基于量子人工蜂群算法的配电网多目标优化重构

Multi-objective Optimal Reconfiguration of DistributionNetwork Based on Quantum Artificial Bee Colony Algorithm

为了保证配电网优化运行,本文以系统网损最小、节点最低电压幅值最大、开关操作次数最少为目标构造配电网多目标优化重构模型,采用量子人工蜂群算法和帕累托(Pareto)支配关系求解。针对易于陷入局部最优解问题的人工蜂群算法,引入量子理论来进行蜂群的搜索,扩大了全局搜索范围,使其收敛于全局最优解,对于多目标问题,采用拥挤度来控制Pareto最优解的个数。将算法应用于标准IEEE 33节点配电网和加入分布式电源的配电网进行重构测试,实验表明该方法是有效和可行的。

In order to ensure the optimal operation of the distribution network,this paper constructs a multi-objective optimization reconfiguration model of the distribution network with the goals of minimum system loss,maximum node voltage amplitude and minimum number of switching operations,and use the quantum artificial bee colony algorithm and Pareto dominance relationship to solve the model.For the artificial bee colony algorithm which is likely to fall into the local optimal solution problem,quantum theory is introduced to search the bee colony,which expands the global search range and makes it converge to the global optimal solution.For multi-objective problems,the crowding degree is used to control the number of Pareto optimal solution.The algorithm is applied to the standard IEEE 33-node distribution network and the distribution network with distributed power sources for reconstruction testing.The experimental results show that the method is effective and feasible.