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Comparison of linear and nonlinear statistical models for analyzing determinants of residential energy consumption

Title
Comparison of linear and nonlinear statistical models for analyzing determinants of residential energy consumption
Authors
Kim, You-JeongLee, Soo-JinJin, Hye-SunSuh, In-AeSong, Seung-Yeong
Ewha Authors
송승영
SCOPUS Author ID
송승영scopus
Issue Date
2020
Journal Title
ENERGY AND BUILDINGS
ISSN
0378-7788JCR Link

1872-6178JCR Link
Citation
ENERGY AND BUILDINGS vol. 223
Keywords
DeterminantsEnergy consumption by end useData-driven approachesMultiple linear regressionDecision tree
Publisher
ELSEVIER SCIENCE SA
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
To effectively establish and implement energy-saving plans for existing buildings, it is important to identify the determinants that influence actual energy consumption. Linear statistical models that have widely used in prior studies present 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 approach 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 71 apartment units in Seoul, South Korea, which were collected by smart-metering and field survey. Through MLR and DT models, building, system, and occupant characteristics that significantly affect each of energy consumption for each end use were identified. In the results, some determinants were common in both models, while some determinants (e.g. the year of the building permit, coefficient of performance of air conditioners, etc.) were found only in the DT. The findings in this study imply that it is desirable to use nonlinear models such as a DT rather than relying only on linear models for comprehensive analysis of the relationships and interactions between variables. (c) 2020 Elsevier B.V. All rights reserved.
DOI
10.1016/j.enbuild.2020.110226
Appears in Collections:
공과대학 > 건축도시시스템공학과 > Journal papers
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