{"title":"Peak Demand Reduction using Energy Storage System for Demand Response","authors":"Hannie Zang, Sunyong Kim, D. Kang, Hyuk Lim","doi":"10.1145/3360322.3360988","DOIUrl":null,"url":null,"abstract":"This paper proposes an energy storage system (ESS) management algorithm to reduce the peak electricity consumption for demand response (DR). In a building equipped with an ESS and a photovoltaic generator, the amount of energy charged into the ESS can be used to reduce the peak demand of the following day. The proposed algorithm calculates the feasible amount of peak demand reduction using the information about the amount of net energy demand and the energy charged in ESS, and provides the ESS charging and discharging schedule that can achieve the maximum reduction of the peak demand for DR requests. To examine the performance of the proposed algorithm, a case study was conducted using real-life data measured within a campus building.","PeriodicalId":128826,"journal":{"name":"Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3360322.3360988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an energy storage system (ESS) management algorithm to reduce the peak electricity consumption for demand response (DR). In a building equipped with an ESS and a photovoltaic generator, the amount of energy charged into the ESS can be used to reduce the peak demand of the following day. The proposed algorithm calculates the feasible amount of peak demand reduction using the information about the amount of net energy demand and the energy charged in ESS, and provides the ESS charging and discharging schedule that can achieve the maximum reduction of the peak demand for DR requests. To examine the performance of the proposed algorithm, a case study was conducted using real-life data measured within a campus building.