Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings

Jaewan Joe, Seunghyeon Min, Seunghwan Oh, Byungwoo Jung, Yu Min Kim, Deuk Woo Kim, Seung Eon Lee and Dong Hyuk Yi
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Jaewan Joe: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Seunghyeon Min: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Seunghwan Oh: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Byungwoo Jung: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Yu Min Kim: Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea
Deuk Woo Kim: Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea
Seung Eon Lee: Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea
Dong Hyuk Yi: Korea Testing Laboratory, Jinju 52852, Korea

Sustainability, 2022, vol. 14, issue 10, 1-13

Abstract: 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.

Keywords: reference building model; building energy policymaking; regression; greenhouse gas (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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