Active Power Rescheduling for Avoiding Voltage Collapse Using Modified Bare Bones Particle Swarm Optimization

Original Contribution

Abstract

MW-generation rescheduling is being considered for voltage stability improvement under stressed operating condition. At times it can avoid voltage collapse. This paper describes an algorithm for determination of optimum MW-generation participation pattern for static voltage stability margin enhancement. The optimum search direction has been obtained by employing modified bare born particle swarm optimization technique. Optimum search direction is based on maximization of distance to point of collapse in generation space. Developed algorithm has been implemented on a standard 25 bus test system. Results obtained have been compared with those obtained using standard particle swarm optimization.

Keywords

Voltage stability Particle swarm optimization Bare bones particle swarm optimization MW-generation rescheduling Loadability 

References

  1. 1.
    A. Tiranuchit, R.J. Thomas, A posturing strategy against voltage instabilities in electric power systems. IEEE Trans. Power Syst. 3(1), 87–93 (1988)CrossRefGoogle Scholar
  2. 2.
    H. Song, B. Lee, S.H. Kwan, V. Ajjarapu, Reactive reserve based contingency constrained optimal power flow (RCCOPF) for enhancement of voltage stability margins. IEEE Trans. Power Syst. 18(4), 1538–1546 (2003)CrossRefGoogle Scholar
  3. 3.
    L.D. Arya, D.K. Sakravdia, D.P. Kothari, Corrective rescheduling for static voltage stability control. Int. J. Electr. Power Energy Syst. 27, 3–12 (2005)CrossRefGoogle Scholar
  4. 4.
    J.G. Vlachogiannis, K.Y. Lee, A comparative study on particle swarm optimization for optimal steady state performance of power system. IEEE Trans. Power Syst. 21(4), 1718–1728 (2006)CrossRefGoogle Scholar
  5. 5.
    L.D. Arya, L.S. Titare, D.P. Kothari, Improved particle swarm optimization applied to reactive power reserve maximization. Int. J. Electr. Power Energy Syst. 32(6), 368–374 (2010)CrossRefGoogle Scholar
  6. 6.
    R.A. Schlueter, A voltage stability security assessment method. IEEE Trans. Power Syst. 13(4), 1423–1431 (1998)CrossRefGoogle Scholar
  7. 7.
    D.S. Kirschen, H.P.V. Meeteren, MW/voltage control in a linear, programming based optimal power flow. IEEE Trans. Power Syst. 3(2), 481–489 (1988)CrossRefGoogle Scholar
  8. 8.
    S.G. Johansson, J.E. Daalder, D. Popovic, D.J. Hill, Avoiding voltage collapse by fast active rescheduling. Int. J. Electr. Power Energy Syst. 19(8), 501–509 (1997)CrossRefGoogle Scholar
  9. 9.
    F. Karbalaei, S. Jadid, M. Kalanter, A Novel method for fast computation of saddle node bifurcation point in power systems using an optimization technique. Int. J. Energy Convers. Manag. 47, 582–589 (2006)CrossRefGoogle Scholar
  10. 10.
    A.A. El-Dib, H.K.M. Yousef, M.M. El-Metwally, Z. Osmon, Maximum loadability of power systems using hybrid particle swarm optimization. Electr. Power Syst. Res. 76, 485–492 (2006)CrossRefGoogle Scholar
  11. 11.
    K. Vishakha, D. Thukaram, L. Jenkins, An approach for real power rescheduling to improve system stability margins under normal and network contingencies. Electr. Power Syst. Res. 71(2), 109–117 (2004)CrossRefGoogle Scholar
  12. 12.
    P. Kessel, H. Glavitsch, Estimating the voltage stability of a power system. IEEE Trans. Power Deliv. 13, 346–354 (1986)CrossRefGoogle Scholar
  13. 13.
    R. Wang, R.H. Lasseter, Re-dispatching generation to increase power system security margin and support low voltage bus. IEEE Trans. Power Syst. 15(2), 496–501 (2006)CrossRefGoogle Scholar
  14. 14.
    R.C. Eberhart, J. Kennedy, in Proceedings of the Sixth International Symposium Micro Machine Human Science, Nagoya, Japan (1995), pp. 39–43Google Scholar
  15. 15.
    J.B. Park, K.S. Lee, J.R. Shin, K.Y. Lee, A particle swarm optimization for economic dispatch with non-smooth costfuctions. IEEE Trans. Power Syst. 20(1), 34–42 (2005)CrossRefGoogle Scholar
  16. 16.
    J. Kennedy, in Proceedings of the IEEE Swarm Intelligence Symposium, pp. 80–87 (2003)Google Scholar
  17. 17.
    G.H.M. Omran, A.P. Engelbrecht, A. Salman, Bare bones differential evolution’. Eur. J. Oper. Res. 196, 128–139 (2009)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    H. Zhang, D.D. Kennedy, G.P. Rangaiah, A.B. Petriciolet, ‘Novel bare-bones particle swarm optimization and its performance for modeling vapour–liquid equilibrium data. Int. J. Fluid Phase Equilib. 301, 30–45 (2011)Google Scholar

Copyright information

© The Institution of Engineers (India) 2015

Authors and Affiliations

  1. 1.Department of Electrical EngineeringAcropolis Technical CampusIndoreIndia
  2. 2.Department of ElectronicsMaharaja Ranjit Singh College of Professional SciencesIndoreIndia

Personalised recommendations