import pandas as pd import numpy as np import chardet from algorithmContract.confBusiness import * class CommonBusiness: def getFloat32(self): return "float32" def isNone(self, value): return value is None def getUseColumns(self, confData: ConfBusiness): useColumns = [] if not self.isNone(confData.field_turbine_time): useColumns.append(confData.field_turbine_time) if not self.isNone(confData.field_turbine_name): useColumns.append(confData.field_turbine_name) if not self.isNone(confData.field_wind_speed): useColumns.append(confData.field_wind_speed) if not self.isNone(confData.field_power): useColumns.append(confData.field_power) if not self.isNone(confData.field_pitch_angle1): useColumns.append(confData.field_pitch_angle1) if not self.isNone(confData.field_rotor_speed): useColumns.append(confData.field_rotor_speed) if not self.isNone(confData.field_gen_speed): useColumns.append(confData.field_gen_speed) if not self.isNone(confData.field_torque): useColumns.append(confData.field_torque) if not self.isNone(confData.field_wind_dir): useColumns.append(confData.field_wind_dir) if not self.isNone(confData.field_angle_included): useColumns.append(confData.field_angle_included) if not self.isNone(confData.field_nacelle_pos): useColumns.append(confData.field_nacelle_pos) if not self.isNone(confData.field_env_temp): useColumns.append(confData.field_env_temp) if not self.isNone(confData.field_nacelle_temp): useColumns.append(confData.field_nacelle_temp) if not self.isNone(confData.field_turbine_state): useColumns.append(confData.field_turbine_state) if not self.isNone(confData.field_Cabin_Vibrate_X): useColumns.append(confData.field_Cabin_Vibrate_X) if not self.isNone(confData.field_Cabin_Vibrate_Y): useColumns.append(confData.field_Cabin_Vibrate_Y) if not self.isNone(confData.field_activePowerSet): useColumns.append(confData.field_activePowerSet) if not self.isNone(confData.field_activePowerAvailable): useColumns.append(confData.field_activePowerAvailable) if not self.isNone(confData.field_temperature_large_components): temperature_cols = confData.field_temperature_large_components.split( ',') for temperatureColumn in temperature_cols: useColumns.append(temperatureColumn) return useColumns def recalculationOfGeneratorSpeedforShow(self, dataFrame: pd.DataFrame, confData: ConfBusiness): if not self.isNone(confData.value_gen_speed_multiple) and confData.field_gen_speed in dataFrame.columns: dataFrame[confData.field_gen_speed] = dataFrame[confData.field_gen_speed] * \ confData.value_gen_speed_multiple dataFrame[Field_GeneratorTorque] = dataFrame[confData.field_gen_speed] def contractGuaranteePowerCurveData(self, csvPowerCurveFilePath, confData: ConfBusiness): with open(csvPowerCurveFilePath, 'rb') as f: result = chardet.detect(f.read()) dataFrameGuaranteePowerCurve = pd.read_csv(csvPowerCurveFilePath, encoding= result['encoding'] ) return dataFrameGuaranteePowerCurve def calculateTSR(self, dataFrame: pd.DataFrame, confData: ConfBusiness): """ 使用叶轮/主轴转速、风速、叶轮直径，计算叶尖速比(TSR) """ # Calculate tsr if not self.isNone(confData.rotor_diameter) \ and not self.isNone(confData.field_wind_speed) and confData.field_wind_speed in dataFrame.columns \ and not self.isNone(confData.field_rotor_speed) and confData.field_rotor_speed in dataFrame.columns: dataFrame[confData.field_rotor_speed] = pd.to_numeric( dataFrame[confData.field_rotor_speed], errors='coerce') dataFrame[confData.field_wind_speed] = pd.to_numeric( dataFrame[confData.field_wind_speed], errors='coerce') rotor_diameter = pd.to_numeric( confData.rotor_diameter, errors='coerce') dataFrame[Field_PowerFloor] = dataFrame[confData.field_power].apply( lambda x: int(x / 10) * 10 if pd.notnull(x) else np.nan # 保留NaN值 ) dataFrame[Field_TSR] = (dataFrame[confData.field_rotor_speed] * 0.104667 * (rotor_diameter / 2)) / dataFrame[confData.field_wind_speed] def calculateCp2(self,dataFrame: pd.DataFrame,airDensity,rotorDiameter,fieldWindSpeed,fieldActivePower): """ 使用有功功率、风速、空气密度、叶轮直径，计算风能利用系数(Cp) """ # Calculate cp if not self.isNone(airDensity) and not self.isNone(rotorDiameter) \ and not self.isNone(fieldWindSpeed) and fieldWindSpeed in dataFrame.columns \ and not self.isNone(fieldActivePower) and fieldActivePower in dataFrame.columns: dataFrame[fieldActivePower] = pd.to_numeric( dataFrame[fieldActivePower], errors='coerce') dataFrame[fieldWindSpeed] = pd.to_numeric( dataFrame[fieldWindSpeed], errors='coerce') rotor_diameter = pd.to_numeric( rotorDiameter, errors='coerce') air_density = pd.to_numeric(airDensity, errors='coerce') dataFrame[Field_PowerFloor] = dataFrame[fieldActivePower].apply( lambda x: int(x / 10) * 10 if pd.notnull(x) else np.nan # 保留NaN值 ) dataFrame[Field_Cp] = dataFrame[fieldActivePower] * 1000 / \ (0.5 * np.pi * air_density * (rotor_diameter ** 2) / 4 * dataFrame[fieldWindSpeed] ** 3) def calculateCp(self, dataFrame: pd.DataFrame, confData: ConfBusiness): """ 使用有功功率、风速、空气密度、叶轮直径，计算风能利用系数(Cp) """ self.calculateCp2(dataFrame,confData.density_air,confData.rotor_diameter,confData.field_wind_speed,confData.field_power) # # Calculate cp # if not self.isNone(confData.density_air) and not self.isNone(confData.rotor_diameter) \ # and not self.isNone(confData.field_wind_speed) and confData.field_wind_speed in dataFrame.columns \ # and not self.isNone(confData.field_power) and confData.field_power in dataFrame.columns: # dataFrame[confData.field_power] = pd.to_numeric( # dataFrame[confData.field_power], errors='coerce') # dataFrame[confData.field_wind_speed] = pd.to_numeric( # dataFrame[confData.field_wind_speed], errors='coerce') # rotor_diameter = pd.to_numeric( # confData.rotor_diameter, errors='coerce') # air_density = pd.to_numeric(confData.density_air, errors='coerce') # dataFrame[Field_PowerFloor] = dataFrame[confData.field_power].apply( # lambda x: int(x / 10) * 10 if pd.notnull(x) else np.nan # 保留NaN值 # ) # dataFrame[Field_Cp] = dataFrame[confData.field_power] * 1000 / \ # (0.5 * np.pi * air_density * # (rotor_diameter ** 2) / 4 * dataFrame[confData.field_wind_speed] ** 3)