Optimal setting gain of PSS-AVR based on particle swarm optimization for power system stability improvement

Muhamad Haddin; Soebagio; Adi Soeprijanto; Mauridhi Hery Purnomo

Optimal setting gain of PSS-AVR based on particle swarm optimization for power system stability improvement

Muhamad Haddin^*, Soebagio, Adi Soeprijanto, Mauridhi Hery Purnomo

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

This paper presents the settings of automatic voltage regulator (AVR) and power system stabilizer (PSS) on a single machine infinite bus (SMIB) to improve the dynamic stability of the power system. This setting is done by determining the fitness function of AVR (K_A) and PSS (K_PSS) gain using Particle Swarm Optimization (PSO) algorithm. The main purpose of this setting is to minimize the oscillation frequency so that it would improve the stability of electric power. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. Simulation results show that the proposed method is very effective for improving the damping of electromechanical oscillations of the power system. The proposed method shows that the power system produces a reduced rate of 11% overshoot and settling time 40%.

Original language	English
Pages (from-to)	42-47
Number of pages	6
Journal	Journal of Theoretical and Applied Information Technology
Volume	42
Issue number	1
Publication status	Published - Aug 2012

Keywords

Dynamic stability
Modified PSO
Setting gain of PSS-AVR

Cite this

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abstract = "This paper presents the settings of automatic voltage regulator (AVR) and power system stabilizer (PSS) on a single machine infinite bus (SMIB) to improve the dynamic stability of the power system. This setting is done by determining the fitness function of AVR (KA) and PSS (KPSS) gain using Particle Swarm Optimization (PSO) algorithm. The main purpose of this setting is to minimize the oscillation frequency so that it would improve the stability of electric power. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. Simulation results show that the proposed method is very effective for improving the damping of electromechanical oscillations of the power system. The proposed method shows that the power system produces a reduced rate of 11% overshoot and settling time 40%.",

keywords = "Dynamic stability, Modified PSO, Setting gain of PSS-AVR",

author = "Muhamad Haddin and Soebagio and Adi Soeprijanto and Purnomo, {Mauridhi Hery}",

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T1 - Optimal setting gain of PSS-AVR based on particle swarm optimization for power system stability improvement

AU - Haddin, Muhamad

AU - Soebagio,

AU - Soeprijanto, Adi

AU - Purnomo, Mauridhi Hery

PY - 2012/8

Y1 - 2012/8

N2 - This paper presents the settings of automatic voltage regulator (AVR) and power system stabilizer (PSS) on a single machine infinite bus (SMIB) to improve the dynamic stability of the power system. This setting is done by determining the fitness function of AVR (KA) and PSS (KPSS) gain using Particle Swarm Optimization (PSO) algorithm. The main purpose of this setting is to minimize the oscillation frequency so that it would improve the stability of electric power. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. Simulation results show that the proposed method is very effective for improving the damping of electromechanical oscillations of the power system. The proposed method shows that the power system produces a reduced rate of 11% overshoot and settling time 40%.

AB - This paper presents the settings of automatic voltage regulator (AVR) and power system stabilizer (PSS) on a single machine infinite bus (SMIB) to improve the dynamic stability of the power system. This setting is done by determining the fitness function of AVR (KA) and PSS (KPSS) gain using Particle Swarm Optimization (PSO) algorithm. The main purpose of this setting is to minimize the oscillation frequency so that it would improve the stability of electric power. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. Simulation results show that the proposed method is very effective for improving the damping of electromechanical oscillations of the power system. The proposed method shows that the power system produces a reduced rate of 11% overshoot and settling time 40%.

KW - Dynamic stability

KW - Modified PSO

KW - Setting gain of PSS-AVR

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JF - Journal of Theoretical and Applied Information Technology

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ER -

Optimal setting gain of PSS-AVR based on particle swarm optimization for power system stability improvement

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Keywords

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