IDEAS home Printed from https://ideas.repec.org/p/zbw/fisisi/s52007.html
   My bibliography  Save this paper

Agent-based simulation of electricity markets: a literature review

Author

Listed:
  • Sensfuß, Frank
  • Ragwitz, Mario
  • Genoese, Massimo
  • Möst, Dominik

Abstract

Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets.

Suggested Citation

  • 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).
    • Handle: RePEc:zbw:fisisi:s52007
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/28520/1/570113083.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Day, Christopher J & Bunn, Derek W, 2001. "Divestiture of Generation Assets in the Electricity Pool of England and Wales: A Computational Approach to Analyzing Market Power," Journal of Regulatory Economics, Springer, vol. 19(2), pages 123-141, March.
    2. Derek Bunn & Fernando Oliveira, 2003. "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation," Annals of Operations Research, Springer, vol. 121(1), pages 57-77, July.
    3. 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.
    4. Sun, Junjie & Tesfatsion, Leigh, 2006. "DC Optimal Power Flow Formulation and Solution Using QuadProgJ," Working Papers 18221, Iowa State University, Department of Economics.
    5. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    6. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    7. Michael J. North, 2001. "Multi-Agent Social and Organizational Modeling of Electric Power and Natural Gas Markets," Computational and Mathematical Organization Theory, Springer, vol. 7(4), pages 331-337, December.
    8. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    9. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    10. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    11. Nicolaisen, James & Smith, Matthew & Petrov, Valentin & Tesfatsion, Leigh, 2000. "Concentration and Capacity Effects on Electricity Market Power," Staff General Research Papers Archive 1847, Iowa State University, Department of Economics.
    12. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    13. Bunn, Derek W. & Martoccia, Maria, 2005. "Unilateral and collusive market power in the electricity pool of England and Wales," Energy Economics, Elsevier, vol. 27(2), pages 305-315, March.
    14. Koesrindartoto, Deddy P., 2002. "Discrete Double Auctions with Artificial Adaptive Agents: A Case Study of an Electricity Market Using a Double Auction Simulator," Staff General Research Papers Archive 10017, Iowa State University, Department of Economics.
    15. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    16. Bower, John & Bunn, Derek, 2001. "Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 561-592, March.
    17. Koesrindartoto, Deddy P. & Tesfatsion, Leigh, 2004. "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach," Staff General Research Papers Archive 12326, Iowa State University, Department of Economics.
    18. 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.
    19. Klemperer, Paul D & Meyer, Margaret A, 1989. "Supply Function Equilibria in Oligopoly under Uncertainty," Econometrica, Econometric Society, vol. 57(6), pages 1243-1277, November.
    20. Bower, John & Bunn, Derek W. & Wattendrup, Claus, 2001. "A model-based analysis of strategic consolidation in the German electricity industry," Energy Policy, Elsevier, vol. 29(12), pages 987-1005, October.
    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. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    2. Kraan, Oscar & Kramer, Gert Jan & Nikolic, Igor & Chappin, Emile & Koning, Vinzenz, 2019. "Why fully liberalised electricity markets will fail to meet deep decarbonisation targets even with strong carbon pricing," Energy Policy, Elsevier, vol. 131(C), pages 99-110.
    3. Herrmann, J.K. & Savin, I., 2017. "Optimal policy identification: Insights from the German electricity market," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 71-90.
    4. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    5. Frank Beckenbach & Maria Daskalakis & David Hofmann, 2018. "Agent-Based Analysis of Industrial Dynamics and Paths of Environmental Policy: The Case of Non-renewable Energy Production in Germany," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 953-994, October.
    6. Weiss, Olga & Pareschi, Giacomo & Georges, Gil & Boulouchos, Konstantinos, 2021. "The Swiss energy transition: Policies to address the Energy Trilemma," Energy Policy, Elsevier, vol. 148(PA).
    7. Haghnevis, Moeed & Askin, Ronald G. & Armbruster, Dieter, 2016. "An agent-based modeling optimization approach for understanding behavior of engineered complex adaptive systems," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 67-87.
    8. Rosen, Christiane & Madlener, Reinhard, 2012. "Auction Design for Local Reserve Energy Markets," FCN Working Papers 7/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2013.
    9. Cristian Zambrano & Yris Olaya, 2017. "An agent-based simulation approach to congestion management for the Colombian electricity market," Annals of Operations Research, Springer, vol. 258(2), pages 217-236, November.
    10. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.
    11. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Industry evolution, rational agents and the transition to sustainable electricity production," Energy Policy, Elsevier, vol. 39(10), pages 6440-6452, October.
    12. Laura Torralba-Díaz & Christoph Schimeczek & Matthias Reeg & Georgios Savvidis & Marc Deissenroth-Uhrig & Felix Guthoff & Benjamin Fleischer & Kai Hufendiek, 2020. "Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model," Energies, MDPI, vol. 13(15), pages 1-19, July.
    13. Milad Maralani & Milad Maralani & Basil Sharp & Golbon Zakeri, 2016. "The Potential Impact of Industrial Energy Savings on The New Zealand Economy," EcoMod2016 9308, EcoMod.
    14. Herrmann, Johannes & Savin, Ivan, 2015. "Evolution of the electricity market in Germany: Identifying policy implications by an agent-based model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112959, Verein für Socialpolitik / German Economic Association.
    15. Will, Christian & Zimmermann, Florian & Ensslen, Axel & Fraunholz, Christoph & Jochem, Patrick & Keles, Dogan, 2023. "Can electric vehicle charging be carbon neutral? Uniting smart charging and renewables," Working Paper Series in Production and Energy 69, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    16. Kraan, O. & Kramer, G.J. & Nikolic, I., 2018. "Investment in the future electricity system - An agent-based modelling approach," Energy, Elsevier, vol. 151(C), pages 569-580.
    17. Kueppers, Martin & Paredes Pineda, Stephany Nicole & Metzger, Michael & Huber, Matthias & Paulus, Simon & Heger, Hans Joerg & Niessen, Stefan, 2021. "Decarbonization pathways of worldwide energy systems – Definition and modeling of archetypes," Applied Energy, Elsevier, vol. 285(C).
    18. Arango, Santiago & Larsen, Erik, 2011. "Cycles in deregulated electricity markets: Empirical evidence from two decades," Energy Policy, Elsevier, vol. 39(5), pages 2457-2466, May.
    19. 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.
    20. Weiss, Olga & Bogdanov, Dmitry & Salovaara, Kaisa & Honkapuro, Samuli, 2017. "Market designs for a 100% renewable energy system: Case isolated power system of Israel," Energy, Elsevier, vol. 119(C), pages 266-277.
    21. Bunn, Derek & Yusupov, Tim, 2015. "The progressive inefficiency of replacing renewable obligation certificates with contracts-for-differences in the UK electricity market," Energy Policy, Elsevier, vol. 82(C), pages 298-309.
    22. Marc Deissenroth & Martin Klein & Kristina Nienhaus & Matthias Reeg, 2017. "Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration," Complexity, Hindawi, vol. 2017, pages 1-24, December.

    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. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    2. Albert Banal-Estañol & Augusto Rupérez-Micola, 2010. "Are agent-based simulations robust? The wholesale electricity trading case," Economics Working Papers 1214, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Banal-Estañol, Albert & Rupérez Micola, Augusto, 2011. "Behavioural simulations in spot electricity markets," European Journal of Operational Research, Elsevier, vol. 214(1), pages 147-159, October.
    4. 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.
    5. 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.
    6. Eric Guerci & Stefano Ivaldi & Silvano Cincotti, 2008. "Learning Agents in an Artificial Power Exchange: Tacit Collusion, Market Power and Efficiency of Two Double-auction Mechanisms," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 73-98, September.
    7. Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.
    8. repec:hal:spmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS
    9. repec:hal:spmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    10. Rahimiyan, Morteza & Rajabi Mashhadi, Habib, 2010. "Evaluating the efficiency of divestiture policy in promoting competitiveness using an analytical method and agent-based computational economics," Energy Policy, Elsevier, vol. 38(3), pages 1588-1595, March.
    11. Lin-Ju Chen & Lei Zhu & Ying Fan & Sheng-Hua Cai, 2013. "Long-Term Impacts of Carbon Tax and Feed-in Tariff Policies on China's Generating Portfolio and Carbon Emissions: A Multi-Agent-Based Analysis," Energy & Environment, , vol. 24(7-8), pages 1271-1293, December.
    12. 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.
    13. Rashidova E.A., 2017. "Agent-based modeling of wholesale electricity market," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 17(1), pages 70-85.
    14. Alan Mehlenbacher, 2007. "Multiagent System Platform for Auction Simulations," Department Discussion Papers 0706, Department of Economics, University of Victoria.
    15. Shu-Heng Chen & Bin-Tzong Chie & Ying-Fang Kao & Ragupathy Venkatachalam, 2019. "Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 305-341, June.
    16. Schuster, Stephan, 2012. "Applications in Agent-Based Computational Economics," MPRA Paper 47201, University Library of Munich, Germany.
    17. E. J. Anderson & T. D. H. Cau, 2009. "Modeling Implicit Collusion Using Coevolution," Operations Research, INFORMS, vol. 57(2), pages 439-455, April.
    18. 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.
    19. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    20. Zhang, Hui & Cao, Libin & Zhang, Bing, 2017. "Emissions trading and technology adoption: An adaptive agent-based analysis of thermal power plants in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 23-32.
    21. Markose, Sheri & Alentorn, Amadeo & Koesrindartoto, Deddy & Allen, Peter & Blythe, Phil & Grosso, Sergio, 2007. "A smart market for passenger road transport (SMPRT) congestion: An application of computational mechanism design," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 2001-2032, June.
    22. Mellár, Tamás & Hau, Orsolya & Sebestyén, Tamás, 2013. "Láthatóvá tehető-e a láthatatlan kéz? Egy ágensalapú piaci modell tapasztalatai [Can the invisible hand be rendered visible? Experiences of an agent-based market model]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 992-1024.

    More about this item

    Statistics

    Access and download statistics

    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:zbw:fisisi:s52007. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isfhgde.html .

    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.