IDEAS home Printed from https://ideas.repec.org/p/wuu/wpaper/hsc1310.html
   My bibliography  Save this paper

Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs

Author

Listed:
  • Anna Kowalska-Pyzalska
  • Katarzyna Maciejowska
  • Katarzyna Sznajd-Weron
  • Karol Suszczynski
  • Rafal Weron

Abstract

Using an agent-based modeling approach we study the temporal dynamics of consumer opinions regarding switching to dynamic electricity tariffs and the actual decisions to switch. We assume that the decision to switch is based on the unanimity of $\tau$ past opinions. The resulting model explains why there is such a big discrepancy between consumer opinions, as measured by market surveys, and the actual participation in pilot programs and the adoption of dynamic tariffs. We argue that due to the high indifference level in today's retail electricity markets, customer opinions are very unstable and change frequently. The conducted simulation study shows that reducing the indifference level can result in narrowing the intention-behavior gap. A similar effect can be achieved by decreasing the decision time that a consumer takes to make a decision.

Suggested Citation

  • Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Karol Suszczynski & Rafal Weron, 2013. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," HSC Research Reports HSC/13/10, Hugo Steinhaus Center, Wroclaw University of Technology.
  • Handle: RePEc:wuu:wpaper:hsc1310
    as

    Download full text from publisher

    File URL: http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_13_10.pdf
    File Function: Original version, 2013; Final version published in Energy Policy 72, 164-174 (2014; doi:10.1016/j.enpol.2014.04.021)
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Scarpa, Riccardo & Willis, Ken, 2010. "Willingness-to-pay for renewable energy: Primary and discretionary choice of British households' for micro-generation technologies," Energy Economics, Elsevier, vol. 32(1), pages 129-136, January.
    2. Jager, Wander, 2006. "Stimulating the diffusion of photovoltaic systems: A behavioural perspective," Energy Policy, Elsevier, vol. 34(14), pages 1935-1943, September.
    3. Berninghaus, Siegfried K. & Haller, Sven & Krüger, Tyll & Neumann, Thomas & Schosser, Stephan & Vogt, Bodo, 2013. "Risk attitude, beliefs, and information in a Corruption Game – An experimental analysis," Journal of Economic Psychology, Elsevier, vol. 34(C), pages 46-60.
    4. Gadenne, David & Sharma, Bishnu & Kerr, Don & Smith, Tim, 2011. "The influence of consumers' environmental beliefs and attitudes on energy saving behaviours," Energy Policy, Elsevier, vol. 39(12), pages 7684-7694.
    5. McMichael, Megan & Shipworth, David, 2013. "The value of social networks in the diffusion of energy-efficiency innovations in UK households," Energy Policy, Elsevier, vol. 53(C), pages 159-168.
    6. Ian Ayres & Sophie Raseman & Alice Shih, 2013. "Evidence from Two Large Field Experiments that Peer Comparison Feedback Can Reduce Residential Energy Usage," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 29(5), pages 992-1022, October.
    7. Gangale, Flavia & Mengolini, Anna & Onyeji, Ijeoma, 2013. "Consumer engagement: An insight from smart grid projects in Europe," Energy Policy, Elsevier, vol. 60(C), pages 621-628.
    8. Thorsnes, Paul & Williams, John & Lawson, Rob, 2012. "Consumer responses to time varying prices for electricity," Energy Policy, Elsevier, vol. 49(C), pages 552-561.
    9. Stephenson, Janet & Barton, Barry & Carrington, Gerry & Gnoth, Daniel & Lawson, Rob & Thorsnes, Paul, 2010. "Energy cultures: A framework for understanding energy behaviours," Energy Policy, Elsevier, vol. 38(10), pages 6120-6129, October.
    10. Baddeley, M., 2011. "Energy, the Environment and Behaviour Change: A survey of insights from behavioural economics," Cambridge Working Papers in Economics 1162, Faculty of Economics, University of Cambridge.
    11. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    12. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    13. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    14. Zhang, T. & Nuttall, W.J., 2008. "Evaluating Government’s Policies on Promoting Smart Metering in Retail Electricity Markets via Agent Based Simulation," Cambridge Working Papers in Economics 0842, Faculty of Economics, University of Cambridge.
    15. Sznajd-Weron, K. & Weron, R., 2003. "How effective is advertising in duopoly markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 437-444.
    16. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Modeling consumer opinions towards dynamic pricing: An agent-based approach," HSC Research Reports HSC/14/06, Hugo Steinhaus Center, Wroclaw University of Technology.
    17. Diaz-Rainey, Ivan & Tzavara, Dionisia, 2012. "Financing the decarbonized energy system through green electricity tariffs: A diffusion model of an induced consumer environmental market," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1693-1704.
    18. Weyant, John P., 2011. "Accelerating the development and diffusion of new energy technologies: Beyond the "valley of death"," Energy Economics, Elsevier, vol. 33(4), pages 674-682, July.
    19. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
    20. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    21. Ritsuko Ozaki, 2011. "Adopting sustainable innovation: what makes consumers sign up to green electricity?," Business Strategy and the Environment, Wiley Blackwell, vol. 20(1), pages 1-17, January.
    22. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    23. Gyberg, Per & Palm, Jenny, 2009. "Influencing households' energy behaviour--how is this done and on what premises?," Energy Policy, Elsevier, vol. 37(7), pages 2807-2813, July.
    24. Alexandra-Gwyn Paetz & Elisabeth Dütschke & Wolf Fichtner, 2012. "Smart Homes as a Means to Sustainable Energy Consumption: A Study of Consumer Perceptions," Journal of Consumer Policy, Springer, vol. 35(1), pages 23-41, March.
    25. Darby, Sarah J. & McKenna, Eoghan, 2012. "Social implications of residential demand response in cool temperate climates," Energy Policy, Elsevier, vol. 49(C), pages 759-769.
    26. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    27. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    28. Pongiglione, Francesca, 2011. "Climate Change and Individual Decision Making: An Examination of Knowledge, Risk Perception, Self-interest and Their Interplay," Climate Change and Sustainable Development 119094, Fondazione Eni Enrico Mattei (FEEM).
    29. Sidiras, Dimitrios K. & Koukios, Emmanuel G., 2004. "Solar systems diffusion in local markets," Energy Policy, Elsevier, vol. 32(18), pages 2007-2018, December.
    30. Guillaume Deffuant & Frederic Amblard, 2003. "Simple is Beautiful? and Necessary," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(1), pages 1-6.
    31. Ian Ayres & Sophie Raseman & Alice Shih, 2009. "Evidence from Two Large Field Experiments that Peer Comparison Feedback Can Reduce Residential Energy Usage," NBER Working Papers 15386, National Bureau of Economic Research, Inc.
    32. Dütschke, Elisabeth & Paetz, Alexandra-Gwyn, 2013. "Dynamic electricity pricing—Which programs do consumers prefer?," Energy Policy, Elsevier, vol. 59(C), pages 226-234.
    33. Zarnikau, Jay, 2003. "Consumer demand for `green power' and energy efficiency," Energy Policy, Elsevier, vol. 31(15), pages 1661-1672, December.
    34. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    35. 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.
    36. Ernst Fehr & Urs Fischbacher, 2002. "Why Social Preferences Matter -- The Impact of Non-Selfish Motives on Competition, Cooperation and Incentives," Economic Journal, Royal Economic Society, vol. 112(478), pages 1-33, March.
    37. Greenleaf, Eric A & Lehmann, Donald R, 1995. "Reasons for Substantial Delay in Consumer Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(2), pages 186-199, September.
    38. Francesca Pongiglione, 2011. "Climate Change and Individual Decision Making: An Examination of Knowledge, Risk Perception, Self-interest and Their Interplay," Working Papers 2011.72, Fondazione Eni Enrico Mattei.
    39. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    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. Anna Kowalska-Pyzalska, 2015. "Social acceptance of green energy and dynamic electricity tariffs - a short review," HSC Research Reports HSC/15/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    2. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    5. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    6. Anna Kowalska-Pyzalska & Katarzyna Byrka, 2019. "Determinants of the Willingness to Energy Monitoring by Residential Consumers: A Case Study in the City of Wroclaw in Poland," Energies, MDPI, vol. 12(5), pages 1-20, March.
    7. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Modeling consumer opinions towards dynamic pricing: An agent-based approach," HSC Research Reports HSC/14/06, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. Weron, Tomasz & Kowalska-Pyzalska, Anna & Weron, Rafał, 2018. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 591-600.
    9. Yash Chawla & Anna Kowalska-Pyzalska, 2019. "Public Awareness and Consumer Acceptance of Smart Meters among Polish Social Media Users," Energies, MDPI, vol. 12(14), pages 1-27, July.
    10. Anna Kowalska-Pyzalska, 2018. "An empirical analysis of green energy adoption among residential consumers in Poland," HSC Research Reports HSC/18/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Fang, Xingming & Wang, Lu & Sun, Chuanwang & Zheng, Xuemei & Wei, Jing, 2021. "Gap between words and actions: Empirical study on consistency of residents supporting renewable energy development in China," Energy Policy, Elsevier, vol. 148(PA).
    12. Baddeley, M., 2011. "Energy, the Environment and Behaviour Change: A survey of insights from behavioural economics," Cambridge Working Papers in Economics 1162, Faculty of Economics, University of Cambridge.
    13. Anna Kowalska-Pyzalska & Katarzyna Byrka & Jakub Serek, 2020. "How to Foster the Adoption of Electricity Smart Meters? A Longitudinal Field Study of Residential Consumers," Energies, MDPI, vol. 13(18), pages 1-19, September.
    14. Anna Kowalska-Pyzalska, 2018. "An Empirical Analysis of Green Electricity Adoption Among Residential Consumers in Poland," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    15. Chawla, Yash & Kowalska-Pyzalska, Anna & Skowrońska-Szmer, Anna, 2020. "Perspectives of smart meters’ roll-out in India: An empirical analysis of consumers’ awareness and preferences," Energy Policy, Elsevier, vol. 146(C).
    16. Lopes, Marta A.R. & Henggeler Antunes, Carlos & Janda, Kathryn B. & Peixoto, Paulo & Martins, Nelson, 2016. "The potential of energy behaviours in a smart(er) grid: Policy implications from a Portuguese exploratory study," Energy Policy, Elsevier, vol. 90(C), pages 233-245.
    17. Šćepanović, Sanja & Warnier, Martijn & Nurminen, Jukka K., 2017. "The role of context in residential energy interventions: A meta review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1146-1168.
    18. Magdalena Grębosz-Krawczyk & Agnieszka Zakrzewska-Bielawska & Sylwia Flaszewska, 2021. "From Words to Deeds: The Impact of Pro-Environmental Self-Identity on Green Energy Purchase Intention," Energies, MDPI, vol. 14(18), pages 1-17, September.
    19. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    20. Hobman, Elizabeth V. & Frederiks, Elisha R. & Stenner, Karen & Meikle, Sarah, 2016. "Uptake and usage of cost-reflective electricity pricing: Insights from psychology and behavioural economics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 455-467.

    More about this item

    Keywords

    Dynamic pricing; Demand response; Consumer decisions; Intention-behavior gap; Innovation diffusion; Agent-based model;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:wuu:wpaper:hsc1310. See general information about how to correct material in RePEc.

    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: Rafal Weron (email available below). General contact details of provider: https://edirc.repec.org/data/hspwrpl.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.