IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v84y2015icp65-73.html
   My bibliography  Save this article

New optimized model for water temperature calculation of river-water source heat pump and its application in simulation of energy consumption

Author

Listed:
  • Si, Pengfei
  • Li, Angui
  • Rong, Xiangyang
  • Feng, Ya
  • Yang, Zhengwu
  • Gao, Qinglong

Abstract

The energy consumption calculation plays an important role in the analysis of project economic and social benefits. In order to calculate energy consumption accurately, this research presents a water temperature of condenser inlet calculation model of river-water source heat pump unit. The feasibility and calculation error of the model had been analyzed. Additionally, the new water temperature calculation model had been validated via an engineering case. The results showed that the hourly water temperature in 24 h could be replaced by daily average water temperature due to little change of the daily water temperature change. In this case, the calculation error could be less than 5%. It is found that despite water temperature has many influenced factors, there is a remarkable relationship between the daily average water temperature and daily average outdoor dry bulb temperature by data analysis (R2 ≈ 0.9). The influence of river sampling location on water temperature calculation of condenser inlet could be ignored due to slight temperature changes (within 0.15 °C). The method proposed in this paper met the engineering accuracy and provided a very effective method for the engineering calculation of energy consumption of water chilling unit.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:84:y:2015:i:c:p:65-73
    DOI: 10.1016/j.renene.2015.06.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148115300380
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2015.06.015?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. & 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.
    2. 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.
    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. Zheng, Wandong & Yin, Hao & Li, Bojia & Zhang, Huan & Jurasz, Jakub & Zhong, Lei, 2022. "Heating performance and spatial analysis of seawater-source heat pump with staggered tube-bundle heat exchanger," Applied Energy, Elsevier, vol. 305(C).
    2. Dong, Yixiu & Yan, Hongzhi & Wang, Ruzhu, 2024. "Significant thermal upgrade via cascade high temperature heat pump with low GWP working fluids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    3. Zhou, Zhihua & Wu, Shengwei & Du, Tao & Chen, Guanyi & Zhang, Zhiming & Zuo, Jian & He, Qing, 2016. "The energy-saving effects of ground-coupled heat pump system integrated with borehole free cooling: A study in China," Applied Energy, Elsevier, vol. 182(C), pages 9-19.
    4. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    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. 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).
    8. 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.
    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. 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.
    11. 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.
    12. Averfalk, Helge & Ingvarsson, Paul & Persson, Urban & Gong, Mei & Werner, Sven, 2017. "Large heat pumps in Swedish district heating systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1275-1284.
    13. Yu, Jie & Zhang, Huan & You, Shijun, 2012. "Heat transfer analysis and experimental verification of casted heat exchanger in non-icing and icing conditions in winter," Renewable Energy, Elsevier, vol. 41(C), pages 39-43.
    14. 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.
    15. Pan, Wei & Qin, Hao & Zhao, Yisong, 2017. "Challenges for energy and carbon modeling of high-rise buildings: The case of public housing in Hong Kong," Resources, Conservation & Recycling, Elsevier, vol. 123(C), pages 208-218.
    16. 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.
    17. Lund, Rasmus & Persson, Urban, 2016. "Mapping of potential heat sources for heat pumps for district heating in Denmark," Energy, Elsevier, vol. 110(C), pages 129-138.
    18. Eskafi, Majid & Ásmundsson, Ragnar & Jónsson, Steingrímur, 2019. "Feasibility of seawater heat extraction from sub-Arctic coastal water; a case study of Onundarfjordur, northwest Iceland," Renewable Energy, Elsevier, vol. 134(C), pages 95-102.
    19. 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.
    20. Čož, T. Duh & Kitanovski, A. & Poredoš, A., 2017. "Exergoeconomic optimization of a district cooling network," Energy, Elsevier, vol. 135(C), pages 342-351.

    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:renene:v:84:y:2015:i:c:p:65-73. 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/renewable-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.