Probability-based predictive self-healing reconfiguration for shipboard power systems

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Probability-based predictive self-healing reconfiguration for shipboard power systems

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The electric power systems in US Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. During battle, various weapons may attack a ship causing severe damage to the electrical system on the ship. This damage can lead to de-energisation of critical loads which can eventually decrease a ship's survivability. It is very important therefore to maintain the availability of power to the loads that keep the power system operational. There exists technology for ships that can detect incoming weapons. This knowledge can be used to determine reconfiguration actions which can be taken before the actual hit to reduce the damage to the electrical system when the weapon hits. Then reconfiguration for restoration can be performed after the hit to reconfigure loads de-energised by the damage from the hit. A new automated probabilistic predictive self-healing methodology to determine such reconfiguration control actions is presented. Implementation of these actions will lead to less damage caused by a weapon hit and can considerably improve a ship's chances of surviving an attack. This probabilistic approach entails three major functions: weapon damage assessment, pre-hit reconfiguration before a weapon hit for damage reduction and reconfiguration for restoration after a weapon hit to restore de-energised loads. A case study is presented to illustrate the new methodology.

Inspec keywords: probability; power system control; predictive control; power system restoration; ships

Other keywords: critical load de-energisation; weapon damage assessment; shipboard power systems; automated probabilistic methodology; probability; pre-hit reconfiguration; restoration reconfiguration; US Navy ships; predictive selfhealing reconfiguration

Subjects: Control of electric power systems; Military control systems; Marine system control; Power system management, operation and economics; Optimal control; Transportation; Power system control; Other military topics

References

    1. 1)
      • R.G. Lee , E. Archer , T.K. Garland-Collins , D.E. Johnson , G.M. Moss , A.W. Mowat , C. Sparkes . (1988) Guided weapons.
    2. 2)
      • Zivi, E.L.: `Integrated shipboard power and automation control challenge problem', Proc. 2002 IEEE Power Engineering Society Summer Meeting, 21–25 July 2002, 1, p. 325–330.
    3. 3)
      • Srivastava, S.K.: `Multi-agent system for predictive reconfiguration of shipboard power systems', 2003, PhD., Texas A&M University.
    4. 4)
      • R.M. Lloyd . (1998) Conventional warhead systems physics and engineering design.
    5. 5)
      • `Multilogic, Exsys developer user manual', 1999, version 8.1.9.
    6. 6)
    7. 7)
    8. 8)
      • Rajbhandari, U.P.: `Development of a geographical information system based model of a shipboard power system', 2001, M.S., Texas A&M University.
    9. 9)
    10. 10)
      • D. Emerson . (1980) TSARINA – user's guide to a computer model for damage assessment of complex airbase targets.
    11. 11)
      • Srivastava, S.K., Butler-Purry, K.L.: `A pre-hit probabilistic reconfiguration methodology for shipboard power systems', Proc. 2005 IEEE Electric Ship Technologies Symposium, 25–27 July 2005, Philadelphia, PA, p. 99–104.
    12. 12)
      • Zima, M., Anderson, G.: `Wide area monitoring and control as a tool for mitigation of cascading failures', Proc. 2004 Int. Conf. Probabilistic Methods Applied to Power Systems, Ames, IA, 14–16 September 2004, p. 663–669.
    13. 13)
      • G.M. Clark , D. Cooke . (1998) A basic course in statistics.
    14. 14)
    15. 15)
    16. 16)
      • `Roadmap to an electric naval force', US Naval Research Advisory Committee Report, July 2002.
    17. 17)
      • Butler-Purry, K., Sarma, N.D.R., Xiao, H., Adediran, A., Srivastava, S., Qi, L., Rajbandari, U., Thompson, J.: `Final report– predictive reconfiguration of shipboard power systems', Office of Naval Research Project No. N00014-99-1-0704, August 2003, Texas Engineering Experiment Station.
    18. 18)
      • Baran, M., Mahajan, N.: `System reconfiguration on shipboard DC zonal electrical system', Proc. 2005 IEEE Electric Ship Technologies Symposium, 25–27 July 2005, Philadelphia, PA, p. 86–92.
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