AUTHORS: Oscar Danilo Montoya, Walter Gil-Gonzalez, Luis F. Grisales-Norena

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ABSTRACT: This paper addresses the optimal power flow (OPF) problem in direct current (DC) power grids via a hybrid Gauss-Seidel-Genetic-Algorithm methodology through a master-slave optimization strategy. In the master stage, a genetic algorithm is employed to select the power dispatch for any distributed generator while the slave stage, Gauss-Seidel method is used for solving the resulting power flow equations without recurring to matrix inversions. This approach is important since it can be easily implementable over any simple programming toolbox finding the optimal solution of the OPF problem. Genetic-Algorithm proposed in this paper corresponds to a continuous variant of the conventional binary approaches. Computational results show the efficiency and accuracy of the proposed optimization method when is compared to GAMS/CONOPT nonlinear solver.

KEYWORDS: Direct current power grids, distributed generation, Gauss-Seidel method, genetic algorithm, hybrid master-slave optimization strategy, optimal power flow problem

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