Ieva Pakere, Ivonna Bērziņa, Dace Lauka, D. Blumberga
{"title":"Cooling load as a blind spot for energy system development","authors":"Ieva Pakere, Ivonna Bērziņa, Dace Lauka, D. Blumberga","doi":"10.1109/RTUCON51174.2020.9316562","DOIUrl":null,"url":null,"abstract":"The power consumption for building cooling continues to increase due to higher indoor microclimate requirements and rising outdoor temperatures in summer period. However, the information on real room cooling requirements in Latvia is not currently listed and it is a blind spot when planning solutions for energy efficient cooling system. Therefore, the article presents the methodology for determination of power for cooling purposes in educational building by using hourly power consumption data and regression models.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316562","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
The power consumption for building cooling continues to increase due to higher indoor microclimate requirements and rising outdoor temperatures in summer period. However, the information on real room cooling requirements in Latvia is not currently listed and it is a blind spot when planning solutions for energy efficient cooling system. Therefore, the article presents the methodology for determination of power for cooling purposes in educational building by using hourly power consumption data and regression models.
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