Control Co-Design of Hydrokinetic Turbines Considering Dynamic–Hydrodynamic Coupling

Hydrokinetic turbine (HKT) controllers are traditionally optimized after determining physical turbine variables. However, simultaneously varying controls and turbine shape by considering the interactions between the control space and the turbine shape can significantly enhance the system performance in contrast to the conventional sequential design approach. This article delves into this prospect by introducing a control co-design (CCD) framework tailored for this simultaneous optimization for a variable-speed HKT rotor. The proposed CCD framework integrates a dynamic–hydrodynamic model that captures the intricate interplay between hydrodynamic performance and control strategies for the HKT under time-varying flow profiles. We systematically investigate cases with diverse control constraints in a time-varying flow environment to explore the coupling between the control space and the physical system. We demonstrate the advantages of the CCD framework over the conventional sequential design methodology through comparative study cases. CCD optimization considering a single flow condition leads to an overly specialized design that underperforms at other off-design conditions. The stochastic nature of the flow thereby highlights the need to account for a broader range of flow speeds in the HKT design process. To address this challenge, we introduce a multipoint CCD optimization that accounts for the annual flow probability distribution. The multipoint CCD approach demonstrates higher annual energy extraction compared to optimizations based on a single flow condition.