{"title":"Optimal Accommodation of Renewable DGs in Distribution System Considering Plug-in Electric Vehicles Using Gorilla Troops Optimizer","authors":"M. M. Sankar, K. Chatterjee","doi":"10.1109/REEDCON57544.2023.10151205","DOIUrl":null,"url":null,"abstract":"Rapid adoption of plug-in electric vehicles (PEVs) can create a sizable burden on distribution networks. For proactive planning of the distribution network, it is vital to consider PEV loads while optimally allocating distributed generators (DGs). In this study, renewable wind turbines and solar photovoltaic based DG units are optimally accommodated in the distribution system while addressing the uncertainties in the wind and solar power generation. A realistic time-varying mixed load model is adopted, and the PEV loads are integrated considering different charging profiles. Gorilla troops optimizer (GTO) algorithm is employed for determining the best locations and ratings of renewable DGs with minimization of real power loss, bus voltage deviation and augmentation of voltage stability index as objectives. The methodology is tested on a 33-bus benchmark distribution network. The outcomes are objectively evaluated in terms of the optimization objectives, and a comparative analysis is presented to substantiate the potency of GTO algorithm.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REEDCON57544.2023.10151205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Rapid adoption of plug-in electric vehicles (PEVs) can create a sizable burden on distribution networks. For proactive planning of the distribution network, it is vital to consider PEV loads while optimally allocating distributed generators (DGs). In this study, renewable wind turbines and solar photovoltaic based DG units are optimally accommodated in the distribution system while addressing the uncertainties in the wind and solar power generation. A realistic time-varying mixed load model is adopted, and the PEV loads are integrated considering different charging profiles. Gorilla troops optimizer (GTO) algorithm is employed for determining the best locations and ratings of renewable DGs with minimization of real power loss, bus voltage deviation and augmentation of voltage stability index as objectives. The methodology is tested on a 33-bus benchmark distribution network. The outcomes are objectively evaluated in terms of the optimization objectives, and a comparative analysis is presented to substantiate the potency of GTO algorithm.