Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Identification of Principal Factors in Determining Building Peak Energy Shaving Capacities during Demand Response Events
In the U.S., the building sector consumes 70% of electricity and lays massive pressure on national grids. To avoid electricity blackouts, demand response programs incentivize end-consumers for reducing their electricity demand during peak hours. Therefore, it is essential for grid operators to understand the electricity shaving capacity of buildings. However, previous studies either simplify buildings as black-boxes—resulting in low accuracy in estimations, or represent buildings with detailed information—resulting in over-parameterized models. In this study, the authors provided a computational framework to identify principal factors that dictate peak shaving capacities of buildings. In total, fifteen buildings during twelve DR events were used as testbeds as validation. The results showed that the day-in-the-week and the quantity of relevant equipment are part of the principal factors behind peak capacity determination. With this framework, practitioners can represent buildings beyond black-boxes with less complexity and promising accuracy of peak shaving capacity determination.
Identification of Principal Factors in Determining Building Peak Energy Shaving Capacities during Demand Response Events
In the U.S., the building sector consumes 70% of electricity and lays massive pressure on national grids. To avoid electricity blackouts, demand response programs incentivize end-consumers for reducing their electricity demand during peak hours. Therefore, it is essential for grid operators to understand the electricity shaving capacity of buildings. However, previous studies either simplify buildings as black-boxes—resulting in low accuracy in estimations, or represent buildings with detailed information—resulting in over-parameterized models. In this study, the authors provided a computational framework to identify principal factors that dictate peak shaving capacities of buildings. In total, fifteen buildings during twelve DR events were used as testbeds as validation. The results showed that the day-in-the-week and the quantity of relevant equipment are part of the principal factors behind peak capacity determination. With this framework, practitioners can represent buildings beyond black-boxes with less complexity and promising accuracy of peak shaving capacity determination.
Identification of Principal Factors in Determining Building Peak Energy Shaving Capacities during Demand Response Events
Yu, Xinran (Autor:in) / Ergan, Semiha (Autor:in)
ASCE International Conference on Computing in Civil Engineering 2019 ; 2019 ; Atlanta, Georgia
Computing in Civil Engineering 2019 ; 547-554
13.06.2019
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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