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Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis

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  • Soo-Jin Lee

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

  • You-Jeong Kim

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

  • Hye-Sun Jin

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

  • Sung-Im Kim

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

  • Soo-Yeon Ha

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

  • Seung-Yeong Song

    (Department of Architectural and Urban System Engineering, Ewha Womans University, Seoul 03760, Korea)

Abstract

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-R 2 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.

Suggested Citation

  • Soo-Jin Lee & You-Jeong Kim & Hye-Sun Jin & Sung-Im Kim & Soo-Yeon Ha & Seung-Yeong Song, 2019. "Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis," Energies, MDPI, vol. 12(12), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2327-:d:240759
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    References listed on IDEAS

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    Cited by:

    1. Hye Gi Kim & Sun Sook Kim, 2020. "Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database," Energies, MDPI, vol. 13(4), pages 1-18, February.

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