Optimal tunning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization

El-Zonkoly, Amany; Khalil, Alamgir; Ahmied, Naser M.

doi:10.1016/j.eswa.2007.12.069

Cited by 117 publications

(57 citation statements)

References 16 publications

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“…But, the PSO technique can produce an excellent solution within shorter calculation time and stable convergence characteristic than other stochastic techniques [8]. In fact, PSO is a stochastic global optimization approach based on swarm behavior such as fish and bird schooling in nature [30].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, high performance excitation systems are essential to maintain steady state and transient stability of generators and provide rapid control and recover of terminal voltage [6,7]. The generator excitation system using an automatic voltage regulator (AVR) maintains the terminal voltage magnitude of a synchronous generator to a defined level [8]. It also plays an essential role to control the reactive power and improve the stability.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, a number of various ingenious computation techniques namely: Simulated Annealing (SA) algorithm, Evolutionary Programming (EP), Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) have been employed by scholars to solve the different optimization problems of electrical engineering [8,[18][19][20][21][22][23][24][25][26][27][28][29]. But, the PSO technique can produce an excellent solution within shorter calculation time and stable convergence characteristic than other stochastic techniques [8].…”

Section: Introductionmentioning

confidence: 99%

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Transient Stability Analysis of Power System by Coordinated PSS-AVR Design Based on PSO Technique

Falehi¹,

Rostami²,

Mehrjadi³

2011

ENG

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In this paper, Power System Stabilizer (PSS) and Automatic Voltage Regulator (AVR) are coordinated to improve the transient stability of generator in power system. Coordinated design problem of AVR and PSS is formulated as an optimization problem. Particle Swarm Optimization (PSO) technique is an advanced robust search method by the swarming or cooperative behavior of biological populations mechanism. The performance of PSO has been certified in solution of highly non-linear objectives. Thus, PSO technique has been employed to optimize the parameters of PSS and AVR in order to reduce the power system oscillations during the load changing conditions in single-machine, infinite-bus power system. The results of nonlinear simulation suggest that, by coordinated design of AVR and PSS based on PSO technique power system oscillations are exceptionally damped. Correspondingly, it's shown that power system stability is superiorly enhanced than the uncoordinated designed of the PSS and the AVR controllers.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Transient Stability Analysis of Power System by Coordinated PSS-AVR Design Based on PSO Technique

Falehi¹,

Rostami²,

Mehrjadi³

2011

ENG

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show abstract

“…In essence, the PSS provides a component of electrical torque in phase with speed variations on the rotor [5]. Equipping the generator with PSS, Alleviating the electromechanical oscillations of power system has been increased via providing a supplementary control signal to the excitation system [6][7][8]. Fundamentally, PSS injects a stabilizing signal to Automatic Voltage Regulator (AVR) that modulates the generator excitation and compensates the negative torque of the AVR [9].…”

Section: Introductionmentioning

confidence: 99%

Design and Scrutiny of Maiden PSS for Alleviation of Power System Oscillations Using RCGA and PSO Techniques

Falehi¹

2013

Journal of Electrical Engineering and Technology

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-In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.

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“…Son diversas las aplicaciones que pueden encontrarse de la mano de diferentes autores (Bo et al, 2007;Perez y Behdinan, 2007;Zhang et al, 2008;El-Zonkoly et al, 2009;Marinakis y Marinaki, 2010). Durante esta investigación, la PSO ha demostrado ser potente frente a la solución de varios problemas de optimización (Montalvo et al, 2007b;Izquierdo et al, 2008c;Izquierdo et al, 2008d;Montalvo et al, 2008a;Montalvo et al, 2008b).…”

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Diseño óptimo de sistemas de distribución de agua mediante Agent Swarm Optimization

Arango¹

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Optimal tunning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization

Cited by 117 publications

References 16 publications

Transient Stability Analysis of Power System by Coordinated PSS-AVR Design Based on PSO Technique

Transient Stability Analysis of Power System by Coordinated PSS-AVR Design Based on PSO Technique

Design and Scrutiny of Maiden PSS for Alleviation of Power System Oscillations Using RCGA and PSO Techniques

Diseño óptimo de sistemas de distribución de agua mediante Agent Swarm Optimization

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