APPLICATION AND COMPARATIVE PERFORMANCE ANALYSIS OF PSO AND ABC ALGORITHMS FOR OPTIMAL DESIGN OF MULTI-MACHINE POWER SYSTEM STABILIZERS

Serdar Ekinci
1.328 241

Abstract


This paper presents the application and performance comparison of PSO and ABC optimization techniques, for multi-objective design of power system stabilizers (PSSs) in the multi-machine power system. The design objective is to improve the power system stability. The PSSs parameters tuning problem is converted to an optimization problem with the time domain-based objective function and both PSO and ABC optimization techniques are used to search for optimal stabilizers parameters. The optimized stabilizers are tested on multi-machine electric power system subjected to different disturbances. The performance of both optimization techniques in terms of computational time, convergence rate and solution quality is compared. The eigenvalue analysis, nonlinear time-domain simulation results, critical clearing times and some performance indices studies are introduced and compared in order to demonstrate the effectiveness of both optimization techniques in designing stabilizers, to enhance the dynamic stability of the system. What is more, the potential and superiority of the ABC algorithm over the PSO algorithm are verified.


Keywords


Artificial Bee Colony (ABC) algorithm; Particle Swarm Optimization (PSO); PSS design; dynamic stability; multi-machine power system.

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