【摘要】 针对太阳能LED路灯的亮灯需求和电能完全依赖天气的矛盾,提出了一种感知天气的太阳能LED路灯控制系统,通过历史天气信息和太阳能历史发电量,建立了神经网络模型预测未来太阳能发电量,并通过ZigBee和GPRS数据通信网络将预测的发电量信息发送给太阳能LED路灯终端控制器,路灯终端控制器根据预测发电量与蓄电池剩余电量,采用模糊控制策略,调整亮度,达到最佳的亮灯效果,尤其延长了连续阴雨天气的亮灯时间。更多还原

【Abstract】 To solve the contradiction between lighting requirement of solar LED street lamp and power depending on weather,a Solar LED Street Light Charge Controller with the Perception of Weather Charge is designed. Neural Network Model is built to make a prediction of future solar power through the historical weather information and previous generation of solar power. The prediction of power generation is sent to terminal controller of solar LED street lamp through data communication network based on Zig Bee and GPRS. Fuzzy control strategy is used to adjust the brightness of LED light by the terminal controller through the predicted power generation and remaining power of battery,and the best lighting effect is achieved.What’s more,the continuous lighting time of rainy weather is increased.更多还原