基于双重混合粒子群算法的配电网重构

为进一步优化配电网运行结构,将混合蛙跳思想引入粒子群算法,结合配电网结构简化、支路分组,提出一种基于双重混合粒子群算法的配电网重构策略。为提高粒子搜索效率、防止算法早熟,首先,等效简化配电网结构图,对支路分组,缩短编码维数;其次,将各粒子依据一定规则分组,采用基于混合蛙跳思想的二进制粒子群算法进行支路组搜索,且对粒子历史最优值进行多次分组,组内搜索采用二进制粒子群搜索算法。运用该方法分别对IEEE33节点配电系统和136节点配电系统进行仿真,并与遗传算法和粒子群遗传混合算法进行对比分析,结果表明该方法收敛速度快,可得到最优网络重构结果,有效降低网损。

Reconfiguration of Distribution Network Based on Double Hybrid Particle Swarm Algorithm

To further optimize the operation structure of the distribution network,by embedding the idea of mixing leapfrog in the particle swarm algorithm and combining with network structure simplification and branches grouping,this paper proposes a distribution network reconfiguration strategy based on the double hybrid particle swarm algorithm. In order to improve search efficiency and avoid algorithm premature,firstly,the network structure is simplified and decomposed into subsystems in order to reduce the coding dimension. Secondly,the particles are divided into different groups according to certain rules. A binary particle swarm optimization algorithm based on the idea of mixing leapfrog is used to search between groups;the historical optimal value wouldbe regrouped repeatedly;and a group binary particle swarm search algorithmproposed in this paper is used to search within the group. The proposed algorithm is tested on the IEEE33 nodes and 136 nodes distribution power system respectively,and compared with the genetic algorithm and a hybrid algorithm based on the genetic algorithm and the particle swarm algorithm. Simulation results illustrate that the proposed algorithm can determine the optimal configuration,which can significantly reduce system energy losses,with fast convergence rate.