A Physical Model-Based Data-Driven Approach to Overcome Data Scarcity and Predict Building Energy Consumption

Kyoungcheol Oh, Eui-Jong Kim and Chang-Young Park
Additional contact information
Kyoungcheol Oh: Division of Architecture, College of Engineering, INHA University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea
Eui-Jong Kim: Division of Architecture, College of Engineering, INHA University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea
Chang-Young Park: Institute of Green Building and New Technology, Mirae Environment Plan Architects, Seoul 01905, Korea

Sustainability, 2022, vol. 14, issue 15, 1-14

Abstract: Predicting building energy consumption needs to be anticipated to save building energy and effectively control the predictions. This study depicted the target building as a physical model to improve the learning performance in a data-scarce environment and proposed a model that uses simulation results as the input for a data-driven model. Case studies were conducted with different quantities of data. The proposed hybrid method proposed in this study showed a higher prediction accuracy showing a cvRMSE of 22.8% and an MAE of 6.1% than using the conventional data-driven method and satisfying the tolerance criteria of ASHRAE Guideline 14 in all the test cases.

Keywords: heat pump energy consumption prediction; physical modeling; data-driven model; data scarcity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/15/9464/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/15/9464/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:15:p:9464-:d:878285

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().