Performance Evaluation of Antlion Optimizer Based Regulator in Automatic Generation Control of Interconnected Power System

Abstract

This paper presents an application of the recently introduced Antlion Optimizer (ALO) to find the parameters of primary governor loop of thermal generators for successful Automatic Generation Control (AGC) of two-area interconnected power system. Two standard objective functions, Integral Square Error (ISE) and Integral Time Absolute Error (ITAE), have been employed to carry out this parameter estimation process. The problem is transformed in optimization problem to obtain integral gains, speed regulation, and frequency sensitivity coefficient for both areas. The comparison of the regulator performance obtained from ALO is carried out with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA) based regulators. Different types of perturbations and load changes are incorporated to establish the efficacy of the obtained design. It is observed that ALO outperforms all three optimization methods for this real problem. The optimization performance of ALO is compared with other algorithms on the basis of standard deviations in the values of parameters and objective functions.