Power curve measurement with a nacelle mounted lidar

Nacelle‐based lidars are an attractive alternative to conventional mast base reference wind instrumentation where the erection of a mast is expensive, for example offshore. In this paper, the use of this new technology for the specific application of wind turbine power performance measurement is tested. A pulsed lidar prototype, measuring horizontally, was installed on the nacelle of a multi‐megawatt wind turbine. A met mast with a top‐mounted cup anemometer standing at two rotor diameters in front of the turbine was used as a reference. After a data‐filtering step, the comparison of the 10 min mean wind speed measured by the lidar to that measured by the cup anemometer showed a deviation of about 1.4% on average. The power curve measured with the lidar was very similar to that measured with the cup anemometer although the lidar power curve was slightly distorted because of the deviation in wind speed measurements. A lower scatter in the power curve was observed for the lidar than for the mast. Since the lidar follows the turbine nacelle as it yaws, it always measures upwind. The wind measured by the lidar therefore shows a higher correlation with the turbine power fluctuations than the wind measured by the mast. Finally, the lidar is never in the wake of the turbine under test contrary to the cup anemometer; therefore, the wind sector usable for power curve measurement was larger than the sector for which the cup anemometer was not disturbed by any obstacle. The power curve obtained with the lidar for the wind sector in which the mast is in the wake of the turbine under test compared well with the power curve obtained on the standard sector. Copyright © 2013 John Wiley & Sons, Ltd.     

Using nacelle‐based wind speed observations to improve power curve modeling for wind power forecasting

Wind power forecasting for projection times of 0–48 h can have a particular value in facilitating the integration of wind power into power systems. Accurate observations of the wind speed received by wind turbines are important inputs for some of the most useful methods for making such forecasts. In particular, they are used to derive power curves relating wind speeds to wind power production. By using power curve modeling, this paper compares two types of wind speed observations typically available at wind farms: the wind speed and wind direction measurements at the nacelles of the wind turbines and those at one or more on‐site meteorological masts (met masts). For the three Australian wind farms studied in this project, the results favor the nacelle‐based observations despite the inherent interference from the nacelle and the blades and despite calibration corrections to the met mast observations. This trend was found to be stronger for wind farm sites with more complex terrain. In addition, a numerical weather prediction (NWP) system was used to show that, for the wind farms studied, smaller single time‐series forecast errors can be achieved with the average wind speed from the nacelle‐based observations. This suggests that the nacelle‐average observations are more representative of the wind behavior predicted by an NWP system than the met mast observations. Also, when using an NWP system to predict wind farm power production, it suggests the use of a wind farm power curve based on nacelle‐average observations instead of met mast observations. Further, it suggests that historical and real‐time nacelle‐average observations should be calculated for large wind farms and used in wind power forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

Turbine‐scale wind field measurements using dual‐Doppler lidar

Spatially resolved measurements of microscale winds are retrieved using scanning dual‐Doppler lidar and then compared with independent in situ wind measurements. Data for this study were obtained during a month‐long field campaign conducted at a site in north‐central Oklahoma in November of 2010. Observational platforms include one instrumented 60 m meteorological tower and two scanning coherent Doppler lidars. The lidars were configured to perform coordinated dual‐Doppler scans surrounding the 60 m tower, and the resulting radial velocity observations were processed to retrieve the three‐component velocity vector field on surfaces defined by the intersecting scan planes. The dual‐Doppler analysis method is described, and three‐dimensional visualizations of the retrieved fields are presented. The retrieved winds are compared with sonic anemometer (SA) measurements at the 60 m level on the tower. The Pearson correlation coefficient between the retrievals and the SA wind speeds was greater than 0.97, and the wind direction difference was very small (<0.1^o), suggesting that the dual‐Doppler technique can be used to examine fine‐scale variations in the flow. However, the mean percent difference between the SA and dual‐Doppler wind speed was approximately 15%, with the SA consistently measuring larger wind speeds. To identify the source of the discrepancy, a multi‐instrument intercomparison study was performed involving lidar wind speeds derived from standard velocity‐azimuth display (VAD) analysis of plan position indicator scan data, a nearby 915 MHz radar wind profiler (RWP) and radiosondes. The lidar VAD, RWP and radiosondes wind speeds were found to agree to within 3%. By contrast, SA wind speeds were found to be approximately 14% larger than the lidar VAD wind speeds. These results suggest that the SA produced wind speeds that were too large. Copyright © 2013 John Wiley & Sons, Ltd.     

Classifying rotor‐layer wind to reduce offshore available power uncertainty

Rotor‐layer wind resource and turbine available power uncertainties prior to wind farm construction may contribute to significant increases in project risk and costs. Such uncertainties exist in part due to limited offshore wind measurements between 40 and 250 m and the lack of empirical methods to describe wind profiles that deviate from a priori, expected power law conditions. In this article, we introduce a novel wind profile classification algorithm that accounts for nonstandard, unexpected profiles that deviate from near power law conditions. Using this algorithm, offshore Doppler wind lidar measurements in the Mid‐Atlantic Bight are classified based on goodness‐of‐fit to several mathematical expressions and relative speed criteria. Results elucidate the limitations of using power law extrapolation methods to approximate average wind profile shape/shear conditions, as only approximately 18% of profiles fit well with this expression, while most consist of unexpected wind shear. Further, results demonstrate a relationship between classified profile variability and coastal meteorological features, including stability and offshore fetch. Power law profiles persist during unstable conditions and relatively weaker northeasterly flow from water (large fetch), whereas unexpected classified profiles are prevalent during stable conditions and stronger southwesterly flow from land (small fetch). Finally, the magnitude of the discrepancy between hub‐height wind speed and rotor equivalent wind speed available power estimates varies by classified wind‐profile type. During unexpected classified profiles, both a significant overprediction and underprediction of hub‐height wind available power is possible, illustrating the importance of accounting for site‐specific rotor‐layer wind shear when predicting available power.     

Accounting for the speed shear in wind turbine power performance measurement

The current IEC standard for wind turbine power performance measurement only requires measurement of the wind speed at hub height assuming this wind speed to be representative for the whole rotor swept area. However, the power output of a wind turbine depends on the kinetic energy flux, which itself depends on the wind speed profile, especially for large turbines. Therefore, it is important to characterize the wind profile in front of the turbine, and this should be preferably achieved by measuring the wind speed over the vertical range between lower and higher rotor tips. In this paper, we describe an experiment in which wind speed profiles were measured in front of a multimegawatt turbine using a ground–based pulsed lidar. Ignoring the vertical shear was shown to overestimate the kinetic energy flux of these profiles, in particular for those deviating significantly from a power law profile. As a consequence, the power curve obtained for these deviant profiles was different from that obtained for the ‘near power law’ profiles. An equivalent wind speed based on the kinetic energy derived from the measured wind speed profile was then used to plot the performance curves. The curves obtained for the two kinds of profiles were very similar, corresponding to a significant reduction of the scatter for an undivided data set. This new method for power curve measurement results in a power curve less sensitive to shear. It is therefore expected to eventually reduce the power curve measurement uncertainty and improve the annual energy production estimation. Copyright © 2011 John Wiley & Sons, Ltd.     

A spinner‐integrated wind lidar for enhanced wind turbine control

A field test with a continuous wave wind lidar (ZephIR) installed in the rotating spinner of a wind turbine for unimpeded preview measurements of the upwind approaching wind conditions is described. The experimental setup with the wind lidar on the tip of the rotating spinner of a large 80 m rotor diameter, 59 m hub height 2.3 MW wind turbine (Vestas NM80), located at Tjæreborg Enge in western Denmark is presented. Preview wind data at two selected upwind measurement distances, acquired during two measurement periods of different wind speed and atmospheric stability conditions, are analyzed. The lidar‐measured speed, shear and direction of the wind field previewed in front of the turbine are compared with reference measurements from an adjacent met mast and also with the speed and direction measurements on top of the nacelle behind the rotor plane used by the wind turbine itself. Yaw alignment of the wind turbine based on the spinner lidar measurements is compared with wind direction measurements from both the nearby reference met mast and the turbine's own yaw alignment wind vane. Furthermore, the ability to detect vertical wind shear and vertical direction veer in the inflow, through the analysis of the spinner lidar data, is investigated. Finally, the potential for enhancing turbine control and performance based on wind lidar preview measurements in combination with feed‐forward enabled turbine controllers is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Performance evaluation of a floating lidar buoy in nearshore conditions

This work provides a signal‐processing and statistical‐error analysis methodology to assess key performance indicators for a floating Doppler wind lidar. The study introduces the raw‐to‐clean data processing chain, error assessment indicators and key performance indicators, as well as two filtering methods at post‐processing level to alleviate the impact of angular motion and spatial variability of the wind flow on the performance indicators. Towards this aim, the study mainly revisits horizontal wind speed (HWS) and turbulence intensity measurements with a floating ZephIR 300 lidar buoy during a 38 day nearshore test campaign in Pont del Petroli (Barcelona). Typical day cases along with overall statistics for the whole campaign are discussed to illustrate the methodology and processing tools developed. Copyright © 2017 John Wiley & Sons, Ltd.     

Testing and validation of multi‐lidar scanning strategies for wind energy applications

Several factors cause lidars to measure different values of turbulence than an anemometer on a tower, including volume averaging, instrument noise and the use of a scanning circle to estimate the wind field. One way to avoid the use of a scanning circle is to deploy multiple scanning lidars and point them toward the same volume in space to collect velocity measurements and extract high‐resolution turbulence information. This paper explores the use of two multi‐lidar scanning strategies, the tri‐Doppler technique and the virtual tower technique, for measuring 3‐D turbulence. In summer 2013, a vertically profiling Leosphere WindCube lidar and three Halo Photonics Streamline lidars were operated at the Southern Great Plains Atmospheric Radiation Measurement site to test these multi‐lidar scanning strategies. During the first half of the field campaign, all three scanning lidars were pointed at approximately the same point in space and a tri‐Doppler analysis was completed to calculate the three‐dimensional wind vector every second. Next, all three scanning lidars were used to build a ‘virtual tower’ above the WindCube lidar. Results indicate that the tri‐Doppler technique measures higher values of horizontal turbulence than the WindCube lidar under stable atmospheric conditions, reduces variance contamination under unstable conditions and can measure high‐resolution profiles of mean wind speed and direction. The virtual tower technique provides adequate turbulence information under stable conditions but cannot capture the full temporal variability of turbulence experienced under unstable conditions because of the time needed to readjust the scans. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of potential power production at on‐ and offshore sites

This article presents analyses of the potential power production from turbines located in the near‐shore and offshore environment relative to an onshore location, using half‐hourly average wind speed data from four sites in the Danish wind monitoring network. These measurement sites are located in a relatively high wind speed environment, and data from these sites indicate a high degree of spatial coherence. For these sites and representative turbine specifications (rated power 1·3–2 W) the fraction of time with power output in excess of 500 kW is twice as high for the offshore location as for the land site. Also, the fraction of time with negligible power production (defined as <100 kW output from the turbines described herein) is less than 20% for the offshore site and twice as high at the land‐based location. Capacity factors are higher for coastal sites than for the land site, and the annual capacity factor for the offshore location is twice that of the land site. Potential power output at the offshore site exhibits approximately the same seasonal variation as at the land site but little diurnal variation. Copyright © 2001 John Wiley & Sons, Ltd.     

Copula‐based model for wind turbine power curve outlier rejection

Power curve measurements provide a conventional and effective means of assessing the performance of a wind turbine, both commercially and technically. Increasingly high wind penetration in power systems and offshore accessibility issues make it even more important to monitor the condition and performance of wind turbines based on timely and accurate wind speed and power measurements. Power curve data from Supervisory Control and Data Acquisition (SCADA) system records, however, often contain significant measurement deviations, which are commonly produced as a consequence of wind turbine operational transitions rather than stemming from physical degradation of the plant. Using such raw data for wind turbine condition monitoring purposes is thus likely to lead to high false alarm rates, which would make the actual fault detection unreliable and would potentially add unnecessarily to the costs of maintenance. To this end, this paper proposes a probabilistic method for excluding outliers, developed around a copula‐based joint probability model. This approach has the capability of capturing the complex non‐linear multivariate relationship between parameters, based on their univariate marginal distributions; through the use of a copula, data points that deviate significantly from the consolidated power curve can then be removed depending on this derived joint probability distribution. After filtering the data in this manner, it is shown how the resulting power curves are better defined and less subject to uncertainty, whilst broadly retaining the dominant statistical characteristics. These improved power curves make subsequent condition monitoring more effective in the reliable detection of faults. Copyright © 2013 John Wiley & Sons, Ltd.     

Validation of a CFD model with a synchronized triple‐lidar system in the wind turbine induction zone

A novel validation methodology allows verifying a CFD model over the entire wind turbine induction zone using measurements from three synchronized lidars. The validation procedure relies on spatially discretizing the probability density function of the measured free‐stream wind speed. The resulting distributions are reproduced numerically by weighting steady‐state Reynolds averaged Navier‐Stokes simulations accordingly. The only input varying between these computations is the velocity at the inlet boundary. The rotor is modelled using an actuator disc. So as to compare lidar and simulations, the spatial and temporal uncertainty of the measurements is quantified and propagated through the data processing. For all velocity components the maximal difference between measurements and model are below 4.5% relative to the average wind speed for most of the validation space. This applies to both mean and standard deviation. One rotor radius upstream the difference reaches maximally 1.3% for the axial component. © 2017 The Authors. Wind Energy Published by John Wiley & Sons, Ltd.     

Simulation comparison of wake mitigation control strategies for a two‐turbine case

Wind turbines arranged in a wind plant impact each other through their wakes. Wind plant control is an active research field that attempts to improve wind plant performance by coordinating control of individual turbines to take into account these turbine–wake interactions. In this paper, high‐fidelity simulations of a two‐turbine fully waked scenario are used to investigate several wake mitigation strategies, including modification of yaw and tilt angles of an upstream turbine to induce wake skew, as well as repositioning of the downstream turbine. The simulation results are compared through change relative to a baseline operation in terms of overall power capture and loading on the upstream and downstream turbine. Results demonstrated improved power production for all methods. Analysis of control options, including individual pitch control, shows potential to minimize the increase of, or even reduce, turbine loads.Copyright © 2014 John Wiley & Sons, Ltd.     

Estimating the potential yield of small building‐mounted wind turbines

The wind profile in the urban boundary layer is described as following a logarithmic curve above the mean building height and an exponential curve below it. By considering the urban landscape to be an array of cubes, a method is described for calculating the surface roughness length and displacement height of this profile. Firstly, a computational fluid dynamics (CFD) model employing a k‐? turbulence model is used to simulate the flow around a cube. The results of this simulation are compared with wind tunnel measurements in order to validate the code. Then, the CFD model is used to simulate the wind flow around a simple pitched‐roof building, using a semi‐logarithmic inflow profile. An array of similar pitched‐roof houses is modelled using CFD to determine the flow characteristics within an urban area. Mean wind speeds at potential turbine mounting points are studied, and optimum mounting points are identified for different prevailing wind directions. A methodology is proposed for estimating the energy yield of a building‐mounted turbine from simple information such as wind atlas wind speed and building density. The energy yield of a small turbine on a hypothetical house in west London is estimated. The energy yield is shown to be very low, particularly if the turbine is mounted below rooftop height. It should be stressed that the complexity of modelling such urban environments using such a computational model has limitations and results can only be considered approximate, but nonetheless, gives an indication of expected yields within the built environment. Copyright © 2007 John Wiley & Sons, Ltd.     

The influence of non‐logarithmic wind speed profiles on potential power output at Danish offshore sites

Detailed knowledge of mean wind speed profiles is essential for properly assessing the power output of a potential wind farm. Since atmospheric stratification plays a crucial role in affecting wind speed profiles, obtaining a detailed picture of the climatology of stability conditions at a given site is very important. In the present study, long time series from offshore measurement sites around Denmark are analysed, with the aim of quantifying the role of atmospheric stability in wind speed profiles and in our ability to model them. A simple method for evaluating stability is applied, and the resulting statistics of the atmospheric stratification is thoroughly studied. A significant improvement in the mean wind speed profile prediction is obtained by applying a stability correction to the logarithmic profiles suitable for neutral conditions. These results are finally used to estimate power densities at different heights. Copyright © 2004 John Wiley & Sons, Ltd.     

Analysis and study of two‐dimensional parameter bifurcation of wind power farms and composite loads

This study focuses on the stability of power system based on codimension‐two bifurcation theory. In this paper, we investigate the impact of load modeling on permissible wind power generation margins in distribution networks. The study considers codimension‐two bifurcations of equilibria and limit cycles in wind power systems depending on varying two parameters simultaneously. The principle parameter is the wind power generation, and the other parameter depends on the different types of loads. The types of loads are ZIP, exponential recovery, dynamic induction loads, and composite load models. To study the effects of the induction motor loads, the proportion of the static component in the motor load is changed and assessed with respect to their mechanical loads. Wind generation margin boundaries are traced, and saddle‐node, Hopf, and limit‐induced bifurcation branches are obtained, delimiting the stable and unstable operating regions in the parameter space. The analysis presented in this paper can pave the way for determining methods for improving and monitoring these margins with consideration to the system parameters and load composition.     

One‐year observations of the wind distribution and low‐level jet occurrence at Braunschweig,North German Plain

A data set consisting of one‐year vertical profiles of horizontal wind speed obtained with lidar at Braunschweig Airport, North German Plain, is analyzed with respect to the low‐level jet (LLJ). The observations reveal a typical LLJ altitude between 80 and 360 m, a frequency of occurrence up to almost 9% for some altitudes, and a typical wind speed between 4 and 9 m s^?1. LLJ events occurred most frequently in summer during the night. In the winter, LLJs were observed both during day and night. The Weibull distribution for wind speed is presented for different heights. The most probable wind speed of the Weibull distribution increases from 4 m s^?1 at 40 m altitude to values exceeding 7 m s^?1 for altitudes above 240 m. There is a significant difference for the Weibull parameters determined with a monthly, seasonal and annual data set. The contribution of the LLJ to the overall wind speed distribution is analyzed. An LLJ event occurred on 52% of the days over the year, with a total measurement time of 739 h. As the typical rated speed for onshore wind turbines is in the range from 11.5 to 14.5 m s^?1 and the typical hub height is in the range of 100 to 150 m, it can be expected that wind turbines are affected by the LLJ. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluation of a wind speed estimator for effective hub‐height and shear components

Estimates of the effective wind speed disturbances acting on a wind turbine are useful in a variety of control applications. With some simplifications, it is shown that for zero yaw error, any wind field interacting with a turbine can be equivalently described using a hub‐height (uniform) component as well as linear horizontal and vertical shear components. A Kalman filter‐based wind speed estimator is presented for estimation of these effective hub‐height and shear components. The wind speed estimator is evaluated in the frequency domain using the FAST aeroelastic simulator with the National Renewable Energy Laboratory's 5 MW reference wind turbine model and realistic hub‐height and shear disturbances. In addition, the impact of the inflow model, used to simulate the rotor aerodynamics, on the Kalman filter performance is investigated. It is found that the estimator accuracy strongly depends on the inflow model used. In general, the estimator performs well up to a bandwidth of 1 Hz when the inflow model used for simulation matches the model used to create the linear Kalman filter model and blade pitch angle remains close to the linearization operating point. However, inaccuracies in the linear model of the turbine when dynamic inflow is used for simulation as well as nonlinearities in the turbine dynamics due to blade pitch actuation cause performance to degrade. Finally, the improvement gained by employing a non‐causal wind speed estimator is assessed, showing a minor increase in performance. Copyright © 2014 John Wiley & Sons, Ltd.     

On the robustness of the fixed points for a dynamical performance characteristic—or: a closer look at the Langevin power curve

In this paper, we review a dynamical power curve concept that was introduced in earlier publications and shown to provide results for a wind turbine's power characteristic with several benefits compared with the IEC 61400‐12‐1 standard procedure. After summarizing the theoretical concept based on the theory of Langevin processes and their reconstruction, we enlarge on a number of specific practical issues. Special attention is paid to the convergence or robustness of the reconstructed results, and their dependence on different settings for the data analysis scheme is studied. A key issue for the procedure that is investigated in this paper is the variability of the wind speed data that may be controlled by applying a specific data filter. It is seen that the necessity for filtering depends both on the time scales present in the wind data in relation to the wind turbine power dynamics and to some degree also on the correlation between the wind and the power signal. The observations and findings altogether suggest that the dynamical performance characteristic, as it is considered here, is definitely a promising concept, particularly since it allows much flexibility in the handling of noisy performance data, but with some technical difficulties that demand a careful consideration in order to obtain reproducible and representative results. Copyright © 2014 John Wiley & Sons, Ltd.     

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

The issue of tracking the optimal power for wind energy conversion systems (WECSs) via regulating the rotor speed of the generator is taken into account in this study. Additionally, a novel polynomial observer is proposed for estimating not only aerodynamic torque in WECSs but also d‐axis and electromagnetic torque. Therefore, in this new approach, only the rotor speed of the generator is required to be measured instead of measuring all state variables. With the new observer form, the aerodynamic torque does not need to satisfy any constraints, which are mandatory in the previous methods. It should be noted that this methodology has not been investigated for the WECSs in any previous papers. To design a complete control system, a linear optimal control method cooperated with the polynomial observer is employed to track the optimal trajectory of a generator. Moreover, in this paper, the permanent magnet synchronous generator is used. In addition, on the basis of the Lyapunov theory and sum‐of‐square (SOS) technique, the conditions for observer synthesis are derived in the main theorems. Finally, the simulation results are provided to prove the effectiveness and merit of the proposed method.     

Investigation of wake interaction using full‐scale lidar measurements and large eddy simulation

In this paper, wake interaction resulting from two stall regulated turbines aligned with the incoming wind is studied experimentally and numerically. The experimental work is based on a full‐scale remote sensing campaign involving three nacelle mounted scanning lidars. A thorough analysis and interpretation of the measurements is performed to overcome either the lack of or the poor calibration of relevant turbine operational sensors, as well as other uncertainties inherent in resolving wakes from full‐scale experiments. The numerical work is based on the in‐house EllipSys3D computational fluid dynamics flow solver, using large eddy simulation and fully turbulent inflow. The rotors are modelled using the actuator disc technique. A mutual validation of the computational fluid dynamics model with the measurements is conducted for a selected dataset, where wake interaction occurs. This validation is based on a comparison between wake deficit, wake generated turbulence, turbine power production and thrust force. An excellent agreement between measurement and simulation is seen in both the fixed and the meandering frame of reference. Copyright © 2015 John Wiley & Sons, Ltd.