Abstract
Ocean current turbines (OCTs) offer a promising pathway to expand marine energy capacity by harnessing consistent underwater currents such as the Gulf Stream. However, face OCTs face technical and economic risks due to inefficient energy capture and structural fatigue caused by dynamic marine environments. A hybrid modeling and simulation framework is presented for evaluating and optimizing blade-level control in OCTs using active Twist Angle Distribution (TAD). The approach reduces fatigue loading by enabling localized control over blade shape while enhancing hydrodynamic performance.
The proposed method integrates CFD simulations in STAR-CCM+, OpenFAST models, and machine learning to evaluate the benefits of shape-adaptive OCT blades. A genetic algorithm optimizes the TAD, using neural networks trained on OpenFAST simulations to serve as surrogate models. Data-driven models enable efficient design space exploration and reduce computational time. The virtual disk model in STAR-CCM+ is used to simulate wake dynamics and assess downstream flow characteristics associated with TAD variations.
A test case using Reference Model 1 (RM1) demonstrates the effectiveness of this approach in controlled simulations. RM1’s dual-rotor, monopile-mounted configuration allows for detailed evaluation of blade performance without platform dynamics. Simulations show that optimized twist profiles can achieve up to a 23.09% reduction in fatigue loading for composite materials under constant flow conditions. These findings support the feasibility of integrating adaptive control strategies in OCT design, contributing to reduced operations and maintenance (O&M) costs and longer component life.
The optimization strategy combines device design, reliability, and economic performance. Incorporating fatigue-driven cost factors into the optimization process enables OCT designers to consider lifecycle impacts and Levelized Cost of Energy (LCOE) from the outset. The hybrid framework also supports scenario-based analysis, enabling comparisons across TAD profiles, flow conditions, and material types.
Future work will validate the closed-loop interface between the CFD model and the TAD search algorithm, expand the simulation campaign to cover variable ocean conditions and incorporate environmental impact metrics such as wake interaction and flow recovery. The approach aims to advance the economic and environmental viability of OCTs, supporting the deployment of marine energy systems.