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Modeling and implementation of an artificial electricity market using agent-based technology

Author

Listed:
  • Guerci, E.
  • Ivaldi, S.
  • Pastore, S.
  • Cincotti, S.

Abstract

This paper focuses on modeling power exchanges in a multi-agent interacting framework with reduced behavioral assumptions. A model of the day ahead market session of OMEL (the Spanish Power Exchange) is proposed using real demand data with simulated seller strategies. The number of sellers is defined at the first stage and the quantity of goods is distributed over the population of agents according to several initial distributions. A Clearing-house mechanism matches the cumulative demand and supply curves in order to determine the market-clearing price. The resulting price time-series are statistically tested to verify the validity of the model. Results show the main properties of real market and assess the validity of the proposed model.

Suggested Citation

  • Guerci, E. & Ivaldi, S. & Pastore, S. & Cincotti, S., 2005. "Modeling and implementation of an artificial electricity market using agent-based technology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 69-76.
    • Handle: RePEc:eee:phsmap:v:355:y:2005:i:1:p:69-76
    DOI: 10.1016/j.physa.2005.02.068
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    References listed on IDEAS

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    1. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    2. Ángel León & Antonio Rubia, 2001. "Comportamiento Del Precio Y Volatilidad En El Pool Eléctrico Español," Working Papers. Serie EC 2001-04, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    3. Derek W. Bunn and Fernando Oliveira, 2001. "An Application of Agent-based Simulation to the New Electricity Trading Arrangements of England and Wales," Computing in Economics and Finance 2001 93, Society for Computational Economics.
    4. Mendelson, Haim, 1982. "Market Behavior in a Clearing House," Econometrica, Econometric Society, vol. 50(6), pages 1505-1524, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Sandro Sapio, 2006. "An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets," LEM Papers Series 2006/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Liu, Beibei & He, Pan & Zhang, Bing & Bi, Jun, 2012. "Impacts of alternative allowance allocation methods under a cap-and-trade program in power sector," Energy Policy, Elsevier, vol. 47(C), pages 405-415.
    3. 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.
    4. Silvano Cincotti & Eric Guerci, 2005. "Agent-based simulation of power exchange with heterogeneous production companies," Computing in Economics and Finance 2005 334, Society for Computational Economics.
    5. 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.
    6. Sarıca, Kemal & Kumbaroğlu, Gürkan & Or, Ilhan, 2012. "Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach," Energy, Elsevier, vol. 44(1), pages 830-852.
    7. Yong Liu & Fei Li & Yunpeng Su, 2019. "Critical Factors Influencing the Evolution of Companies’ Environmental Behavior: An Agent-Based Computational Economic Approach," SAGE Open, , vol. 9(1), pages 21582440198, February.
    8. Oliveira, Fernando, 2008. "The value of information in electricity investment games," Energy Policy, Elsevier, vol. 36(7), pages 2364-2375, July.

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