{"title":"An Optimal Power Control Strategy For A Plug In Electric Vehicle Based On Online Multi-Objective Particle Swarm Optimization","authors":"M. Rekik, Marwa Grami, L. Krichen","doi":"10.1109/IC_ASET53395.2022.9765949","DOIUrl":null,"url":null,"abstract":"The developed work in this paper focuses on the optimal integration of rechargeable electric vehicles into the smart grid. Indeed, an optimization control is proposed to improve the dynamics and the response of these vehicles by adjusting all the parameters of their regulators during participation in the both concepts: vehicles to grid and grid to vehicles. The suggested approach is performed using the Online multi-objective Particle-Swarm-Optimization (PSO) algorithm. Simulation results obtained by \"Matlab Simulink\" will be presented to show the feasibility of this studied approach.","PeriodicalId":6874,"journal":{"name":"2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"40 1","pages":"538-543"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC_ASET53395.2022.9765949","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
The developed work in this paper focuses on the optimal integration of rechargeable electric vehicles into the smart grid. Indeed, an optimization control is proposed to improve the dynamics and the response of these vehicles by adjusting all the parameters of their regulators during participation in the both concepts: vehicles to grid and grid to vehicles. The suggested approach is performed using the Online multi-objective Particle-Swarm-Optimization (PSO) algorithm. Simulation results obtained by "Matlab Simulink" will be presented to show the feasibility of this studied approach.
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