Design of robust power system stabilizer based on PSO

Babaei, Ebrahim; Galvani, Sadjad; Jirdehi, Mehdi Ahmadi

doi:10.1109/isiea.2009.5356455

Cited by 27 publications

(12 citation statements)

References 16 publications

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“…As shown in this figure when using 4 PSO based tuned PSS, achieve good results and provide superior damping in comparison the conventional method. Setting for the conventional method taken from [1]. Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

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A Novel Method for Detecting Optimal Location and Parameters of Power System Stabilizer (PSS) Based On Intelligent Techniques

E.Saadati¹,

A.Damaki²,

S.Radman³

2015

IJAREEIE

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This paper presents a new technique to design a Power System Stabilizer (PSS) in multi-machine power system. The method is based on the Particle Swarm Optimization (PSO) algorithm for tuning PSS parameters including lead-lag compensator time constants as well as the controller gain. For evaluating the particles evolution throughout the searching process, an eigenvalue-based multi-objective function is used. The DIgSILENT is used as tool for modelling test system and programming PSO algorithm. Then by using a fuzzy approach implemented in Matlab/fuzzy toolbox the optimal number and location for PSSs specified. Two-area (four-machine 11bus) Power system is considered as the case study in this paper. Simulation results for various operating conditions prove the capability of the proposed algorithm in damping improvement of power system.

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Section: Simulation Resultsmentioning

confidence: 99%

“…Tw is usually pre-specified. Thus this parameter is not considered as a control variable and it has been set to 10 in all PSSs [1,5,16]. So the PSS parameters that are consider adjustable and remain to be optimized are the gain KPSS, and time constants T1, T2, T3 and T4.…”

mentioning

confidence: 99%

A Novel Method for Detecting Optimal Location and Parameters of Power System Stabilizer (PSS) Based On Intelligent Techniques

E.Saadati¹,

A.Damaki²,

S.Radman³

2015

IJAREEIE

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“…Particle Swarm Optimization (PSO), a quite popular method of the swarm intelligence family, is suggested in [14][15][16][17] to design robust PSSs. An algorithm of PSO-based fuzzy logic PSSs is proposed in [18] to damp the multimachine power system oscillations.…”

Section: Introductionmentioning

confidence: 99%

Dynamic genetic algorithms for robust design of multimachine power system stabilizers

Alkhatib¹,

Duveau²

2013

International Journal of Electrical Power & Energy Systems

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“…Under these conditions the occurrence of any contingency may lead to instability. 1 Power system stabilizers (PSS) are used as supplementary control devices to provide extra damping and to improve the dynamic performance of the power system. A PSS is basically a phase compensator, designed to provide phase lead to its input signal, which contains information about electromechanical oscillations.…”

Section: Introductionmentioning

confidence: 99%

“…However, it requires a very long run time that may be several minutes or even several hours depending on the size of the system under study. 20 In Babaei et al 1 a PSO-based PSS design with a higher convergence speed than GA was suggested that was based on the time domain response of the power system. It has been reported by Goshal et al 21 that the BFA technique can be considered as soft computing intelligence in the field of power system optimization.…”

Section: Introductionmentioning

confidence: 99%

A new optimization approach for multi-machine power system stabilizer design using a smart bacteria foraging algorithm

2013

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This paper presents a new optimization method for designing the parameters of a power system stabilizer (PSS) using a smart bacteria foraging algorithm (SBFA). The proposed technique, which is a modification of the bacteria foraging method (BFA), can direct bacteria by performing a tumble with a smart unit of length, decreasing the cost function better than the conventional BFA method. This algorithm not only considers social intelligence, but also emphasizes the individual intelligence of bacteria for finding a better nutritional path. A new cost function in the proposed SBFA has been used for specifying the direction of movement after a tumble. This approach led to a higher convergence speed and also better performance than the BFA. The effectiveness of the proposed method has been tested on a multi-machine power system while considering a frequency error-based objective function to enhance damping of the electromechanical oscillation modes. Simulation results for the proposed method are compared with conventional PSS, BFA-and fuzzy-based PSS methods. The results show the superior performance of the proposed SBFA-based PSS in comparison with other techniques for damping power system oscillations. KeywordsSmart bacteria foraging algorithm (SBFA), power system stabilizer, bacteria foraging algorithm (BFA), multi-machine power system.

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Design of robust power system stabilizer based on PSO

Cited by 27 publications

References 16 publications

A Novel Method for Detecting Optimal Location and Parameters of Power System Stabilizer (PSS) Based On Intelligent Techniques

A Novel Method for Detecting Optimal Location and Parameters of Power System Stabilizer (PSS) Based On Intelligent Techniques

Dynamic genetic algorithms for robust design of multimachine power system stabilizers

A new optimization approach for multi-machine power system stabilizer design using a smart bacteria foraging algorithm

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