Fault section location of distribution networks based on an improved whale algorithm

Abstract

Accurate location of the fault section in distribution networks is essential in ensuring power supply reliability and self-healing. Based on the extraction and analysis of fault feature information of automatic monitoring devices， this paper constructs the switching function and fitness function suitable for multi-state and different distributed power sources. It introduces additional fault criteria to improve the traditional fitness function. Moreover， it proposes an improved whale optimization algorithm based on multiple strategies. It uses the Sobol sequence to obtain a uniformly distributed initial population and uses differential variation perturbation factor and adaptive weight to improve the optimization accuracy and convergence speed. The simulation on an example shows that the improved whale optimization algorithm used in fault location is characterized by its strong fault tolerance， high fault identification rate， and optimization stability； Moreover， the algorithm can enhance the solution efficiency of fault location.

Keywords

• improved whale optimization algorithm （iwoa）
• fault location
• auxiliary fault criterion
• sobol sequence
• differential variation perturbation factor