IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitmx/v10y2013i05ns0219877013400208.html
   My bibliography  Save this article

Agent-Based Simulation Of Consumer Demand For Smart Metering Tariffs

Author

Listed:
  • MARTIN RIXEN

    (Whu-Otto Beisheim School of Management, Burgplatz 2, 56179 Vallendar, Germany)

  • JÜRGEN WEIGAND

    (Whu-Otto Beisheim School of Management, Burgplatz 2, 56179 Vallendar, Germany)

Abstract

An agent-based model simulates consumer demand for smart metering tariffs. It utilizes the Bass Diffusion Model and Rogers's adopter categories to locate demand-side barriers and drivers. Integration of empirical census microdata enables a validated socio-economic background for each consumer. The key performance indicators diffusion-speed and diffusion-level measure the effectiveness of regulatory interventions to induce diffusion. Pricing, promotion and quantity-regulation policies are tested. Scenario results emphasize the impact of both epidemic and probit effects. Speed of adoption is mainly triggered via interactions and consumer awareness. Level of diffusion primarily depends on pricing, willingness-to-pay and cost-benefit-thresholds. Data mining on agent's attributes highlight weaknesses in current regulatory requirements due to disadvantages in consumer acceptance and policy effectiveness. A "cash-for-clunkers" program could tackle major barriers for adoption and boost diffusion through synergies of pricing and promotion interventions.

Suggested Citation

  • Martin Rixen & Jürgen Weigand, 2013. "Agent-Based Simulation Of Consumer Demand For Smart Metering Tariffs," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 1-26.
    • Handle: RePEc:wsi:ijitmx:v:10:y:2013:i:05:n:s0219877013400208
    DOI: 10.1142/S0219877013400208
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219877013400208
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219877013400208?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. Brophy Haney, A. & Jamasb, T. & Pollitt, M.G., 2009. "Smart Metering and Electricity Demand: Technology, Economics and International Experience," Cambridge Working Papers in Economics 0905, Faculty of Economics, University of Cambridge.
    2. 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.
    3. Tao Zhang & William J. Nuttall, 2007. "An Agent Based Simulation of Smart Metering Technology Adoption," Working Papers EPRG 0727, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    4. Tao Zhang & William J. Nuttall, 2012. "An Agent-Based Simulation of Smart Metering Technology Adoption," International Journal of Agent Technologies and Systems (IJATS), IGI Global, vol. 4(1), pages 17-38, January.
    5. Vasconcelos & Jorge, 2008. "Survey of Regulatory and Technological Developments Concerning Smart Metering in the European Union Electricity Market," EUI-RSCAS Working Papers 1, European University Institute (EUI), Robert Schuman Centre of Advanced Studies (RSCAS).
    6. Pollitt, M.G., 2009. "Electricity Liberalisation in the European Union: A Progress Report," Cambridge Working Papers in Economics 0953, Faculty of Economics, University of Cambridge.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    2. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    3. Strong, Derek Ryan, 2017. "The Early Diffusion of Smart Meters in the US Electric Power Industry," Thesis Commons 7zprk, Center for Open Science.

    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. Rious, Vincent & Perez, Yannick & Roques, Fabien, 2015. "Which electricity market design to encourage the development of demand response?," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 128-138.
    2. Mah, Daphne Ngar-yin & van der Vleuten, Johannes Marinus & Hills, Peter & Tao, Julia, 2012. "Consumer perceptions of smart grid development: Results of a Hong Kong survey and policy implications," Energy Policy, Elsevier, vol. 49(C), pages 204-216.
    3. Claire Bergaentzlé, 2012. "Particularités d'adoption des compteurs intelligents au Royaume-Uni et en Allemagne : entre marchés de comptage libéralisé et règles à mettre en place pour un réel smart grid intégré," Post-Print halshs-00793322, HAL.
    4. Adela Conchado & Pedro Linares, 2010. "The Economic Impact of Demand-Response Programs on Power Systems. A survey of the State of the Art," Working Papers 02-2010, Economics for Energy.
    5. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    6. Elena Claire Ricci, 2013. "Smart-Grids and Climate Change. Consumer adoption of smart energy behaviour: a system dynamics approach to evaluate the mitigation potential," Working Papers 2013.71, Fondazione Eni Enrico Mattei.
    7. 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.
    8. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    9. repec:ers:journl:v:xv:y:2012:i:sie:p:157-194 is not listed on IDEAS
    10. Davide Della Giustina & Stefano Rinaldi & Stefano Robustelli & Andrea Angioni, 2021. "Massive Generation of Customer Load Profiles for Large Scale State Estimation Deployment: An Approach to Exploit AMI Limited Data," Energies, MDPI, vol. 14(5), pages 1-26, February.
    11. Chen, Hao & Cui, Jian & Song, Feng & Jiang, Zhigao, 2022. "Evaluating the impacts of reforming and integrating China's electricity sector," Energy Economics, Elsevier, vol. 108(C).
    12. Swora, Mariusz, 2011. "Smart grids after the third liberalization package: current developments and future challenges for regulatory policy in the electricity sector," MPRA Paper 34897, University Library of Munich, Germany.
    13. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    14. Isabel Soares & Paula Sarmento, 2012. "Unbundling in the Telecommunications and the Electricity Sectors: How Far should it Go?," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 157-194.
    15. 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.
    16. Bastianin, Andrea & Castelnovo, Paolo & Florio, Massimo, 2018. "Evaluating regulatory reform of network industries: a survey of empirical models based on categorical proxies," Utilities Policy, Elsevier, vol. 55(C), pages 115-128.
    17. Polemis, Michael L., 2016. "New evidence on the impact of structural reforms on electricity sector performance," Energy Policy, Elsevier, vol. 92(C), pages 420-431.
    18. Polemis, Michael L. & Fafaliou, Irene, 2015. "Electricity regulation and FDIs spillovers in the OECD: A panel data econometric approach," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 110-123.
    19. Clastres, Cédric & Khalfallah, Haikel, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Energy Economics, Elsevier, vol. 98(C).
    20. Steven M. Smith, 2019. "The Relative Economic Merits of Alternative Water Rights," Working Papers 2019-08, Colorado School of Mines, Division of Economics and Business.
    21. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.

    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:wsi:ijitmx:v:10:y:2013:i:05:n:s0219877013400208. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitm/ijitm.shtml .

    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.