International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 5, No. 10, 8 Sep. 2013
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Transient Stability Assessment using Decision Trees and Fuzzy Logic Techniques
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Author(s)
Index Terms
Transient Stability, Artificial Intelligence, Inductive Inference, Decision Trees, Fuzzy Logic
Abstract
Many techniques are used for Transient Stability assessment (TSA) of synchronous generators encompassing traditional time domain state numerical integration, Lyapunov based methods, probabilistic approaches and Artificial Intelligence (AI) techniques like pattern recognition and artificial neural networks.
This paper examines another two proposed artificial intelligence techniques to tackle the transient stability problem. The first technique is based on the Inductive Inference Reasoning (IIR) approach which belongs to a particular family of machine learning from examples. The second presents a simple fuzzy logic classifier system for TSA. Not only steady state but transient attributes are used for transient stability estimation so as to reflect machine dynamics and network changes due to faults.
The two techniques are tested on a standard test power system. The performance evaluation demonstrated satisfactory results in early detection of machine instability. The advantage of the two techniques is that they are straightforward and simple for on-line implementation.
Cite This Paper
A. Y. Abdelaziz, M. A. El-Dessouki, "Transient Stability Assessment using Decision Trees and Fuzzy Logic Techniques", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.10, pp.1-10, 2013. DOI:10.5815/ijisa.2013.10.01
Reference
[1]H. W. Dommel and N. Sato, “Fast Transient Stability Solutions”, IEEE Transactions on Power Apparatus and Systems, Vol. PAS-91, July/August 1972, pp. 1643-1650.
[2]A. A. Fouad, and S. E. Stanton, “Transient Stability of a Multi-machine Evaluation Power System”, Part I, II , IEEE Transactions on Power Apparatus and Systems, Vol. 100, No. 7, July 1981, pp. 3408-3424.
[3]R. Billiniton and P. R. S. Kuruganty, “Probabilistic Assessment of Transient Stability in a Practical Multimachine System”, IEEE Transactions on Power Apparatus and Systems, Vol. PAS-100, No. 7, July 1981, pp. 3634-3641.
[4]H. Hakimmashhadi, “Fast Transient Security Assessment”, Ph. D. Thesis, Purdue University, Indiana, USA, August 1982.
[5]A. M. El-Arabaty, H. E. A. Talaat, M. M. Mansour, and A. Y. Abdelaziz, “Out-of-step Detection Based on Pattern Recognition”, International Journal of Electrical Power & Energy Systems, Vol. 16, No. 4, August 1994, pp. 269-275.
[6]E. Hobson and G. N. Allen, “Effectiveness of Artificial Neural Networks for First Swing Stability Determination of Practical Systems”, IEEE Transactions on Power Systems, Vol. 9, No. 2, May 1994, pp. 1062-1068.
[7]A. Y. Abdelaziz, M. R. Irving, A. M. El-Arabaty and M. M. Mansour, “Out-of-step Prediction Based on Artificial Neural Networks”, Electrical Power Systems Research, Vol.34, No. 2, August 1995, pp. 135-142.
[8]L. Wehenkel, Th. Van Cutsem and M. Ribbens-Pavalla, “An Artificial Intelligence Framework for On-line Transient Stability Assessment of Power Systems”, IEEETransactions on Power Systems,Vol. 4, No. 2, May 1989, pp. 789-800.
[9]L. Wehenkel, M. Ribbens-Pavalla, E. Euxibie and B. Heilbronn, “Decision Trees Based Transient Stability Method: A case Study”, IEEE Transactions on Power Systems, Vol. 9, No.1, February 1994, pp. 459-468.
[10]S. Rovnyak, S. Kretsinger, J. Thorp and D. Brown, “Decision Trees for Real-Time Transient Stability Prediction”, IEEE Transactions on Power Systems, Vol. 9, No. 3, August1994, pp. 1417-1426.
[11]K. Yabe, K. Yoshida, N. Rostam Kalai, P. E. Nielsen and D. J. Leonard, “The New Concept of an Artificial Intelligent Based Smart Relay”, International Journal of Engineering Intelligent Systems, Vol. 2, No. 4, December 1994, pp. 213-221.
[12]S. Rovnyak, C. Taylor and Y. Sheng, “Decision Trees Using Apparent Resistance to Detect Impending Loss of Synchronism”, IEEE Transactions on Power Delivery, Vol. 15, No.4, October 2000, pp. 1157 - 1162.
[13]S. P. Teeuwsen, I. Erlich, M. El-Sharkawi and U. Bachmann, “Genetic Algorithm and Decision Tree-Based Oscillatory Stability Assessment, IEEE Transactions on Power Systems, Vol. 21, No. 2, May 2006, pp. 746 - 753.
[14]J. L. Souflis, A. V. Machias and B. C. Papadias, “An Application of Fuzzy Concepts to Transient Stability Evaluation”, IEEE Transactions on Power Systems, Vol. 4, No. 3, August 1989, pp. 1003-1009.
[15]L. Lai, J. T. Ma, M. Almoncid and Y. Yang, “On-line Multi-machine Power System Stability Assessment with Fuzzy Logic Classifier”, Proceedings of the 30th Universities Power Engineering Conference, UPEC’95, Greenwich, September 1995, pp. 172-175
[16]H. E. A. Talaat, “Predictive Out-of-Step Relaying using Fuzzy Rule-Based Classification”, Electric Power Systems Research, Vol. 48, No. 3, January 1999, pp. 143-149.
[17]C. Liu, S. Tsay, Y. Wang and M. Su, “Neuro-Fuzzy Approach to Real-Time Transient Stability Prediction based on Synchronized Phasor Measurements”, Electric Power Systems Research, Vol. 49, No. 2, March 1999, pp. 123–127.
[18]W. P. Ferreira, M. d. C. G. Silveira, A. P. Lotufo, Carlos. R. Minussi, “Transient Stability Analysis of Electric Energy Systems via a Fuzzy ART-ARTMAP Neural Network”, Electric Power Systems Research, Vol. 76, No. 6, April 2006, pp. 466-475.
[19]W. Li, J. Zhou, K. Xie and X. Xiong, “Power System Risk Assessment Using a Hybrid Method of Fuzzy Set and Monte Carlo Simulation”, IEEE Transactions on Power Systems, Vol. 23, No. 2, May 2008, pp. 336 – 343.
[20]R. S. Michalski, J. G. Carbonell and T. M. Mitchell, “Machine Learning: An Artificial Intelligence Approach”, Tioga Publishing Company, Palo Alto, 1983.
[21]J. Mamoh, X. W. Ma and K. Tomsovic, “Overview and Literature Survey of Fuzzy Set Theory in Power Systems”, IEEE Transactions on Power Systems, Vol. 10, No. 3, August 1995, pp. 1676-1690.
[22]E. Cox, “The fuzzy System Handbook: A Practitioner’s Guide to Building, Using, and Maintaining Fuzzy Systems”, Academic Press, USA, 1994.
[23]P. M. Anderson and A. A. Fouad, “Power System Control and Stability”, Iowa State University Press, Iowa, 1977.