Power network topology recognition using neural networks

Electric Machines and Power Systems

Volumn 27, Issue 2, 1999, Pages 195-208

  Abd El Reheim, Mohamed Abd El Aal ^a  

^a Ain Shams University   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRIC NETWORK TOPOLOGY; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; PATTERN RECOGNITION SYSTEMS;

POWER NETWORK TOPOLOGY RECOGNITION;

ELECTRIC POWER TRANSMISSION NETWORKS;

EID: 0033079013     PISSN: 0731356X     EISSN: 15210502     Source Type: Journal    
DOI: 10.1080/073135699269398     Document Type: Article

References (17)

1. Dabbaghchi, I., Christie, R. D., Rosenwald, G. W., and Liu, C., 1997, AI application areas in power systems, IEEE-Expert, Intelligent Systems and Their Applications, Vol. 12, No. 1, pp. 58-66, January-February.
2. Falcov, D. M. and Arias, M. A., 1994, State estimation and observability analysis based on Echelon forms of the linearized measurement model, IEEE Trans. On Power System, Vol. 9, No. 2, pp. 979-987, May.
3. Hammerstron, D., 1993, Neural networks at work, IEEE Spectrum, pp. 26-28, June.
4. Hammerstron, D., 1993, Working with neural network, IEEE Spectrum, pp. 46-53, July.
5. Haykins, S., 1994, Neural networks, A comprehensive foundation, Canada, Book, Macmillan College Publishing Company.
6. Jannavithula, S. and Billinton, R., 1997, Topological analysis in bulk power system reliability evaluation, IEEE Trans. On Power System, Vol. 12, No. 1, pp. 456-463, May.
7. Korre, G. N. and Contaxis, G. C., 1994, A tool for the evaluation and selection of state estimator measurements, IEEE Trans. On Power System, Vol. 9, No. 2, pp. 1110-1116, May.
8. Maouche, A. S. and Adams, N., 1997, Expert system approach for security assessment of electrical power network, Record of the Fifth International Middle East Power Conference MEPCON-97, Alexandria, Egypt, January 4-6.
9. Neurodynamind, 1992, Dynamind—User-Guide, Book, Version 3.0, Colorado.
10. Patteson, D. W., 1996, Artificial neural networks theory and applications, Book, Prentice Hall, Singapore.
11. Singh, N. and Oesch, F., 1994, Practice experience with rule-based on-line topology error detection, IEEE Trans. On Power System, Vol. 9, No. 2, pp. 841-847, May.
12. The Matlab Works, Inc., 1991, Matlab User’s Guide, Version 4.2b.
13. Werbos, P. J., 1990, Backpropagation through time: What it does and how do it, Proceedings of the IEEE, Special Issue on Neural Network Theory & Modeling—I, Vol. 78, No. 10, pp. 1550-1560, October.
14. Windrow, B. and Lehr, M. A., 1990, 30 years of adaptive neural networks: Preparation, Madaline, and backpropagation, Proceedings of the IEEE, Special Issue on Neural Network Theory & Modeling—I, Vol. 78, No. 9, pp. 1415-1442, September.
15. Yale, K., 1997, Preparing the right data diet for training neural network, IEEE Spectrum, pp. 64-66, March.
16. Zhou, O., Davidson, J., and Fouad, A. A., 1994, Application of artifial neural networks in power security and vulnerability assessment, IEEE Trans. On Power System, Vol. 9, No. 1, pp. 525-532, May.
17. Zurada, J. M., 1992, Introduction of artifial neural systems, Book, West Publishing Company, New York.