Impact of control strategies on the control co-design of spar floating offshore wind turbines

Offshore wind energy has the potential to transform global energy systems by providing clean and sustainable power. Optimizing both plant and control design is crucial for realizing this potential. This paper examines the impact of Open-Loop Optimal Control (OLOC), Model Predictive Control (MPC), and the ROSCO Controller on the Control Co-Design (CCD) of spar floating offshore wind turbines. By integrating plant and control design, we evaluate performance and feasibility under each strategy. Results show that OLOC achieves the highest Annual Energy Production (AEP) by leveraging full system information, while MPC balances performance and computational cost. The ROSCO controller, with its fixed structure, offers a straightforward implementation but faces challenges in meeting certain constraints. We analyze the role of MPC prediction horizon and the impact of control strategy mismatches between CCD and practical implementation. Findings highlight the need to account for practical constraints during design to minimize performance losses. Additionally, we explore AEP sensitivity to key design variables under different controllers, identifying critical factors for optimization. These insights contribute to advancing offshore wind turbine design by improving performance and reducing costs.