IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v140y2015icp33-43.html
   My bibliography  Save this article

Performance assessment of district cooling systems for a new development district at planning stage

Author

Listed:
  • Gang, Wenjie
  • Wang, Shengwei
  • Gao, Diance
  • Xiao, Fu

Abstract

A district cooling system supplies cooling to a group of buildings in a district. It has been widely used for its high energy and economic performance, especially in Asian and European countries. It is supposed that a district cooling system can achieve good performance when used in the subtropical area like Hong Kong, where the cooling is required throughout the year and the building density is very high. This study aims to quantitatively assess the performance of the district cooling system in a new development area in Hong Kong. By modeling the buildings and cooling systems of the new district based on the current plan, the performance of district cooling system is compared with the conventional cooling system, which refers to individual in-building cooling systems. Three cases with different chilled water systems are simulated and analyzed. Results show that the district cooling system is more efficient than the individual cooling system, with less energy consumption and operational cost. Energy consumption of main subsystems is compared and the energy saving potential of district cooling system is analyzed. Sensitivity study of district cooling system performance at partial load is conducted and results show that the district cooling system is more efficient under different load conditions during night time.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:140:y:2015:i:c:p:33-43
    DOI: 10.1016/j.apenergy.2014.11.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914011635
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2014.11.014?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. 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.
    2. Rezaie, Behnaz & Reddy, Bale V. & Rosen, Marc A., 2014. "An enviro-economic function for assessing energy resources for district energy systems," Energy, Elsevier, vol. 70(C), pages 159-164.
    3. Shu, Haiwen & Duanmu, Lin & Zhang, Chaohui & Zhu, Yingxin, 2010. "Study on the decision-making of district cooling and heating systems by means of value engineering," Renewable Energy, Elsevier, vol. 35(9), pages 1929-1939.
    4. 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.
    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.
    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. Zhu, Xiaochen & Fuli, Wang, 2023. "Energy savings bottleneck diagnosis and optimization decision method for industrial auxiliary system based on energy efficiency gap analysis," Energy, Elsevier, vol. 263(PE).
    2. 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.
    3. 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.
    4. Li, Sihui & Gong, Guangcai & Peng, Jinqing, 2019. "Dynamic coupling method between air-source heat pumps and buildings in China’s hot-summer/cold-winter zone," Applied Energy, Elsevier, vol. 254(C).
    5. 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.
    6. 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.
    7. 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.
    8. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    9. 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.
    10. 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.
    11. Ding, Yan & Wang, Qiaochu & Kong, Xiangfei & Yang, Kun, 2019. "Multi-objective optimisation approach for campus energy plant operation based on building heating load scenarios," Applied Energy, Elsevier, vol. 250(C), pages 1600-1617.
    12. Arabkoohsar, A. & Andresen, G.B., 2019. "Design and optimization of a novel system for trigeneration," Energy, Elsevier, vol. 168(C), pages 247-260.
    13. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Coupling optimization of urban spatial structure and neighborhood-scale distributed energy systems," Energy, Elsevier, vol. 144(C), pages 472-481.
    14. Ahn, Jonghoon & Cho, Soolyeon, 2017. "Anti-logic or common sense that can hinder machine’s energy performance: Energy and comfort control models based on artificial intelligence responding to abnormal indoor environments," Applied Energy, Elsevier, vol. 204(C), pages 117-130.
    15. Gang, Wenjie & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "Robust optimal design of building cooling systems considering cooling load uncertainty and equipment reliability," Applied Energy, Elsevier, vol. 159(C), pages 265-275.
    16. 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).
    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. 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. 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.
    20. 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. 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.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    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. 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. 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.
    10. Colmenar-Santos, Antonio & Rosales-Asensio, Enrique & Borge-Diez, David & Collado-Fernández, Eduardo, 2016. "Evaluation of the cost of using power plant reject heat in low-temperature district heating and cooling networks," Applied Energy, Elsevier, vol. 162(C), pages 892-907.
    11. 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.
    12. 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.
    13. Zhong, Wei & Feng, Hongcui & Wang, Xuguang & Wu, Dingfei & Xue, Minghua & Wang, Jian, 2015. "Online hydraulic calculation and operation optimization of industrial steam heating networks considering heat dissipation in pipes," Energy, Elsevier, vol. 87(C), pages 566-577.
    14. Shu, Haiwen & Duanmu, Lin & Zhang, Chaohui & Zhu, Yingxin, 2010. "Study on the decision-making of district cooling and heating systems by means of value engineering," Renewable Energy, Elsevier, vol. 35(9), pages 1929-1939.
    15. 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.
    16. 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).
    17. Compton, M. & Rezaie, B., 2017. "Enviro-exergy sustainability analysis of boiler evolution in district energy system," Energy, Elsevier, vol. 119(C), pages 257-265.
    18. Broadstock, David C. & Wang, Xiangnan, 2024. "District cooling services: A bibliometric review and topic classification of existing research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PB).
    19. Si, Pengfei & Li, Angui & Rong, Xiangyang & Feng, Ya & Yang, Zhengwu & Gao, Qinglong, 2015. "New optimized model for water temperature calculation of river-water source heat pump and its application in simulation of energy consumption," Renewable Energy, Elsevier, vol. 84(C), pages 65-73.
    20. Su, Lingqi & Nie, Ting & On Ho, Chi & Yang, Zheng & Calvez, Philippe & Jain, Rishee K. & Schwegler, Ben, 2022. "Optimizing pipe network design and central plant positioning of district heating and cooling System: A Graph-Based Multi-Objective genetic algorithm approach," Applied Energy, Elsevier, vol. 325(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:140:y:2015:i:c:p:33-43. 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.