i-manager Publications

AI Based Static Security Assessment of Power System

N. Aishwarya *, Shekhappa G. Ankaliki **

*-** Department of Electrical and Electronics Engineering, SDM college of Engineering and Technology, Dharwad, Karnataka, India.

Periodicity:May - July'2020
DOI : https://doi.org/10.26634/jps.8.2.17629

Abstract

Contingency selection and ranking using fast and accurate method has become a main issue to ensure the secured operation of power systems. This work proposes multi-layer feed forward artificial neural network (MLFFN) and radial basis function network (RBFN) to demonstrate the static security assessment. In this, the composite security index which is capable of accurately differentiating the secure and insecure cases of power system based on contingency selection, and ranking are done. For each contingency in power system, the composite security index is computed using conventional Newton-Raphson load flow analysis. The MLFFN and RBFN takes all possible loading conditions and probable contingencies as input and assess the system security by screening the credible contingencies and ranking them in the order of severity based on composite security index. The proposed approach is demonstrated by considering the IEEE 30 Bus system using MATLAB simulation.

Keywords

Security Index, Contingency Screening and Ranking, Multi-Layer Feed Forward Neural Network, Static Security Assessment, Radial Basis Function Network.

How to Cite this Article?

Aishwarya, N., and Ankaliki, S. G. (2020). AI Based Static Security Assessment of Power System. i-manager's Journal on Power Systems Engineering, 8(2), 16-23. https://doi.org/10.26634/jps.8.2.17629

References

[1]. Balu, N., Bertram, T., Bose, A., Brandwajn, V., Cauley, G., Curtice, D., ... Wrubel, J. N. (1992). On-line power system security analysis. Proceedings of the IEEE, 80(2), 262-282. https://doi.org/10.1109/5.123296

[2]. Kalyani, S., & Swarup, K. S. (2013). Static security assessment in power systems using multi-class SVM with parameter selection methods. International Journal of Computer Theory and Engineering, 5(3), 465-471.

[3]. Li, Y., Li, Y., & Sun, Y. (2018). Online static security assessment of power systems based on lasso algorithm. Applied Sciences, 8(9), 1442-1466. https://doi.org/10.3390 /app8091442

[4]. Morison, K. (2002, July). Power system security in the new market environment: Future directions. In IEEE Power Engineering Society Summer Meeting (Vol. 3, pp. 1416- 1417). IEEE.

[5]. Morison, K., Wang, L., & Kundur, P. (2004). Power system security assessment. IEEE Power and Energy Magazine, 2(5), 30-39.

[6]. Nara, K., Tanaka, K., Kodama, H., Shoults, R. R., Chen, M. S., Van Olinda, P., & Bertagnolli, D. (1985). On-line contingency selection algorithm for voltage security analysis. IEEE Transactions on Power Apparatus and Systems, 4, 846-856. https://doi.org/10.1109/TPAS.1985. 319085

[7]. Sekhar, P., & Mohanty, S. (2016). An online power system static security assessment module using multi-layer perceptron and radial basis function network. International Journal of Electrical Power & Energy Systems, 76, 165-173. https://doi.org/10.1016/j.ijepes.2015.11.009

[8]. Sidhu, T. S., & Cui, L. (2000). Contingency screening for steady-state security analysis by using FFT and artificial neural networks. IEEE Transactions on Power Systems, 15(1), 421-426. https://doi.org/10.1109/59.852154

[9]. Song, H. (2006, May). Static analysis of vulnerability and security margin of the power system. In 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition (pp. 147-152). IEEE. https://doi.org/10.1109/TDC.2006.166 8474

[10]. Srivani, J., & Swarup, K. S. (2008). Power system static security assessment and evaluation using external system equivalents. International Journal of Electrical Power & Energy Systems, 30(2), 83-92.

[11]. Sunitha, R., Kumar, R. S., & Abraham, T. M. (2009, January). Development of a composite security index for static security evaluation. In TENCON 2009-2009 IEEE Region 10 Conference (pp. 1-6). IEEE. https://doi.org/10.1 109/TENCON.2009.5396229

[12]. Sunitha, R., Kumar, R. S., & Mathew, A. T. (2011). A composite security index for on-line steady-state security evaluation. Electric Power Components and Systems, 39(1), 1-14. https://doi.org/10.1080/15325008.2010. 492448

[13]. Sunitha, R., Kumar, R. S., & Mathew, A. T. (2013). Online static security assessment module using artificial neural networks. IEEE Transactions on Power Systems, 28(4), 4328- 4335. https://doi.org/10.1109/TPWRS.2013.2267557

AI Based Static Security Assessment of Power System

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content:

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25