Intelligent control for large-scale variable speed variable pitch wind turbines

Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances. Automatic control is crucial for the efficiency and reliability of wind turbines. On the basis of simplified and proper model of variable speed variable pitch wind turbines, the effective wind speed is estimated using extended Kaiman filter. Intelligent control schemes proposed in the paper include two loops which operate in synchronism with each other. At below-rated wind speed, the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture. At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power. The simulation shows the effectiveness of the intelligent control.

Asymptotic Tracking Control for Wind Turbines in Variable Speed Mode

This paper presents a variable speed control strategy for wind turbines in order to capture maximum wind power.Wind turbines are modeled as a two-mass drive-train system with generator torque control.Based on the obtained wind turbine model,variable speed control schemes are developed.Nonlinear tracking controllers are designed to achieve asymptotic tracking for a prescribed rotor speed reference signal so as to yield maximum wind power capture.Due to the difficulty of torsional angle measurement,an observer-based control scheme that uses only rotor speed information is further developed for global asymptotic output tracking.The effectiveness of the proposed control methods is illustrated by simulation results.

PID-Type Fuzzy Controller for Grid-Supporting Inverter of Battery in Embedded Small Variable Speed Wind Turbine

Frequency and voltage of embedded variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) is strongly affected by wind speed fluctuations. In practice, power imbalance between supply and demand is also common, especially when VSWT-PMSG is connected to a weak micro grid (MG). If load demand fluctuations become high, isolated MG may be unable to stabilize the frequency and voltage so that battery storage needs to be installed into the MG to adjust energy supply and demand. To allow flexible control of active and reactive power flow from/to battery storage, grid-supporting inverters are used. For a system that contains highly nonlinear components, the use of conventional linear proportional-integral-derivative (PID) controllers may cause system performance deterioration. Additionally, these controllers show slow, oscillating responses, and complex equations are required to obtain optimum responses in other controllers. To cope with these limitations, this paper proposes PID-type fuzzy controller (PIDfc) design to control grid-supporting inverter of battery. To ensure safe battery operating limits, we also propose a new controller scheme called intelligent battery protection (IBP). This IBP is integrated into PIDfc. Several simulation tests are performed to verify the scheme’s effectiveness. The results show that the proposed PIDfc controller exhibits improved performance and acceptable responses, and can be used instead of conventional controllers.

The Control System Simulation of Variable-Speed Constant-Frequency Wind Turbine

In general,Variable-Speed Constant Frequency (VSCF)Wind generation system is controlled by stator voltage orientation method which based on the mathematic model of VSCF Wind generation system and discussed the control strategy.Present the whole dynamic control model of variable-speed wind generator system in MATLAB/ Simulink,and the simulation results confirm the validity and effectiveness of the proposed control strategy.

Advanced Control of a PMSG Wind Turbine

In this work, an intelligent artificial control of a variable speed wind turbine (PMSG) is proposed. First, a mathematical model of turbine written at variable speed is established to investigate simulations results. In order to optimize energy production from wind, a pitch angle and DC bus control law is synthesized using PI controllers. Then, an intelligent artificial control such as fuzzy logic and artificial neural network control is applied. Its simulated performances are then compared to those of a classical PI controller. Results obtained in MATLAB/Simulink environment show that the fuzzy and the neuro control is more robust and has superior dynamic performance and hence is found to be a suitable replacement of the conventional PI controller for the high performance drive applications.

PMSG Wind Energy Conversion System: Modeling and Control

In this paper, a model of a variable speed wind turbine using a permanent magnet synchronous generator (PMSG) is presented and the control schemes are proposed. The model presents the aerodynamic part of the wind turbine, the mechanic and the electric parts. Simulations have been conducted with Matlab/Simulink to validate the model and the proposed control schemes.

Effective participation of wind turbines in frequency control of a two-area power system using coot optimization

In this paper,load frequency control is performed for a two-area power system incorporating a high penetration of renewable energy sources.A droop controller for a type 3 wind turbine is used to extract the stored kinetic energy from the rotating masses during sudden load disturbances.An auxiliary storage controller is applied to achieve effec-tive frequency response.The coot optimization algorithm(COA)is applied to allocate the optimum parameters of the fractional-order proportional integral derivative(FOPID),droop and auxiliary storage controllers.The fitness function is represented by the summation of integral square deviations in tie line power,and Areas 1 and 2 frequency errors.The robustness of the COA is proven by comparing the results with benchmarked optimizers including:atomic orbital search,honey badger algorithm,water cycle algorithm and particle swarm optimization.Performance assessment is confirmed in the following four scenarios:(i)optimization while including PID controllers;(ii)optimization while including FOPID controllers;(iii)validation of COA results under various load disturbances;and(iv)validation of the proposed controllers under varying weather conditions.

Fractional-order Sliding Mode Control of Hybrid Drive Wind Turbine for Improving Low-voltage Ride-through Capacity

A hybrid drive wind turbine equipped with a speed regulating differential mechanism can generate electricity at the grid frequency by an electrically excited synchronous generator without requiring fully or partially rated converters. This mechanism has extensively been studied in recent years. To enhance the transient operation performance and low-voltage ridethrough capacity of the proposed hybrid drive wind turbine, we aim to synthesize an advanced control scheme for the flexible regulation of synchronous generator excitation based on fractional-order sliding mode theory. Moreover, an extended state observer is constructed to cooperate with the designed controller and jointly compensate for parametric uncertainties and external disturbances. A dedicated simulation model of a 1.5 MW hybrid drive wind turbine is established and verified through an experimental platform. The results show satisfactory model performance with the maximum and average speed errors of 1.67% and 1.05%, respectively. Moreover, comparative case studies are carried out considering parametric uncertainties and different wind conditions and grid faults, by which the superiority of the proposed controller for improving system ongrid operation performance is verified.

Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control

This paper presents a nonlinear control approach to variable speed wind turbine(VSWT)with a wind speed estimator.The dynamics of the wind turbine(WT)is derived from single mass model.In this work,a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed.The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation.In order to achieve the above objectives,VSWT should operate close to the optimal power coefficient.The generator torque is considered as the control input to achieve maximum energy capture.From the literature,it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics,increased power loss and complex control law.In addition,they are not robust with respect to input disturbances.In order to overcome the above drawbacks,adaptive fuzzy integral sliding mode control(AFISMC)is proposed for VSWT control.The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control.The result shows the better performance of AFISMC and its robustness to input disturbances.In this paper,the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function,and the sliding gain is adapted using a fuzzy technique which makes the controller more robust.

Adaptive Interval Type-2 Fuzzy Controller for Variable-speed Wind Turbine

In this paper,an adaptive interval type-2 fuzzy controller is proposed for variable-speed and variable-pitch wind turbines.Because of attractive features of the well-known wind turbine baseline controller,the proposed controller acts as an augmented controller and works in parallel to the baseline controller.As typical variable-speed wind turbines have different controllers for different operation regions,for each operation region,a dedicated interval tvpe-2 fuzzy controller is designed.Because of the uncertainty in wind speed measurement,modern control techniques try to estimate this value.However,in contrast to these modern control techniques,the proposed controller is independent of the wind speed estimation.Thus,there is a better saving in cost and computational burden.To evaluate the effectiveness of the proposed controller,simulations are conducted with wind profiles which span all operation regions.Results show that,compared with the baseline controller,the proposed controller enhances power generations and reduces mechanical loads concurrently.

Gain-scheduling control of a floating offshore wind turbine above rated wind speed

This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.

实际风况下萨沃纽斯风力机集群性能及布局规律研究

为探究风况条件对萨沃纽斯风力机集群功率输出和安装方向的影响,基于变转速控制策略和计算流体力学仿真结果,获得了集群在我国8个典型站点不同安装方向下的输出功率,分析了集群在实际风况下的最佳布局规律,并验证了规律的普适性。仿真结果表明:在沈阳、厦门、昆明、呼和浩特、青岛、喀什、大连以及郑州8个站点合理安装集群,可使单台机组的输出功率分别提升至原来的1.14、1.23、1.31、1.20、1.21、1.24、1.12、1.11倍;对于有明显单一主风能风向的地区,集群应正对此方向摆放;对于两个主风能风向相位差较大的地区,需选择两者中周围风能更丰富的方向排布集群;对于有3个主风能风向、主风能风向不明显或风能分布比较均匀的地区,应先使机组相互格挡的方位避开风能相对集中区,再选择风能资源较丰富的方向排布集群。该研究可使实际风况下萨沃纽斯风力机集群耦合增益最大化,并为复杂风场条件下集群安装方向的选择提供参考。

兆瓦级风电机组叶片延长载荷分析及平稳运行控制方法

为提高已建成风场中风电机组的发电效益,风电机组叶片延长是其有效途径之一。然而,叶片延长后风电机组易受到不同湍流强度扰动而导致机组极限载荷大幅变化,甚至损伤。首先从叶根、轮毂与塔基三个部位分别分析了湍流对风电机组的极限载荷变化。针对中低风速区间高湍流风况导致机组变桨频繁与功率输出不稳定的问题,采用桨距角控制与转速优化相结合的主动减载控制策略,通过预留出一部分转子转速以应对减载后的湍流现象,减轻变桨系统的负担。实验结果表明,在减载25%的情况下,所采用控制策略能够使桨距角基本稳定在2.5°左右,有效地减缓了湍流波动对桨距角,为使用叶尖延长等技术的风电机组稳定运行提供了一定的理论基础。

基于自适应遗传算法的风电机组变桨控制参数自寻优方法

当前,风力发电机组变桨系统采用传统PID参数整定方法,整定效率低、精确度和适应性差。为此,文章提出一种基于自适应遗传算法的风力发电机组变桨控制参数自寻优方法,包括变增益变桨PID参数自寻优和塔架加阻参数自寻优。其首先阐述了变桨控制系统基本原理;接着基于遗传算法根据风力发电机组不同机型对约束条件进行规划设计,涉及初始种群选择、自寻优算法约束及适应度函数设计;最后对传统参数整定方法与自寻优参数整定方法的响应曲线、仿真及现场运行结果进行对比分析。结果表明,相较传统方法整定的PID参数,自寻优变桨参数下发电机转速波动约降低10%,塔底My疲劳载荷约降低2%,对整定效率、精确度及适应性具有较好的改善效果。

计及风电综合惯性控制的电力系统扩展频率响应模型

现有的系统频率响应(SFR)模型对风电综合惯性控制的考虑较为简略,对场内风速差异以及转速恢复阶段等考虑不足,难以准确地反映出系统频率特性。为此,文中提出一种扩展SFR模型。首先,讨论了风电综合惯性控制的机理,分析了扰动后动态过程中风电机组转速与系统频率的交互影响。接着,基于风电机组动力学模型,采用小信号线性化方法推导了调频阶段与转速恢复阶段的风电机组传递函数,构建了含单台等值风电机组的扩展SFR模型。对于多风速风电场,提出了基于临界风速及风速相似度的风电机组预估-修正分群方法,将处于相同阶段且动态特性相似的风电机组划为同一群进行聚合,构建了含多台等值机的扩展SFR模型。最后,将扩展SFR模型应用于修改后的10机39节点系统的频率响应计算。仿真结果表明,该模型较好地反映了风电调频对频率的影响,具有较高的精度和较快的计算速度。

提升惯量响应与转速恢复的风储协调惯量控制方法

为提升风–储联合运行场站的动态频率支撑能力,并针对当前控制方法不能兼顾惯量响应强度与快速转速恢复、频率二次跌落抑制的问题,提出了一种提升惯量响应与转速恢复的风储协调惯量控制方法。在风机控制侧,根据储能可调功率及风机转速运行约束制定风机惯量控制策略,以最大化提取转子动能,增强风机惯量响应能力。在风机转速恢复阶段,由储能可调功率完全补偿风机功率下调量,加快风机转速恢复、抑制系统频率二次跌落;在储能控制侧,通过判断各风机运行阶段,提出基于差异化时序确定储能输出功率的控制策略。算例验证表明,所提方法在显著增强风机惯量响应能力条件下,能加快转子转速恢复,并有效抑制系统频率二次跌落。

基于遗传粒子群算法风电机组变速与变桨系统PI控制器设计

为了提升风电机组的控制精度并降低关键承载部件的载荷情况,通过遗传粒子群方法研究了变速与变桨系统比例积分(proportional integral,PI)控制器的设计。首先,采用泰勒级数将风电机组线性化展开为状态空间方程。然后,通过提取输入、输出和平衡点分别构建变速与变桨系统的数学模型。其次,分别采用Routh法和最小二乘法将变速与变桨系统辨识为低阶惯性系统和惯性时延系统。然后分别基于时间加权绝对误差积分准则和Chien-Hrones-Reswick法整定变速与变桨系统PI控制参数。最后,采用帕累托方法分配控制目标的权重关系并基于遗传粒子群算法优化变速与变桨系统PI控制参数,进而采用最小二乘法将其分别与风速和桨距角拟合构建自适应PI控制。结果表明:在变速控制中能够有效提升输出功率并抑制塔架顶部侧向振动;在变桨控制中能够有效平抑输出功率和发电机转速波动并降低叶片根部载荷情况。可见通过遗传粒子群方法设计的变速与变桨系统PI控制器具有良好的有效性和适用性。

大规模风电并网下抽水蓄能参与电网调频的模型预测控制策略

变速抽水蓄能机组在高比例风电并网的电力系统中具有深度参与频率调节的能力。针对短时风电功率波动引起电力系统频率扰动的问题,根据抽水蓄能机组不同的运行工况,提出抽水蓄能参与频率调节的模型预测控制策略。在发电运行时,利用风机的减载备用改善抽蓄机组因水锤效应引起的调频效果不佳的问题;在电动运行时,利用抽蓄机组快速响应的特点,有效平抑风电功率波动,提高风电机组的风能利用率。该策略在考虑抽蓄机组和风电机组各自约束条件的前提下,通过求解滚动时域内最优控制问题,协调各机组之间的有功出力分配,提高电网的调频性能。最后在Matlab/Simulink仿真平台对所提策略进行仿真验证,结果表明该策略能够有效改善抽水蓄能机组平抑风电功率波动时的调频效果。