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Analysis and Optimization of Cooling Water System Operating Cost under Changes in Ambient Temperature and Working Medium Flow

Author

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  • Peng Wang

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Institute of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China)

  • Jinling Lu

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Institute of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China)

  • Qingsen Cai

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Institute of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China)

  • Senlin Chen

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Institute of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China)

  • Xingqi Luo

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Institute of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China)

Abstract

The circulating cooling water system is widely used in various industrial production fields, and its operating cost largely depends on external factors, such as ambient temperature and working medium flow. Considering the relative elevation of the heat exchanger, this study establishes a total system operation cost analysis and optimization model based on the superstructure method. The model uses ambient dry bulb temperature, ambient wet bulb temperature, and working medium flow as random variables. Water supply temperature is adopted as the decision variable, and the minimum operating cost of the system is used as the objective function. An analysis of the effect of the three random variables on the operation cost shows that the effect of ambient dry bulb temperature on the operation cost is negligible, and the effect of ambient wet bulb temperature and working medium flow on the operation cost is significant. In addition, a control equation of water supply temperature is established to determine the “near optimal” operation, which is based on the correlation among ambient wet bulb temperature, working medium flow, and optimal water supply temperature. Then, the method is applied to a case system. The operating cost of the system is reduced by 22–31% at different times during the sampling day.

Suggested Citation

  • Peng Wang & Jinling Lu & Qingsen Cai & Senlin Chen & Xingqi Luo, 2021. "Analysis and Optimization of Cooling Water System Operating Cost under Changes in Ambient Temperature and Working Medium Flow," Energies, MDPI, vol. 14(21), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6903-:d:661298
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    References listed on IDEAS

    as
    1. Gao, Wei & Feng, Xiao, 2017. "The power target of a fluid machinery network in a circulating water system," Applied Energy, Elsevier, vol. 205(C), pages 847-854.
    2. Zhang, Haitian & Feng, Xiao & Wang, Yufei & Zhang, Zhen, 2019. "Sequential optimization of cooler and pump networks with different types of cooling," Energy, Elsevier, vol. 179(C), pages 815-822.
    3. Panjeshahi, Mohammad Hassan & Tahouni, Nassim, 2008. "Pressure drop optimisation in debottlenecking of heat exchanger networks," Energy, Elsevier, vol. 33(6), pages 942-951.
    4. Sun, Jin & Feng, Xiao & Wang, Yufei & Deng, Chun & Chu, Khim Hoong, 2014. "Pump network optimization for a cooling water system," Energy, Elsevier, vol. 67(C), pages 506-512.
    5. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2017. "Energy recovery in cooling water system by hydro turbines," Energy, Elsevier, vol. 139(C), pages 329-340.
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    Cited by:

    1. Peng Wang & Xingqi Luo & Jinling Lu & Qiyao Xue & Jiawei Gao & Senlin Chen, 2022. "Energy and Economic Analysis of Power Generation Using Residual Pressure of a Circulating Cooling Water System," Sustainability, MDPI, vol. 14(19), pages 1-20, October.

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