Average Voltage and Multilayer Perceptron Neural Network Based Scheme to Predict Transient Stability Status

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Emmanuel Asuming Frimpong
Philip Okyere
Johnson Asumadu

Keywords

Abstract

This paper presents a technique that predicts the transient stability status of a power system after a disturbance. It uses generator bus voltage as input parameter and a trained single-input multilayer perceptron neural network (MLPNN) as decision tool. When activated, the scheme samples voltages of all generator buses. Two sets of voltage values are extracted from each sampled generator bus voltage. For each set, the minimum voltage value is obtained. An average value is computed from the minimum voltage values extracted from the first sample sets of the various generator buses. The average value is then used to compute the deviations of the minimum voltage values from the second sets of data. The deviations are then summed and used as input to a trained MLPNN which indicates the stability status. The technique was tested using the IEEE 39-bus test system and its accuracy found to be 98.97%.

References

[1] K. N. Al-Tallaq and E. A. Feilat, "Online detection of out-of-step operation based on prony analysis-impedance relaying", Proceedings of the 5th WSEAS International Conference on Power Systems and Electromagnetic Compatibility, pp. 55-60, 2005.

[2] P.A. Trodden, W. A. Bukhsh, A. Grothey and K.I.M. McKinnon, "MILP islanding of power networks by bus splitting", Proceedings of IEEE Power and Energy Society General Meeting, 2012.

[3] P. Kundur et al., "Definition and classification of power system stability", IEEE Transactions on Power Systems, vol. 26, no. 2, pp. 1387-1400, 2004.

[4] N. Amjady and S. F. Majedi, "Transient stability prediction by a hybrid intelligent system", IEEE Transaction on Power Systems, vol. 22, no. 3, pp. 1275 -1283, 2007.

[5] E. A. Frimpong, P. Y. Okyere and J. A. Asumadu, "Neural Network and Speed Deviation Based Generator Out-Of-Step Prediction Scheme". Journal of Electrical and Electronic Engineering, vol. 15, no. 2, pp. 1-8, 2015.

[6] D. R. Gurusinghe and A. D. Rajapakse, "Post-Disturbance Transient Stability Status Prediction Using Synchrophasor Measurements", IEEE Transactions on Power Systems, vol. 31, no. 5, pp. 3656-3664, 2016.

[7] Y. Zhou, J. Wu, Z. Yu, L. Ji and L. Hao. "A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier", Energies, vol. 9, pp. 1-20, 2016.

[8] A. N. AL-Masri, M. Z. A. A. Kadir, H. Hizam and N. Mariun, "A Novel Implementation for Generator Rotor Angle Stability Prediction Using an Adaptive Artificial Neural Network Application for Dynamic Security Assessment”, IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2516-2525, 2013.

[9] A. D. Rajapakse, F. Gomez, O. M. K. K. Nanayakkara, P. A. Crossley and V. V. Terzija, "Rotor angle stability prediction using post-disturbance voltage trajectory patterns", IEEE Transactions on Power Systems, vol. 25, no. 2, pp. 945-956, 2010.

[10] D. Hou, "Relay Element Performance During Power, System Frequency Excursions", Proceedings of 61st Annual Conference for Protective Relay Engineers, College Station, Texas, 2008.
[11] Power System Simulator for Engineers, PSS®E University Edition, 2016.

[12] A. N. Fathian and M. R. Gholamian, “Using MLP and RBF Neural Networks to Improve the Prediction of Exchange Rate Time Series with ARIMA", International Journal of Information and Electronics Engineering, vol. 2, no. 4, pp. 543-546, 2012.

[13] H. Memarian and S. K. Balasundram, "Comparison between Multi-Layer Perceptron and Radial Basis Function Networks for Sediment Load Estimation in a Tropical Watershed", Journal of Water Resource and Protection, vol. 4, pp. 870-876, 2012.

[14] E.A. Frimpong, "Prediction of Transient Stability Status and Coherent Generator Groups". PhD, Department of Electrical and Electronic Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, 2015.

[15] Y. Song, "Design of Secondary Voltage and Stability Controls with Multiple Control Objectives", PhD, School of Electrical and Computer Engineering, Georgia Institute of Technology, Georgia, 2009.

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