Comparison of robust and intelligent based power system stabilizers

Abstract

Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional power system stabilizers (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. Intelligent based methods such as Fuzzy logic and genetic algorithms and also robust control methods such as quantitative feedback theory (QFT) have already been used for designing PSS. In this paper the goal is to study comparison of different methods used for designing PSS. For this purpose the Conventional PSS (CPSS), fuzzy based PSS (FPSS), genetic algorithms based PSS (GA-PSS) and also QFT based PSS (QFT-PSS) are considered for comparison purposes. A single machine infinite bus power system with system parametric uncertainties is considered as a case study and the proposed methods are evaluated against one another at this test system. The simulation results clearly indicate the effectiveness and validity of the proposed methods. Key words: Electric power system stabilizer, low frequency oscillations, genetic algorithms optimization, fuzzy logic, quantitative feedback theory.