Agent-Based Gaming Approach for Electricity Markets

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 96)


The Electricity Market in Japan has been an oligopolistic market since the previous century, but it will be a liberalised competitive market soon due to a policy change. It is supposed to provide wholesale power markets. Therefore it has high possibilities to become two-sided markets with strong wholesalers. The two-sided markets have been researched using mathematical economics models recent years. The model, however, can only deal with one or two players on a market, therefore it has limitations to analyse more various players. On the other hand, many research projects of dynamic pricing and incentive mechanisms have been carried out on power markets. Some of the studies use agent-based modelling to analyse them as autonomous agents and optimised decision-making algorithms. These studies have shown interesting results, but they also have limitations to analyse further more complex markets and decision making processes of market players taking managing conditions into consideration. In this study, we adopt Agent-based gaming to analyse them on a two-sided electricity market.


Electricity market Two-sided market Agent-based gaming 


  1. 1.
    Boudreau, K.J., Hagiu, A.: Platform rules: multi-sided platforms as regulations. Platf. Market. Innov. 1, 163–191 (2009)Google Scholar
  2. 2.
    Unno, M., Xu, H.: Opitmal platform strategies in the smartphone market. IEEJ Trans. Electr. Inf. Syst. 132(3), 467–476 (2012)Google Scholar
  3. 3.
    Bacon, D.F., et al.: Predicting your own effort. In: International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), vol. 2, pp. 695–702 (2012)Google Scholar
  4. 4.
    Samadi, P., Schober, R. Wong, V.W.S.: Optimal energy consumption scheduling using mechanism design for the future smart grid. In: 2011 IEEE International Conference on Smart Grid Communications, pp. 369–374, October 2011Google Scholar
  5. 5.
  6. 6.
    Jager, W., Van der Vegt, G.: Management of complex systems: towards agent based gaming for policy. In: Janssen, M. (ed.) Policy Practice and Digital Science: Integrating Complex Systems, Social Simulation and Public Administration in Policy Research. Springer Science in the Public Administration and Information Technology series edited Christopher G. Reddick (2015)CrossRefGoogle Scholar
  7. 7.
    Rochet, J., Tirol, J.: Platform competition in two-sided markets. J. Eur. Econ. Assoc. 1(4), 990–1029 (2003)CrossRefGoogle Scholar
  8. 8.
    Rochet, J., Tirol, J.: Two-sided markets : a progress report. Rand J. Econ. 37(3), 645–667 (2006)CrossRefGoogle Scholar
  9. 9.
    Sannikov, Y.: A continuous time version of the principal-agent problem. Rev. Econ. J. Stud. 75(3), 957–984 (2008)MathSciNetCrossRefGoogle Scholar
  10. 10.
  11. 11.
    Grimm, V.: Pattern-orinted modeling of agent-based complex systems: lessons from ecology. Science 310, 987–991 (2005)CrossRefGoogle Scholar
  12. 12.
    Delre, S.A., Jager, W., Janssen, M.A.: Diffusion dynamics in small-world networks with heterogeneous consumers. Comput. Math. Organ. Theory 13, 185–202 (2007)CrossRefGoogle Scholar
  13. 13.
    Toivonen, R., Onnela, J.P., Saramaki, J., Hyvonen, J., Kaski, K.: A model for social networks. Balt. Congr. Future Internet Commun. 371(2), 851–860 (2006)Google Scholar
  14. 14.
    Kurahashi, S., Saito, M.: Informative and normative effects using a selective advertisement. SICE J. Control Meas. Syst. Integr. 6(2), 076–082 (2013)CrossRefGoogle Scholar
  15. 15.
    Yang, C., Kurahashi, S., Ono, I., Terano, T.: Pattern-oriented inverse simulation for analyzing social problems: family strategies in civil service examination in imperial China. Adv. Complex Syst. 15(7), 1–21 (2012). 1250038MathSciNetCrossRefGoogle Scholar

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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of TsukubaTokyoJapan

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