A Review Study on Optimization of Load Frequency Control in Marine Microgrid Systems Using Advanced Controllers and Algorithms

ABSTRACT

Marine microgrids are gradually adopted in modern shipboard power systems; however, maintaining frequency stability under varying load conditions and operational uncertainties remains a main challenge. The objective of this study is to systematically review and examine the optimization of load frequency control (LFC) in marine microgrid systems using advanced controllers and intelligent optimization algorithms. The methodology includes a comprehensive review of literature on classical and modern LFC techniques, dynamic modeling approaches, innovative control strategies, metaheuristic optimization methods, and machine learning‐based solutions for frequency regulation. The key results specify that conventional PI/PID controllers provide basic frequency control but exhibit limitations under highly dynamic marine conditions. Advanced controllers, including adaptive, robust, optimal, and intelligent control strategies, validate improved frequency regulation, stability, and disturbance rejection capabilities. Also, optimization algorithms such as particle swarm optimization, genetic algorithms, and machine learning techniques enhance controller tuning, system robustness, and dynamic response. Comparative analysis shows that hybrid approaches combining advanced control methods with optimization algorithms offer superior performance compared to standalone techniques. In conclusion, optimized LFC is vital for reliable marine microgrid operation, and hybrid intelligent control frameworks signify the most promising solution. Future research should focus on lightweight, real‐time adaptive models to overcome computational and implementation challenges while confirming sustainable and resilient marine power system performance.