IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-00871023.html
   My bibliography  Save this paper

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

Author

Listed:
  • Eric Guerci

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (... - 2019) - COMUE UCA - COMUE Université Côte d'Azur (2015-2019) - CNRS - Centre National de la Recherche Scientifique - UCA - Université Côte d'Azur, GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - École Centrale de Marseille - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université)

  • Stefano Ivaldi

    (Chercheur indépendant)

  • Stefano Pastore

    (DICAR - Dipartimento di Ingegneria e Architettura - Università degli studi di Trieste)

  • Silvano Cincotti

    (DIME - Dipartimento di ingegneria meccanica, energetica, gestionale e dei trasporti - Universita degli studi di Genova)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Eric Guerci & Stefano Ivaldi & Stefano Pastore & Silvano Cincotti, 2005. "Modeling and implementation of an artificial electricity market using agent-based technology," Post-Print halshs-00871023, HAL.
  • Handle: RePEc:hal:journl:halshs-00871023
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00871023
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    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

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


    Cited by:

    1. 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.
    2. 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.
    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. 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.
    5. 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.
    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. Oliveira, Fernando, 2008. "The value of information in electricity investment games," Energy Policy, Elsevier, vol. 36(7), pages 2364-2375, July.
    8. 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.

    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. Gaivoronskaia, E. & Tsyplakov, A., 2018. "Using a Modified Erev-Roth Algorithm in an Agent-Based Electricity Market Model," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 55-83.
    2. Dawid Herbert & Gemkow Simon & Harting Philipp & Kabus Kordian & Wersching Klaus & Neugart Michael, 2008. "Skills, Innovation, and Growth: An Agent-Based Policy Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 251-275, April.
    3. Atakelty Hailu & Sophie Thoyer, 2007. "Designing Multi‐unit Multiple Bid Auctions: An Agent‐based Computational Model of Uniform, Discriminatory and Generalised Vickrey Auctions," The Economic Record, The Economic Society of Australia, vol. 83(s1), pages 57-72, September.
    4. 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.
    5. Marie-Noëlle Calès & Laurent Granier & Nadège Marchand, 2012. "Competition between Clearing Houses on the European Market," Post-Print halshs-00959121, HAL.
    6. 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.
    7. Nicolas Audet & Toni Gravelle & Jing Yang, 2002. "Alternative Trading Systems: Does One Shoe Fit All?," Staff Working Papers 02-33, Bank of Canada.
    8. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    9. Somani, Abhishek, 2012. "Financial risk management and market performance in restructured electric power markets: Theoretical and agent-based test bed studies," ISU General Staff Papers 201201010800003479, Iowa State University, Department of Economics.
    10. Deddy Koesrindartoto, 2003. "Treasury Auctions, Uniform or Discriminatory?: An Agent-based Approach," Computing in Economics and Finance 2003 241, Society for Computational Economics.
    11. Esmaeili Aliabadi, Danial & Kaya, Murat & Sahin, Guvenc, 2017. "Competition, risk and learning in electricity markets: An agent-based simulation study," Applied Energy, Elsevier, vol. 195(C), pages 1000-1011.
    12. Atakelty Hailu & Sophie Thoyer, 2006. "Multi-unit auction format design," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(2), pages 129-146, November.
    13. Christian Gouriéroux & Gaëlle Le Fol, 1998. "Effet des modes de négociation sur les échanges," Revue Économique, Programme National Persée, vol. 49(3), pages 795-808.
    14. Sandro Sapio, 2004. "Markets Design, Bidding Rules, and Long Memory in Electricity Prices," Revue d'Économie Industrielle, Programme National Persée, vol. 107(1), pages 151-170.
    15. Tang, Ling & Wu, Jiaqian & Yu, Lean & Bao, Qin, 2017. "Carbon allowance auction design of China's emissions trading scheme: A multi-agent-based approach," Energy Policy, Elsevier, vol. 102(C), pages 30-40.
    16. Li, Hongyan & Tesfatsion, Leigh, 2012. "Co-learning patterns as emergent market phenomena: An electricity market illustration," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 395-419.
    17. Anatoliy Swishchuk & Nelson Vadori, 2016. "A Semi-Markovian Modeling of Limit Order Markets," Papers 1601.01710, arXiv.org.
    18. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    19. Leigh Tesfatsion, 2017. "Elements of Dynamic Economic Modeling: Presentation and Analysis," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 192-216, March.
    20. Haoyang Liu & Zhaogang Song & James Vickery, 2021. "Defragmenting Markets: Evidence from Agency MBS," Staff Reports 965, Federal Reserve Bank of New York.

    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:hal:journl:halshs-00871023. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.