Simulation of wind turbine wake interaction using the vorticity transport model

The aerodynamic interactions that can occur within a wind farm can result in the constituent turbines generating a lower power output than would be possible if each of the turbines were operated in isolation. Tightening of the constraints on the siting of wind farms is likely to increase the scale of the problem in the future. The aerodynamic performance of turbine rotors and the mechanisms that couple the fluid dynamics of multiple rotors can be most readily understood by simplifying the problem and considering the interaction between only two rotors. The aerodynamic interaction between two rotors in both co-axial and offset configurations has been simulated using the Vorticity Transport Model. The aerodynamic interaction is a function of the tip speed ratio, and both the streamwise and crosswind separation between the rotors. The simulations show that the momentum deficit at a turbine operating within the wake developed by the rotor of a second turbine is governed by the development of instabilities within the wake of the upwind rotor, and the ensuing structure of the wake as it impinges on the downwind rotor. If the wind farm configuration or wind conditions are such that a turbine rotor is subject to partial impingement by the wake produced by an upstream turbine, then significant unsteadiness in the aerodynamic loading on the rotor blades of the downwind turbine can result, and this unsteadiness can have considerable implications for the fatigue life of the blade structure and rotor hub

Simulating wind turbine interactions using the vorticity transport equations

The aerodynamic interactions that can occur within a wind farm result in the constituent turbines generating a lower power output than would be possible if each of the turbines were operated in isolation. Tightening of the constraints on the siting of wind farms is likely to increase the scale of the problem in the future. The aerodynamic performance ofturbine rotors and the mechanisms that couple the fluid dynamics of multiple rotors can be understood best by simplifying the problem and considering the interaction between only two rotors. The aerodynamic interaction between two rotors in both axial and yawed wind conditions has been simulated using the Vorticity Transport Model. The aerodynamic interaction is a function of the tip speed ratio, the separation between the rotors, and the angle of yaw to the incident wind. The simulations show that the momentum deficit at a turbine operating within the wake developed by the rotor of a second turbine can limitsubstantially the mean power coefficient that can be developed by the turbine rotor. In addition, the significant unsteadiness in the aerodynamic loading on the rotor blades that results from the inherent asymmetry of the interaction, particularly in certain configurations and wind conditions, has considerable implications for the fatigue life of the blade structure and rotor hub. The Vorticity Transport Model enables the simulation the wakedynamics within wind farms and the subsequent aerodynamic interaction to be evaluated over a broad range of wind farm configurations and operating conditions

The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential

Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( CF ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that CF values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying.This work was financially supported by the Spanish Government through the MINECO project CGL2016-76561-R, (MINECO/ERDF, UE) and the University of the Basque Country (UPV/EHU, GIU 17/002). ERA5 hindcast data were downloaded at no cost from the Copernicus Climate Data Store. All the calculations and plots were made using R: https://www.r-project.org

The interaction of helical tip and root vortices in a wind turbine wake

Analysis of the helical vortices measured behind a model wind turbine in a water channel are reported. Phase-locked measurements using planar particle image ve- locimetry are taken behind a Glauert rotor to investigate the evolution and breakdown of the helical vortex structures. Existing linear stability theory predicts helical vortex filaments to be susceptible to three unstable modes. The current work presents tip and root vortex evolution in the wake for varying tip speed ratio and shows a breaking of the helical symmetry and merging of the vortices due to mutual inductance between the vortical filaments. The merging of the vortices is shown to be steady with rotor phase, however, small-scale non-periodic meander of the vortex positions is also ob- served. The generation of the helical wake is demonstrated to be closely coupled with the blade aerodynamics, strongly influencing the vortex properties which are shown to agree with theoretical predictions of the circulation shed into the wake by the blades. The mutual inductance of the helices is shown to occur at the same non-dimensional wake distance

Modelling sea breeze climatologies and interactions on coasts in the southern North Sea: Implications for offshore wind energy

Current understanding of the behaviour of sea breezes in the offshore environment is limited but rapidly requires improvement due, not least, to the expansion of the offshore wind energy industry. Here we report on contrasting characteristics of three sea-breeze types on five coastlines around the southern North Sea from an 11 year model-simulated climatology. We present and test an identification method which distinguishes sea-breeze types which can, in principle, be adapted for other coastlines around the world. The coherence of the composite results for each type demonstrates that the method is very effective in resolving and distinguishing characteristics and features. Some features, such as jets and calm zones, are shown to influence offshore wind farm development areas, including the sites of the proposed wind farms up to 200 km offshore. A large variability in sea-breeze frequency between neighbouring coastlines of up to a factor of 3 is revealed. Additionally, there is a strong association between sea-breeze type on one coastline and that which may form coincidentally on another nearby. This association can be as high as 86% between, for example, the North Norfolk and East Norfolk coasts. We show, through associations between sea-breeze events on coastlines with contrasting orientations, that each coastline can be important for influencing the wind climate of another. Furthermore, we highlight that each sea-breeze type needs separate consideration in wind power resource assessment and that future larger turbines will be more sensitive to sea-breeze impacts

Etude numérique et expérimentale de l'écoulement autour d'un rotor éolien

An improved model of an actuator surface is proposed, representing the flow around a wind turbine. This model was developed in conjunction with a Navier-Stokes solver using a blade element method for the calculation of power and wake development. Blades have been replaced with thin surfaces, and a boundary condition of “pressure discontinuity” has been applied with rotor inflow and blade-section characteristics. The proposed improvement consists of applying tangential body forces along the chord, in addition to normal body forces resulting from pressure discontinuity along the blade cross-section. The proposed model has been validated for the flow around a horizontal-axis wind turbine. The results obtained from the proposed model are compared with the experimental results obtained from PIV-wind tunnel techniques. The comparison has displayed the necessity of the proposed model for accurate reproduction of the wake behind rotor. The rapidity of calculation, in comparison to full-geometry modelling, appears to be promising for wind farm simulations.Un modèle amélioré de surface active est proposé pour représenter l’écoulement autour d'une éolienne. Ce modèle est développé en association avec un solveur Navier-Stokes et en utilisant une méthode d'élément de pale pour le calcul de la puissance de l’éolienne et du développement du sillage. Les pales sont remplacées par des surfaces minces, et une condition limite de "discontinuité de pression" a été appliquée à partir de la vitesse d'entrée dans le rotor et des caractéristiques du profil de pale. L'amélioration proposée consiste à appliquer des forces volumiques tangentielles le long de la corde, en plus des forces volumiques normales résultantes de la discontinuité de pression à travers la surface de la pale. Le modèle proposé a été validé pour l'écoulement autour d'une éolienne à axe horizontal. Les résultats obtenus à partir du modèle proposé sont comparés avec les résultats expérimentaux obtenus en soufflerie par la technique PIV. La comparaison a démontré l’intérêt du modèle proposé pour une bonne reproduction du sillage derrière le rotor. La rapidité de calcul, par rapport à la simulation d’une géométrie complète des pales, semble promettant pour des simulations de parcs éoliens.Recherche financée par le laboratoire et par l'Institut CARNOT ART

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power grid. Aiming to provide reference strategies for relevant researchers as well as practical applications, this paper attempts to provide the literature investigation and methods analysis of deep learning, enforcement learning and transfer learning in wind speed and wind power forecasting modeling. Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure, temperature, roughness, and obstacles. As an effective method of high-dimensional feature extraction, deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design, such as adding noise to outputs, evolutionary learning used to optimize hidden layer weights, optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for forecasting. The establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness, instantaneity and seasonal characteristics

Investigation of wind turbine flow and wake

This paper is dedicated to the investigation and analysis of wind turbine wake. An experimental work is undertaken in wind tunnel on a horizontal axis wind turbine model. The velocity field in the wake is measured using PIV with phase synchronization in order to relate velocity and vortices to the rotating blades. The tip vortices are investigated in successive azimuthal positions of the rotor. A specially developed algorithm based on the circulation maximum detects the positions of the vortex cores and permits to use conditional averaging technique. The analysis of obtained velocity fields enables to determine the vortex core diameter, the swirl velocity distribution and the vortex diffusion as functions of the vortex age. The quality of obtained results permits to use them as reference for the validation of numerical computations

Turbulence-resolving simulations of wind turbine wakes

Turbulence-resolving simulations of wind turbine wakes are presented using a high--order flow solver combined with both a standard and a novel dynamic implicit spectral vanishing viscosity (iSVV and dynamic iSVV) model to account for subgrid-scale (SGS) stresses. The numerical solutions are compared against wind tunnel measurements, which include mean velocity and turbulent intensity profiles, as well as integral rotor quantities such as power and thrust coefficients. For the standard (also termed static) case the magnitude of the spectral vanishing viscosity is selected via a heuristic analysis of the wake statistics, while in the case of the dynamic model the magnitude is adjusted both in space and time at each time step. The study focuses on examining the ability of the two approaches, standard (static) and dynamic, to accurately capture the wake features, both qualitatively and quantitatively. The results suggest that the static method can become over-dissipative when the magnitude of the spectral viscosity is increased, while the dynamic approach which adjusts the magnitude of dissipation locally is shown to be more appropriate for a non-homogeneous flow such that of a wind turbine wake

Meteorologically Defined Limits to Reduction in the Variability of Outputs from a Coupled Wind Farm System in the Central US

Studies suggest that onshore wind resources in the contiguous US could readily accommodate present and anticipated future US demand for electricity. The problem with the output from a single wind farm located in any particular region is that it is variable on time scales ranging from minutes to days posing difficulties for incorporating relevant outputs into an integrated power system. The high frequency (shorter than once per day) variability of contributions from individual wind farms is determined mainly by locally generated small scale boundary layer. The low frequency variability (longer than once per day) is associated with the passage of transient waves in the atmosphere with a characteristic time scale of several days. Using 5 years of assimilated wind data, we show that the high frequency variability of wind-generated power can be significantly reduced by coupling outputs from 5 to 10 wind farms distributed uniformly over a ten state region of the Central US in this study. More than 95% of the remaining variability of the coupled system is concentrated at time scales longer than a day, allowing operators to take advantage of multi-day weather forecasts in scheduling projected contributions from wind.Engineering and Applied Science