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基于Pareto准则的多目标配电网重构方法利用自适应多目标粒子群优化(AMOPSO)算法进行优化,采用基于图论的拓扑修正策略来避免迭代过程中的不可行解,保证网络的辐射性约束,提高配电网重构效率;线性变化的惯性权重和学习因子可提高算法的寻优能力,保证Pareto解集的多样性.以含分布式电源(DG)的IEEE33节点系统为算例得到具有多样性的高质量Pareto解集,该结果不仅可验证所提出的多目标重构方法在解决配电网重构问题的有效性,也可证明DG的接入可减小配电网的网损、电压偏移量等.最后采用模糊决策法从Pareto解集中选出最佳调和解.“,”The multi-objective distribution network reconfiguration method based on Pareto criterion was optimized by the adaptive multi-objective particle swarm optimization (AMOPSO) algorithm.The topology correction strategy based on graph theory was used to avoid the infeasible solution in the iterative process to ensure the radioactivity constraints of network and improve the recomqguration efficiency of distribution network.Moreover,the inertia weight and learning factor of linear change could improve the optimization ability of algorithm and keep the diversity of the Pareto set.The high-quality Pareto set with diversity was obtained by using the IEEE 33-node system with distributed generation (DG) as example.This result not only could verify the validity of the proposed multi-objective reconstruction method in solving the problem of distribution network reconfiguration,but also could prove that DG access could reduce the distribution network loss,voltage offset and so on.Finally,the fuzzy decision method was used to select the best harmonic solution from the Pareto set.