Global limit states for the design of floating wind turbine support structures

Reliability is an essential parameter for offshore wind turbines which are located some distance from the coast in mostly quite harsh environments. Limited weather windows for maintenance and repair work indicate the relevance for using reliability-based methods during the design process of wind turbine structures. This is even more crucial but also more challenging for floating devices due to the highly complex system dynamics and interactions. In this work, the use of global limit states for the design of floating support structures is elaborated. Reliability criteria which are essential for floating wind turbine systems are selected and their critical values are defined. Based on these, the global limit state functions can be set up. Furthermore, the dependencies and predefined boundary conditions of the parameters for the design of floating support structure have to be worked out, so that the modifiable variables can be identified and their effect on the global limit state functions and reliability criteria analysed. This study should serve as basis for developing a reliability-based optimisation tool for the design of floating wind turbine support structures, which uses global limit states and could be extended to consider local characteristics as well

Python-Modelica framework for automated simulation and optimization

Modeling and simulation are essential for the development of complex engineering systems, such as wind turbines. Thus, Fraunhofer IWES (Fraunhofer Institute for Wind Energy Systems) has developed the MoWiT (Modelica for Wind Turbines) library for fully-coupled aero-hydro-servo-elastic simulations of wind turbine systems. To meet the needs for detailed assessment and design development of such sophisticated engineering systems, which imply iterative steps for design optimization, a Python-Modelica framework is set up and presented in this paper. By means of this, the simulation of MoWiT models can easily be managed, including redefinition of model parameters, specification of output sensors and simulation settings, integration of optimization algorithms, post-processing of simulation results, as well as parallel execution of several simulations. The application of this Python-Modelica framework is shown based on the example of a design optimization task of a floating wind turbine support structure

Critical review of floating support structures for offshore wind farm deployment

Floating structures enable offshore wind power deployment at numerous deep water sites with promising wind potential where bottom-fixed systems are no longer feasible. However, the large diversity in existing floater concepts slows down the development and maturing processes of floating offshore wind turbines. Thus, in this work, different floating support structures are assessed with respect to their suitability for offshore wind farm deployment. A survey is conducted to examine the capacities of selected floater types, grouped into ten categories, with respect to ten specified criteria focusing on wind farm deployment. By this means, a multi-criteria decision analysis (MCDA) is carried out, using the technique for order preference by similarity to ideal solution (TOPSIS). With the individual scores of the different systems, considering the weighting of each criterion, suitable concepts are identified and potential hybrid designs, combining advantages of different solutions, are suggested

Development and verification of an aero-hydro-servo-elastic coupled model of dynamics for FOWT, based on the MoWiT library

The complexity of floating offshore wind turbine (FOWT) systems, with their coupled motions, aero-hydro-servo-elastic dynamics, as well as non-linear system behavior and components, makes modeling and simulation indispensable. To ensure the correct implementation of the ulti-physics, the engineering models and codes have to be verified and, subsequently, validated for proving the realistic representation of the real system behavior. Within the IEA Wind Task 23 Subtask offshore code-to-code comparisons have been performed. Based on these studies, using the OC3 hase IV spar-buoy FOWT system, the Modelica for Wind Turbines (MoWiT) library, developed at Fraunhofer IWES, is verified. MoWiT is capable of fully-coupled aero-hydro-servo-elastic simulations of wind turbine systems, onshore, offshore bottom-fixed, or even offshore floating. The hierarchical programing and multibody approach in the object-oriented and equation-based modeling language Modelica have the advantage (over some other simulation tools) of component-based modeling and, hence, easily modifying the implemented system model. The code-to-code comparisons with the results from the OC3 studies show, apart from expected differences due to required assumptions in consequence of missing data and incomplete information, good agreement and, consequently, substantiate the capability of MoWiT for fully-coupled aero-hydro-servo-elastic simulations of FOWT systems

A review of reliability-based methods for risk analysis and their application in the offshore wind industry

Offshore and marine renewable energy applications are governed by a number of uncertainties relevant to the design process and operational management of assets. Risk and reliability analysis methods can allow for systematic assessment of these uncertainties, supporting decisions integrating associated consequences in case of unexpected events. This paper focuses on the review and classification of such methods applied specifically within the offshore wind industry. The quite broad differentiation between qualitative and quantitative methods, as well as some which could belong to both groups depending on the way in which they are used, is further differentiated, based on the most commonly applied theories. Besides the traditional qualitative failure mode, tree, diagrammatic, and hazard analyses, more sophisticated and novel techniques, such as correlation failure mode analysis, threat matrix, or dynamic fault tree analysis, are coming to the fore. Similarly, the well-practised quantitative approaches of an analytical nature, such as the concept of limit states and first or second order reliability methods, and of a stochastic nature, such as Monte Carlo simulation, response surface, or importance sampling methods, are still common practice. Further, Bayesian approaches, reliability-based design optimisation tools, multivariate analyses, fuzzy set theory, and data pooling strategies are finding more and more use within the reliability assessment of offshore and marine renewable energy assets

A fully integrated optimization framework for designing a complex geometry offshore wind turbine spar-type floating support structure

Spar-type platforms for floating offshore wind turbines are considered suitable for commercial wind farm deployment. To reduce the hurdles of such floating systems becoming competitive, in situ aero-hydro-servo-elastic simulations are applied to support conceptual design optimization by including transient and non-linear loads. For reasons of flexibility, the utilized optimization framework and problem are modularly structured so that the setup can be applied to both an initial conceptual design study for bringing innovative floater configurations to light and a subsequent optimization for obtaining detailed designs. In this paper, a spar floater for a 5 MW wind turbine is used as the basis. The approach for generating an initial but very innovative conceptual floater design comprises the segmentation of the floating cylinder into three parts, the specification of a freer optimization formulation with fewer restrictions on the floater geometry, and the allowance for alternative ballast materials. The optimization of the support structure focuses primarily on cost reduction, expressed in terms of the objective to minimize the floater structural material. The optimization results demonstrate significant potential for cost savings when alternative structural and manufacturing strategies are considered

Multi-criteria decision analysis for benchmarking human-free lifting solutions in the offshorewind energy environment

With single components weighing up to hundreds of tonnes and lifted to heights of approximately 100 m, offshore wind turbines can pose risks to personnel, assets, and the environment during installation and maintenance interventions. Guidelines and standards for health and safety in lifting operations exist; however, having people directly beneath the load is still common practice in offshore wind turbine installations. Concepts for human-free offshore lifting operations in the categories of guidance and control, connections, and assembly are studied in this work. This paper documents the process of applying Multi-Criteria Decision Analysis (MCDA), using experts' opinions for the importance of defined criteria obtained by conducting an industry survey, to benchmark the suitability of the concepts at two stages. Stage one streamlined possible options and stage two ranked the remaining suite of options after further development. The survey results showed that criteria such as 'reduction of risk', 'handling improvement' and 'reliability of operation' were most important. The most viable options, weighted by industry opinion, to remove personnel from areas of high risk are: Boom Lock and tag lines, a camera system with mechanical guidance, and automated bolt installation/fastening for seafastening. The decision analysis framework developed can be applied to similar problems to inform choices subject to multiple criteria

Design optimization of the OC3 phase IV floating spar-buoy, based on global limit states

Floating offshore wind turbine (FOWT) systems are a fast-evolving technology, however, still have to gain economic competitiveness to allow commercial market uptake. Design optimization, focusing on cost reduction while ensuring optimum system performance, plays a key role in achieving these goals. Hence, in this work, an approach for optimizing a floating concept, utilizing global limit states, is developed. The optimization is carried out in Python, linked with Modelica and Dymola for modeling and simulation. For the FOWT design, the over-dimensioned OC3 spar-buoy is utilized. This is modified during the optimization regarding its geometrical dimensions and ballasting. The optimization criteria stability, mean and dynamic displacements, and tower top acceleration are used for formulating the objective functions. The optimization is carried out for one design load case, which is most critical for the considered criteria. Based on an initial study, NSGAII is chosen as optimizer. The convergence of the optimization is examined and the optimum design solution selected. In post-processing analyses, the overall performance of the optimized FOWT system is approved. The presented approach shows one example for the design optimization of a FOWT system and should deal as basis for more advanced design optimization tasks, including local characteristics and reliability aspects

Larger MW-class floater designs without upscaling? A direct optimization approach

The trend towards larger offshore wind turbines (WTs) implies the need for bigger support structures. These are commonly derived from existing structures through upscaling and subsequent optimization. To reduce the number of design steps, this work proposes a direct optimization approach, by which means a support structure for a larger WT is obtained through an automated optimization procedure based on a smaller existing system. Due to the suitability of floating platforms for large MW-class WTs, this study is based on the OC3 spar-buoy designed for the NREL 5 MW WT. Using a Python-Modelica framework, developed at Fraunhofer IWES, the spar-buoy geometry is adjusted through iterative optimization steps to finally support a 7.5 MW WT. The optimization procedure focuses on the global system performance in a design-relevant load case. This study shows that larger support structures, appropriate to meet the objective of the hydrodynamic system behavior, can be obtained through automated optimization of existing designs without the intermediate step of upscaling

Human-free offshore lifting solutions

With single elements weighing up to hundreds of tonnes and lifted to heights of 100 meters, offshore wind turbines can pose risks to personnel, assets, and the environment during installation and maintenance interventions. To increase safety during offshore lifts, this study focuses on solutions for human-free lifting operations. Ideas in the categories of logistics, connections, as well as guidance and control, were discussed and ranked by means of a multi-criteria decision analysis. Based upon 38 survey responses weighting 21 predefined decision criteria, the most promising concepts were selected. Logistically, pre-assembled systems would reduce the number of lifts and thus reduce the risk. A MATLAB-based code has been developed to optimise installation time, lifted weight, and number of lifts. Automated bolting and seafastening solutions have high potential to increase safety during the transport of the wind turbine elements and, additionally, speed up the process. Finally, the wind turbine should be lifted on top of the support structure without having personnel being under the load. A multi-directional mechanical guiding element has been designed and tested successfully in combination with visual guidance by cameras in a small-scale experiment