| Title |
Correlation Analysis Between Non-Energy Public Data of Residential Buildings and Annual Energy Consumption by Usage |
| Authors |
Ji-Hyoung Kim ; Seon-In Kim ; Young-Joon Park ; Deuk-Woo Kim ; Eui-Jong Kim |
| DOI |
https://doi.org/10.6110/KJACR.2024.36.12.606 |
| Keywords |
건물에너지; 공공데이터; 공동주택; 다중회귀모델 Building energy; Housing public data; Multifamily housing; Multiple regression model |
| Abstract |
The purpose of this study was to develop a multiple regression model for evaluating energy consumption in residential buildings, particularly apartment complexes. With growing concern over global warming and climate change, policies, research, and projects aimed at Net-zero are being implemented worldwide. South Korea is also enforcing the Building Energy Efficiency Certification system (BEEC). However, the BEEC evaluates building energy efficiency based on theoretical energy performance through Energy Use Intensity (EUI), which leads to discrepancies from actual energy usage and hinders precise and objective evaluations. To address this, this study proposed a multiple regression model that could utilize public data to classify building clusters and segment energy uses for a more accurate evaluation. The research process began with collecting public data on apartment complexes in Seoul. After preprocessing the data, clustering techniques were applied to group complexes with similar characteristics. Energy uses were divided into base, cooling, and heating. The model's performance was then quantitatively evaluated. Results of this study provide a complementary framework to BEEC for assessing energy consumption in apartment complexes. They could serve as baseline data for achieving carbon neutrality. |