{"title":"An Optimal Accommodation of Distributed Generation in Power Distribution Systems","authors":"B. Kiran Babu, Sydulu Maheswarapu","doi":"10.1109/NPSC.2018.8771743","DOIUrl":null,"url":null,"abstract":"This work presents a novel Multi Verse Optimisation (MVO) algorithm to solve the optimal accommodation of distributed generation (OADG) problem of power distribution systems (PDS). The proposed algorithm uses the concepts of white-hole, black-hole and worm-hole to realise the algorithm steps. The white-hole is used in the exploration phase. Whereas the black-hole and worm-hole are used in exploitation phase. The objectives to be optimised are: minimisation of real power loss, minimisation of bus voltage deviation, and maximisation of voltage stability index. The proposed approach is validated through IEEE 33-bus and IEEE 69-bus radial power distribution systems and results are compared with genetic algorithm (GA), Particle swarm optimisation (PSO), Hybrid GA-PSO, Teaching learning based optimisation (TLBO), and Quasi-oppositional teaching learning based optimisation (QOTLBO) algorithms and found to be promising.","PeriodicalId":185930,"journal":{"name":"2018 20th National Power Systems Conference (NPSC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 20th National Power Systems Conference (NPSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NPSC.2018.8771743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This work presents a novel Multi Verse Optimisation (MVO) algorithm to solve the optimal accommodation of distributed generation (OADG) problem of power distribution systems (PDS). The proposed algorithm uses the concepts of white-hole, black-hole and worm-hole to realise the algorithm steps. The white-hole is used in the exploration phase. Whereas the black-hole and worm-hole are used in exploitation phase. The objectives to be optimised are: minimisation of real power loss, minimisation of bus voltage deviation, and maximisation of voltage stability index. The proposed approach is validated through IEEE 33-bus and IEEE 69-bus radial power distribution systems and results are compared with genetic algorithm (GA), Particle swarm optimisation (PSO), Hybrid GA-PSO, Teaching learning based optimisation (TLBO), and Quasi-oppositional teaching learning based optimisation (QOTLBO) algorithms and found to be promising.