Prediction of commercial building lighting energy consumption based on EPSO-BP

被引：0

作者：

Sha, Guorong ^{[1
]}

Qian, Qing ^{[2
]}

机构：

[1] Nanjing Inst Ind & Technol, Sch Transportat, Nanjing 211800, Jiangsu, Peoples R China

[2] Nanjing Univ Technol, Sch Elect Engn & Control Sci, Nanjing 211800, Jiangsu, Peoples R China

来源：

2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS) | 2018年

关键词：

Lighting energy consumption; Improved particle swarm optimization; Sub-item energy consumption; NEURAL-NETWORKS; MODEL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It aims to distinguish the whereabouts of the total energy consumption of commercial building lighting accurately and improve prediction accuracy. Based on the use of commercial building lighting energy consumption, this paper divides the total lighting energy consumption into three sections, such as the advertising lighting energy consumption, decorative lighting energy consumption and special lighting energy consumption. The EPSO-BP prediction model is constructed and the sub-item prediction of energy consumption of commercial building lighting is realized through MATLAB software. The advertising lighting energy consumption, decorative lighting energy consumption and special lighting energy consumption are predicted by this model, and compared with the other models. The experimental results show that the prediction model proposed in this paper can distinguish the whereabouts of the total energy consumption and predict the lighting energy consumption in the various sub-items of the commercial building more accurately and effectively.

引用

页码：1035 / 1040

页数：6

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