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Heating and cooling networks: A comprehensive review of modelling approaches to map future directions

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  • Brown, Alastair
  • Foley, Aoife
  • Laverty, David
  • McLoone, Seán
  • Keatley, Patrick

Abstract

Future energy systems rely on integrating renewable energy resources to decarbonise the heating and cooling sectors and contribute to global net zero targets. Traditional approaches to energy modelling are segregated as focus tends to be on individual objectives such as minimising operational cost. Furthermore, they are limited with respect to computational time, level of precision and scalability. Model complexity is greater for district heating and cooling systems when compared to power systems due to the thermal behaviour and fluid dynamic principles which are present. Prevailing research tends to deliver a detailed analysis of specific elements within the network, but an approach for visualising the whole system is still missing. This study aims to evaluate the current tools and techniques used to model heating and cooling networks and then propose a more up to date hybrid approach that utilises recent technical advancements. A detailed literature review outlines existing modelling methods and assesses the capabilities of available software tools. The results are summarised in a Pugh Matrix using relevant criteria to compare and select the most appropriate methods. The review concludes that energy models must evolve to become interdisciplinary and multi-objective to simulate a smart energy system.

Suggested Citation

  • Brown, Alastair & Foley, Aoife & Laverty, David & McLoone, Seán & Keatley, Patrick, 2022. "Heating and cooling networks: A comprehensive review of modelling approaches to map future directions," Energy, Elsevier, vol. 261(PB).
    • Handle: RePEc:eee:energy:v:261:y:2022:i:pb:s0360544222019557
    DOI: 10.1016/j.energy.2022.125060
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    2. Chiatti, Chiara & Fabiani, Claudia & Bondi, Roberto & Zampini, Giulia & Latterini, Loredana & Pisello, Anna Laura, 2023. "Controlled combination of phosphorescent and fluorescent materials to exploit energy-saving potential in the built environment," Energy, Elsevier, vol. 275(C).
    3. Haoran Ju & Yongxue Wang & Yiwu Feng & Lijun Zheng, 2024. "Numerical Study on Peak Shaving Performance of Combined Heat and Power Unit Assisted by Heating Storage in Long-Distance Pipelines Scheduled by Particle Swarm Optimization Method," Energies, MDPI, vol. 17(2), pages 1-18, January.
    4. Mitterrutzner, Benjamin & Callegher, Claudio Zandonella & Fraboni, Riccardo & Wilczynski, Eric & Pezzutto, Simon, 2023. "Review of heating and cooling technologies for buildings: A techno-economic case study of eleven European countries," Energy, Elsevier, vol. 284(C).
    5. Belliardi, Marco & Caputo, Paola & Ferla, Giulio & Cereghetti, Nerio & Antonioli Mantegazzini, Barbara, 2023. "An innovative application of 5GDHC: A techno-economic assessment of shallow geothermal systems potential in different European climates," Energy, Elsevier, vol. 280(C).
    6. Zhang, Ran & Xu, Xiaodong & Liu, Ke & Kong, Lingyu & Wang, Wei & Wortmann, Thomas, 2024. "Airflow modelling for building design: A designers' review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    7. Xie, Zichan & Wang, Haichao & Hua, Pengmin & Lahdelma, Risto, 2023. "Discrete event simulation for dynamic thermal modelling of district heating pipe," Energy, Elsevier, vol. 285(C).
    8. Salenbien, R. & Wack, Y. & Baelmans, M. & Blommaert, M., 2023. "Geographically informed automated non-linear topology optimization of district heating networks," Energy, Elsevier, vol. 283(C).

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