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Application of entransy in the analysis of HVAC systems in buildings

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  • Zhang, Lun
  • Liu, Xiaohua
  • Jiang, Yi

Abstract

The main task of HVAC systems in the cooling condition is to remove heat from indoor environment to outdoor environment. HVAC systems are complex networks of various processes, e.g., heat transfer, heat–work conversion, heat–humidity conversion, etc. These processes correspond to equipment such as heat exchangers, indoor cooling terminals, heat pumps, and cooling towers. Single analysis method or thermal parameter could hardly describe all the processes in an HVAC system. Exergy destruction refers to the loss of heat–work conversion ability. Reducing exergy destruction indicates less supplied exergy (input work) of HVAC systems. Entransy is a new parameter defined as heat transfer ability. Entransy dissipation refers to the loss of heat transfer ability. When the purpose of heat transfer is cooling or heating, entransy analysis is a direct method for optimizing heat transfer processes. Loss of HVAC system is mainly in heat transfer process. The entransy dissipation extremum principle or the minimum thermal resistance principle is suitable for analyzing heat transfer process in HVAC system. For indoor cooling, reducing entransy dissipation will increase chilled water temperature. Flow unmatched coefficient ξ represents an increase of thermal resistance of heat exchanger if the calorific capacities of the fluids are different.

Suggested Citation

  • Zhang, Lun & Liu, Xiaohua & Jiang, Yi, 2013. "Application of entransy in the analysis of HVAC systems in buildings," Energy, Elsevier, vol. 53(C), pages 332-342.
    • Handle: RePEc:eee:energy:v:53:y:2013:i:c:p:332-342
    DOI: 10.1016/j.energy.2013.02.015
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    References listed on IDEAS

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    Cited by:

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    3. Wang, Sheng & Xie, Xiaoyun & Jiang, Yi, 2014. "Optimization design of the large temperature lift/drop multi-stage vertical absorption temperature transformer based on entransy dissipation method," Energy, Elsevier, vol. 68(C), pages 712-721.
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    5. He, Yueer & Liu, Meng & Kvan, Thomas & Yan, Lu, 2019. "A quantity-quality-based optimization method for indoor thermal environment design," Energy, Elsevier, vol. 170(C), pages 1261-1278.
    6. Zeng, Yaohui & Zhang, Zijun & Kusiak, Andrew, 2015. "Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms," Energy, Elsevier, vol. 86(C), pages 393-402.
    7. Men, Yiyu & Liu, Xiaohua & Zhang, Tao, 2020. "Analytical solutions of heat and mass transfer process in combined gas-water heat exchanger applied for waste heat recovery," Energy, Elsevier, vol. 206(C).
    8. Guiqiang Wang & Haiman Wang & Zhiqiang Kang & Guohui Feng, 2020. "Data-Driven Optimization for Capacity Control of Multiple Ground Source Heat Pump System in Heating Mode," Energies, MDPI, vol. 13(14), pages 1-15, July.
    9. Yan, Bofeng & Xue, Song & Li, Yuanfei & Duan, Jinhui & Zeng, Ming, 2016. "Gas-fired combined cooling, heating and power (CCHP) in Beijing: A techno-economic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 118-131.

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