The submitted manuscript suggests an analytical model/approach to connect the near-wake wind deficit with the mid an far-wake deficit. The atmospheric turbulence is considered as the main driver for the wind deficit decay rate in this approach. The analytical solution is backed by a numerical solution of the momentum conservation equation derived from Navier-Stokes equations. In-situ wake UAS measurements are the basis and motivation for the model approach shown in the manuscript.

This paper presents two methods on how to estimate the lift force that is created by a wing. These methods were experimentally assessed in a wind tunnel. Furthermore, an active trailing edge flap, as seen on airplanes for example, is used to alleviate fluctuating loads that are created within the employed wind tunnel. Thereby, an active flow control device is examined that can be potentially serve on wind turbines to lower fatigue or lower the material used for the blades.

Floating offshore wind technology has high potential, but still faces challenges for gaining economic competitiveness to allow commercial market uptake. Hence, design optimization plays a key role, however, the final optimum floater obtained highly depends on the specified optimization problem. Thus, by considering alternative structural realization approaches, not that stringent limitations on the structure and dimensions are required. This way, more innovative floater designs can be captured.

The manuscript deals with the optimization of parameters of widely-used wake models based on LiDAR measurements. A discussion on the accuracy achieved with the optimized models is provided together with their physical implications.

When assessing the wind resources for wind farm development, the first step is to measure the wind from tall meteorology masts. As met masts are expensive, they are not built at every planned wind turbine position but sparsely while trying to minimise the distance. However, this paper shows that it is better to focus on the similarity between the met mast and the wind turbines than the distance. Met masts at similar positions reduce the uncertainty of wind resource assessments significantly.

A methodology to design electrothermal de-icing protection for wind turbines is presented. The method relies in modeling and experimental testing to determine the critical ice thickness. The critical ice thickness needed is dependent on the ice tensile strength which varies with icing conditions. The ice tensile strength must be overcome by the stress that a debonded ice structure exerts under centrifugal force at its root region, where it attaches to a non-debonded ice region.

This paper assesses the behaviour and causality of sudden variations in wind power generation over a short period of time, also called ramp events. It is shown, amongst other things, that ramps at the study site are mostly associated with frontal activity and convective processes. Overall, the research contributes to a better understanding of the drivers and behaviours of wind power ramps at the wind farm scale, beneficial to ramp forecasting and ramp modelling.

This article presents the results of a field experiment investigating wake steering in an onshore wind farm. The measurements show that wake steering leads to increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. The results suggest that further research is necessary before wake steering will consistently lead to energy gains in wind farms.

Mountain waves can create oscillations in low-level wind speeds and subsequently in the power output of wind plants. We document such oscillations by analyzing sodar and lidar observations, nacelle wind speeds, power observations, and WRF model simulations. This research describes how maintain waves form in the Columbia Basin in the United States, how they affect wind energy production, and their impacts on operational forecasting, wind plant layout, and integration of power into the grid.

The performance of an open-loop wake steering controller is investigated with a new wind tunnel experiment. Three scaled wind turbines are placed on a large turntable and exposed to a turbulent inflow, resulting in dynamically varying wake interactions. The study highlights the importance of using a robust formulation and plant flow models of appropriate fidelity, and the existence of possible margins for improvement by the use of dynamic controllers.

The article describes results of experimental wind tunnel and CFD testing of four different straight bladed vertical axis wind turbine model configurations. The experiment tested a novel concept of vertically dividing and azimuthally shifting a turbine rotor into two parts with a specific uneven height division in order to limit cycle amplitudes and average cycle values of bending moments at the bottom of the turbine shaft to increase product lifetime, especially for industrial scale turbines.

The potential of collective offshore wind power is quantified using 16 years of hourly wind speed observations. Wind power intermittency is reduced through a hypothetical electricity grid connecting five sites at the Norwegian continental shelf. We identify large-scale atmospheric situations resulting in long term periods of power shut-down. Wind power variability and risk-measures decrease in an interconnected wind power system.

Machine learning is quickly becoming a commonly used technique for wind speed and power forecasting, and is especially useful when combined with other forecasting techniques. This study utilizes a popular machine learning algorithm, an artificial neural network (ANN), in an attempt to predict the forecasting error of a statistical forecasting model. Various atmospheric characteristics are used as ANN inputs in an effort to discern the most useful atmospheric information for this purpose.

Very short-term wind power forecasts are gaining increasing importance with the rising share of renewables in today's energy system. In this work, we developed a methodology to forecast wind power of offshore wind turbines on minute-scales utilising single Doppler long-range lidar measurements. The model was able to outperform persistence during unstable stratification in terms of deterministic as well as probabilistic scores, while it showed large shortcomings for stable atmospheric conditions.

We suggest a methodology for correlating loads with component reliability of turbines in wind farms by combining physical modeling with machine learning. The suggested approach is demonstrated on an offshore wind farm for comparing performance, loads and lifetime estimations against recorded main bearing failures from maintenance reports. It is found that turbines positioned at the border of the wind farm with a higher expected AEP are estimated to experience earlier main bearing failures.

This research paper investigates for the first time the potential of thrust set-point optimization in large wind farms for mitigating gravity-wave induced blockage effects, with the aim of increasing the wind-farm energy extraction. The optimization tool is applied to almost two thousand different atmospheric states. Overall, energy gains above 4 % are observed for 77 % of the cases.

Robust and accurate dynamic stall modeling remains one of the most difficult tasks in wind turbine load calculations despite its long research effort in the past. The present paper describes a new second order dynamic stall model for wind turbine airfoils. The new model is robust and improves the prediction for the aerodynamic forces and their higher harmonic effects due to vortex shedding, but also provides improved predictions for pitching moment and drag.

We use a mesoscale numerical weather prediction model to conduct a case study of a thunderstorm outflow passing over and interacting with a wind farm. These simulations, along with observations from a nearby radar and surface station, confirm that interactions with the wind farm cause the outflow to reduce its speed by over 20 km/hr, with brief but significant impacts to the local meteorology, including temperature, moisture, and winds. Precipitation accumulation across the region was unaffected.

The main goal of this study was to develop a physical simulation of some simplified extreme wind conditions that are defined by a standard for wind turbines. Most of the research works in this area are limited to numerical and theoretical studies. Being able to simulate these dynamic flow fields can be a contribution for future scholars working in the wind energy areas to make these wind energy systems more reliable which finally helps to accelerate the reduction of the cost of electricity.

The paper presents a concept of a multi-rotor system as a floating off-shore wind turbine. The results show that it may be an alternative to conventional wind turbines and even be cheaper in a long run, thus lowering the cost of energy to consumers. It may also solve technological barriers. The motivation for research was the idea of providing a technology vision for regions, where certain local supply chain can be employed to revitalize the shipyard industry while using renewable energy.

A test implementation of a method to mitigate adverse interactions between wind turbines in a wind farm is investigated in terms of behavior and success. Measurements of the atmospheric flow around a pair of wind turbines and power readings of the wind turbines itself are analyzed for this purpose. The behavior of the wake agrees with the predictions of newer analytical models and a bias of the wind direction perceived by the wind turbine under certain conditions is reducing the power gains.

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 two orders of magnitude faster and less expensive than using conventional site measurements. This enables analysis of a larger number of projects and thereby increase the chances of discovering the best available sites. The uncertainty in mean wind speed predictions is found to be about 4 %.