Optimal Design of Power System Stabilizer Using Particle Swarm Optimization

By Zhao Hui. 2006

502 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/03ec461a73a1e42ff09616ae2a2873e1d8a2fdc5

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Citations in the corpus

Calibration of a water and energy balance model: Recursive parameter estimation versus particle swarm optimization (2009, background): “Furthermore, the algorithm has a lesser tendency of getting trapped in local minima and the balance between the global and local exploration of the search space can be controlled [Engelbrecht, 2006; Abido, 2002].”
On the computation of all global minimizers through particle swarm optimization (2004, background): “Among other applications, it has been applied to tackle multiobjective problems [14]–[19], minimax problems [20], [21], integer programming problems [22], noisy and continuously changing environments [23]–[26], errors-in-variables problems [27], existence of function zeros [28], and numerous enginee”
Analysis of the publications on the applications of particle swarm optimisation (2008, background): “6 Journal of Artificial Evolution and Applications cooker design, VLSI design, RF circuit synthesis [22], worst case electronic design, filter design [23], antenna design [24], CMOS wideband amplifier design, motor design, logic circuits design, power systems [25], transmission lines, mechanical des”
Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives (2008, unknown): “It has been applied to evolve weights and structure of neural networks [38–40], analyze human tremor [41], register 3Dto-3D biomedical image [42], play games [43], control reactive power and voltage [44, 45], pattern recognition [46], etc.”
A particle swarm optimization for economic dispatch with nonsmooth cost functions (2005, methodology): “Recently, PSO have been successfully applied to various fields of power system optimization such as power system stabilizer design [5], reactive power and voltage control [3], and dynamic security border identification [6].”
A Survey of Particle Swarm Optimization Applications in Electric Power Systems (2009, methodology): “In [37] and [38], PSO was employed to find the optimal settings of power system stabilizer parameters.”
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems (2008, methodology): “1) Controller Tuning: Specifically, PSO has been proposed in the literature as an efficient algorithm to tune the gains in classical PID controllers, as well as in nonlinear controllers [195]–[201].”