• Energy Research

Abstract. The structural optimization problem of jacket substructures for offshore wind turbines is commonly considered as a pure tube dimensioning problem with given topology, minimizing the entire mass of the structure. However, this approach goes along with the assumption that the given topology is fixed in any case. The present work contributes to the improvement of the state of the art by utilizing more detailed models for geometry, costs, and structural design code checks. They are assembled in an optimization scheme, in order to consider the jacket optimization problem from a different point of view that is closer to practical applications. The objective function is replaced by a sum term comprising several cost terms. To address the issue of high demand of numerical capacity, a machine learning approach based on Gaussian process regression is applied to reduce numerical cost and enhance the number of considered design load cases. The proposed approach is meant to provide decision guidance in the first phase of wind farm planning. A numerical example for a NREL 5 MW turbine under FINO3 environmental conditions is computed by two effective optimization methods (sequential quadratic programming and an interior-point method), allowing for the estimation of characteristic design variables of a jacket substructure. In order to resolve the mixed-integer problem formulation, multiple subproblems with fixed integer design variables are solved. The approach shows reasonable and promising results, useful both for further research and technical applications.

Abstract. In the last decades, the unsteady vortex-lattice method (UVLM) has gained a lot of acceptance to study large onshore–offshore wind turbines (WTs). Furthermore, and due to the development of more powerful computers, parallelization strategies, and algorithms like the fast multipole method, it is possible to use vortex-based methods to analyze and simulate wind farms (WFs). However, UVLM-based solvers require structured meshes, which are generally very tedious to build using classical mesh generators, such as those utilized in the context of finite element methods (FEMs). Wind farm meshing is further complicated by the large number of design parameters associated with the wind turbine (coning angle, tilt angle, blade shape, etc.), farm layout, modeling of the terrain topography (for onshore WFs), and modeling of the sea level surface (for offshore WFs), which makes the use of FEM-oriented meshing tools almost inapplicable. In the literature there is a total absence of meshing tools when it comes to building aerodynamic grids of WTs and WFs to be used along with UVLM-based solvers. Therefore, in this work, we present a detailed description of the geometric modeling and computational implementation of an interactive UVLM-oriented mesh generator, named UVLMeshGen, developed entirely in MATLAB® and easily adaptable to GNU OCTAVE, for wind turbines and onshore–offshore wind farms. The meshing tool developed here consists of (i) a geometric processor in charge of designing and discretizing an entire wind farm and (ii) an independent module in charge of computing the kinematics for the entire WF. The output data provided by the UVLMeshGen consist of nodal coordinates and connectivity arrays, making it especially attractive and useful to be used by other flow potential solvers using vortices, sources and sinks, or dipoles/doublets, among others. The work is completed by providing a series of aerodynamic results related to WTs and WFs to show the capabilities of the mesh generator, without going into detailed discussions of wind turbine aerodynamics, which are not the focus of this paper. The meshing tool developed here is freely available under a Creative Commons Attribution 4.0 International License (Roccia, 2023).

Abstract Offshore wind energy is a seminal technology to achieve the goals set for renewable energy deployment. However, today's offshore wind energy projects are mostly not yet sufficiently competitive. The optimization of offshore wind turbine substructures with regard to costs and reliability is a promising approach to increase competitiveness. Today, interdisciplinary analyses considering sophisticated engineering models and their complex economic effects are not widespread. Existing approaches are deterministic. This research gap is addressed by combining an aero-elastic wind turbine model with an economic viability model for probabilistic investment analyses. The impact of different monopile designs on the stochastic cost-efficiency of an offshore wind farm is investigated. Monopiles are varied with regard to diameters and wall thicknesses creating designs with increased lifetimes but higher capital expenditures (durable designs) and vice versa (cheaper designs). For each substructure, the aero-elastic wind turbine model yields distributions for the fatigue lifetime and electricity yield and different capital expenditures, which are applied to the economic viability model. For other components, e.g. blades, constant lifetimes and costs are assumed. The results indicate that the gain of increased stochastic lifetimes exceeds the benefit of reduced initial costs, if the overall lifetime is not governed by other turbine components' lifetimes.

Abstract. The main obstacles in preliminary design studies or optimization of jacket substructures for offshore wind turbines are high numerical expenses for structural code checks and simplistic cost assumptions. In order to create a basis for fast design evaluations, this work provides the following: first, a jacket model is proposed that covers topology and tube sizing with a limited set of design variables. Second, a cost model is proposed that goes beyond the simple and common mass-dependent approach. And third, the issue of numerical efficiency is addressed by surrogate models for both fatigue and ultimate limit state code checks. In addition, this work shows an example utilizing all models. The outcome can be utilized for preliminary design studies and jacket optimization schemes. It is suitable for scientific and industrial applications.

Abstract. In the last decades, the unsteady vortex-lattice method (UVLM) has gained a lot of acceptance to study large onshore/offshore wind turbines (WTs). Furthermore, and due to the development of more powerful computers, parallelization strategies and algorithms like the fast multipole method, it is possible to use vortex-based methods to analyze and simulate wind farms (WFs). However, UVLM-based solvers require structured meshes, which are generally very tedious to build using classical mesh generators, such as those utilized in the context of finite element methods (FEMs). Wind farm meshing is further complicated by the large number of design parameters associated with the wind turbine (pre-cone angle, tilt angle, blade shape, etc.), farm layout, modeling of the terrain topography (for onshore WFs), and modeling of the sea level surface (for offshore WFs), which makes the use of FEM-oriented meshing tools almost inapplicable. In the literature there is a total absence of meshing tools when it comes to building aerodynamic grids of WTs and WFs to be used along with UVLM-based solvers. Therefore, in this work, we present a detailed description of the geometric modeling and computational implementation of an interactive UVLM-oriented mesh generator, named UVLMeshGen, developed entirely in Matlab® and easily adaptable to GNU OCTAVE, for wind turbines and onshore/offshore wind farms. The meshing tool developed here consists of: i) a geometric processor in charge of designing and discretizing an entire wind farm; and ii) an independent module in charge of computing the kinematics for the entire WF. The output data provided by the UVLMeshGen consist of nodal coordinates and connectivity arrays, making it especially attractive and useful to be used by other flow potential solvers using: doublets, sources and sinks, or dipoles, among others. The work is completed by providing a series of aerodynamic results related to WTs and WFs to show the capabilities of the mesh generator, without going into detailed discussions of wind turbine aerodynamics, which are not the focus of this paper. The meshing tool developed here is freely available under a Creative Commons Attribution 4.0 International License Roccia (2023).

Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.

AbstractFor substructures of offshore wind turbines, the fatigue limit state is in most cases a decisive design factor. However, to calculate the fatigue lifetime of wind turbines, numerous time domain simulations for different load cases with changing environmental conditions are necessary. According to the state of the art, wind speed bins (of 2 m s−1) are employed, while keeping all other environmental states constant. However, assuming constant parameters in each wind speed bin is an unfounded simplification. Therefore, in this study, methodologies for fatigue assessment considering scattering environmental conditions are investigated by assuming statistical distributions for environmental conditions for all wind speeds that are derived using real data measured at the North Sea research platform FINO3. These statistical distributions are used to conduct time domain simulations of an OC3 monopile—with a 5‐MW wind turbine—using the aero‐servo‐hydro‐elastic simulation framework FAST. The fatigue lifetime is calculated, and its uncertainty due to finite sampling is assessed. It is shown that if scattering environmental states in each wind speed bin are applied, the uncertainty due to finite sampling is significant. Furthermore, only some wind speed bins contribute to the overall fatigue damage. Based on these findings, in a last step, different Monte Carlo sampling concepts are investigated to reduce the number of simulations needed to calculate the fatigue lifetime with a defined uncertainty. By combining several wind speed bins and by sampling according to the damage distribution, it is proved that the number of simulations can be reduced by more than 30% without increasing the uncertainty.