Abstract

In this paper, the application of the fuzzy logic based power systems stabilizer (FLPSS) to damp power system oscillation is presented. Various types of fuzzy logic controller are used to replace the conventional power system stabilizer (CPSS). The classic fuzzy logic controller based PSS (FLCPSS), the polar FLC (PFLCPSS) and the interval type-2 fuzzy logic controller based PSS (IT2FLCPSS) are applied to the New England - New York interconnected power system and the obtained results are compared. For coordination purposes, genetic algorithm (GA) is used to tune the FLCPSS’s gains. The non-linear simulation in the presence of noise confirms the robustness and the superiority of the IT2FLCPSS.

Highlights

  • Hadj AbdallahEngineering School of Engineering, Department, Engineering School of Engineering School of

  • Nowadays, power systems are driven to work around their limits of stability in a fast and flexible way

  • Various types of power systems stabilizers (PSSs) controllers namely fuzzy logic controller based PSS (FLCPSS) [2], PFLCPSS [1], conventional power system stabilizer (CPSS) and our contribution of IT2FLCPSS are presented in this paper

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Summary

Hadj Abdallah

Engineering School of Engineering, Department, Engineering School of Engineering School of. University of Sfax, University of Hail, University of Medea, Sfax, University of Sfax, Sfax, University of Sfax, Sfax, Tunisia. Abstract—In this paper, the application of the fuzzy logic based power systems stabilizer (FLPSS) to damp power system oscillation is presented. Various types of fuzzy logic controller are used to replace the conventional power system stabilizer (CPSS). The classic fuzzy logic controller based PSS (FLCPSS), the polar FLC (PFLCPSS) and the interval type-2 fuzzy logic controller based PSS (IT2FLCPSS) are applied to the New England - New York interconnected power system and the obtained results are compared. Genetic algorithm (GA) is used to tune the FLCPSS’s gains. The non-linear simulation in the presence of noise confirms the robustness and the superiority of the IT2FLCPSS

INTRODUCTION
TYPE-2 FUZZY LOGIC SYSTEM DESIGN
FLCPSS and IT2FLC
PFLCPSS
MULTIMACHINE POWER SYSTEM MODEL
Tuning of the Gains
CONCLUSION
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