Dynamic Analysis and Structural Optimization of Support Structures for bottom-fixed Offshore Wind Turbines

Abstract

Wind energy is recognized as a reliable and affordable source of energy for generating electricity. Up to date most of the wind energy capacity is installed onshore, but legal regulations and a shortage of potential locations limit its expansion. An attractive alternative for the further expansion of wind energy is the establishment of offshore wind farms. Offshore wind turbines require a support structure. Its design is typically adapted for the specific site conditions encountered, but is often not fully optimized. The limiting factor is the optimization process itself. It is a challenging task due to a large number of parameters, the complex numerical models, and numerous load analyses. The most accurate analysis method currently available requires lengthy simulations in the time domain, since offshore wind turbines are highly dynamic and tightly coupled systems and are subjected to nonlinear and time history dependent effects. The research activities within the scope of this thesis aim to enhance the design optimization of offshore wind turbine support structures. The focus is on bottom fixed support structures, such as jackets and monopiles. The overall objective is to contribute to a better understanding of specific issues related to the dynamic analysis and optimization problem. Methods to accelerate the dynamic analysis as well as smart and computer aided optimization algorithms are investigated. Decoupled analysis methods where aerodynamic damping is represented by single dashpots on tower top were investigated. It is shown that this analysis method can provide quick results for conceptual studies with acceptable differences (at most 2.5 %) compared to an integrated analysis. GPU accelerated impulse based substructuring allowed to obtain time series for reaction forces and moments forty times faster compared to specialized commercial available state of the art software. The easy implementation of GPU programming makes it an approach with great potential for academic as well as industrial implementation. Several optimization algorithms were investigated. Utilizing a genetic algorithm showed that an automated optimization including the topology of a lattice support structure is feasible. The implementation is straightforward, but finding an optimal design solution might become computationally demanding due to the stochastic nature of the algorithm. A method to reduce the number of iterations necessary for the algorithm to converge by one third is presented. A second gradient free optimization algorithm that allows for an automated optimization is the local optimization approach. It only requires around six analyses in time domain to find an optimal solution. Implementing a computer aided optimization algorithm is the first step of an automated optimization. Achieving an optimised design solution within an acceptable time frame and reasonable computational effort additionally requires a dynamic analysis of the offshore wind turbine that is faster than the current simulations in time domain. It is shown that faster alternatives exist, but the required accuracy has not yet been achieved. Algorithms as well as analysis method have to be further extended and improved.