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District heat network extension to decarbonise building stock: A bottom-up agent-based approach

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  • Pagani, M.
  • Maire, P.
  • Korosec, W.
  • Chokani, N.
  • Abhari, R.S.

Abstract

A novel framework, that is comprised of large-scale, agent-based models of residential buildings and the occupants of the buildings, and a bottom-up heat demand model, is developed to assess scenarios related to the extension of a city’s district heat network. The agent-based models account for the characteristics of the individual buildings and the behaviours of the individual occupants. The bottom-up heat demand model accounts for the spatial and temporal differences in heat demand of individual buildings. It is shown that by accounting for the behaviour of building occupants the time-resolved dynamics of heat demand are more accurately captured and the quantitative prediction of the heat demand is improved compared to prior approaches. The novel framework is applied to assess the extension of the district heat network of a mid-sized city in Switzerland, whereby the likelihood of a building to connecting to the extended network can be considered. By accounting both for the profitability of the predicted heat demand and for the likelihood of a building being connected to the extended network, the internal rate of return of the infrastructure can be increased by 25%, compared to an extension of the network where these aspects are not considered. Overall, this novel framework provides insights and cost-effective solutions for policy makers and energy multi-utilities regarding the decarbonisation of building stock.

Suggested Citation

  • Pagani, M. & Maire, P. & Korosec, W. & Chokani, N. & Abhari, R.S., 2020. "District heat network extension to decarbonise building stock: A bottom-up agent-based approach," Applied Energy, Elsevier, vol. 272(C).
    • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920306899
    DOI: 10.1016/j.apenergy.2020.115177
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    References listed on IDEAS

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    1. Persson, Urban & Werner, Sven, 2012. "District heating in sequential energy supply," Applied Energy, Elsevier, vol. 95(C), pages 123-131.
    2. Eser, P. & Chokani, N. & Abhari, R., 2019. "Impact of Nord Stream 2 and LNG on gas trade and security of supply in the European gas network of 2030," Applied Energy, Elsevier, vol. 238(C), pages 816-830.
    3. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    4. Eser, Patrick & Singh, Antriksh & Chokani, Ndaona & Abhari, Reza S., 2016. "Effect of increased renewables generation on operation of thermal power plants," Applied Energy, Elsevier, vol. 164(C), pages 723-732.
    5. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    6. Pagani, M. & Korosec, W. & Chokani, N. & Abhari, R.S., 2019. "User behaviour and electric vehicle charging infrastructure: An agent-based model assessment," Applied Energy, Elsevier, vol. 254(C).
    7. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    8. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
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    Cited by:

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    3. Nava-Guerrero, Graciela-del-Carmen & Hansen, Helle Hvid & Korevaar, Gijsbert & Lukszo, Zofia, 2022. "An agent-based exploration of the effect of multi-criteria decisions on complex socio-technical heat transitions," Applied Energy, Elsevier, vol. 306(PB).

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