M. Dwivedi, Gitanjali Mehta, Asif Iqbal, H. Shekhar
{"title":"Performance enhancement of solar PV system under partial shaded condition using PSO","authors":"M. Dwivedi, Gitanjali Mehta, Asif Iqbal, H. Shekhar","doi":"10.1109/ICCCNT.2017.8204082","DOIUrl":null,"url":null,"abstract":"The purpose of this research is to focus on performance enhancement of Photovoltaic system by improving Maximum Power Point Tracking (MPPT) techniques for sustainable green electricity production for future generation. The conventional MPPT algorithms performs well in uniform irradiance condition but unable to reach at the desired maximum power point (MPP)in partial shading condition (PSC). This demands necessity for development of efficient optimization techniques those are capable of reaching the global maximum power point (GMPP) in a PV system under PSC. Accordingly, this research work provides a comprehensive assessment on tracking performance of Particle Swarm Optimization (PSO) algorithm under PSC. A comparative study of this optimization technique has been performed against two conventional algorithms named Perturb and Observe (P&O) and Incremental Conductance (INC). Results confirm that the PSO algorithm guarantees fast convergence to GMPP and have better performance in comparison with the conventional ones.","PeriodicalId":6581,"journal":{"name":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","volume":"10 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2017.8204082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The purpose of this research is to focus on performance enhancement of Photovoltaic system by improving Maximum Power Point Tracking (MPPT) techniques for sustainable green electricity production for future generation. The conventional MPPT algorithms performs well in uniform irradiance condition but unable to reach at the desired maximum power point (MPP)in partial shading condition (PSC). This demands necessity for development of efficient optimization techniques those are capable of reaching the global maximum power point (GMPP) in a PV system under PSC. Accordingly, this research work provides a comprehensive assessment on tracking performance of Particle Swarm Optimization (PSO) algorithm under PSC. A comparative study of this optimization technique has been performed against two conventional algorithms named Perturb and Observe (P&O) and Incremental Conductance (INC). Results confirm that the PSO algorithm guarantees fast convergence to GMPP and have better performance in comparison with the conventional ones.