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A robust capacity configuration selection method of multiple-chiller system concerned with the uncertainty of annual hourly load profile

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  • Jia, Zhiyang
  • Jin, Xinqiao
  • Lyu, Yuan
  • Xue, Qi
  • Du, Zhimin

Abstract

In conventional method, capacity configuration of multiple-chiller system is optimized to achieve the required annual EER (energy efficiency ratio) limit according to a certain annual hourly load profile. However, it usually results in that the required annual EER limit may not be reached because the uncertainty of annual hourly load profile is not concerned. To improve the tolerance for uncertainty of annual hourly load profile, this paper presents a robust method of capacity configuration selection of multiple-chiller system. The maximum acceptable uncertainty region is defined as the maximum range of load variation that a capacity configurated multiple-chiller system can satisfy the required annual EER limit. The robustness index of a capacity configuration is defined according to the area of the maximum acceptable uncertainty region. A novel configuration framework is proposed based on robustness index. The proposed method is validated by configuring multiple-chiller system of a factory building. Results show that multiple-chiller system configurated by proposed method is more robust than that by conventional method. The proposed method can ensure the annual EER of multiple-chiller system to satisfy the required annual EER limit with uncertainty of annual hourly load profile, and its reliability is improved by 14% compared with conventional method.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023940
    DOI: 10.1016/j.energy.2023.129000
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    References listed on IDEAS

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    1. Lee, W.L. & Lee, S.H., 2007. "Developing a simplified model for evaluating chiller-system configurations," Applied Energy, Elsevier, vol. 84(3), pages 290-306, March.
    2. Lian, Kuang-Yow & Hong, Yong-Jie & Chang, Che-Wei & Su, Yu-Wei, 2022. "A novel data-driven optimal chiller loading regulator based on backward modeling approach," Applied Energy, Elsevier, vol. 327(C).
    3. Cheng, Qi & Wang, Shengwei & Yan, Chengchu & Xiao, Fu, 2017. "Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings," Applied Energy, Elsevier, vol. 185(P2), pages 1613-1624.
    4. Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
    5. Gang, Wenjie & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "Robust optimal design of building cooling systems considering cooling load uncertainty and equipment reliability," Applied Energy, Elsevier, vol. 159(C), pages 265-275.
    6. Niu, Jide & Tian, Zhe & Yue, Lu, 2020. "Robust optimal design of building cooling sources considering the uncertainty and cross-correlation of demand and source," Applied Energy, Elsevier, vol. 265(C).
    7. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Huang, Zhijia, 2017. "Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties," Applied Energy, Elsevier, vol. 187(C), pages 62-71.
    8. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Cui, Zhitao & You, Zhiqiang & Ma, Xiaowen, 2023. "Robust enhancement of chiller sequencing control for tolerating sensor measurement uncertainties through controlling small-scale thermal energy storage," Energy, Elsevier, vol. 280(C).
    9. Cheng, Qi & Wang, Shengwei & Yan, Chengchu, 2017. "Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability," Energy, Elsevier, vol. 118(C), pages 489-501.
    10. Xu, Lei & Wang, Shengwei & Tang, Rui, 2019. "Probabilistic load forecasting for buildings considering weather forecasting uncertainty and uncertain peak load," Applied Energy, Elsevier, vol. 237(C), pages 180-195.
    11. Li, Hangxin & Wang, Shengwei, 2017. "Probabilistic optimal design concerning uncertainties and on-site adaptive commissioning of air-conditioning water pump systems in buildings," Applied Energy, Elsevier, vol. 202(C), pages 53-65.
    12. Li, Hangxin & Wang, Shengwei, 2020. "Coordinated robust optimal design of building envelope and energy systems for zero/low energy buildings considering uncertainties," Applied Energy, Elsevier, vol. 265(C).
    13. Zhuang, Chaoqun & Wang, Shengwei & Shan, Kui, 2019. "Probabilistic optimal design of cleanroom air-conditioning systems facilitating optimal ventilation control under uncertainties," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    14. 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.
    15. Chen, Yixing & Hong, Tianzhen, 2018. "Impacts of building geometry modeling methods on the simulation results of urban building energy models," Applied Energy, Elsevier, vol. 215(C), pages 717-735.
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