A novel perturbed particle swarm optimization-based support vector machine for fault diagnosis in power distribution systems

作者：Thom Hoang Thi^*; Yuan Cho Ming; Vu Quoc Tuan

来源：Turkish Journal of Electrical Engineering and Computer Sciences, 2018, 26(1): 518-529.

DOI：10.3906/elk-1705-241

• Fault diagnosis
• particle swarm optimization
• power distribution networks support vector machine
• time-domain reflectometry

In this paper, a novel perturbed particle swarm optimization (PPSO) algorithm is investigated to improve the performance of a support vector machine (SVM) for short-circuit fault diagnosis in power distribution systems. In the proposed PPSO algorithm, the velocity of each particle is perturbed whenever the particles strike into a local optimum, in order to achieve a higher quality solution to optimization problems. Furthermore, the concept of proposed perturbation is applied to three variants of PSO, and improved corresponding algorithms are named perturbed C-PSO (PC-PSO), perturbed T-PSO (PT-PSO), and perturbed K-PSO (PK-PSO). For the purpose of fault diagnosis, the time domain reflectometry (TDR) method with pseudorandom binary sequence (PRBS) excitation is considered to generate the necessary fault simulation data set. The proposed approaches are tested on a typical two-lateral radial distribution network.

• 出版日期2018
• 单位中国人民解放军海军大连舰艇学院