{"title":"基于爬行动物搜索算法的电动汽车在风力综合配电系统中的最优定位","authors":"N. Rehman, M. Mufti, Neeraj Gupta","doi":"10.13052/dgaej2156-3306.3817","DOIUrl":null,"url":null,"abstract":"Distributed generation (DG) has been employed over the years in distribution systems to enhance system voltage profile, improve voltage regulation and minimise power losses leading to improved stability besides economic benefits. This work addresses an application of reptile search algorithm (RSA) based optimization technique to determine the optimal placement of electric vehicles (EVs) in distribution systems. A matrix approach based radial distribution load flow method is adopted to determine the optimal location of DGs with the heuristic intelligent search approach of RSA looking after the optimal placement of EV loads. This work presents a standard IEEE-33 and 69 bus system integrated with a wind turbine generating system (WTGS). The system is modeled for optimal placement of EV loads such that the system voltage is maintained within allowable limits by reducing overall system losses. The optimal placement of EV loads in a radial distribution network (RDN) implies establishing an efficient active distribution network satisfying several operating parameters like bus voltage limits and current capacity of feeders while maintaining network radiality with minimal system losses. The proposed technique is investigated on the benchmark IEEE-33 and 69 bus test systems. The simulated results depict a substantial improvement in convergence characteristics and reduction in system losses.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"255 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal Location of Electric Vehicles in a Wind Integrated Distribution System Using Reptile Search Algorithm\",\"authors\":\"N. Rehman, M. Mufti, Neeraj Gupta\",\"doi\":\"10.13052/dgaej2156-3306.3817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distributed generation (DG) has been employed over the years in distribution systems to enhance system voltage profile, improve voltage regulation and minimise power losses leading to improved stability besides economic benefits. This work addresses an application of reptile search algorithm (RSA) based optimization technique to determine the optimal placement of electric vehicles (EVs) in distribution systems. A matrix approach based radial distribution load flow method is adopted to determine the optimal location of DGs with the heuristic intelligent search approach of RSA looking after the optimal placement of EV loads. This work presents a standard IEEE-33 and 69 bus system integrated with a wind turbine generating system (WTGS). The system is modeled for optimal placement of EV loads such that the system voltage is maintained within allowable limits by reducing overall system losses. The optimal placement of EV loads in a radial distribution network (RDN) implies establishing an efficient active distribution network satisfying several operating parameters like bus voltage limits and current capacity of feeders while maintaining network radiality with minimal system losses. The proposed technique is investigated on the benchmark IEEE-33 and 69 bus test systems. The simulated results depict a substantial improvement in convergence characteristics and reduction in system losses.\",\"PeriodicalId\":11205,\"journal\":{\"name\":\"Distributed Generation & Alternative Energy Journal\",\"volume\":\"255 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Distributed Generation & Alternative Energy Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13052/dgaej2156-3306.3817\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Distributed Generation & Alternative Energy Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/dgaej2156-3306.3817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Location of Electric Vehicles in a Wind Integrated Distribution System Using Reptile Search Algorithm
Distributed generation (DG) has been employed over the years in distribution systems to enhance system voltage profile, improve voltage regulation and minimise power losses leading to improved stability besides economic benefits. This work addresses an application of reptile search algorithm (RSA) based optimization technique to determine the optimal placement of electric vehicles (EVs) in distribution systems. A matrix approach based radial distribution load flow method is adopted to determine the optimal location of DGs with the heuristic intelligent search approach of RSA looking after the optimal placement of EV loads. This work presents a standard IEEE-33 and 69 bus system integrated with a wind turbine generating system (WTGS). The system is modeled for optimal placement of EV loads such that the system voltage is maintained within allowable limits by reducing overall system losses. The optimal placement of EV loads in a radial distribution network (RDN) implies establishing an efficient active distribution network satisfying several operating parameters like bus voltage limits and current capacity of feeders while maintaining network radiality with minimal system losses. The proposed technique is investigated on the benchmark IEEE-33 and 69 bus test systems. The simulated results depict a substantial improvement in convergence characteristics and reduction in system losses.