Optimization of Powers by Evolutionary Methods of a Complex Electrical System
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In this paper, we propose a method for optimizing the powers of a complex power system based on a hybrid approach. The basic idea is to do a combination of a genetic algorithm (GA) and a metaheuristic computational method based on the particle swarm algorithm (PSO) in order to ensure their benefits and minimize their disadvantages, using both exploration capabilities, the analogy of the AG, and operational robustness of the PSO. Our task is to minimize the total cost of production function of electrical energy using a hybrid genetic algorithm. The application of this method was tested on an electrical network of IEEE 57-node and the results we obtained show the advantage of optimizing by the marriage of the two methods in a single algorithm.
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