Improvement and Stabilization of Output Voltages in a Vertical Tidal Turbine Using Intelligent Control Strategies
Fanambinantsoa Philibert Andriniriniaimalaza, Nour Murad (PIMENT), Randriamaitso Telesphore, Bilal Habachi (SPE), Randriatefison Nirilalaina, Manasina Ruffin, Andrianirina Charles Bernard, Ravelo Blaise (NUIST)

TL;DR
This paper presents AI-based hybrid control strategies, including PSO and ANN-PSO, to improve and stabilize the output voltages of a tidal turbine's generator, enhancing efficiency and reliability.
Contribution
It introduces a novel hybrid ANN-PSO control methodology for optimizing turbine speed and voltage stability in tidal energy systems.
Findings
PSO control significantly improves voltage stability
Hybrid ANN-PSO enhances real-time voltage regulation
Simulation shows increased efficiency at 1.5 m/s water flow
Abstract
This article investigates on the improvement and stabilization of alternating current (AC) and direct current (DC) output voltages in a Permanent Magnet Synchronous Generator (PMSG) driven by a vertical-axis tidal turbine using advanced control strategies. The research integrates artificial intelligence (AI)-based techniques to enhance voltage stability and efficiency. Initially, the Maximum Power Point Tracking (MPPT) approach based on Tip Speed Ratio (TSR) and Artificial Neural Network (ANN) Fuzzy logic controllers is explored. To further optimize the performance, Particle Swarm Optimization (PSO) and a hybrid ANN-PSO methodology are implemented. These strategies aim to refine the reference rotational speed of the turbine while minimizing deviations from optimal power extraction conditions. The simulation results of a tidal turbine operating at a water flow velocity of 1.5 m/s…
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Taxonomy
TopicsWind Turbine Control Systems · Wind Energy Research and Development · Wave and Wind Energy Systems
