IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v150y2018icp653-669.html
   My bibliography  Save this article

Simultaneous design of pump network and cooling tower allocations for cooling water system synthesis

Author

Listed:
  • Zheng, Chenglin
  • Chen, Xi
  • Zhu, Lingyu
  • Shi, Jiaqi

Abstract

To avoid wasting resources and energy, a simultaneous design approach is proposed for process synthesis of cooling water system in this paper. For a cooling water system involving multiple supplies and cooling water using operations, an integrated optimization is presented in which the pump network, cooling water network and cooling tower are designed as a whole system. Mixed-integer nonlinear programming based on a superstructure description is formulated by considering the configuration of the main-auxiliary pump, the location of the cooling towers, and the supply mode of cooling water simultaneously. Four operational cases are presented and analyzed in detail for the integrated cooling water system design. In all cases, global optimality is achieved with zero integrality gap, thus indicating that the optimal location and load of each cooling tower along with the optimal configurations of the pump network and the cooling water network are obtained. Relaxation techniques for addressing the nonlinear terms in the model are also presented and good performance in computation speed can be achieved.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:653-669
    DOI: 10.1016/j.energy.2018.02.150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218303840
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.02.150?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Zijun & Zeng, Yaohui & Kusiak, Andrew, 2012. "Minimizing pump energy in a wastewater processing plant," Energy, Elsevier, vol. 47(1), pages 505-514.
    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. 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. Bohong Wang & Yongtu Liang & Wei Zhao & Yun Shen & Meng Yuan & Zhimin Li & Jian Guo, 2021. "A Continuous Pump Location Optimization Method for Water Pipe Network Design," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 447-464, January.
    2. Zirngast, Klavdija & Kravanja, Zdravko & Novak Pintarič, Zorka, 2021. "An improved algorithm for synthesis of heat exchanger network with a large number of uncertain parameters," Energy, Elsevier, vol. 233(C).
    3. 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. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2017. "Energy recovery in cooling water system by hydro turbines," Energy, Elsevier, vol. 139(C), pages 329-340.
    2. 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.
    3. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2018. "Optimization of multi-plants cooling water system," Energy, Elsevier, vol. 150(C), pages 797-815.
    4. 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.
    5. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    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. 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).
    8. Taghavifar, Hadi & Khalilarya, Shahram & Jafarmadar, Samad, 2014. "Diesel engine spray characteristics prediction with hybridized artificial neural network optimized by genetic algorithm," Energy, Elsevier, vol. 71(C), pages 656-664.
    9. 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.
    10. Zhang, Zijun & Kusiak, Andrew & Zeng, Yaohui & Wei, Xiupeng, 2016. "Modeling and optimization of a wastewater pumping system with data-mining methods," Applied Energy, Elsevier, vol. 164(C), pages 303-311.
    11. 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.
    12. 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.
    13. Máša, Vítězslav & Stehlík, Petr & Touš, Michal & Vondra, Marek, 2018. "Key pillars of successful energy saving projects in small and medium industrial enterprises," Energy, Elsevier, vol. 158(C), pages 293-304.
    14. Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).
    15. 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.
    16. Arun Shankar, Vishnu Kalaiselvan & Umashankar, Subramaniam & Paramasivam, Shanmugam & Hanigovszki, Norbert, 2016. "A comprehensive review on energy efficiency enhancement initiatives in centrifugal pumping system," Applied Energy, Elsevier, vol. 181(C), pages 495-513.
    17. 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.
    18. Sha, Huajing & Xu, Peng & Yang, Zhiwei & Chen, Yongbao & Tang, Jixu, 2019. "Overview of computational intelligence for building energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 76-90.
    19. Theocharis, Dimitrios & Rodrigues, Vasco Sanchez & Pettit, Stephen & Haider, Jane, 2019. "Feasibility of the Northern Sea Route: The role of distance, fuel prices, ice breaking fees and ship size for the product tanker market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 111-135.
    20. Luca O. Turci & Jingcheng Wang & Ibrahim Brahmia, 2020. "Adaptive and Improved Multi-population Based Nature-inspired Optimization Algorithms for Water Pump Station Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2869-2885, July.

    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:eee:energy:v:150:y:2018:i:c:p:653-669. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.