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.     

Preview predictive control layer design based upon known wind turbine blade‐pitch controllers

The use of upstream wind measurements has motivated the development of blade‐pitch preview controllers for improving rotor speed tracking and structural load reduction beyond that achievable via conventional feedback control. Such preview controllers, typically based upon model predictive control (MPC) for its constraint handling properties, alter the closed‐loop dynamics of the existing blade‐pitch feedback control system. This can result in a deterioration of the robustness properties and performance of the existing feedback control system. Furthermore, performance gains from utilising the upcoming real‐time measurements cannot be easily distinguished from the feedback control, making it difficult to formulate a clear business case for the use of preview control. Therefore, the aim of this work is to formulate a modular MPC layer on top of a given output‐feedback blade‐pitch controller, with a view to retaining the closed‐loop robustness and frequency‐domain performance of the latter. The separate nature of the proposed controller structure enables clear and transparent quantification of the benefits gained by using preview control, beyond that of the underlying feedback controller. This is illustrated by results obtained from high‐fidelity closed‐loop turbine simulations, showing the proposed control scheme incorporating knowledge of the oncoming wind and constraints achieved significant 43% and 30% reductions in the rotor speed and flap‐wise blade moment standard deviations, respectively. Additionally, the chance of constraint violations on the rotor speed decreased remarkably from 2.15% to 0.01%, compared to the nominal controller. Copyright © 2017 John Wiley & Sons, Ltd.     

参与电网调频的风电机组线性变参数变桨控制策略

风电机组参与调频时其输出功率的调整将改变风电机组变桨动作的风速范围,同时由于桨距角调节气动功率的灵敏度随风况变化,使得传统PI变桨控制难以适用于风电机组参与调频时的复杂工况,出现风电机组转速振荡问题。提出一种基于线性变参数(Linear Parameter Varying, LPV)系统的风电机组变桨控制方法,对风电机组模型进行线性化,根据风速和桨距角的变化范围进行凸分解,得到其具有四面体结构的LPV模型,通过求解不同平衡点处的线性矩阵不等式(Linear Matrix Inequality, LMI)设计出相应的变桨控制器。仿真结果表明:与传统PI变桨控制相比,LPV变桨控制能有效减小转速的波动,降低低速轴载荷以及减小桨距角的波动程度,验证了该控制策略的有效性和先进性。     

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.     

High‐fidelity linear time‐invariant model of a smart rotor with adaptive trailing edge flaps

A high‐fidelity linear time‐invariant model of the aero‐servo‐elastic response of a wind turbine with trailing‐edge flaps is presented and used for systematic tuning of an individual flap controller. The model includes the quasi‐steady aerodynamic effects of trailing‐edge flaps on wind turbine blades and is integrated in the linear aeroelastic code HAWCStab2. The dynamic response predicted by the linear model is validated against non‐linear simulations, and the quasi‐steady assumption does not cause any significant response bias for flap deflection with frequencies up to 2–3 Hz. The linear aero‐servo‐elastic model support the design, systematic tuning and model synthesis of smart rotor control systems. As an example application, the gains of an individual flap controller are tuned using the Ziegler–Nichols method for the full‐order poles. The flap controller is based on feedback of inverse Coleman transformed and low‐pass filtered flapwise blade root moments to the cyclic flap angles through two proportional‐integral controllers. The load alleviation potential of the active flap control, anticipated by the frequency response of the linear closed‐loop model, is also confirmed by non‐linear time simulations. The simulations report reductions of lifetime fatigue damage up to 17% at the blade root and up to 4% at the tower bottom. Copyright © 2016 John Wiley & Sons, Ltd.     

双馈式变速变距风电机组LPV控制器设计

提出了一种将闭环极点配置到满足动态响应区域内的增益调度LPV(linear parameter varying)鲁棒H_∞控制器设计新方法,以解决机组的动态稳定性问题.利用LPV的凸分解方法,将风电机组线性化模型化为具有凸多面体结构的LPV模型,然后利用LMI(linear matrix inequalities)方法对凸多面体各顶点分别设计满足H_∞性能和闭环极点配置的反馈增益,再利用各顶点设计的反馈控制器综合得到具有凸多面体结构的IPV控制器.与PID控制的仿真结果相比较,验证了该控制器具有良好的控制性能.     

Optimization‐based load reduction during rapid shutdown of multi‐megawatt wind turbine generators

This paper describes an optimization‐based approach to reducing extreme structural loads during rapid or emergency shutdown of multi‐megawatt wind turbine generators. The load reduction problem is cast into an optimal control formulation, and a simple, low‐order model is developed in order for this optimization problem to be tractable in reasonable time using state‐of‐the‐art numerical methods. To handle the variations in wind speed and turbulence inherent to wind turbine operation as well as the presence of model mismatch, a real‐time optimization strategy based on fast sensitivity updates is also considered, whose online computational burden is limited to the repeated solution of quadratic programs that are designed offline. The low‐order model and both the open‐loop and closed‐loop optimal control strategies are validated against a high‐fidelity model in the simulation environment Bladed ? for an industrial 3 MW wind turbine. Under favorable shutdown scenarios, i.e. when the wind turbine is operating properly and the actuators and sensors are not faulty, large reductions of the first compressive peak and subsequent compressive/tensile peaks of the tower load pattern are obtained at various above‐rated wind speeds compared with normal pitch control shutdown. Extension to more challenging shutdown scenarios are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.     

Open‐loop frequency response analysis of a wind turbine using a high‐order linear aeroelastic model

Wind turbine controllers are commonly designed on the basis of low‐order linear models to capture the aeroelastic wind turbine response due to control actions and disturbances. This paper characterizes the aeroelastic wind turbine dynamics that influence the open‐loop frequency response from generator torque and collective pitch control actions of a modern non‐floating wind turbine based on a high‐order linear model. The model is a linearization of a geometrically non‐linear finite beam element model coupled with an unsteady blade element momentum model of aerodynamic forces including effects of shed vorticity and dynamic stall. The main findings are that the lowest collective flap modes have limited influence on the response from generator torque to generator speed, due to large aerodynamic damping. The transfer function from collective pitch to generator speed is affected by two non‐minimum phase zeros below the frequency of the first drivetrain mode. To correctly predict the non‐minimum phase zeros, it is essential to include lateral tower and blade flap degrees of freedom. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Model predictive control for wind turbines with distributed active flaps: incorporating inflow signals and actuator constraints

This paper describes the implementation of system identification and controller design techniques using model predictive control (MPC) for wind turbines with distributed active flaps for load control. An aeroservoelastic model of the 5 MW NREL/Upwind reference wind turbine, implemented in the code DU_SWAMP, is used in an industry‐based MPC controller design cycle, involving the use of dedicated system identification techniques. The novel multiple‐input multiple‐output MPC controllers, which incorporate flap actuator constraints and the use of local inflow measurement signals, are designed and implemented for various operating points. The controllers are evaluated in standard power production load cases and fatigue load reductions up to 27.3% are achieved. The distributed flaps controller scheme is also compared with simpler single‐flap single‐input single‐output and individual pitch controller schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

Stability analysis of pitch‐regulated,variable‐speed wind turbines in closed loop operation using a linear eigenvalue approach

A multi‐body aeroelastic design code based on the implementation of the combined aeroelastic beam element is extended to cover closed loop operation conditions of wind turbines. The equations of a controller for variable generator speed and pitch‐controlled operation in high wind speeds are combined with the aeroelastic equations of motion for the complete wind turbine, in order to provide a compound aeroservoelastic system of equations. The control equations comprise linear differential equations for the pitch and generator torque actuators, the control feedback elements (proportional–integral control) and the various filters acting on the feedback signals. In its non‐linear form, the dynamic equations are integrated in time to provide the reference state, while upon linearization of the system and transformation in the non‐rotating frame, the linear stability equations are derived. Stability results for a multi‐MW wind turbine show that the coupling of the controller dynamics with the aeroelastic dynamics of the machine is important and must be taken into account in view of defining the controller parameters. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive tower damping control for offshore wind turbines

This paper deals with the problem of wind turbine tower damping control design and implementation in situations where the support structure parameters vary from their nominal design values. Such situations can, in practice, occur for onshore and especially offshore wind turbines and are attributed to aging, turbine installation, scour or marine sand dunes phenomena and biofouling. Practical experience of wind turbine manufacturing industry has shown that such effects are most easily quantified in terms of the first natural frequency of the turbine support structure. The paper brings forward a study regarding the amount to which nominal tower damping controller performance is affected by changes in the turbine natural frequency. Subsequently, an adaptive tower damping control loop is designed using linear parameter‐varying control synthesis; the proposed tower damping controller depends on this varying parameter which is assumed throughout the study to be readily available. An investigation of the fatigue load reduction performance in comparison with the original tower damping control approach is given for a generic three‐bladed horizontal‐axis wind turbine. Copyright © 2016 John Wiley & Sons, Ltd.     

Individual blade pitch control of floating offshore wind turbines

Floating wind turbines offer a feasible solution for going further offshore into deeper waters. However, using a floating platform introduces additional motions that must be taken into account in the design stage. Therefore, the control system becomes an important component in controlling these motions. Several controllers have been developed specifically for floating wind turbines. Some controllers were designed to avoid structural resonance, while others were used to regulate rotor speed and platform pitching. The development of a periodic state space controller that utilizes individual blade pitching to improve power output and reduce platform motions in above rated wind speed region is presented. Individual blade pitching creates asymmetric aerodynamic loads in addition to the symmetric loads created by collective blade pitching to increase the platform restoring moments. Simulation results using a high‐fidelity non‐linear turbine model show that the individual blade pitch controller reduces power fluctuations, platform rolling rate and platform pitching rate by 44%, 39% and 43%, respectively, relative to a baseline controller (gain scheduled proportional–integral blade pitch controller) developed specifically for floating wind turbine systems. Turbine fatigue loads were also reduced; tower side–side fatigue loads were reduced by 39%. Copyright © 2009 John Wiley & Sons, Ltd.     

Optimal blade pitch control with realistic preview wind measurements

In above‐rated wind speeds, the goal of a wind turbine blade pitch controller is to regulate rotor speed while minimizing structural loads and pitch actuation. This controller is typically feedback only, relying on a generator speed measurement, and sometimes strain gages and accelerometers. A preview measurement of the incoming wind speed (from a turbine‐mounted lidar, for example) allows the addition of feedforward control, which enables improved performance compared with feedback‐only control. The performance improvement depends both on the amount of preview time available in the wind speed measurement and the coherence between the wind measurement and the wind that is actually experienced by the turbine. We show how to design a collective‐pitch optimal controller that takes both of these factors into account. Simulation results show significant improvement compared with baseline controllers and are well correlated with linear model‐based results. Linear model‐based results show the benefit of preview measurements for various preview times and measurement coherences. Copyright © 2016 John Wiley & Sons, Ltd.     

Model‐based receding horizon control of wind farms for secondary frequency regulation

In this study, we propose the use of model‐based receding horizon control to enable a wind farm to provide secondary frequency regulation for a power grid. The controller is built by first proposing a time‐varying one‐dimensional wake model, which is validated against large eddy simulations of a wind farm at startup. This wake model is then used as a plant model for a closed‐loop receding horizon controller that uses wind speed measurements at each turbine as feedback. The control method is tested in large eddy simulations with actuator disk wind turbine models representing an 84‐turbine wind farm that aims to track sample frequency regulation reference signals spanning 40 min time intervals. This type of control generally requires wind turbines to reduce their power set points or curtail wind power output (derate the power output) by the same amount as the maximum upward variation in power level required by the reference signal. However, our control approach provides good tracking performance in the test system considered with only a 4% derate for a regulation signal with an 8% maximum upward variation. This performance improvement has the potential to reduce the opportunity cost associated with lost revenue in the bulk power market that is typically associated with providing frequency regulation services. Copyright © 2017 John Wiley & Sons, Ltd.     

Analysis and optimal individual pitch control decoupling by inclusion of an azimuth offset in the multiblade coordinate transformation

With the trend of increasing wind turbine rotor diameters, the mitigation of blade fatigue loadings is of special interest to extend the turbine lifetime. Fatigue load reductions can be partly accomplished using individual pitch control (IPC) facilitated by the so‐called multiblade coordinate (MBC) transformation. This operation transforms and decouples the blade load signals in a yaw‐axis and tilt‐axis. However, in practical scenarios, the resulting transformed system still shows coupling between the axes, posing a need for more advanced multiple input multiple output (MIMO) control architectures. This paper presents a novel analysis and design framework for decoupling of the nonrotating axes by the inclusion of an azimuth offset in the reverse MBC transformation, enabling the application of simple single‐input single‐output (SISO) controllers. A thorough analysis is given by including the azimuth offset in a frequency‐domain representation. The result is evaluated on simplified blade models, as well as linearizations obtained from the NREL 5–MW reference wind turbine. A sensitivity and decoupling assessment justify the application of decentralized SISO control loops for IPC. Furthermore, closed‐loop high‐fidelity simulations show beneficial effects on pitch actuation and blade fatigue load reductions.     

Robust gain scheduling baseline controller for floating offshore wind turbines

The possibility of a pitch instability for floating wind turbines, due to the blade‐pitch controller, has been discussed extensively in recent years. Contrary to many advanced multi‐input‐multi‐output controllers that have been proposed, this paper aims at a standard proportional‐integral type, only feeding back the rotor speed error. The advantage of this controller is its standard layout, equal to onshore turbines, and the clearly defined model‐based control design procedure, which can be fully automated. It is more robust than most advanced controllers because it does not require additional signals of the floating platform, which make controllers often sensitive to unmodeled dynamics. For the design of this controller, a tailored linearized coupled dynamic model of reduced order is used with a detailed representation of the hydrodynamic viscous drag. The stability margin is the main design criterion at each wind speed. This results in a gain scheduling function, which looks fundamentally different than the one of onshore turbines. The model‐based controller design process has been automated, dependent only on a given stability margin. In spite of the simple structure, the results show that the controller performance satisfies common design requirements of wind turbines, which is confirmed by a model of higher fidelity than the controller design model. The controller performance is compared against an advanced controller and the fixed‐bottom version of the same turbine, indicating clearly the different challenges of floating wind control and possible remedies.     

双馈风电机组电能质量特性联合仿真建模分析

建立双馈风电机组（DFIG）联合仿真精细化模型——GH Bladed-Matlab模型。在GH Bladed中搭建机组主要机械部件模型,在Matlab中搭建机组的主要电气部件。选取2.2 MW的双馈风电机组搭建模型,根据现场测试数据修正GH Bladed-Matlab模型,使仿真得到的机组闪变外特性、谐波外特性、功率控制外特性与其现场测试波形外特性基本保持一致,确保研究得到的联合仿真模型高精确性。所建立的模型在针对机组电能质量特性因素定性研究的基础上,结合数据进行定量分析,为同系列机组电能质量特性优化提供参考。