Mahmoud F. Mahmoud, Ahmed T. Mohamed, R. Swief, L. Said, A. Radwan
{"title":"MPPT for a Partially Shaded PV System Using Accelerated Particle Swarms","authors":"Mahmoud F. Mahmoud, Ahmed T. Mohamed, R. Swief, L. Said, A. Radwan","doi":"10.1109/ICM52667.2021.9664922","DOIUrl":null,"url":null,"abstract":"MPPT is developed to get the most power out from photovoltaic (PV) modules in various conditions, including changing weather and partial shading (PS). The partial shade of a PV system is a significant issue. PV systems’ power characteristics are so complicated under PS that there are a variety of MPPs. Traditional MPPT methods may become stuck in Local MPPs(LMPPs) instead of Global MPPs (GMPP). The GMPP can be tracked fast and correctly using accelerated particle swarm optimization (APSO). By comparing the employed algorithm to the traditional ones, simulation results validate the optimization performance.","PeriodicalId":212613,"journal":{"name":"2021 International Conference on Microelectronics (ICM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Microelectronics (ICM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM52667.2021.9664922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
MPPT is developed to get the most power out from photovoltaic (PV) modules in various conditions, including changing weather and partial shading (PS). The partial shade of a PV system is a significant issue. PV systems’ power characteristics are so complicated under PS that there are a variety of MPPs. Traditional MPPT methods may become stuck in Local MPPs(LMPPs) instead of Global MPPs (GMPP). The GMPP can be tracked fast and correctly using accelerated particle swarm optimization (APSO). By comparing the employed algorithm to the traditional ones, simulation results validate the optimization performance.