Advanced Adaptive Particle Swarm Optimization based SVC Controller for Power System Stability
Автор: Poonam Singhal, S. K. Agarwal, Narendra Kumar
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 1 vol.7, 2014 года.
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The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overcoming the premature convergence & stagnation problems as in basic PSO algorithm & Particle swarm optimization with shrinkage factor & inertia weight approach (PSO-SFIWA). In this paper SMIB system along with PID damped SVC controller is considered for study. The generator speed deviation is used as an auxiliary signal to SVC, to generate the desired damping. This controller improves the dynamic performance of power system by reducing the steady-state error. The controller parameters are optimized using basic PSO, PSO-SFIWA & Advanced Adaptive PSO. Computational results show that Advanced Adaptive based SVC controller is able to find better quality solution as compare to conventional PSO & PSO-SFIWA Techniques.
Small Signal Stability SMIB (single machine on infinite bus bar), SVC (Static Var Compensator), Particle Swarm Optimization (PSO), PSO with Shrinkage Factor & Inertia Weight Approach (PSO-SFIWA), PSO with Time Varying Acceleration Coefficients (PSO-TVAC)
Короткий адрес: https://sciup.org/15010651
IDR: 15010651
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