Abstract

Design optimization, which focuses on cost reduction and at the same time guarantees optimal system performance and high operational reliability, is crucial to accomplishing the aim of achieving economic competitiveness in order to enable a commercial market launch of floating offshore wind turbine technology. Thus, in this chapter, various design optimization tasks are addressed and performed: (1) Within a design optimization approach based on global limit states, geometric dimensions and ballast characteristics of the reference floating support structure are altered during the optimization process, and optimization criteria that focus on the global system performance, comprising the system’s rotational stability, translational motions, and nacelle acceleration, form the objective functions. While only one most critical design load case scenario underlies the simulations within the optimization process, the optimized floating wind turbine system performance in various environmental conditions is approved in post-processing analyses. This approach forms the basis for other design optimization tasks of higher complexity. (2) An alternative, fully integrated optimization approach is adopted to find innovative floater designs. Thus, three cylindrical sections with individual diameters and heights as well as the ballast filling height are the modifiable design variables of the optimization problem, and the optimization objective, which is to minimize the floater structural material, shall represent the overall goal of cost reduction. The applied methodology enables the exploration of alternative structural realization approaches, which free the design from previous stringent limitations on dimensions and configurations. In this way, more innovative and cost-efficient floater designs can be captured. (3) By means of an automated direct optimization approach, a floating structure—appropriate to support a higher MW-class wind turbine and meet the specified optimization objectives and criteria regarding the hydrodynamic system behavior—is obtained from the current reference design directly through optimization, requiring only a few initial adaptations in the numerical model. This approach eliminates the need for intermediate upscaling and therefore reduces the number of design steps.

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