IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v66y2014icp267-279.html
   My bibliography  Save this article

An analysis of UK policies for domestic energy reduction using an agent based tool

Author

Listed:
  • Lee, Timothy
  • Yao, Runming
  • Coker, Phil

Abstract

This paper introduces a new agent-based model, which incorporates the actions of individual homeowners in a long-term domestic stock model, and details how it was applied in energy policy analysis. The results indicate that current policies are likely to fall significantly short of the 80% target and suggest that current subsidy levels need re-examining. In the model, current subsidy levels appear to offer too much support to some technologies, which in turn leads to the suppression of other technologies that have a greater energy saving potential. The model can be used by policy makers to develop further scenarios to find alternative, more effective, sets of policy measures. The model is currently limited to the owner-occupied stock in England, although it can be expanded, subject to the availability of data.

Suggested Citation

  • Lee, Timothy & Yao, Runming & Coker, Phil, 2014. "An analysis of UK policies for domestic energy reduction using an agent based tool," Energy Policy, Elsevier, vol. 66(C), pages 267-279.
    • Handle: RePEc:eee:enepol:v:66:y:2014:i:c:p:267-279
    DOI: 10.1016/j.enpol.2013.11.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030142151301104X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2013.11.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    2. Tran, Martino, 2012. "Technology-behavioural modelling of energy innovation diffusion in the UK," Applied Energy, Elsevier, vol. 95(C), pages 1-11.
    3. Adamowicz W. & Louviere J. & Williams M., 1994. "Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities," Journal of Environmental Economics and Management, Elsevier, vol. 26(3), pages 271-292, May.
    4. Lee, Timothy & Yao, Runming, 2013. "Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis," Energy Policy, Elsevier, vol. 52(C), pages 363-372.
    5. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Comparing aggregating methods for constructing the composite environmental index: An objective measure," Ecological Economics, Elsevier, vol. 59(3), pages 305-311, September.
    6. Shorrock, LD & Dunster, JE, 1997. "The physically-based model BREHOMES and its use in deriving scenarios for the energy use and carbon dioxide emissions of the UK housing stock," Energy Policy, Elsevier, vol. 25(12), pages 1027-1037, October.
    7. Ruud Kempener, 2009. "Simulating Personal Carbon Trading: An Agent-Based Model," SPRU Working Paper Series 177, SPRU - Science Policy Research Unit, University of Sussex Business School.
    8. 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.
    9. Yang, Yulan & Li, Baizhan & Yao, Runming, 2010. "A method of identifying and weighting indicators of energy efficiency assessment in Chinese residential buildings," Energy Policy, Elsevier, vol. 38(12), pages 7687-7697, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lee, Timothy & Yao, Runming, 2013. "Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis," Energy Policy, Elsevier, vol. 52(C), pages 363-372.
    2. Hossein Sabzian & Mohammad Ali Shafia & Mehdi Ghazanfari & Ali Bonyadi Naeini, 2020. "Modeling the Adoption and Diffusion of Mobile Telecommunications Technologies in Iran: A Computational Approach Based on Agent-Based Modeling and Social Network Theory," Sustainability, MDPI, vol. 12(7), pages 1-36, April.
    3. 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.
    4. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    5. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    6. Kelly, S., 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector," Cambridge Working Papers in Economics 1139, Faculty of Economics, University of Cambridge.
    7. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    8. Gnann, Till & Stephens, Thomas S. & Lin, Zhenhong & Plötz, Patrick & Liu, Changzheng & Brokate, Jens, 2018. "What drives the market for plug-in electric vehicles? - A review of international PEV market diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 158-164.
    9. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    10. Martin Van Bueren & Jeff Bennett, 2004. "Towards the development of a transferable set of value estimates for environmental attributes," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(1), pages 1-32, March.
    11. Atallah, Shadi S. & Huang, Ju-Chin & Leahy, Jessica & Bennett, Karen, 2020. "Preference Heterogeneity and Neighborhood Effect in Invasive Species Control: The Case of Glossy Buckthorn in New Hampshire and Maine Forests," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304623, Agricultural and Applied Economics Association.
    12. Nick Hanley & Douglas MacMillan & Robert E. Wright & Craig Bullock & Ian Simpson & Dave Parsisson & Bob Crabtree, 1998. "Contingent Valuation Versus Choice Experiments: Estimating the Benefits of Environmentally Sensitive Areas in Scotland," Journal of Agricultural Economics, Wiley Blackwell, vol. 49(1), pages 1-15, March.
    13. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    14. Wang Chang & Yun Zhu & Che-Jen Lin & Saravanan Arunachalam & Shuxiao Wang & Jia Xing & Tingting Fang & Shicheng Long & Jinying Li & Geng Chen, 2022. "Environmental Justice Assessment of Fine Particles, Ozone, and Mercury over the Pearl River Delta Region, China," Sustainability, MDPI, vol. 14(17), pages 1-15, August.
    15. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
    16. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    18. Pereira, Iraci Miranda & Assis, Eleonora Sad de, 2013. "Urban energy consumption mapping for energy management," Energy Policy, Elsevier, vol. 59(C), pages 257-269.
    19. Stefano Ceolotto & Eleanor Denny, 2021. "Putting a new 'spin' on energy labels: measuring the impact of reframing energy efficiency on tumble dryer choices in a multi-country experiment," Trinity Economics Papers tep1521, Trinity College Dublin, Department of Economics.
    20. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:66:y:2014:i:c:p:267-279. 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: . General contact details of provider: http://www.elsevier.com/locate/enpol .

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.