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Artificial Neural Networks Based Power System State Estimation

Manjula S. Sureban*, Shekhappa G. Ankaliki **

*PG. Scholar, Department of Electrical and Electronics Engineering, SDM College of Engineering & Technology, Dharwad, India

** Professor, Department of Electrical and Electronics Engineering, SDM College of Engineering & Technology, Dharwad, India

Periodicity:October - December'2014
DOI : https://doi.org/10.26634/jse.9.2.3323

Abstract

Increased Interconnectlon of the power system along with deregulated structure to satisfy growing demand has brought new challenges for power system state estlmatlon. The estlmatlon of power system stofe [1,3] in such interconnected system has become complex due to comp/exity in modelling and uncertalntles. This makes ANN a ideal candldate for state estimation, since if can accurately map the relationshlp between the measured varlable and other state variables of the power system with reduced computational resources as compared to weighted least square approach[2]. Using only load bus parameters for various operating condifions with an ANN other states of the power system can be accurately estimated. This paper dlscusses an approach to estimate the state of power system using ANN in MATLAB.

Keywords

Keywords. StateEstimation,Neural Networks, BackPropagation Algorithm

How to Cite this Article?

Sureban,M.S., and Ankaliki,S. (2014). Artificial Neural Networks Based Power System State Estimation. i-manager’s Journal on Software Engineering,9(2),9-16. https://doi.org/10.26634/jse.9.2.3323

References

[1]. John J. Groinger, Yonh lorollno, Williom D. Stevenson, Power System Analysis.

[2]. D P Kothori, I J Nogroth, Adjunct. Modern Power System Analysis, Third Edition. Birlo Ins I I I y7" of Technologt and Science, Pilani Tata

3]. Ali Abur, Antonio Gomez Expos/to, Power System State Estimation Theory ond Implemention.

[4]. D. Soxeno, S.N. Singh and K.S. Verma (2010). Application of computational intelligence in emerging power systems, International Journal of Engineering, Science and Technology Vol. 2, No. 3, 2010, pp, 1-7.

[5]. A.D. Dongore, R.R. Khorde, Amit D.Kochore (2012). Introduction to Artificial Neural Network. /International Journal of Engineering and Innovative Technology, Vol.2, Issue 1 .

[6]. Monjulo S. Surebon, S.G. Ankoliki, (2014). "Observability Analysis, stole estimation and bad data detection for power system using measured data," i- manager's Journal on Power Systems Engineering, Vol. 2 No. 3" , Aug-Oct' I 4, Print ISSN 2277-.5 I 10, E-ISSN 2322- 0368, pp, 22-27.

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