{"title":"不同类型DG在配电系统中的单、多配置","authors":"O. Oladepo","doi":"10.36108/ujees/2202.40.0132","DOIUrl":null,"url":null,"abstract":"Integration of distributed generation on power distribution system impacts the network for improved voltage stability and power quality. However, inaccurate sizing and placement of the energy sources can worsen the network performance. This paper proposes a hybrid particle swarm optimization/whale optimization algorithm for the optimal placement of different distribution generation types on a power network. Standalone metaheuristics are efficient and robust optimization tools but are mostly challenged with convergence and sub-optimal solutions. The exploration potential of particle swarm optimization with the selection of higher inertial weight is annexed with the exploitation phase of the whale optimization algorithm. The proposed technique is verified on IEEE 33 – bus distribution system. Results show 86.12% and 89.84% improvement in voltage deviation for Type I and Type III DG injection respectively. Besides, the convergence is achieved in less than 50 iterations compared to standalone methods.","PeriodicalId":23413,"journal":{"name":"UNIOSUN Journal of Engineering and Environmental Sciences","volume":"120 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single and Multiple Placements of Different DG Types On the Power Distribution System\",\"authors\":\"O. Oladepo\",\"doi\":\"10.36108/ujees/2202.40.0132\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Integration of distributed generation on power distribution system impacts the network for improved voltage stability and power quality. However, inaccurate sizing and placement of the energy sources can worsen the network performance. This paper proposes a hybrid particle swarm optimization/whale optimization algorithm for the optimal placement of different distribution generation types on a power network. Standalone metaheuristics are efficient and robust optimization tools but are mostly challenged with convergence and sub-optimal solutions. The exploration potential of particle swarm optimization with the selection of higher inertial weight is annexed with the exploitation phase of the whale optimization algorithm. The proposed technique is verified on IEEE 33 – bus distribution system. Results show 86.12% and 89.84% improvement in voltage deviation for Type I and Type III DG injection respectively. Besides, the convergence is achieved in less than 50 iterations compared to standalone methods.\",\"PeriodicalId\":23413,\"journal\":{\"name\":\"UNIOSUN Journal of Engineering and Environmental Sciences\",\"volume\":\"120 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"UNIOSUN Journal of Engineering and Environmental Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36108/ujees/2202.40.0132\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"UNIOSUN Journal of Engineering and Environmental Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36108/ujees/2202.40.0132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Single and Multiple Placements of Different DG Types On the Power Distribution System
Integration of distributed generation on power distribution system impacts the network for improved voltage stability and power quality. However, inaccurate sizing and placement of the energy sources can worsen the network performance. This paper proposes a hybrid particle swarm optimization/whale optimization algorithm for the optimal placement of different distribution generation types on a power network. Standalone metaheuristics are efficient and robust optimization tools but are mostly challenged with convergence and sub-optimal solutions. The exploration potential of particle swarm optimization with the selection of higher inertial weight is annexed with the exploitation phase of the whale optimization algorithm. The proposed technique is verified on IEEE 33 – bus distribution system. Results show 86.12% and 89.84% improvement in voltage deviation for Type I and Type III DG injection respectively. Besides, the convergence is achieved in less than 50 iterations compared to standalone methods.