Symphony – Agent-Based Platform for Distributed Smart Grid Experiments

  • Michel A. Oey
  • Zulkuf Genc
  • Elizabeth Ogston
  • Frances M. T. Brazier
Part of the Communications in Computer and Information Science book series (CCIS, volume 430)


The electricity networks in many countries are facing a number of challenges due to growth in peak demand, integration of renewable energy sources, increasing security risks and environmental concerns. Smart Grid, as an automated and widely distributed energy network, offers viable solutions to those challenges. Software agents running on customer premises or embedded in appliances and equipment can be used to plan future energy consumption and to shift loads according to pre-defined constraints. However, testing such distributed solutions prior to actual deployment in domestic households is a challenge. Simulations may not capture all the aspects of distributed, large-scale, complex environments, such as one can find in the Smart Grid. This paper presents a distributed Smart Grid simulation/emulation environment called Symphony that allows running real-world experiments within distributed environment with the participation of multiple actors. Symphony is being developed in the context of a European Institute for Innovation and Technology project.


multi-agent smart-grid distributed AgentScape simulation emulation Symphony experiment platform 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Brazier, F.M., Kephart, J.O., Van Dyke Parunak, H., Huhns, M.N.: Agents and service-oriented computing for autonomic computing: A research agenda. IEEE Internet Computing 13(3), 82–87 (2009)CrossRefGoogle Scholar
  2. 2.
    European Union. European Institute of Innovation & Technology,
  3. 3.
    Gollmann, D.: Computer Security, 3rd edn. Wiley (2011)Google Scholar
  4. 4.
    IIDS. AgentScape Agent Middleware,
  5. 5.
    International Electrotechnical Commission. IEC Standards,
  6. 6.
    James, G., Cohen, D., Dodier, R., Platt, G., Palmer, D.: A deployed multi-agent framework for distributed energy applications. In: Proceedings of the Fifth Int. Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2006, pp. 676–678. ACM, New York (2006)CrossRefGoogle Scholar
  7. 7.
    Ketter, W.: Power Trading Agent Competition,
  8. 8.
    Ketter, W., Collins, J., Reddy, P.: Power tac: A competitive economic simulation of the smart grid. Energy Economics 39, 262–270 (2013)CrossRefGoogle Scholar
  9. 9.
    North, M., Collier, N., Ozik, J., Tatara, E., Macal, C., Bragen, M., Sydelko, P.: Complex adaptive systems modeling with repast simphony. Complex Adaptive Systems Modeling 1(1), 3 (2013)CrossRefGoogle Scholar
  10. 10.
    Oey, M.A., van Splunter, S., Ogston, E.F.Y., Warnier, M., Brazier, F.M.T.: A framework for developing agent-based distributed applications. In: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2010), pp. 470–474. IEEE Press, Washington, DC (2010)CrossRefGoogle Scholar
  11. 11.
    Ogston, E., Brazier, F.: Apportionment of control in virtual power stations. In: 2009 Second Int. Conference on Infrastructure Systems and Services: Developing 21st Century Infrastructure Networks (INFRA), pp. 1–6 (December 2009)Google Scholar
  12. 12.
    Ogston, E.F.Y., Brazier, F.M.T.: Agentscope: Multi-agent systems development in focus. In: Tenth Int. Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011), Taipei, Taiwan, pp. 389–396. IFAAMAS (May 2011)Google Scholar
  13. 13.
    Overeinder, B.J., Brazier, F.M.T.: Scalable middleware environment for agent-based internet applications. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds.) PARA 2004. LNCS, vol. 3732, pp. 675–679. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Pipattanasomporn, M., Feroze, H., Rahman, S.: Multi-agent systems in a distributed smart grid: Design and implementation. In: IEEE/PES Power Systems Conference and Exposition, PSCE 2009, pp. 1–8 (March 2009)Google Scholar
  15. 15.
    Pournaras, E., Warnier, M., Brazier, F.M.T.: A distributed agent-based approach to stabilization of global resource utilization. In: The International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2009). IEEE (March 2009)Google Scholar
  16. 16.
    Repast Development Team. The repast suite,
  17. 17.
    Seventh Framework Research Programme of the European Commission (FP7). CASSANDRA,
  18. 18.
    Tesauro, G., Chess, D.M., Walsh, W.E., Das, R., Segal, A., Whalley, I., Kephart, J.O., White, S.R.: A multi-agent systems approach to autonomic computing. In: Proceedings of the Third Int. Joint Conference on Autonomous Agents and Multiagent Systems. AAMAS 2004, vol. 1, pp. 464–471. IEEE Computer Society, Washington, DC (2004)Google Scholar
  19. 19.
    Tisue, S., Wilensky, U.: Netlogo: A simple environment for modeling complexity. In: International Conference on Complex Systems, pp. 16–21 (2004)Google Scholar
  20. 20.
    Wijngaards, N.J.E., Overeinder, B.J., van Steen, M., Brazier, F.M.T.: Supporting internet-scale multi-agent systems. Data and Knowledge Engineering 41(2-3), 229–245 (2002)CrossRefzbMATHGoogle Scholar
  21. 21.
    Wilensky, U.: NetLogo and NetLogo User Manual (1999),

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michel A. Oey
    • 1
  • Zulkuf Genc
    • 1
  • Elizabeth Ogston
    • 1
  • Frances M. T. Brazier
    • 1
  1. 1.Delft University of TechnologyThe Netherlands

Personalised recommendations