BP算法预测控制在供热系统中的节能应用  

Energy-saving Application of BP Algorithm Predictive Control in Heating System

作　　者：朱冬雪 鹿世化[1] 张帆 过继伟 葛雪锋 ZHU Dong-xue;LU Shi-hu;ZHANG Fan;GUO Ji-wei;GE Xue-feng(School of Energy and Mechanical Engineering,Nanjing Normal University;Zhejiang CHINTASTRO Technology Co.,Ltd.)

机构地区：[1]南京师范大学能源与机械工程学院 [2]浙江正泰聚能科技有限公司

出　　处：《建筑热能通风空调》2020年第4期50-52,65,共4页Building Energy & Environment

基　　金：国家自然科学基金资助项目(No.61603194);江苏省高校自然科学基金(16KJB120002)。

摘　　要：针对集中供热系统二次管网水力失衡而导致采暖用户室内冷热不均、系统运行能耗高等问题,采用BP神经网络对建筑热负荷和IBV电子平衡阀的开度进行预测的方法,对供热系统进行节能控制。通过系统改造前后同期运行数据对比可得,在满足用户用热需求的基础上,末端用户耗热量减少7.4%,系统总能耗减少9.5%。试验数据表明,BP神经网络算法预测控制方法大大降低了小区供热系统的运行能耗。BP算法控制系统对集中供热系统的节能改造和工程应用方面的发展具有很大的贡献。Aiming at the problems of unbalanced heating and cooling of heating users and high energy consumption of system operation caused by the hydraulic imbalance of the secondary pipe network of the central heating system, the BP neural network is used to predict the building heat load and the opening of the IBV electronic balance valve for energy-saving control of heating systems. Based on comparison of the running data of the same period before and after the system transformation, based on meeting the user’s heat demand, the end user’s heat consumption is reduced by 7.4%and the total system energy consumption is reduced by 9.5%. Experimental data show that the BP neural network algorithm predictive control method greatly reduces the energy consumption of the district heating system. The BP algorithm control system has made great contributions to the development of energy-saving transformation and engineering applications of central heating systems.

关 键 词：集中供热 BP神经网络 热负荷 电子平衡阀 节能 

分 类 号：TU995[建筑科学—供热、供燃气、通风及空调工程]