Development and validation of an AI-Driven model for the La Rance tidal barrage: A generalisable case study

In this work, an AI-Driven (autonomous) model representation of the La Rance tidal barrage was developed using novel parametrisation and Deep Reinforcement Learning (DRL) techniques. Our results were validated with experimental measurements, yielding first Tidal Range Structure (TRS) against a constructed made available to academics. order proper Rance, methodologies for simulating (i) turbines (in pumping power generation modes), (ii) transition ramp functions (for opening closing hydraulic structures) (iii) equivalent lagoon wetted area. Furthermore, updated DRL method implemented optimising operation structures that compose Rance. The achieved objective work verify capabilities TRS appropriately predict turbine water level variations. addition, observed operational strategy yearly energy output our appeared be comparable those reported barrage. outcomes (developed implementations) are generalisable can applied other projects. provided insights which allow more realistic simulation operation, enabled through model.