{"title":"Scheduling of Residential Appliances Using DSM with Energy Storage in Smart Grid Environment","authors":"N. Babu, S. Vijay, D. Saha, L. Saikia","doi":"10.1109/EPETSG.2018.8658620","DOIUrl":null,"url":null,"abstract":"Demand side management (DSM), with the integration of energy storage devices in the user end has an essential role to play in the development of futuristic smart grids. In this proposed work, a smart power system is presented where each residential user is equipped with an energy storage device. A DSM technique is proposed by rescheduling the operating time slots of each appliance, to minimize the energy cost and also peak-to-average ratio of the system. Particle swarm optimization (PSO) is employed for the autonomous rescheduling purpose of each user's energy consumption pattern for different appliances. Simulations are carried out for all the user's appliances with and without DSM along with Energy consumption systems and battery storage devices with the PSO algorithm in order to reshape the load profile in the proposed model.","PeriodicalId":385912,"journal":{"name":"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPETSG.2018.8658620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Demand side management (DSM), with the integration of energy storage devices in the user end has an essential role to play in the development of futuristic smart grids. In this proposed work, a smart power system is presented where each residential user is equipped with an energy storage device. A DSM technique is proposed by rescheduling the operating time slots of each appliance, to minimize the energy cost and also peak-to-average ratio of the system. Particle swarm optimization (PSO) is employed for the autonomous rescheduling purpose of each user's energy consumption pattern for different appliances. Simulations are carried out for all the user's appliances with and without DSM along with Energy consumption systems and battery storage devices with the PSO algorithm in order to reshape the load profile in the proposed model.