{"title":"Load frequency control in Island micro-grid with electric vehicles and renewable energy sources using modified fractional order PID controller","authors":"O. Tola, Ovis Daniel Irefu, J. G. Ambafi","doi":"10.11591/ijpeds.v15.i1.pp168-179","DOIUrl":null,"url":null,"abstract":"This paper presents a modified fractional-order proportional-integral-differential (MFOPID) controller for load frequency control in an Island microgrid based on an electric vehicle (EV) and renewable energy source. It tackles the intermittent energy sources and the dynamic of the load change with reduced speed and the quality of response generated on the microgrid. The MFOPID controller gains are well turned using a metaheuristic grasshopper optimization algorithm (GOA) technique to determine its robustness and optimal system performance. The controller gains are evaluated with three different searching agent populations. The proposed MFOPID with GOA improved system performance frequency by 19.485 Hz compared to 14.1151 Hz of the benchmark model. It takes 6.9068 s of the proposed model to settle compared to 16.6796 s of FOPID.","PeriodicalId":355274,"journal":{"name":"International Journal of Power Electronics and Drive Systems (IJPEDS)","volume":"21 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power Electronics and Drive Systems (IJPEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijpeds.v15.i1.pp168-179","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 modified fractional-order proportional-integral-differential (MFOPID) controller for load frequency control in an Island microgrid based on an electric vehicle (EV) and renewable energy source. It tackles the intermittent energy sources and the dynamic of the load change with reduced speed and the quality of response generated on the microgrid. The MFOPID controller gains are well turned using a metaheuristic grasshopper optimization algorithm (GOA) technique to determine its robustness and optimal system performance. The controller gains are evaluated with three different searching agent populations. The proposed MFOPID with GOA improved system performance frequency by 19.485 Hz compared to 14.1151 Hz of the benchmark model. It takes 6.9068 s of the proposed model to settle compared to 16.6796 s of FOPID.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
