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Collaborative optimization between passive design measures and active heating systems for building heating in Qinghai-Tibet plateau of China

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  • Wang, Xiaoliang
  • Mai, Xianmin
  • Lei, Bo
  • Bi, Haiquan
  • Zhao, Bing
  • Mao, Gang

Abstract

Due to cold winter and cool summer in Qinghai-Tibet plateau, heating energy consumption accounts for a large proportion in the building energy consumption and reducing heating energy consumption is one of the main energy-saving methods for buildings. In the process of building heating, passive design measures and active heating systems (AHS) are always working together. To optimize the heating performance, it is necessary to coordinate the relationship between passive design measures and the AHS. However, it is impossible to obtain the specific quantitative optimized relationship between passive design measures and AHS based on existing research methods. To address this lack of knowledge, a collaborative optimization design method (CODM) is proposed in this paper to optimize the cost and the energy consumption of heating in the life cycle of the building. In CODM, comprehensive effects of passive design measures and the AHS on the total cost and the total energy consumption for building heating are analyzed. A railway passenger station is selected as a case study and results show that compared with initial design, the optimal total heating cost and total heating energy consumption for building heating can reduce 1948 ￥/m2 and 2292 kW h/m2 for the life cycle of the building, respectively.

Suggested Citation

  • Wang, Xiaoliang & Mai, Xianmin & Lei, Bo & Bi, Haiquan & Zhao, Bing & Mao, Gang, 2020. "Collaborative optimization between passive design measures and active heating systems for building heating in Qinghai-Tibet plateau of China," Renewable Energy, Elsevier, vol. 147(P1), pages 683-694.
    • Handle: RePEc:eee:renene:v:147:y:2020:i:p1:p:683-694
    DOI: 10.1016/j.renene.2019.09.031
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    References listed on IDEAS

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    1. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
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    Cited by:

    1. Jiang, L. & Li, S. & Wang, R.Q. & Fan, Y.B. & Zhang, X.J. & Roskilly, A.P., 2021. "Performance analysis on a hybrid compression-assisted sorption thermal battery for seasonal heat storage in severe cold region," Renewable Energy, Elsevier, vol. 180(C), pages 398-409.
    2. Ahsan Waqar & Idris Othman & Nasir Shafiq & Hasim Altan & Bertug Ozarisoy, 2023. "Modeling the Effect of Overcoming the Barriers to Passive Design Implementation on Project Sustainability Building Success: A Structural Equation Modeling Perspective," Sustainability, MDPI, vol. 15(11), pages 1-26, June.
    3. Hawks, M.A. & Cho, S., 2024. "Review and analysis of current solutions and trends for zero energy building (ZEB) thermal systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    4. Liu, Yanfeng & Zhao, Yiting & Chen, Yaowen & Wang, Dengjia & Li, Yong & Yuan, Xipeng, 2022. "Design optimization of the solar heating system for office buildings based on life cycle cost in Qinghai-Tibet plateau of China," Energy, Elsevier, vol. 246(C).
    5. Weihao Huang & Qifan Xu, 2024. "Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches," Sustainability, MDPI, vol. 16(10), pages 1-35, May.
    6. Huan Zhang & Yajie Wang & Xianze Liu & Fujing Wan & Wandong Zheng, 2024. "Multi-Objective Optimization with Active–Passive Technology Synergy for Rural Residences in Northern China," Energies, MDPI, vol. 17(7), pages 1-25, March.

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