基于BP神经网络的空调能耗预测与监控系统  

Air-conditioning energy consumption prediction and monitoring system based on BP neural network

作　　者：王定奥 刘清惓[1,2] 戴伟 浦玮 WANG Ding’ao;LIU Qingquan;DAI Wei;PU Wei(College of Electronics and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Key Laboratory of Meteorological Observation and Information Processing,Nanjing University of Information Science Technology,Nanjing 210044,China;Key Laboratory of MEMS of Ministry of Education,Southeast University,Nanjing 210096,China)

机构地区：[1]南京信息工程大学电子与信息工程学院,江苏南京210044 [2]南京信息工程大学江苏省气象探测与信息处理重点实验室,江苏南京210044 [3]东南大学MEMS教育部重点实验室,江苏南京210096

出　　处：《现代电子技术》2019年第22期140-144,共5页Modern Electronics Technique

基　　金：国家公益性行业(气象)科研专项项目(GYHY200906037;GYHY201306079);国家自然科学基金(41275042);江苏高校优势学科Ⅱ期建设工程项目(PAPD-Ⅱ)资助~~

摘　　要：针对空调能耗受室内外环境多因素影响而难以预测的问题,提出一种基于BP(Back Propagation)神经网络的空调能耗预测与监控系统。该方法将室外温湿度、房间冷热负荷、空调维持温湿度作为BP神经的输入,利用DeST分析并仿真在不同环境条件下的空调能耗。实验结果与样本数据比较可得,两者误差百分比在[-1.319%,1.270%]。为便于算法的实际应用,亦设计一套基于MVVM(Model View ViewModel)架构思想的空调能耗监测系统,并用Java将空调能耗预测方程进行封装。In allusion to the problem that the air conditioning energy consumption is hard to predict due to the influence of multiple factors in indoor and outdoor environments,an air conditioning energy consumption prediction and monitoring system based on BP(back propagation)neural network is proposed.The outdoor humiture,room cooling and heating loads,and air conditioning maintenance humiture are taken as the input of BP neural network,and the air conditioning energy consumption un der conditions of different environments is analyzed and simulated by means of DeST.It is found by comparison that the error be tween the experiment result and sample data is-1.319%~1.270%.In order to facilitate the practical application of the algo rithm,a set of air conditioning energy consumption monitoring system based on MVVM(Model View ViewModel)architecture imagine is designed,in which the prediction equation is packaged with Java.

关 键 词：空调能耗 系统设计 模型建立 BP神经网络 数据拟合 仿真实验 

分 类 号：TN948.64[电子电信—信号与信息处理] 34[电子电信—信息与通信工程] TP301.6[自动化与计算机技术—计算机系统结构]