Ekinci, Serdar2019-07-032019-07-032016-06-20Ekinci, S . (2016). Application and comparative performance analysis of PSO and ABC algorithms for optimal design of multimachine power system stabilizers. Gazi University Journal of Science, 29 (2), pp. 323-334.2147-1762https://hdl.handle.net/20.500.12402/2171This 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 timedomain 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.eninfo:eu-repo/semantics/openAccessAttribution-ShareAlike 3.0 United StatesArtificial Bee Colony (ABC) AlgorithmParticle Swarm Optimization (PSO)PSS DesignDynamic StabilityMulti-Machine Power SystemApplication and comparative performance analysis of PSO and ABC algorithms for optimal design of multimachine power system stabilizersArticleQ3N/A