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Benchmarking Evaluation of Building Energy Consumption Based on Data Mining

Author

Listed:
  • Thomas Wu

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Bo Wang

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Dongdong Zhang

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Ziwei Zhao

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Hongyu Zhu

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

University building energy consumption is an important proportion of the total energy consumption of society. In order to work out the problem of poor practicability of the existing benchmarking management method of campus building energy consumption, this study proposes an evaluation model of campus building energy consumption benchmarking management. By analyzing several types of feature data of buildings, this study uses random forest method to determine the building features that have outstanding contributions to building energy consumption intensity and building classification, and uses the K-means method to reclassify buildings based on the building features obtained after screening, to obtain a building category that is more in line with the actual use situation and to solve the problem that the existing building classification is not in line with the reality. Compared with the original classification method, the new classification method showed significant improvement in many indexes, among which DBI decreased by 60.8% and CH increased by 3.73 times. Finally, the quart lines of buildings in the category of new buildings are calculated to obtain the low energy consumption line, medium energy consumption line and high energy consumption line of buildings, so as to improve the accuracy and practicability of energy consumption line classification.

Suggested Citation

  • Thomas Wu & Bo Wang & Dongdong Zhang & Ziwei Zhao & Hongyu Zhu, 2023. "Benchmarking Evaluation of Building Energy Consumption Based on Data Mining," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5211-:d:1098004
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    References listed on IDEAS

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    Cited by:

    1. Mohammed Alnahhal†& Omar Antar & Ahmad Sakhrieh & Muataz Al Hazza, 2024. "Analyzing Energy Consumption in Universities: A Literature Review," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 18-27, May.
    2. Ming Liu & Yufei Que & Nanxin Yang & Chongyi Yan & Qibo Liu, 2024. "Research on Multi-Objective Optimization Design of University Student Center in China Based on Low Energy Consumption and Thermal Comfort," Energies, MDPI, vol. 17(9), pages 1-22, April.

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