M. Böhringer, Achraf Kharrat, J. Hanson, David Petermann, N. Büchau, Christian Hein, Sebastian Baumann, C. Preusche
{"title":"Dimensioning of Community Energy Storages for Multi-Use Purposes using Households’ Storage Requirements","authors":"M. Böhringer, Achraf Kharrat, J. Hanson, David Petermann, N. Büchau, Christian Hein, Sebastian Baumann, C. Preusche","doi":"10.1109/UPEC55022.2022.9917871","DOIUrl":null,"url":null,"abstract":"In this paper, a method is presented to determine community energy storage’s size in residential districts. To identify required storage size, different clusters are formed for households’ storage requirements. Clusters are differing in generation and load size, as well as using heat pumps and/or electric vehicle charging stations. Maximum installed capacity of photovoltaics plays a relevant role in cluster classification as well. Taking corresponding needs from multi-use operation into account, the model is extended accordingly. It becomes clear that relevant for shared storage sizing are the months in spring and autumn. Major drivers during these months are the use of electric heat pumps as well as installed photovoltaic capacity. In contrast, electric vehicle charging stations generally increases storage shares across all months and all clusters. Using storage shares determined for clusters and characteristics, potential for secondary use is determined on two different bases in a second step of the analysis. Results show that during spring and autumn, storage is mostly used by households. By contrast during summer and winter, up to 85% is available for other services. Findings are finally determined using an example of residential district in the region of Darmstadt, South Hesse. The proportion of available flexibility is expected to be high, with a maximum of almost 87 % in the month of December.","PeriodicalId":371561,"journal":{"name":"2022 57th International Universities Power Engineering Conference (UPEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 57th International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC55022.2022.9917871","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
In this paper, a method is presented to determine community energy storage’s size in residential districts. To identify required storage size, different clusters are formed for households’ storage requirements. Clusters are differing in generation and load size, as well as using heat pumps and/or electric vehicle charging stations. Maximum installed capacity of photovoltaics plays a relevant role in cluster classification as well. Taking corresponding needs from multi-use operation into account, the model is extended accordingly. It becomes clear that relevant for shared storage sizing are the months in spring and autumn. Major drivers during these months are the use of electric heat pumps as well as installed photovoltaic capacity. In contrast, electric vehicle charging stations generally increases storage shares across all months and all clusters. Using storage shares determined for clusters and characteristics, potential for secondary use is determined on two different bases in a second step of the analysis. Results show that during spring and autumn, storage is mostly used by households. By contrast during summer and winter, up to 85% is available for other services. Findings are finally determined using an example of residential district in the region of Darmstadt, South Hesse. The proportion of available flexibility is expected to be high, with a maximum of almost 87 % in the month of December.