• DocumentCode
    816649
  • Title

    Agent-Based Approach to Handle Business Complexity in U.S. Wholesale Power Trading

  • Author

    Sueyoshi, Toshiyuki ; Tadiparthi, Gopalakrishna Reddy

  • Author_Institution
    Dept. of Manage., New Mexico Inst. of Min. & Technol., Socorro, NM
  • Volume
    22
  • Issue
    2
  • fYear
    2007
  • fDate
    5/1/2007 12:00:00 AM
  • Firstpage
    532
  • Lastpage
    543
  • Abstract
    This study documents the practicality of an agent-based approach by examining how two groups of agents handle business complexity related to power trading. Three important findings are identified in this research. First, the proposed approach can estimate fluctuations of electricity prices as well as other well-known methods such as neural networks and genetic algorithms. Second, multiple learning capabilities incorporated in adaptive agents do not have an advantage over limited learning capabilities in predicting the market price of electricity. Finally, a theoretical extension of multiple learning capabilities may have potential for developing the agent-based approach for power trading
  • Keywords
    genetic algorithms; neural nets; power engineering computing; power markets; power system economics; software agents; US wholesale power trading; adaptive agents; agent-based approach; business complexity; electricity market price; electricity price fluctuation estimation; genetic algorithms; multiple learning capabilities; neural networks; Assembly systems; Computer science; Electronic mail; Fluctuations; Genetic algorithms; Machine learning; Neural networks; Numerical analysis; Operations research; Power markets; Agent-based approach; machine learning; numerical analysis; power trading;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2007.894856
  • Filename
    4162622