Advertisement

New Applications of Multi-Agent System Technologies to Power Systems

  • Chen-Ching Liu
  • Hao Li
  • Yoshifumi Zoka
Part of the Power Systems book series (POWSYS)

Abstract

This chapter provides a state-of-the-art summary of multi-agent system technologies for power system applications. New applications to controlled islanding of power systems and MicroGrid with distributed generations are discussed. A new defense system concept, Strategic Power Infrastructure Defense (SPID), has been developed. Controlled islanding is an important extension of the SPID system and the multi-agent system is a promising technology for implementation of the SPID concept. The University of Washington is also developing the intelligent control system for MicroGrids. In this chapter, the multi-agent technology applications to these two topics are discussed with specific examples.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Lekkas GP, Avouris NM, Papakonstantinou GK, (1995) Development of Distributed Problem Solving Systems for Dynamic Environments. IEEE Trans. on Power Systems, Man, and Cybernetics, vol 25, pp 400–414CrossRefGoogle Scholar
  2. [2]
    Cuppari A, Guida PL, Martelli M, Mascardi V, Zini F (1999) Prototyping Freight Trains Traffic Management Using Multi-Agent Systems. International Conference on Information Intelligence and Systems, pp 646–653Google Scholar
  3. [3]
    Gruer P, Hilaire V, Koukarn A (2001) Multi-Agent Approach to Modelling and Simulation of Urban Transportation Systems. IEEE International Conference on Systems, Man, and Cybernetics, vol 4, pp 2499–2504Google Scholar
  4. [4]
    Jarvis D, Jarvis J, McFarlane D, Lucas A, Ronnquist R (2001) Implementing a Multi-Agent Systems Approach to Collaborative Autonomous Manufacturing Operations. Aerospace Conference, IEEE Proceedings., vol 6 , pp 2803–2811Google Scholar
  5. [5]
    Brennan RW, William O (2000) A Simulation Test-Bed to Evaluate Multi-Agent Control of Manufacturing Systems. Simulation Conference Proceedings, vol 2, pp 1747–1756Google Scholar
  6. [6]
    Ferber J (1999) Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-WesleyGoogle Scholar
  7. [7]
    Grossman RL, Nerode A, Ravn AP, Rischel H (1993) Hybrid Systems. Springer-VerlagCrossRefGoogle Scholar
  8. [8]
    Liu CC, Jung J, Heydt GT, Vittal V, Phadke AG (2000) Conceptual Design of the Strategic Power Infrastructure Defense (SPID) System. IEEE Control System Magazine, Aug., pp 40–52Google Scholar
  9. [9]
    Jung J, Liu CC (2001) Multi-Agent Technology for Vulnerability Assessment and Control. Proceedings, of IEEE Summer Meeting, pp 1287–1292Google Scholar
  10. [10]
    Sutton RS, Barto AG, Williams RJ (1992) Re-Inforcement Learning in Direct Adaptive Optimal Control. IEEE Control System Magazine, April, pp 19–22Google Scholar
  11. [11]
    Sutton R, Barto AG (1998) Reinforcement Learning: An Introduction. MIT PressGoogle Scholar
  12. [12]
    Jung J, Liu CC, Tanimoto SL, Vittal V (2002) Adaptation in Load Shedding Under Vulnerable Operating Conditions. IEEE Trans. on Power Systems, vol 17, Issue 4, pp 1199–1205CrossRefGoogle Scholar
  13. [13]
    You H, Vittal V, Jung J, Liu CC, Amin M, Adapa R (2002) An Intelligent Adaptive Load Shedding Scheme. 14th Power Systems Computation Conference (PSCC), Sevilla, SpainGoogle Scholar
  14. [14]
    Archer BA, Davies JB (2002) System Islanding Considerations for Improving Power System Restoration at Manitoba Hydro. IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2002), vol 1, pp 60–65Google Scholar
  15. [15]
    Agematsu S, Imai S, Tsukui R, Watanabe H, Nakamura T, Matsushima T (2001) Islanding Protection System with Active and Reactive Power Balancing Control for Tokyo Metropolitan Power System and Actual Operational Experiences. Seventh International Conference on (IEE) Developments in Power System Protection, pp 351–354Google Scholar
  16. [16]
    Rajamani K, Hambarde UK (1999) Islanding and Load Shedding Schemes for Captive Power Plants. IEEE Trans. on Power Delivery, vol 14, no 3, pp 805–809CrossRefGoogle Scholar
  17. [17]
    Brooks RA (1991) Intelligent without Reason. Massachusetts Institute of Technology, Artificial Intelligence Journal (47), pp 139–159CrossRefGoogle Scholar
  18. [18]
    (1996) WSCC Disturbance Report for the Power System Outage that Occurred on the Western Interconnection, [Online] http://www.wscc.com
  19. [19]
    Labrou Y, Finin T (2003) A Proposal for a New KQML Specification. University of Maryland. [Online] http://www.cs.umbc.edu/kqmlGoogle Scholar
  20. [20]
    Chiariglione L (1998) FIPA 98 Specification, Foundation for Intelligent Physical Agent. [Online] http://www.cselt.it/fipa/spec/fipa98Google Scholar
  21. [21]
    Hagen L, Kahng AB (1992) New Spectral Methods for Ratio Cut Partitioning and Clustering. IEEE Trans. on Computer-Aided Design of Integrated Circuits and Systems, vol 11, pp 1074–1085CrossRefGoogle Scholar
  22. [22]
    Chan TF, Ciarlet Jr. P, Szeto WK (1997) On the Optimality of the Median Cut Spectral Bisection Graph Partitioning Method. SIAM Journal on Computing, vol 18, no 3, pp 943–948MathSciNetzbMATHCrossRefGoogle Scholar
  23. [23]
    Lasseter R, Akhil A, Marnay C, Stephens J, Dagle J, Guttromson R, Melio-poulous AS, Yinger R, Eto J (2002) Integration of Distributed Energy Resources: The CERTS MicroGrid Concept. White paper prepared for U. S. Department of Energy, California Energy CommissionCrossRefGoogle Scholar
  24. [24]
    Office of Power Technologies (2001) Energy Efficiency and Renewable Energy, Department of Energy. Transmission Reliability Multi-Year Program Plan FY 2001–2005Google Scholar
  25. [25]
    Jenkins N, Allan R, Crossley P, Kirschen D, Strabac G (2000) Embedded Generation. IEE, LondonCrossRefGoogle Scholar
  26. [26]
    Roy S, Malik OP, Hope GS (1991) An Adaptive Control Scheme for Speed Control of Diesel Driven Power-Plants. IEEE Trans. on Energy Conversion, vol 6, no 4, pp 605–611CrossRefGoogle Scholar
  27. [27]
    Stavrakakis GS, Kariniotaks GN (1995) A General Simulation Algorithm for The Accurate Assessment of Isolated Diesel-Wind Turbines Systems Interaction, Part I: A General Multimachine Power System Model. IEEE Trans. on Energy Conversion, vol 10, no 3, pp 577–583CrossRefGoogle Scholar
  28. [28]
    IEEE Committee Report (1973) Dynamic models for Steam and Hydro Turbines. IEEE Trans. on Power Apparatus and Systems, PAS-92, pp 1906–1915Google Scholar
  29. [29]
    Lasseter RH (1998) Control of Distributed Resources. Bulk Power System Dynamics and Control IV — Restructuring, Santorini, GreeceGoogle Scholar
  30. [30]
    Mathworks Co. [Online] http://www.mathworks.com/
  31. [31]
    Kamwa I, Grondin R, Hebert Y (2001) Wide-Area Measurement Based Stabilizing Control of Large Power Systems — A Decentralized/Hierarchical Approach. IEEE Trans. on Power Systems, vol 16, no 1, pp 136–153CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Chen-Ching Liu
    • 1
  • Hao Li
    • 1
  • Yoshifumi Zoka
    • 1
  1. 1.Department of Electrical EngineeringUniversity of WashingtonUSA

Personalised recommendations