Research on the Decision-Making Method for the Passive Design Parameters of Zero Energy Houses in Severe Cold Regions Based on Decision Trees

Gang Yao, Yuan Chen (), Chaofan Han and Zhongcheng Duan
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Gang Yao: School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
Yuan Chen: School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
Chaofan Han: School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
Zhongcheng Duan: School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China

Energies, 2024, vol. 17, issue 2, 1-21

Abstract: As the field of zero energy building design and research continues to progress, the use of data analysis methods is on the rise. These methods are applied to create assessment criteria, compare performance, and aid in design decision making. Decision trees, as a data-driven approach, offer interpretability and predictability, assisting designers in summarizing their design experience and serving as a foundation for design references. However, the current application of decision tree methods in the zero energy house sector primarily focuses on HVAC systems, lacking a comprehensive exploration from an architectural design perspective. Therefore, this study presents an empirical method for building and applying models based on decision trees, using zero energy house cases in severely cold regions of China as samples. Through an analysis of the interactions among various passive design parameters and the use of EnergyPlus for performance simulations, a decision tree model is established. This model aids in determining the recommended combinations of passive design parameters that meet the criteria of low energy consumption. Moreover, feature weighting highlights the most influential passive design parameters on building energy consumption, including the length of the architectural gestalt plane, the roof shape, and the ground thermal resistance. This research provides valuable methods and guidance for the design and construction of zero energy houses in severely cold regions of China.

Keywords: severe cold regions; zero energy house; passive design; decision trees (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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