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On the Conception of Intelligent Power Plants Based on Multiple Agent Systems

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Advances in Soft Computing (MICAI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10062))

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Abstract

Lately, great efforts have been made to develop effective hybrid power systems, which consist of a mixture of renewable and conventional power plants, energy storage systems and power consumers. The very dissimilar characteristics of these elements, as well as the ever increasing performance requirements imposed to them, makes the design of control systems for power generation plants a remarkably challenging task. A promising approach to provide effective solutions to this problem is by applying the paradigms of Intelligent Agents and Multi-Agent Systems. In this paper, the definition of an Intelligent Multi-Agent System for Supervision and Control (iMASSC) is proposed to create intelligent power plants for either renewable or conventional power generation units. A Multi-Agent System with a generic structure is used instead of a single specific Intelligent Agent. This approach is more realistic in that it takes into account the complexity of current power plants. Later, the community of intelligent power plants, through autonomous and coherent collaboration, will achieve the objectives of the hybrid power system. Hence, the iMASSC model is expected to provide feasible solutions to the operation of modern intelligent hybrid power systems and smart grids.

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References

  1. Galloway, B.: Introduction to industrial control networks. IEEE Commun. Surv. Tutor. 15(2), 860–880 (2012)

    Article  Google Scholar 

  2. Luger, G., Stubblefield, W.: Artificial intelligence: structures and strategies for complex problem solving (2004)

    Google Scholar 

  3. Van Tan, V., Yoo, D.-S., Yi, M.-J.: A multiagent-system framework for hierarchical control and monitoring of complex process control systems. In: Bui, T.D., Ho, T.V., Ha, Q.T. (eds.) PRIMA 2008. LNCS, vol. 5357, pp. 381–388. Springer, Heidelberg (2008). doi:10.1007/978-3-540-89674-6_42

    Chapter  Google Scholar 

  4. Ward, P.T., Mellor, S.J.: Structured Development for Real-Time Systems, vol. 1–3. Yourdon Press (1985)

    Google Scholar 

  5. Gomma, A.: A software design method for real-time systems. Comm. ACM. 27(9), 938 (1984)

    Article  Google Scholar 

  6. Jennings, N.: Controlling cooperative problem solving in industrial multiagent systems using joint intention. Artif. Intell. 75(2), 195 (1995)

    Article  Google Scholar 

  7. Wooldridge, M.: Agent-based software engineering. IIE Proc. Soft. Eng. 144, 26 (1997)

    Article  Google Scholar 

  8. Knapik, M., Johnson, J.: Developing Intelligent Agents for Distributed Systems: Exploring Architecture Technologies, and Applications. McGraw-Hill, New York (1998)

    Google Scholar 

  9. Wooldridge, M., Weiss, G.: Multi-Agent Systems. The MIT Press, Cambridge (1999)

    Google Scholar 

  10. Ferber, J.: Multi-agent Systems: An Introduction to Artificial Intelligence. Addison-Wesley, Boston (1999)

    Google Scholar 

  11. Sycara, K.P.: Multiagent systems. AI Mag. 19, 79 (1998). Summer

    Google Scholar 

  12. Durfee, E.H., Lesser, V.: Negotiating task decomposition and allocation using partial global planning. Distrib. Artif. Intell. 2, 229 (1989). Morgan Kaufmann

    Article  Google Scholar 

  13. Decker, K.S., Sycara, K.: Intelligent adaptive information agents. J. Intell. Inf. Syst. 9(3), 239 (1997)

    Article  Google Scholar 

  14. Cossentino, M., El Fallah Seghrouchni, A., Winikoff, M. (eds.): EMAS 2013. LNCS (LNAI), vol. 8245. Springer, Heidelberg (2013). doi:10.1007/978-3-642-45343-4

    Google Scholar 

  15. Jennings, N., Sycara, K., Wooldridge, M.: A roadmap for agent research and development. Auton. Agents Multiagent Syst. 1(1), 7–38 (1998)

    Article  Google Scholar 

  16. McArthur, S., Davidson, E., Catterson, V., Dimeas, A., Hatziargyriou, N., Ponci, F., Funabashi, T.: Multi-agent systems for power engineering applications, part i: concepts, approaches and technical challenge. IEEE Trans. Power Systems 22(4), 1743–1752 (2007)

    Article  Google Scholar 

  17. Velasco, J.R., Gonzalez, J.C., Magdalena, L., Iglesias, C.A.: Multiagent-based control systems: a hybrid approach to distributed process control. Control Eng. Pract. 4(6), 839 (1996)

    Article  Google Scholar 

  18. Chakraborty, S., Simões, M.G., Kramer, W.E.: Power Electronics for Renewable and Distributed Energy Systems: A sourcebook of Topologies, Control and Integration. Springer, London (2013). doi:10.1007/978-1-4471-5104-3

    Book  Google Scholar 

  19. Lee, K.Y., Head, J.D., Gomes, J.R., Williams C.S.: Multi-agent system based intelligent distributed control system for power plants. In: IEEE Power and Energy Society General Meeting, pp. 1–7 (2011)

    Google Scholar 

  20. Tolbert, L., Qi, H. and Peng, F., Scalable multi-agent system for real-time electric, power management. In: Power Engineering Society Summer Meeting IEE, vol. 3, pp. 1676–1679 (2001)

    Google Scholar 

  21. Lagorse, J., Paire, D., Miraoui, A.: A multi-agent system for energy management of distributed power sources. Renew. Energy 35(1), 174–182 (2010)

    Article  Google Scholar 

  22. Roche, R., Blunier, B., Miraoui, A., Hilaire, V., Koukam, A.: Multi-agent systems for grid energy management: a short review. In: IECON 2010 36th Annual Conference on IEEE Industrial Electronics Society, pp. 3341–3346. IEEE (2010)

    Google Scholar 

  23. Narkhede, M.S., Chatterji, S., Ghosh, S.: Multi-agent Systems (MAS) controlled smart grid a review. Int. J. Comput. Appl., 0975–8887 (2013)

    Google Scholar 

  24. Khare, A.R., Kumar, B.Y.: Multiagent structures in hybrid renewable power system: a review. J. Renew. Sustain. Energy 7, 063101 (2015)

    Article  Google Scholar 

  25. Ling, Y.: Computational Intelligence in Industrial Application. CRC Press/Balkema, Leiden (2015)

    Book  Google Scholar 

  26. Dimeas, A.L., Hatziargyriou, N.D.: Operation of a multiagent system for microgrid control. IEEE Trans. Power Syst. 20(3), 1447–1455 (2005)

    Article  Google Scholar 

  27. McArthur, S., Davidson, E., Catterson, V., Dimeas, A., Hatziargyriou, N., Ponci, F., Funabashi, T.: 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)

    Article  Google Scholar 

  28. Dimeas, A.L., Hatziargyriou, N.D.: Agent based control for microgrids. In: IEEE Power Engineering Society General Meeting, Tampa, FL, USA, pp. 1–5 (2007)

    Google Scholar 

  29. Chatzivasiliadis, S.J., Hatziargyriou, N.D., Dimeas, A.L.: Development of an agent based intelligent control system for microgrids. In: IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA, USA, pp. 1–6 (2008)

    Google Scholar 

  30. Jian, Z., Qian, A., Chuanwen, J., Xingang, W, Zhanghua, Z., Chenghong, G.: The application of multi agent system in microgrid coordination control. In: International Conference on Sustainable Power Generation and Supply, Nanjing, pp. 1–6 (2009)

    Google Scholar 

  31. Zheng, W., Cai, J.: A multi-agent system for distributed energy resources control in microgrid. In: 5th International Conference on Critical Infrastructure (CRIS), Beijing, China, pp. 1–5 (2010)

    Google Scholar 

  32. Cai, N., Mitras, J.: A decentralized control architecture for a microgrid with power electronic interfaces. In: North American Power Symposium, Arlington, TX, USA, pp. 1–8 (2010)

    Google Scholar 

  33. Kuo, M.T., Lu, S.D.: Design and implementation of real-time intelligent control and structure based on multi-agent systems in microgrids. Energies 6, 6045–6059 (2013)

    Article  Google Scholar 

  34. Kuznetsova, Y., Li, Y., Ruiz, C., Rio, E.: An integrated framework of agent-based modelling and robust optimization for microgrid energy management. Appl. Energy 129, 70–88 (2014)

    Article  Google Scholar 

  35. Wu, Z., Gu, W.: Active power and frequency control of islanded microgrid based on multi-agent technology. Electr. Power Automob. Equip. 11, 57–61 (2009)

    Google Scholar 

  36. Velik, R., Nicolay, P.: A cognitive decision agent architecture for optimal energy management of microgrids. Energy Convers. Manag. 86, 831–847 (2014)

    Article  Google Scholar 

  37. Kantamneni, A., Brown, L.E., Parker, G., Weaver, W.W.: Survey of multi-agent systems for microgrid controls. Eng. Appl. Artif. Intell. 45, 192–203 (2015)

    Article  Google Scholar 

  38. Zambonelli, F., Jennings, N., Wooldridge, M.: Developing multiagent systems: the Gaia methodology. ACM Trans. Softw. Eng. Methodol. (TOSEM) 12(3), 370 (2003)

    Article  Google Scholar 

  39. Philips, L., Link, H., Smith, R., Welland, L.: Agent-based control of distributed infrastructure resources. Technical report, Sandia National Laboratories (2006)

    Google Scholar 

  40. Jimeno, J., Anduaga, J., Oyarzabal, J., de Muro, A.G.: Architecture of a microgrid energy management system. Eur. Trans. Electr. Power 21(2), 1142–1158 (2011)

    Article  Google Scholar 

  41. Rumley, S., Kaegi, E., Rudnick, H., Germond, A.: Multi-agent approach to electrical distribution networks control. In: 32nd Annual IEEE International Computer Software and Applications, CPMPSAC 2008, pp. 575–580, 28 July 2008

    Google Scholar 

  42. James, G., Cohen, D., Dodier R., Platt, G., Palmer, D.: A deployed multi-agent framework for distributed energy applications. In: AAMAS 2006: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 676–678. ACM, New York (2006)

    Google Scholar 

  43. Rahman, S., Pippattanasomporn, M., Teklu, Y.: Intelligent distributed autonomous power systems (IDAPS). In: Power Engineering Society General Meeting, pp. 1–8. IEEE (2007)

    Google Scholar 

  44. Kok, J.K., Scheepers, M.J.J., Kamphuis, I.G.: Intelligence in electricity networks for embedding renewables and distributed generation. In: Negenborn, R., Lukszo, Z., Hellendoorn, H. (eds.) Intelligent Infrastructures. Intelligent Systems, Control and Automation: Science and Engineering, vol. 42, pp. 179–209. Springer, Dordrecht (2010). doi:10.1007/978-90-481-3598-1_8

    Chapter  Google Scholar 

  45. Momoh, J.: Smart Grid, Fundamentals of Design and Analysis. John Wiley & Sons, Inc., Hoboken, New Jersey (2012). El-Hawary, M.E., IEEE Press Series on Power Engineering

    Google Scholar 

  46. Garduno-Ramirez, R., Lee, K.Y.: Intelligent multiagent control for power plants. In: Leondes, C.T. (ed.) Intelligent Systems: Technology and Applications. Control and Electric Power Systems, vol. 6, pp. 181–209. CRC Press, Boca Raton (2002)

    Google Scholar 

  47. Rosenof, H.P., Ghosh, A.: Batch Process Automation: Theory and Practice. Van Nostrand Reinhold, New York (1987)

    Book  Google Scholar 

  48. Albus, J.S.: Outline for a theory of intelligence. IEEE Trans. Syst. Man Cybern. 21(3), 473–509 (1991)

    Article  MathSciNet  Google Scholar 

  49. Saridis, G.N.: Analytic formulation of the principle of increasing precision with decreasing intelligence for intelligent machines. Automatica 25(3), 461–467 (1989)

    Article  MATH  Google Scholar 

  50. Garduno-Ramirez, R.: Fossil-Fuel Power Plant Control: An Intelligent Hybrid Approach. Lambert Academic Publishing, Saarbrücken (2010)

    Google Scholar 

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Acknowledgements

Mónica Borunda wish to thank Consejo Nacional de Ciencia y Tecnologa (CONACYT) for funding her Catedra Research Position (ID 71557), and Instituto Nacional de Electricidad y Energas Limpias (INEEL) as host institution.

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Authors and Affiliations

  1. Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca, Mexico

    Raul Garduno-Ramirez

  2. Conacyt - Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca, Mexico

    Mónica Borunda

Authors
  1. Raul Garduno-Ramirez
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  2. Mónica Borunda
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Correspondence to Raul Garduno-Ramirez .

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Editors and Affiliations

  1. Instituto Politécnico Nacional, Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, México DF, Mexico

    Obdulia Pichardo-Lagunas

  2. INFOTEC Aguascalientes, Aguascalientes, Mexico

    Sabino Miranda-Jiménez

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Garduno-Ramirez, R., Borunda, M. (2017). On the Conception of Intelligent Power Plants Based on Multiple Agent Systems. In: Pichardo-Lagunas, O., Miranda-Jiménez, S. (eds) Advances in Soft Computing. MICAI 2016. Lecture Notes in Computer Science(), vol 10062. Springer, Cham. https://doi.org/10.1007/978-3-319-62428-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-62428-0_8

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