IDEAS home Printed from https://ideas.repec.org/p/isu/genres/12776.html
   My bibliography  Save this paper

An Agent-Based Computational Laboratory for Wholesale Power Market Design

Author

Listed:
  • Sun, Junjie
  • Tesfatsion, Leigh S.

Abstract

This study reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Market power findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. Related work can be accessed at: http://www2.econ.iastate.edu/tesfatsi/AMESMarketHome.htm

Suggested Citation

  • Sun, Junjie & Tesfatsion, Leigh S., 2007. "An Agent-Based Computational Laboratory for Wholesale Power Market Design," Staff General Research Papers Archive 12776, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:12776
    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:

    Citations

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


    Cited by:

    1. 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.
    2. Zheng Ma & Mette Jessen Schultz & Kristoffer Christensen & Magnus Værbak & Yves Demazeau & Bo Nørregaard Jørgensen, 2019. "The Application of Ontologies in Multi-Agent Systems in the Energy Sector: A Scoping Review," Energies, MDPI, vol. 12(16), pages 1-31, August.
    3. Priyanka Shinde & Ioannis Boukas & David Radu & Miguel Manuel de Villena & Mikael Amelin, 2021. "Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach," Energies, MDPI, vol. 14(13), pages 1-31, June.
    4. Moradi, Mohammad H. & Razini, Saleh & Mahdi Hosseinian, S., 2016. "State of art of multiagent systems in power engineering: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 814-824.

    More about this item

    Keywords

    Wholesale electric power markets; restructuring; locational marginal price; software; Agent-based test bed; AMES;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D6 - Microeconomics - - Welfare Economics
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:isu:genres:12776. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Curtis Balmer (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.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.