{"title":"智能家居可再生能源集成的日前设备调度","authors":"I. Hammou Ou Ali, M. Ouassaid, M. Maaroufi","doi":"10.1109/ROPEC50909.2020.9258708","DOIUrl":null,"url":null,"abstract":"In this paper, a residential appliance scheduling problem is addressed. Usually, the householders main attention is focused on reducing the amount of money put into the energy suppliers pocket without affecting the comfort level. The proposed model aims at scheduling the home appliances in such a way the cost and discomfort are reduced. The problem is formulated as a mixed integer linear programming in which the decision variables are the optimal starting time of the appliances. The model is simulated under a day-ahead electricity pricing for three cases: traditional user, smart user, and smart prosumer. Simulation results show that the proposed technique optimally schedules the appliances so that the electricity payments is reduced and the users comfort is increased.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Day ahead appliance scheduling with renewable energy integration for smart homes\",\"authors\":\"I. Hammou Ou Ali, M. Ouassaid, M. Maaroufi\",\"doi\":\"10.1109/ROPEC50909.2020.9258708\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a residential appliance scheduling problem is addressed. Usually, the householders main attention is focused on reducing the amount of money put into the energy suppliers pocket without affecting the comfort level. The proposed model aims at scheduling the home appliances in such a way the cost and discomfort are reduced. The problem is formulated as a mixed integer linear programming in which the decision variables are the optimal starting time of the appliances. The model is simulated under a day-ahead electricity pricing for three cases: traditional user, smart user, and smart prosumer. Simulation results show that the proposed technique optimally schedules the appliances so that the electricity payments is reduced and the users comfort is increased.\",\"PeriodicalId\":177447,\"journal\":{\"name\":\"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROPEC50909.2020.9258708\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROPEC50909.2020.9258708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Day ahead appliance scheduling with renewable energy integration for smart homes
In this paper, a residential appliance scheduling problem is addressed. Usually, the householders main attention is focused on reducing the amount of money put into the energy suppliers pocket without affecting the comfort level. The proposed model aims at scheduling the home appliances in such a way the cost and discomfort are reduced. The problem is formulated as a mixed integer linear programming in which the decision variables are the optimal starting time of the appliances. The model is simulated under a day-ahead electricity pricing for three cases: traditional user, smart user, and smart prosumer. Simulation results show that the proposed technique optimally schedules the appliances so that the electricity payments is reduced and the users comfort is increased.