基于MEA⁃BP神经网络的建筑能耗预测模型

doi:10.13229/j.cnki.jdxbgxb20210436

吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (5): 1857-1865.doi: 10.13229/j.cnki.jdxbgxb20210436

• 计算机科学与技术 • 上一篇

基于MEA⁃BP神经网络的建筑能耗预测模型

滕文龙¹( ),丛炳虎¹,商云坤¹,张予宸¹,白天²( )

^1.吉林大学第一医院，长春 130021
^2.吉林大学计算机科学与技术学院，长春 130021

收稿日期:2021-05-17 出版日期:2021-09-01 发布日期:2021-09-16
通讯作者: 白天 E-mail:tengwenlong@jlu.edu.cn;baitian@jlu.edu.cn
作者简介:滕文龙（1975-），男，助理研究员.研究方向：节能软件与硬件开发.E-mail：tengwenlong@jlu.edu.cn
基金资助:
国家自然科学基金项目(61702214);吉林省科技厅自由探索重点项目(YDZJ202101ZYTS128);吉林省科技厅国际合作项目(20200801033GH)

Modeling of building energy consumption prediction based on MEA⁃BP neural network

Wen-long TENG¹(),Bing-hu CONG¹,Yun-kun SHANG¹,Yu-chen ZHANG¹,Tian BAI²( )

^1.The First Hospital of Jilin University，Changchun 130021，China
^2.College of Computer Science and Technology，Jilin University，Changchun 130021，China

Received:2021-05-17 Online:2021-09-01 Published:2021-09-16
Contact: Tian BAI E-mail:tengwenlong@jlu.edu.cn;baitian@jlu.edu.cn

摘要/Abstract

摘要：

针对节能管理方面面临内部能耗状况无法准确计量、缺乏科学的能耗指标和评价标准、能耗管理考虑不够等问题，本文建立了MEA-BP神经网络能耗预测模型。基于能耗监管平台输出的历史能耗数据，对BP神经网络与MEA-BP神经网络进行训练，使用训练后的模型对建筑能耗进行预测，对比能耗预测值与能耗真实值，发现MEA-BP模型的能耗预测结果精度较高，有实际应用价值。根据能耗预测值，通过能耗监测平台对用能设施、用能方式进行相应控制与改善，提升了水、电、暖、气的节能效率，实现了最优的能耗控制和能源有效利用。

关键词: 公共建筑, 神经网络, 能耗监测平台, 能耗数据, 能耗预测

Abstract:

In order to solve the problems of energy saving management， such as poor measurement accuracy of internal energy consumption， inconsistency of scientific energy consumption index and evaluation standard， and insufficient level of energy consumption management， the MEA-BP neural network predicting the building energy consumption is established. Based on the historical energy consumption data output from the energy consumption supervision platform， the BP neural network and MEA-BP neural network were trained. By comparing the actual value with predicted value on energy consumption， it is found that MEA-BP model is more accurate in predicting energy consumption. The MEA-BP model combined with energy consumption supervision platform could improve the energy saving efficiency about water， electricity， heating and gas， achieving the optimal energy consumption control and efficient use of energy.

Key words: public buildings, neural network, energy consumption supervision platform, data of energy consumption, energy consumption prediction

中图分类号:

U491.1

滕文龙,丛炳虎,商云坤,张予宸,白天. 基于MEA⁃BP神经网络的建筑能耗预测模型[J]. 吉林大学学报(工学版), 2021, 51(5): 1857-1865.

Wen-long TENG,Bing-hu CONG,Yun-kun SHANG,Yu-chen ZHANG,Tian BAI. Modeling of building energy consumption prediction based on MEA⁃BP neural network[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1857-1865.

图/表 13

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基于MEA⁃BP神经网络的建筑能耗预测模型

Modeling of building energy consumption prediction based on MEA⁃BP neural network

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