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A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems

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  • Du, Zhimin
  • Jin, Xinqiao
  • Fang, Xing
  • Fan, Bo

Abstract

Optimal control strategies have been increasingly developed in heating, ventilation and air conditioning (HVAC) systems. The commonly used evaluation method, which compares the system’s energy consumption under proposed strategy with that under its original control, has several limitations. A dual-benchmark based CPI (control-perfect index) evaluation method is presented to assess the operation of an airport HVAC system under various control strategies. Firstly, the exergy loss models based on the HVAC productive structure are developed to analyze the exergy efficiency of component and system. Secondly, control-perfect index based on the process exergy analysis is presented as an evaluation factor for the operation of HVAC system. In addition, the original control of system is used as the 1st benchmark to estimate the energy saving capacity of proposed strategy. The ideal operation, which is obtained through the global optimization of exergy loss models, is used as the 2nd benchmark to estimate the improving potential of candidate strategy. Finally, twelve control strategies used in the airport HVAC system are evaluated through the CPI analysis of both component and system. Their energy saving ratios to Benchmark 1 and improving potentials to Benchmark 2 are compared, respectively.

Suggested Citation

  • Du, Zhimin & Jin, Xinqiao & Fang, Xing & Fan, Bo, 2016. "A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems," Applied Energy, Elsevier, vol. 183(C), pages 700-714.
    • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:700-714
    DOI: 10.1016/j.apenergy.2016.09.019
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    References listed on IDEAS

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    Cited by:

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    5. Jia, Zhiyang & Jin, Xinqiao & Lyu, Yuan & Xue, Qi & Du, Zhimin, 2023. "A robust capacity configuration selection method of multiple-chiller system concerned with the uncertainty of annual hourly load profile," Energy, Elsevier, vol. 282(C).
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    7. Alessia Arteconi & Fabio Polonara, 2018. "Assessing the Demand Side Management Potential and the Energy Flexibility of Heat Pumps in Buildings," Energies, MDPI, vol. 11(7), pages 1-19, July.
    8. Deng, Jiewen & Wei, Qingpeng & Qian, Yangyang & Zhang, Hui, 2018. "Does magnetic bearing variable-speed centrifugal chiller perform truly energy efficient in buildings: Field-test and simulation results," Applied Energy, Elsevier, vol. 229(C), pages 998-1009.
    9. Asad, Hussain Syed & Yuen, Richard Kwok Kit & Huang, Gongsheng, 2017. "Multiplexed real-time optimization of HVAC systems with enhanced control stability," Applied Energy, Elsevier, vol. 187(C), pages 640-651.
    10. Li, Guannan & Hu, Yunpeng & Chen, Huanxin & Li, Haorong & Hu, Min & Guo, Yabin & Liu, Jiangyan & Sun, Shaobo & Sun, Miao, 2017. "Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions," Applied Energy, Elsevier, vol. 185(P1), pages 846-861.
    11. Jing Zhao & Yu Shan, 2020. "A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System," Energies, MDPI, vol. 13(3), pages 1-17, January.
    12. Junqi Wang & Rundong Liu & Linfeng Zhang & Hussain Syed ASAD & Erlin Meng, 2019. "Triggering Optimal Control of Air Conditioning Systems by Event-Driven Mechanism: Comparing Direct and Indirect Approaches," Energies, MDPI, vol. 12(20), pages 1-20, October.

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