Grey wolf optimizer based regulator design for automatic generation control of interconnected power system

This paper presents an application of grey wolf optimizer (GWO) in order to find the parameters of primary governor loop for successful Automatic Generation Control of two areas’ interconnected power system. Two standard objective functions, Integral Square Error and Integral Time Absolute Error (ITAE), have been employed to carry out this parameter estimation process. Eigenvalues along with dynamic response analysis reveals that criterion of ITAE yields better performance. The comparison of the regulator performance obtained from GWO is carried out with Genetic Algorithm (GA), Particle Swarm Optimization, and Gravitational Search Algorithm. Different types of perturbations and load changes are incorporated in order to establish the efficacy of the obtained design. It is observed that GWO outperforms all three optimization methods. The optimization performance of GWO is compared with other algorithms on the basis of standard deviations in the values of parameters and objective functions.