• DocumentCode
    2122703
  • Title

    Energy and operating reserves procurement in presence of capacity limits

  • Author

    Haring, Tobias ; Andersson, Göran

  • Author_Institution
    EEH - Power Syst. Lab., ETH Zurich, Zurich, Switzerland
  • fYear
    2012
  • fDate
    9-12 Sept. 2012
  • Firstpage
    349
  • Lastpage
    354
  • Abstract
    In this paper we make use of an agent-based approach to model strategic behavior of supply units in an simultaneous clearing of spot energy and operating reserve power/energy. Generation units submit bids for energy and reserve power capacity as well as reserve energy. The test system shows the incidence of capacity limits as well as remote renewable energy penetration. The contributions of this paper are twofold: First, in contrast to the literature in agent-based electricity market simulation frameworks with discrete action sets we apply a “continuous” action set mechanism. The algorithm is derived from the common Q-learning approach. Second we show in a representative North-South model with substantial renewable energy-infeed and capacity limits the incidence of Locational Marginal Pricing on energy as well as reserve power markets in combination with strategically acting generation units.
  • Keywords
    learning (artificial intelligence); multi-agent systems; power engineering computing; power markets; pricing; Q-learning approach; agent-based approach; agent-based electricity market simulation frameworks; continuous action set mechanism; energy reserve procurement; locational marginal pricing; multiagent system; operating reserve procurement; remote renewable energy penetration; renewable energy-infeed; representative North-South model; reserve energy; reserve power capacity; reserve power markets; spot energy simultaneous clearing; strategically acting generation units; supply units; test system; Algorithm design and analysis; Generators; Mathematical model; Power markets; Pricing; Renewable energy resources; Electricity Market; continuous Q-learning; market design; multi-agent system; renewable energy in-feed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Conference and Exhibition (ENERGYCON), 2012 IEEE International
  • Conference_Location
    Florence
  • Print_ISBN
    978-1-4673-1453-4
  • Type

    conf

  • DOI
    10.1109/EnergyCon.2012.6347782
  • Filename
    6347782