IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v205y2017icp635-643.html
   My bibliography  Save this article

Quantitative evaluation of the impact of building load characteristics on energy performance of district cooling systems

Author

Listed:
  • Yan, Chengchu
  • Gang, Wenjie
  • Niu, Xiaofeng
  • Peng, Xujian
  • Wang, Shengwei

Abstract

With the rapid increase of research and application of district cooling systems (DCS), the controversy whether DCS is really energy-efficient is intensifying. Building load characteristics of DCS may be a main reason for this controversy. However, how building load characteristics affect the energy performance and which load characteristics can ensure a high performance? To answer such critical questions and improve the energy performance of DCS, this paper presents a systematic method for quantitative analysis and evaluation of the impact of building load characteristics on the energy performance of DCS. Key energy performance indicators are proposed. The load characteristics of DCS are described and quantified by introducing the concept of Lorenz curve and Gini coefficient. “Grouping coefficient” is proposed to evaluate the rationality of grouping different buildings into the same branch of chilled water distribution system. Case studies are conducted to investigate the performance of DCS under different load characteristics and to compare with conventional cooling systems. The impact of Gini coefficient and grouping coefficient on the energy performance of chiller plant, chilled water distribution system and the whole DCS are analysed. Recommendations are provided for future’s application of DCS and individual cooling systems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:205:y:2017:i:c:p:635-643
    DOI: 10.1016/j.apenergy.2017.08.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917310371
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.022?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. 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.
    2. 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.
    3. Cui, Borui & Gao, Dian-ce & Xiao, Fu & Wang, Shengwei, 2017. "Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings," Applied Energy, Elsevier, vol. 201(C), pages 382-396.
    4. Yan, Chengchu & Shi, Wenxing & Li, Xianting & Wang, Shengwei, 2016. "A seasonal cold storage system based on separate type heat pipe for sustainable building cooling," Renewable Energy, Elsevier, vol. 85(C), pages 880-889.
    5. 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.
    6. Liew, Peng Yen & Walmsley, Timothy Gordon & Wan Alwi, Sharifah Rafidah & Abdul Manan, Zainuddin & Klemeš, Jiří Jaromír & Varbanov, Petar Sabev, 2016. "Integrating district cooling systems in Locally Integrated Energy Sectors through Total Site Heat Integration," Applied Energy, Elsevier, vol. 184(C), pages 1350-1363.
    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. 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.
    9. Yan, Chengchu & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "A multi-level energy performance diagnosis method for energy information poor buildings," Energy, Elsevier, vol. 83(C), pages 189-203.
    10. Zhen, Li & Lin, D.M. & Shu, H.W. & Jiang, Shuang & Zhu, Y.X., 2007. "District cooling and heating with seawater as heat source and sink in Dalian, China," Renewable Energy, Elsevier, vol. 32(15), pages 2603-2616.
    11. Yan, Chengchu & Shi, Wenxing & Li, Xianting & Zhao, Yang, 2016. "Optimal design and application of a compound cold storage system combining seasonal ice storage and chilled water storage," Applied Energy, Elsevier, vol. 171(C), pages 1-11.
    12. 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.
    13. 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.
    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. Li, Ruonan & Mhaskar, Prashant & Mahalec, Vladimir, 2021. "Integration of energy systems for buildings and light industrial plants," Energy, Elsevier, vol. 233(C).
    2. Jing, Rui & Wang, Meng & Liang, Hao & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2018. "Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints," Applied Energy, Elsevier, vol. 231(C), pages 534-548.
    3. 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.
    4. 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.
    5. 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).
    6. Junqi Wang & Rundong Liu & Linfeng Zhang & Hussain Syed ASAD & Erlin Meng, 2019. "Triggering Optimal Control of Air Conditioning Systems by Event-Driven Mechanism: Comparing Direct and Indirect Approaches," Energies, MDPI, vol. 12(20), pages 1-20, October.
    7. Yizhe Xu & Chengchu Yan & Hao Qian & Liang Sun & Gang Wang & Yanlong Jiang, 2021. "A Novel Optimization Method for Conventional Primary and Secondary School Classrooms in Southern China Considering Energy Demand, Thermal Comfort and Daylighting," Sustainability, MDPI, vol. 13(23), pages 1-19, November.
    8. Huang, Rui & Tian, Lixin, 2021. "CO2 emissions inequality through the lens of developing countries," Applied Energy, Elsevier, vol. 281(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. 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.
    3. 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.
    4. 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.
    5. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    6. Gang, Wenjie & Augenbroe, Godfried & Wang, Shengwei & Fan, Cheng & Xiao, Fu, 2016. "An uncertainty-based design optimization method for district cooling systems," Energy, Elsevier, vol. 102(C), pages 516-527.
    7. An, Jingjing & Yan, Da & Hong, Tianzhen & Sun, Kaiyu, 2017. "A novel stochastic modeling method to simulate cooling loads in residential districts," Applied Energy, Elsevier, vol. 206(C), pages 134-149.
    8. Happle, Gabriel & Fonseca, Jimeno A. & Schlueter, Arno, 2020. "Impacts of diversity in commercial building occupancy profiles on district energy demand and supply," Applied Energy, Elsevier, vol. 277(C).
    9. 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).
    10. Deng, Na & Cai, Rongchang & Gao, Yuan & Zhou, Zhihua & He, Guansong & Liu, Dongyi & Zhang, Awen, 2017. "A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin," Energy, Elsevier, vol. 141(C), pages 1750-1763.
    11. 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.
    12. 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).
    13. 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.
    14. 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.
    15. 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.
    16. 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).
    17. Best, Robert E. & Flager, Forest & Lepech, Michael D., 2015. "Modeling and optimization of building mix and energy supply technology for urban districts," Applied Energy, Elsevier, vol. 159(C), pages 161-177.
    18. 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.
    19. 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).
    20. Barth, Florian & Schüppler, Simon & Menberg, Kathrin & Blum, Philipp, 2023. "Estimating cooling capacities from aerial images using convolutional neural networks," Applied Energy, Elsevier, vol. 349(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:205:y:2017:i:c:p:635-643. 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.