Large‐eddy simulations with extremum‐seeking control for individual wind turbine power optimization

Large‐eddy simulations of the flow past an array of three aligned turbines have been performed. The study is focused on below rated (Region 2) wind speeds. The turbines are controlled through the generator torque gain, as usually done in Region 2. Two operating strategies are considered: (i) preset individual optimum torque gain based on a model for the power coefficient (baseline case) and (ii) real‐time optimization of torque gain for maximizing each individual turbine power capture during operation. The real‐time optimization is carried out through a model‐free approach, namely, extremum‐seeking control. It is shown that ESC is capable of increasing the power production of the array by 6.5% relative to the baseline case. The extremum‐seeking control reduces the torque gain of the downstream turbines, thus increasing the angular speed of the blades. This results in improved aerodynamics near the tip of the blade that is the portion contributing mostly to the torque and power. In addition, an increase in angular speed leads to a larger entrainment in the wake, which also contributes to provide additional available power downstream. It is also shown that the tip speed ratio may not be a reliable performance indicator when the turbines are in waked conditions. This may be a concern when using optimal parameter settings, determined from isolated turbine models, in applications with waked turbines. Copyright © 2017 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.     

Disturbance observer‐based integral sliding mode control for wind energy conversion systems

Recently, wind power production has been under the focus in generating power and became one of the main sources of alternative energy. Generating of maximum power from wind energy conversion system (WECS) requires accurate estimation of aerodynamic torque and uncertainties presented in the system. The current paper proposed the generalized high‐order disturbance observer (GHODO) with integral sliding mode control (ISMC) for extraction of maximum power via variable speed wind turbine by accurate estimation of wind speed. The assumption in previous works that considers the aerodynamic torque as slow‐varying is not applicable for the real system. Therefore, the high‐order disturbance observers were designed for precise estimation of uncertainties with fast‐changing behavior. A robust control system was designed to control the speed of the rotor at the optimal speed ratio. The obtained simulation results have shown the better performance characteristics than conventional linear quadratic regulator (LQR) approach. The stability of the proposed algorithm was proven by Lyapunov stability anaysis. Simulations results were obtained in Matlab/Simulink environment.     

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.     

Uncertainty of power curve measurement with a two‐beam nacelle‐mounted lidar

Nacelle lidars are attractive for offshore measurements since they can provide measurements of the free wind speed in front of the turbine rotor without erecting a met mast, which significantly reduces the cost of the measurements. Nacelle‐mounted pulsed lidars with two lines of sight (LOS) have already been demonstrated to be suitable for use in power performance measurements. To be considered as a professional tool, however, power curve measurements performed using these instruments require traceable calibrated measurements and the quantification of the wind speed measurement uncertainty. Here we present and demonstrate a procedure fulfilling these needs. A nacelle lidar went through a comprehensive calibration procedure. This calibration took place in two stages. First with the lidar on the ground, the tilt and roll readings of the inclinometers in the nacelle lidar were calibrated. Then the lidar was installed on a 9m high platform in order to calibrate the wind speed measurement. The lidar's radial wind speed measurement along each LOS was compared with the wind speed measured by a calibrated cup anemometer, projected along the LOS direction. The various sources of uncertainty in the lidar wind speed measurement have been thoroughly determined: uncertainty of the reference anemometer, the horizontal and vertical positioning of the beam, the lack of homogeneity of the flow within the probe volume, lidar measurement mean deviation and standard uncertainty. The resulting uncertainty lies between 1 and 2% for the wind speed range between cut‐in and rated wind speed. Finally, the lidar was mounted on the nacelle of a wind turbine in order to perform a power curve measurement. The wind speed was simultaneously measured with a mast‐top mounted cup anemometer placed two rotor diameters upwind of the turbine. The wind speed uncertainty related to the lidar tilting was calculated based on the tilt angle uncertainty derived from the inclinometer calibration and the deviation of the measurement height from hub height. The resulting combined uncertainty in the power curve using the nacelle lidar was less than 10% larger on average than that obtained with the mast mounted cup anemometer. Copyright © 2015 John Wiley & Sons, Ltd.     

Detection of nacelle anemometer faults in a wind farm minimizing the uncertainty

The performance assessment of wind farms requires the acquisition of accurate power and wind speed data of each turbine. Nowadays, the nacelle anemometry is widely studied as an option for power performance verification. Therefore, systems to detect the nacelle anemometer faults in a wind farm in operation are necessary for maintenance purposes. In this paper, we propose a method to detect wind speed deviations of the nacelle anemometers by comparing them with the nearby anemometers. This comparison is made through an approach to estimate the wind speed in each nacelle. The approach is based on the discretization of wind speed data using the bin method. The key issue of this proposal is the estimation of the anemometer deviations considering the range of data with lower uncertainty. To this end, an average uncertainty model per bin and direction sector has been integrated into the method. The tests show that using wind speeds higher than 4.5 m s ^{? 1} gives the lowest uncertainty. Data from two wind farms have been used to test this method, and the obtained results have allowed the detection of problematic anemometers. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulating Feedback Linearization control of wind turbines using high‐order models

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

Calibration of a spinner anemometer for wind speed measurements

The power curve of a wind turbine can be measured, according to IEC 61400‐12‐2 with a nacelle‐mounted anemometer. Typically, a sonic anemometer or a cup anemometer and a wind vane are mounted on the back of the nacelle roof. Another option is to use a spinner anemometer. The measurement principle of the spinner anemometer is based on the flow distortion caused by the wind turbine spinner. The flow on the spinner surface is measured by means of three 1D sonic sensors mounted on the spinner and a conversion algorithm to convert the wind velocity components measured by the three sonic sensors to horizontal wind speed, yaw misalignment and flow inclination angle. The algorithm utilizes two calibration constants that are specific to the spinner shape, blade root design and to the mounting positions of the sonic sensors on the spinner. The present analysis describes methods to determine the calibration constant related to wind speed measurements. The first and preferred method is based on the definition of the calibration constant and uses wind speed measurements during the stopped condition of the wind turbine. Two alternative methods that did not require the turbine to be stopped were investigated: one used relatively high wind speed measurements during normal operation of the wind turbine, while the other one used a CFD simulation of the flow over the spinner. The method that entails stopping the turbine in good wind conditions showed the best results and is recommended. The evaluation of uncertainty was not included in the present analysis. Copyright © 2016 The Authors Wind Energy Published by 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.     

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.     

变速变桨风力发电机组的优化控制

提出了大型变速变桨风力发电机组在不同控制阶段的优化控制策略。在低风速时,采用自适应转矩控制方式,实现机组的变速运行,追踪最佳风能利用系数。在额定风速以上时,为了解决传统桨距控制方式系统超调量大的问题,提出了一种新型气动转矩观测器,并将气动转矩与发电机转矩偏差输入控制器。通过Bladed外部控制器模块编程并进行仿真,结果表明,所提出的控制策略能够更好地追踪最大功率点,并改善桨距控制效果,稳定功率输出。     

Fractional‐order sliding mode control for hybrid drive wind power generation system with disturbances in the grid

The proposal of hybrid drive grid‐connected wind turbine based on speed regulating differential mechanism (SRDM) has been made in this paper to generate constant‐frequency power without fully‐ or partially‐rated frequency converters so as well improve electric power quality. However, disturbances in the power grid including sudden load fluctuation and sub‐synchronous resonance (SSR) can lead to the pulsating torque to act on the shaft section between SG and exciter at the main generator collector, such that the speed regulating accuracy of SRDM is seriously affected. As a result, this paper synthesizes a new‐type fractional‐order sliding mode controller (FOSMC) with a load torque observer (LTO) for the high‐accuracy speed control of permanent magnet synchronous motor (PMSM) in SRDM. Taking advantage of ridge regression algorithm, related parameters including rotational inertia and viscous friction coefficient of speed regulating system are calculated accurately. Finally, comparative experiments are carried out under four cases of mean of 5, 10, 13, and 21 m/s wind speeds to verify the satisfactory performances of designed FOSMC with LTO. Comparative experimental results show that FOSMC with LTO can effectively eliminate undesirable chattering effect. Additionally, under operating conditions of changing wind speeds, SSR, and sudden load fluctuation in power grid, the output speed of SRDM that corresponds directly to the frequency output of SG can be steadily and accurately regulated by using proposed control scheme. SRDM equipped with designed controller enables the power frequency to meet the National Standard of PR China perfectly.     

Investigation of maximum wind power extraction using adaptive virtual lookup‐table approach

With the advance of power electronic technology, direct‐driven permanent magnet synchronous generators (PMSG) have increasingly drawn interests to wind turbine manufacturers. Unlike a fixed‐speed wind turbine, the maximum power extraction of a PMSG wind turbine is affected by (1) electrical characteristics of the generator, (2) aerodynamic characteristics of the turbine blades, and (3) maximum power extraction strategies. In an environment integrating all the three characteristics, it is found in this paper that the existing commercial lookup‐table maximum power extraction mechanism suitable to a DFIG wind turbine is not suitable to a PMSG wind turbine. Through the integrative study of all the three characteristics, this paper proposes a novel PMSG maximum power extraction design. The special features of the proposed strategy include (i) an adaptive virtual lookup‐table approach for PMSG maximum power extraction and (ii) an implementation of the peak power‐tracking scheme based on a novel direct‐current vector control configuration. The proposed maximum power extraction mechanism with a nested speed‐ and current‐loop control structure is built by using MatLab SimPowerSystems. Simulation studies demonstrate that the proposed PMSG peak power‐tracking strategy has superior performance in various aspects under both stable and gust wind conditions. Copyright © 2010 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.     

Power generation control of a hydrostatic wind turbine implemented by model‐free adaptive control scheme

The hydrostatic wind turbine (HWT) is a type of wind turbine that uses hydrostatic transmission (HST) drivetrain to replace the traditional gearbox drivetrain. Without the fragile and expensive gearbox and power converters, HWT can potentially reduce the maintenance costs owing to the gearbox and power converter failures in wind power system, especially in offshore cases. We design an MFAC torque controller to regulate the pump torque of the HWT and compared with an torque controller. Then we design an MFAC pitch controller to stabilise the rotor speed of HWT and compared with a gain‐scheduling proportional‐integral (PI) controller and a gain‐scheduling PI controller with antiwindup (PIAW). The results indicate that MFAC torque controller provides more effective tracking performance than the controller and that MFAC pitch controller shows better rotor speed stabilisation performance in comparison with the gain‐scheduling PI controller and PIAW.     

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.     

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 predictive control of a wind turbine using short‐term wind field predictions

As wind turbines become larger and hence more flexible, the design of advanced controllers to mitigate fatigue damage and optimise power capture is becoming increasingly important. The majority of the existing literature focuses on feedback controllers that use measurements from the turbine itself and possibly an estimate or measurement of the current local wind profile. This work investigates a predictive controller that can use short‐term predictions about the approaching wind field to improve performance by compensating for measurement and actuation delays. Simulations are carried out using the FAST aeroelastic design code modelling the NREL 5 MW reference turbine, and controllers are designed for both above rated and below rated wind conditions using model predictive control. Tests are conducted in various wind conditions and with different future wind information available. It is shown that in above rated wind conditions, significant fatigue load reductions are possible compared with a controller that knows only the current wind profile. However, this is very much dependent on the speed of the pitch actuator response and the wind conditions. In below rated wind conditions, the goals of power capture and fatigue load control were considered separately. It was found that power capture could only be improved using wind predictions if the wind speed changed rapidly during the simulation and that fatigue loads were not consistently reduced when wind predictions were available, indicating that wind predictions are of limited benefit in below rated wind conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Linear models‐based LPV modelling and control for wind turbines

The non‐linear behaviour of wind turbines demands control strategies that guarantee the robustness of the closed‐loop system. Linear parameter‐varying (LPV) controllers adapt their dynamics to the system operating points, and the robustness of the closed loop is guaranteed in the controller design process. An LPV collective pitch controller has been developed within this work to regulate the generator speed in the above rated power production control zone. The performance of this LPV controller has been compared with two baseline control strategies previously designed, on the basis of classical gain scheduling methods and linear time‐invariant robust H_∞ controllers. The synthesis of the LPV controller is based on the solution of a linear matrix inequalities system, proposed in a mixed‐sensitivity control scenario where not only weight functions are used but also an LPV model of the wind turbine is necessary. As a contribution, the LPV model used is derived from a family of linear models extracted from the linearization process of the wind turbine non‐linear model. The offshore wind turbine of 5 MW defined in the Upwind European project is the used reference non‐linear model, and it has been modelled using the GH Bladed 4.0 software package. The designed LPV controller has been validated in GH Bladed, and an exhaustive analysis has been carried out to calculate fatigue load reductions on wind turbine components, as well as to analyse the load mitigation in some extreme cases. Copyright © 2014 John Wiley & Sons, Ltd.