Agent-Based Modelling of Policy Interventions on District Heating Adoption

Authors

DOI:

https://doi.org/10.52825/isec.v1i.1161

Keywords:

Agent-Based Modelling, Policy Analysis, District Heating Adoption

Abstract

This study employs an agent-based model to examine the adoption of District Heating Networks (DHNs) in heat zoning areas, focusing on the impact of three policy interventions, subsidy, tax and mandating connections. Analysing a case in South Yorkshire, UK, the research highlights a notable synergy in policies, with a combined £25.5 million from subsidies and tax incentives leading to a 28% (£33 million) reduction in infrastructure costs. The policies accelerated the DHN connection rate, achieving full coverage by 2028, two years ahead of the baseline scenario. Investment costs per household were significantly reduced from £2000 to £1460, aligning with governmental cost projections. The study acknowledges optimistic connection rates and suggests future work to include realistic project timelines and incorporate social and behavioural factors in DHN adoption. The findings show the effectiveness of integrated policy frameworks in promoting DHNs.

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References

Committee on Climate Change, “The Sixth Carbon Budget,” 2020. [Online] Available: www.theccc.org.uk/publications.

Frontier Economics, “Agent based modelling of a heat market,” 2021.

D. Gadenne, B. Sharma, D. Kerr, and T. Smith, “The influence of consumers’ environmental beliefs and attitudes on energy saving behaviours,” Energy Policy, vol. 39, no. 12, pp. 7684–7694, Dec. 2011, doi: https://doi.org/10.1016/j.enpol.2011.09.002.

S. Hall, “World Economic Forum,” 2022.

International Energy Association, “World Energy Investment,” Paris, France, 2022.

Energy Saving Trust, “What is District Heating?” 2018. [Online] Available: https://energysavingtrust.org.uk/what-district-heating/.

J. Busch, C. S. E. Bale, C. Knoeri, and K. Roelich, “Emergence of District-Heating Networks; Barriers and Enablers in the Development Process,” 2014.

M. Dowson, “Connecting Existing Buildings to District Heating Networks,” 2016.

P. Vuthi, I. Peters, and J. Sudeikat, “Agent-based modeling (ABM) for urban neighborhood energy systems: literature review and proposal for an all integrative ABM approach,” Energy Informatics, vol. 5, 2022.

L. M. H. Hall and A. R. Buckley, “A review of energy systems models in the UK: Prevalent usage and categorisation,” Appl Energy, vol. 169, pp. 607–628, 2016, doi: https://doi.org/10.1016/j.apenergy.2016.02.026.

L. X. W. Hesselink and E. J. L. Chappin, “Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies,” Renewable and Sustainable Energy Reviews, vol. 99, pp. 29–41, 2019, doi: https://doi.org/10.1016/j.rser.2018.09.023.

J. Webb, “Improvising innovation in UK urban district heating: The convergence of social and environmental agendas in Aberdeen,” Energy Policy, vol. 78, pp. 265–272, 2015, doi: https://doi.org/10.1016/j.enpol.2014.12.003.

B. Talebi, P. A. Mirzaei, A. Bastani, and F. Haghighat, “A Review of District Heating Systems: Modeling and Optimization,” Frontiers in Built Environment, vol. 2, Oct. 2016, doi: https://doi.org/10.3389/fbuil.2016.00022.

J. Busch, K. Roelich, C. S. E. Bale, and C. Knoeri, “Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks,” Energy Policy, vol. 98, pp. 66–75, Oct. 2016, doi: https://doi.org/10.1016/j.enpol.2016.08.028.

M. Pagani, P. Maire, W. Korosec, N. Chokani, and R. S. Abhari, “District heat network extension to decarbonise building stock: A bottom-up agent-based approach,” Applied Energy, vol. 269, May 2020, doi: https://doi.org/10.1016/j.apenergy.2020.115021.

F. Wernstedt and P. Davidsson, “An Agent-Based Approach to Monitoring and Control of District Heating Systems,” in Agent Technologies, Infrastructures, Tools, and Applications for E-Services, Berlin, Heidelberg, 2002, pp. 144–157.

G.-del-Carmen Nava-Guerrero, H. H. Hansen, G. Korevaar, and Z. Lukszo, “The effect of group decisions in heat transitions: An agent-based approach,” Energy Policy, vol. 152, Apr. 2021, doi: https://doi.org/10.1016/j.enpol.2021.112149.

Department for Business, Energy & Industrial Strategy, "Heat Network Zoning," UK Government, [Online]. Available: https://www.gov.uk/government/collections/heat-network-zoning. [Accessed 07.01.2024].

T. A. Company, “No Title.” 2019, [Online]. Available: https://www.anylogic.com.

Office for National Statistics, "Census 2021 Tables and Supporting Information," UK Government, [Online]. Available: https://www.nomisweb.co.uk/sources/census_2021_ts. [Accessed 05.01.2024].

Office of Gas and Electricity Markets (Ofgem), "Ofgem Consumer Survey 2020 - Decarbonisation Insights," UK Government, [Online]. Available: https://www.ofgem.gov.uk/publications/ofgem-consumer-survey-2020-decarbonisation-insights. [Accessed 08.01.2024].

Department for Business, Energy & Industrial Strategy, "Heat Networks," UK Government, [Online]. Available: https://assets.publishing.service.gov.uk/media/5a802b44e5274a2e8ab4e95d/heat_networks.pdf. [05.01.2024].

Office for National Statistics. "Gross Domestic Product (GDP)." [Online]. Available: https://www.ons.gov.uk/economy/grossdomesticproductgdp. [Accessed: 10.01.2024].

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Published

2024-04-26

How to Cite

Cowley, T., Hutty, T., & Brown, S. (2024). Agent-Based Modelling of Policy Interventions on District Heating Adoption. International Sustainable Energy Conference - Proceedings, 1. https://doi.org/10.52825/isec.v1i.1161

Conference Proceedings Volume

Section

Policies for Phase-Out Fossil Fuels and Carbon Management