International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Power System Sensitivity Analysis for Probabilistic Small Signal Stability Assessment in a Deregulated Environment

  • Dong Zhao Yang (School of Information Technology and Electrical Engineering, The University of Queensland) ;
  • Pang Chee Khiang (Department of Electrical and Computer Engineering, National University of Singapore) ;
  • Zhang Pei (Electric Power Research Institute (EPRI))
  • Published : 2005.06.01
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Abstract

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

Keywords

References

  1. R. C. Burchett and G. T. Heydt, 'Probabilistic methods for power system dynamic stability studies,' IEEE Trans. Power App. and Sys., vol. PAS-97, no. 3, pp. 695-702, May/June 1978
  2. F. L. Pagola, I. J. Perez-Arriaga, and G. C. Verghese, 'On sensitivities, residues and participations: applications to oscillatory stability analysis and control,' IEEE Trans. on Power Systems, vol. 4, no. 1, pp. 278-285, February 1989
  3. . E. Van Ness and J. M. Boyle, 'Sensitivities of Large Multiple-Loop Control Systems,' IEEE Trans. on Automatic Control, vol. AC-IO, pp. 308-315, 1965
  4. K. W. Wang, C. Y. Chung, C. T. Tse, and K. M. Tsang, 'Improved probabilistic method for power system dynamic stability studies,' IEE Proceedings-Generation, Transmission and Distribution, vol. 147, no. I, pp. 37-43, January 2000
  5. K. W. Wang, C. T. Tse, X. Y. Bian, and A. K. David, 'Probabilistic eigenvalue sensitivity analysis and PSS design in multimachine systems,' IEEE Trans. on Power Systems, vol. 18, no. 1, pp. 1439-1445, November 2003
  6. E. Chiado, F. Gagliardi, and D. Lauria, 'Probabilistic approach to transient stability evaluation,' IEE Proceedings-Generation, Transmission and Distribution, vol. 141, no. 5, pp. 537-544, September 1994
  7. G. J. Anders, Probability Concepts in Electric Power Systems, John Wiley & Sons, 1990
  8. P. Kundur, Power System Stability and Control, McGraw-Hill, 1994
  9. Y. V. Makarov and Z. Y. Dong, Eigenvalues and Eigenfunctions, vol. Computational Science & Engineering, Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, 1998
  10. IEEE Committee Report, 'Dynamic models for steam and hydro turbines in power system studies,' IEEE Trans. on Power App. Sys., vol. 92,no.6,pp. 1904-1915, 1973
  11. H. Cramer, Mathematical Methods of Statistics, Princeton University Press, 1966
  12. M. G. Kendall, 'Proof of relations connected with the tetrachoric series and its generalization,' Biometrika, vol. 32, no. 2, pp. 196-198, October 1941
  13. A. Papoulis, Probability, Random Variables and Stochastic Processes, McGraw-Hill, 1984
  14. A. Saltelli, K. Chan, and E. M. Scott, Sensitivity Analysis, John Wiley & Sons, 2000