Analysing the Impact of Rationality on the Italian Electricity Market

  • Sara Bevilacqua
  • Célia da Costa PereiraEmail author
  • Eric Guerci
  • Frédéric Precioso
  • Claudio Sartori
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11676)


We analyze the behavior of the Italian electricity market with an agent-based model. In particular, we are interested in testing the assumption that the market participants are fully rational in the economical sense. To this aim, we extend a previous model by considering a wider class of cases. After checking that the new model is a correct generalization of the existing model, we compare three optimization methods to implement the agents rationality and we verify that the model exhibits a very good fit to the real data. This leads us to conclude that our model can be used to predict the behavior of this market.


  1. 1.
    Betrò, B., Cugiani, M., Schoen, F.: Monte Carlo Methods in Numerical Integration and Optimization. Applied Mathematics Monographs CNR. Giardini, Pisa (1990)Google Scholar
  2. 2.
    Ela, E., et al.: Electricity markets and renewables. IEEE Power Energy Mag. 15(27), 1540–7977 (2015)Google Scholar
  3. 3.
    Faia, R., Pinto, T., Vale, Z.A.: GA optimization technique for portfolio optimization of electricity market participation. In: 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, Athens, Greece, 6–9 December 2016, pp. 1–7 (2016)Google Scholar
  4. 4.
    Giulioni, G., Hernández, C., Posada, M., López-Paredes, A. (eds.): Artificial Economics: The Generative Method in Economics. Lecture Notes in Economics and Mathematical Systems, vol. 631, 1st edn. Springer, Berlin (2009). Scholar
  5. 5.
  6. 6.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley, Reading (1989)zbMATHGoogle Scholar
  7. 7.
    Guerci, E., Rastegar, M.A., Cincotti, S.: Agent-based modeling and simulation of competitive wholesale electricity markets. In: Rebennack, S., Pardalos, P.M., Pereira, M.V.F., Iliadis, N.A. (eds.) Handbook of Power Systems II. Energy Systems, pp. 241–286. Springer, Berlin (2010). Scholar
  8. 8.
    Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)Google Scholar
  9. 9.
    Kennedy, J.: Particle swarm optimization. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 967–972. Springer, Boston (2017). Scholar
  10. 10.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Part IV, pp. 1942–1948 (1995)Google Scholar
  11. 11.
    Pinto, T., Morais, H., Oliveira, P., Vale, Z., Praça, I., Ramos, C.: A new approach for multi-agent coalition formation and management in the scope of electricity markets. Energy 36(8), 5004–5015 (2011)CrossRefGoogle Scholar
  12. 12.
    Santos, G., Pinto, T., Praça, I., Vale, Z.: Mascem: optimizing the performance of a multi-agent system. Energy 111((Supplement C)), 513–524 (2016)CrossRefGoogle Scholar
  13. 13.
    Silva, F., Teixeira, B., Pinto, T., Santos, G., Praça, I., Vale, Z.: Demonstration of realistic multi-agent scenario generator for electricity markets simulation. In: Demazeau, Y., Decker, K.S., Bajo Pérez, J., de la Prieta, F. (eds.) PAAMS 2015. LNCS (LNAI), vol. 9086, pp. 316–319. Springer, Cham (2015). Scholar
  14. 14.
    Sioshansi, F.P.: Evolution of Global Electricity Markets: New Paradigms, New Challenges, New Approaches. Academic Press (2013) CrossRefGoogle Scholar
  15. 15.
    Tribbia, C.: Solving the italian electricity power exchange (2015)Google Scholar
  16. 16.
    Urieli, D.: Autonomous trading in modern electricity markets. AI Matters 2(4), 18–19 (2016)CrossRefGoogle Scholar
  17. 17.
    Urieli, D., Stone, P.: Autonomous electricity trading using time-of-use tariffs in a competitive market. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 12–17 February 2016, Phoenix, Arizona, USA, pp. 345–352 (2016)Google Scholar
  18. 18.
    Vytelingum, P., Ramchurn, S.D., Voice, T., Rogers, A., Jennings, N.R.: Trading agents for the smart electricity grid. In: AAMAS, pp. 897–904. IFAAMAS (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sara Bevilacqua
    • 1
  • Célia da Costa Pereira
    • 2
    Email author
  • Eric Guerci
    • 3
  • Frédéric Precioso
    • 2
  • Claudio Sartori
    • 1
  1. 1.Università di BolognaBolognaItaly
  2. 2.Université Côte d’Azur, CNRS, I3S LabSophia AntipolisFrance
  3. 3.Université Côte d’Azur, CNRS - GREDEGSophia AntipolisFrance

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