{"title":"A Direct Search Nelder Mead MPPT based Induction Motor Drive for Solar PV Water Pumping Systems","authors":"K. Swetha, Barry Venugopal Reddy, R. Jain","doi":"10.1109/NPSC57038.2022.10069049","DOIUrl":null,"url":null,"abstract":"This paper presents a Nelder Mead (NM) approach for solar photovoltaic (SPV) array-based water pumping systems (WPS) to achieve maximum power point tracking (MPPT). The conventional MPPT algorithms fail to track global MPPT under partial shading conditions. The NM algorithm mainly consists of four operations (reflection, expansion, contraction, and shrinkage) which aid in the rapid convergence of all the particles to a global optimum. This results in a negligible steady-state error. The two-stage PV system is modeled and simulated in MATLAB/Simulink. To verify the effectiveness of the proposed system, it is compared with the perturb and observe and particle swarm optimization method. The NM algorithm converges in an average time duration of 0.25 s with an efficiency of 99.85%. The proposed two-stage system performance has been improved with the reduction in steady-state oscillation when compared with the conventional method.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 22nd National Power Systems Conference (NPSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NPSC57038.2022.10069049","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
This paper presents a Nelder Mead (NM) approach for solar photovoltaic (SPV) array-based water pumping systems (WPS) to achieve maximum power point tracking (MPPT). The conventional MPPT algorithms fail to track global MPPT under partial shading conditions. The NM algorithm mainly consists of four operations (reflection, expansion, contraction, and shrinkage) which aid in the rapid convergence of all the particles to a global optimum. This results in a negligible steady-state error. The two-stage PV system is modeled and simulated in MATLAB/Simulink. To verify the effectiveness of the proposed system, it is compared with the perturb and observe and particle swarm optimization method. The NM algorithm converges in an average time duration of 0.25 s with an efficiency of 99.85%. The proposed two-stage system performance has been improved with the reduction in steady-state oscillation when compared with the conventional method.