Adaptive-Width Generalized Correntropy Diffusion Algorithm for Robust Control Strategy of Microgrid Autonomous Operation

Abstract

This study introduces a new method for achieving the robust performance of an isolated microgrid (MG) using an adaptive-width generalized correntropy diffusion algorithm (AWGC-DA). In the approach, the width of the kernel is adjustable, allowing the program to reject misleading input from attackers; the technique may identify attackers using a simple identification rule. The Response Surface Methodology is utilized in combination with three optimization algorithms: the Coot bird metaheuristic optimizer (COOT), the sunflower optimization (SFO), and the particle swarm optimization (PSO) to improve the technique's effectiveness. To assess the effectiveness of the new technique, a standard microgrid is tested under three different scenarios: (1) disconnected from the utility grid (autonomous status); (2) variations in load while in autonomous status; and (3) a three-phase fault while in autonomous status. In addition, numerous simulations are performed using the PSCAD/EMTDC software to verify the efficacy of the proposed technique. The main contribution of this study is to enhance the system transients by minimizing the overshoots, steady state error, and settling time which increases the efficacy of the autonomous MG process. Finally, to demonstrate its validity, the performance of the suggested approach is compared to that of other methods, including the LMSRE-based adaptive control, EBS-ABA, COOT, SFO, and PSO algorithms. The results confirm that the AWGC-DA method outperforms the other methods regarding the system's transient response.