Adaptive underfrequency load shedding using particle swarm optimization algorithm

Abstract

Underfrequency load shedding plays an important role in prevention of the power system blackout. The common load shedding methods are based on measuring the frequency first derivative; therefore, an error in measurement process can highly affect their performance. Also, for properper formance of these load shedding schemes, the exact value of some parameters of power system is needed. Any error in estimation of these parameters reduces the reliability of these load shedding schemes. In this paper, an underfrequency load shedding method based on the forecast minimum frequency of system is proposed. In this method, the samples of the power system frequency are taken after disturbance; then, particles warm optimization algorithm is used to forecast the minimum frequency based on these samples. To verify the effectiveness of the proposed loads hedding scheme, its performance has been compared with a newly suggested method.