Frequency Control for a Stand-alone Micro-grid System using Honey Badger Algorithm

In a micro-grid (μ G) power system, the presence 0 critical loads and Renewable Energy (RE) sources leads to frequency oscillations, increased control error, and diminished system inertia due to an imbalance between demand and supply To address these challenges, Load Frequency Control (LFC) i employed to regulate frequency and enhance controlles performance during steady-state operation. Therefore, advanced, rapid, and effective algorithm is required for accurate tuning that can simultaneously decrease control error while improving controller performance and dynamics. In this study a newly developed optimization technique called the Honey Badger Algorithm (HBA) is utilized to fine-tune the LFC cascaded 2-Degree of Freedom (DOF) Proportional Integral (PI) and Proportional Derivative (PDF) controller for an independent μ G. The proposed algorithm significantly improves frequency dynamics, reducing peak deviation by 98.23% in comparison to alternative methods like Genetic Algorithm (GA) Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), and Crow Search Algorithm (CSA) under the best-performing Performance Index Criteria (PIC) individually.