IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks

Listed author(s):
  • Busch, Jonathan
  • Roelich, Katy
  • Bale, Catherine S.E.
  • Knoeri, Christof
Registered author(s):

    The potential contribution of local energy infrastructure – such as heat networks – to the transition to a low carbon economy is increasingly recognised in international, national and municipal policy. Creating the policy environment to foster the scaling up of local energy infrastructure is, however, still challenging; despite national policy action and local authority interest the growth of heat networks in UK cities remains slow. Techno-economic energy system models commonly used to inform policy are not designed to address institutional and governance barriers. We present an agent-based model of heat network development in UK cities in which policy interventions aimed at the institutional and governance barriers faced by diverse actors can be explored. Three types of project instigators are included – municipal, commercial and community – which have distinct decision heuristics and capabilities and follow a multi-stage development process. Scenarios of policy interventions developed in a companion modelling approach indicate that the effect of interventions differs between actors depending on their capabilities. Successful interventions account for the specific motivations and capabilities of different actors, provide a portfolio of support along the development process and recognise the important strategic role of local authorities in supporting low carbon energy infrastructure.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421516305560
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 100 (2017)
    Issue (Month): C ()
    Pages: 170-180

    as
    in new window

    Handle: RePEc:eee:enepol:v:100:y:2017:i:c:p:170-180
    DOI: 10.1016/j.enpol.2016.10.011
    Contact details of provider: Web page: http://www.elsevier.com/locate/enpol

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as
    in new window


    1. Li, Francis G.N. & Trutnevyte, Evelina & Strachan, Neil, 2015. "A review of socio-technical energy transition (STET) models," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 290-305.
    2. Bale, Catherine S.E. & Foxon, Timothy J. & Hannon, Matthew J. & Gale, William F., 2012. "Strategic energy planning within local authorities in the UK: A study of the city of Leeds," Energy Policy, Elsevier, vol. 48(C), pages 242-251.
    3. Christof Knoeri & Igor Nikolic & Hans-Joerg Althaus & Claudia R. Binder, 2014. "Enhancing Recycling of Construction Materials: An Agent Based Model with Empirically Based Decision Parameters," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(3), pages 1-10.
    4. Noam Bergman & Alex Haxeltine & Lorraine Whitmarsh & Jonathan Köhler & Michel Schilperoord & Jan Rotmans, 2008. "Modelling Socio-Technical Transition Patterns and Pathways," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-7.
    5. Yvonne Rydin & Catalina Turcu & Simon Guy & Patrick Austin, 2013. "Mapping the coevolution of urban energy systems: pathways of change," Environment and Planning A, Pion Ltd, London, vol. 45(3), pages 634-649, March.
    6. Robinson, Scott A. & Rai, Varun, 2015. "Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach," Applied Energy, Elsevier, vol. 151(C), pages 273-284.
    7. Christophe Le Page & Kadiri Serge Bobo & Towa Olivier William Kamgaing & Bobo Fernanda Ngahane & Matthias Waltert, 2015. "Interactive Simulations with a Stylized Scale Model to Codesign with Villagers an Agent-Based Model of Bushmeat Hunting in the Periphery of Korup National Park (Cameroon)," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-8.
    8. Wolf, Ingo & Schröder, Tobias & Neumann, Jochen & de Haan, Gerhard, 2015. "Changing minds about electric cars: An empirically grounded agent-based modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 269-285.
    9. Alanne, Kari & Saari, Arto, 2006. "Distributed energy generation and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(6), pages 539-558, December.
    10. Mitchell, Catherine & Woodman, Bridget, 2010. "Towards trust in regulation--moving to a public value regulation," Energy Policy, Elsevier, vol. 38(6), pages 2644-2651, June.
    11. Foxon, Timothy J., 2011. "A coevolutionary framework for analysing a transition to a sustainable low carbon economy," Ecological Economics, Elsevier, vol. 70(12), pages 2258-2267.
    12. Faber, Albert & Valente, Marco & Janssen, Peter, 2010. "Exploring domestic micro-cogeneration in the Netherlands: An agent-based demand model for technology diffusion," Energy Policy, Elsevier, vol. 38(6), pages 2763-2775, June.
    13. Eppstein, Margaret J. & Grover, David K. & Marshall, Jeffrey S. & Rizzo, Donna M., 2011. "An agent-based model to study market penetration of plug-in hybrid electric vehicles," Energy Policy, Elsevier, vol. 39(6), pages 3789-3802, June.
    14. Hannon, Matthew J. & Foxon, Timothy J. & Gale, William F., 2013. "The co-evolutionary relationship between Energy Service Companies and the UK energy system: Implications for a low-carbon transition," Energy Policy, Elsevier, vol. 61(C), pages 1031-1045.
    15. Maya Sopha, Bertha & Klöckner, Christian A. & Hertwich, Edgar G., 2011. "Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation," Energy Policy, Elsevier, vol. 39(5), pages 2722-2729, May.
    16. O'Brien, Geoff & Hope, Alex, 2010. "Localism and energy: Negotiating approaches to embedding resilience in energy systems," Energy Policy, Elsevier, vol. 38(12), pages 7550-7558, December.
    17. Hecher, Maria & Vilsmaier, Ulli & Akhavan, Roya & Binder, Claudia R., 2016. "An integrative analysis of energy transitions in energy regions: A case study of ökoEnergieland in Austria," Ecological Economics, Elsevier, vol. 121(C), pages 40-53.
    18. Roger Fouquet & Peter J. G. Pearson, 1998. "A Thousand Years of Energy Use in the United Kingdom," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-41.
    19. Andrea L. Hicks & Thomas L. Theis & Moira L. Zellner, 2015. "Emergent Effects of Residential Lighting Choices: Prospects for Energy Savings," Journal of Industrial Ecology, Yale University, vol. 19(2), pages 285-295, 04.
    20. Eriksson, Ola & Finnveden, Goran & Ekvall, Tomas & Bjorklund, Anna, 2007. "Life cycle assessment of fuels for district heating: A comparison of waste incineration, biomass- and natural gas combustion," Energy Policy, Elsevier, vol. 35(2), pages 1346-1362, February.
    21. Paul Guyot & Shinichi Honiden, 2006. "Agent-Based Participatory Simulations: Merging Multi-Agent Systems and Role-Playing Games," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(4), pages 1-8.
    22. Henry Chesbrough & Richard S. Rosenbloom, 2002. "The role of the business model in capturing value from innovation: evidence from Xerox Corporation's technology spin-off companies," Industrial and Corporate Change, Oxford University Press, vol. 11(3), pages 529-555, June.
    23. Seyfang, Gill & Park, Jung Jin & Smith, Adrian, 2013. "A thousand flowers blooming? An examination of community energy in the UK," Energy Policy, Elsevier, vol. 61(C), pages 977-989.
    24. Christof Knoeri & Claudia R. Binder & Hans-Joerg Althaus, 2011. "An Agent Operationalization Approach for Context Specific Agent-Based Modeling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(2), pages 1-4.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:100:y:2017:i:c:p:170-180. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.