Artificial Neural Network Based Power System Stability Analysis

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 150)

Abstract

In this paper, an Artificial Neural Network (ANN) approach for the analysis of a power system stability has been proposed and proved to be effective. Here the main consideration is the power system voltage stability i.e. static voltage stability. With instance of 9-Bus [3] power system, also worked on IEEE-57 Bus [4] system and it is verified that the method is effective for power system voltage stability assessment.[3, 4, 8] The implementation of these structures is shown through Mat lab and by the use of ANN approach [5, 6] and the above two methods are compared for the test system. The network would be a useful tool to assess power system voltage stability quickly.

Keywords

ANN Power system voltage stability VCPI Newton–Raphson method Load flow BP neural network 

References

  1. 1.
    Han X, Zheng Z Voltage stability assessment based on BP neural network. Nannan TIAN College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan ChinaGoogle Scholar
  2. 2.
    Kessel P, Glavitch H (1986) Estimating the voltage stability of power systems. IEEE Trans Power Deliv 1(3):346354CrossRefGoogle Scholar
  3. 3.
    Subramani C, Sekhar Dash S, Jagadeesh kumar M (2009) Voltage stability based collapse prediction and weak cluster identification. Int J Electr Power Eng 3(2):124–128Google Scholar
  4. 4.
    Kamalasadan S, Srivastava AK, Thukaram D (2006) Novel algorithm for online voltage stability assessment based on feed forward neural network. 2006 IEEEGoogle Scholar
  5. 5.
    Chen D, Mohler RR (2003) Neural-network-based load modeling and its use in voltage stability analysis. IEEE Trans Control Sys Technol 11(4):460–470Google Scholar
  6. 6.
    Chen X, Guang PX (2003) Artificial Neural network technology and its application. China Electric Power Press, BeijingGoogle Scholar
  7. 7.
    Shuangxi Z, Lingzhi Z, Xijiu G, Xiaohai W (2003) The voltage stability and its controlling of power system. China Electric Power Press, BeijingGoogle Scholar
  8. 8.
    Salama MM, Ebtsam MS et al (2001) Estimating the voltage collapse proximity indicator using artificial neural network. Energy Convers Manage 42:6979Google Scholar
  9. 9.
    Abdul Rehman M, Musirin I, Othman MM (2008) Evolutionary programming based technique for secure operating point identification in static voltage stability assessment. J Artif Intell 1(1):12–20Google Scholar
  10. 10.
    Anderson PM, Fouad AA (2003) Power system control and stability, 2nd edn. IEEE PressGoogle Scholar
  11. 11.
    Tamura Y, Mori H, Iwamoto S (1983) Relationship between voltage instability and multiple load flow solutions in electric power systems. IEEE Trans Power Apparat Sys PAS-102:5Google Scholar
  12. 12.
    Jarjis J, Galiana FD (1981) Quantitative analysis of steady state stability in power networks. IEEE Trans Power Apparat Sys PAS-100:1Google Scholar
  13. 13.
    Martin T, Howard B, Demuth MH, Beale H (1996) Neural networks design. PWS pub, pp 170–178Google Scholar
  14. 14.
    Simon H (2004) Neural networks a comprehensive foundation. Pearson Education, India pp 30–35Google Scholar
  15. 15.
    Dinavahi VR, Srivastava SC (2001) ANN based voltage stability margin prediction. IEEE PES Summer Meet 2001 2:1275–1280Google Scholar
  16. 16.
    Charabarti S, Jeyasurya B (2004) On-Line voltage stability monitoring using artificial neural network. Large engineering system conference on power engineering, 2004, LESCOPE 2004, pp 71–75Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringG.M.R. Institute Of TechnologyRajamIndia

Personalised recommendations