A hybrid Particle Swarm Optimization and Bacterial Foraging for optimal Power System Stabilizers design

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.

► A hybrid approach involving PSO and BFOA algorithm for designing PSSs is discussed.
► The design problem of PSSs is formulated as an optimization problem.
► The superiority of the BSO in tuning PSSs compared with PSO and BFOA is validated.
► The effectiveness of the proposed controller in damping oscillations is assured.