We show in the paper that the upscaling of turbines has led to new requirements in simulation of the unsteady aerodynamic forces by the engineering blade element momentum (BEM) model, originally developed for simulation of the aerodynamics of propellers and helicopters. We present a new implementation of the BEM model on a polar grid which can be characterized as an engineering actuator disc model. The aeroelastic load impact of the new BEM implementation is analyzed and quantified.

Offshore wind farm clusters cause reduced wind speeds in downstream regions which can extend over more than 50 km. We analysed the impact of these so-called cluster wakes on a distant wind farm using remote-sensing wind measurements and power production data. Cluster wakes caused power losses up to 55 km downstream in certain atmospheric states. A better understanding of cluster wake effects reduces uncertainties in offshore wind resource assessment and improves offshore areal planning.

Wakes of a multi-rotor wind turbine configuration are evaluated using numerical simulations. Compared to equivalent conventional single-rotor turbine wakes, multi-rotor turbine wakes are found to recover faster and generate less turbulence; thus, multi-rotor turbine wind farms are more efficient, with smaller wake losses. The benefits of multi-rotor wind farms over conventional wind farms are sensitive to tip spacing, thrust coefficient and turbine spacing.

A WindScanner system consisting of two synchronized scanning lidars potentially represents a cost-effective solution for multipoint measurements. However, the lidar limitations and the site limitations are detrimental to the installation of lidars and number and location of measurement positions. To simplify the process of finding suitable measurement positions and lidar installation locations, a campaign planning workflow was devised. The paper describes the workflow and how it was digitalized.

Offshore wind energy is a burgeoning area of renewable energy that is at an early stage of development in the United States. Exposure of offshore wind turbines to hurricanes must be assessed and mitigated to ensure the security of the renewable energy supply. This research assesses the impact of hurricane wind fields on the structural response of wind turbines. Such wind fields have characteristics that may pose heretofore unforeseen structural challenges to offshore wind turbines.

This paper presents a review of existing theory and practice relating to main bearings for wind turbines. Topics covered include wind conditions and resulting rotor loads, main-bearing models, damage mechanisms and fault detection procedures.

Wind turbine performance depends on various atmospheric conditions. We quantified the effect of the change in wind direction and speed with height (direction and speed wind shear) on turbine power at a wind farm in Iowa. Turbine performance was affected during large direction shear and small speed shear conditions and favored for the opposite scenarios. These effects make direction shear significant when analyzing the influence of different atmospheric variables on turbine operation.

A computational fluid dynamics (CFD) solver is coupled with a structure solver to predict the dynamic response of a horizontal axis wind turbine structure. CFD provides much more accurate and more realistic aerodynamic loads that cannot be achieved by traditional methods such as blade element momentum theory. As a result, the aeroelastic response of the wind turbine structure, taking into account blade–tower interactions, is described in more detail.

From the basic aerodynamic theory of wind turbine rotors, it is a well-known fact that there is a relationship between the loading of the rotor and power efficiency. It shows that there is a loading that maximizes the power efficiency, and it is common to target this maximum when designing rotors. But in this paper it is found that for rotors constrained by a load, the maximum power is found by decreasing the loading and increasing the rotor radius. Max power efficiency is therefore not optimal.

We present a framework for reducing the cost of support structures for offshore wind turbines that takes into account the many uncertainties that go into the design process. The results demonstrate how an efficient new approach, tailored for support structure design, allows the state of the art for design without uncertainties to be used within a framework that does include these uncertainties. This allows more realistic, and less conservative, design methods to be used for practical design.

This work summarizes the results of the intelligence-sharing initiative of the Power Curve Working Group. Participants in this share exercise applied a handful of selected power curve modeling correction methods on their power performance test data, and they submitted the results for the coauthors to analyze. In this paper, we describe the share exercise, explain the analysis methodologies, and perform statistical tests to evaluate the correction methods in various inflow conditions.

As more electrical energy is generated by wind turbines, older generation technologies such as coal and gas are being displaced. This situation presents a challenge in the sense that the additional services once provided by fossil generators must now be sourced from elsewhere. Our work provides real-world data showing the capabilities of wind generators in providing the specific service of secondary frequency regulation (automatic generation control, AGC).

An analytical wake model with a double-Gaussian velocity distribution is used to improve on a similar formulation by Keane et al (2016). The choice of a double-Gaussian shape function is motivated by the behavior of the near-wake region that is observed in numerical simulations and experimental measurements. The model is calibrated and validated using large eddy simulations replicating scaled wind turbine experiments, yielding improved results with respect to a classical single-Gaussian profile.

The interaction between wind turbines in a wind farm through their wakes is a widely studied research area. Until recently, research was focused on finding constant turbine inputs that optimize the performance of the wind farm. However, recent studies have shown that time-varying, dynamic inputs might be more beneficial. In this paper, the validity of this approach is further investigated by implementing it in scaled wind tunnel experiments and assessing load effects, showing promising results.

The design and management of an offshore wind farm involve expertise in many disciplines. It is hard for a single person to maintain the overview needed. Therefore, we have created WESgraph, a knowledge base for the wind farm domain, implemented as a graph database. It stores descriptions of the multitude of domain concepts and their various interconnections. It allows users to explore the domain and search for relationships within and across disciplines, enabling various applications.

Meteorological and oceanic datasets are fundamental to the modeling of offshore wind farms. Data quality issues in one such dataset led us to conduct a study to establish whether such issues are more generally present in these datasets. The answer is yes and users should be aware of this. We therefore also investigated how such issues can be avoided. The result is a set of techniques and recommendations for dataset producers, leading to substantial quality improvements with limited extra effort.

We aim to develop fast and reliable surrogate models for yaw-based wind farm control. The surrogates, based on polynomial chaos expansion, are built using high-fidelity flow simulations combined with aeroelastic simulations of the turbine performance and loads. Optimization results performed using two Vestas V27 turbines in a row for a specific atmospheric condition suggest that a power gain of almost 3 % ± 1 % can be achieved at close spacing by yawing the upstream turbine more than 15°.

Wind turbine blade leading edge erosion (LEE) is potentially a significant source of energy loss and expense for wind farm operators. This study presents a novel approach to characterizing LEE potential from precipitation across the contiguous USA based on publicly available National Weather Service dual-polarization RADAR data. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments.

Simulations of wind farms allow the estimation of the forces acting on the turbines and thus their lifetime and power production. Representing the actual geometric shape of turbines in a realistic atmospheric flow is computationally expensive; therefore they are modelled in a simplified manner. Unfortunately, these simplifications negatively impact the estimated forces. We developed an open-source aerodynamic model that corrects the forces, giving more accurate estimates of lifetime and power.

The design of wind turbines and wind farms can be improved by increasing the accuracy of the inflow models representing the atmospheric boundary layer (ABL). In this work we employ numerical simulations of the idealized ABL, which can represent the mean effects of Coriolis and buoyancy forces and surface roughness. We find a new model-based similarity that provides a better understanding of the idealized ABL. In addition, we extend the model to include effects of convective buoyancy forces.

Europe's offshore wind resource mapping is part of the New European Wind Atlas (NEWA) international consortium effort. This study presents the results of analysis of synthetic aperture radar (SAR) ocean wind maps based on Envisat and Sentinel-1 with a brief description of the wind retrieval process and Advanced Scatterometer (ASCAT) ocean wind maps. Furthermore, the Weather Research and Forecasting (WRF) offshore wind atlas of NEWA is presented.

This work has analyzed historical data of 10 min averaged wind speed measurements to investigate the accuracy of the commonly used equations for describing the wind velocity as a function of the height above ground. The results of analyzing data from a wide range of sites show that the common equations do not sufficiently describe certain physical phenomena, especially at offshore and coastal locations. The results imply that there is a need for more advanced models.

We investigate the trade-offs in optimization of wake steering strategies, where upstream turbines are positioned to deflect wakes away from downstream turbines, with a probabilistic perspective. We identify inputs that are sensitive to uncertainty and demonstrate a realistic optimization under uncertainty for a wind power plant control strategy. Designing explicitly around uncertainty yielded control strategies that were generally less aggressive and more robust to the uncertain input.

In wind farms, the interaction between neighboring turbines can cause notable power losses. The focus of the paper is on how the combination of turbine yaw misalignment and wake effects influences the power loss in a wind turbine. The results of the paper show a more notable power loss due to turbine misalignment when turbines are closely spaced. The presented conclusions enable better predictions of a turbine's power production, which can assist the wind farm design process.