Microgrid Modelling and Analysis Using Game Theory Methods

  • Petros Aristidou
  • Aris Dimeas
  • Nikos Hatziargyriou
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 54)


Game theory is a branch of applied mathematics that is, most notably, used in economics as well as in engineering and other disciplines. Game theory attempts to mathematically capture behaviour in strategic situations, in which an individual’s success in making choices depends on the choices of others. The microgrid encompasses a portion of an electric power distribution system that is located downstream of the distribution substation, and it includes a variety of DER units and different types of end users of electricity and/or heat. Microgrids promote the use of new technologies, under the general Smart Grids’ umbrella, in order to achieve more efficient use of electric energy, better protection, improved control and provide services to the users. For the materialization of the infrastructure needed to implement this model, engineers have nominated technologies like smart agents, distributed computing, smart sensors and others, as well as, a solid and fast communication infrastructure. In this decentralized environment, multiple decision making participants interact, each striving to optimize its own objectives. Thus, a game theoretic approach is attempted to model and analyse the strategic situations arising from the interactions.


Microgrid game theory decision makers 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aumann, R.J.: What is game theory trying to accomplish. Frontiers of economics 29, 28–99 (1985)MathSciNetGoogle Scholar
  2. 2.
    Braithwait, S.: Behavior modification. IEEE Power and Energy Magazine 8(3), 36–45 (2010)CrossRefGoogle Scholar
  3. 3.
    Colin, C.: Behavioral game theory: experiments in strategic interaction. Russesll Sage Foundation, London (2003)zbMATHGoogle Scholar
  4. 4.
    Dimeas, A.L., Hatziargyriou, N.D.: Operation of a multiagent system for microgrid control. IEEE Transactions on Power Systems 20(3), 1447–1455 (2005)CrossRefGoogle Scholar
  5. 5.
    Eatwell, J., Milgate, M., Newman, P. (eds.): The new palgrave: A dictionary of economics, ch. 2, p. 46082. Palgrave Macmillan, Oxford (1987)Google Scholar
  6. 6.
    Gibbons, R.: Game Theory for Applied Economists (1992)Google Scholar
  7. 7.
    Katiraei, F., Iravani, R., Hatziargyriou, N., Dimeas, A.: MicroGrids Management, control and Operation Aspects of MicroGrids. IEEE Power Energy Mag. 6(3), 54–65 (2008)CrossRefGoogle Scholar
  8. 8.
    McArthur, S.D.J., Davidson, E.M., Catterson, V.M., Dimeas, A.L., Hatziargyriou, N.D., Ponci, F., Funabashi, T.: Multi-agent systems for power engineering applications Part II: Technologies, standards, and tools for building multi-agent systems. IEEE Transactions on Power Systems 22(4), 1753–1759 (2007)CrossRefGoogle Scholar
  9. 9.
    Parsons, S., Wooldridge, M.: Game theory and decision theory in multi-agent systems. Autonomous Agents and Multi-Agent Systems 5(3), 243–254 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Reiss, P.C., White, M.W.: Household electricity demand (2002)Google Scholar
  11. 11.
    Shor, M.: Dictionary of game theory terms, game theory. net (July 2010) (online)Google Scholar
  12. 12.
    von Neumann, J., Morgenstern, O.: Theory of games and economic behavior. Princeton University Press, Princeton (1944)zbMATHGoogle Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2011

Authors and Affiliations

  • Petros Aristidou
    • 1
  • Aris Dimeas
    • 1
  • Nikos Hatziargyriou
    • 1
  1. 1.School of Electrical and Computer EngineeringNational Technical University of AthensAthensGreece

Personalised recommendations