IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i21p6903-d661298.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/21/6903/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/21/6903/
    Download Restriction: no
    ---><---

    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. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2017. "Energy recovery in cooling water system by hydro turbines," Energy, Elsevier, vol. 139(C), pages 329-340.
    3. 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.
    4. Panjeshahi, Mohammad Hassan & Tahouni, Nassim, 2008. "Pressure drop optimisation in debottlenecking of heat exchanger networks," Energy, Elsevier, vol. 33(6), pages 942-951.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2018. "Optimization of multi-plants cooling water system," Energy, Elsevier, vol. 150(C), pages 797-815.
    3. Zheng, Chenglin & Chen, Xi & Zhu, Lingyu & Shi, Jiaqi, 2018. "Simultaneous design of pump network and cooling tower allocations for cooling water system synthesis," Energy, Elsevier, vol. 150(C), pages 653-669.
    4. Hebert Lugo-Granados & Lázaro Canizalez-Dávalos & Martín Picón-Núñez, 2021. "Comprehensive analysis of the thermohydraulic performance of cooling networks subject to fouling and undergoing retrofit projects," Energy & Environment, , vol. 32(8), pages 1414-1436, December.
    5. Andiappan, Viknesh & Ng, Denny K.S. & Tan, Raymond R., 2017. "Design Operability and Retrofit Analysis (DORA) framework for energy systems," Energy, Elsevier, vol. 134(C), pages 1038-1052.
    6. Wang, Yufei & Zhan, Shihui & Feng, Xiao, 2015. "Optimization of velocity for energy saving and mitigating fouling in a crude oil preheat train with fixed network structure," Energy, Elsevier, vol. 93(P2), pages 1478-1488.
    7. Venturini, Mauro & Manservigi, Lucrezia & Alvisi, Stefano & Simani, Silvio, 2018. "Development of a physics-based model to predict the performance of pumps as turbines," Applied Energy, Elsevier, vol. 231(C), pages 343-354.
    8. Picón-Núñez, Martín & Rumbo-Arias, Jamel E., 2021. "Improving thermal energy recovery systems using welded plate heat exchangers," Energy, Elsevier, vol. 235(C).
    9. Shen, Zhicheng & Yao, Yao & Wang, Qiliang & Lu, Lin & Yang, Hongxing, 2023. "A novel micro power generation system to efficiently harvest hydroelectric energy for power supply to water intelligent networks of urban water pipelines," Energy, Elsevier, vol. 268(C).
    10. Liu, Pu & Cui, Guomin & Xiao, Yuan & Chen, Jiaxing, 2018. "A new heuristic algorithm with the step size adjustment strategy for heat exchanger network synthesis," Energy, Elsevier, vol. 143(C), pages 12-24.
    11. Gu, Yandong & Pei, Ji & Yuan, Shouqi & Wang, Wenjie & Zhang, Fan & Wang, Peng & Appiah, Desmond & Liu, Yong, 2019. "Clocking effect of vaned diffuser on hydraulic performance of high-power pump by using the numerical flow loss visualization method," Energy, Elsevier, vol. 170(C), pages 986-997.
    12. 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.
    13. Pan, Ming & Smith, Robin & Bulatov, Igor, 2013. "A novel optimization approach of improving energy recovery in retrofitting heat exchanger network with exchanger details," Energy, Elsevier, vol. 57(C), pages 188-200.
    14. Kew Hong Chew & Jiří Jaromír Klemeš & Sharifah Rafidah Wan Alwi & Zainuddin Abdul Manan & Andrea Pietro Reverberi, 2015. "Total Site Heat Integration Considering Pressure Drops," Energies, MDPI, vol. 8(2), pages 1-24, February.
    15. Valiani, Saba & Tahouni, Nassim & Panjeshahi, M. Hassan, 2017. "Optimization of pre-combustion capture for thermal power plants using Pinch Analysis," Energy, Elsevier, vol. 119(C), pages 950-960.
    16. Soltani, Hadi & Shafiei, Sirous, 2011. "Heat exchanger networks retrofit with considering pressure drop by coupling genetic algorithm with LP (linear programming) and ILP (integer linear programming) methods," Energy, Elsevier, vol. 36(5), pages 2381-2391.
    17. 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.
    18. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2017. "Energy recovery in cooling water system by hydro turbines," Energy, Elsevier, vol. 139(C), pages 329-340.
    19. Tian, Jiayang & Wang, Yufei & Feng, Xiao, 2016. "Simultaneous optimization of flow velocity and cleaning schedule for mitigating fouling in refinery heat exchanger networks," Energy, Elsevier, vol. 109(C), pages 1118-1129.
    20. Ifaei, Pouya & Farid, Alireza & Yoo, ChangKyoo, 2018. "An optimal renewable energy management strategy with and without hydropower using a factor weighted multi-criteria decision making analysis and nation-wide big data - Case study in Iran," Energy, Elsevier, vol. 158(C), pages 357-372.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6903-:d:661298. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.