Type-2 Fuzzy Logic Controller Based PSS for Large Scale Power Systems Stability

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 13 Oct 2018Publisher:Engineering, Technology & Applied Science ResearchJournal:Engineering, Technology & Applied Science Research, volume 8, pages 3,380-3,386 (issn: 2241-4487, eissn: 1792-8036,

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Authors: Omar Kahouli; B. Ashammari; Karim Sebaa; Meriam Djebali; Hsan Hadj Abdallah;

doi: 10.48084/etasr.2234 , 10.5281/zenodo.1490363 , 10.60692/xn033-ng063 , 10.60692/acwtj-sm538 , 10.5281/zenodo.1490364

Type-2 Fuzzy Logic Controller Based PSS for Large Scale Power Systems Stability

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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.

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Keywords

Artificial intelligence, FLCPSS, Robustness (evolution), Control Systems, Control (management), Biochemistry, Quantum mechanics, Gene, Electric power system, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), Electrical and Electronic Engineering, Biology, Load Frequency Control, PFLCPS, Control engineering, Physics, Load Frequency Control in Power Systems, Controller (irrigation), GA, CPSS, Power System Stability and Control Analysis, Power Systems, Power (physics), Computer science, Agronomy, IT2FLPSS, Intelligent Control, Integration of Distributed Generation in Power Systems, Fuzzy logic, Chemistry, Fuzzy control system, Physical Sciences, Power System Stability, prony analysis

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