Design of a Robust Controller for AGC with Combined Intelligence Techniques
In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.
[1] D.M.V. Kumar, "Intelligent controllers for automatic generation
control," Proceedings of IEEE TENCON-98, Energy, Computer,
Communication control, vol. 2, 1998, pp. 557-574.
[2] Y. L. Abdel-Magid and M M. Dawoud, "Tuning of AGC of
interconnected reheat thermal systems with genetic algorithms," IEEE
International Conference on Systems, Man and Cybernetics, Vancouver,
BC, vol. 3, 1995, pp. 2622 - 2627.
[3] J. J. Grefenstette, "Optimization of control parameters for genetics
algorithms," IEEE Trans. Systems, Man and Cybernetics, SMC-16, no.
1, Feb. 1986.
[4] K. De Jong, "Adaptive system design: a genetic approach," IEEE Trans.
Systems, Man and Cybernetics, SMC-10, no. 9, pp. 1566-574, Sept.
1980.
[5] P. J. Fleming and C. M. Fonseca, "Genetic algorithms in control systems
engineering," Research Report No. 470, Dept. of Automatic control and
Systems Engineering, University of Shefleld, Sheffield, U.K., March
1993.
[6] R. C. Eberhart and Y. Shi, "Particle swarm optimization: developments,
applications and resources," Proceedings of the IEEE Congress on
Evolutionav Computation (CEC 2001), Seoul, Korea, 2001, pp. 81-86.
[7] R. Eberhart and J. Kennedy, "Particle swarm optimization," Proceedings
of the IEEE International Conference on Neural Networks, Perth,
Australia, December 1995.
[8] Y. L. Abdel-Magid and M. A. Abido, "AGC tuning of interconnected
reheat thermal systems with particle swarm optimization," Proc.10th
IEEE International Conference on Electronics, Circuits and Systems,
ICECS, vol. 1, 2003, pp. 376- 379.
[9] S. P. Ghoshal, "Application of GA/GA-SA based fuzzy automatic
generation control of a multi-area thermal generating system,"
Electric Power Systems Research, vol. 70, no. 2, pp. 115-127, July 2004.
[10] G. A. Chown, R. C. Hartman, "Design & experience of fuzzy logic
controller for automatic generation control (AGC)," IEEE Trans. on
Power Systems, vol. 13, no. 3, pp. 965-970, Aug. 1998.
[11] A.A.A. Osim and A.R. Aoki, "Particle swarm optimization for fuzzy
membership functions optimization," Proc. 2002 IEEE International
Conference on Systems, Man and Cybernetics, vol. 3, Oct. 2002, pp. 6-
10.
[12] Y.L. Karnavas and D.P. Papadoppulos, "AGC for autonomous power
system using combined intelligent techniques," Electric Power Systems
Research, vol. 62, no. 3, pp. 225-39, July 2002.
[13] R. N. Patel, "Application of artificial intelligence for tuning the
parameters of an AGC," International Journal of Mathematical,
Physical and Engineering Sciences, World Academy of Science,
Engineering and Technology (WASET), vol. 1, no. 1, pp. 34-39, 2008.
[14] Earl Cox, Fuzzy Fundamentals. IEEE Spectrum, Oct 1992, pp. 58-61.
[15] SimPowerSystems User guide. Available: http://www.mathworks.com
[1] D.M.V. Kumar, "Intelligent controllers for automatic generation
control," Proceedings of IEEE TENCON-98, Energy, Computer,
Communication control, vol. 2, 1998, pp. 557-574.
[2] Y. L. Abdel-Magid and M M. Dawoud, "Tuning of AGC of
interconnected reheat thermal systems with genetic algorithms," IEEE
International Conference on Systems, Man and Cybernetics, Vancouver,
BC, vol. 3, 1995, pp. 2622 - 2627.
[3] J. J. Grefenstette, "Optimization of control parameters for genetics
algorithms," IEEE Trans. Systems, Man and Cybernetics, SMC-16, no.
1, Feb. 1986.
[4] K. De Jong, "Adaptive system design: a genetic approach," IEEE Trans.
Systems, Man and Cybernetics, SMC-10, no. 9, pp. 1566-574, Sept.
1980.
[5] P. J. Fleming and C. M. Fonseca, "Genetic algorithms in control systems
engineering," Research Report No. 470, Dept. of Automatic control and
Systems Engineering, University of Shefleld, Sheffield, U.K., March
1993.
[6] R. C. Eberhart and Y. Shi, "Particle swarm optimization: developments,
applications and resources," Proceedings of the IEEE Congress on
Evolutionav Computation (CEC 2001), Seoul, Korea, 2001, pp. 81-86.
[7] R. Eberhart and J. Kennedy, "Particle swarm optimization," Proceedings
of the IEEE International Conference on Neural Networks, Perth,
Australia, December 1995.
[8] Y. L. Abdel-Magid and M. A. Abido, "AGC tuning of interconnected
reheat thermal systems with particle swarm optimization," Proc.10th
IEEE International Conference on Electronics, Circuits and Systems,
ICECS, vol. 1, 2003, pp. 376- 379.
[9] S. P. Ghoshal, "Application of GA/GA-SA based fuzzy automatic
generation control of a multi-area thermal generating system,"
Electric Power Systems Research, vol. 70, no. 2, pp. 115-127, July 2004.
[10] G. A. Chown, R. C. Hartman, "Design & experience of fuzzy logic
controller for automatic generation control (AGC)," IEEE Trans. on
Power Systems, vol. 13, no. 3, pp. 965-970, Aug. 1998.
[11] A.A.A. Osim and A.R. Aoki, "Particle swarm optimization for fuzzy
membership functions optimization," Proc. 2002 IEEE International
Conference on Systems, Man and Cybernetics, vol. 3, Oct. 2002, pp. 6-
10.
[12] Y.L. Karnavas and D.P. Papadoppulos, "AGC for autonomous power
system using combined intelligent techniques," Electric Power Systems
Research, vol. 62, no. 3, pp. 225-39, July 2002.
[13] R. N. Patel, "Application of artificial intelligence for tuning the
parameters of an AGC," International Journal of Mathematical,
Physical and Engineering Sciences, World Academy of Science,
Engineering and Technology (WASET), vol. 1, no. 1, pp. 34-39, 2008.
[14] Earl Cox, Fuzzy Fundamentals. IEEE Spectrum, Oct 1992, pp. 58-61.
[15] SimPowerSystems User guide. Available: http://www.mathworks.com
@article{"International Journal of Electrical, Electronic and Communication Sciences:53664", author = "R. N. Patel and S. K. Sinha and R. Prasad", title = "Design of a Robust Controller for AGC with Combined Intelligence Techniques", abstract = "In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.
", keywords = "Artificial intelligence, Automatic generation control,
Fuzzy control, Genetic Algorithm, Particle swarm optimization,
Power systems.", volume = "2", number = "9", pages = "1881-7", }
