Solar street light controller for harsh environments

Abstract

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.