IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v274y2023ics0360544223007570.html
   My bibliography  Save this article

Optimal load dispatch of multi-source looped district cooling systems based on energy and hydraulic performances

Author

Listed:
  • Gao, Cheng
  • Wang, Dan
  • Sun, Yuying
  • Wang, Wei
  • Zhang, Xiuyu

Abstract

Multi-source looped district cooling (MLDC) systems exhibit promising application potential owing to their ability to utilize various renewable energy resources. The load dispatch for multiple sources is considered a critical factor during operation owing to its effects on the energy and hydraulic performance. However, few studies have investigated the behavior of energy and hydraulic performance under different load dispatch ratios (LDRs). In addition, straightforward methods for determining the optimal load dispatch of MLDC systems have not been introduced. This study investigated the relationship between the load dispatch and operating performance and proposed a fundamental method to achieve optimal load dispatch for MLDC systems and overcome the existing challenges. A double-source looped district cooling system was selected as the case study, and its Modelica model was developed. Subsequently, we investigated the relationship between the LDRs and operating performance, and verified the existence of an optimal LDR (LDRopt), which achieves the best hydraulic performance and lowest energy consumption. Finally, a dataset constructed using a hybrid optimization algorithm was employed to develop a multi-variable data-driven model for predicting LDRopt under various load conditions. This study provides a valuable framework and recommendations for further investigation of the optimal control of MLDC systems.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:274:y:2023:i:c:s0360544223007570
    DOI: 10.1016/j.energy.2023.127363
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223007570
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127363?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. Pieper, Henrik & Ommen, Torben & Elmegaard, Brian & Brix Markussen, Wiebke, 2019. "Assessment of a combination of three heat sources for heat pumps to supply district heating," Energy, Elsevier, vol. 176(C), pages 156-170.
    2. Capone, Martina & Guelpa, Elisa & Mancò, Giulia & Verda, Vittorio, 2021. "Integration of storage and thermal demand response to unlock flexibility in district multi-energy systems," Energy, Elsevier, vol. 237(C).
    3. Lingmin, Chen & Jiekang, Wu & Fan, Wu & Huiling, Tang & Changjie, Li & Yan, Xiong, 2020. "Energy flow optimization method for multi-energy system oriented to combined cooling, heating and power," Energy, Elsevier, vol. 211(C).
    4. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    5. Saidur, R. & Hasanuzzaman, M. & Mahlia, T.M.I. & Rahim, N.A. & Mohammed, H.A., 2011. "Chillers energy consumption, energy savings and emission analysis in an institutional buildings," Energy, Elsevier, vol. 36(8), pages 5233-5238.
    6. Ismaen, Rabah & El Mekkawy, Tarek Y. & Pokharel, Shaligram & Al-Salem, Mohammed, 2022. "System requirements and optimization of multi-chillers district cooling plants," Energy, Elsevier, vol. 246(C).
    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. 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).
    9. Wang, Jiangjiang & Liu, Yi & Ren, Fukang & Lu, Shuaikang, 2020. "Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility," Energy, Elsevier, vol. 197(C).
    10. 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.
    11. Volkova, Anna & Krupenski, Igor & Ledvanov, Aleksandr & Hlebnikov, Aleksandr & Lepiksaar, Kertu & Latõšov, Eduard & Mašatin, Vladislav, 2020. "Energy cascade connection of a low-temperature district heating network to the return line of a high-temperature district heating network," Energy, Elsevier, vol. 198(C).
    12. 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).
    13. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    14. 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).
    15. Wang, Jiangjiang & Yang, Ying, 2017. "A hybrid operating strategy of combined cooling, heating and power system for multiple demands considering domestic hot water preferentially: A case study," Energy, Elsevier, vol. 122(C), pages 444-457.
    16. Dai, Yuanhang & Hao, Junhong & Wang, Xingce & Chen, Lei & Chen, Qun & Du, Xiaoze, 2022. "A comprehensive model and its optimal dispatch of an integrated electrical-thermal system with multiple heat sources," Energy, Elsevier, vol. 261(PA).
    17. 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.
    18. Fang, Tingting & Lahdelma, Risto, 2015. "Genetic optimization of multi-plant heat production in district heating networks," Applied Energy, Elsevier, vol. 159(C), pages 610-619.
    19. Ran, Fengming & Gao, Dian-ce & Zhang, Xu & Chen, Shuyue, 2020. "A virtual sensor based self-adjusting control for HVAC fast demand response in commercial buildings towards smart grid applications," Applied Energy, Elsevier, vol. 269(C).
    20. Gang, Wenjie & Wang, Shengwei & Gao, Diance & Xiao, Fu, 2015. "Performance assessment of district cooling systems for a new development district at planning stage," Applied Energy, Elsevier, vol. 140(C), pages 33-43.
    21. Jie, Pengfei & Tian, Zhe & Yuan, Shanshan & Zhu, Neng, 2012. "Modeling the dynamic characteristics of a district heating network," Energy, Elsevier, vol. 39(1), pages 126-134.
    22. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
    23. Yan, Aibin & Zhao, Jun & An, Qingsong & Zhao, Yulong & Li, Hailong & Huang, Yrjö Jun, 2013. "Hydraulic performance of a new district heating systems with distributed variable speed pumps," Applied Energy, Elsevier, vol. 112(C), pages 876-885.
    24. 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).
    25. Edtmayer, Hermann & Nageler, Peter & Heimrath, Richard & Mach, Thomas & Hochenauer, Christoph, 2021. "Investigation on sector coupling potentials of a 5th generation district heating and cooling network," Energy, Elsevier, vol. 230(C).
    26. Abugabbara, Marwan & Javed, Saqib & Johansson, Dennis, 2022. "A simulation model for the design and analysis of district systems with simultaneous heating and cooling demands," Energy, Elsevier, vol. 261(PA).
    27. Chen, Ke & Pan, Ming, 2021. "Operation optimization of combined cooling, heating, and power superstructure system for satisfying demand fluctuation," Energy, Elsevier, vol. 237(C).
    28. Jiajia Chen & Xiaoqin Zhang & Shengjia Li, 2017. "Multiple linear regression with compositional response and covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2270-2285, September.
    29. Wang, Yaran & You, Shijun & Zhang, Huan & Zheng, Wandong & Zheng, Xuejing & Miao, Qingwei, 2017. "Hydraulic performance optimization of meshed district heating network with multiple heat sources," Energy, Elsevier, vol. 126(C), pages 603-621.
    30. 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)

    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. 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.
    2. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
    3. 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.
    4. 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).
    5. Mengting Jiang & Camilo Rindt & David M. J. Smeulders, 2022. "Optimal Planning of Future District Heating Systems—A Review," Energies, MDPI, vol. 15(19), pages 1-38, September.
    6. Licklederer, Thomas & Hamacher, Thomas & Kramer, Michael & Perić, Vedran S., 2021. "Thermohydraulic model of Smart Thermal Grids with bidirectional power flow between prosumers," Energy, Elsevier, vol. 230(C).
    7. Romanov, D. & Leiss, B., 2022. "Geothermal energy at different depths for district heating and cooling of existing and future building stock," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    9. 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.
    10. Lu, Shuai & Gu, Wei & Zhou, Jinhui & Zhang, Xuesong & Wu, Chenyu, 2018. "Coordinated dispatch of multi-energy system with district heating network: Modeling and solution strategy," Energy, Elsevier, vol. 152(C), pages 358-370.
    11. Wang, Yaran & Shi, Kaiyu & Zheng, Xuejing & You, Shijun & Zhang, Huan & Zhu, Chengzhi & Li, Liang & Wei, Shen & Ding, Chao & Wang, Na, 2020. "Thermo-hydraulic coupled analysis of meshed district heating networks based on improved breadth first search method," Energy, Elsevier, vol. 205(C).
    12. 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).
    13. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    14. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    15. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    16. Sameti, Mohammad & Haghighat, Fariborz, 2018. "Integration of distributed energy storage into net-zero energy district systems: Optimum design and operation," Energy, Elsevier, vol. 153(C), pages 575-591.
    17. Zhang, Lipeng & Gudmundsson, Oddgeir & Thorsen, Jan Eric & Li, Hongwei & Li, Xiaopeng & Svendsen, Svend, 2016. "Method for reducing excess heat supply experienced in typical Chinese district heating systems by achieving hydraulic balance and improving indoor air temperature control at the building level," Energy, Elsevier, vol. 107(C), pages 431-442.
    18. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    19. 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).
    20. 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).

    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:274:y:2023:i:c:s0360544223007570. 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.