Fractional order PID controller for load frequency control in a deregulated hybrid power system using Aquila Optimization

Abstract

This paper presents an innovative approach for automatic generation control for power system under a deregulated setting. The main objective of this work is to optimally tune the parameters of the fractional-order controller using the newly developed Aquila Optimizer (AO) to enhance system performance. A test system comprising a thermal power plant, a hydroelectric system, a gas turbine-based power plant, and wind energy sources is examined under deregulated environment. The study emphasizes the minimization of frequency variations, tie line deviations, and area control errors during diverse operational shifts. The proposed control strategy explores the response of generators in a hybrid deregulated power system, emphasizing the critical role of properly tuned Fractional Order Proportional-Integral-Derivative (FOPID) controllers in ensuring system stability. The potential and effectiveness of the proposed algorithm are compared with particle swarm optimization (PSO) and whale optimization algorithm (WOA) based controller performance for the same test system. The objective function for optimization is set as the minimization of the integral time and absolute error (ITAE) performance index. Furthermore, the efficacy of the proposed technique is compared with the Unified Power Flow Controller (UPFC) and its superiority is validated. Performance evaluation of the hybrid power system is conducted under Poolco agreement, bilateral agreement, and varying operating conditions. Comparative assessments reveal the superiority of the AO-driven FOPID over other techniques, demonstrating improved system metrics, including frequencies across different areas, tie-line power variations, and generator outputs.