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The design and financing of commercial‐scale floating offshore wind projects require a better understanding of how power generation differs between newer floating turbines and well‐established fixed‐bottom turbines. In floating turbines, platform mobility causes additional rotor motion that can change the time‐averaged power generation. In this work, OpenFAST simulations examine the power generated by the National Renewable Energy Laboratory's 5‐MW reference turbine mounted on the OC3‐UMaine spar and OC4‐DeepCWind semisubmersible floating platforms, subjected to extreme irregular waves and below‐rated turbulent inflow wind from large‐eddy simulations of a neutral atmospheric boundary layer. For these below‐rated conditions, average power generation in floating turbines is most affected by two types of turbine displacements: an average rotor pitch angle that reduces power, caused by platform pitch; and rotor motion upwind‐downwind that increases power, caused by platform surge and pitch. The relative balance between these two effects determines whether a floating platform causes power gains or losses compared to a fixed‐bottom turbine; for example, the spar creates modest (3.1%–4.5%) power gains, whereas the semisubmersible creates insignificant (0.1%–0.2%) power gains for the simulated conditions. Furthermore, platform surge and pitch motions must be analyzed concurrently to fully capture power generation in floating turbines, which is not yet universal practice. Finally, a simple analytical model for predicting average power in floating turbines under below‐rated wind speeds is proposed, incorporating effects from both the time‐averaged pitch displacement and the dynamic upwind‐downwind displacements.

Offshore sites hold great promise for the growth of wind energy. To tap the vast resource in deep water sites, new support structures, such as those that float, are needed. For floating structures to succeed, they must withstand the offshore wind and wave environment. Two new methods for controlling a floating turbine and reducing the platform and blade loads are presented. The first is a method for controlling collective blade pitch and reducing platform pitch motion, a significant problem for floating structures. The rated generator speed is made a function of the platform pitch velocity. When the platform is pitching upwind, the set point generator speed is set to a larger value, and vice versa. For constant generator torque, this approach essentially makes the rated power a variable that depends on the platform pitch velocity. Fundamentally, this control approach trades power variability for platform pitch variability. The results will show substantial reductions in platform pitch motion but minor increases in power variability. Second, an individual blade pitch controller (IPC) designed to reduce blade fatigue loads is implemented for a floating turbine. The IPC approach is commonly utilized for reducing the IP fatigue loads on the blades. The goal of implementing this IPC approach is to investigate how traditional load reduction control, which is successful for onshore turbines, integrates and performs with floating turbines. The results will demonstrate the unique challenge of reducing blade loads on a floating turbine.

The lack of aerodynamic damping of wind turbine blades in the edgewise direction causes larger dynamic responses and lowers the reliability. As blades become longer, edgewise fatigue loading increases rapidly. To mitigate the blade edgewise vibration, structural control techniques using a tuned mass damper (TMD) are applied in this paper. The “TMD” module in FASTv8 was upgraded to enable the high-fidelity simulation of structural control of the blade response. With the developed tool, the optimal parameters and generalized design formulas were established through a parametric study. Also, the control effect of the optimal blade-TMD on reducing fatigue and extreme loads of two different multi-megawatts turbine blades is investigated. Fully-coupled non-linear time marching simulations were conducted by running key design load cases (DLCs) with site-specific meteorological conditions. The results provide insight into the potential benefits and impacts of passive structural control to reduce the fatigue and extreme loads of turbine blades.

A method is developed for using the levelized cost of energy as the objective function for offshore wind farm layout optimization problems. The method converts the cost of energy into a function of turbine position only. To accomplish this, wind speed data are first characterized by direction sector. Continuous functions are then fitted to the Weibull parameters for each direction sector. The wind direction probability density function and the turbine power curve are also transformed into continuous functions. For each turbine in the farm, the continuous function that describes the Weibull scale parameter can be scaled to reflect wake losses from other turbines. The function may also be adjusted according to the variation in wind speed with fetch. The annual energy production of the farm is thus modeled as a function only of the turbine positions. When combined with wind farm cost estimates, the levelized cost of energy is still only a function of turbine position and can then be used as an objective function within a variety of optimization algorithms.

This paper presents a new upscaling methodology for semi-submersible floating offshore wind turbine platforms. The size and power rating of offshore wind turbines have been growing in recent years, with modern wind turbines rated at 10–18 MW in contrast with 2–5 MW in 2010. It is not apparent how much further wind turbine size can be increased before it is unjustified. Scaling relations are a useful method for analyzing wind turbine designs to understand the mass, load, and cost increases with size. Scaling relations currently do not exist but are needed for floating offshore platforms to understand how the technical and economic development of floating offshore wind energy may develop with increasing turbine size. In this paper, a hydrodynamic model has been developed to capture the key platform response in pitch. The hydrodynamic model is validated using OpenFAST, a high-fidelity offshore wind turbine simulation software. An upscaling methodology is then applied to two semi-submersible case studies of reference systems (the Offshore Code Comparison Collaboration Continuation (OC4) 5 MW and the International Energy Agency (IEA) 15 MW). For each case study, the platform pitch angle at rated wind turbine thrust is constrained to a specified value. The results show that platform dimensions scale to a factor of 0.75, and the platform steel mass scales to a factor of 1.5 when the wall thickness is kept constant. This study is the first to develop generalized upscaling relations that can be used for other triangular semi-submersible platforms that have three outer columns with the turbine mounted at the center of the system. This is in contrast with other studies that upscale a specific design to a larger power rating. This upscaling methodology provides new insight into trends for semi-submersible platform upscaling as turbine size increases.

The orientation of a three-legged offshore wind jacket structure in 60 m water depth, supporting the IEA 15 MW reference turbine, has been assessed for optimizing the jacket pile design. A reference site off the coast of Massachusetts was considered, including site-specific metocean conditions and realistically plausible geotechnical conditions. Soil–structure interaction was modeled using three-dimensional finite-element (FE) ground–structure simulations to obtain equivalent mudline springs, which were subsequently used in nonlinear elastic simulations, considering aerodynamic and hydrodynamic loading of extreme sea states in the time domain. Jacket pile loads were found to be sensitive to the maximum 50-year wave direction, as opposed to the wind direction, indicating that the jacket orientation should be considered relative to the dominant wave direction. The results further demonstrated that the jacket orientation has a substantial impact on the overall jacket pile mass and maximum pile embedment depth and therefore represents an important opportunity for project cost and risk reductions. Finally, this research highlights the importance of detailed knowledge of the full global model behavior (both turbine and foundation) for capturing this optimization potential, particularly due to the influence of wind–wave misalignment on pile loads. Close collaboration between the turbine supplier and foundation designer, at the appropriate design stages, is essential.

Wind turbines located in a wind farm are subject to a wind field that is substantially modified when compared to the ambient wind field due to wake effects. It is clear that in addition to the power, a tool that could model the loads of the waked turbine is needed. In this work, a wind farm wake model is created using a single wake model based on the dynamic wake meandering model to systematically model the wake effects and thus the power and loads of an entire wind farm with an arbitrary wind turbine layout and wind condition. This wind farm wake model is incorporated into the National Wind Technology Center design codes. Preliminary results demonstrate that this wind farm tool yields satisfactory results when compared with Simulator for Wind Farm Applications, a high fidelity computational fluid dynamics Large eddy simulation model, and with experimentally-obtained field data. The integration of the wind farm model with the National Wind Technology Center design codes is described in detail and validation results of the tool are provided.

This paper describes the analysis of a wind turbine and support structure subject to simulated hurricane wind fields. The hurricane wind fields, which result from a large eddy simulation of a hurricane, exhibit features such as very high gust factors (>1.7), rapid direction changes (30∘ in 30 s), and substantial veer. Wind fields including these features have not previously been used in an analysis of a wind turbine, and their effect on structural loads may be an important driver of enhanced design considerations. With a focus on blade root loads and tower base loads, the simulations show that these features of hurricane wind fields can lead to loads that are substantially in excess of those that would be predicted if wind fields with equally high mean wind speeds but without the associated direction change and veer were used in the analysis. This result, if further verified for a range of hurricane and tropical storm simulations, should provide an impetus for revisiting design standards.

Floating offshore wind turbines in deep waters offer significant advantages to onshore and near-shore wind turbines. However, due to the motion of floating platforms in response to wind and wave loading, the aerodynamics are substantially more complex. Traditional aerodynamic models and design codes do not adequately account for the floating platform dynamics. Previous research at the University of Massachusetts, Amherst developed the Wake Induced Dynamics Simulator, or WInDS, a free vortex wake model of wind turbines that explicitly includes the velocity components from platform motion. WInDS rigorously accounts for the unsteady interactions between the wind turbine rotor and its wake, however, as a potential flow model, the unsteady viscous response in the blade boundary layer is neglected. This work addressed this concern through the integration of a Leishman-Beddoes dynamic stall model into WInDS. Several improvements to the Leishman-Beddoes dynamic stall model are proposed to improve the synthesis of 2D steady airfoil data and to improve stability when couple with WInDS. The stand-alone dynamic stall model was validated against 2D unsteady data from the OSU pitch oscillation experiments and the coupled WInDS model was validated against three-dimensional data from NREL’s UAE Phase VI campaign. WInDS with dynamic stall shows substantial improvements in load predictions under unsteady conditions. WInDS with the dynamic stall model should provide the necessary aerodynamic model fidelity for future research and design work on floating offshore wind turbines.

The International Electrotechnical Commission (IEC) design standard (IEC 61400-3) for offshore wind turbines includes a design load case which considers loads on the turbine during extreme conditions, when the wind turbine is not operating and the blades are feathered. The recommendation of this design standard is to simulate 6 one-hour periods, each with wind and wave fields modeled as random processes, and to calculate design loads as the mean of the maximum from the six simulations. Previous studies have investigated this recommendation for fixed bottom offshore wind turbines and raised concerns about the stability of the estimate of the design load calculated using these guidelines. The research presented in this paper calculates statistics of extreme design loads as a function of the number of one-hour simulations considered for three offshore wind turbine support structures: a fixed-bottom turbine supported by a monopile and two floating turbines, a spar buoy and a semi-submersible. The study considers one extreme design load, the moment at the tower base, one set of 50-year metocean conditions representive of the Northeast U.S. Atlantic coast, and five combinations of wind and wave models, including linear and nonlinear representations of irregular waves. The data generated from this study are used to assess the stability of the estimate of the extreme load for various numbers of one-hour simulations for each turbine type. The study shows that, for the considered metocean conditions and models, the monopile exhibits the least stability in the estimate of the extreme load and therefore requires more one-hour simulations to have comparable stability as the two floating support structures. Explanations for this result are provided along with a probabilistic formulation for estimating variability of design loads more efficiently, using fewer one-hour simulations.