Real-time rotor effective wind speed estimation based on actuator disc theory: Design and full-scale experimental validation

The use of state estimation techniques offers a means of inferring rotor effective wind speed from standard measurements of wind turbines. Typical wind speed estimators rely upon a pre-computed quasi-steady aerodynamic mapping, which describes the relationship between pitch angle and tip-speed ratio and the power coefficient. In practice, the static mapping does not capture the influence of turbine structural dynamics and atmospheric turbulence, inevitably resulting in poor performance of the wind speed estimation. In addition, the turbine aerodynamic properties might not be easily accessible. Thus, this paper presents a rotor effective wind speed estimation method that obviates the requirement for prior knowledge of turbine power coefficients. Specifically, the proposed method exploits a simple actuator disc model, where the aerodynamic power and thrust coefficients can be characterized in terms of axial induction factors. Based on this insight and standard turbine measurements, real-time estimation of rotor effective wind speed and axial induction factors can then be achieved using a simplified turbine drive-train model and an extended Kalman filter. In addition, the actuator disc model can be updated easily over time by calibrating solely two correction factors. Thus, the proposed algorithm presents an alternative for estimating the rotor effective wind speed, which is valuable for numerous applications, for example, LiDAR-assisted control and coherence studies.     

Short‐term spatio‐temporal prediction of wind speed and direction

This paper aims to produce a low‐complexity predictor for the hourly mean wind speed and direction from 1 to 6 h ahead at multiple sites distributed around the UK. The wind speed and direction are modelled via the magnitude and phase of a complex‐valued time series. A multichannel adaptive filter is set to predict this signal on the basis of its past values and the spatio‐temporal correlation between wind signals measured at numerous geographical locations. The filter coefficients are determined by minimizing the mean square prediction error. To account for the time‐varying nature of the wind data and the underlying system, we propose a cyclo‐stationary Wiener solution, which is shown to produce an accurate predictor. An iterative solution, which provides lower computational complexity, increased robustness towards ill‐conditioning of the data covariance matrices and the ability to track time‐variations in the underlying system, is also presented. The approaches are tested on wind speed and direction data measured at various sites across the UK. Results show that the proposed techniques are able to predict wind speed as accurately as state‐of‐the‐art wind speed forecasting benchmarks while simultaneously providing valuable directional information. Copyright © 2013 John Wiley & Sons, Ltd.     

An M‐Rice wind speed frequency distribution

Several known statistical distributions can describe wind speed data, the most commonly used being the Weibull family. In this paper, a new law, called ‘M‐Rice’, is proposed for modeling wind speed frequency distributions. Inspired by recent empirical findings that suggest the existence of some cascading process in the mesoscale range, we consider that wind speed can be described by a seasonal AutoRegressive Moving Average (ARMA) model where the noise term is ‘multifractal’, i.e. associated with a random cascade. This leads to the distribution of wind speeds according to the M‐Rice probability distribution function, i.e. a Rice distribution multiplicatively convolved with a normal law. A comparison based on the estimation of the mean wind speed and power density values as well as on the different goodness‐of‐fit tests (the Kolmogorov–Smirnov test, the Kuiper test and the quantile–quantile plot) was made between this new distribution and the Weibull distribution for 35 data sets of wind speed from the Netherlands and Corsica (France) sites. Accordingly, the M‐Rice and Weibull distributions provided comparable performances; however, the quantile–quantile plots suggest that the M‐Rice distribution provides a better fit of extreme wind speed data. Beyond these good results, our approach allows one to interpret the observed values of Weibull parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of simulators for variable‐speed wind turbine transient analysis

This paper presents a comparison of three variable‐speed wind turbine simulators used for a 2 MW wind turbine short‐term transient behaviour study during a symmetrical network disturbance. The simulator with doubly fed induction generator (DFIG) analytical model, the simulator with a finite element method (FEM) DFIG model and the wind turbine simulator with an analytical model of DFIG are compared. The comparison of the simulation results shows the influence of the different modelling approaches on the short‐term transient simulation accuracy. Copyright © 2005 John Wiley & Sons, Ltd.     

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.     

Short‐term forecasting of surface layer wind speed using a continuous random cascade model

This paper describes a statistical method for short‐term forecasting (1–12 h ahead) of surface layer wind speed using only recent observations, relying on the notion of continuous cascades. Inspired by recent empirical findings that suggest the existence of some cascading process in the mesoscale range, we consider that wind speed can be described by a seasonal component and a fluctuating part represented by a ‘multifractal noise’ associated with a random cascade. Performances of our model are tested on hourly wind speed series gathered at various locations in Corsica (France) and the Netherlands. The obtained results show that a better modeling of the noise term based on cascade process enhances the forecast; furthermore, there is a systematic improvement in the prediction as compared with reference models. Copyright © 2011 John Wiley & Sons, Ltd.     

Modelling and control of synchronous generators for wide‐range variable‐speed wind turbines

The modelling and control of a wide‐range variable speed wind turbine based on a synchronous generator are presented. Two different methods to control the operation of the synchronous generator are investigated, i.e. load angle control and instantaneous vector control. The dynamic performance characteristics of these control strategies are evaluated and compared using three model representations of the generator: a non‐reduced order model including both stator and rotor transients, a reduced order model with stator transients neglected, and a steady‐state model that neglects generator electrical dynamics. Assessment on the performance of grid‐side controller is shown during network fault and frequency variation. A simplified wind turbine model representation is also developed and proposed for large‐scale power system studies. Simulation results in Matlab/Simulink are presented and discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms

Turbulence characteristics of the wind farm inflow have a significant impact on the energy production and the lifetime of a wind farm. The common approach is to use the meteorological mast measurements to estimate the turbulence intensity (TI) but they are not always available and the turbulence varies over the extent of the wind farm. This paper describes a method to estimate the TI at individual turbine locations by using the rotor effective wind speed calculated via high frequency turbine data.The method is applied to Lillgrund and Horns Rev-I offshore wind farms and the results are compared with TI derived from the meteorological mast, nacelle mounted anemometer on the turbines and estimation based on the standard deviation of power. The results show that the proposed TI estimation method is in the best agreement with the meteorological mast. Therefore, the rotor effective wind speed is shown to be applicable for the TI assessment in real-time wind farm calculations under different operational conditions. Furthermore, the TI in the wake is seen to follow the same trend with the estimated wake deficit which enables to quantify the turbulence in terms of the wake loss locally inside the wind farm.     

Dynamic models of wind farms with fixed speed wind turbines

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds.The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.     

Detection of faulty high speed wind turbine bearing using signal intensity estimator technique

Bearings are typically used in wind turbines to support shafts and gears that increase rotational speed from a low speed rotor to a higher speed electrical generator. For various bearing applications, condition monitoring using vibration measurements has remained a subject of intense study to the present day since several decades. Various signal processing techniques are used to analyse vibration signals and extract features related to defects. Statistical indicators such as Crest Factor (CF) and Kurtosis (KU) were reported as very sensitive indicators when the presence of the defects is pronounced, whilst their values may come down to the level of undamaged components when the damage is well advanced. Further, these indicators were applied to an acquired data from proposed diagnostic models, test rigs, and instrumentations that were specifically used for particular research tests, and thus, it is essential to undertake further investigations and analysis to assess the influence of other factors such as the structural noise and other operating conditions on the real‐world applications. With this in mind, the present work proposes Signal Intensity Estimator (SIE) as a new technique to discriminate individual types of early natural damage in real‐world wind turbine bearings. Comparative results between SIE and conventional indicators such as KU and CF are also presented. It was concluded that SIE has an advantage over the other fault indicators if sufficient data are provided.     

Cost‐effective shaft torque observer for condition monitoring of wind turbines

Improvement of condition monitoring (CM) systems for wind turbines (WTs) and reduction of the cost of wind energy are possible if knowledge about the condition of different WT components is available. CM based on the WT drive train shaft torque signal can give a better understanding of the gearbox failure mechanisms as well as provide a method for detecting mass imbalance and aerodynamic asymmetry. The major obstacle preventing the industrial application of CM based on the shaft torque signal is the costly measurement equipment which is impractical for long‐term use on operating WTs. This paper suggests a novel approach for low‐cost, indirect monitoring of the shaft torque from standard WT measurements. The shaft torque is estimated recursively from measurements of generator torque, high speed shaft and low speed shaft angular speeds using the well‐known Kalman filter theory. The performance of the augmented Kalman filter with fading memory (AKFF) is compared with the augmented Kalman filter (AKF) using simulated data of the WT for different load conditions, measurement noise levels and WT fault scenarios. A multiple‐model algorithm, based on a set of different Kalman filters, is designed for practical implementation of the shaft torque estimator. Its performance is validated for a scenario where there are frequent changes of operating points. The proposed cost‐effective shaft torque estimator overcomes all major problems, which prevent the industrial application of CM systems based on shaft torque measurements. Future work will be focused on validating the method using experimental data and developing suitable signal processing algorithms for fault detection. Copyright © 2013 John Wiley & Sons, Ltd.     

A new formulation for rotor equivalent wind speed for wind resource assessment and wind power forecasting

The spurt of growth in the wind energy industry has led to the development of many new technologies to study this energy resource and improve the efficiency of wind turbines. One of the key factors in wind farm characterization is the prediction of power output of the wind farm that is a strong function of the turbulence in the wind speed and direction. A new formulation for calculating the expected power from a wind turbine in the presence of wind shear, turbulence, directional shear and direction fluctuations is presented. It is observed that wind shear, directional shear and direction fluctuations reduce the power producing capability, while turbulent intensity increases it. However, there is a complicated superposition of these effects that alters the characteristics of the power estimate that indicates the need for the new formulation. Data from two field experiments is used to estimate the wind power using the new formulation, and results are compared to previous formulations. Comparison of the estimates of available power from the new formulation is not compared to actual power outputs and will be a subject of future work. © 2015 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

Experimental study of a small wind turbine for low‐ and medium‐wind regimes

The results of an experimental assessment of a small prototype battery charging wind turbine designed for low‐ and medium‐wind regimes are presented. The turbine is based on a newly designed axial flow permanent magnet synchronous generator and a three‐bladed rotor with variable twist and taper blades. Overspeed control is performed by a furling mechanism. The turbine has the unique feature of being capable of operating at either 12, 24 or 48 V system voltage, requiring no load control in any case. In the 48 V configuration, the system is capable of providing 2 kWh day^?1 for an average wind speed as low as 3.5 m s^?1 and an air density of 85% of the standard pressure and temperature value. The experimental assessment has been conducted under field conditions with the turbine mounted on a 20 m guy‐wired tubular tower. The experimental power curves are shown to be in good agreement with a detailed aerodynamical and electromechanical model of the turbine for non‐furling conditions and for wind speeds above the theoretical cut‐in speed. In the case of the rapidly spinning load configurations, a finite power production at wind speeds below the theoretical cut‐in speed can be observed, which can be explained in terms of inertia effects. During the measurement campaigns with high loads, we were able to observe bifurcations of the power curve, which can be explained in terms of instabilities arising in situations of transition from attached to separated flow. A full experimental C_p(λ)‐curve has been constructed by operating the turbine under different load conditions and the findings are in good agreement with a variable Reynolds‐number blade‐element momentum model. The three proposed system configurations have been found to operate with a high aerodynamic efficiency with typical values of the power coefficient in the 0.40–0.45 range. Copyright © 2009 John Wiley & Sons, Ltd.     

On design,modelling, and analysis of a 10‐MW medium‐speed drivetrain for offshore wind turbines

The design of a medium‐speed drivetrain for the Technical University of Denmark (DTU) 10‐MW reference offshore wind turbine is presented. A four‐point support drivetrain layout that is equipped with a gearbox with two planetary stages and one parallel stage is proposed. Then, the drivetrain components are designed based on design loads and criteria that are recommended in relevant international standards. Finally, an optimized drivetrain model is obtained via an iterative design process that minimizes the weight and volume. A high‐fidelity numerical model is established via the multibody system approach. Then, the developed drivetrain model is compared with the simplified model that was proposed by DTU, and the two models agree well. In addition, a drivetrain resonance evaluation is conducted based on the Campbell diagrams and the modal energy distribution. Detailed parameters for the drivetrain design and dynamic modelling are provided to support the reproduction of the drivetrain model. A decoupled approach, which consists of global aero‐hydro‐servo‐elastic analysis and local drivetrain analysis, is used to determine the drivetrain dynamic response. The 20‐year fatigue damages of gears and bearings are calculated based on the stress or load duration distributions, the Palmgren‐Miner linear accumulative damage hypothesis, and long‐term environmental condition distributions. Then, an inspection priority map is established based on the failure ranking of the drivetrain components, which supports drivetrain inspection and maintenance assessment and further model optimization. The detailed modelling of the baseline drivetrain model provides a basis for benchmark studies and support for future research on multimegawatt offshore wind turbines.     

Comparison of the performance and stability of two torsional vibration dampers for variable‐speed wind turbines

Alleviation of excess fatigue loads due to vibrations in the drive‐train of wind turbines can be achieved through the use of torsional vibration dampers. Two torsional dampers based on different design approaches were designed and assessed: the first employs a conventional band‐pass filter technique, whereas the second involves an alternative model‐based approach. Frequency domain analyses were carried out on the system with the two dampers for the cases with and without model uncertainty. The system using the band‐pass filter‐based damper showed deterioration in stability and performance when subjected to uncertainty in the model and had to be re‐tuned to recover a good damping performance. Conversely, the system employing the model‐based damper maintained good stability and superior damping performance in the presence of model uncertainties. These attributes can ensure that the damper exhibits a good performance even if the wind turbine parameters vary during operation, such as when ice forms on the blades. Time domain simulations were carried out to verify the frequency domain analyses. © 2014 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Model of a synthetic wind speed time series generator

Wind energy has assumed a great relevance in the operation and planning of today's power systems due to the exponential increase of installations in the last 10 years. For this reason, many performed studies have looked at suitable representations of wind generation for power system analysis. One of the main elements to consider for this purpose is the model of the wind speed that is usually required as input. Wind speed measurements may represent a solution for this problem, but, for techniques such as sequential Monte Carlo simulation, they have to be long enough in order to describe a wide range of possible wind conditions. If these information are not available, synthetic wind speed time series may be a useful tool as well, but their generator must preserve statistical and stochastic features of the phenomenon. This paper deals with this issue: a generator for synthetic wind speed time series is described and some statistical issues (seasonal characteristics, autocorrelation functions, average values and distribution functions) are used for verification. The output of the model has been designed as input for sequential Monte Carlo simulation; however, it is expected that it can be used for other similar studies on wind generation. Copyright © 2007 John Wiley & Sons, Ltd.     

Cox–Ingersoll–Ross model for wind speed modeling and forecasting

We propose a dynamic model for the squared norm of the wind speed which is a Markov diffusion process. It presents several advantages. Since the transition probability densities are in closed form, it can be calibrated with the maximum likelihood method. It presents nice modeling features both in terms of marginal probability density function and temporal correlation. We have tested the model with real wind speed data set provided by the National Renewable Energy Laboratory. The model fits very well with the data. Besides, we obtained a very good performance in forecasting wind speed at short term. This is an interesting perspective for operational use in industry. Copyright © 2015 John Wiley & Sons, Ltd.     

风道式风力发电机迎风及调速方法

为降低风道式风力发电机的成本,提出了一种风力发电机迎风及调速方法。在风道装置始终正对风向的条件下,由于偏心机构和凸轮机构的共同作用,在风速低时,风轮正对着风向,在风速超限时,风轮相应侧偏,以限制风轮转速。基于空气动力学基本理论,推导出其结构参数的表达式,并叙述了各结构参数的选取原则。该方法可有效地起到大风限速的作用,提高风力发电机工作的稳定性。该调速机构结构简单、成本低,安装维护方便。