A method for performing numerical wind resource assessments in the absence of on-site measurements is presented and validated against field measurements. Numerical wind resource assessment is at least 2 orders of magnitude faster and less expensive than using conventional site measurements. This enables analysis of a larger number of projects and thereby increases the chances of discovering the best available sites. The uncertainty in mean wind speed predictions is found to be about 4 %.

Recently, there has been an increased awareness of leading-edge erosion of wind turbine blades. An option to mitigate the erosion at the leading edges is the deceleration of the wind turbine blades during severe precipitation events. This work shows that a vertically pointing radar can be used to nowcast precipitation events with the required spatial and temporal resolution. Furthermore, nowcasting allows a reduction in the rotational speed prior to the impact of precipitation on the blades.

This paper introduces the Tocha wind farm, presents the different layouts adopted in the instrumentation of the wind turbines and shows initial results. At this preliminary stage, the capabilities of the very extensive monitoring layout are demonstrated. The results presented demonstrate the ability of the different monitoring components to track the modal parameters of the system, composed of tower and rotor, and to characterize the internal loads at the tower base and blade roots.

Model error and uncertainty is a challenge in the wind energy industry, potentially leading to mischaracterization of millions of dollars' worth of wind resource. This paper combines meteorological knowledge with machine learning techniques, specifically artificial neural networks (ANNs), to better extrapolate wind speeds. It is found that ANNs can reduce power-law extrapolation error by up to 52 % while simultaneously reducing uncertainty. A test case is shown to help decipher the ANN results.

This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.

Converting an upwind wind turbine into a downwind configuration is shown to come with higher edgewise loads due to lower edgewise damping. The study shows from modal displacements of a reduced-order turbine model that the interaction between the forces on the rotor, the rotor motion, and the tower torsion is the main reason for the observed damping decrease.

Flatback airfoils are used in the root region of wind turbine blades since they have several structural and aerodynamic benefits. Several flow control devices are incorporated to mitigate the effects of vortex shedding in the wake of such airfoils. In this work, two different numerical approaches are compared to wind tunnel measurements to assess the suitability of each method for predicting the performance of the flow control devices in terms of loads and unsteady characteristics.

A huge number of wind turbines have reached their designated lifetime of 20 years. Most of the turbines installed were overdesigned. In practice, these turbines could potentially operate longer to increase the energy yield. For the use case turbine considered in this work, a simple lifetime extension of 8.7 years increases the energy yield by 43.5 %. When the swept rotor area is increased by means of a blade tip extension, the yield is increased by an additional 2.3 %.

The article describes a hybrid modeling approach to optimize the energy capture of wind farms. Hybrid modeling combines mechanistic and data-driven models. The data-driven part is used to correct inaccuracies of the mechanistic model. The hybrid approach allows for adjustment of the mechanistic model beyond simple parameter estimation. It is, therefore, an attractive approach in wind farm control. The approach is illustrated in several numerical case studies.

The paper compares actuator discs in propeller and wind turbine mode. At very low rotational speed, propeller discs have an expanding wake while still energy is put into the wake. The velocity at the disc in the plane containing the axis is practically uniform: a few per mille deviation for wind turbine discs and a few per cent for propeller discs. The deviations are caused by the different strengths of the singularity in the wake boundary vorticity strength at its leading edge.

This paper validates a method to estimate the vertical wind shear and detect the presence and location of an impinging wake with field data. Shear and wake awareness have multiple uses, from turbine and farm control to monitoring and forecasting. Results indicate a very good correlation between the estimated vertical shear and the one measured by a met mast and a remarkable ability to locate and track the motion of an impinging wake on an affected rotor.

This paper addresses the topic of far-offshore wind energy exploitation. Far-offshore wind energy exploitation is not feasible with grid-connected floating wind turbines because grid-connection cost, installation cost and O&M cost would be prohibitive. An enabling technology is the energy ship concept, which is described and modeled in the paper. A design of an energy ship is proposed. It is estimated that it could produce 5 GWh per annum of chemical energy (methanol).

This study presents a marriage of unsteady aerodynamics and machine learning. When airfoils are subjected to high inflow angles, the flow no longer follows the surface and the flow is said to be separated. In this flow regime, the forces experienced by the airfoil are highly unsteady. This study uses a range of machine learning techniques to extract infomation from test data to help us understand the flow regime and makes recomendations on how to model it.

Wind turbine rotors are usually designed to maximize power performance, accepting any loading results. However, from the most basic wind turbine theory, actuator disc theory, two other optimization paths are demonstrated, which may lead to more cost-effective technology – the low-induction rotor where an expanded rotor diameter and some extra power is achieved without increasing the blade root bending moment and the secondary rotor which can provide a very low torque and low-cost drivetrain.

Vortex-induced vibrations are structural vibrations that can occur due to the shedding of flow vortices when a fluid flow passes around a structure. Here, conditions specific to wind turbine towers are investigated numerically. The work highlights a complex interplay between structural and fluid dynamics. In particular, certain conditions lead to a continuous alternation between self-exciting and self-limiting vortex-induced vibrations, linked to a change in the sign of the aerodynamic damping.

This study presents a measurement campaign, which consists of two nacelle-mounted lidar systems in a densely packed onshore wind farm. The aim of the campaign is to validate and improve wake models for load and power estimations in wind farms. Based on the findings from the measurements, the formulation of the wake degradation in the dynamic wake meandering model has been adjusted, so that the recalibrated model coincides very well with the measurements and thereby reduces the uncertainties.

Motivated by the need for wind turbine rotor blade tests in flows with atmospheric-like properties like gusts, we present a new setup to generate strong, rapid, turbulent gusts in a wind tunnel. The setup consists of a rotating bar that cuts through the inlet of the wind tunnel which generates the gust, and it is called the chopper. In this work, the flow generated by the chopper is characterized, and we show how the gust and its turbulence evolve downstream.

Bat carcass surveys guided by likely fall zone distributions require accurate descriptions of carcass aerodynamics. This research introduces a new methodology resulting in the first direct measurements of bat carcass drag coefficients. The drag coefficient for three carcasses of three different species was found to be within a range of 0.70–1.23, with a terminal velocity between 6.63 and 17.57 m s⁻¹. This information is useful for assessing the impact of wind farm projects on wildlife.

Aeroelastic design load calculations play a key role in determining the design loads of the different wind turbine components. This study compares load estimations from calculations using a Blade Element Momentum aerodynamic model with estimations from calculations using a higher-order Lifting-Line Free Vortex Wake aerodynamic model. The paper finds and explains the differences in fatigue and extreme turbine loads for power production simulations that cover a wide range of turbulent wind speeds.

The present publication has contributed towards making vortex wake models ready for application to certification load calculations. The reduction in flapwise blade root moment fatigue loading using vortex wake models instead of the blade element momentum method has been verified using dedicated CFD simulations. A validation effort against a long-term field measurement campaign featuring 2.5 MW turbines has confirmed the improved prediction of unsteady load characteristics by vortex wake models.

This work addresses the mechanical modelling of complex beamlike structures, which may be curved, twisted and tapered in their reference state and undergo large displacements, 3D cross-sectional warping and small strains. A model suitable for the problem at hand is proposed. It can be used to analyze large deflections under prescribed loads and determine the stress and strain fields in the structure. Analytical and numerical results obtained by applying the proposed modelling approach are shown.

When a new rotor blade is designed, a prototype needs to be qualified by testing in two separate directions before it can be used in the field. These tests are time-consuming and expensive. Combining these two tests into one by applying loads in two directions simultaneously is a possible method to reduce time and costs. This paper presents a new computational method, which is capable of designing these complex tests and shows exemplarily that the combined test is faster than traditional tests.

The paper describes a new method that uses standard historical operational data and reconstructs the flow at the rotor disk of each turbine in a wind farm. The method is based on a baseline wind farm flow and wake model, augmented with error terms that are learned from operational data using an ad hoc system identification approach. Both wind tunnel experiments and real data from a wind farm at a complex terrain site are used to show the capabilities of the new method.

This paper outlines a novel segment test methodology for wind turbine rotor blades. It mainly aims at improving the efficiency of the fatigue test as a future test method at Fraunhofer IWES. The numerical simulation reveals that this method has a significant time savings of up to 43 % and 52 % for 60 and 90 m blades, while improving test quality within an acceptable range of overload. This test methodology could be a technical solution for future offshore rotor blades longer than 100 m.

In offshore wind, it is important to have an accurate wind resource assessment. Measure–correlate–predict (MCP) is a statistical method used in the assessment of the wind resource at a candidate site. Being a statistical method, it is subject to uncertainty, resulting in an uncertainty in the power output from the wind farm. This study involves the use of wind data from the island of Malta and uses a hypothetical wind farm to establish the best MCP methodology for the wind resource assessment.

The presented work investigates the potential of the lattice Boltzmann method (LBM) for numerical simulations of wind turbine wakes. The LBM is a rather novel, alternative approach for computational fluid dynamics (CFD) that allows for significantly faster simulations. The study shows that the method provides similar results when compared to classical CFD approaches while only requiring a fraction of the computational demand.