光伏板污秽度状态评价及清扫决策系统的研究  

Research on Photovoltaic Panels Filthy State Evaluation and Cleaning Decision System

作　　者：李佳奇 李爽 李斌 刘碧琦 王亮[3] LI Jiaqi;LI Shuang;LI Bin;LIU Biqi;WANG Liang(Electric Power Research Institute of State Grid Liaoning Electric Power Co.,Ltd.,Shenyang,Liaoning 110006,China;State Grid Liaoning Information and Communication Co.,Ltd.,Shenyang,Liaoning 110006,China;Shenyang Institute of Engineering,Shenyang,Liaoning 110136,China)

机构地区：[1]国网辽宁省电力有限公司电力科学研究院,辽宁沈阳110006 [2]国网辽宁省电力有限公司信息通信分公司,辽宁沈阳110006 [3]沈阳工程学院,辽宁沈阳110136

出　　处：《东北电力技术》2023年第9期1-5,12,共6页Northeast Electric Power Technology

基　　金：国网辽宁省电力有限公司青创和群促项目(2022YF-101)。

摘　　要：随着光伏电站的大规模应用,其关键组件光伏板的污秽度直接决定了发电效率和经济收益,然而是否具备合理的清扫决策给光伏板清洁运维工作带来巨大挑战。为此,以单片机为核心并结合温湿度传感器、太阳光辐射度传感器、PM2.5传感器、光伏电压检测模块,设计了光伏板污秽度状态评价系统,以实现光伏电站收益最大化。提出利用改进型BP神经网络实现清扫决策的模型,为构建新型电力系统目标愿景及完善多元化清洁能源供应体系提供参考。With the large-scale application of photovoltaic power stations,a key component,the filthy state of photovoltaic panels directly determines the power generation efficiency and economic benefits.However,it brings a huge difficulty weather there is a reasonable cleaning decision for photovoltaic panels cleaning operations.Therefore,with the single chip processor as the core and connecting with the temperature and humidity,solar radiation sensor,PM2.5 sensor,PV voltage detection module design photovoltaic panels filthy state evaluation system achieve the maximum photovoltaic power station profit.Based on improved BP neural network to realize clean decision-making model,it provides a reference for building a new type of power system goal vision and improving a diversified clean energy supply system.

关 键 词：改进型BP神经网络 光伏板 污秽度 状态评价 清扫决策 

分 类 号：TM93[电气工程—电力电子与电力传动]