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Journal of Engineering
Volume 2013, Article ID 510572, 13 pages
http://dx.doi.org/10.1155/2013/510572
Research Article

A Novel Fuzzy RPID Controller for Multiarea AGC with IABC Optimization

1Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
2Electrical Engineering Department, Islamic Azad University, Ardabil, Iran

Received 12 December 2012; Revised 14 April 2013; Accepted 14 April 2013

Academic Editor: Mohammed Chadli

Copyright © 2013 Javad Javidan and Ali Ghasemi. 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.

Linked References

  1. A. Nargelas and R. Bikulcius, “Distributed automatic generation control in the conditions of electricity market,” Power and Electrical Engineering, vol. 3, no. 4, pp. 43–49, 2001. View at Google Scholar
  2. H. Bevrani, F. Daneshfar, and T. Hiyama, “A new intelligent agent-based AGC design with real-time application,” IEEE Transactions on Systems, Man, and Cybernetics C, vol. 42, no. 6, pp. 994–1002, 2012. View at Google Scholar
  3. M. Zribi, M. Al-Rashed, and M. Alrifai, “Adaptive decentralized load frequency control of multi area power systems,” International Journal of Electrical Power & Energy Systems, vol. 27, no. 8, pp. 575–583, 2005. View at Google Scholar
  4. V. Donde, M. A. Pai, and I. A. Hiskens, “Simulation and optimization in an AGC system after deregulation,” IEEE Transactions on Power Systems, vol. 16, no. 3, pp. 481–489, 2001. View at Publisher · View at Google Scholar · View at Scopus
  5. P. Bhatt, R. Roy, and S. P. Ghoshal, “Optimized multi area AGC simulation in restructured power systems,” International Journal of Electrical Power and Energy Systems, vol. 32, no. 4, pp. 311–322, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Ghasemi, M. S. Naderi, and O. Abedinia, “Robust LFC in deregulated environment: fuzzy PID using HBMO,” in Proceedings of the 10th International Conference on Environment and Electrical Engineering (EEEIC '11), 2011. View at Publisher · View at Google Scholar
  7. S. Taher, R. Hematti, A. Abdolalipour, and S. H. Tabei, “Optimal decentralized load frequency control using HPSO algorithms in deregulated power systems,” American Journal of Applied Sciences, vol. 5, no. 9, pp. 1167–1174, 2008. View at Google Scholar
  8. E. S. Ali and S. M. Abd-Elazim, “Bacteria foraging optimization algorithm based load frequency controller for interconnected power system,” Electrical Power and Energy Systems, vol. 33, pp. 633–638, 2011. View at Google Scholar
  9. P. Aravindan and M. Y. Sanavullah, “Fuzzy logic based automatic frequency control of two area power system with GRC,” International Journal of Computational Intelligence Research, vol. 5, no. 1, pp. 37–44, 2009. View at Google Scholar
  10. E. Yesil, M. Guzelkaya, and I. Eksin, “Self tuning fuzzy PID type load and frequency controller,” Energy Conversion and Management, vol. 45, no. 3, pp. 377–390, 2004. View at Publisher · View at Google Scholar · View at Scopus
  11. A. Ghasemi, B. Wyns, and O. Abedinia, “Robust fuzzy PSS design using ABC,” in Proceedings of the 10th International Conference on Environment and Electrical Engineering (EEEIC '11), 2011.
  12. G. Panda, S. Panda, and C. Ardil, “Automatic generation control of interconnected power system with generation rate constraints by hybrid neuro fuzzy approach,” International Journal of Electrical Power & Energy Systems, vol. 2, no. 1, pp. 13–18, 2009. View at Google Scholar
  13. S. P. Ghoshal, “Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control,” Electric Power Systems Research, vol. 72, no. 3, pp. 203–212, 2004. View at Publisher · View at Google Scholar · View at Scopus
  14. D. Karaboga, “An idea based on honey bee swarm for numerical optimization,” Technical Report TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, Kayseri, Turkey, 2005. View at Google Scholar
  15. D. Karaboga and B. Basturk, “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm,” Journal of Global Optimization, vol. 39, no. 3, pp. 459–471, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. S. L. Sabat, S. K. Udgata, and A. Abraham, “Artificial bee colony algorithm for small signal model parameter extraction of MESFET,” Engineering Applications of Artificial Intelligence, vol. 23, no. 5, pp. 689–694, 2010. View at Publisher · View at Google Scholar
  17. P. W. Tsai, J. S. Pan, B. Y. Liao, and S. C. Chu, “Enhanced artificial bee colony optimization,” International Journal of Innovative Computing, Information and Control, vol. 5, no. 12, pp. 5081–5092, 2009. View at Google Scholar · View at Scopus
  18. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi, “GSA: a gravitational search algorithm,” Information Sciences, vol. 179, no. 13, pp. 2232–2248, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. G. A. Gurzadyan, Space Dynamics, Taylor & Francis, London, UK, 2002.
  20. Y. P. Kuo and T. H. S. Li, “GA-based fuzzy PI/PD controller for automotive active suspension system,” IEEE Transactions on Industrial Electronics, vol. 46, no. 6, pp. 1051–1056, 1999. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Chadli and T.-M. Guerra, “LMI solution for robust static output feedback control of Takagi-Sugeno fuzzy models,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 6, pp. 1160–1165, 2012. View at Publisher · View at Google Scholar
  22. S. Bououden, M. Chadli, S. Filali, and A. El Hajjaji, “Fuzzy model based multivariable predictive control of a variable speed wind turbine: LMI approach,” Renewable Energy, vol. 37, no. 1, pp. 434–439, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. A. Ghasemi, H. Shayeghi, and H. Alkhatib, “Robust design of multimachine power system stabilizers using fuzzy gravitational search algorithm,” Electrical Power & Energy Systems, vol. 51, pp. 190–200, 2013. View at Google Scholar
  24. H. A. Shayanfar, H. Shayeghi, A. Jalili, and M. Sivandian, “A genetic algorithm based AGC of a restructured power system,” in Proceedings of the International Conference on Artificial Intelligence, pp. 237–240, Las Vegas, Nev, USA, June 2006.