name, diameter, hub_height, power_norm,
TI_eff_lst=np.linspace(0, .5, 6), default_TI_eff=.1,
Air_density_lst=np.linspace(.9, 1.5, 5), default_Air_density=1.225,
max_cp=.49, constant_ct=.8,
gear_loss_const=.01, gear_loss_var=.014, generator_loss=0.03, converter_loss=.03,
wsp_lst=np.arange(.1, 30, .5),
additional_models=[SimpleYawModel()]):
"""Wind turbine with generic standard power curve based on max_cp, rated power and losses.
Ct is computed from the basic 1d momentum theory
The power and ct curves depends on turbulence intensity(TI_eff) and air density(Air_density)
Parameters
----------
name : str
Wind turbine name
diameter : int or float
Diameter of wind turbine
power_norm : int or float
Nominal power [kW]
diameter : int or float
Rotor diameter [m]
TI_eff_lst : array_like
List of turbulence intensities to include in tabular
default_TI_eff : float, optional
Default turbulence intensity, default is 10%
Air_density_lst : array_like
List of air densities [kg/m^3] to include in tabular
default_Air_density : float, optional
Default air_density [kg/m^3], defualt is 1.225
max_cp : float
Maximum power coefficient
constant_ct : float, optional
Ct value in constant-ct region
gear_loss_const : float
Constant gear loss [%]
gear_loss_var : float
Variable gear loss [%]
generator_loss : float
Generator loss [%]
converter_loss : float
converter loss [%]
additional_models : list, optional
list of additional models.
"""
data = np.moveaxis([[standard_power_ct_curve(power_norm, diameter, ti, rho, max_cp, constant_ct, gear_loss_const,
gear_loss_var, generator_loss, converter_loss, wsp_lst)[1:]
for rho in Air_density_lst]
for ti in TI_eff_lst], -1, 0)
p = data[:, :, :, 0]
ct = data[:, :, :, 1]
powerCtFunction = PowerCtNDTabular(
input_keys=['ws', 'TI_eff', 'Air_density'],
value_lst=[wsp_lst, TI_eff_lst, Air_density_lst],
power_arr=p * 1000, power_unit='w', ct_arr=ct,
Mads M. Pedersen
committed
default_value_dict={k: v for k, v in [('TI_eff', default_TI_eff), ('Air_density', default_Air_density)]
if v is not None},
additional_models=additional_models)
WindTurbine.__init__(self, name, diameter, hub_height, powerCtFunction)