Abstract
The increasing environmental challenges and global warming concerns have driven a shift towards renewable energy-based power generation, particularly in microgrids. However, marine microgrids face challenges in load-frequency regulation due to renewable energy intermittency, unpredictable load variations, and nonlinear system dynamics. Conventional control strategies often struggle with poor convergence, limited adaptability, and suboptimal frequency stabilization. Addressing these challenges requires an advanced control optimization technique for robust frequency regulation and system stability in dynamic marine environments. This study proposes a Chaotic Chimp-Mountain Gazelle Optimizer (CCMGO) for optimizing fractional-order proportional-integral-derivative (FOPID) controllers, enhancing load-frequency regulation in a multi-source marine microgrid. The system integrates wave energy, wind turbines, solar towers, and photovoltaic energy, along with controlled biogas turbines, micro hydro turbines, and bio-diesel engine generation. To improve frequency stability and grid flexibility, battery energy storage systems, ultra-capacitors, and electric vehicles are incorporated for dynamic compensation. The CCMGO algorithm combines the exploration strength of the mountain gazelle optimizer with solution diversity enhancements from chaotic mapping and chimp optimization algorithm, preventing premature convergence and improving control efficiency. The performance of CCMGO-optimized controllers (PID, PD-PID, FOPI-FOPID, and FOPID) is evaluated under various load conditions, including impulse, ramp, and stochastic disturbances, to test robustness and adaptability. Simulation results demonstrate that CCMGO-based FOPID controllers outperform conventional strategies, achieving lower frequency deviations, faster settling times, and enhanced transient response. These findings establish CCMGO-FOPID as a powerful tool for optimizing control performance in marine microgrids, ensuring greater resilience, stability, and energy efficiency.