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.     

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.     

Modelling and control of variable‐speed multi‐pole permanent magnet synchronous generator wind turbine

Emphasis of this article is on variable‐speed pitch‐controlled wind turbines with multi‐pole permanent magnet synchronous generator (PMSG) and on their extremely soft drive‐train shafts. A model and a control strategy for a full back‐to‐back converter wind turbine with multi‐pole PMSG are described. The model comprises submodels of the aerodynamic rotor, the drive‐train by a two‐mass model, the permanent magnet generator and the full‐scale converter system. The control strategy, which embraces both the wind turbine control itself and the control of the full‐scale converter, has tasks to control independently the active and reactive powers, to assist the power system and to ensure a stable normal operation of the wind turbine itself. A multi‐pole PMSG connected to the grid through a full‐scale converter has no inherent damping, and therefore, such configuration can become practically unstable, if no damping by means of external measures is applied. In this work, the frequency converter is designed to damp actively the drive‐train oscillations, thus ensuring stable operation. The dynamic performance of the presented model and control strategy is assessed and emphasized in normal operation conditions by means of simulations in the power system simulation tool DIgSILENT. Copyright © 2008 John Wiley & Sons, Ltd.     

A robust power control strategy to enhance LVRT capability of grid‐connected DFIG‐based wind energy systems

This paper presents a new robust and effective control strategy to mitigate symmetrical voltage dips in a grid‐connected doubly fed induction generator (DFIG) wind energy conversion system without any additional hardware in the system. The aim is to control the power transmitted to the grid so as to keep the electrical and mechanical quantities above their threshold protection values during a voltage dip transient. To achieve this, the references of the powers are readjusted to adapt the wind energy conversion system to the fault conditions. Robust control strategies, combining the merits of sliding mode theory and fuzzy logic, are then proposed in this paper. These controllers are derived from the dynamic model of the DFIG considering the variations in the stator flux generated by the voltage drop. This approach is found to yield better performance than other control design methods which assume the flux in the stator to remain constant in amplitude. This control scheme is compliant with the fault‐ride‐through grid codes which require the wind turbine generator to remain connected during voltage dips. A series of simulation scenarios are carried out on a 3‐MW wind turbine system to demonstrate the effectiveness of the proposed control schemes under voltage dips and parameter uncertainty conditions.     

Control of variable‐speed wind turbines by LPV gain scheduling

This article considers gain‐scheduling control of variable‐speed wind energy conversion systems (WECS) in the context of linear parameter‐varying (LPV) systems. The typical problems of the classic gain‐scheduling techniques, such as stability guarantees, undesirable transient responses in the controller commutations and arduous design procedures, can be avoided with this new formulation. A model of a variable‐speed WECS expressed in LPV form and an optimal LPV gain‐scheduling control strategy are presented. Copyright © 2004 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.     

New design of robust PID controller based on meta‐heuristic algorithms for wind energy conversion system

This paper proposes a new robust control method for a wind energy conversion system. The suggested method can damp the deviations in the generator speed because of the penetration of wind speed and load demand fluctuations in the electrical grid. Furthermore, it can overcome the uncertainties of the plant parameters because of load demand fluctuations and the errors of the implementation. The new method has been built based on new simple frequency‐domain conditions and the whale optimization algorithm (WOA). This method is utilized to design a robust proportional‐integral‐derivative (PID) controller based on the WOA in order to enhance the damping characteristics of the wind energy conversion system. Simulation results confirm the superiority and robustness of the proposed technique against the wind speed fluctuations and the plant parameters uncertainties compared with other meta‐heuristic algorithms.     

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.     

SSCI mitigation of grid‐connected DFIG wind turbines with fractional‐order sliding mode controller

To mitigate subsynchronous control interaction (SSCI) in doubly fed induction generator (DFIG)‐based wind farm, this paper proposes a robust controller for rotor‐side converter (RSC) using fractional‐order sliding mode controller (FOSMC). The proposed FOSMC can improve robustness and convergence properties of the controlled system, thus achieving SSCI damping under various operating conditions. Impedance‐based analysis and time‐domain simulation are performed to check the capability of the designed FOSMC as compared with conventional sliding mode control (SMC) and subsynchronous damping control (SSDC). Simulation results demonstrate that FOSMC can mitigate SSCI within shorter time and effectively reduce the fluctuation range of system transient responses under various operating conditions of wind speeds and compensation levels. Moreover, FOSMC also improves system robustness against parameter uncertainties and external disturbances, which is important for safe operation of realistic wind farms.     

Load reduction on a clipper liberty wind turbine with linear parameter‐varying individual blade pitch control

The increasing size of modern wind turbines also increases the structural loads caused by effects such as turbulence or asymmetries in the inflowing wind field. Consequently, the use of advanced control algorithms for active load reduction has become a relevant part of current wind turbine control systems. In this paper, an individual blade pitch control law is designed using multivariable linear parameter‐varying control techniques. It reduces the structural loads both on the rotating and non‐rotating parts of the turbine. Classical individual blade pitch control strategies rely on single‐control loops with low bandwidth. The proposed approach makes it possible to use a higher bandwidth since it accounts for coupling at higher frequencies. A controller is designed for the utility‐scale 2.5 MW Liberty research turbine operated by the University of Minnesota. Stability and performance are verified using the high‐fidelity nonlinear simulation and baseline controllers that were directly obtained from the manufacturer. Copyright © 2017 John Wiley & Sons, Ltd.     

Identification in closed‐loop operation of models for collective pitch robust controller design

To achieve load reduction and power optimization, wind turbine controllers design requires the availability of reliable control‐oriented linear models. These are needed for model‐based controller design. Model identification of wind turbine while operating in closed loop is an appropriate solution that has recently shown its capabilities when linear time‐invariant controllers and complicated control structures are present. However, the collective pitch control loop, one of the most important wind turbine loops, uses non‐linear controllers. Typically, this non‐linear controller is a combination of a linear controller and a gain scheduling. This paper presents a new algorithm for identification in closed‐loop operation that allows the use of this kind of non‐linear controllers. The algorithm is applied for identification the collective pitch demand to generator speed of a wind turbine at various operating points. The obtained models are presented and discussed from a control point of view. The validity of these models is illustrated by their use for the design of a linear fix robust controller. The performance based on simulation data of this linear controller is similar to that obtained with simulations based on a linear controller with gain scheduling, but its design and implementation is much simpler. Copyright © 2012 John Wiley & Sons, Ltd.     

IPC-based robust disturbance accommodating control for load mitigation and speed regulation of wind turbines

Over the past few decades, global demand for renewable energy has been rising steadily. To meet this demand, there has been an exponential growth in size of wind turbines (WTs) to capture more energy from wind. Consequent increase in weight and flexibility of WT components has led to increased structural loading, affecting reliability of these wind energy conversion systems. Spatio-temporal variation of rotor effective wind field acts as a disturbance to a WT system, hence, necessitating controllers that can cancel this disturbance. Additionally, assumptions made in extracting linear models for controller design lead to modeling errors resulting from changing operating conditions. Previous attempts have proposed robust controllers incorporating wind disturbance models. However, these controllers have been evaluated on smaller WTs, which experience lower structural loading than larger ones. Additionally, a majority these controllers are based on collective pitch control (CPC), hence do not address loading in the blades. To address these challenges, this contribution proposes an independent pitch-based robust disturbance accommodating controller (IPC-RDAC) for reducing structural loads and regulating generator speed in utility-scale WTs. The proposed controller is designed using $$-synthesis approach and is evaluated on the 5 MW National Renewable Energy Laboratory (NREL) reference WT. Its performance is evaluated against a gain-scheduled proportional integral (GSPI)-based reference open-source controller (ROSCO) and a CPC-based RDAC (CPC-RDAC) controller, developed previously by the authors. Simulation results for various wind conditions show that the proposed controller offers improved performance in blade and tower load mitigation, as well a generator speed regulation.     

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.     

Time‐adaptive wind turbine model for an LES framework

Most large‐eddy simulation studies related to wind energy have been carried out either by using a fixed pressure gradient to ensure that mean wind direction is perpendicular to the wind turbine rotor disk or by forcing the flow with a geostrophic wind and timely readjusting the turbines' orientation. This has not allowed for the study of wind farm characteristics with a time‐varying wind vector. In this paper, a new time‐adaptive wind turbine model for the large‐eddy simulation framework is introduced. The new algorithm enables the wind turbines to dynamically realign with the incoming wind vector and self‐adjust the yaw orientation with the incoming wind vector similar to real wind turbines. The performance of the new model is tested first with a neutrally stratified atmospheric flow forced with a time‐varying geostrophic wind vector. A posteriori, the new model is used to further explore the interaction between a synthetic time‐changing thermal atmospheric boundary layer and an embedded wind farm. Results show that there is significant potential power to be harvested during the unstable time periods at the cost of designing wind turbines capable of adapting to the enhanced variance of these periods. Stable periods provide less power but are more constant over time with an enhanced lateral shear induced by an increased change in wind direction with height. Copyright © 2015 John Wiley & Sons, Ltd.     

Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization

The problem of designing a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed. The objective is to operate the wind turbines in order to have maximum wind power extraction while also the mechanical loads are reduced. Two control strategies were proposed seeking a better performance. The first strategy uses a tracking controller that ensures the optimal angular velocity for the rotor. The second strategy uses a Maximum Power Point Tracking (MPPT) algorithm while a non-homogeneous quasi-continuous high-order sliding mode controller is applied to ensure the power tracking. Two algorithms were developed to solve the tracking control problem for the first strategy. The first one is a sliding mode output feedback torque controller combined with a wind speed estimator. The second algorithm is a quasi-continuous high-order sliding mode controller to ensure the speed tracking. The proposed controllers are compared with existing control strategies and their performance is validated using a FAST model based on the Controls Advanced Research Turbine (CART). The controllers show a good performance in terms of energy extraction and load reduction.     

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.     

Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind

For region‐2 operation of wind turbines in practice, the optimal torque gain can deviate from the nominal value because of the variations in turbine and wind conditions. The extremum‐seeking control (ESC) has shown its potential as a model‐free region‐2 control solution in some recent work; however, the ESC with rotor power feedback suffers from undesirable convergence under fluctuating wind. In this paper, we propose to use an estimated power coefficient as the objective function for the torque‐gain ESC, where the hub‐height free‐stream wind speed (FSWS) is estimated with the nacelle anemometer measurement on the basis of the so‐called nacelle transfer function (NTF) between the nacelle anemometer and met‐tower measurement. A sensitivity analysis is performed to quantify the impact of the wind speed estimation error on the estimation of power coefficient. An ESC integrated interregion switching scheme is proposed to avoid the load increase. Simulation results show that, compared with the power feedback‐based ESC, the proposed method can greatly improve the convergence rate of ESC under fluctuating wind, even under relatively large wind speed estimation error. Evaluation for the fatigue loads of wind turbine shows that the proposed control strategy induces mild increase of the wind turbine load.     

Analysis of light detection and ranging wind speed measurements for wind turbine control

Light detection and ranging (LIDAR) systems are able to measure the speed of incoming wind before it reaches a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine structural loads. However, the degree to which such preview‐based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuous‐wave or pulsed Doppler LIDAR systems, in terms of root‐mean‐square measurement error, to determine their applicability to feedforward control. In particular, the impacts of measurement range, angular offset of the LIDAR beam from the wind direction, and measurement noise are studied for various wind conditions. A realistic simulation case involving a scanning LIDAR unit mounted in the spinner of a MW‐scale wind turbine is studied in depth, with emphasis on preview distances that provide minimum measurement error for a specific scan radius. Measurement error is analyzed for LIDAR‐based estimates of point wind speeds at the rotor as well as spanwise averaged blade effective wind speeds. The impact of turbulence structures with high coherent turbulent kinetic energy on measurement error is discussed as well. Copyright © 2013 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.     

Variable‐sized wind turbines are a possibility for wind farm optimization

The potential benefits associated with harnessing available momentum and reducing turbulence levels in a wind farm composed of wind turbines of alternating size are investigated through wind tunnel experiments. A variable size turbine array composed of 3 by 8 model wind turbines is placed in a boundary layer flow developed over both a smooth and rough surfaces under neutrally stratified thermal conditions. Cross‐wire anemometry is used to capture high resolution and simultaneous measurements of the streamwise and vertical velocity components at various locations along the central plane of the wind farm. A laser tachometer is employed to obtain the instantaneous angular velocity of various turbines. The results suggest that wind turbine size heterogeneity in a wind farm introduces distinctive flow interactions not possible in its homogeneous counterpart. In particular, reduced levels of turbulence around the wind turbine rotors may have positive effects on turbulent loading. The turbines also appear to perform quite uniformly along the entire wind farm, whereas surface roughness impacts the velocity recovery and the spectral content of the turbulent flow within the wind farm. Copyright © 2013 John Wiley & Sons, Ltd.