ZEMCH 2019 International Conference Proceedings April.2020 | Page 19
Analyzing Determinants of Energy Consumption for
Heating and Cooling in Apartment Units –
Comparison of Linear and Nonlinear Statistical
Models
You‐Jeong Kim 1 , Soo‐Jin Lee 1 , Hye‐Sun Jin 1 and Seung‐Yeong Song 1, *
1 Department of Architecture & Urban Systems Engineering, Ewha Womans University; [email protected]
* Correspondence: [email protected]; Tel.: +82 02‐3277‐3913
Abstract: To develop detailed and effective energy saving plans for existing buildings, determinants
of actual energy consumption should be identified first. Linear statistical models that have widely
used in prior studies presents a major limitation in treating nonlinear problems. Therefore, any
determinant having nonlinear relationship with the energy consumption has been hardly found. To
address this problem, this study proposes a novel way to discover hidden determinants, using both
linear and nonlinear models: multiple linear regression (MLR) and decision tree (DT). This study used
energy consumption and characteristics data of 53 apartment units in Seoul, which were collected by
real‐metering and field survey. Through MLR and DT models, building, system, and occupant
characteristics that significantly affect each of energy consumption for heating and cooling were
identified. As a result, some of determinants were common in both models while some were not (e.g.
year of building permit, COP of air conditioner, and number of employed residents). The result
implies that it is desirable to analyze determinants of energy consumption using both linear and
nonlinear models instead of relying on a single model.
Keywords: Determinants of Energy Consumption; Data‐driven Analysis; Multiple Linear Regression;
Decision Tree; EUI for Heating and Cooling; Apartment Uni
Analyzing Determinants of Energy Consumption for Heating and Cooling in Apartment Units –
Comparison of Linear and Nonlinear Statistical Models
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