from CoolProp.HumidAirProp import HAPropsSI from temp_humid_cal.excess_temp_modify import ExcessTempModify from temp_humid_cal.interval_start_stop_AHU import IntervalOnOffAHU from data_initialize_standard.constant import * # from logs_conf.logger import * from logs.logger import * import pandas as pd import time class TempHumiFunction(object): def __init__(self, terminal_data, code_data, chiller_outer): self.data = terminal_data self.config = code_data # self.modify = modify_data self.chiller_outer = chiller_outer self.chiller_mode = code_data['runMode'] def terminal_limit_cal(self, data): """ 监测点的限值计算 :param data: :param dict_code: :return: """ if self.chiller_mode == 0: data['tempLimit'] = data['coolingTempUpper'] - self.config['tempMargin'] data['humiLimit'] = data['coolingHumiUpper'] - self.config['humiMargin'] elif self.chiller_mode == 1: data['tempLimit'] = data['heatingTempDown'] + self.config['tempMargin'] else: logger.critical("============冷机运行模式输入错误============") return data def delta_temp_humi(self, data): if self.chiller_mode == 0: data['deltaTemp'] = data['tempLimit'] - data['tempReal'] data['deltaHumi'] = data['humiLimit'] - data['humiReal'] elif self.chiller_mode == 1: data['deltaTemp'] = data['tempReal'] - data['tempLimit'] data['deltaHumi'] = None else: logger.critical("============冷机运行模式输入错误============") return data def delta_dew_point(self, data): normal_condition = (data['tempReal'] <= TerminalTempRange['upperLimit']) & (data['tempReal'] > TerminalTempRange['lowerLimit']) & \ (data['humiReal'] <= TerminalHumiRange['upperLimit']) & (data['humiReal'] > TerminalHumiRange['lowerLimit']) data_normal = data[normal_condition] # 筛选出温度和湿度范围在正常区间的数据，避免异常数据（如空值或极大值）调物性时出错 data_abnormal = data.drop(data_normal.index) if self.chiller_mode == 0 and not data_normal.empty: data_normal.loc[:, ['dewTempReal']] = round(data_normal.apply( lambda x: HAPropsSI('D', 'T', x['tempReal'] + 273.15, 'P', 101325, 'R', x['humiReal'] / 100.0), axis=1) - 273.15, 1) data_normal.loc[:, ['dewTempLimit']] = round(data_normal.apply( lambda x: HAPropsSI('D', 'T', x['tempLimit'] + 273.15, 'P', 101325, 'R', x['humiLimit'] / 100.0), axis=1) - 273.15, 1) data_normal.loc[:, ['deltaDewPoint']] = data_normal['dewTempLimit'] - data_normal['dewTempReal'] if not data_abnormal.empty: data_abnormal['dewTempReal'] = None data_abnormal['dewTempLimit'] = None data_abnormal['deltaDewPoint'] = None data = pd.concat([data_normal, data_abnormal]) return data def excess_modify(self, terminal_data): data = self.delta_temp_humi(terminal_data) excess_condition = (data['deltaTemp'] < 0) | (data['deltaHumi'] < 0) # 温度或湿度超限的判断条件 terminal_excess = data[excess_condition] # 温度或湿度超限的监测点 terminal_remain = data[~excess_condition] # 未超限的监测点 if not terminal_excess.empty: logger.critical("============存在监测点超限情况，开始温湿度限值修正计算============") etm = ExcessTempModify(terminal_excess, self.config, self.chiller_outer) # terminal_excess 超标的监测点数据 if etm.data_judge(): logger.critical("============监测点修正相关数据正常，进入修正计算============") Time1 = time.time() terminal_excess = etm.get_modified_air_temp_humi() # 温湿度计算 Time2 = time.time() logger.critical("============温湿度超标点限值修正计算耗时: {}s ============".format(Time2 - Time1)) else: logger.critical("============监测点修正相关数据异常，退出温湿度限值修正计算============") else: logger.critical("============不存在温度或湿度超限情况，温湿度上下限不修正============") data = pd.concat([terminal_excess, terminal_remain]) return data def average_temp_humi(self, data_temp_humi): temp_mean = data_temp_humi["tempReal"].mean() humi_mean = data_temp_humi["humiReal"].mean() data_mean = {"tempHumiMeterId": "average", "terminalName": "average", "coolingTempUpper": 25, "coolingHumiUpper": 60, "heatingTempDown": 29} # 这里的上下限值实际取平均限值配置值，当前不适配写死 if self.chiller_mode == 0: data_mean['tempLimit'] = data_mean['coolingTempUpper'] - self.config['tempMargin'] data_mean['humiLimit'] = data_mean['coolingHumiUpper'] - self.config['humiMargin'] data_mean['deltaTemp'] = data_mean['tempLimit'] - temp_mean data_mean['deltaHumi'] = data_mean['humiLimit'] - humi_mean elif self.chiller_mode == 1: data_mean['tempLimit'] = data_mean['heatingTempDown'] + self.config['tempMargin'] data_mean['deltaTemp'] = data_mean['tempReal'] - data_mean['tempLimit'] data_mean['deltaHumi'] = None else: logger.critical("============冷机运行模式输入错误============") data_mean_df = pd.DataFrame([data_mean]) if self.config['calMode'] == 1: data = data_mean_df else: data = pd.concat([data_temp_humi, data_mean_df]) return data def temp_humi_cal(self): data_temp_humi = self.terminal_limit_cal(self.data) # 确定监测点的上下限值 if self.config['calMode'] == 0 or self.config['calMode'] == 2: # 监测点计算模式为常规或者综合 if self.config['energyMode'] == 0: # 0为智能节能模式，1为需求优先模式 logger.critical("============智控模式为智能节能模式，进入温湿度上下限修正计算============") data_temp_humi = self.excess_modify(data_temp_humi) else: logger.critical("============智控模式为需求优先模式，温湿度上下限不修正============") data_temp_humi = self.delta_temp_humi(data_temp_humi) data_temp_humi = self.delta_dew_point(data_temp_humi) ioa = IntervalOnOffAHU(data_temp_humi, self.config) data_temp_humi = ioa.exclude_ahu_short_time() if self.config['calMode'] == 1 or self.config['calMode'] == 2: # 监测点计算模式为仅平均温湿度或者综合 logger.critical("============监测点计算模式为仅平均温湿度或综合模式，进入平均温湿度计算============") data_temp_humi = self.average_temp_humi(data_temp_humi) return data_temp_humi class JudgeOutRange(object): def __init__(self, data_temp_humi, dict_code): self.data = data_temp_humi self.config = dict_code self.chiller_mode = dict_code['runMode'] def is_out_of_range(self): """制冷模式根据 控制依据 配置项判断 温度、露点或湿度是否超标，制热模式下只判断温度是否超标""" results = {'isOutRange': '', 'minDelta': '', 'minName': ''} # 分别代表是否超标，最不利监测点对应值，最不利监测点名称 if self.chiller_mode == 0 and self.config['controlBasis'] == 0: # 制冷模式，控制依据，0为仅温度，1为仅湿度，2为温度和湿度 if self.data['deltaTemp'].min() < 0: results['isOutRange'] = 1 # 1表示温度超标 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：温度超标，最不利监测点是 %s============" % (results['minName'])) elif self.data['deltaDewPoint'].min() < 0: results['isOutRange'] = 2 # 2表示露点超标 results['minName'] = self.data.loc[self.data['deltaDewPoint'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：露点超标，最不利监测点是 %s============" % (results['minName'])) else: if (self.data['deltaTemp'].min() is None) or pd.isna(self.data['deltaTemp'].min()): logger.critical("============监测点超标情况：监测点输入数据异常============") else: results['isOutRange'] = 0 # 0表示不超标 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：无超标情况，最不利监测点是 %s============" % (results['minName'])) elif self.chiller_mode == 0 and self.config['controlBasis'] == 1: if self.data['deltaHumi'].min() < 0: results['isOutRange'] = 3 # 3表示湿度超标 results['minName'] = self.data.loc[self.data['deltaHumi'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：湿度超标，最不利监测点是 %s============" % (results['minName'])) else: if (self.data['deltaHumi'].min() is None) or pd.isna(self.data['deltaHumi'].min()): logger.critical("============监测点超标情况：监测点输入数据异常============") else: results['isOutRange'] = 0 # 0表示不超标 results['minName'] = self.data.loc[self.data['deltaHumi'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：无超标情况，最不利监测点是 %s============" % (results['minName'])) elif self.chiller_mode == 0 and self.config['controlBasis'] == 2: if self.data['deltaTemp'].min() < 0: results['isOutRange'] = 1 # 1表示温度超标 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：温度超标，最不利监测点是 %s============" % (results['minName'])) elif self.data['deltaHumi'].min() < 0: results['isOutRange'] = 3 # 3表示湿度超标 results['minName'] = self.data.loc[self.data['deltaHumi'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：湿度超标，最不利监测点是 %s============" % (results['minName'])) else: if (self.data['deltaTemp'].min() is None) or pd.isna(self.data['deltaTemp'].min() is None): logger.critical("============监测点超标情况：监测点输入数据异常============") else: results['isOutRange'] = 0 # 0表示不超标 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：无超标情况，最不利监测点是 %s============" % (results['minName'])) elif self.chiller_mode == 1: if self.data['deltaTemp'].min() < 0: results['isOutRange'] = 1 # 1表示超标, 0表示不超标 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：温度超标，最不利监测点是 %s============" % (results['minName'])) else: if (self.data['deltaTemp'].min() is None) or pd.isna(self.data['deltaTemp'].min()): logger.critical("============监测点超标情况：监测点输入数据异常============") else: results['isOutRange'] = 0 results['minName'] = self.data.loc[self.data['deltaTemp'].idxmin(), 'ahuName'] logger.critical("============监测点超标情况：温度超标，最不利监测点是 %s============" % (results['minName'])) else: logger.critical("============冷机运行模式输入错误============") return results # if __name__ == '__main__': # # # 监测点的实时数据 # data_df_cal = pd.DataFrame({ # "tempHumiMeterId": ["3000638", "3000694", "3000691", "3000692", "3000693"], # "terminalName": ["监测点A", "监测点B", "监测点C", "监测点D", "监测点E"], # 'ahuStartTime': ["2025-4-10 23:00:00", "2025-4-10 23:00:00", "2025-4-10 23:00:00", # "2025-4-10 23:00:00", "2025-4-10 23:00:00"], # "coolingTempUpper": [25.0, 26.0, 25, 25, 25], # "coolingHumiUpper": [60.0, 65.0, 65, 65, 65], # "heatingTempDown": [18.0, 17.5, 24, 24, 26], # # "tempReal": [None, None, None, None, None], # "tempReal": [24.5, 25.3, 24, 20, 20], # "humiReal": [50, 50, 50, 50, 50], # # "humiReal": [None, None, None, None, None], # }) # # station_data_ = {"chilledWaterMainTempOut": [7, 7, 7], # 'timeIndex': ["2025-4-3 12:00:00", "2025-4-4 12:00:00", "2025-4-5 12:00:00"]} # # sensor_data_ = { # "3000638": {"name": "sensor1", "tempReal": [10, 20, 30], "humiReal": [10, 20, 30], "tempSupply": [1, 2, 3]}, # "3000694": {"name": "sensor2", "tempReal": [10, 20, 30], "humiReal": [10, 20, 30], "tempSupply": [1, 2, 3]}, # "3000654": {"name": "sensor3", "tempReal": [10, 20, 30], "humiReal": [10, 20, 30], "tempSupply": [1, 2, 3]}} # # 冷机的历史7天数据 # chiller_data_ = {"301": {"name": 1, "currentPercent": [20, 20, 30], "chillerPowerRatio": [50, 50, 50], # "chillerWaterTempOut": [7, 7, 7], "set": [7, 7, 7], # 'waterTempControlMode': 0, 'chillerWaterTempSetInitial': 7, 'capacity': 10}, # "302": {"name": 1, "currentPercent": [10, 20, 30], "chillerPowerRatio": [50, 50, 50], # "chillerWaterTempOut": [7, 7, 7], "set": [7, 7, 7], # 'waterTempControlMode': 0, 'chillerWaterTempSetInitial': 7, 'capacity': 10}} # modify_data = {'terminalData': sensor_data_, 'chillerData': chiller_data_, 'stationData': station_data_} # config_info = {"handleService": 1, "controlMode": 1, "isHardwareControl": 1, "calPeriod": 3, # "minControlStep": 0.1, "chillerWaterTempSetInitial": 7, "chillerWaterTempSetUpper": 12, # "chillerWaterTempSetLower": 7, "energyMode": 1, "controlBasis": 0, "tempMargin": 0.2, # "humiMargin": 2, "mainTempMode": 0, "samplePeriod": 60, "upTempControlPeriod": 10, # "downTempControlPeriod": 12, 'runMode': 0, 'calMode': 0, 'allChillerControlSelect': [0, 0, 0], # 'triggerTime': "2025-4-5 12:00:00"} # thf = TempHumiFunction(data_df_cal, config_info, modify_data) # 监测点实时数据，冷站数据 # data = thf.temp_humi_cal() # 监测点历史数据，冷机历史数据 # pd.set_option('display.max_rows', None) # pd.set_option('display.max_columns', None) # # judge = JudgeOutRange(data, config_info) # result = judge.is_out_of_range()