Optimal Tuning of Single Input Power System Stabilizer Using Quasi-Oppositional Butterfly Optimization Algorithm

Abstract

Low frequency oscillation has been a major threat in large interconnected power systems. These low frequency oscillation curtains the power transfer capability of the line, thereby affecting the small signal analysis of the system and hence the performance of the system comes to a stake. Power system stabilizer (PSS) helps in diminishing these low frequency oscillations by providing auxiliary control signal to the generator excitation input. In this chapter, the authors have incorporated the concept of quasi-oppositional based learning (OBL) in butterfly optimization algorithm (BOA) to solve PSS problem. The proposed technique has been implemented on SMIB system and the supremacy of the suggested QOBOA accept has been accurated by different loading conditions to show the flexibility of QOBOA. The computed results thus obtained by the proposed techniques have been verified by comparing the results with those obtained by well published algorithms. The convergence characteristics as well authenticate the sovereignty of the considered algorithms.