液压储能在风力发电储能中的应用

风力发电系统为实现系统稳定和持续供电,必须配备合适的储能装置.因此提出以下设想:将风能首先转化为液压能,并以液压蓄能器作为储能装置.不但可以实现系统的稳定和持续供电,还可以将发电机等设备降至地面,大大节约塔架的建造成本和风机的维护费用,并实现通过液压调速回路稳定电压.在上述设想的基础上,设计了一套实验模型,针对液压储能的系统效率和稳压效果进行仿真分析,结果表明:液压系统效率为72.9%,发电电压波动幅度小于0.83%,效率和稳压效果都能满足要求.     

PMSM无速度传感器最优转矩控制系统的研究

针对永磁同步电机自身特点及转子位置和速度检测问题,采用最优转矩控制策略,提出了将脉振高频电压信号注入法和模型参考自适应法有机结合的新型无速度传感器的复合方法,设计了PMSM无速度传感器的SVPWM最优转矩控制系统.通过设计速度切换方案,实现速度的平稳过渡.此复合方法解决了单一方法不能在全速度范围内同时兼顾良好的动态、稳态性能的问题.仿真结果表明:该方法能可靠地实现包括初始磁位在内的转子位置和速度的精确检测和控制,系统具有优良的动态、稳态性能.     

浅谈风力发电机组的监控系统

风力资源丰富的地区一般都是在沿海地区、海岛、海上、山口或草原地区,针对分散安装的风力发电机组要求能够实现无人值守运行和进行远程监控,因此对风力发电机组控制系统的自动化程度和可靠性提出了极高的要求。本文详细介绍了大型风力发电机组监控系统的基本结构、数据监测内容、信息通讯方式、控制软件功能特点及系统的抗干扰措施等。     

带ESO的ANFTSMC控制PMSM的新型MPTC无传感器控制策略

针对电动汽车中永磁同步电机传统控制策略对电机控制性能差的问题,提出了一种新型的自适应非奇异快速终端滑模模型预测转矩控制策略.设计了新型自适应指数趋近率,用性质更佳的双曲正切函数tanh()替换传统的切换函数sgn(),并构造了带ESO扰动观测的新型ANFTSMC作为系统转速控制器,消弱了抖振,提高了系统鲁棒性.为实现调速系统的无传感器控制,构造了基于tanh(Fal)的ESO转速观测器.与传统基于Fal函数的ESO相比,观测误差较小,观测精度较高.同时,针对预测转矩控制策略,提出了新型的目标函数构造方法,避免了权重系数的设计,并对传统电压矢量选择方法进行了改进与优化,减少了算法的计算量,结合所设计的新型控制器可有效提高系统的快速性,增加算法的实用性.     

风力发电机组偏航控制系统的优化及仿真

针对风精度在(±150)内时出现了风向标传感器不能正常工作,进而不能实现对风能的最大捕获,降低风力发电机组的发电效率的问题.提出了基于大范围风向变化的偏舷控制系统的优化策略:在风向变化绝对值(偏航角度)>150时,改善传感器自身性能;在风向变化绝对值<150时,采用陀螺仪和爬山算法相结合的方法来控制偏航机构.快速调节机舱的偏转角度,实现对捕获最大风能的偏航控制系统的优化.     

直驱型风力发电机组控制策略研究

针对直驱型风力发电机组常规控制策略中因扭矩和转速振荡幅值大、持续时间长,导致整个机组在较长的时间内受到损害,从而影响机组可靠性及寿命的问题,对当前的直驱型风力发电机组的特点及需求进行了总结,阐述了直驱型风力发电机组的常规控制策略的基本原理.结合直驱型风力发电机组的特点及需求分析了常规控制策略中扭矩和转速振荡幅值大,且稳定时间较长的不足,在此基础上提出了在直驱型风力发电机组变流器控制策略中引入扭矩比例系数来优化传统控制策略的方法.仿真和测试平台试验结果验证了优化后控制策略的性能明显优于传统的控制策略;在风速变化范围相同的条件下,优化后的风电机组的扭矩和转速振荡幅值比传统控制策略的机组减少了40％,且振荡持续时间也减少了1/3,对风电机组的损害明显减小.该优化方法能明显的提高机组的可靠性,从而能有效延长机组的使用寿命.     

风力发电机新型液压制动控制系统的研究

针对现有风力发电机液压制动系统现状,提出一种新型液压制动系统(柔性液压制动系统),建立风力发电机新型液压制动控制系统的模型,并用AMESim软件平台进行仿真,从理论上验证该制动系统的可靠性,并对影响该制动系统动态特性的因素进行分析,为开发新型液压制动控制器提供依据。     

基于风速预测的风电机组自动解缆优化方案研究

针对当前风电机组解缆控制存在的问题,首先对目标风电场的解缆情况进行了统计分析,指出优化解缆控制方案的必要性;然后提出了基于PSO-LSSVM模型的超短期风速预测方法,实现了对未来30 min内平均风速的预测;最后提出了基于超短期风速预测的风电机组自动解缆优化方案,并对目标风电场的解缆控制方案进行了优化升级。测试结果表明PSO-LSSVM模型与LSSVM模型相比具有更高的预测精度,能够满足解缆控制的要求;优化后的解缆控制方案有效降低了因解缆造成的电量损失,具有良好的工程应用价值。     

基于模糊控制的风力发电机组低风速时最大风能追踪控制仿真研究

在分析风力发电系统在低风速时对风能最大限度追踪的情况下,建立系统的仿真模型,并在此基础上提出了一种基于模糊控制的智能控制方法.该方法利用模糊系统的非线性控制模型,解决了难以精确控制的困难.以叶尖速比的偏差及其变化为输入对象,以励磁电压为输出对象对低风速时进行控制,其控制目的是获得最优叶尖速比,以使风力发电系统在低风速时平稳运行并获取最大风能.最后,以MATLAB的仿真模块进行验证仿真,结果证明提出方法的有效性和实用性.     

风机叶片打磨机器人的动力学控制

针对风机叶片打磨加工的特性,设计了可替代人工作业的机器人系统.在对风机叶片打磨机器人系统进行动力学建模的基础上,分别提取出移动平台和机械手的动力学模型.针对两个子系统分别采用了滑模控制和PD(比例微分)反馈控制.最后进行了仿真实验,通过对实验结果的分析得出:所建立的控制器可实现对风机叶片打磨机器人的有效控制,仿真结果符合移动机械手系统的相关特性.     

Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms

The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers.     

Spindle position regulation for wind power generators

The three-time-scale plant model of a wind power generator, including a wind turbine, a flexible vertical shaft, a variable inertia flywheel (VIF) module, an active magnetic bearing (AMB) unit and the applied wind sequence, is constructed. In order to make the wind power generator be still able to operate as the spindle speed exceeds its rated speed, the VIF is equipped so that the spindle speed can be appropriately slowed down once any stronger wind field is exerted. Currently, most of wind energy input is, as a matter of fact, a waste since the commercially available wind power generators only operate for fairly mild or low-speed wind field. To prevent any potential damage due to collision by shaft against conventional bearings, the AMB unit is proposed to replace the traditional bearings and regulate the shaft position deviation. By singular perturbation order-reduction technique, a lower-order plant model can be established for the synthesis of feedback controller. It is found that two major system parameter uncertainties, an additive uncertainty and a multiplicative uncertainty, are constituted by the wind turbine and the VIF, respectively. The upper bounds of system parameters variation can be therefore estimated and the frequency shaping sliding mode control (FSSMC) loop is proposed to account for these uncertainties and suppress the unmodeled higher-order plant dynamics. At last, the efficacy of the FSSMC is verified by intensive computer and experimental simulations for regulation on position deviation of the shaft and counter-balance of unpredictable wind disturbance.     

基于神经网络PID的变速变桨距控制设计

在风力发电中,为了提高风力发电的能量转换效率对风力发电机进行变速变桨距控制,按照所需要的功率系数值确定所需要的变桨角度,以保证功率的稳定.本文研究利用神经网络PID控制器作为变速变桨距系统的控制器.在风速低于额定风速时,采用的是变速控制,此时风能效率高于采用失速控制风电机组的风能效率,具有优化的气动特性;在风速高于额定风速的情况下,根据风速的变化调整桨叶节距角,从而调节发电机的输出功率,使风力发电机组的输出功率保持稳定.最后,利用Simulink构建整个控制系统,对系统进行Matlab仿真.结果表明,使用神经网络PID控制的风力发电系统在风速从额定风速到切出风速时,相对失速控制风电机组,采用变桨距控制风电机组的功率恒定,发电品质较好.     

兆瓦级风力发电机组模糊控制系统设计

以风速变化和变化率为输入量、以调桨量为输出量建立模糊控制器,给出了模糊控制规则表,实现了调桨模糊控制,同时阐述了偏航、制动、机舱振动、电缆缠绕等系统的实时控制,论证了系统的鲁棒性.     

含风、光发电单元的电动汽车充电站智能网络控制系统

针对风、光电等可再生能源以及电动汽车的广泛发展,对EV充电站与可再生能源的综合利用架构进行了分析,探讨了集成可再生能源发电单元的充电站运行模式和盈利方式,设计了一种含风光发电单元的电动汽车充电站网络控制系统。综合考虑EV入网、需求信息和站内功率补偿需求,提出了一种无需可再生能源出力预测实体的EV充电站智能控制策略。从功能需求角度出发,设计了充电站智能网络控制通信架构,为智能控制的决策与执行以及站内辅助管理功能的具体实现提供了有力支撑。研究结果表明,该控制系统能够有效改善站内可再生能源利用效率,并提高充电站运营者和EV用户的经济性,可以为示范城市充电基础设施的运行提供依据和技术支撑。     

New hybrid sensorless speed of a non-salient pole PMSG coupled to wind turbine using a modified switching algorithm

The paper focuses on the design of position and speed observers for the rotor of a non-salient pole permanent magnet synchronous generator (NSPPMSG) coupled to a wind turbine. With the random nature of wind speed this observer is required to provide a position and speed estimates over a wide speed range. The proposed hybrid structure combines two observers and a switching algorithm to select the appropriate observer based on a modified weighting coefficients method. The first observer is a higher-order sliding mode observer (HOSMO) based on modified super twisting algorithm (STA) with correction term and operates in the medium and nominal wind speed ranges. The second observer is used in the low speed range and is based on the rotor flux estimation and the control by injecting a direct reference current different to zero. The stability of each observer has been successfully assessed using an appropriate Lyapunov function. The simulation results obtained show the effectiveness and performance of the proposed observer and control scheme.     

额定风速以上永磁同步风力发电系统的自适应控制

由于受到机械负载和电气负荷限制,风力发电系统在额定风速以上时必须运行在恒功率状态,考虑到风机本身固有的非线性特性,以及大风速下外界干扰对风机系统参数的影响,设计了风力发电系统的自适应控制器.采用永磁电机转子磁场矢量控制原理,实现了发电机系统解耦控制和恒功率控制.理论分析和仿真结果表明,所设计的控制器可以保证在额定风速以上变化,系统参数不确定的情况下,仍能使永磁同步风力发电系统安全可靠运行并获取最大风能的目的.     

Variable speed wind turbine control by discrete-time sliding mode approach

The aim of this paper is to propose a new design variable speed wind turbine control by discrete-time sliding mode approach. This methodology is designed for linear saturated system. The saturation constraint is reported on inputs vector. To this end, the back stepping design procedure is followed to construct a suitable sliding manifold that guarantees the attainment of a stabilization control objective. It is well known that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The objectives are to synthesize robust controllers that maximize the energy extracted from wind, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. Simulation results of the proposed scheme are presented.     

Computational study on wind turbine airfoils based on active control for deformable flaps

This study numerically investigates the aerodynamic performance of Deformable trailing edge flaps (DTEFs) to reduce the fatigue and ultimate loads of wind turbine blades. A parametric design is adopted to ensure the flexible deformation of the DTEFs. Based on experimental data, a simulation of a baseline airfoil is performed with two methods: A fully coupled viscous/inviscid method employed by the XFOIL program and a Reynolds-averaged Navier–Stokes solver with a Transition SST (T-SST) turbulence model. The static and dynamic performances of DTEFs are then investigated under different flow conditions by using T-SST and maximizing its numerous advantages. Results indicate that under steady conditions, the effects of flap deflection on the integral forces and flow field structures of airfoils vary from attached flow conditions to separated conditions. The gaps between unsteady aerodynamic responses and static values are greater in attached flow and light stall conditions than in deep stall conditions. The ability of DTEFs to control the fatigue loads on wind turbine blades is verified. Specifically, DTEFs effectively alleviate the force fluctuations on blades under gust-induced swinging when wind speed measurements are considered.     

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies.