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Original Article

Artificial Neural Network Based Transient Stability Assessment of the Benin Sub Regional 330kv Network

  • Paper ID 51
  • Volume 3, Issue 2
  • Pages: 33-37
  • Published Online: May-August 2026
  • 387 Views
Open Access Peer Reviewed

Authors

  • Esene Christopher Akhimien1
  • M.J.E. Evbogbai2
  • H.E. Amhenrior3

1 2 3 Department of Electrical and Electronic Engineering, Edo State University, Iyamho, Edo State, Nigeria.

Article Information

DOI
No Doi
Published Online
May-August 2026
Pages
33-37
Article Type
Original Article
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References

1. Abdel-Magid, I. M., & Abido, M. A. (2004). Application of neural networks for power system stability assessment. Electric Power Systems
Research, 69(2– 3)145–154. https://doi.org/10.1016/j.epsr.2003.11.0072. Anderson, P. M., & Fouad, A. A. (2003). Power system control and stability (2nd ed.). IEEE Press and Related Disorders. 2009;7(3):221–
230
3. Kundur, P. (1994). Power system stability and control. McGraw-Hill.
4. Ogunlade, O., & Adeyemi, O. (2019). Application of ANN for transient stability assessment of Nigerian power system. International
Journal of Electrical Power & Energy Systems, 109, 123–132. https://doi.org/10.1016/j.ijepes.2019.01.007
5. Pai, M. A. (1989). Energy function analysis for power system stability. Kluwer Academic Publishers foundation.Diabetes Care.
2008;31(4):811
6. Sauer, P. W., & Pai, M. A. (1998). Power system dynamics and stability. Prentice Hall.
7. Sobajic, D. J., & Pao, Y. H. (2015). Machine learning techniques for power system stability enhancement. Electric Power Systems
Research, 123, 103–111. https://doi.org/10.1016/j.epsr.2015.02.006
8. Xue, Y., & Pavella, M. (1989). A new method for transient stability assessment of power systems. IEEE Transactions on Power Systems,
4(1), 105–113. https://doi.org/10.1109/59.19216
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