Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems

摘要: In the bacteria foraging optimization algorithm (BFAO), chemotactic process is randomly set, imposing that swarm together and keep a safe distance from each other. hybrid particle (hBFOA-PSO) principle of swarming introduced in framework BFAO. The hBFOA-PSO based on adjustment bacterium position according to neighborhood environment. this paper, effectiveness has been tested for automatic generation control (AGC) an interconnected power system. A widely used linear model two area non-reheat thermal system equipped with proportional-integral (PI) controller considered initially design analysis purpose. At first, conventional integral time multiply absolute error (ITAE) objective function performance compared PSO, BFOA GA. Further modified using ITAE, damping ratio dominant eigenvalues settling appropriate weight coefficients proposed increase controller. Further, robustness carried out by varying operating load condition constants speed governor, turbine, tie-line range +50% -50% as well size step perturbation demonstrate optimized PI approach also extended non-linear considering effect governor dead band non-linearity superiority shown comparing results craziness (CRAZYPSO) identical Finally, study three both hydro units different comparison between ANFIS provided.