{"title":"基于最优日前负荷转移的智能电网需求侧管理策略","authors":"Rajaa Naji El Idrissi, M. Ouassaid, M. Maaroufi","doi":"10.1109/IRSEC.2018.8702994","DOIUrl":null,"url":null,"abstract":"In this work a load shifting for demand side management (DSM) strategy is developed. The strategy is based on an improved version of differential evolution DE, named Back Tracking Search Algorithm (BSA) is proposed in order to minimize the peak load demand and the total utility cost of three kinds of customers i.e. residential, commercial and industrial. The obtained simulation results are compared with those obtained using Particle Swarm Optimization (PSO) algorithm. This comparison highlights the effectiveness of BSA to handle a large number of different type devices.","PeriodicalId":186042,"journal":{"name":"2018 6th International Renewable and Sustainable Energy Conference (IRSEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Demand Side Management Strategy by Optimal Day-ahead Load Shifting in Smart Grid\",\"authors\":\"Rajaa Naji El Idrissi, M. Ouassaid, M. Maaroufi\",\"doi\":\"10.1109/IRSEC.2018.8702994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work a load shifting for demand side management (DSM) strategy is developed. The strategy is based on an improved version of differential evolution DE, named Back Tracking Search Algorithm (BSA) is proposed in order to minimize the peak load demand and the total utility cost of three kinds of customers i.e. residential, commercial and industrial. The obtained simulation results are compared with those obtained using Particle Swarm Optimization (PSO) algorithm. This comparison highlights the effectiveness of BSA to handle a large number of different type devices.\",\"PeriodicalId\":186042,\"journal\":{\"name\":\"2018 6th International Renewable and Sustainable Energy Conference (IRSEC)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 6th International Renewable and Sustainable Energy Conference (IRSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRSEC.2018.8702994\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 6th International Renewable and Sustainable Energy Conference (IRSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRSEC.2018.8702994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Demand Side Management Strategy by Optimal Day-ahead Load Shifting in Smart Grid
In this work a load shifting for demand side management (DSM) strategy is developed. The strategy is based on an improved version of differential evolution DE, named Back Tracking Search Algorithm (BSA) is proposed in order to minimize the peak load demand and the total utility cost of three kinds of customers i.e. residential, commercial and industrial. The obtained simulation results are compared with those obtained using Particle Swarm Optimization (PSO) algorithm. This comparison highlights the effectiveness of BSA to handle a large number of different type devices.
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