优化的GA算法在大型配电网络重构中的应用

Application of Optimized GA Algorithm in Large Distribution Network Reconfiguration

当前对配电网重构的研究多数针对于中小型网络,而对大型网络的研究较少,为此,提出了一种优化的GA(Genetic Algorithm)算法应用于大型配电网络重构中,对其基因操作过程进行优化。引入精英策略,最大程度保留父代最优个体的遗传信息,在变异的过程中再次引入“局部变异”,产生的子代种群更具多样性。对重构的目标函数引入关联系数,简化计算复杂度。将该算法应用于IEEE118节点算例,重构后线损及电压降落程度与蒙特卡洛模拟法所得结果相对比,实验结果表明,该算法明显更优,并证明了该算法在大型配电网重构的可行性和有效性。

Because most of the current research on distribution network reconfiguration is aimed at small and medium-sized networks, and there is less research on large networks, an optimized GA(Genetic Algorithm) algorithm is proposed. In the large-scale distribution network reconfiguration, the gene operation process is optimized, and the elite strategy is introduced to retain the genetic information of the parent optimal individual to the greatest extent. In the process of variation, the “local variation” is introduced again, and the offspring population is more diverse. The correlation coefficient is introduced into the reconstructed objective function to simplify the computational complexity. The algorithm is applied to IEEE118 node system. Compared to the results obtained by MC(Monte Carlo) simulation method, the reconstructed network loss and voltage deviation are obviously better, which proves the feasibility and effectiveness of the algorithm in large-scale distribution network reconstruction.