Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4682))

Included in the following conference series:

  • 1745 Accesses

Abstract

Power system small signal stability concerns the ability of the power system to maintain stable subject to small disturbances. The method of frequency-domain analysis, namely the analysis of system eigenstructure, is commonly employed for the study of small signal stability. However, we often face high-order system matrix due to the large number of generating units so that it will be undesirable to calculate and analyze the whole system eigenstructure. The main purpose of this paper is to present an algorithm to find out the eigenvalue of the worst-damped electromechanical mode or the eigenvalues of all unstable electromechanical modes, i.e. to figure out those eigenvalues of critical oscillatory modes. The proposed algorithm takes advantage of the specific feature of the parallel structure of connection networks for calculating the eigenvalues. Numerical results from performing eigenvalue analysis on a sample power system are demonstrated to verify the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, P.M., Fouad, A.A.: Power System Control and Stability. IEEE Press, Los Alamitos (1994)

    Google Scholar 

  2. Kundur, P.: Power System Stability and Control. McGraw-Hill, New York (1994)

    Google Scholar 

  3. Rogers, G.: Power System Oscillations. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

  4. Campagnolom, J.M., Martins, L., Lima, T.G.: Fast Small-Signal Stability Assessment Using Parallel Processing. IEEE Trans. on Power Systems 9, 949–956 (1994)

    Article  Google Scholar 

  5. Angelidis, G., Semlyen, A.: Efficient Calculation of Critical Eigenvalue Clusters in The Small Signal Stability Analysis of Large Power System. IEEE Trans. on Power Systems 10, 427–432 (1995)

    Article  Google Scholar 

  6. Campagnolo, J.M., Martins, N.D., Falcao, M.: An Efficient and Robust Eigenvalue Method for Small-Signal Stability Assessment in Parallel Computers. IEEE Trans. on Power Systems 10, 506–511 (1995)

    Article  Google Scholar 

  7. Lima, T.G., Bezerra, H., Martins, L.: New Methods for Fast Small-Signal Stability Assessment of Large Scale Power System. IEEE Trans. on Power Systems 10, 1979–1985 (1995)

    Article  Google Scholar 

  8. Angelidis, G., Semlyen, A.: Improved Methodologies for the Calculation of Critical Eigenvalues in Small Signal Stability Analysis. IEEE Transactions on Power Systems 11, 1209–1217 (1996)

    Article  Google Scholar 

  9. Makarov, Y.V., Dong, Z.Y., Hill, D.J.: A General Method for Small Signal Stability Analysis. IEEE Trans. on Power Systems 13, 979–985 (1998)

    Article  Google Scholar 

  10. Wang, K.W., Chung, C Y., Tse, C.T., Tsang, K.M.: Multimachine Eigenvalues Sensitivities of Power System Parameters. IEEE Trans.on Power Systems 15, 741–747 (2000)

    Article  Google Scholar 

  11. Gomes, S., Martins, N., Portela, C.: Computing Small-Signal Stability Boundaries for Large-Scale Power Systems. IEEE Trans. on Power Systems 18, 747–752 (2003)

    Article  Google Scholar 

  12. Zhang, X., Shen, C.: A Distributed-computing-based Eigenvalue Algorithm for Stability Analysis of Large-scale Power Systems. In: Proceedings of 2006 International Conference on Power System Technology pp. 1–5 (2006)

    Google Scholar 

  13. Kailath, T.: Linear Systems. Prentice-Hall, Englewood Cliffs (1980)

    MATH  Google Scholar 

  14. Ogata, K.: System Dynamics, 4th edn. Prentice-Hall, Englewood Cliffs (2003)

    Google Scholar 

  15. Oja, E.: A Simplified Neuron Model as a Principle Components Analyzer. Journal of Mathematical Biology 15, 267–273 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  16. Lau, C.: Neural Networks-Theoretical Foundations and Analysis. IEEE Computer Society Press, Los Alamitos (1992)

    Google Scholar 

  17. Li, T.Y.: Eigen-decompositioned Neural Networks for Beaming Estimation. M.Sc. Thesis, National Taiwan Ocean University (1994)

    Google Scholar 

  18. Nauck, D., Klawonn, F., Kruse, R.: Neuro-Fuzzy System. John Wiley & Sons, Chichester (1997)

    Google Scholar 

  19. Haykin, S.: Neural Network. Prentice-Hall, Englewood Cliffs (1999)

    Google Scholar 

  20. Golub, G.H., van Loan, C.F.: Matrix Computations. 2nd edn. The Johns Hopkins University Press (1989)

    Google Scholar 

  21. Goldberg, J.L.: Matrix Theory with Applications. McGraw-Hill, New York (1992)

    Google Scholar 

  22. Datta, B.N.: Numerical Linear Algebra and Applications. Brooks/Cole (1995)

    Google Scholar 

  23. Anton, H., Rorres, C.: Elementary Linear Algebra Application. John Wiley & Sons, Inc, Chichester (2000)

    Google Scholar 

  24. Leon, S.J.: Linear Algebra with Applications, 6th edn. Prentice-Hall, Englewood Cliffs (2002)

    Google Scholar 

  25. Yu, Y.N., Siggers, C.: Stabilization and Optimal Control Signal for Power Systems. IEEE Trans. on Power Apparatus and Systems 90, 1469–1481 (1971)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

De-Shuang Huang Laurent Heutte Marco Loog

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Huang, PH., Li, CC. (2007). Partial Eigenanalysis for Power System Stability Study by Connection Network. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74205-0_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74201-2

  • Online ISBN: 978-3-540-74205-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics