基于Salp群算法的部分遮阳条件下并网光伏系统全局MPPT控制

Nourhan M. Elbehairy, Hazem H. Mostafa, R. Swief
{"title":"基于Salp群算法的部分遮阳条件下并网光伏系统全局MPPT控制","authors":"Nourhan M. Elbehairy, Hazem H. Mostafa, R. Swief","doi":"10.1109/MEPCON55441.2022.10021693","DOIUrl":null,"url":null,"abstract":"This work presents a new population-based algorithm with fast convergence and high efficiency. This algorithm is the Salp Swarm Algorithm (SSA). SSA is used as a Global Maximum Power Point Tracking (GMPPT) for PV system that is tied to a grid under partial shading conditions. The algorithm is proposed to resolve the lack in efficiency and tracking speed, since the algorithm has less tuning parameters and fast convergence than other swarm algorithms. In addition, what makes it unique is that the best results is always stored so that it is not lost in the search space. A comparative analysis is done to validate the proposed technique with the famous Grey Wolf Optimization. The proposed algorithm is validated under different partial shading conditions. Also for more validation it is tested under a step change in irradiance. The results indicate the high tracking efficiency and robustness of the salp swarm algorithm GMPPT over other modern techniques along with the fast convergence time.","PeriodicalId":174878,"journal":{"name":"2022 23rd International Middle East Power Systems Conference (MEPCON)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global MPPT Controller for a Grid Tied PV System Under Partial Shading Conditions Using Salp Swarm Algorithm\",\"authors\":\"Nourhan M. Elbehairy, Hazem H. Mostafa, R. Swief\",\"doi\":\"10.1109/MEPCON55441.2022.10021693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents a new population-based algorithm with fast convergence and high efficiency. This algorithm is the Salp Swarm Algorithm (SSA). SSA is used as a Global Maximum Power Point Tracking (GMPPT) for PV system that is tied to a grid under partial shading conditions. The algorithm is proposed to resolve the lack in efficiency and tracking speed, since the algorithm has less tuning parameters and fast convergence than other swarm algorithms. In addition, what makes it unique is that the best results is always stored so that it is not lost in the search space. A comparative analysis is done to validate the proposed technique with the famous Grey Wolf Optimization. The proposed algorithm is validated under different partial shading conditions. Also for more validation it is tested under a step change in irradiance. The results indicate the high tracking efficiency and robustness of the salp swarm algorithm GMPPT over other modern techniques along with the fast convergence time.\",\"PeriodicalId\":174878,\"journal\":{\"name\":\"2022 23rd International Middle East Power Systems Conference (MEPCON)\",\"volume\":\"157 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 23rd International Middle East Power Systems Conference (MEPCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MEPCON55441.2022.10021693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 23rd International Middle East Power Systems Conference (MEPCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEPCON55441.2022.10021693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种新的基于种群的算法,收敛速度快,效率高。该算法被称为Salp Swarm algorithm (SSA)。SSA用于在部分遮阳条件下与电网相连的光伏系统的全球最大功率点跟踪(GMPPT)。该算法具有比其他群算法更少的调优参数和更快的收敛速度,因而在效率和跟踪速度方面存在不足。此外,它的独特之处在于始终存储最佳结果,以免在搜索空间中丢失。并与著名的灰狼优化算法进行了对比分析。在不同的部分遮光条件下对算法进行了验证。同样,为了进一步验证,它在辐照度的阶跃变化下进行了测试。结果表明,与其他现代算法相比,该算法具有较高的跟踪效率和鲁棒性,且收敛时间快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global MPPT Controller for a Grid Tied PV System Under Partial Shading Conditions Using Salp Swarm Algorithm
This work presents a new population-based algorithm with fast convergence and high efficiency. This algorithm is the Salp Swarm Algorithm (SSA). SSA is used as a Global Maximum Power Point Tracking (GMPPT) for PV system that is tied to a grid under partial shading conditions. The algorithm is proposed to resolve the lack in efficiency and tracking speed, since the algorithm has less tuning parameters and fast convergence than other swarm algorithms. In addition, what makes it unique is that the best results is always stored so that it is not lost in the search space. A comparative analysis is done to validate the proposed technique with the famous Grey Wolf Optimization. The proposed algorithm is validated under different partial shading conditions. Also for more validation it is tested under a step change in irradiance. The results indicate the high tracking efficiency and robustness of the salp swarm algorithm GMPPT over other modern techniques along with the fast convergence time.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信