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Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters

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  • Lumbreras, Mikel
  • Garay-Martinez, Roberto
  • Arregi, Beñat
  • Martin-Escudero, Koldobika
  • Diarce, Gonzalo
  • Raud, Margus
  • Hagu, Indrek

Abstract

An accurate characterization and prediction of heat loads in buildings connected to a District Heating (DH) network is crucial for the effective operation of these systems. The high variability of the heat production process of DH networks with low supply temperatures and derived from the incorporation of different heat sources increases the need for heat demand prediction models. This paper presents a novel data-driven model for the characterization and prediction of heating demand in buildings connected to a DH network.

Suggested Citation

  • Lumbreras, Mikel & Garay-Martinez, Roberto & Arregi, Beñat & Martin-Escudero, Koldobika & Diarce, Gonzalo & Raud, Margus & Hagu, Indrek, 2022. "Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters," Energy, Elsevier, vol. 239(PD).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pd:s0360544221025664
    DOI: 10.1016/j.energy.2021.122318
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    References listed on IDEAS

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    5. Arash Mohammadi Fallah & Ehsan Ghafourian & Ladan Shahzamani Sichani & Hossein Ghafourian & Behdad Arandian & Moncef L. Nehdi, 2023. "Novel Neural Network Optimized by Electrostatic Discharge Algorithm for Modification of Buildings Energy Performance," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    6. Yousaf Murtaza Rind & Muhammad Haseeb Raza & Muhammad Zubair & Muhammad Qasim Mehmood & Yehia Massoud, 2023. "Smart Energy Meters for Smart Grids, an Internet of Things Perspective," Energies, MDPI, vol. 16(4), pages 1-35, February.
    7. Košnjek, Edvard & Sučić, Boris & Kostić, Dušan & Smolej, Tom, 2024. "An energy community as a platform for local sector coupling: From complex modelling to simulation and implementation," Energy, Elsevier, vol. 286(C).
    8. Wang, Zhijin & Liu, Xiufeng & Huang, Yaohui & Zhang, Peisong & Fu, Yonggang, 2023. "A multivariate time series graph neural network for district heat load forecasting," Energy, Elsevier, vol. 278(PA).
    9. Liu, Zhikai & Zhang, Huan & Wang, Yaran & Song, Zixu & You, Shijun & Jiang, Yan & Wu, Zhangxiang, 2022. "A thermal-hydraulic coupled simulation approach for the temperature and flow rate control strategy evaluation of the multi-room radiator heating system," Energy, Elsevier, vol. 246(C).
    10. Hua, Pengmin & Wang, Haichao & Xie, Zichan & Lahdelma, Risto, 2024. "District heating load patterns and short-term forecasting for buildings and city level," Energy, Elsevier, vol. 289(C).
    11. Wang, Yongjie & Zhan, Changhong & Li, Guanghao & Ren, Shaochen, 2024. "Comparison of algorithms for heat load prediction of buildings," Energy, Elsevier, vol. 297(C).

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