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.     

Markovian power curves for wind turbines

This paper shows a novel method to characterize wind turbine power performance directly from high‐frequency fluctuating measurements. In particular, we show how to evaluate the dynamic response of the wind turbine system on fluctuating wind speed in the range of seconds. The method is based on the stochastic differential equations known as the Langevin equations of diffusive Markov processes. Thus, the fluctuating wind turbine power output is decomposed into two functions: (i) the relaxation, which describes the deterministic dynamic response of the wind turbine to its desired operation state, and (ii) the stochastic force (noise), which is an intrinsic feature of the system of wind power conversion. As a main result, we show that independently of the turbulence intensity of the wind, the characteristic of the wind turbine power performance is properly reconstructed. This characteristic is given by their fixed points (steady states) from the deterministic dynamic relaxation conditioned for given wind speed values. The method to estimate these coefficients directly from the data is presented and applied to numerical model data, as well as to real‐world measured power output data. The method is universal and is not only more accurate than the current standard procedure of ensemble averaging (IEC‐61400‐12) but it also allows a faster and robust estimation of wind turbines' power curves. Copyright © 2007 John Wiley & Sons, Ltd.     

Regulation of WTG dynamic response to parameter variations of analytic wind stochasticity

Although variable‐speed operation can reduce the impact of transient wind gusts and subsequent component fatigue, this is still an unknown factor that must now be quantified. Reduction in drive‐train stresses caused by fatigue loads in high wind turbulence is fundamental to realizing both output power leveling and long service life for a wind turbine generator (WTG). This paper presents an evolutionary controller comprising a linear quadratic Gaussian (LQG) and neurocontroller acting in tandem to effect optimal performance under high turbulence intensities, for a variable‐speed, fixed‐pitch WTG. The control objectives are maximum energy conversion and reduction in mechanical stresses on the system components. The proposed paradigm utilizes generator torque in controlling the rotor speed in relation to the highly turbulent wind speed, thereby ensuring the extracted aerodynamic power is maintained at a constant value, while shaft moments are regulated. The performance of the proposed controller is compared with that of the LQG and it is found that the former is more efficient in maintaining rated power, minimizing shaft torque variations, and shows robustness to parameter variations. Copyright © 2007 John Wiley & Sons, Ltd.     

Evaluation of log‐of‐power extremum seeking control for wind turbines using large eddy simulations

The extremum seeking control (ESC) algorithm has been proposed to determine operating parameters that maximize power production below rated wind speeds (region II). This is usually done by measuring the turbine's power signal to determine optimal values for parameters of the control law or actuator settings. This paper shows that the standard ESC with power feedback is quite sensitive to variations in mean wind speed, with long convergence time at low wind speeds and aggressive transient response, possibly unstable, at high wind speeds. The paper also evaluates the performance, as measured by the dynamic and steady state response, of the ESC with feedback of the logarithm of the power signal (LP‐ESC). Large eddy simulations (LES) demonstrate that the LP‐ESC, calibrated at a given wind speed, exhibits consistent robust performance at all wind speeds in a typical region II. The LP‐ESC is able to achieve the optimal set‐point within a prescribed settling time, despite variations in the mean wind speed, turbulence, and shear. The LES have been conducted using realistic wind input profiles with shear and turbulence. The ESC and LP‐ESC are implemented in the LES without assuming the availability of analytical gradients.     

Modelling the aerodynamics of vertical‐axis wind turbines in unsteady wind conditions

Most numerical and experimental studies of the performance of vertical‐axis wind turbines have been conducted with the rotors in steady, and thus somewhat artificial, wind conditions—with the result that turbine aerodynamics, under varying wind conditions, are still poorly understood. The vorticity transport model has been used to investigate the aerodynamic performance and wake dynamics, both in steady and unsteady wind conditions, of three different vertical‐axis wind turbines: one with a straight‐bladed configuration, another with a curved‐bladed configuration and another with a helically twisted configuration. The turbines with non‐twisted blades are shown to be somewhat less efficient than the turbine with helically twisted blades when the rotors are operated at constant rotational speed in unsteady wind conditions. In steady wind conditions, the power coefficients that are produced by both the straight‐bladed and curved‐bladed turbines vary considerably within one rotor revolution because of the continuously varying angle of attack on the blades and, thus, the inherent unsteadiness in the blade aerodynamic loading. These variations are much larger, and thus far more significant, than those that are induced by the unsteadiness in the wind conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd.     

Sensitivity of southern California wind energy to turbine characteristics

Using output from a high‐resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut‐in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut‐out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd.     

Model predictive control for wind power gradients

We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We use the turbine inertia as an additional energy storage device, by varying its speed over time, and coordinate the flows of energy to achieve the goal. The control variables are turbine pitch, generator torque and charge/discharge rates for the storage device, each of which can be varied over given ranges. The system dynamics are quite non‐linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can transform the problem to one with linear dynamics and convex constraints. Thus, the problem can be globally solved, using robust, fast solvers tailored for embedded control applications. We implement the optimal control problem in a receding horizon manner and provide extensive closed‐loop tests with real wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production. Copyright © 2014 John Wiley & Sons, Ltd.     

Generating wind time series as a hybrid of measured and simulated data

Certain applications, such as analysing the effect of a wind farm on grid frequency regulation, require several years of wind power data measured at intervals of a few seconds. We have developed a method to generate days to years of non‐stationary wind speed time series sampled at high rates by combining measured and simulated data. Measured wind speed data, typically 10–15 min averages, capture the non‐stationary characteristics of wind speed variation: diurnal variations, the passing of weather fronts, and seasonal variations. Simulated wind speed data, generated from spectral models, add realistic turbulence between the empirical data. The wind speed time series generated with this method agree very well with measured time series, both qualitatively and quantitatively. The power output of a wind turbine simulated with wind data generated by this method demonstrates energy production, ramp rates and reserve requirements that closely match the power output of a turbine simulated turbine with measured wind data. Copyright © 2011 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.     

Transient and dynamic control of a variable speed wind turbine with synchronous generator

In this article, a controller for dynamic and transient control of a variable speed wind turbine with a full‐scale converter‐connected high‐speed synchronous generator is presented. First, the phenomenon of drive train oscillations in wind turbines with full‐scale converter‐connected generators is discussed. Based on this discussion, a controller is presented that dampens these oscillations without impacting on the power that the wind turbine injects into the grid. Since wind turbines are increasingly demanded to take over power system stabilizing and control tasks, the presented wind turbine design is further enhanced to support the grid in transient grid events. A controller is designed that allows the wind turbine to ride through transient grid faults. Since such faults often cause power system oscillations, another controller is added that enables the turbine to participate in the damping of such oscillations. It is concluded that the controllers presented keep the wind turbine stable under any operating conditions, and that they are capable of adding substantial damping to the power system. Copyright © 2007 John Wiley & Sons, Ltd.     

Adjustment of wind farm power output through flexible turbine operation using wind farm control

When the installed capacity of wind power becomes high, the power generated by wind farms can no longer simply be that dictated by the wind speed. With sufficiently high penetration, it will be necessary for wind farms to provide assistance with supply‐demand matching. The work presented here introduces a wind farm controller that regulates the power generated by the wind farm to match the grid requirements by causing the power generated by each turbine to be adjusted. Further, benefits include fast response to reach the wind farm power demanded, flexibility, little fluctuation in the wind farm power output and provision of synthetic inertia. Copyright © 2015 John Wiley & Sons, Ltd.     

基于Matlab/Simulink的风力机性能仿真研究

随着风力发电技术的发展,变速风力发电技术成为了风力发电发展的趋势。风力机作为变速风力发电机组的重要部分,其性能影响到风力发电机组的整体性能。根据变速风力机的静态性能特点,采用Matlab／Simulink软件对其进行建模,并给变速风力发电机组风力机输入模拟变速风速进行仿真研究,给出了风力机的静态性能数据和仿真波形。结果表明：通过调节影响风力机性能的各因素,保持发电机的转速与主导风速之间特定的最优比例系数,使得风力机保持在最佳叶尖速比下运行,跟随变速风速可实现最大风能捕获;对变速风力机的静态性能研究建模方法是正确可行的。     

Simulation model of wind turbine 3p torque oscillations due to wind shear and tower shadow

To determine the control structures and possible power quality issues, the dynamic torque generated by the blades of a wind turbine must be represented. This paper presents an analytical formulation of the generated aerodynamic torque of a three-bladed wind turbine including the effects of wind shear and tower shadow. The comprehensive model includes turbine-specific parameters such as radius, height, and tower dimensions, as well as the site-specific parameter, the wind shear exponent. The model proves the existence of a 3p pulsation due to wind shear and explains why it cannot be easily identified in field measurements. The proportionality constant between the torque and the wind speed is determined allowing direct aerodynamic torque calculation from an equivalent wind speed. It is shown that the tower shadow effect is more dominant than the wind shear effect in determining the dynamic torque, although there is a small dc reduction in the torque oscillation due to wind shear. The model is suitable for real-time wind turbine simulation or other time domain simulation of wind turbines in power systems.     

A flywheel in a wind turbine rotor for inertia control

In this paper, a flywheel energy storage that is an integral part of a wind turbine rotor is proposed. The rotor blades of a wind turbine are equipped with internal weights, which increase the inertia of the rotor. The inertia of this flywheel can be controlled by varying the position of the weights, i.e. by positioning them closer to the center of rotation (closer to the hub) or closer to the tip of the blades. The simulation model used in this study is introduced briefly. The equation system of the flywheel is set up. Finally, simulations of different scenarios show the performance of this controllable flywheel. The conclusion is that the proposed system can mitigate transients in the power output of wind turbines. Hence, it can support the frequency control in a power system by contributing to the power system inertia. © 2014 The Authors. Wind Energy published by 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.     

Quantification of power losses due to wind turbine wake interactions through SCADA,meteorological and wind LiDAR data

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met‐tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut‐in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability‐driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60‐80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.     

Platform stabilization and load reduction of floating offshore wind turbines with tension‐leg platform using dynamic vibration absorbers

Floating offshore wind turbines (FOWT) are subject to significant increases in structural loads due to the platform motion under turbulent wind and wave. The under‐actuation challenge in FOWT control demands for development of extra actuators for platform stabilization. For FOWT with tension‐leg platform (TLP), this paper presents a comprehensive study on design and control simulation for realizing active mooring line control via the deployment of vertically operated dynamic vibration absorbers (DVAs) at the spokes of TLP structure. The DVA is designed based on the suppression of the primary modes of platform pitch and roll motion. In addition to the enhancement of FAST‐based simulation module, an 11 degrees‐of‐freedom (DOFs) control‐oriented model is derived for the TLP‐FOWT‐DVA system. Based on the control‐oriented model, a linear quadratic regulator (LQR) controller is designed. Simulations are performed for 9 m/s and 18 m/s turbulent winds with different wind and wave directions. The wind turbine performance, platform motions, and structural fatigue loads are evaluated. The results show that the platform motion and tower loads in the lateral direction are significantly reduced, while the tower load in the fore‐aft direction can be moderately reduced. Also, significant reduction in the mooring line tension loads is observed. For achieving the performance in platform motion stabilization and load reduction, the average power consumption of the DVA actuators is less than 0.27% of the wind turbine power generated during the simulated periods. The figures of merits promise significant potential for the feasibility of DVA based control for TLP‐FOWT.     

Met‐ocean conditions influence on floating offshore wind farms power production

Met‐ocean conditions may affect the performance of a floating wind turbine, since a harsh climate could lead the system to exceed its operating thresholds and thus to force the machine shutdown. In this paper, it is a proposed methodology to evaluate the effect of met‐ocean conditions on the long‐term dynamic behaviour, and energy production, of a floating wind farm. For a sample of 500 MW farm located off the coast of Aberdeen (Scotland), 20 years of met‐ocean data are generated by means of meteorological reanalysis techniques. A subset of 1000 hourly conditions is selected, by means of a maximum dissimilarity algorithm, and input to a dynamic floating wind turbine model. Numerical results are then interpolated for the whole set of met‐ocean data, using radial basis functions. This approach allows to dramatically reduce the global computation time. Tower inclination and hub acceleration are chosen as relevant operating parameters: the former mainly depends on mean wind speed and direction, being largest at rated wind speed. The latter is also affected by significant wave height, and reaches its highest values when wind and waves are aligned. For each simulation, any machine exceeding the selected safety threshold is considered to be shut down. Assuming continuous operation, the average lifespan capacity factor of the farm is 50.2%; more restrictive tolerances result in a non‐linear reduction of the energy production. This approach may help both at the design and the operational stage, in determining the best trade‐off between energy production and safe operation. Copyright © 2015 John Wiley & Sons, Ltd.     

雾霾之后的反思

新年过后的第二个周末,浓重的雾霾已在全国多个城市肆虐,这让人们的心情变得糟糕。数据显示,截至1月13日零时,全国有33个城市的部分监测点PM2.5浓度超过300微克/立方米,个别城市出现PM2.5"爆表",比如北京的PM2.5浓度最高达到950微克/立方米。环保专家称,如此严重的空气质量污染,可以说已近人类所能承受的极限。于是,人们看到了政府有关方面发布的紧急预案,比如通知市民减少户外活动,要求学校停止户外体育锻炼,这体现了政府的责任意识。但我们是满足于制定完美的灾情应对预案,还是谋求从根本上消除灾难?