Voltage Sag State Estimation Based on Hybrid Particle Swarm Optimization Algorithm

This paper presents an approach applying Hybrid Particle Swarm Optimization algorithm to voltage sag frequency state estimation, based on the monitoring system determined by optimum allocation method of voltage sag monitoring nodes. Voltage sag frequency state estimation is interpreted as the estimation of the number of voltage sags occurring at non-monitored buses from the recorded voltage sags occurrence number at the monitored buses. In this study, a Hybrid Particle Swarm Optimization algorithm is proposed to solve the problem of voltage sag state estimation by the use of round-off method. The effectiveness and accuracy of the proposed approach are verified by the case study of the IEEE-39 standard test system.