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Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis.
- Source :
- Energies (19961073); Jun2019, Vol. 12 Issue 12, p2327, 1p, 2 Color Photographs, 2 Diagrams, 7 Charts, 2 Graphs
- Publication Year :
- 2019
-
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<superscript>2</superscript> 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 12
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 137191196
- Full Text :
- https://doi.org/10.3390/en12122327