Intelligent Cleaning Strategy of Photovoltaic Solar Cell Modules

IF 0.6 4区 工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC Journal of Nanoelectronics and Optoelectronics Pub Date : 2023-04-01 DOI:10.1166/jno.2023.3414
Xiaojing Jiang
{"title":"Intelligent Cleaning Strategy of Photovoltaic Solar Cell Modules","authors":"Xiaojing Jiang","doi":"10.1166/jno.2023.3414","DOIUrl":null,"url":null,"abstract":"With the decrease of disposable energy and the increase of social demand for power resources, photovoltaic power generation technology has been rapidly developed. The photovoltaic modules exposed outdoors for a long time accumulate serious ash, and the photovoltaic power generation\n efficiency is affected, so the photovoltaic modules need to be cleaned. Since various factors affecting the power generation efficiency of photovoltaic modules are difficult to quantify and mostly rely on the experience judgment of operation and maintenance personnel, this paper uses the historical\n operation data of photovoltaic power stations, comprehensively considers various influencing factors, establishes an intelligent cleaning data model, and combines the cleaning cost analysis to provide a basis for intelligent control of photovoltaic module cleaning robots.","PeriodicalId":16446,"journal":{"name":"Journal of Nanoelectronics and Optoelectronics","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nanoelectronics and Optoelectronics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1166/jno.2023.3414","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

With the decrease of disposable energy and the increase of social demand for power resources, photovoltaic power generation technology has been rapidly developed. The photovoltaic modules exposed outdoors for a long time accumulate serious ash, and the photovoltaic power generation efficiency is affected, so the photovoltaic modules need to be cleaned. Since various factors affecting the power generation efficiency of photovoltaic modules are difficult to quantify and mostly rely on the experience judgment of operation and maintenance personnel, this paper uses the historical operation data of photovoltaic power stations, comprehensively considers various influencing factors, establishes an intelligent cleaning data model, and combines the cleaning cost analysis to provide a basis for intelligent control of photovoltaic module cleaning robots.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
光伏太阳能电池组件的智能清洁策略
随着一次性能源的减少和社会对电力资源需求的增加,光伏发电技术得到了迅速发展。光伏组件长时间暴露在户外,积灰严重,影响光伏发电效率,需要对光伏组件进行清洗。由于影响光伏组件发电效率的各种因素难以量化,且多依赖运维人员的经验判断,本文利用光伏电站历史运行数据,综合考虑各种影响因素,建立智能清洗数据模型,并结合清洗成本分析,为光伏组件清洗机器人的智能控制提供依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Nanoelectronics and Optoelectronics
Journal of Nanoelectronics and Optoelectronics 工程技术-工程:电子与电气
自引率
16.70%
发文量
48
审稿时长
12.5 months
期刊最新文献
Pulsed Optoelectronic Rangefinder and Its Measurement Applications in Architectural Design Rationality Assessment Electrochemical Micro-Reaction and Failure Mechanism of New Materials Used at Low Temperature in Coastal Environment Ultrawideband Tunable Polarization Converter Based on Metamaterials Nanofluid Heat Transfer and Flow Characteristics in a Convex Plate Heat Exchanger Based on Multi-Objective Optimization Characterization of ZnO/rGO Nanocomposite and Its Application for Photocatalytic Degradation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1