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).

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.

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.

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 %.

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.

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.

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.

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.

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.

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 %.