Coordinated Tuning of SVC and PSSs in Power System using Teaching Learning Based Algorithm

Abstract

This paper presents the application of the teaching learning based optimization (TLO) for coordinated tuning of the static var compensator (SVC) and power system stabilizers (PSSs) damping controllers. The objective is to improve the damping of low frequency electromechanical oscillations in a multi-machine electric power system. In this work, an eigenvalue-based objective function is used for the coordinated tuning of PSSs and SVC controller parameters. To ensure the robustness of the proposed controller, the tuning process takes a large and pre-specified set of operating conditions into account. The effectiveness of the proposed stabilizer is demonstrated through the eigenvalue analysis and nonlinear time-domain simulation. The results of these studies prove that the simultaneous tuning of the TLO based coordinated controller (TLPSS&SVC) has an excellent capability in damping power system low frequency oscillations and enhances greatly the system’s dynamic stability. Moreover, it significantly outperforms both the uncoordinated designed stabilizers of the TLO based PSS (TLPSS) and the TLO based SVC (TLSVC).