Wind Energy Community Research Articles

Potential of Wake Scaling Techniques for Vertical-Axis Wind Turbine Wake Prediction

Analytical wake models are widely used to predict wind turbine wakes. While these models are well-established for horizontal-axis wind turbines (HAWTs), the analytical wake models for vertical-axis wind turbines (VAWTs) remain under-explored in the wind energy community. In this study, the accuracy of two wake scaling techniques is evaluated to predict the change in the normalized maximum wake velocity deficit behind VAWTs by re-scaling the maximum wake velocity deficit behind an actuator disk with the same thrust coefficient. The wake scaling is defined in terms of equivalent diameter, considering the geometrical properties of the wake-generating object. Two different equivalent diameters are compared, namely the momentum diameter and hydraulic diameter. Different approaches are used to calculate the change in the normalized wake velocity deficit behind a disk with the same thrust coefficient as the VAWT. The streamwise distance is scaled with the equivalent diameter to predict the normalized maximum wake velocity deficit behind the desired VAWT. The performance of the proposed framework is assessed using large-eddy simulation data of VAWTs operating in a turbulent boundary layer with varying operating conditions and aspect ratios. For all of the cases, the momentum diameter scaling provides reasonable predictions of the VAWT normalized maximum wake velocity deficit.

Viability of Green Hydrogen Production at Benguela Wind Energy Community Project in Lüderitz, Namibia

Viability of Green Hydrogen Production at Benguela Wind Energy Community Project in Lüderitz, Namibia

Comparison of horizontal wind speed and direction measurements from dual-Doppler radar and profiling lidars

Dual-Doppler radar is a relatively new technology in the wind energy community and thus not yet studied vastly. This paper aims to compare horizontal wind speed and direction data retrieved from dual-Doppler radar and profiling lidars within the American WAKE experimeNt (AWAKEN) to investigate the influence of measurement height, wind direction and speed on the comparison. The 10-min averaged data show a better agreement of the measurements for higher altitudes, especially at faster wind speeds. For the wind direction, two sectors of larger differences in the measurements were detected: around 270° transient winds occur with a higher frequency than in other sectors. To explain the different measurement values in the wind direction sector around 90°, further studies, e.g. on the influence of atmospheric stability, are necessary.

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations.At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

Improving data sharing in wind energy - structural health monitoring case study

A lack of data sharing in the wind energy sector presents a large barrier to increasing the value of wind energy through innovation. One way of improving data sharing is to make it “FAIR”: findable, accessible, interoperable and reusable. The FAIR Data Maturity Model is a tool developed by the Research Data Alliance that can be used to assess and improve the “FAIRness” of data, by quantifying the extent of its findability, accessibility, interoperability and reusability. In this work, we investigate how the FAIR Data Maturity Model could be applied to improve data sharing in the wind energy sector, via a structural health monitoring (SHM) case study. This case study is created as part of a WeDoWind challenge, and was chosen due to the high potential of SHM in reducing the costs of energy through predictive maintenance. WeDoWind is a framework for creating mutually beneficial collaborations, and the WeDoWind wind energy ecosystem is a growing ecosystem of diverse people all over the world sharing and exchanging knowledge and data. It is found that the FAIRness of the provided data set is limited due to the lack of community standards, and the absence of public data sharing services catering specifically to the wind energy context. However, the FAIR Data Maturity Model is successfully applied to improve the FAIRness of the data sets in the case study. A participant survey shows that this made data sharing easier in the context of a WeDoWind data sharing project. Finally, the project results in a set of recommendations for helping the wind energy community to improve the FAIRness of data.

Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy

To enable easier uptake and flexible usage for the wind energy community, a general tool chain integration platform for multi-disciplinary analysis and optimization, TopDesign, is proposed and developed. This work describes its concept and the initial implementation. The platform is written in Python and provided as an open source framework. The design of this platform puts emphasis on flexibility, usability and extensibility. General model classes with standard interfaces, which can wrap custom tools/models in different formats based on different programming languages, will be provided together with examples that are easy to understand and modify. Coupling tools/models into a system thus becomes an easy task of connecting models by inputs and outputs and defining workflow with a directed graph. To demonstrate the usage of the proposed platform, we implement a wind farm evaluation system by coupling the PyWake model, the FLORIS model and self-written constraint models in the platform and apply it in solving wind farm layout optimization problems with two algorithms, as implemented in an in-house optimization Python library. A case study for a wind farm composed of 9 turbines shows the potential of the proposed platform and methodology.

Modelling of cup anemometry and dynamic overspeeding in average wind speed measurements

Abstract. Cup anemometers measure average wind speed in the atmosphere and have been used for one and a half centuries by meteorologists. Within the last half century, cup anemometers have been used extensively in wind energy to measure wind resources and performance of wind turbines. Meteorologists researched cup anemometer behaviour and found dynamic overspeeding to be an inherent and significant systematic error. The wind energy community has strong accuracy requirements for power performance measurements on wind turbines, and this led in the last 2 decades to new research on cup anemometer characteristics, which was taken to a new level with the development of improved calibration procedures, cup anemometer calculation models and classification methods. Research projects in wind energy demonstrated, by field and wind tunnel measurements, that angular response was a significant contributor to uncertainty and that dynamic overspeeding was a significant but less important contributor. Earlier research was mainly made on cup anemometers with hemispherical cups on long arms, ​​​​​​​and dynamic overspeeding was considered an inherent and high uncertainty error for cup anemometers. Research on conical cups on short arms has now shown that zero or low overspeeding is present on a well-designed cup anemometer, providing a much lower overspeeding uncertainty error. Different cup anemometer calculation models were investigated in order to find derived overspeeding characteristics. The general and often used parabolic torque coefficient model showed that zero overspeeding is present when the speed ratio roots of the torque coefficient curve go through the equilibrium speed ratio and zero. The two-cup drag model is a special case of the parabolic torque coefficient model but with the second root being reciprocal to the equilibrium speed ratio. The drag model always results in a positive maximum overspeeding of the order of 1.1 times the turbulence intensity squared. A linear torque coefficient results in maximum overspeeding levels equal to the turbulence intensity squared. Torque characteristics of a cup anemometer with hemispherical cups fit slightly well to the drag model, but a cup anemometer with conical cups does not fit to the drag model nor the parabolic model; it fits better to a partial linear model and even better to an optimized torque model. The most accurate modelling of cup anemometer characteristics is at present made with the ACCUWIND model (Dahlberg et al., 2006). This model uses tabulated torque coefficient and angular response data measured in a wind tunnel. The ACCUWIND model is found in International Electrotechnical Commission (IEC) wind turbine power performance standards, where it is used in a classification system for estimation of operational uncertainties. For an actual comparison of two cup anemometers, with respectively hemispherical and conical cups, the influence of dynamic overspeeding was found to be relatively low compared to angular response, but for conical cups it was specifically low.

Demagnetization effects of surface-mounted permanent magnet synchronous wind generator

To prevent fossil resources from being depleted and protect the natural balance, renewable resources come to the forefront as an alternative to fossil resources. Wind energy resources, among the renewable energy resources, are important in terms of ensuring the reliability of energy and the use of their resources. Generators are the most important components for the conversion of wind power. Permanent magnet synchronous generators (PMSGs) are preferred in wind turbines since they have high efficiency and high volume/torque densities, thereby optimization of the PMSGs is an important topic for the wind energy community. On the one hand, these machines can cause problems due to overheating and mechanical friction during their long-time operation. To identify the performance lack of the machines due to the de-magnetization faults, systematic work has been performed. When a magnet of a PMSG is de-magnetized at different rates (i.e. 33%, 50%, and 100%), we have explored the artifacts in the electric generation. Besides, the torque performances of the generator at rated load are examined and the flux density distributions are revealed. The rated torque decreased substantially when the demagnetization rate of the magnet increased.

Convex economic model predictive control for blade loads mitigation on wind turbines

AbstractEconomic model predictive control (EMPC) has received increasing attention in the wind energy community due to its ability to trade‐off economic objectives with ease. However, for wind turbine applications, inherent nonlinearities, such as from aerodynamics, pose difficulties in attaining a convex optimal control problem (OCP), by which real‐time deployment is not only possible but also a globally optimal solution is guaranteed. A variable transformation can be utilized to obtain a convex OCP, where nominal variables, such as rotational speed, pitch angle, and torque, are exchanged with an alternative set in terms of power and energy. The ensuing convex EMPC (CEMPC) possesses linear dynamics, convex constraints, and concave economic objectives and has been successfully employed to address power control and tower fatigue alleviation. This work focuses on extending the blade loads mitigation aspect of the CEMPC framework by exploiting its individual pitch control (IPC) capabilities, resulting in a novel CEMPC‐IPC technique. This extension is made possible by reformulating static blade and rotor moments in terms of individual blade aerodynamic powers and rotational kinetic energy of the drivetrain. The effectiveness of the proposed method is showcased in a mid‐fidelity wind turbine simulation environment in various wind cases, in which comparisons with a basic CEMPC without load mitigation capability and a baseline IPC are made.

A CFD‐based analysis of dynamic induction techniques for wind farm control applications

SummaryRecently, dynamic induction control is gaining the interest of the wind energy community as a promising strategy to increase the overall wind farm power production. Such a technique is based on a dynamic variation of the upstream rotor thrust, generated through a suitable blade pitch motion, to promote a faster wake recovery. Notwithstanding some promising results already published, the knowledge of the physical mechanism, connecting dynamic induction to the increased in‐wake velocity, was not yet exploited to enhance control effectiveness. This paper, through a computational fluid dynamics procedure based on large eddy simulations coupled with actuator line models, provides a description of the working principles of this control from a fluid dynamics standpoint. The analyses show that the faster recovery is strictly connected to the ability of the blade tip vortices to roll up and sucking energy from the outer flow. Exploiting such knowledge, a novel control strategy, which improves the vortex roll up mechanism, is proposed and analyzed. The new control proved more effective than standard techniques especially for very low turbine spacing.

A passively self‐adjusting floating wind farm layout to increase the annual energy production

AbstractWake losses inside a wind farm occur due to the aerodynamic interactions when a downwind turbine is in the wake of upwind turbines. The ability of floating offshore wind turbines (FOWTs) to relocate their positions in the horizontal plane introduces an opportunity to decrease the wake losses in a floating wind farm (FWF). Our goal is to use this ability to passively move the downwind FOWT out of the wake of upwind ones. Since the mooring system (MS) attached to a FOWT is responsible for its station keeping, the horizontal motions of the FOWT depend on the MS design. Hence, if we can design the MS to passively move the FOWT out of the wake, we can increase the FWF annual energy production (AEP). In this paper, we investigate if we can benefit from relocating FOWTs in a FWF and increase its AEP. In addition, we present a novel approach that considers the ability of a FOWT to relocate its position as a new degree of freedom (DoF) in the FWF layout design. This means we will have a self‐adjusting wind farm layout where the FOWTs passively re‐arrange themselves depending on the wind direction and the wind speed. Consequently, we will have a slightly different wind farm layout for every wind direction and every wind speed. To achieve this layout, we include the MS design as part of the FWF's layout design. In a self‐adjusting FWF layout, each FOWT is attached to a customized MS design allowing it to relocate its position in the best way possible according to the wind direction, to increase the overall AEP of the wind farm. The results of one case study show that the novel approach can increase the FWF's AEP by 1.6% when compared with a current state of the art optimized floating wind farm layout. Finally, we implemented our method as an open‐source python tool to be used and enhanced further within the wind energy community.

Wind tunnel research, dynamics, and scaling for wind energy

The interaction of wind turbines with turbulent atmospheric boundary layer (ABL) flows represents a complex multi-scale problem that spans several orders of magnitudes of spatial and temporal scales. These scales range from the interactions of large wind farms with the ABL (on the order of tens of kilometers) to the small length scale of the wind turbine blade boundary layer (order of a millimeter). Detailed studies of multi-scale wind energy aerodynamics are timely and vital to maximize the efficiency of current and future wind energy projects, be they onshore, bottom-fixed offshore, or floating offshore. Among different research modalities, wind tunnel experiments have been at the forefront of research efforts in the wind energy community over the last few decades. They provide valuable insight about the aerodynamics of wind turbines and wind farms, which are important in relation to optimized performance of these machines. The major advantage of wind tunnel research is that wind turbines can be experimentally studied under fully controlled and repeatable conditions allowing for systematic research on the wind turbine interactions that extract energy from the incoming atmospheric flow. Detailed experimental data collected in the wind tunnel are also invaluable for validating and calibrating numerical models.

Offshore reanalysis wind speed assessment across the wind turbine rotor layer off the United States Pacific coast

Abstract. The California Pacific coast is characterized by considerable wind resource and areas of dense population, propelling interest in offshore wind energy as the United States moves toward a sustainable and decarbonized energy future. Reanalysis models continue to serve the wind energy community in a multitude of ways, and the need for validation in locations where observations have been historically limited, such as offshore environments, is strong. The U.S. Department of Energy (DOE) owns two lidar buoys that collect wind speed observations across the wind turbine rotor layer along with meteorological and oceanographic data near the surface to characterize the wind resource. Lidar buoy data collected from recent deployments off the northern California coast near Humboldt County and the central California coast near Morro Bay allow for validation of commonly used reanalysis products. In this article, wind speeds from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), the Climate Forecast System version 2 (CFSv2), the North American Regional Reanalysis (NARR), the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), and the analysis system of the Rapid Refresh (RAP) are validated at heights within the wind turbine rotor layer ranging from 50 to 100 m. The validation results offer guidance on the performance and uncertainty associated with utilizing reanalyses for offshore wind resource characterization, providing the offshore wind energy community with information on the conditions that lead to reanalysis error. At both California coast locations, the reanalyses tend to underestimate the observed rotor-level wind resource. Occasions of large reanalysis error occur in conjunction with stable atmospheric conditions, wind speeds associated with peak turbine power production (> 10 m s−1), and mischaracterization of the diurnal wind speed cycle in summer months.

Characterising wind shear exponents in the offshore area using Lidar measurements

From a practical standpoint, the 1/7th power law has been extensively used for wind speed extrapolation in wind energy community. However, numerous studies have suggested that unrestricted use of the 1/7th power law can be sometimes misleading due to the highly variable nature of wind shear. Hence, the main goal of this study is to unveil the wind shear characteristics at an offshore site using 3-yr wind Lidar measurement data. The calculation indicates that more than 80% of wind shear exponents (WSEs) are less than 0.14, and the occurrence of negative WSE is more frequent than those over-land. The mean value of WSE increases with wind speed, while the variance exhibits a decreasing pattern. The seasonal variability of WSE is apparent, with a maximum in April and a minimum in September and October. Likewise, the WSE varies within a diurnal cycle, in which higher values are often observed in night-times, while lower and almost constant values are found during daytime. In addition, the effect of atmospheric stability on WSE is also evident, with larger mean values obtained in near-neutral and stable conditions.

Evaluation of a lattice Boltzmann-based wind-turbine actuator line model against a Navier-Stokes approach

Due to the cost and difficulty to precisely measure aerodynamic quantities in onshore and offshore wind farms, researchers often rely on high-fidelity large eddy simulation, based on Navier-Stokes flow solvers. However, the cost of such simulation is very high and does not allow, in practice, extensive parametric studies for large wind farms. Among others, the lattice Boltzmann method is a good candidate for much faster, ExaScale wind farm flow simulations. The present paper aims to assess the validity of a lattice Boltzmann-based actuator line model and highlights its strengths and potential weaknesses. With this intent, comparisons against a Navier-Stokes approach commonly used in the wind energy community are performed. We assess the potential of the lattice Boltzmann method to reduce the computational cost of such simulations by analyzing the performance of the different solvers and their scalability. The lattice Boltzmann-based waLBerla solver reduces the computational costs significantly compared to SOWFA while maintaining the same accuracy as the Navier-Stokes-based method. Furthermore, we show that a multi-GPU implementation leads to an even more drastic reduction of the computational time, achieving faster-than-real-time simulations. This performance will allow extensive parametric studies over large wind farms in future studies.

Field Study of Turbulence Intensity measurement by Nacelle Mounted Lidar (NML)

In this paper, Nacelle Mounted LiDAR (NML) was used to study Turbulence Intensity (TI) by dataset from three measurement campaigns, using two approaches: the white box test and the black box test. The white box test was to compare TI LOS using each Line Of Sight, while the black box test was to compare TI Hub using all LOS by relative reconstruction algorithm at wind turbine hub height. The result of white box test showed that the correlation coefficient of TI LOS varied from 0.923 to 0.955 and the slope varied from 0.978 to 1.030. The result of black box test showed that the correlation coefficient of TI Hub is 0.8337∼0.8924 and the slope is 0.904∼0.935. This study provided some promising results to wind energy community, which could be the evidence base for the further investigation for the temporal-spatial turbulence structure in low Atmospheric Boundary Layer.

Estimation of Damage Equivalent Loads of Drivetrain of Wind Turbines using Machine Learning

In the recent years machine learning techniques have attracted the attention of wind energy community to make use of the large amount of available data produced from the running wind turbines. These modern wind turbines are typically equipped with measurement systems and sensors that can provide a wealth of information about the operating conditions of the machine. Nevertheless, not all the acquired raw data can be used effectively to enhance the operation of a turbine. This work addresses the question of estimating the damage equivalent loads (DEL) of different components of a drivetrain. The estimation is based on low frequency sampled typically available SCADA measurements. Typical SCADA measurements that are used as input for the estimation model are generator rotational speed, low speed shaft torque and generator torque as well as, wind speed and direction. Several machine learning methods as random forests (RF), support vector machines (SVM), linear regression (LR), decision trees and neural networks (NN) were developed, exhibiting different behavior for each approach. The qualitative and quantitative performance of each algorithm are evaluated and compared against each other. Furthermore, analysis of importance of the input features is presented.

International assessment of priority environmental issues for land-based and offshore wind energy development

Non-technical summary A substantial increase in wind energy deployment worldwide is required to help achieve international targets for decreasing global carbon emissions and limiting the impacts of climate change. In response to global concerns regarding the environmental effects of wind energy, the International Energy Agency Wind Technical Collaborative Program initiated Task 34 – Working Together to Resolve Environmental Effects of Wind Energy or WREN. As part of WREN, this study performed an international assessment with the global wind energy and environmental community to determine priority environmental issues over the next 5‒10 years and help support collaborative interactions among researchers, developers, regulators, and stakeholders. Technical summary A systematic assessment was performed using feedback from the international community to identify priority environmental issues for land-based and offshore wind energy development. Given the global nature of wind energy development, feedback was of interest from all countries where such development is underway or planned to help meet United Nations Intergovernmental Panel on Climate Change targets. The assessment prioritized environmental issues over the next 5–10 years associated with wind energy development and received a total of 294 responses from 28 countries. For land-based wind, the highest-ranked issues included turbine collision risk for volant species (birds and bats), cumulative effects on species and ecosystems, and indirect effects such as avoidance and displacement. For offshore wind, the highest-ranked issues included cumulative effects, turbine collision risk, underwater noise (e.g. marine mammals and fish), and displacement. Emerging considerations for these priorities include potential application to future technologies (e.g. larger turbines and floating turbines), new stressors and species in frontier regions, and cumulative effects for multiple projects at a regional scale. For both land-based and offshore wind, effectiveness of minimization measures (e.g. detection and deterrence technologies) and costs for monitoring, minimization, and mitigation were identified as overarching challenges. Social media summary Turbine collisions and cumulative effects among the international environmental priorities for wind energy development.

Storm Anatol over Europe in December 1999: impacts on societal and energy infrastructure

Abstract. Storm Anatol impacted the North Sea and northern Europe on 3–4 December 1999. It brought hurricane force winds to Denmark and northern Germany, and high winds also in Sweden and countries around the Baltic Sea. For many meteorological stations in Denmark, the wind speeds were the highest on record and the storm was ranked as a century event. The storm impacts included extensive forest damage, fatalities, hundreds of injuries, power outages, transportation interruptions, as well as storm surge flooding on the west coast of Denmark. Strongly committed to wind energy, Denmark lost 13 onshore wind turbines destroyed during the storm. An important industry insurer noted that this was a remarkably low number, considering the storm intensity and the large number of turbines (>3500) installed in the country. In 1999, offshore wind energy was just getting started in Europe, and the storm provided an important test of environmental extreme conditions impacting offshore infrastructure. This contribution takes a closer look at the regional met-ocean conditions during the storm. A brief overview is made of the wind field and available wave measurements from the North Sea. An examination is made of water level measurements from around the North Sea to characterize the storm surge and identify possible meteo-tsunamis and infragravity waves. Offshore accidents are briefly discussed to assess if there had been unusual wave strikes on shipping or platforms. At the time of the storm in 1999, there was a growing awareness in the scientific community of possible changes in ambient sea state conditions and the increasing threat of rogue waves. The offshore wind energy community had become aware from the impact of rogue waves from damage at the research platform FINO1 in the southern North Sea during severe storms in 2006, 2007, 2009, and 2013. Storm Anatol may have been another rogue wave storm at an earlier stage of offshore wind energy development.

A Review on Modeling of Bionic Flow Control Methods for Large-Scale Wind Turbine Blades

Due to complicated working conditions, the normal operating large-scale wind turbine blades are often suffering from some inevitable problems, i.e., friction adhesion, flow separation and acoustic noise, which may significantly affect the aerodynamic performance of the blades and thus the wind turbine system. Therefore, effective measurements must be taken to solve these issues. Correspondingly, several novel bionic flow control methods by mimicking shark skin, whale fin and owl wing, i.e., riblet, leading-edge protuberance and trailing-edge serration, have been recently studied, and good progresses have been made in terms of effectiveness, analysis and mechanism. However, these potential techniques are unable to be widely applied within wind energy community due to the lack of reasonable modeling methods, clearly reflecting the effect of bionic structures on the flow field around, which results in incapability to carry out further optimal design of bionic blade. To this end, this review paper first concentrated on a summary of the control mechanisms of three bionic techniques. Based on this, some feasible ideas of model buildup were proposed. Finally, the flow analyses around the typical blade airfoils were chosen as case studies to verify the feasibility and accuracy of these simulation methods.