K. Yuasa, Yoshiharu Takeuchi, T. Babasaki, Ichiro Omura
{"title":"Optimized Energy Allocation Method Based on Capital Asset Pricing Model for Multi-use of Battery Energy Storage System","authors":"K. Yuasa, Yoshiharu Takeuchi, T. Babasaki, Ichiro Omura","doi":"10.23919/IPEC-Himeji2022-ECCE53331.2022.9807094","DOIUrl":null,"url":null,"abstract":"We propose an optimized energy allocation method for multi-use applications of battery energy storage systems (BESS). The proposed method uses the capital asset pricing model (CAPM), an expansion of portfolio theory used in financial engineering, to quantitatively evaluate the expected return and risk resulting from the energy allocation of BESS. By using this method, it is possible to determine the maximum expected return for the selected acceptable risk. The predictability is further improved by applying an ensemble approach to the proposed method. We report the results of a case study on the effectiveness of the proposed method for three energy trading markets. The results revealed a mean absolute error of approximately 2.0% between the expected return of the proposed method and the actual return.","PeriodicalId":256507,"journal":{"name":"2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IPEC-Himeji2022-ECCE53331.2022.9807094","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
We propose an optimized energy allocation method for multi-use applications of battery energy storage systems (BESS). The proposed method uses the capital asset pricing model (CAPM), an expansion of portfolio theory used in financial engineering, to quantitatively evaluate the expected return and risk resulting from the energy allocation of BESS. By using this method, it is possible to determine the maximum expected return for the selected acceptable risk. The predictability is further improved by applying an ensemble approach to the proposed method. We report the results of a case study on the effectiveness of the proposed method for three energy trading markets. The results revealed a mean absolute error of approximately 2.0% between the expected return of the proposed method and the actual return.