Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings
This study aims to support building energy policymaking for office buildings in South Korea through regression models by considering the global temperature rise. The key variables representing building energy standards and codes are selected, and their impact on the annual energy consumption is simulated using EnergyPlus reference models. Then, simplified regression models are built on the basis of the annual energy consumption using the selected variables. The prediction performance of the developed model for forecasting the annual energy consumption of each reference building is good, and the prediction error is negligible. An additional global coefficient is estimated to address the impact of increased outdoor air temperature in the future. The final model shows fair prediction performance with global coefficients of 1.27 and 0.9 for cooling and heating, respectively. It is expected that the proposed simplified model can be leveraged by non-expert policymakers to predict building energy consumption and corresponding greenhouse gas emissions for the target year.
Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings
This study aims to support building energy policymaking for office buildings in South Korea through regression models by considering the global temperature rise. The key variables representing building energy standards and codes are selected, and their impact on the annual energy consumption is simulated using EnergyPlus reference models. Then, simplified regression models are built on the basis of the annual energy consumption using the selected variables. The prediction performance of the developed model for forecasting the annual energy consumption of each reference building is good, and the prediction error is negligible. An additional global coefficient is estimated to address the impact of increased outdoor air temperature in the future. The final model shows fair prediction performance with global coefficients of 1.27 and 0.9 for cooling and heating, respectively. It is expected that the proposed simplified model can be leveraged by non-expert policymakers to predict building energy consumption and corresponding greenhouse gas emissions for the target year.
Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings
Jaewan Joe (Autor:in) / Seunghyeon Min (Autor:in) / Seunghwan Oh (Autor:in) / Byungwoo Jung (Autor:in) / Yu Min Kim (Autor:in) / Deuk Woo Kim (Autor:in) / Seung Eon Lee (Autor:in) / Dong Hyuk Yi (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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