A computational framework for the co-optimization of platform hydrodynamic and passive structural control of floating offshore wind turbines

Abstract

Floating offshore wind turbines extract rich and stable wind energy in the deep sea. However, they face severe sea conditions and high maintenance costs, and a promising method is needed to generate a high-performing, reliable, and robust design. Traditional sequential methods overlook the coupling between sub-systems and may miss the global optimum. The control co-design method, in contrast, focuses on the integrated optimization of the whole system. However, implementing co-simulation and co-optimization for co-design is challenging. In this study, a control co-design framework is developed and validated to couple the platform hydrodynamics with multi-physical wind turbines for integrated simulations and optimization. Based on this framework, the floating platform and tuned mass damper are co-optimized by establishing an efficient Kriging-enhanced Genetic algorithm. A case study is conducted using a 10 MW floating offshore wind turbine for demonstration. The platform shape and tuned mass dampers are parameterized by five and three design variables, respectively. To minimize platform mass, two formulations are proposed, that is, multi- and single-objective, for scenarios with and without consideration of structural loads. These formulas are solved under pre-defined turbulent wind and irregular wave conditions. Compared to the baseline model, the optimal design significantly reduces platform mass, enhancing both power generation and platform motion stability. After involving structural load in optimization, the optimal platform mass, energy production, and platform motion stability are degraded. These findings demonstrate the effectiveness of the co-design framework in optimizing platform geometry and passive structural control.