Residential end-use energy estimation models in Korean apartment units through multiple regression analysis

Soo Jin Lee, You Jeong Kim, Hye Sun Jin, Sung Im Kim, Soo Yeon Ha, Seung Yeong Song

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The aim of this study was to develop a mathematical regression model for predicting end-use energy consumption in the residential sector. To this end, housing characteristics were collected through a field survey and in-depth interviews with residents of 71 households (15 apartment complexes) in Seoul, South Korea, and annual data on end-use energy consumption were collected from measurement systems installed within each apartment unit. Based on the data collected, correlativity between the field-survey data and end-use energy consumption was analyzed, and effective independent variables from the field-survey data were selected. Regression models were developed and validated for estimating six end uses of energy consumption: heating, cooling, domestic hot water (DHW), lighting, electric appliances, and cooking. Regression analysis for ventilation was not applied, and instead a calculation formula was derived, because the energy-consumption proportion was too low. The adj-R2 of the estimation model ranged from 0.406 to 0.703, and the maximum error between measured and estimated values was around ±30%, depending on the end use.

Original languageEnglish
Article number2327
Issue number12
StatePublished - 2019

Bibliographical note

Funding Information:
Funding: This research was supported by a grant (19AUDP-B079104-06) from the Architecture and Urban Development Research Program, funded by the Ministry of Land, Infrastructure, and Transport of the Korean Government.

Publisher Copyright:
© 2019 by the Authors.


  • Apartment unit
  • End-use energy consumption
  • Estimationmodel
  • Multiple regression analysis


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