IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v285y2023ics0360544223029079.html
   My bibliography  Save this article

A new data mining strategy for performance evaluation of a shared energy recovery system integrated with data centres and district heating networks

Author

Listed:
  • Du, Han
  • Zhou, Xinlei
  • Nord, Natasa
  • Carden, Yale
  • Ma, Zhenjun

Abstract

This study presents a new data mining strategy to discover the performance and operational patterns of a shared energy recovery (SER) system with a data centre and a district heating network. Multidimensional clustering incorporated with a composite performance metric was first used to evaluate the typical performance of the system and reveal the interactions among different performance indicators. Decision tree analysis was then used to identify distinct system performances under different external conditions. Temporal clustering analysis was lastly used to identify the impact of recovered waste heat on the variations in heat supply from the district heating substation. The strategy was evaluated through a case study SER system at a university campus located in Norway. It was found that the most frequent performance accounted for 34 % of the total operational period with the instantaneous waste heat recovery rate of 572.9 kW, the temperature of waste heat of 57.2 °C, and the coefficient of performance of the heat pumps of 2.0. The outdoor air temperature and supply water temperature from the main district heating substation to the campus buildings showed a significant impact on the SER system performance. Moreover, the results showed that the SER system can help reduce the energy use of the district heating networks while increasing the fluctuations of heat supply from the main district heating substation.

Suggested Citation

  • Du, Han & Zhou, Xinlei & Nord, Natasa & Carden, Yale & Ma, Zhenjun, 2023. "A new data mining strategy for performance evaluation of a shared energy recovery system integrated with data centres and district heating networks," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223029079
    DOI: 10.1016/j.energy.2023.129513
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223029079
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129513?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. Calikus, Ece & Nowaczyk, Sławomir & Sant'Anna, Anita & Gadd, Henrik & Werner, Sven, 2019. "A data-driven approach for discovering heat load patterns in district heating," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    2. Wahlroos, Mikko & Pärssinen, Matti & Rinne, Samuli & Syri, Sanna & Manner, Jukka, 2018. "Future views on waste heat utilization – Case of data centers in Northern Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P2), pages 1749-1764.
    3. Zahoor Ali Khan & Muhammad Adil & Nadeem Javaid & Malik Najmus Saqib & Muhammad Shafiq & Jin-Ghoo Choi, 2020. "Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data," Sustainability, MDPI, vol. 12(19), pages 1-25, September.
    4. Zhang, Shuyang & Zhang, Lun & Zhang, Xiaosong, 2022. "Clustering based on dynamic time warping to extract typical daily patterns from long-term operation data of a ground source heat pump system," Energy, Elsevier, vol. 249(C).
    5. Jeffrey D. Sachs & Guido Schmidt-Traub & Mariana Mazzucato & Dirk Messner & Nebojsa Nakicenovic & Johan Rockström, 2019. "Six Transformations to achieve the Sustainable Development Goals," Nature Sustainability, Nature, vol. 2(9), pages 805-814, September.
    6. Jani, Hardik K. & Kachhwaha, Surendra Singh & Nagababu, Garlapati & Das, Alok, 2022. "Temporal and spatial simultaneity assessment of wind-solar energy resources in India by statistical analysis and machine learning clustering approach," Energy, Elsevier, vol. 248(C).
    7. Wahlroos, Mikko & Pärssinen, Matti & Manner, Jukka & Syri, Sanna, 2017. "Utilizing data center waste heat in district heating – Impacts on energy efficiency and prospects for low-temperature district heating networks," Energy, Elsevier, vol. 140(P1), pages 1228-1238.
    8. Köfinger, M. & Schmidt, R.R. & Basciotti, D. & Terreros, O. & Baldvinsson, I. & Mayrhofer, J. & Moser, S. & Tichler, R. & Pauli, H., 2018. "Simulation based evaluation of large scale waste heat utilization in urban district heating networks: Optimized integration and operation of a seasonal storage," Energy, Elsevier, vol. 159(C), pages 1161-1174.
    9. Ebrahimi, Khosrow & Jones, Gerard F. & Fleischer, Amy S., 2014. "A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 622-638.
    10. Huang, Ke & Yuan, Jianjuan & Zhou, Zhihua & Zheng, Xuejing, 2022. "Analysis and evaluation of heat source data of large-scale heating system based on descriptive data mining techniques," Energy, Elsevier, vol. 251(C).
    11. Zhang, Chaobo & Xue, Xue & Zhao, Yang & Zhang, Xuejun & Li, Tingting, 2019. "An improved association rule mining-based method for revealing operational problems of building heating, ventilation and air conditioning (HVAC) systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Li, Haoran & Hou, Juan & Hong, Tianzhen & Ding, Yuemin & Nord, Natasa, 2021. "Energy, economic, and environmental analysis of integration of thermal energy storage into district heating systems using waste heat from data centres," Energy, Elsevier, vol. 219(C).
    13. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    14. Wirtz, Marco & Kivilip, Lukas & Remmen, Peter & Müller, Dirk, 2020. "5th Generation District Heating: A novel design approach based on mathematical optimization," Applied Energy, Elsevier, vol. 260(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, Haoran & Hou, Juan & Hong, Tianzhen & Ding, Yuemin & Nord, Natasa, 2021. "Energy, economic, and environmental analysis of integration of thermal energy storage into district heating systems using waste heat from data centres," Energy, Elsevier, vol. 219(C).
    2. Huang, Yongping & Deng, Zilong & Chen, Yongping & Zhang, Chengbin, 2023. "Performance investigation of a biomimetic latent heat thermal energy storage device for waste heat recovery in data centers," Applied Energy, Elsevier, vol. 335(C).
    3. Hou, Juan & Li, Haoran & Nord, Natasa & Huang, Gongsheng, 2023. "Model predictive control for a university heat prosumer with data centre waste heat and thermal energy storage," Energy, Elsevier, vol. 267(C).
    4. Yuan, Xiaolei & Liang, Yumin & Hu, Xinyi & Xu, Yizhe & Chen, Yongbao & Kosonen, Risto, 2023. "Waste heat recoveries in data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    5. Jodeiri, A.M. & Goldsworthy, M.J. & Buffa, S. & Cozzini, M., 2022. "Role of sustainable heat sources in transition towards fourth generation district heating – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    6. 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.
    7. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    8. Arnaudo, Monica & Dalgren, Johan & Topel, Monika & Laumert, Björn, 2021. "Waste heat recovery in low temperature networks versus domestic heat pumps - A techno-economic and environmental analysis," Energy, Elsevier, vol. 219(C).
    9. Li, Haoran & Hou, Juan & Tian, Zhiyong & Hong, Tianzhen & Nord, Natasa & Rohde, Daniel, 2022. "Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage," Energy, Elsevier, vol. 239(PB).
    10. Anna Grzegórska & Piotr Rybarczyk & Valdas Lukoševičius & Joanna Sobczak & Andrzej Rogala, 2021. "Smart Asset Management for District Heating Systems in the Baltic Sea Region," Energies, MDPI, vol. 14(2), pages 1-25, January.
    11. Hering, Dominik & Xhonneux, André & Müller, Dirk, 2021. "Design optimization of a heating network with multiple heat pumps using mixed integer quadratically constrained programming," Energy, Elsevier, vol. 226(C).
    12. Li, Haoran & Hou, Juan & Hong, Tianzhen & Nord, Natasa, 2022. "Distinguish between the economic optimal and lowest distribution temperatures for heat-prosumer-based district heating systems with short-term thermal energy storage," Energy, Elsevier, vol. 248(C).
    13. Hiltunen, Pauli & Syri, Sanna, 2021. "Low-temperature waste heat enabling abandoning coal in Espoo district heating system," Energy, Elsevier, vol. 231(C).
    14. Chen, Xiaoyuan & Jiang, Shan & Chen, Yu & Lei, Yi & Zhang, Donghui & Zhang, Mingshun & Gou, Huayu & Shen, Boyang, 2022. "A 10 MW class data center with ultra-dense high-efficiency energy distribution: Design and economic evaluation of superconducting DC busbar networks," Energy, Elsevier, vol. 250(C).
    15. Jerez Monsalves, Juan & Bergaentzlé, Claire & Keles, Dogan, 2023. "Impacts of flexible-cooling and waste-heat recovery from data centres on energy systems: A Danish case study," Energy, Elsevier, vol. 281(C).
    16. Weijian Ding & Behzad Ebrahimi & Byoung-Do Kim & Connie L. Devenport & Amy E. Childress, 2024. "Analysis of Anthropogenic Waste Heat Emission from an Academic Data Center," Energies, MDPI, vol. 17(8), pages 1-20, April.
    17. Li, Weiwei & Qian, Tong & Zhang, Yin & Shen, Yueqing & Wu, Chenghu & Tang, Wenhu, 2023. "Distributionally robust chance-constrained planning for regional integrated electricity–heat systems with data centers considering wind power uncertainty," Applied Energy, Elsevier, vol. 336(C).
    18. Kristina Lygnerud & Sarka Langer, 2022. "Urban Sustainability: Recovering and Utilizing Urban Excess Heat," Energies, MDPI, vol. 15(24), pages 1-11, December.
    19. Paiho, Satu & Saastamoinen, Heidi, 2018. "How to develop district heating in Finland?," Energy Policy, Elsevier, vol. 122(C), pages 668-676.
    20. Abdelsalam, Mohamed Y. & Friedrich, Kelton & Mohamed, Saber & Chebeir, Jorge & Lakhian, Vickram & Sullivan, Brendan & Abdalla, Ahmed & Van Ryn, Jessica & Girard, Jeffrey & Lightstone, Marilyn F. & Buc, 2023. "Integrated community energy and harvesting systems: A climate action strategy for cold climates," Applied Energy, Elsevier, vol. 346(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:285:y:2023:i:c:s0360544223029079. 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.