Fault Location Method for an Active Distribution Network Based on a Hierarchical Optimization Model and Fault Confidence Factors

Abstract

With extensive access to distributed power sources and the rising electricity load, the structure and tide of distribution networks are becoming increasingly large and complex, leading to great challenges for fault location methods. In this paper, the power coupling phenomenon of the T-section in the distribution network is studied, and a hierarchical optimization model for fault location is proposed based on the port equivalence principle, which divides the fault location into two levels—area location and section location—to reduce the fault search dimension. Then, an improved binary particle swarm optimization algorithm (IBPSO) applied to the area location is proposed to improve the convergence accuracy and speed by optimizing the convergence criterion and integrating the chaotic mapping and mutation strategies. Finally, based on the topological characteristics of the sections in the fault area, a fault candidate scenario screening method based on the fault confidence factor is proposed to realize a second dimensionality reduction in the section location link. Simulation tests show that the proposed method demonstrates a good dimensionality reduction effect for large-scale, active distribution networks; additionally, the accuracy rate is improved by 25.7% and the location speed is improved by 300 ms when compared with traditional fault location methods.