Classification of events in distribution networks using autonomous neural models

2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09

Volumn , Issue , 2009, Pages 284-289

  Lazzaretti, André E ^a   Ferreira, Vitor H ^b   Neto, Hugo Vieira ^c   Riella, Rodrigo J ^a   Omori, Julio ^d  

^a Institute of Technology for Development LACTEC   (Brazil)

^b FLUMINENSE FEDERAL UNIVERSITY   (Brazil)

^c UNIVERSIDADE TECNOLÓGICA FEDERAL DO PARANÁ   (Brazil)

^d Energy Company of Paraná COPEL   (Brazil)

Author keywords

Bayesian inference applied to multi layer perceptrons; Input selection; Model complexity; Quality of service event classification; Support vector machines; Wavelet transform

Indexed keywords

BAYESIAN NETWORKS; COMPLEX NETWORKS; ELECTRIC UTILITIES; FEEDFORWARD NEURAL NETWORKS; INFERENCE ENGINES; INTELLIGENT SYSTEMS; QUALITY OF SERVICE; SUPPORT VECTOR MACHINES; WAVELET TRANSFORMS;

AUTOMATIC CLASSIFICATION; ELECTRICITY DISTRIBUTION NETWORKS; EVENT CLASSIFICATION; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; INPUT SELECTION; MODEL COMPLEXITY; MULTI LAYER PERCEPTRON; MULTI-LAYER PERCEPTRONS;

MULTILAYER NEURAL NETWORKS;

EID: 76549106094     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISAP.2009.5352812     Document Type: Conference Paper

References (22)

1. J. Morais, Y. Pires, C. Cardoso, and A. Klautau, "Data mining applied to the electric power industry: Classification of short-circuit faults in transmission lines," in Proceedings of the 7th International Conference on Intelligent Systems Design and Application, October 2007, pp. 943- 948.
2. ANEEL, Procedimentos de Distribuiçã de Energia Elétrica no Sistema Elétrico Nacional - PRODIST, Módulo 8 - Qualidade de Energia Elétrica, Agência Nacional de Energia Elétrica, 2007, in Portuguese.
3. R. J. Riella, V. P. Ferrari, G. Paulillo, M. R. Ortega, and J. G. Pereira, "Desenvolvimento de um sistema de monitoramento contínuo da qualidade da energia elétrica para subestações de distribuição" in Anais do XVIII Seminário Nacional de Distribuição de Energia Elétrica, October 2008, in Portuguese.
4. R. C. Dugan, M. F. McGranaghan, S. Santoso, and H. W. Beaty, Electrical Power System Quality, 2nd ed. McGraw-Hill, 2002.
5. EMTP, Alternative Transients Program (ATP) Rule Book, Can Am EMTP User's Group, 1995.
6. K. M. Silva, B. A. Souza, and N. S. D. Brito, "Fault detection and classification in transmission lines based on wavelet transform and ANN," IEEE Transactions on Power Delivery, vol.21, no.4, pp. 2058- 2063, October 2006.
7. O. Dag and C. Ucak, "Fault classification for power distribution systems via a combined wavelet-neural approach," in Proceedings of the 2006 International Conference on Power System Technology, vol.2, November 2004, pp. 1309-1314.
8. H. Zheng-You, C. Xiaoqing, and L. Guoming, "Wavelet entropy measure definition and its application for transmission line fault detection and identification," in Proceedings of the 2006 International Conference on Power System Technology, October 2006, pp. 1-6.
9. J. Arrillaga, B. C. Smith, N. R. Watson, and A. R. Wood, Power System Harmonics. Wiley, 2003.
10. O. Delmont Filho, "Um algoritmo para deteçãoo, localiza̧ãoo e classifica̧ãoo de distúrbios em qualidade da energia elétrica utilizando a transformada wavelet," Ph.D. dissertation, EESC/USP, São Carlos, 2007, in Portuguese.
11. V. H. Ferreira and A. P. A. da Silva, "Toward estimating autonomous neural network load forecasters," IEEE Transactions on Power Systems, vol.22, no.4, pp. 1554-1562, November 2007.
12. V. H. Ferreira, "Desenvolvimento de modelos neurais autǒnomos para previsão de carga elétrica," Ph.D. dissertation, COPPE/UFRJ, Rio de Janeiro, 2008, in Portuguese.
13. I. Daubechies, Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, 1992.
14. S. Mallat, A Wavelet Tour of Signal Processing, 2nd ed. Academic Press, 1999.
15. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford University Press, 1995.
16. D. J. C. Mackay, "Bayesian methods for adaptive models," Ph.D. dissertation, Caltech, Pasadena, 1992.
17. V. N. Vapnik, Statistical Learning Theory. Wiley-Interscience, 1998.
18. V. Cherkassky and F. F. Mulier, Learning from Data: Concepts, Theory and Methods. Wiley, 1998.
19. B. Schölkopf and A. J. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. MIT Press, 2001.
20. V. Vapnik and O. Chapelle, "Bounds on error expectation for support vector machines," Neural Computation, vol.12, no.9, pp. 2013-2036, September 2000.
21. O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee, "Choosing multiple parameters for support vector machines," Machine Learning, vol.46, no.1-3, pp. 131-159, January 2002. (Pubitemid 34129966)
22. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning Addison-Wesley Professional, 1989.