{"title":"智能变压器、软开路点和电池储能系统下配电网的能量管理","authors":"Abhishek Singh, A. Maulik","doi":"10.1109/ICoPESA54515.2022.9754445","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-objective energy management scheme is proposed to simultaneously reduce the expected cost of operation, improve the voltage stability, minimize the average voltage deviation in a distribution network comprising renewable generation sources (solar and wind), and plug-in hybrid electric vehicle loads. Power electronic converter-based devices like soft open point and smart transformer are controlled in a coordinated fashion to realize the objectives of the energy management strategy. A probabilistic approach models the uncertainties of renewable generation, load, charging power requirement of plugin hybrid electric vehicles, and grid energy price. \"Hong's 2m point estimate method\" is used to incorporate the uncertainties in the optimal power flow. Simulation studies are carried out on a modified thirty-three bus distribution network. Simulation results demonstrate that the proposed probabilistic energy management strategy can reduce the expected cost of operation by ~ 1.48%, improve the voltage stability by at least ~ 27.26%, and reduce the average voltage deviation by at least ~ 77.50%.","PeriodicalId":142509,"journal":{"name":"2022 International Conference on Power Energy Systems and Applications (ICoPESA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Energy Management of Distribution Network in the Presence of Smart Transformers, Soft Open Points, and Battery Energy Storage System\",\"authors\":\"Abhishek Singh, A. Maulik\",\"doi\":\"10.1109/ICoPESA54515.2022.9754445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a multi-objective energy management scheme is proposed to simultaneously reduce the expected cost of operation, improve the voltage stability, minimize the average voltage deviation in a distribution network comprising renewable generation sources (solar and wind), and plug-in hybrid electric vehicle loads. Power electronic converter-based devices like soft open point and smart transformer are controlled in a coordinated fashion to realize the objectives of the energy management strategy. A probabilistic approach models the uncertainties of renewable generation, load, charging power requirement of plugin hybrid electric vehicles, and grid energy price. \\\"Hong's 2m point estimate method\\\" is used to incorporate the uncertainties in the optimal power flow. Simulation studies are carried out on a modified thirty-three bus distribution network. Simulation results demonstrate that the proposed probabilistic energy management strategy can reduce the expected cost of operation by ~ 1.48%, improve the voltage stability by at least ~ 27.26%, and reduce the average voltage deviation by at least ~ 77.50%.\",\"PeriodicalId\":142509,\"journal\":{\"name\":\"2022 International Conference on Power Energy Systems and Applications (ICoPESA)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Power Energy Systems and Applications (ICoPESA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICoPESA54515.2022.9754445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Power Energy Systems and Applications (ICoPESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoPESA54515.2022.9754445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy Management of Distribution Network in the Presence of Smart Transformers, Soft Open Points, and Battery Energy Storage System
In this paper, a multi-objective energy management scheme is proposed to simultaneously reduce the expected cost of operation, improve the voltage stability, minimize the average voltage deviation in a distribution network comprising renewable generation sources (solar and wind), and plug-in hybrid electric vehicle loads. Power electronic converter-based devices like soft open point and smart transformer are controlled in a coordinated fashion to realize the objectives of the energy management strategy. A probabilistic approach models the uncertainties of renewable generation, load, charging power requirement of plugin hybrid electric vehicles, and grid energy price. "Hong's 2m point estimate method" is used to incorporate the uncertainties in the optimal power flow. Simulation studies are carried out on a modified thirty-three bus distribution network. Simulation results demonstrate that the proposed probabilistic energy management strategy can reduce the expected cost of operation by ~ 1.48%, improve the voltage stability by at least ~ 27.26%, and reduce the average voltage deviation by at least ~ 77.50%.