IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v239y2022ipbs0360544221023057.html
   My bibliography  Save this article

Research on performance and control strategy of multi-cold source district cooling system

Author

Listed:
  • Zhang, Wei
  • Hong, Wenpeng
  • Jin, Xu

Abstract

In China, the annual energy consumption for cooling represents a relatively large and rising trend. District cooling systems (DCSs) have attracted increasing attention owing to their energy-saving operation and high-efficiency. However, a reasonable operation strategy for DCSs with multi-cold sources is still a problem. The main objective of this paper is to present a computer model to investigate the performance of large-scale DCSs in China based on survey data. To evaluate the performance of the system, we established a baseline model and a DCS model with ice thermal storage (ITS). We also developed a control logic that can respond to real-time load changes in a timely manner for both models. A comparison of the two models under a set control strategy revealed that the carbon dioxide emissions (CDEs) and energy consumption of the DCS and ITS (DCS&ITS) were 9% higher than the baseline model without ITS, but the cumulative cooling capacity also increased by 20% to satisfy users 14% of the cooling load demand. ITS has eased the pressure on the power grid while reducing operating costs. The annual operating cost of DCS&ITS was reduced by 6.78% compared with the baseline model, and the overall system efficiency increased by 9.46%.

Suggested Citation

  • Zhang, Wei & Hong, Wenpeng & Jin, Xu, 2022. "Research on performance and control strategy of multi-cold source district cooling system," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023057
    DOI: 10.1016/j.energy.2021.122057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221023057
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122057?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. Chiam, Zhonglin & Easwaran, Arvind & Mouquet, David & Fazlollahi, Samira & Millás, Jaume V., 2019. "A hierarchical framework for holistic optimization of the operations of district cooling systems," Applied Energy, Elsevier, vol. 239(C), pages 23-40.
    2. Farah, Sleiman & Liu, Ming & Saman, Wasim, 2019. "Numerical investigation of phase change material thermal storage for space cooling," Applied Energy, Elsevier, vol. 239(C), pages 526-535.
    3. Inayat, Abrar & Raza, Mohsin, 2019. "District cooling system via renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 360-373.
    4. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    5. Ebrahimi, Khosrow & Jones, Gerard F. & Fleischer, Amy S., 2014. "A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 622-638.
    6. Asian Development Bank Institute, 2017. "District Cooling in the People’s Republic of China: Status and Development Potential," Working Papers id:11722, eSocialSciences.
    7. Yan, Chengchu & Gang, Wenjie & Niu, Xiaofeng & Peng, Xujian & Wang, Shengwei, 2017. "Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems," Applied Energy, Elsevier, vol. 205(C), pages 635-643.
    8. Lake, Andrew & Rezaie, Behanz & Beyerlein, Steven, 2017. "Review of district heating and cooling systems for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 417-425.
    9. Gang, Wenjie & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2016. "District cooling systems: Technology integration, system optimization, challenges and opportunities for applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 253-264.
    10. Valerie Eveloy & Dereje S. Ayou, 2019. "Sustainable District Cooling Systems: Status, Challenges, and Future Opportunities, with Emphasis on Cooling-Dominated Regions," Energies, MDPI, vol. 12(2), pages 1-64, January.
    11. Rezaie, Behnaz & Rosen, Marc A., 2012. "District heating and cooling: Review of technology and potential enhancements," Applied Energy, Elsevier, vol. 93(C), pages 2-10.
    12. Sun, Fangtian & Li, Junlong & Fu, Lin & Li, Yonghong & Wang, Ruixiang & Zhang, Shigang, 2020. "New configurations of district heating and cooling system based on absorption and compression chillers driven by waste heat of flue gas from coke ovens," Energy, Elsevier, vol. 193(C).
    13. Jangsten, Maria & Filipsson, Peter & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2020. "High Temperature District Cooling: Challenges and Possibilities Based on an Existing District Cooling System and its Connected Buildings," Energy, Elsevier, vol. 199(C).
    14. Cox, Sam J. & Kim, Dongsu & Cho, Heejin & Mago, Pedro, 2019. "Real time optimal control of district cooling system with thermal energy storage using neural networks," Applied Energy, Elsevier, vol. 238(C), pages 466-480.
    15. Luo, Na & Hong, Tianzhen & Li, Hui & Jia, Ruoxi & Weng, Wenguo, 2017. "Data analytics and optimization of an ice-based energy storage system for commercial buildings," Applied Energy, Elsevier, vol. 204(C), pages 459-475.
    16. Udomsri, Seksan & Bales, Chris & Martin, Andrew R. & Martin, Viktoria, 2012. "Decentralized cooling in district heating network: System simulation and parametric study," Applied Energy, Elsevier, vol. 92(C), pages 175-184.
    17. Chan, Apple L.S. & Chow, Tin-Tai & Fong, Square K.F. & Lin, John Z., 2006. "Performance evaluation of district cooling plant with ice storage," Energy, Elsevier, vol. 31(14), pages 2750-2762.
    18. Anderson, Austin & Rezaie, Behnaz & Rosen, Marc A., 2021. "An innovative approach to enhance sustainability of a district cooling system by adjusting cold thermal storage and chiller operation," Energy, Elsevier, vol. 214(C).
    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. Yan, Biao & Yang, Wansheng & He, Fuquan & Huang, Kehua & Zeng, Wenhao & Zhang, Wenlong & Ye, Haiseng, 2022. "Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact," Energy, Elsevier, vol. 255(C).
    2. Ahmed Al-Nini & Hamdan Haji Ya & Najib Al-Mahbashi & Hilmi Hussin, 2023. "A Review on Green Cooling: Exploring the Benefits of Sustainable Energy-Powered District Cooling with Thermal Energy Storage," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    3. Gao, Cheng & Wang, Dan & Sun, Yuying & Wang, Wei & Zhang, Xiuyu, 2023. "Optimal load dispatch of multi-source looped district cooling systems based on energy and hydraulic performances," Energy, Elsevier, vol. 274(C).

    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. Valerie Eveloy & Dereje S. Ayou, 2019. "Sustainable District Cooling Systems: Status, Challenges, and Future Opportunities, with Emphasis on Cooling-Dominated Regions," Energies, MDPI, vol. 12(2), pages 1-64, January.
    2. Zabala, Laura & Febres, Jesus & Sterling, Raymond & López, Susana & Keane, Marcus, 2020. "Virtual testbed for model predictive control development in district cooling systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    3. Sun, Fangtian & Li, Junlong & Fu, Lin & Li, Yonghong & Wang, Ruixiang & Zhang, Shigang, 2020. "New configurations of district heating and cooling system based on absorption and compression chillers driven by waste heat of flue gas from coke ovens," Energy, Elsevier, vol. 193(C).
    4. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    5. Yan, Chengchu & Gang, Wenjie & Niu, Xiaofeng & Peng, Xujian & Wang, Shengwei, 2017. "Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems," Applied Energy, Elsevier, vol. 205(C), pages 635-643.
    6. Cao, Hui & Lin, Jiajing & Li, Nan, 2023. "Optimal control and energy efficiency evaluation of district ice storage system," Energy, Elsevier, vol. 276(C).
    7. Rabah Ismaen & Tarek Y. ElMekkawy & Shaligram Pokharel & Adel Elomri & Mohammed Al-Salem, 2022. "Solar Technology and District Cooling System in a Hot Climate Regions: Optimal Configuration and Technology Selection," Energies, MDPI, vol. 15(7), pages 1-24, April.
    8. Ríos-Ocampo, J.P. & Olaya, Y. & Osorio, A. & Henao, D. & Smith, R. & Arango-Aramburo, S., 2022. "Thermal districts in Colombia: Developing a methodology to estimate the cooling potential demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    9. Østergaard, Poul Alberg & Werner, Sven & Dyrelund, Anders & Lund, Henrik & Arabkoohsar, Ahmad & Sorknæs, Peter & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Mathiesen, Brian Vad, 2022. "The four generations of district cooling - A categorization of the development in district cooling from origin to future prospect," Energy, Elsevier, vol. 253(C).
    10. Mika Fabricius & Daniel Øland Tarp & Thomas Wehl Rasmussen & Ahmad Arabkoohsar, 2020. "Utilization of Excess Production of Waste-Fired CHP Plants for District Cooling Supply, an Effective Solution for a Serious Challenge," Energies, MDPI, vol. 13(13), pages 1-21, June.
    11. Rismanchi, B., 2017. "District energy network (DEN), current global status and future development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 571-579.
    12. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu, 2023. "Globally optimal control of hybrid chilled water plants integrated with small-scale thermal energy storage for energy-efficient operation," Energy, Elsevier, vol. 262(PA).
    13. Deng, Na & He, Guansong & Gao, Yuan & Yang, Bin & Zhao, Jun & He, Shunming & Tian, Xue, 2017. "Comparative analysis of optimal operation strategies for district heating and cooling system based on design and actual load," Applied Energy, Elsevier, vol. 205(C), pages 577-588.
    14. Werner, Sven, 2017. "International review of district heating and cooling," Energy, Elsevier, vol. 137(C), pages 617-631.
    15. Neri, Manfredi & Guelpa, Elisa & Verda, Vittorio, 2022. "Design and connection optimization of a district cooling network: Mixed integer programming and heuristic approach," Applied Energy, Elsevier, vol. 306(PA).
    16. Inayat, Abrar & Raza, Mohsin, 2019. "District cooling system via renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 360-373.
    17. Pieper, Henrik & Krupenski, Igor & Brix Markussen, Wiebke & Ommen, Torben & Siirde, Andres & Volkova, Anna, 2021. "Method of linear approximation of COP for heat pumps and chillers based on thermodynamic modelling and off-design operation," Energy, Elsevier, vol. 230(C).
    18. Simon Pezzutto & Philippe Riviere & Lukas Kranzl & Andrea Zambito & Giulio Quaglini & Antonio Novelli & Marcus Hummel & Luigi Bottecchia & Eric Wilczynski, 2022. "Recent Advances in District Cooling Diffusion in the EU27+UK: An Assessment of the Market," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    19. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
    20. Li, Yu & Rezgui, Yacine & Zhu, Hanxing, 2017. "District heating and cooling optimization and enhancement – Towards integration of renewables, storage and smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 281-294.

    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:239:y:2022:i:pb:s0360544221023057. 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.