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Agent-Based Simulation Of Consumer Demand For Smart Metering Tariffs

Author

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  • 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
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    References listed on IDEAS

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    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., 2007. "An Agent Based Simulation Of Smart Metering Technology Adoption," Cambridge Working Papers in Economics 0760, Faculty of Economics, University of Cambridge.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
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    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.

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