基于GA-QPSO算法的含分布式电源配电网优化重构设计

Design of Distribution Network Reconfiguration Containing Distributed Generation Based on GA-QPSO Algorithm

为了适应当前配电网结构日趋复杂且分布式电源大量接入的情况,提出一种改进的量子粒子群优化算法并成功应用于含分布式电源的配电网优化重构中。该算法通过在标准量子粒子群算法中引入遗传算法的“遗传”和“变异”操作,对粒子各等位基因实行概率进化,以提高种群基因的多样性,克服原算法前期易陷入局部收敛的缺陷。改进算法后通过设置变异因子,并以轮盘赌的方式对各粒子实行自我交叉操作,既保留了进化过程中的优秀基因,同时也兼顾了全局性和收敛性。对多种算例进行仿真分析结果表明,该算法可以快速搜寻到较优的电网结构,有效降低有功网损,提高各节点电压水平,为含分布式电源的配电网重构研究提供了思路和参考。

In order to adapt to the increasing complexity of the current distribution network structure and the large number of distributed power sources,an improved quantum particle swarm optimization algorithm is proposed and successfully applied to the optimization and reconstruction of the distribution network containing distributed power sources.The algorithm introduces the"genetic"and"mutation"operations of the genetic algorithm into the standard quantum particle swarm algorithm to implement probabilistic evolution for each allele of the particle,thereby increasing the diversity of the population gene and avoiding the algorithm from falling into local convergence at the initial stage.In the later stage of the algorithm,by setting the mutation factor and performing self-crossing operations on each particle in a roulette way,it not only retains the excellent genes in the evolution process,but also takes into account the globality and convergence.Through the simulation analysis of various calculation examples,the results show that the algorithm can quickly search for a better grid structure,effectively reduce the active power loss,and increase the voltage level of each node.At the same time,the algorithm also provides ideas and references for the reconstruction of distribution networks containing distributed power sources.