{"title":"主动配电网中智能电动车停车场的优化规划","authors":"H. Hosseinnia, J. Modarresi, H. Delavaripour","doi":"10.1109/PSC49016.2019.9081525","DOIUrl":null,"url":null,"abstract":"Smart electric vehicle parking lots (SEVPL) can operate as generator and load, and charge and discharge their storage systems. This leads to a nearby flat daily load curve. Therefore, distribution network operator (DNO) prefers to install SEVPL in the distribution network (DN). In this paper, optimal planning of SEVPL is formulated as a cost function in DN. The proposed SEVPL includes: diesel generator (DG), photovoitaic system (PV) and batteries. Demand response (DR) under time of use (TOU) pricing is employed to transfer consumption from the on-peak time to the off-peak time. All uncertainties of the system are considered in the problem codification. All simulations are carried out in MATLAB software, and improved particle swarm optimization algorithm (IPSO) is used to solve the optimization problem.","PeriodicalId":359817,"journal":{"name":"2019 International Power System Conference (PSC)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal Planning of Smart Electric Vehicle Parking lot in the Active Distribution Network\",\"authors\":\"H. Hosseinnia, J. Modarresi, H. Delavaripour\",\"doi\":\"10.1109/PSC49016.2019.9081525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart electric vehicle parking lots (SEVPL) can operate as generator and load, and charge and discharge their storage systems. This leads to a nearby flat daily load curve. Therefore, distribution network operator (DNO) prefers to install SEVPL in the distribution network (DN). In this paper, optimal planning of SEVPL is formulated as a cost function in DN. The proposed SEVPL includes: diesel generator (DG), photovoitaic system (PV) and batteries. Demand response (DR) under time of use (TOU) pricing is employed to transfer consumption from the on-peak time to the off-peak time. All uncertainties of the system are considered in the problem codification. All simulations are carried out in MATLAB software, and improved particle swarm optimization algorithm (IPSO) is used to solve the optimization problem.\",\"PeriodicalId\":359817,\"journal\":{\"name\":\"2019 International Power System Conference (PSC)\",\"volume\":\"228 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Power System Conference (PSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PSC49016.2019.9081525\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Power System Conference (PSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSC49016.2019.9081525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Planning of Smart Electric Vehicle Parking lot in the Active Distribution Network
Smart electric vehicle parking lots (SEVPL) can operate as generator and load, and charge and discharge their storage systems. This leads to a nearby flat daily load curve. Therefore, distribution network operator (DNO) prefers to install SEVPL in the distribution network (DN). In this paper, optimal planning of SEVPL is formulated as a cost function in DN. The proposed SEVPL includes: diesel generator (DG), photovoitaic system (PV) and batteries. Demand response (DR) under time of use (TOU) pricing is employed to transfer consumption from the on-peak time to the off-peak time. All uncertainties of the system are considered in the problem codification. All simulations are carried out in MATLAB software, and improved particle swarm optimization algorithm (IPSO) is used to solve the optimization problem.
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