A Comprehensive Review of Intelligent Maximum Power Point Tracking Techniques for Grid-Integrated Tidal Energy Conversion Systems
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Abstract
With the increasing importance of clean and dependable energy production methods, interest in marine renewable energy sources has greatly increased in recent years, particularly tidal energy owing to its predictability and energy density. Maximum Power Point Tracking (MPPT) methods have to be sophisticated in order to extract tidal energy effectively under varying tidal current conditions. This review presents an in-depth study of tidal energy conversion systems along with their MPPT methods and modern optimization techniques. The functioning principles of tidal turbines, Permanent Magnet Synchronous Generators (PMSGs), converters, and grid integration systems are investigated in the work. Comparison of classical MPPT methods (TSR, OTC, and HCS) is provided and their deficiencies under dynamic operating conditions are discussed. In addition, modern advances in intelligent optimization techniques such as Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Neural Networks (ANNs), Fuzzy Logic (FL), and Reinforcement Learning (RL) is investigated in terms of accuracy, speed of convergence, harvesting efficiency, and stability of the system.
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