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首页> 外文期刊>WSEAS Transactions on Power Systems >Optimal power dispatch of DGs in DC power grids: a hybrid Gauss-Seidel-Genetic-Algorithm methodology for solving the OPF problem
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Optimal power dispatch of DGs in DC power grids: a hybrid Gauss-Seidel-Genetic-Algorithm methodology for solving the OPF problem

机译:DC电网中DGS的最佳功率调度:一种用于解决OPF问题的混合高斯-Seidel-遗传算法方法

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摘要

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.
机译:本文通过主从优化策略,通过混合高斯-Seidel-enidel族遗传算法方法解决了直流(DC)电网中的最佳功率流量(OPF)问题。 在主阶段,采用遗传算法来选择用于从级,Gauss-Seidel方法的任何分布式发电机的功率分配,用于求解所得到的功率流方程而不重复到矩阵逆转。 这种方法很重要,因为它可以在任何简单的编程工具箱上方找到OPF问题的最佳解决方案。 本文提出的遗传算法对应于传统二进制方法的连续变体。 计算结果表明,与GAMS / CONOPT非线性求解器相比,所提出的优化方法的效率和准确性。

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