Control Co-Design of a Ducted Hydrokinetic Turbine

Focusing on a renewable energy application, this work presents a control co-design (CCD) framework to optimize a ducted hydrokinetic turbine. The optimization aims to improve the techno-economic performance of a baseline design with real flow data. A Kriging-based surrogate model is introduced to capture the hydrodynamics of the ducted turbine concept. A reliable assessment of the deployment site requires year-long simulation, which poses a significant computational challenge. A computationally efficient CCD formulation is presented with failure rate and generator efficiency considerations. This formulation incorporates indirect control variables to reduce computational effort. The findings provide evidence of plant-controller coupling within the system, and highlights the conditions associated with it. A case study is undertaken to substantiate and validate the assumptions made in the formulation. The system optimization results in a net 8% techno-economic performance improvement when compared to a sequentially optimized design.