Abstracted/indexed

As wind power becomes more popular, there is a growing demand for accurate power production forecasts. In this paper we investigated different methods to improve wind power forecasts for an offshore location in the Baltic Sea, using both simple and more advanced techniques. The performance of the methods are evaluated for different weather conditions. Smoothing the forecast was found to be the best method in general, but we recommend to select which method to use based on the forecasted weather.

The e-Telltale, a new aerodynamic sensor have been tested in a large wind tunnel in the CSTB. This sensor have been designed to detect the flow separation on wind turbine blades which can cause energy production losses and increased aging of the blades. Theses wind tunnel tests higlighted the good ability of the e-Telltale to detect the flow separation and the influence of the size and location of the e-Telltale on the flow separation detection.

We develop two machine-learning-based approaches to temporally extrapolate uncertainty in hub-height wind speed modeled by a numerical weather prediction model. We test our approaches in the California Outer Continental Shelf, where a significant offshore wind energy development is currently being planned, and we find that both provide accurate results.

This article presents a novel method to improve offshore surface wind speeds estimated by Synthetic Aperture Radar satellites and extrapolate them to higher altitudes. It can provide maps of the offshore extractible wind power up to 200 m and thus complement numerical models, especially in coastal areas. The method uses geometrical parameters of the sensor and parameters related to the atmospheric stability, combining them with machine learning. The final accuracy at 200 m is within 4 %.

Wind turbine wake behavior in hilly terrain depends on various atmospheric conditions. We modeled a wind turbine located on top of a ridge in Portugal during typical nighttime and daytime atmospheric conditions and validated these model results with observational data. During nighttime conditions, the wake deflected downwards following the terrain. During daytime conditions, the wake deflected upwards. These results can provide insight into wind turbine siting and operation in hilly regions.

A model for computing vertical-axis wind turbine farms was developed using computational fluid dynamics open-source software. This model has the potential of evaluating wind farm configurations which can lead to a higher annual energy yield. Such configurations have not been studied thoroughly due to the fact that most analysis tools are computational expensive, this model can be run in personal computers within a matter of minutes or hours depending on the number of turbines.

We perform a validation of the new simulation tool FAST.Farm for the prediction of power output and structural loads in single wake conditions with respect to measurement data from the offshore wind farm alpha ventus. With a new wake-added turbulence functionality added to FAST.Farm, good agreement between simulations and measurements is achieved for the considered quantities. Hereby, we give insights into load characteristics of an offshore wind turbine subjected to single wake conditions.

Modern rotor blade designs depend on detailed numerical models and simulations. Thus, a validated modelling methodology is fundamental for reliable designs. This paper briefly presents a modelling algorithm for rotor blades, its validation against real life full scale blade tests and the respective test data. The hybrid 3D shell/solid finite element model is successfully validated against the conducted classical bending tests in flap-wise and lead-lag direction as well as novel torsion tests.

Light detection and ranging (lidar), has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, because of their measurement principle, common lidars suffer from errors at orographically complex, i.e. hilly or mountainious sites. This study analyses the impact of the five main influencing factors in a non-dimensional, model-based parameter study.

Floating Offshore Wind Turbines may experience large surge motions which, when faster than the local wind speed, cause rotor-wake interaction. We derive a model which is able to predict the wind speed at the wind turbine, even for large and fast motions and load variations of the wind turbine. The proposed dynamic inflow model includes an adaptation for highly loaded flow and it is accurate and simple enough to be easily implemented in most Blade Element Momentum design models.

This research involves studying the flow around the section of a wind turbine blade albeit at a lower Reynolds number or flow speed using wall-resolved large-eddy simulations, a form of computer simulation that resolves the important scales of the flow. Among the many interesting results, it is shown that the energy entering the boundary layer around the airfoil or section of the blade is proportional to the square of the incoming flow turbulence intensity.

A novel inverse problem-based methodology is developed to estimate the drive train main shaft torsional stiffness and displacement only by acquisition SCADA measurements. It involves Tikhonov regularisation for regularising the measurement data and the collage method for system identification. These estimated quantities can be used to identify the site-specific torsional loads of the main shaft and to quantify the remaining useful life of the main shaft as well as other drive train components.

The publication of the Reference Open-Source Controller (ROSCO) provides a controller and generic controller tuning process to the wind energy research community that can perform comparably or better than existing reference wind turbine controllers and includes features that are consistent with industry standards. Notably, ROSCO provides the first known open-source controller with features that specifically address floating offshore wind turbine control.

Wind turbines are frequently placed in forests. We investigate the potential of using satellites to characterise the land surface for wind flow modelling. Maps of forest properties are generated from satellite data and converted to flow modelling maps. Validation is carried out at ten sites. Using the novel satellite-based maps leads to lower errors of the power density than land cover databases, which demonstrates the value of using satellite-based land cover maps for flow modelling.

A new high-resolution data set (NORA3) is validated for offshore wind power purposes for the North Sea and Norwegian Sea. The purpose of the validation is to ensure that NORA3 can act as a planning tool for future offshore wind power installations in the area of concern. The general conclusion of the validation is that NORA3 is well suited for wind power estimates, but gives slightly conservative estimates on the offshore wind metrics.

In RANS-CFD, e^N-based method showed its superiority over local correlation-based transition models (LCTM) coupled with the SST turbulence model for predicting transition behavior at high-Reynolds number flows (3–15 million). In this study, we evaluated performance of two LCTMs coupled with SA turbulence model. As a result, the SA-based two-equation transition model showed a comparable performance with the e^N-based method and better glide ratio (L / D) predictions than the SST-based model.

Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design, and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15–54 for the cases in this paper, depending on the metric that is optimized.

The study aims for a computationally inexpensive model describing the wind deficit behind a wind energy converter analytically using some assumptions and basic governing equations of the atmosphere. Thus, the influence of different atmospheric conditions onto the wake development can be studied in the future which is important e.g. in wind park planning. The model is compared to conventional empirical wake models and in-situ UAS measurements captured along the wake at hub height.

The design of a ducted wind turbine was optimized to maximize the power per total cross-sectional area of the device. The associated power coefficient was 0.69, which is significantly greater than that obtainable from an open rotor turbine. Furthermore, it was shown that there is an optimal duct length, which is 15 % of the rotor diameter.

Turbine-mounted lidars performing inflow scans can be used to optimise wind turbine performance and extend their lifetime. This paper introduces a new method to extract wind inflow information from a turbine-mounted scanning SpinnerLidar based on Proper Orthogonal Decomposition. This method offers a balance between simple reconstruction methods and complicated physics-based solvers. The results show that the model can be used for lidar assisted control, loads validation and turbulence studies.

Floating wind turbines undergoes complex aerodynamic phenomena that are not completely understood. This paper presents an scale-model wind tunnel experiment about the investigated the unsteady aerodynamics of floating turbines with a radically different approach than previous experiments. The problem was studied under different aspects, from airfoil aerodynamics to wake.

Wind turbines are often clustered within wind farms. A consequence is that some wind turbines may be exposed to the wakes of other turbines, which reduces their lifetime due to the wake turbulence. Knowledge of the wake is thus important, and we carried out wind tunnel experiments to investigate the wakes. We show how models that describe wakes of bluff bodies can help to improve the understanding of wind turbine wakes and wind turbine wake models, particularly by including a virtual origin.

Floating wind is the key technology to harvest the abundant wind energy resource of deep waters. This research introduces a new way of controlling the wind turbine to better deal with the action of waves. The turbine is made aware of the incoming waves and the information is exploited to enhance power production.

Wind turbines extract momentum from atmospheric flow and convert that to electricity. This study explores recovery processes in wind farms that replenish the momentum so that wind farms can continue to function. Experiments with a numerical model show that momentum transport by turbulent eddies from above the wind turbines is the major contributor to recovery except for strong wind conditions and high wind turbine density where horizontal advection can also play a major role.

This paper introduces the numerical models of two 15MW Floating Offshore Wind Turbines (FOWTs) WindCrete and Activefloat. WindCrete is a spar floating platform designed by Universitat Politècnica de Catalunya, while the Activefloat is a semi-submersible platform designed by Esteyco. The floaters are designed within the Horizon 2020 project COREWIND. Afterwards, the responses of both models to wind and second order waves are analyzed with an emphasis on the effect of second order waves.