Yuan Cao, Kun Yu, Xingying Chen, Le Bu, Fei Mei, H. Hua, Yu Zheng
{"title":"Optimal Capacity Configuration of Battery Storage System for Zero Energy Office Building on Campus","authors":"Yuan Cao, Kun Yu, Xingying Chen, Le Bu, Fei Mei, H. Hua, Yu Zheng","doi":"10.1109/ICEI57064.2022.00026","DOIUrl":null,"url":null,"abstract":"To reduce greenhouse gas emissions during the operation of buildings, establishing PV systems in buildings has become an effective means. However, PV generation has large intermittency and uncertainty, which makes it difficult to ensure the energy consumption of zero energy building (ZEB). To solve this problem and meet the energy consumption of building loads at different time scales, the battery storage (BS) needs to be installed and the storage capacity needs to be reasonably configured. Not only economic factors but also technical factors must be taken into account at the same time. In this paper, the differences in energy consumption between campus office building loads and ordinary commercial office building loads are analyzed, and then the BS is modelled. After that, the technical and economic indicators are taken into account in the objective function to optimize the capacity of the BS for campus office buildings. The simulation results show that the method adopted in this paper can effectively obtain the optimal capacity configuration for the building battery storage system, and the capacity configuration method can be used for building BS in a more comprehensive way to meet the diverse needs of different scenarios.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Energy Internet (ICEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEI57064.2022.00026","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
To reduce greenhouse gas emissions during the operation of buildings, establishing PV systems in buildings has become an effective means. However, PV generation has large intermittency and uncertainty, which makes it difficult to ensure the energy consumption of zero energy building (ZEB). To solve this problem and meet the energy consumption of building loads at different time scales, the battery storage (BS) needs to be installed and the storage capacity needs to be reasonably configured. Not only economic factors but also technical factors must be taken into account at the same time. In this paper, the differences in energy consumption between campus office building loads and ordinary commercial office building loads are analyzed, and then the BS is modelled. After that, the technical and economic indicators are taken into account in the objective function to optimize the capacity of the BS for campus office buildings. The simulation results show that the method adopted in this paper can effectively obtain the optimal capacity configuration for the building battery storage system, and the capacity configuration method can be used for building BS in a more comprehensive way to meet the diverse needs of different scenarios.