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District heat network as a short-term energy storage

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  • Kouhia, Mikko
  • Laukkanen, Timo
  • Holmberg, Henrik
  • Ahtila, Pekka

Abstract

In this article, we show how a revised district heat network control strategy can be employed to utilize the storage capabilities of the network. An optimization problem is formulated, with minimum operating costs as the objective. Allowing the district heat supply temperature to vary freely within given boundaries results in approximately 2% reduction in annual heat provision costs, in comparison to a reference control scheme in a case study. The benefits of added heat storage functionality in the network are greatest when there is a large difference between district heat generation costs from the available heat sources. In general, supply temperature optimization results in increased operational hours of those plants, whose variable costs are the lowest.

Suggested Citation

  • Kouhia, Mikko & Laukkanen, Timo & Holmberg, Henrik & Ahtila, Pekka, 2019. "District heat network as a short-term energy storage," Energy, Elsevier, vol. 177(C), pages 293-303.
    • Handle: RePEc:eee:energy:v:177:y:2019:i:c:p:293-303
    DOI: 10.1016/j.energy.2019.04.082
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    Cited by:

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    3. Gou, Xing & Chen, Qun & He, Ke-Lun, 2022. "Real-time quantification for dynamic heat storage characteristic of district heating system and its application in dispatch of integrated energy system," Energy, Elsevier, vol. 259(C).
    4. Chen, Qun & Meng, Nan & He, Ke-Lun & Ma, Huan & Gou, Xing, 2024. "Multi-time scale operation optimization of integrated power and thermal system considering load disturbance," Energy, Elsevier, vol. 302(C).
    5. Johansen, Katinka & Johra, Hicham, 2022. "A niche technique overlooked in the Danish district heating sector? Exploring socio-technical perspectives of short-term thermal energy storage for building energy flexibility," Energy, Elsevier, vol. 256(C).
    6. Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).
    7. Boussaid, Taha & Rousset, François & Scuturici, Vasile-Marian & Clausse, Marc, 2024. "Enabling fast prediction of district heating networks transients via a physics-guided graph neural network," Applied Energy, Elsevier, vol. 370(C).

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