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Grey-Box Modelling of District Heating Networks Using Modified LPV Models

Author

Listed:
  • Olamilekan E. Tijani

    (LaTEP, Universite de Pau et des Pays de l’Adour, 64075 Pau, France)

  • Sylvain Serra

    (LaTEP, Universite de Pau et des Pays de l’Adour, 64075 Pau, France)

  • Patrick Lanusse

    (Universite de Bordeaux, CNRS, Bordeaux INP, IMS, UMR 5218, 33400 Talence, France)

  • Rachid Malti

    (Universite de Bordeaux, CNRS, Bordeaux INP, IMS, UMR 5218, 33400 Talence, France)

  • Hugo Viot

    (Nobatek, 67 rue de Mirambeau, 64600 Anglet, France)

  • Jean-Michel Reneaume

    (LaTEP, Universite de Pau et des Pays de l’Adour, 64075 Pau, France)

Abstract

The International Energy Agency (IEA) 2023 report highlights that global energy losses have persisted over the years, with 32% of the energy supply lost in 2022 alone. To mitigate this, this research adopts optimisation to enhance the efficiency of district heating networks (DHNs), a key global energy supply technology. Given the dynamic nature of DHNs and the challenges in predicting disturbances, a dynamic real-time optimisation (DRTO) approach is proposed. However, this research does not implement DRTO; instead, it develops a fast grey-box linear parameter varying (LPV) model for future integration into the DRTO algorithm. A high-fidelity physical model replicating theoretical time delays in pipes serves as a reference for model validation. For a single pipe, the grey-box model achieved a 91.5% fit with an R 2 value of 0.993 and operated 5 times faster than the reference model. At the DHN scale, it captured 98.64% of the reference model’s dynamics, corresponding to an R 2 value of 0.9997, while operating 52 times faster. Low-fidelity physical models (LFPMs) were also developed and validated, proving to be more precise and faster than the grey-box models. This research recommends performing dynamic optimisation with both models to determine which better identifies local minima.

Suggested Citation

  • Olamilekan E. Tijani & Sylvain Serra & Patrick Lanusse & Rachid Malti & Hugo Viot & Jean-Michel Reneaume, 2025. "Grey-Box Modelling of District Heating Networks Using Modified LPV Models," Energies, MDPI, vol. 18(7), pages 1-32, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1626-:d:1619328
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    References listed on IDEAS

    as
    1. Wang, Jinda & Kong, Fansi & Pan, Baoqiang & Zheng, Jinfu & Xue, Puning & Sun, Chunhua & Qi, Chengying, 2024. "Low-order gray-box modeling of heating buildings and the progressive dimension reduction identification of uncertain model parameters," Energy, Elsevier, vol. 294(C).
    2. Duquette, Jean & Rowe, Andrew & Wild, Peter, 2016. "Thermal performance of a steady state physical pipe model for simulating district heating grids with variable flow," Applied Energy, Elsevier, vol. 178(C), pages 383-393.
    3. Li, Yanfei & O'Neill, Zheng & Zhang, Liang & Chen, Jianli & Im, Piljae & DeGraw, Jason, 2021. "Grey-box modeling and application for building energy simulations - A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
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