Add ktho's standard power curve model

wetb/standard_models/power_curve.py

+import numpy as np
+
+
+def standard_power_curve(power_norm, diameter, turbulence_intensity=.1, shear=(0, 100),
+                         rho=1.225, max_cp=.49,
+                         gear_loss_const=.01, gear_loss_var=.014, generator_loss=0.03, converter_loss=.03):
+    """Generate standard power curve
+
+    The method is extracted from an Excel spreadsheet made by Kenneth Thomsen, DTU Windenergy and
+    ported into python by Mads M. Pedersen, DTU Windenergy.
+
+    Parameters
+    ----------
+    power_norm : int or float
+        Nominal power [kW]
+    diameter : int or float
+        Rotor diameter [m]
+    turbulence_intensity : float
+        Turbulence intensity [%]
+    shear : (power shear coefficient, hub height)
+        Power shear arguments\n
+        - Power shear coeficient, alpha\n
+        - Hub height [m]
+    rho : float optional
+        Density of air [kg/m^3], defualt is 1.225
+    max_cp : float
+        Maximum power coefficient
+    gear_loss_const : float
+        Constant gear loss [%]
+    gear_loss_var : float
+        Variable gear loss [%]
+    generator_loss : float
+        Generator loss [%]
+    converter_loss : float
+
+    Examples
+    --------
+    wsp, power = standard_power_curve(10000, 178.3)
+    plot(wsp, power)
+    show()
+    """
+
+
+    area = (diameter / 2) ** 2 * np.pi
+    wsp_lst = np.arange(0.5, 25, .5)
+    sigma_lst = wsp_lst * turbulence_intensity
+
+    def norm_dist(x, my, sigma):
+        if turbulence_intensity > 0:
+            return 1 / np.sqrt(2 * np.pi * sigma ** 2) * np.exp(-(x - my) ** 2 / (2 * sigma ** 2))
+        else:
+            return x == my
+    p_aero = .5 * rho * area * wsp_lst ** 3 * max_cp / 1000
+
+    # calc power - gear, generator and conv loss
+#     gear_loss = gear_loss_const * power_norm + gear_loss_var * p_aero
+#     p_gear = p_aero - gear_loss
+#     p_gear[p_gear < 0] = 0
+#     gen_loss = generator_loss * p_gear
+#     p_gen = p_gear - gen_loss
+#     converter_loss = converter_loss * p_gen
+#     p_raw = p_gen - converter_loss
+#     p_raw[p_raw > power_norm] = power_norm
+    p_raw = p_aero - power_loss(p_aero, power_norm, gear_loss_const, gear_loss_var, generator_loss, converter_loss)
+
+    powers = []
+    shear_weighted_wsp = []
+    alpha, hub_height = shear
+    r = diameter / 2
+    z = np.linspace(hub_height - r, hub_height + r, 100, endpoint=True)
+    shear_factors = (z / hub_height) ** alpha
+    rotor_width = 2 * np.sqrt(r ** 2 - (hub_height - z) ** 2)
+
+    for wsp, sigma in zip(wsp_lst, sigma_lst):
+        shear_weighted_wsp.append(wsp * (np.trapz(shear_factors ** 3 * rotor_width, z) / (area)) ** (1 / 3))
+        ndist = norm_dist(wsp_lst, wsp, sigma)
+        powers.append((ndist * p_raw).sum() / ndist.sum())
+
+    return wsp_lst, lambda wsp : np.interp(wsp, wsp_lst, powers)
+    return wsp_lst, np.interp(shear_weighted_wsp, wsp_lst, powers)
+
+def power_loss(power_aero, power_norm, gear_loss_const=.01, gear_loss_var=.014, generator_loss=0.03, converter_loss=.03):
+    gear_loss = gear_loss_const * power_norm + gear_loss_var * power_aero
+    p_gear = power_aero - gear_loss
+    p_gear[p_gear < 0] = 0
+    gen_loss = generator_loss * p_gear
+    p_gen = p_gear - gen_loss
+    converter_loss = converter_loss * p_gen
+    p_electric = p_gen - converter_loss
+    p_electric[p_electric > power_norm] = power_norm
+    return power_aero - p_electric
+    
+
+if __name__ == '__main__':
+
+
+    from matplotlib.pyplot import plot, show
+    plot(*standard_power_curve(10000, 178.3, 0., (0, 119), gear_loss_const=.0, gear_loss_var=.0, generator_loss=0.0, converter_loss=.0))
+    plot(*standard_power_curve(10000, 178.3, 0.03, (0, 119), gear_loss_const=.0, gear_loss_var=.0, generator_loss=0.0, converter_loss=.0))
+
+
+
+
+    show()