Efficient optimization design method of jacket structures for offshore wind turbines

Abstract

With the gradual implementation of offshore wind energy production, the future tendency is to expand into the deeper water. The jacket foundations will take the place of the present monopile foundations when the water depth increases. The foundations account for the majority of the construction cost for offshore wind farms, and the structural optimization of jackets will bring lucrative economic benefits. Structural optimization is a complex iterative process that requires huge computing costs. Therefore, this paper proposes a structural optimization method based on surrogate models to solve this problem effectively and swiftly obtain optimized design schemes of lightweight jackets for offshore wind turbines. The structural responses of jacket wind turbine systems under the equivalent static extreme loads with a recurrence period of 50 years are mainly considered in structural optimization design, and the key optimization variables of jackets are determined by parameter sensitivity analysis. The finite element models of jackets are transformed into surrogate models, and the genetic algorithm is employed to optimize the surrogate models directly. The optimized jackets are additionally verified through coupled dynamic analysis, besides, buckling strength and fatigue life are also checked. And local refined optimizations are carried out for the failure members. According to the optimized design schemes of lightweight jackets for 30 m, 50 m and 70 m water depths, it is demonstrated that the structural optimization design method is adequate and efficient for jackets of wind turbines. Parameter sensitivity analysis can cut the number of optimization variables in half to improve the optimization efficiency. Furthermore, the application of surrogate models can significantly speed up the optimization process by saving about 98.61% of the original time consumed. The optimization design method of the jackets for offshore wind turbines proposed in this paper is suitable for practical engineering, with high precision and efficiency.