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Evaluating Government’s Policies on Promoting Smart Metering in Retail Electricity Markets via Agent Based Simulation

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  • Zhang, T.
  • Nuttall, W.J.

Abstract

In this paper, we develop an agent-based model of a market game in order to evaluate the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering. We also consider possible supplementary strategies. With the model, we test the effectiveness of four possible strategy options and suggest their policy implications. The context of the paper is a practical application of agent-based simulation to the retail electricity market in Britain. The contribution of the research are both in the areas of policy making for electricity markets and in the methodological use of agent-based simulation for studying social complex systems involving human behaviour.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0842.

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Date of creation: Aug 2008
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Handle: RePEc:cam:camdae:0842

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Web page: http://www.econ.cam.ac.uk/index.htm

Related research

Keywords: agent-based simulation; smart metering technology; the Theory of Planned Behaviour; retail electricity market;

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  1. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 1(1), pages 57-72, March.
  2. Hall, Bronwyn H. & Khan, Beethika, 2003. "Adoption of New Technology," Department of Economics, Working Paper Series qt3wg4p528, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  3. Zhang, Tao & Zhang, David, 2007. "Agent-based simulation of consumer purchase decision-making and the decoy effect," Journal of Business Research, Elsevier, vol. 60(8), pages 912-922, August.
  4. Stoneman, Paul, 2001. "Financial Factors and the Inter Firm Diffusion of New Technology: A Real Options Model," EIFC - Technology and Finance Working Papers 8, United Nations University, Institute for New Technologies.
  5. 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.
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Cited by:
  1. 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.
  2. 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.
  3. Palmer, Johannes & Sorda, Giovanni & Madlener, Reinhard, 2013. "Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-based Simulation," FCN Working Papers 9/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  4. 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.

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