A hybrid Particle Swarm Optimization and Bacterial Foraging for optimal Power System Stabilizers design |
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| Affiliation: | 1. CTVR, Department of Computer Science, University College Cork, Ireland;2. Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada;1. Engineering Mathematics and Physics Department, Faculty of Engineering, Fayoum University, Egypt;2. Engineering Mathematics and Physics Department, Faculty of Engineering, Cairo University, Egypt;3. Electrical Engineering and Computer Science Department, University of California-Irvine, Irvine, USA;4. King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia;1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;2. Engineering Faculty, Near East University, POBOX:99138, Nicosia, North Cyprus, Mersin 10, Turkey |
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| Abstract: | A novel hybrid approach involving Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization Algorithm (BFOA) called Bacterial Swarm Optimization (BSO) is illustrated for optimal Power System Stabilizers (PSSs) design in a multimachine power system. In BSO, the search directions of tumble behavior for each bacterium are oriented by the individual’s best location and the global best location of PSO. The proposed hybrid algorithm has been extensively compared with the original BFOA algorithm and the PSO algorithm. Simulation results have shown the validity of the proposed BSO in tuning PSSs compared with BFOA and PSO. Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power system stability over a wide range of loading conditions and various disturbances. |
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