Power system fault diagnosis based on history driven differential evolution and stochastic time domain simulation

Fault diagnosis is an important task in power system analysis. In this paper, a hybrid method is proposed to perform online fault diagnosis of transmission lines. Stochastic time domain simulation (STDS) is firstly introduced to generate simulated fault and system data so as to improve the computational speed of fault diagnosis and handle the possible malfunction of protective relays and circuit breakers. The fault diagnosis problem is then formulated as an optimization problem, which can take into account the possible malfunction of protection devices and post-fault system trajectories. We propose a novel optimization algorithm, namely history driven differential evolution (HDDE) to solve the formulated optimization problem. The proposed methodology is finally tested using comprehensive case studies to demonstrate its effectiveness. (C) 2014 Published by Elsevier Inc.