Fuzzy PID based PSS design using genetic algorithm

Ermanu A. Hakim; Adi Soeprijanto; H. P. Mauridhi

Fuzzy PID based PSS design using genetic algorithm

Ermanu A. Hakim
, Adi Soeprijanto
, H. P. Mauridhi

Universitas Muhammadiyah Malang

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (K _p. K _d, K _I, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system.

Original language	English
Pages (from-to)	1454-1457
Number of pages	4
Journal	World Academy of Science, Engineering and Technology
Volume	38
Publication status	Published - Feb 2009

Keywords

Fuzzy PID
Genetic Algorithm
Power system stabilizer

Cite this

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title = "Fuzzy PID based PSS design using genetic algorithm",

abstract = "This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (K p. K d, K I, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system.",

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author = "Hakim, \{Ermanu A.\} and Adi Soeprijanto and Mauridhi, \{H. P.\}",

year = "2009",

month = feb,

language = "English",

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journal = "World Academy of Science, Engineering and Technology",

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T1 - Fuzzy PID based PSS design using genetic algorithm

AU - Hakim, Ermanu A.

AU - Soeprijanto, Adi

AU - Mauridhi, H. P.

PY - 2009/2

Y1 - 2009/2

N2 - This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (K p. K d, K I, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system.

AB - This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (K p. K d, K I, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system.

KW - Fuzzy PID

KW - Genetic Algorithm

KW - Power system stabilizer

UR - https://www.scopus.com/pages/publications/78651521898

M3 - Article

AN - SCOPUS:78651521898

SN - 2010-376X

VL - 38

SP - 1454

EP - 1457

JO - World Academy of Science, Engineering and Technology

JF - World Academy of Science, Engineering and Technology

ER -

Fuzzy PID based PSS design using genetic algorithm

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Keywords

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