基于E占优的多目标二进制粒子群算法求解配电网故障恢复

发布时间：2018-06-24 01:31

本文选题：配电网 + 故障恢复　；参考：《电力系统保护与控制》2014年23期

【摘要】：针对基于Pareto占优机制和拥挤距离的经典多目标智能算法在迭代过程中没有考虑决策者的偏好知识,从而影响了算法收敛性的问题,提出了一种基于E占优的多目标二进制粒子群算法求解配电网故障恢复。通过采用改进原点距离的E占优机制,可以将决策者的偏好知识有效地融入到故障恢复方案的评价过程中。在算法迭代过程中,采用轮盘赌策略更新群体极值,采用方案的综合值对外部档案进行维护,使得决策者的偏好知识可以有效地指导下一代种群的产生。最后,通过算例验证了所提算法的可行性和有效性,并且该方法比基于Pareto占优机制和拥挤距离的多目标智能算法拥有更好的收敛性能,得到的最优前沿数量更少,质量更高。
[Abstract]:The classical multi-objective intelligent algorithm based on Pareto dominance mechanism and congestion distance does not take into account the preference knowledge of decision makers in the iterative process, which affects the convergence of the algorithm. A multi-objective binary particle swarm optimization (BPSO) algorithm based on E dominance is proposed for fault recovery of distribution network. The preference knowledge of decision makers can be effectively integrated into the evaluation process of fault recovery scheme by adopting the E-dominant mechanism which improves the origin distance. In the iterative process of the algorithm, the roulette strategy is used to update the population extremum, and the comprehensive value of the scheme is used to maintain the external files, so that the preference knowledge of the decision makers can effectively guide the generation of the next generation population. Finally, an example is given to verify the feasibility and effectiveness of the proposed algorithm, and the proposed algorithm has better convergence performance than the multi-objective intelligent algorithm based on Pareto dominance mechanism and congestion distance, resulting in fewer optimal frontiers and higher quality.
【作者单位】：新能源电力系统国家重点实验室(华北电力大学);沈阳供电公司;
【基金】：国家电网公司科技项目资助(KJ[2013]896)
【分类号】：TM73

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