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Showing 1 results for Differential Evolution (de)

Sedigheh Janipour, Samad Nejatian, Mosayeb Bornapour,
Volume 2, Issue 2 (3-2017)
Abstract

Distribution feeder reconfiguration for loss reduction is a very important way to save the electrical energy. This paper proposes a new hybrid evolutionary algorithm to solve the Distribution Feeder Reconfiguration problem (DFR) .The algorithm is based on combination of a New Fuzzy Adaptive Particle Swarm Optimization (NFAPSO) and differential evolution algorithm (DE) called NFAPSO-DE. To exploit the advantages of the exploration ability of DE and the high speed search system and the ability to control and adjust the parameters of PSO algorithm, a hybrid PSO-DE method is proposed. The hybrid method uses the PSO to find the region of optimal solution, and then a combination of PSO and DE to find the optimal solution. In other hand, due to the results of PSO algorithm highly depends on the values of their parameters such as the inertia weight and learning factors, a fuzzy system is employed to adaptively adjust the parameters during the search process. Finally, the proposed algorithm is tested on 33 bus and 69 bus distribution test systems. The results of simulation shows that the proposed method is very powerful and effective to obtain the global optimization.



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