{"title":"QUANTIFICATION OF DEMAND-SIDE FLEXIBILITY FOR A SMART ACTIVE RESIDENTIAL BUILDING","authors":"V. Stepaniuk, J. Pillai, B. Bak‐Jensen","doi":"10.1049/icp.2021.1376","DOIUrl":null,"url":null,"abstract":"According to EU's energy efficiency and climatic change prevention strategy, one of the largest accents in smartening the grid for high penetration of distributed and intermittent renewable energy sources (RESs) is now being made on buildings. Buildings are the largest end-use sector taking about 40% of total final energy consumption and 55% of electricity consumption in the EU-28 in 2012. It is considered as one of the most prospective platforms when utilised smartly to solve discrepancies from mismatch between intermittent energy generation and demand. Referring to the energy performance of Buildings Directive, the flexibility of a building's overall electricity demand, including its ability to enable participation in demand response (DR) is highlighted as one of three main smart grid readiness indicators and key functionalities of buildings. However, flexibility is easy to define but not easy to quantify. This paper aims to quantify the flexibility, namely the actual amount of peak-hour energy that can be shaved through DR application in active residential building equipped with a heat pump (HP) and hot water storage tank (HWST). The advantage of this study is a detailed HP energy model including restarting delay, energy conversion delay, defrost mode, guaranteed power-on duration, aimed to maximally reflect its operating behaviour. The computation of flexibility is realized using a rule-based management strategy to provide a response to a technical (incentive-based and reliability-oriented) DR signal without violating user thermal comfort preferences when following all the aforementioned limitations. Two different storage sizes and two different operational scenarios “with” and “without” DR application are compared.","PeriodicalId":223615,"journal":{"name":"The 9th Renewable Power Generation Conference (RPG Dublin Online 2021)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 9th Renewable Power Generation Conference (RPG Dublin Online 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/icp.2021.1376","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
According to EU's energy efficiency and climatic change prevention strategy, one of the largest accents in smartening the grid for high penetration of distributed and intermittent renewable energy sources (RESs) is now being made on buildings. Buildings are the largest end-use sector taking about 40% of total final energy consumption and 55% of electricity consumption in the EU-28 in 2012. It is considered as one of the most prospective platforms when utilised smartly to solve discrepancies from mismatch between intermittent energy generation and demand. Referring to the energy performance of Buildings Directive, the flexibility of a building's overall electricity demand, including its ability to enable participation in demand response (DR) is highlighted as one of three main smart grid readiness indicators and key functionalities of buildings. However, flexibility is easy to define but not easy to quantify. This paper aims to quantify the flexibility, namely the actual amount of peak-hour energy that can be shaved through DR application in active residential building equipped with a heat pump (HP) and hot water storage tank (HWST). The advantage of this study is a detailed HP energy model including restarting delay, energy conversion delay, defrost mode, guaranteed power-on duration, aimed to maximally reflect its operating behaviour. The computation of flexibility is realized using a rule-based management strategy to provide a response to a technical (incentive-based and reliability-oriented) DR signal without violating user thermal comfort preferences when following all the aforementioned limitations. Two different storage sizes and two different operational scenarios “with” and “without” DR application are compared.