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A Model Driven Methodology for Developing Multi Agent Solutions for Energy Systems

  • Lamia Ben Romdhane
  • Hassan A. Sleiman
  • Saadia Dhouib
  • Chokri Mraidha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10767)

Abstract

The complexity and intelligence of energy systems has increased in the recent years, whereas using Multi-agent Systems (MAS) has been recommended by IEEE for developing software solutions for modeling, controlling, and simulating their behaviors. Existing proposals on MAS solutions for energy systems proposed ad-hoc solutions for resolving specific problems, without considering interoperability and reusability. We propose a methodology, based on the Model-Driven Engineering (MDE) technique, for developing MAS solutions for energy systems. Our methodology uses the Common Information Model standard (CIM), recommended by IEEE, and the existing Platform Independent agent metamodel PIM4Agents. The proposed methodology allows modeling MAS solutions for power engineering applications, by means of a platform-independent model that abstracts developers from existing agent-oriented methodologies and platforms. Applying model transformations, the generated models can be transformed and executed within several agent platforms such as JACK and JADE. Our proposal has been validated by means of a well-known test case from the literature.

Keywords

Energy systems Model Driven Engineering Multi-agent system IEC common information model 

References

  1. 1.
    JACK Intelligent Agents: The agent oriented software group (AOS) (2006)Google Scholar
  2. 2.
    Amor, M., Fuentes, L., Vallecillo, A.: Bridging the gap between agent-oriented design and implementation using MDA. In: Odell, J., Giorgini, P., Müller, J.P. (eds.) AOSE 2004. LNCS, vol. 3382, pp. 93–108. Springer, Heidelberg (2005).  https://doi.org/10.1007/978-3-540-30578-1_7CrossRefGoogle Scholar
  3. 3.
    Bellifemine, F., Poggi, A., Rimassa, G.: JADE-A FIPA-compliant agent framework. In: Proceedings of PAAM, London, vol. 99, p. 33 (1999)Google Scholar
  4. 4.
    Bernon, C., Cossentino, M., Gleizes, M.-P., Turci, P., Zambonelli, F.: A study of some multi-agent meta-models. In: Odell, J., Giorgini, P., Müller, J.P. (eds.) AOSE 2004. LNCS, vol. 3382, pp. 62–77. Springer, Heidelberg (2005).  https://doi.org/10.1007/978-3-540-30578-1_5CrossRefGoogle Scholar
  5. 5.
    Bernon, C., Gleizes, M.-P., Peyruqueou, S., Picard, G.: ADELFE: a methodology for adaptive multi-agent systems engineering. In: Petta, P., Tolksdorf, R., Zambonelli, F. (eds.) ESAW 2002. LNCS (LNAI), vol. 2577, pp. 156–169. Springer, Heidelberg (2003).  https://doi.org/10.1007/3-540-39173-8_12CrossRefzbMATHGoogle Scholar
  6. 6.
    Beydoun, G., et al.: FAML: a generic metamodel for MAS development. IEEE Trans. Softw. Eng. 35(6), 841–863 (2009)CrossRefGoogle Scholar
  7. 7.
    Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., Mylopoulos, J.: Tropos: an agent-oriented software development methodology. Auton. Agents Multi-Agent Syst. 8(3), 203–236 (2004)CrossRefGoogle Scholar
  8. 8.
    Cossentino, M., Potts, C.: A case tool supported methodology for the design of multi-agent systems. In: International Conference on Software Engineering Research and Practice (SERP 2002) (2002)Google Scholar
  9. 9.
    Gérard, S., Dumoulin, C., Tessier, P., Selic, B.: 19 Papyrus: a UML2 tool for domain-specific language modeling. In: Giese, H., Karsai, G., Lee, E., Rumpe, B., Schätz, B. (eds.) MBEERTS 2007. LNCS, vol. 6100, pp. 361–368. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-16277-0_19CrossRefGoogle Scholar
  10. 10.
    Gungor, V.C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., Hancke, G.P.: Smart grid technologies: communication technologies and standards. IEEE Trans. Ind. Inform. 7(4), 529–539 (2011)CrossRefGoogle Scholar
  11. 11.
    Hahn, C., Madrigal-Mora, C., Fischer, K.: A platform-independent metamodel for multiagent systems. Auton. Agents Multi-Agent Syst. 18(2), 239–266 (2009)CrossRefGoogle Scholar
  12. 12.
    Hernandez, L., et al.: A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Commun. Mag. 51(1), 106–113 (2013)CrossRefGoogle Scholar
  13. 13.
    Kleppe, A.G., Warmer, J.B., Bast, W.: MDA Explained: the Model Driven Architecture: Practice and Promise. Addison-Wesley Professional, Reading (2003)Google Scholar
  14. 14.
    Koritarov, V.S.: Real-world market representation with agents. IEEE Power Energy Mag. 2(4), 39–46 (2004)CrossRefGoogle Scholar
  15. 15.
    Kravari, K., Bassiliades, N.: A survey of agent platforms. J. Artif. Soc. Soc. Simul. 18(1), 11 (2015)CrossRefGoogle Scholar
  16. 16.
    Kremers, E.A.: Modelling and Simulation of Electrical Energy Systems Through a Complex Systems Approach using Agent-Based Models. KIT Scientific Publishing, Karlsruhe (2013)Google Scholar
  17. 17.
    Logenthiran, T., Srinivasan, D., Shun, T.Z.: Demand side management in smart grid using heuristic optimization. IEEE Trans. Smart Grid 3(3), 1244–1252 (2012)CrossRefGoogle Scholar
  18. 18.
    McArthur, S.D., et al.: Multi-agent systems for power engineering applications–Part I: concepts, approaches, and technical challenges. IEEE Trans. Power Syst. 22(4), 1743–1752 (2007)CrossRefGoogle Scholar
  19. 19.
    McArthur, S.D.: Multi-agent systems for power engineering applications–Part II: technologies, standards, and tools for building multi-agent systems. IEEE Trans. Power Syst. 22(4), 1753–1759 (2007)CrossRefGoogle Scholar
  20. 20.
    McMorran, A.W.: An introduction to IEC 61970–301 & 61968–11: The common information model. vol. 93, p. 124. University of Strathclyde (2007)Google Scholar
  21. 21.
    O’Brien, P.D., Nicol, R.C.: FIPA–towards a standard for software agents. BT Technol. J. 16(3), 51–59 (1998)CrossRefGoogle Scholar
  22. 22.
    Pavón, J., Gómez-Sanz, J., Fuentes, R.: Model driven development of multi-agent systems. In: Rensink, A., Warmer, J. (eds.) ECMDA-FA 2006. LNCS, vol. 4066, pp. 284–298. Springer, Heidelberg (2006).  https://doi.org/10.1007/11787044_22CrossRefGoogle Scholar
  23. 23.
    Pipattanasomporn, M., Feroze, H., Rahman, S.: Multi-agent systems in a distributed smart grid: design and implementation. In: Power Systems Conference and Exposition, PSCE 2009, pp. 1–8. IEEE/PES (2009)Google Scholar
  24. 24.
    Romdhane, L.B., Sleiman, H.A., Mraidha, C., Dhouib, S.: Multi-agent solutions for energy systems: a model driven approach. In: 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 1–4, September 2017Google Scholar
  25. 25.
    Schmidt, D.C.: Model-driven engineering. Comput. IEEE Comput. Soc. 39(2), 25 (2006)CrossRefGoogle Scholar
  26. 26.
    Uslar, M., Specht, M., Rohjans, S., Trefke, J., González, J.M.: The Common Information Model CIM: IEC 61968/61970 and 62325-A practical introduction to the CIM. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-25215-0CrossRefGoogle Scholar
  27. 27.
    Wooldridge, M., Jennings, N.R.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995)CrossRefGoogle Scholar
  28. 28.
    Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia methodology for agent-oriented analysis and design. Auton. Agents Multi-Agent Syst. 3(3), 285–312 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.CEA, LIST, Laboratory of Data Analysis and Systems’ IntelligenceGif-sur-YvetteFrance
  2. 2.CEA, LIST, Laboratory of Model Driven Engineering for Embedded SystemsGif-sur-YvetteFrance

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