Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (1): 143-151.doi: 10.23940/ijpe.20.01.p15.143151

• Orginal Article • Previous Articles     Next Articles

Fault Section Location of Active Distribution Network based on Wolf Pack and Differential Evolution Algorithms

Haizhu Yang, Yiming Guo*(), and Xiangyang Liu   

  1. School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454000, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: Yiming Guo E-mail:hpugym@163.com
  • About author:

    Haizhu Yang received his Ph.D. from Beijing Jiaotong University in 2005. He is currently an associate professor in the School of Electrical Engineering and Automation at Henan Polytechnic University. His research interests include power electronics, electrical drive, power systems, and automation.

    Yiming Guo is currently pursuing an M.S degree in the School of Electrical Engineering and Automation at Henan Polytechnic University. His research interests include power systems, automation, and active distribution network fault diagnosis.

    Xiangyang Liu is currently pursuing an M.S degree in the School of Electrical Engineering and Automation at Henan Polytechnic University. His research interests includes power systems and automation.

  • Supported by:
    This work is supported by the National Natural Science Foundation of China (No. 61703144), The authors gratefully acknowledge the reviewers for their helpful comments and suggestions.

Abstract:

Distributed generation changes distribution network topology and power flow direction, creating active distribution networks and making traditional fault location algorithms inapplicable. This paper proposes a fault section location method for active distribution networks based on the wolf pack and differential evolution algorithms, introducing the differential evolution algorithm to the wolf pack algorithm to enrich the population diversity and enhance the global optimization performance. It constructs an evaluation function and a switching function model of active distribution networks and tests the algorithm validity using a benchmark function. The algorithm simulates the fault section location of a 33-node distribution network with DG under different conditions and compares it with other three algorithms. The simulation results show that the algorithm can accurately locate fault sections and has good fault tolerance.

Key words: distributed generation, active distribution network, wolf pack algorithm, differential evolution algorithm, fault section location