Abstract
In this paper, an adaptive genetic algorithm for the capacitor placement problem in a radial distribution system is presented. Based on the measure of the superiority of an individual called elite degree, the adaptive GA dynamically tunes GA parameters such as crossover and mutation during the GA run. The proposed GA is applied to test distribution systems including IEEE 69 with successful results.
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References
Baran, M. E., Wu, F. F.: Optimal Capacitor Placement on Radial Distribution System. IEEE Transactions on Power Delivery, Vol. 4, No. 1 (1989) 725–734
Bäck, T., Hammel, U., Schwefel, H. P.: Evolutionary Computation: Comments on the History and Current State. IEEE Transaction on Evolutionary Computation, Vol.1, No. 1 (1997) 3–17
Cao, Y. J., Wu, Q. H.: Optimal Reactive Power Dispatch Using an Adaptive Genetic Algorithm. Proc. IEE/IEEE Genetic Algorithms in Engineering Systems: Innovations and Applications (1997) 117–122
Grefenstette, J. J.: Optimization of Control Parameters for Genetic Algorithms. IEEE Transaction on Systems, Man, and Cybernetics, Vol. SMC-16, No. 1 (1986) 122–128
Hatta, K., Matsuda, K., Wakabayashi, S., Koide, T.: On-the-fly Crossover Adaptation of Genetic Algorithms. Proc. IEE/IEEE Genetic Algorithms in Engineering Systems: Innovations and Applications (1997) 197–202
Hinterding, R., Michalewicz, Z., Eiben, A. E.: Adaptation in Evolutionary Computation: A Survey. Proc. IEEE International Conference on Evolutionary Computation (1997) 65–69
Huang, Y. C., Yang, H. T., Huang, C. L.: Solving the Capacitor Placement Problem in a Radial Distribution System Using Tabu Search Approach. IEEE Transactions on Power Systems, Vol. 11, No. 4 (1996) 1868–1873
Spears, W. M.: Adapting Crossover in Evolutionary Algorithms. Proc. Evolutionary Programming Conference (1995) 367–384
Srinivas, M., Patnaik, L. M.: Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms. IEEE Transaction on Systems, Man, and Cybernetics, Vol. 24, No. 4 (1994) 656–667
Sundhararajan, S., Pahwa, A.: Optimal Selection of Capacitors for Radial Distribution Systems Using Genetic Algorithms. IEEE PES Summer Meeting, paper no. 93 SM 499-4 (1993)
White, T., Oppacher, F.: Adaptive Crossover Using Automata. Proc. Parallel Problem Solving from Nature — PPSN III (1994) 229–238
Zoka, Y., Sasaki, H., Kubokawa, J., Yokoyama, R., Tanaka, H.: An Optimal Deployment of Fuel Cells in Distribution Systems by Using Genetic Algorithms. Proc. IEEE International Conference on Evolutionary Computation (1995) 479–484
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© 1998 Springer-Verlag Berlin Heidelberg
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Hatta, K., Suzuki, M., Wakabayashi, S., Koide, T. (1998). Solving the capacitor placement problem in a radial distribution system using an adaptive genetic algorithm. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056944
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DOI: https://doi.org/10.1007/BFb0056944
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