文章基本信息

标题：Solar Street Light Controller for Harsh Environments
本地全文：下载
作者：Ping Xue ; Yan-liang Song ; Hong-min Wang 等
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2015
卷号：9
期号：12
页码：161-170
DOI：10.14257/ijsh.2015.9.12.17
出版社：SERSC
摘要：At present, solar street light controller has the issues of unscientific discharge policy widely. Especially in the bad weather conditions, such as cold, Continuous rainy days etc. because of the weather conditions not considered comprehensive, causing the system can't be targeted scientifically discharge, thereby making the system operating time is shorter. To solve this problem, the subject has a more depth research, adding the ambient temperature, rainy weather which having a greater impact on the system to the study, Proposed a solutions of based on improved BP neural network algorithm which depending on the temperature, weather conditions and other factors to determine the discharge power of system to achieve the purposes of maximum energy saving. Finally, the simulation experiment shows that the controller compared with the traditional controller can better cope with the severe environment. It has a strong practical value.
关键词：Solar street light controller; Improved BP neural network; harsh ; environment; alpine; continuous rainy days