集中冷热源系统级节能模型研究  

District Heating and Cooling Source Energy Conservation Model Research on System Level

作　　者：张国华 王亮 李景涛 Zhang Guohua;Wang Liang;Li Jingtao(Shanghai LANDLEAF Architecture Technology Co.,Ltd.,Shanghai 200092,China)

机构地区：[1]上海朗绿建筑科技股份有限公司,上海200092

出　　处：《机电工程技术》2024年第11期71-75,共5页Mechanical & Electrical Engineering Technology

摘　　要：以集中冷热源系统为研究对象,基于系统负荷预测与末端负荷及供能特性适配的变水温模型在系统级层面提出了节能模型。其中系统负荷预测采用动量BP神经网络(MOBP)与遗忘因子模型相结合的方法;以当前室外干球温度、前一天同时刻负荷、前一天同时刻室外干球温度、当前时刻太阳总辐射强度和当前时刻相对湿度为神经网络输入特征变量,以当前时刻负荷为输出变量建立双隐层神经网络,并加入了时序偏差修正,预测精度显著提升。变水温模型则基于适配预测负荷与末端特性的方法建立动态模型,基于实测数据,辨识了新风末端及辐射末端特性参数,进一步计算出动态水温参数,并作为冷热源系统供能设定参数,该优化模型在实际项目中进行了实践应用,负荷预测时序特性与统计特性与实际供热负荷相一致,项目同比节能量达38.8%。Based on the system load prediction and variable water temperature model of adaptation of the end load and the energy supply characteristics,an energy conservation model is proposed at the system level.The load prediction is based on MOBP model and the forgetting factor model.Taking the current outdoor dry bulb temperature,the previous day's load at the same time,the previous day's outdoor dry bulb temperature at the same time,the total solar radiation intensity at the current time and the relative humidity at the current time as the input characteristic variables of the neural network,the double hidden layer neural network is established with the current time load as the output variable,and the timing deviation correction is added to significantly improve the prediction accuracy.The variable water temperature model is based on the method of adapting predictive load and terminal characteristics to establish the variable water temperature dynamic model.Based on the measured data,the variable water temperature model identifies the characteristic parameters of the fresh wind end and the radiation end,and further calculates the dynamic water temperature parameters,which are used as the energy supply parameters of the cooling and heat source system.The energy conservation model is used in actual projects.The result shows that the time series characteristics and statistical characteristics of the load forecast are consistent with the actual heating load and the project saved 38.8%of energy.

关 键 词：冷热源 系统节能 模型研究 负荷预测 变水温模型 

分 类 号：TU831[建筑科学—供热、供燃气、通风及空调工程]