- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Advances in Artificial Neural Systems
Volume 2011 (2011), Article ID 532785, 9 pages
Genetic Algorithm-Based Artificial Neural Network for Voltage Stability Assessment
Electrical Engineering Department, Madhav Institute of Technology and Science, Gwalior 474 005, India
Received 3 May 2011; Accepted 16 June 2011
Academic Editor: Ping Feng Pai
Copyright © 2011 Garima Singh and Laxmi Srivastava. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- L. Srivastava, S. N. Singh, and J. Sharma, “Estimation of loadability margin using parallel self-organizing hierarchical neural network,” Computers and Electrical Engineering, vol. 26, no. 2, pp. 151–167, 2000.
- P. Kundur, Power System Stability and Control, McGraw-Hill, New York, NY, USA, 1994.
- V. Ajjarapu and C. Christy, “The continuation power flow: a tool for steady state voltage stability analysis,” IEEE Transactions on Power Systems, vol. 7, no. 1, pp. 416–423, 1992.
- C. A. Canizares and F. L. Alvarado, “Point of collapse and continuation methods for large AC/DC systems,” IEEE Transactions on Power Systems, vol. 8, no. 1, pp. 1–8, 1993.
- C. A. Canizares, “On bifurcations, voltage collapse and load modeling,” IEEE Transactions on Power Systems, vol. 10, no. 1, pp. 512–522, 1995.
- T. J. Overbye and C. L. DeMarco, “Improved techniques for power system voltage stability assessment using energy methods,” IEEE Transactions on Power Systems, vol. 6, no. 4, pp. 1446–1452, 1991.
- P. A. Löf, T. Smed, G. Andersson, and D. J. Hill, “Fast calculation of a voltage stability index,” IEEE Transactions on Power Systems, vol. 7, no. 1, pp. 54–64, 1992.
- B. Jeyasurya, “Artificial neural networks for power system steady-state voltage instability evaluation,” Electric Power Systems Research, vol. 29, no. 2, pp. 85–90, 1994.
- D. Salatino, R. Sbrizzai, M. Trovato, and M. La Scala, “Online voltage stability assessment of load centers by using neural networks,” Electric Power Systems Research, vol. 32, no. 3, pp. 165–173, 1995.
- A. A. El-Keib and X. Ma, “Application of artificial neural networks in voltage stability assessment,” IEEE Transactions on Power Systems, vol. 10, no. 4, pp. 1890–1896, 1995.
- H. P. Schmidt, “Application of artificial neural networks to the dynamic analysis of the voltage stability problem,” IEE Proceedings: Generation, Transmission & Distribution, vol. 144, pp. 371–376, 1997.
- A. Mohamed and G. B. Jasmon, “Neural network approach to dynamic voltage stability prediction,” Electric Machines and Power Systems, vol. 25, no. 5, pp. 509–523, 1996.
- V. R. Dinavahi and S. C. Srivastava, “ANN based voltage stability margin prediction,” in Proceedings of the IEEE Power Engineering Society Summer Meeting, vol. 2, pp. 1275–1279, Vancouver, Canada, July 2001.
- S. Kamalasadan, D. Thukaram, and A. K. Srivastava, “A new intelligent algorithm for online voltage stability assessment and monitoring,” International Journal of Electrical Power & Energy Systems, vol. 31, no. 2-3, pp. 100–110, 2009.
- S. Chauhan and M. P. Dave, “Kohonen neural network classifier for voltage collapse margin estimation,” Electric Machines and Power Systems, vol. 25, no. 6, pp. 607–619, 1996.
- Y. H. Song, H. B. Wan, and A. T. Johns, “Kohonen neural network based approach to voltage weak buses/areas identification,” IEE Proceedings: Generation, Transmission & Distribution, vol. 144, pp. 340–344, 1997.
- W. Nakawiro and I. Erlich, “Online voltage stability monitoring using artificial neural network,” in Proceedings of the 3rd International Conference on Deregulation and Restructuring and Power Technologies (DRPT '08), pp. 941–947, Nanjing, China, April 2008.
- S. N. Pandey, S. Tapaswi, and L. Srivastava, “Integrated evolutionary neural network approach with distributed computing for congestion management,” Applied Soft Computing Journal, vol. 10, no. 1, pp. 251–260, 2010.
- P. P. Palmes, T. Hayasaka, and S. Usui, “Mutation-based genetic neural network,” IEEE Transactions on Neural Networks, vol. 16, no. 3, pp. 587–600, 2005.
- S. Rajasekaran and G. A. V. Pai, Neural Networks, Fuzzy Logic and Genetic Algorithms—Synthesis and Applications, Prentice-Hall Press, New Delhi, India, 2006.
- P. Ramasubramanian and A. Kannan, “A genetic-algorithm based neural network short-term forecasting framework for database intrusion prediction system,” Soft Computing, vol. 10, no. 8, pp. 699–714, 2006.
- S. K. Oh and W. Pedrycz, “Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms,” Journal of the Franklin Institute, vol. 343, no. 2, pp. 125–136, 2006.
- S. K. Oh, W. Pedrycz, and S. B. Roh, “Genetically optimized hybrid fuzzy set-based polynomial neural networks,” Journal of the Franklin Institute, vol. 348, pp. 415–425, 2011.
- Y.-Y. Hsu, C.-R. Chen, and C.-C. Su, “Analysis of electromechanical modes using an artificial neural network,” IEE Proceedings: Generation, Transmission & Distribution, vol. 141, no. 3, pp. 198–204, 1994.
- S. Sharma and L. Srivastava, “Prediction of transmission line overloading using intelligent technique,” Applied Soft Computing Journal, vol. 8, no. 1, pp. 626–633, 2008.
- L. L. Freris and A. M. Sasson, “Investigation of the load-flow problem,” Proceedings of the Institution of Electrical Engineers, vol. 115, no. 10, pp. 1459–1470, 1968.
- C. A. Canizares and F. L. Alvarado, “UWPFLOW Program,” University of Waterloo, 2000, http://www.power.uwaterloo.ca/.