IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v306y2022ipas0306261921012939.html
   My bibliography  Save this article

Design and connection optimization of a district cooling network: Mixed integer programming and heuristic approach

Author

Listed:
  • Neri, Manfredi
  • Guelpa, Elisa
  • Verda, Vittorio

Abstract

In densely populated areas, district energy systems can bring significant savings and an overall reduction of CO2 emissions. In particular, district cooling is a valid alternative to conventional cooling technologies. Among the issues related to district cooling there is the relative smaller temperature difference between supply and return respect to district heating. This increases the design and operational costs. Consequently a strong focus is needed on the optimization of district cooling networks. In this paper a mixed integer linear programming model (MILP) and a heuristic model have been developed and implemented for the topology optimization of district cooling networks. The models allow to estimate: (i) the optimal design, (ii) the set of buildings that is convenient to connect to a district cooling network. They have been applied to three different case studies and the main results obtained by the two methods have been assessed and compared. The heuristic method proved to be faster, especially for complex networks. On the other hand, the MILP is more precise and the maximum difference among the models in terms of objective function is about 1.3%. A graph clustering method has also been implemented to improve the performances of the heuristic approach by facilitating its convergence.The models through the optimizations can bring savings up to 3.16% of the total life-cycle cost depending on the case study. They could therefore represent a potential tool that supports decision makers in the planning phase of district cooling networks.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921012939
    DOI: 10.1016/j.apenergy.2021.117994
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921012939
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117994?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. Chow, T. T. & Chan, Apple L. S. & Song, C. L., 2004. "Building-mix optimization in district cooling system implementation," Applied Energy, Elsevier, vol. 77(1), pages 1-13, January.
    2. Buffa, Simone & Cozzini, Marco & D’Antoni, Matteo & Baratieri, Marco & Fedrizzi, Roberto, 2019. "5th generation district heating and cooling systems: A review of existing cases in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 504-522.
    3. Egberts, Paul & Tümer, Can & Loh, Kelvin & Octaviano, Ryvo, 2020. "Challenges in heat network design optimization," Energy, Elsevier, vol. 203(C).
    4. Bordin, Chiara & Gordini, Angelo & Vigo, Daniele, 2016. "An optimization approach for district heating strategic network design," European Journal of Operational Research, Elsevier, vol. 252(1), pages 296-307.
    5. 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.
    6. 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.
    7. Powell, Kody M. & Cole, Wesley J. & Ekarika, Udememfon F. & Edgar, Thomas F., 2013. "Optimal chiller loading in a district cooling system with thermal energy storage," Energy, Elsevier, vol. 50(C), pages 445-453.
    8. Guelpa, Elisa & Toro, Claudia & Sciacovelli, Adriano & Melli, Roberto & Sciubba, Enrico & Verda, Vittorio, 2016. "Optimal operation of large district heating networks through fast fluid-dynamic simulation," Energy, Elsevier, vol. 102(C), pages 586-595.
    9. Chow, T. T. & Au, W. H. & Yau, Raymond & Cheng, Vincent & Chan, Apple & Fong, K. F., 2004. "Applying district-cooling technology in Hong Kong," Applied Energy, Elsevier, vol. 79(3), pages 275-289, November.
    10. Guelpa, Elisa & Verda, Vittorio, 2018. "Model for optimal malfunction management in extended district heating networks," Applied Energy, Elsevier, vol. 230(C), pages 519-530.
    11. Jangsten, Maria & Lindholm, Torbjörn & Dalenbäck, Jan-Olof, 2020. "Analysis of operational data from a district cooling system and its connected buildings," Energy, Elsevier, vol. 203(C).
    12. 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.
    13. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    14. Lund, Henrik & Werner, Sven & Wiltshire, Robin & Svendsen, Svend & Thorsen, Jan Eric & Hvelplund, Frede & Mathiesen, Brian Vad, 2014. "4th Generation District Heating (4GDH)," Energy, Elsevier, vol. 68(C), pages 1-11.
    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. Wack, Yannick & Serra, Sylvain & Baelmans, Martine & Reneaume, Jean-Michel & Blommaert, Maarten, 2023. "Nonlinear topology optimization of District Heating Networks: A benchmark of a mixed-integer and a density-based approach," Energy, Elsevier, vol. 278(PB).
    2. Akulker, Handan & Aydin, Erdal, 2023. "Optimal design and operation of a multi-energy microgrid using mixed-integer nonlinear programming: Impact of carbon cap and trade system and taxing on equipment selections," Applied Energy, Elsevier, vol. 330(PA).
    3. Pietro Catrini & Tancredi Testasecca & Alessandro Buscemi & Antonio Piacentino, 2022. "Exergoeconomics as a Cost-Accounting Method in Thermal Grids with the Presence of Renewable Energy Producers," Sustainability, MDPI, vol. 14(7), pages 1-27, March.
    4. Youn, Young Jik & Im, Yong Hoon, 2023. "Assessment of the feasibility for hybrid seawater district cooling model under variable seawater temperature condition: Case study in South Korea," Renewable Energy, Elsevier, vol. 218(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. Guelpa, E. & Capone, M. & Sciacovelli, A. & Vasset, N. & Baviere, R. & Verda, V., 2023. "Reduction of supply temperature in existing district heating: A review of strategies and implementations," Energy, Elsevier, vol. 262(PB).
    2. Omais Abdur Rehman & Valeria Palomba & Andrea Frazzica & Luisa F. Cabeza, 2021. "Enabling Technologies for Sector Coupling: A Review on the Role of Heat Pumps and Thermal Energy Storage," Energies, MDPI, vol. 14(24), pages 1-30, December.
    3. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    5. Nord, Natasa & Shakerin, Mohammad & Tereshchenko, Tymofii & Verda, Vittorio & Borchiellini, Romano, 2021. "Data informed physical models for district heating grids with distributed heat sources to understand thermal and hydraulic aspects," Energy, Elsevier, vol. 222(C).
    6. Olgierd Niemyjski & Ryszard Zwierzchowski, 2021. "Impact of Water Temperature Changes on Water Loss Monitoring in Large District Heating Systems," Energies, MDPI, vol. 14(8), pages 1-19, April.
    7. 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.
    8. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Salah Vaisi & Saleh Mohammadi & Kyoumars Habibi, 2021. "Heat Mapping, a Method for Enhancing the Sustainability of the Smart District Heat Networks," Energies, MDPI, vol. 14(17), pages 1-17, September.
    10. He, Ke-Lun & Zhao, Tian & Ma, Huan & Chen, Qun, 2023. "Optimal operation of integrated power and thermal systems for flexibility improvement based on evaluation and utilization of heat storage in district heating systems," Energy, Elsevier, vol. 274(C).
    11. Simeoni, Patrizia & Ciotti, Gellio & Cottes, Mattia & Meneghetti, Antonella, 2019. "Integrating industrial waste heat recovery into sustainable smart energy systems," Energy, Elsevier, vol. 175(C), pages 941-951.
    12. 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.
    13. Østergaard, Dorte Skaarup & Smith, Kevin Michael & Tunzi, Michele & Svendsen, Svend, 2022. "Low-temperature operation of heating systems to enable 4th generation district heating: A review," Energy, Elsevier, vol. 248(C).
    14. 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.
    15. Meibodi, Saleh S. & Loveridge, Fleur, 2022. "The future role of energy geostructures in fifth generation district heating and cooling networks," Energy, Elsevier, vol. 240(C).
    16. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    17. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    18. 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.
    19. 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.
    20. Pakere, Ieva & Gravelsins, Armands & Lauka, Dace & Bazbauers, Gatis & Blumberga, Dagnija, 2021. "Linking energy efficiency policies toward 4th generation district heating system," Energy, Elsevier, vol. 234(C).

    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:appene:v:306:y:2022:i:pa:s0306261921012939. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.