GeneralWindFarmComponents.py 文件源码

def linearize(self, params, unknowns, resids):  # standard central differencing
        # set step size for finite differencing
        h = 1e-6
        direction_id = self.direction_id

        # calculate upper and lower function values
        wind_speed_ax_high_yaw = np.cos((self.params['yaw%i' % direction_id]+h)*np.pi/180.0)**(self.params['gen_params:pP']/3.0)*self.params['wtVelocity%i' % direction_id]
        wind_speed_ax_low_yaw = np.cos((self.params['yaw%i' % direction_id]-h)*np.pi/180.0)**(self.params['gen_params:pP']/3.0)*self.params['wtVelocity%i' % direction_id]
        wind_speed_ax_high_wind = np.cos(self.params['yaw%i' % direction_id]*np.pi/180.0)**(self.params['gen_params:pP']/3.0)*(self.params['wtVelocity%i' % direction_id]+h)
        wind_speed_ax_low_wind = np.cos(self.params['yaw%i' % direction_id]*np.pi/180.0)**(self.params['gen_params:pP']/3.0)*(self.params['wtVelocity%i' % direction_id]-h)

        # use interpolation on precalculated CP-CT curve
        wind_speed_ax_high_yaw = np.maximum(wind_speed_ax_high_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'][0])
        wind_speed_ax_low_yaw = np.maximum(wind_speed_ax_low_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'][0])
        wind_speed_ax_high_wind = np.maximum(wind_speed_ax_high_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'][0])
        wind_speed_ax_low_wind = np.maximum(wind_speed_ax_low_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'][0])

        wind_speed_ax_high_yaw = np.minimum(wind_speed_ax_high_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'][-1])
        wind_speed_ax_low_yaw = np.minimum(wind_speed_ax_low_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'][-1])
        wind_speed_ax_high_wind = np.minimum(wind_speed_ax_high_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'][-1])
        wind_speed_ax_low_wind = np.minimum(wind_speed_ax_low_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'][-1])

        CP_high_yaw = interp(wind_speed_ax_high_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CP'])
        CP_low_yaw = interp(wind_speed_ax_low_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CP'])
        CP_high_wind = interp(wind_speed_ax_high_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CP'])
        CP_low_wind = interp(wind_speed_ax_low_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CP'])

        CT_high_yaw = interp(wind_speed_ax_high_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CT'])
        CT_low_yaw = interp(wind_speed_ax_low_yaw, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CT'])
        CT_high_wind = interp(wind_speed_ax_high_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CT'])
        CT_low_wind = interp(wind_speed_ax_low_wind, self.params['gen_params:windSpeedToCPCT_wind_speed'], self.params['gen_params:windSpeedToCPCT_CT'])

        # normalize on incoming wind speed to correct coefficients for yaw
        CP_high_yaw = CP_high_yaw * np.cos((self.params['yaw%i' % direction_id]+h)*np.pi/180.0)**self.params['gen_params:pP']
        CP_low_yaw = CP_low_yaw * np.cos((self.params['yaw%i' % direction_id]-h)*np.pi/180.0)**self.params['gen_params:pP']
        CP_high_wind = CP_high_wind * np.cos((self.params['yaw%i' % direction_id])*np.pi/180.0)**self.params['gen_params:pP']
        CP_low_wind = CP_low_wind * np.cos((self.params['yaw%i' % direction_id])*np.pi/180.0)**self.params['gen_params:pP']

        CT_high_yaw = CT_high_yaw * np.cos((self.params['yaw%i' % direction_id]+h)*np.pi/180.0)**2
        CT_low_yaw = CT_low_yaw * np.cos((self.params['yaw%i' % direction_id]-h)*np.pi/180.0)**2
        CT_high_wind = CT_high_wind * np.cos((self.params['yaw%i' % direction_id])*np.pi/180.0)**2
        CT_low_wind = CT_low_wind * np.cos((self.params['yaw%i' % direction_id])*np.pi/180.0)**2

        # compute derivative via central differencing and arrange in sub-matrices of the Jacobian
        dCP_dyaw = np.eye(self.nTurbines)*(CP_high_yaw-CP_low_yaw)/(2.0*h)
        dCP_dwind = np.eye(self.nTurbines)*(CP_high_wind-CP_low_wind)/(2.0*h)
        dCT_dyaw = np.eye(self.nTurbines)*(CT_high_yaw-CT_low_yaw)/(2.0*h)
        dCT_dwind = np.eye(self.nTurbines)*(CT_high_wind-CT_low_wind)/(2.0*h)

        # compile Jacobian dict from sub-matrices
        J = {}
        J['Cp_out', 'yaw%i' % direction_id] = dCP_dyaw
        J['Cp_out', 'wtVelocity%i' % direction_id] = dCP_dwind
        J['Ct_out', 'yaw%i' % direction_id] = dCT_dyaw
        J['Ct_out', 'wtVelocity%i' % direction_id] = dCT_dwind

        return J