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.     

基于威布尔分布的风速概率分布参数估计方法

准确地描述风速特性,直接影响风电场风能资源评估的结果.文章介绍了基于威布尔分布的平均风速及最大风速估计法、矩估计法、最小二乘估计法和极大似然估计法等4种风速概率分布参数估计的方法.通过对乌兰察布地区测风塔实际数据的分析,比较了4种方法的参数估计结果,得到以下结论:在风能资源较丰富地区,平均风速及最大风速估计法的风速拟合效果波动较大,对平均风能密度估计误差较大;矩估计法、最小二乘估计法和极大似然估计法拟合效果良好.     

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.     

Assessing the suitability of wind speed probabilty distribution functions based on wind power density

Three functions have so far predominantly been used for fitting the measured wind speed probability distribution in a given location over a certain period of time, typically monthly or yearly. In the literature, it is common to fit these functions to compare which one fits the measured distribution best in a particular location. During this comparison process, parameters on which the suitability of the fit is judged are required. The parameters that are mostly used are the mean wind speed or the total wind energy output (primary parameters). It is, however, shown in the present study that one cannot judge the suitability of the functions based on the primary parameters alone. Additional parameters (secondary parameters) that complete the primary parameters are required to have a complete assessment of the fit, such as the discrepancy between the measured and fitted distributions, both for the wind speed and wind energy (that is the standard deviation of wind speed and wind energy distributions). Therefore, the secondary statistical parameters have to be known as well as the primary ones to make a judgement about the suitability of the distribution functions analysed. The primary and secondary parameters are calculated from the 12-month of measured hourly wind speed data and detailed analyses of wind speed distributions are undertaken in the present article.     

Switching EKF technique for rotor and stator resistance estimation in speed sensorless control of IMs

High performance speed sensorless control of induction motors (IMs) calls for estimation and control schemes that offer solutions to parameter uncertainties as well as to difficulties involved with accurate flux/velocity estimation at very low and zero speed. In this study, a new EKF based estimation algorithm is proposed for the solution of both problems and is applied in combination with speed sensorless direct vector control (DVC). The technique is based on the consecutive execution of two EKF algorithms, by switching from one algorithm to another at every n sampling periods. The number of sampling periods, n, is determined based on the desired system performance. The switching EKF approach, thus applied, provides an accurate estimation of an increased number of parameters than would be possible with a single EKF algorithm. The simultaneous and accurate estimation of rotor, and stator, R_s resistances, both in the transient and steady state, is an important challenge in speed sensorless IM control and reported studies achieving satisfactory results are few, if any. With the proposed technique in this study, the sensorless estimation of and R_s is achieved in transient and steady state and in both high and low speed operation while also estimating the unknown load torque, velocity, flux and current components. The performance demonstrated by the simulation results at zero speed, as well as at low and high speed operation is very promising when compared with individual EKF algorithms performing either or R_s estimation or with the few other approaches taken in past studies, which require either signal injection and/or a change of algorithms based on the speed range. The results also motivate utilization of the technique for multiple parameter estimation in a variety of control methods.     

Validation and modification of the Blade Element Momentum theory based on comparisons with actuator disc simulations

A comprehensive investigation of the Blade Element Momentum (BEM) model using detailed numerical simulations with an axis symmetric actuator disc (AD) model has been carried out. The present implementation of the BEM model is in a version where exactly the same input in the form of non‐dimensional axial and tangential load coefficients can be used for the BEM model as for the numerical AD model. At a rotor disc loading corresponding to maximum power coefficient, we found close correlation between the AD and BEM model as concerns the integral value of the power coefficient. However, locally along the blade radius, we found considerable deviations with the general tendency, that the BEM model underestimates the power coefficient on the inboard part of the rotor and overestimates the coefficient on the outboard part. A closer investigation of the deviations showed that underestimation of the power coefficient on the inboard part could be ascribed to the pressure variation in the rotating wake not taken into account in the BEM model. We further found that the overestimation of the power coefficient on the outboard part of the rotor is due to the expansion of the flow causing a non‐uniform induction although the loading is uniform. Based on the findings we derived two small engineering sub‐models to be included in the BEM model to account for the physical mechanisms causing the deviations. Finally, the influence of using the corrected BEM model, BEM_cor on two rotor designs is presented. Copyright © 2009 John Wiley & Sons, Ltd.     

Smart dynamic rotor control using active flaps on a small‐scale wind turbine: aeroelastic modeling and comparison with wind tunnel measurements

In this paper, the proof of concept of a smart rotor is illustrated by aeroelastic simulations on a small‐scale rotor and comparison with wind tunnel experiments. The application of advanced feedback controllers using actively deformed flaps in the wind tunnel measurements is shown to alleviate dynamic loads leading to considerable fatigue load reduction. The numerical method for aeroelastically simulating such an experiment is described, together with the process of verifying the methods for accurate prediction of the load reduction potential of such concepts. The small‐scale rotor is simulated using the aeroelastic tool, load predictions are compared with the wind tunnel measurements, and similar control concepts are compared and evaluated in the numerical environment. Conclusions regarding evaluation of the performance of smart rotor concepts for wind turbines are drawn from this threefold research investigation (simulation, experiment and comparison). Copyright © 2012 John Wiley & Sons, Ltd.     

Frequency support capability of variable speed wind turbine based on electromagnetic coupler

In the variable speed wind turbine based on electromagnetic coupler (WT-EMC), a synchronous generator is directly coupled with grid. So like conventional power plants WT-EMC is able to support grid frequency inherently. But due to the reduced inertia of synchronous generator, its frequency support capability has to be enhanced. In this paper, the frequency support capability of WT-EMC is studied at three typical wind conditions and with two control strategies—droop control and inertial control to enhance its frequency support capability. The synchronous generator speed, more stable than the grid frequency which is the input signal for Type 3 and Type 4 wind turbine frequency support controller, is used for the calculation of WT-EMC supplementary torque command. The integrated simulation environment based on the aeroelastic code HAWC2 and software Matlab/Simulink is used to build a 2 MW WT-EMC model and study the frequency support capability of a wind farm consisting of WT-EMC.     

Estimating wind speed probability distribution based on measured data at Burla in Odisha,India

In this work, the wind speed probability distribution is estimated for Burla location in the state of Odisha in the east coast of India. For this purpose, 10 min averaged wind speed data collected over one year period at Burla is utilized. Specifically, Weibull, Gamma, Lognormal, Inverse Gaussian distributions; mixture distributions such as Weibull-Weibull, Gamma-Weibull, Normal-Weibull, and Normal-Normal are examined to evaluate their suitability to represent the measured wind speed. The non-parametric kernel density method is also used to represent the measured wind speed wherever the parametric distributions are not suitable. Chi-square test and Kolmogorov-Smirnov goodness-of-fit tests are used to evaluate the suitability of each of the above distributions.     

基于BP神经网络与遗传算法风电场超短期风速预测优化研究

风速预测对于风力发电并网调度至关重要。基于BP神经网络建立了风速预测模型,并从BP算法及遗传算法自身特点出发,针对BP网络结构确定困难、收敛速度慢等问题,提出创建多种群遗传算法,实现对BP神经网络的结构和权值初始值的同步优化。通过具体算例表明,经优化后的BP算法的收敛步数和计算时间明显减少,预测精度更高,网络整体性能有了显著提高。     

A novel online training neural network-based algorithm for wind speed estimation and adaptive control of PMSG wind turbine system for maximum power extraction

In this paper, an adaptive control scheme for maximum power point tracking of stand-alone PMSG wind turbine systems (WTS) is presented. A novel procedure to estimate the wind speed is derived. To achieve this, a neural network identifier (NNI) is designed in order to approximate the mechanical torque of the WTS. With this information, the wind speed is calculated based on the optimal mechanical torque point. The NNI approximates in real-time the mechanical torque signal and it does not need off-line training to get its optimal parameter values. In this way, it can really approximates any mechanical torque value with good accuracy. In order to regulate the rotor speed to the optimal speed value, a block-backstepping controller is derived. Uniform asymptotic stability of the tracking error origin is proved using Lyapunov arguments. Numerical simulations and comparisons with a standard passivity based controller are made in order to show the good performance of the proposed adaptive scheme.     

基于小波变换与Elman神经网络的短期风速组合预测

风速的准确预测对风电场发电系统的经济和安全运行有着重要的作用。为了克服风速随机性强的缺点,提高短期风速预测的精度,提出了一种将小波变换与Elman神经网络相结合的短期风速组合预测模型。该模型由小波预处理模块和神经网络预测模块组成。首先利用小波预处理模块将风速序列作多尺度分解,重构得到不同频段的子序列,然后利用Elman神经网络模块分别对其训练和预测。实际风速预测结果表明,与单一的Elman和ARMA法相比,该组合预测模型的预测精度有较大的改善,可以用于风电场短期风速的预测。     

Observability of the ambient conditions in model‐based estimation for wind farm control: A focus on static models

Wind farm control (WFC) algorithms rely on an estimate of the ambient wind speed, wind direction, and turbulence intensity in the determination of the optimal control setpoints. However, the measurements available in a commercial wind farm do not always carry sufficient information to estimate these atmospheric quantities. In this paper, a novel measure (“observability”) is introduced that quantifies how well the ambient conditions can be estimated with the measurements at hand through a model inversion approach. The usefulness of this measure is shown through several case studies. While the turbine power signals and the inter‐turbine wake interactions provide information on the wind direction, the case studies presented in this article show that there is a strong need for wind direction measurements for WFC to sufficiently cover observability for any ambient condition. Further, generally, more wake interaction leads to a higher observability. Also, the mathematical framework presented in this article supports the straightforward notion that turbine power measurements provide no additional information compared with local wind speed measurements, implying that power measurements are superfluous. Irregular farm layouts result in a higher observability due to the increase in unique wake interaction. The findings in this paper may be used in WFC to predict which ambient quantities can (theoretically) be estimated. The authors envision that this will assist in the estimation of the ambient conditions in WFC algorithms and can lead to an improvement in the performance of WFC algorithms over the complete envelope of wind farm operation.     

Load mitigation and power tracking capability for wind turbines using linear matrix inequality‐based control design

This article deals with nonlinear model‐based control design for wind turbines. By systematically integrating several mechanical degrees of freedom in the control design model, the load mitigation potential from the proposed multivariable control framework is demonstrated. The application of the linear matrix inequality (LMI)‐based control design is discussed in detail. Apart from the commonly considered power production mode, an extended operating range to provide stabilization of the electrical grid through power tracking is considered. This control functionality allows for an evaluation of the resulting fatigue and ultimate loads for power tracking at different dynamic requirements. The results indicate that under the impact of a dedicated control scheme, this functionality is feasible with respect to the occurring loads and operational behavior of the wind turbine.     

Two-cell theory to measure membrane resistance based on proton flow: Theory development and experimental validation

A two-cell theory is developed to measure proton exchange membrane (PEM) resistance to proton flow during conduction through a PEM fuel cell. The theoretical framework developed herein is based upon fundamental thermodynamic principles and engineering laws. We made appropriate corrections to develop the theoretical model previously proposed by Babu and Nair (B.V. Babu, N. Nair, J. Energy Edu. Sci. Technol. 13 (2004) 13–20) for measuring membrane resistance to the flow of protons, which is the only ion that travels from one electrode to the other through the membrane. A simple experimental set-up and procedure are also developed to validate the theoretical model predictions. A widely used commercial membrane (Nafion^®) and several in-house membranes are examined to compare relative resistance among membranes. According to the theory, resistance of the proton exchange membrane is directly proportional to the time taken for a specific amount of protons to pass through the membrane. A second order differential equation describes the entire process. The results show that theoretical predictions are in excellent agreement with experimental observations. It is our speculation that the investigation results will open up a route to develop a simple device to measure resistance during membrane manufacturing since electrolyte resistance is one of the key performance drivers for the advancement of fuel cell technology.     

Lift-off of jet diffusion flame in sub-atmospheric pressures: An experimental investigation and interpretation based on laminar flame speed

This paper reveals lift-off behavior of jet diffusion flames in sub-atmospheric pressures less than 100 kPa, in view of that the current knowledge on this topic is limited for normal pressure conditions. Physically, the variation of ambient pressure may have significant influence on the lift-off behavior of jet diffusion flames due to the change of some critical parameters such as laminar flame speed. In this work, experiments are conducted in a large pressure-controllable chamber of 3 m (width) × 2 m (length) × 2 m (height) at different sub-atmospheric pressures of 60 kPa, 70 kPa, 80 kPa, 90 kPa as well as at normal pressure of 100 kPa. Axisymmetric turbulent jet diffusion flames are produced by nozzles with diameters of 4 mm, 5 mm and 6 mm using propane as fuel. It is revealed that the lift-off height increases as the pressure decreases and being much higher than that in normal pressure condition. The laminar flame speed with its dependency on pressure is introduced to interpret such behavior based on classic Kalghatgi model. It is found theoretically that the lift-off height has a power law dependency on pressure by P¹⁻ⁿ, where n is overall reaction order of the fuel which is usually larger than 1 indicating a negative power law function with pressure (for example p^−0.75 for propane as n = 1.75) as well verified by the experimental correlation. Finally, a global model is proposed by including such pressure dependency function into the Kalghatgi model, which is shown to well collapse the experimental results of lift-off heights of different sub-atmospheric pressures.     

De‐trending of wind speed variance based on first‐order and second‐order statistical moments only

The lack of efficient methods for de‐trending of wind speed resource data may lead to erroneous wind turbine fatigue and ultimate load predictions. The present paper presents two models, which quantify the effect of an assumed linear trend on wind speed standard deviations as based on available statistical data only. The first model is a pure time series analysis approach, which quantifies the effect of non‐stationary characteristics of ensemble mean wind speeds on the estimated wind speed standard deviations as based on mean wind speed statistics only. This model is applicable to statistics of arbitrary types of time series. The second model uses the full set of information and includes thus additionally observed wind speed standard deviations to estimate the effect of ensemble mean non‐stationarities on wind speed standard deviations. This model takes advantage of a simple physical relationship between first‐order and second‐order statistical moments of wind speeds in the atmospheric boundary layer and is therefore dedicated to wind speed time series but is not applicable to time series in general. The capabilities of the proposed models are discussed by comparing model predictions with conventionally de‐trended characteristics of measured wind speeds using data where high sampled time series are available, and a traditional de‐trending procedure therefore can be applied. This analysis shows that the second model performs significantly better than the first model, and thus in turn that the model constraint, introduced by the physical link between the first and second statistical moments, proves very efficient in the present context. © 2013 The Authors. Wind Energy Published by John Wiley & Sons Ltd.