An Improved Catastrophic Genetic Algorithm and Its Application in Reactive Power Optimization
Ouyang Sen
DOI: 10.4236/epe.2010.24043   PDF    HTML     6,134 Downloads   10,747 Views   Citations


This paper presents an Improved Catastrophic Genetic Algorithm (ICGA) for optimal reactive power optimization. Firstly, a new catastrophic operator to enhance the genetic algorithms’ convergence stability is proposed. Then, a new probability algorithm of crossover depending on the number of generations, and a new probability algorithm of mutation depending on the fitness value are designed to solving the main conflict of the convergent speed with the global astringency. In these ways, the ICGA can prevent premature convergence and instability of genetic-catastrophic algorithms (GCA). Finally, the ICGA is applied for power system reactive power optimization and evaluated on the IEEE 14-bus power system, and the application results show that the proposed method is suitable for reactive power optimization in power system.

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O. Sen, "An Improved Catastrophic Genetic Algorithm and Its Application in Reactive Power Optimization," Energy and Power Engineering, Vol. 2 No. 4, 2010, pp. 306-312. doi: 10.4236/epe.2010.24043.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] K. R. C. Mamandur and R. D. Chenoweth, “Optimal control of reactive power flow for improvements in voltage profiles and for real power loss minimization,” IEEE Transaction on PAS, Vol. 100, No. 7, 1981, pp. 3185- 3194.
[2] L. C. Li, J. Y. Wang, L. Y. Chen, et al., “Optimal reactive power planning of electrical power system,” Proceedings of the CSEE, Vol. 19, No. 2, 1999, pp. 66-69.
[3] M. B. Liu and X. C. Wang, “An application of interior point method to solution of optimization problems in power systems,” Power System Technology, Vol. 23, No. 8, 1999, pp. 61-64, 68.
[4] K. J. Iba, “Reactive Power Optimization by Genetic Algorithm,” IEEE Transactions on Power System, Vol. 9, No. 2, 1994, pp. 685-692.
[5] P. Nallagownden, L T. Thin and N. C. Guan, “Application of Genetic Algorithm for the Reduction of Reactive Power Losses in Radial Distribution System,” IEEE International Conference on Power and Energy, Vol. 26, No. 5, 2006, 76-81.
[6] P. Sreejaya and R. Rejitha, “Reactive power and Voltage Control in Kerala Grid and Optimization of Control Variables Using Genetic Algorithm,” IEEE International Conference on Power System Technology, 2008, 1-4.
[7] H. W. Yan and J. N. Tao, “Reactive power optimization research of power system considered the generation transmission and distribution,” IEEE International Conference on Industrial Technology, Chengdu, 2008, pp. 1-4.
[8] D. E. Goldberg and P. Segrest, “Finite Markov chain analysis of genetic algorithms,” Proceedings of 2nd International Conference Genetic Algorithms, 1987, pp. 1-8.
[9] J. E. Baker, “Reducing bias and inefficiency in the selection algorithm,” Proceedings of the 2nd Annual Conference on Genetic Algorithms, Massachusetts Institute of Technology, Cambridge, 1985, pp. 14-21.
[10] D. E. Goldberg, “Genetic algorithms and rule leaming in dynamic system control,” Proceedings of International Conference on Genetic Algorithms and Their Applications, Pittsburgh, 1985, pp. 8-15.
[11] X. D. Jin and Z. Li, “Genetic-Catastrophic Algorithms and Its Application in Nonlinear Control System,” Journal of System Simulation, Vol. 9, No. 2, 1997, pp. 111- 115.
[12] M. Y. Liao and Y. J. Zhang, “Study on the Effect of Cataclysm Operator on Genetic Algorithm,” Computer Engineering and Application, Vol. 41, No. 13, 2005, pp. 54- 56.
[13] Y. J. Zhang, Z. Ren, H. M. Zhong, Z. Y. Tang and C. Shang, “Cataclysmic Genetic Algorithms Based Optimal Reactive Power Planning,” Automation of Electric Power Systems, Vol. 26, No. 23, 2002, pp. 29-32.
[14] Y. J. Zhang, W. G. Yuan, B. F. Li and M. C. Liao, “Optimal Power Purchase Planning of Hainan Power Grid Company,” The 8th International Power Engineering Conference, December 2007, Singapore, pp. 1854-1858.
[15] D. Wang, Y. K. Shi, J. Y. Cong, H. Sun and J. Y. Zou, “Application of Catastrophic Genetic Algorithm to the Opitmal Configuration of switching Devices in Distribution System,” High Voltage Apparatus, Vol. 40, No. 3, 2004, pp. 180-182.
[16] J. H. Holland, “Adaptation in natural and artificial systems,” University of Michigan Press, Ann Arbor, 1975.
[17] D. E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learning,” Addison-Wesley Publishing Company Inc., Massachusetts, 1989.
[18] L. Davis, Ed., “Genetic Algorithms and Simulated Annealing,” Pitman, London, 1987.
[19] M. Srinivas and L. M. Patnaik, “Adaptive probabilities of crossover and mutation in genetic algorithm,” IEEE Transactions on System, Man and Cybernetics, Vol. 24, No. 4, 1994, pp. 656-667.
[20] Y. J. Zhang, “Cataclysmic Genetic Algorithm and MAS Based Model for Reactive Power Optimization for Power System,” Ph.D. Dissertation, South China University of Technology, Guangzhou, 2004.

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