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Thermal load prediction in district heating systems

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  • Guelpa, Elisa
  • Marincioni, Ludovica
  • Capone, Martina
  • Deputato, Stefania
  • Verda, Vittorio

Abstract

Optimal operation of district heating (DH) systems usually relies on the forecast of thermal demand profiles of the connected buildings. Depending on the purpose of the analysis, thermal request can be required at various levels, from building level to thermal plant level. In the case of demand response for example, thermal request is necessary at a building level to evaluate its applicability and at a plant level to determine the effects. Thermal request profiles are quite different, depending on the observation point. Total requests are not just the summation of the downstream requests, mainly because of the thermal transients. The heat losses also contributes to modify the curves, although generally in a smaller way. In this work, a multi-level thermal request prediction is proposed. This approach has the aim of evaluating the thermal request in the various sections of DH network with reduced computational resources. This includes a compact model for the prediction of building demand and a network model in order to compose together the requests at the various levels. The application to a portion of the Turin district heating network is proposed. This shows that the network dynamics significantly affects the evolution, especially at peak load.

Suggested Citation

  • Guelpa, Elisa & Marincioni, Ludovica & Capone, Martina & Deputato, Stefania & Verda, Vittorio, 2019. "Thermal load prediction in district heating systems," Energy, Elsevier, vol. 176(C), pages 693-703.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:693-703
    DOI: 10.1016/j.energy.2019.04.021
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    1. Paolo Sdringola & Mattia Ricci & Maria Alessandra Ancona & Federico Gianaroli & Cristina Capodaglio & Francesco Melino, 2023. "Modelling a Prototype of Bidirectional Substation for District Heating with Thermal Prosumers," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    2. Guelpa, Elisa & Verda, Vittorio, 2021. "Demand response and other demand side management techniques for district heating: A review," Energy, Elsevier, vol. 219(C).
    3. 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.
    4. Liu, Guoqiang & Zhou, Xuan & Yan, Junwei & Yan, Gang, 2021. "A temperature and time-sharing dynamic control approach for space heating of buildings in district heating system," Energy, Elsevier, vol. 221(C).
    5. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    6. Knudsen, Brage Rugstad & Rohde, Daniel & Kauko, Hanne, 2021. "Thermal energy storage sizing for industrial waste-heat utilization in district heating: A model predictive control approach," Energy, Elsevier, vol. 234(C).
    7. Guelpa, Elisa & Marincioni, Ludovica, 2019. "Demand side management in district heating systems by innovative control," Energy, Elsevier, vol. 188(C).
    8. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. Meibodi, Saleh S. & Loveridge, Fleur, 2022. "The future role of energy geostructures in fifth generation district heating and cooling networks," Energy, Elsevier, vol. 240(C).
    10. Salman Siddiqui & Mark Barrett & John Macadam, 2021. "A High Resolution Spatiotemporal Urban Heat Load Model for GB," Energies, MDPI, vol. 14(14), pages 1-28, July.
    11. Zhang, Qiang & Tian, Zhe & Ma, Zhijun & Li, Genyan & Lu, Yakai & Niu, Jide, 2020. "Development of the heating load prediction model for the residential building of district heating based on model calibration," Energy, Elsevier, vol. 205(C).
    12. Pipiciello, Mauro & Caldera, Matteo & Cozzini, Marco & Ancona, Maria A. & Melino, Francesco & Di Pietra, Biagio, 2021. "Experimental characterization of a prototype of bidirectional substation for district heating with thermal prosumers," Energy, Elsevier, vol. 223(C).
    13. Ma, Zheng & Knotzer, Armin & Billanes, Joy Dalmacio & Jørgensen, Bo Nørregaard, 2020. "A literature review of energy flexibility in district heating with a survey of the stakeholders’ participation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    14. Triebs, Merlin Sebastian & Tsatsaronis, George, 2022. "From heat demand to heat supply: How to obtain more accurate feed-in time series for district heating systems," Applied Energy, Elsevier, vol. 311(C).
    15. Kaiwen Li & Yuanming Song & Rui Wang, 2022. "Multi-Objective Optimal Sizing of HRES under Multiple Scenarios with Undetermined Probability," Mathematics, MDPI, vol. 10(9), pages 1-19, May.
    16. Pavel Rušeljuk & Kertu Lepiksaar & Andres Siirde & Anna Volkova, 2021. "Economic Dispatch of CHP Units through District Heating Network’s Demand-Side Management," Energies, MDPI, vol. 14(15), pages 1-20, July.

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