Version 1
: Received: 14 May 2024 / Approved: 15 May 2024 / Online: 15 May 2024 (07:38:32 CEST)
How to cite:
Xu, Z.; Wang, X.; Tang, S.; Chen, Y.; Yang, Y.; Hui, D. Study on Comprehensive Evaluation and Key Influencing Factors of Rural Building Energy Consumption from Energy-Building-Behavior Composite Perspective. Preprints2024, 2024051012. https://doi.org/10.20944/preprints202405.1012.v1
Xu, Z.; Wang, X.; Tang, S.; Chen, Y.; Yang, Y.; Hui, D. Study on Comprehensive Evaluation and Key Influencing Factors of Rural Building Energy Consumption from Energy-Building-Behavior Composite Perspective. Preprints 2024, 2024051012. https://doi.org/10.20944/preprints202405.1012.v1
Xu, Z.; Wang, X.; Tang, S.; Chen, Y.; Yang, Y.; Hui, D. Study on Comprehensive Evaluation and Key Influencing Factors of Rural Building Energy Consumption from Energy-Building-Behavior Composite Perspective. Preprints2024, 2024051012. https://doi.org/10.20944/preprints202405.1012.v1
APA Style
Xu, Z., Wang, X., Tang, S., Chen, Y., Yang, Y., & Hui, D. (2024). Study on Comprehensive Evaluation and Key Influencing Factors of Rural Building Energy Consumption from Energy-Building-Behavior Composite Perspective. Preprints. https://doi.org/10.20944/preprints202405.1012.v1
Chicago/Turabian Style
Xu, Z., Yan Yang and David Hui. 2024 "Study on Comprehensive Evaluation and Key Influencing Factors of Rural Building Energy Consumption from Energy-Building-Behavior Composite Perspective" Preprints. https://doi.org/10.20944/preprints202405.1012.v1
Abstract
A comprehensive evaluation system of rural building energy consumption from a innovative composite perspective is established, which is suitable for southwest China. the brainstorming method and Delphi method were used to establish the indicator system, the ANP method was applied to calculate the weights of the comprehensive evaluation model, the scoring criteria of all evaluation indexes are constructed based on fuzzy evaluation theory, the applicability of the model is verified by an example of the countryside around Chengdu. The results showed that the score of some factors is low, whole or part area, just like the percentage of clean energy use(C24), the thermal performance of external walls(E21), the implementation of energy-saving measures(S22), were key factors affecting the target level, which has greater potential for improvement. The distribution of comprehensive indicators and evaluation factors have certain spatial distribution characteristics, the overall spatial distribution shows the characterwastic of "high in the southeast and low in the northwest". The key factors and spatial distribution characteristics found can be used as an important basis for the improvement of green energy-saving promotion measures, energy-saving retrofit programmes were proposed in terms of additional solar room, energy-saving of external walls and air-conditioning temperature setting guidance.
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
