- Turkish Journal of Electrical Engineering and Computer Science
- Vol: 26 Issue: 1
- A novel perturbed particle swarm optimization-based support vector machine for fault diagnosis in po...
A novel perturbed particle swarm optimization-based support vector machine for fault diagnosis in power distribution systems
Authors : Hoang Thi Thom, Cho Ming-yuan, Vu Quoc Tuan
Pages : 518-529
View : 10 | Download : 6
Publication Date : 9999-12-31
Article Type : Makaleler
Abstract :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 re ectometry (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.Keywords : Fault diagnosis, particle swarm optimization, power distribution networks support vector machine, time- domain re ectometry