基于TS模糊PID控制模型的发电机控制器设计

研究了对风力双馈感应发电机进行控制的TS模糊PID控制器;针对常规PID控制器难以应对某些对象参数变化大,延时环节较大以及噪声干扰等问题,提出了一种能对发电机控制的TS模糊PID控制器;首先定义了双馈感应发电机的数学模型,在此基础上提出了基于TS模型的PID模糊控制器设计方法,并将其用于双馈感应发电机有功功率控制问题中,最后在加入15%测量噪声干扰的情况下对发电机的TS控制器和TS-PID控制器分别进行了仿真;实验结果表明:采用TS模糊PID控制方法比常规PID具有更强的适应性、鲁棒性和可移植性。     

基于模糊PID的风力发电机桨距角控制

模糊PID控制应用于风力发电机的桨距角控制,其中风力发电机采用具有强非线性的数学模型,模糊PID控制器使用二维线性规则库和高斯型隶属度函数的结构。在MATLAB平台上搭建仿真模型,仿真结果表明采用模糊PID控制比纯PID控制效果稳定,鲁棒性强,能够有效改善风力发电系统变桨距控制效果。     

风电机组变桨距模糊遗传控制算法研究

为提高额定风速以上风力发电机组发电机转速和输出功率的稳定性,基于风电机组的运行特性,建立了风电机组变桨距控制仿真模型;针对遗传算法收敛速度慢的缺点,采用模糊遗传算法对PID控制器参数进行整定。仿真结果表明,基于模糊遗传的控制器不仅提高了遗传算法的收敛速度,且在动态性能及系统稳定性方面均优于遗传算法控制器。     

基于DSP的风力发电机主控制器系统设计

介绍风力发电机控制系统的发展历程和研究现状,详细介绍风力发电机主控制器系统的设计,提出一种以DSP为核心的风力发电机主控制器系统方案。方案采用TMS320C6713为核心处理器,通过设计外围采样、处理等模块,搭建风力发电机主控制器系统硬件模块。采用以太网通信方式和CAN总线通信搭建主控系统的通信方案,同时利用VS2008平台编写主控制器系统的PC端软件,实现对主控制器系统的远程控制。实验表明,该系统运行稳定,用户界面良好,能够满足风力发电机运行的需求。     

模糊控制在大型风力发电机控制中的应用

介绍一种用来控制变桨距大型风力发电机组的模糊控制器。具体介绍了模糊控制算法设计、基本模糊查询表的建立。给出了采用模糊控制的风力发电机控制系统模型结构图。仿真结果表明，不论是跟随性能还是抗干扰性能，采用模糊控制比用PID控制效果好，能克服被控系统模型参数变化和非线性等不确定因素，鲁棒性强，稳态精度高。     

智能全功率MPPT风光互补路灯控制器设计

针对一类普通风光互补路灯控制器转换能效低、稳定性差等问题,设计一种智能全功率MPPT风光互补路灯控制器.采用双MCU处理器PIC16F877A单片机为控制器核心,硬件采用模块化的设计方法,整个控制器由主控制模块、从控制模块、风力发电机智能升压MPPT模块,以及风力发电机点刹控制模块、太阳能智能升压MPPT模块、蓄电池充/放电模块、负载LED灯模块组成,在分析光伏电池和风力发电机最大功率点跟踪问题的基础上,采用风力发电机和太阳能智能全功率MPPT跟踪控制策略.最后,在实验室搭建测试平台,测试结果表明,控制器可以可靠稳定运行,跟普通控制器相比,其充电效率与能源利用能效提高22.1％,能够实现能源的最大化利用.     

基于智能控制方法的风力发电系统的变桨距控制器

以对风力发电机系统进行功率控制为目的,提出基于智能控制方法的变桨距控制器的设计.风力发电系统结构复杂,具有非线性、时变的特点,单纯的模糊控制和PID控制都不能取得良好的控制效果.针对这一问题,提出风力发电系统模糊PID双模变桨距控制策略.使用Matlab中的Simulink组件建立系统模型,进行仿真试验.仿真结果表明,使用模糊PID双模控制变桨距控制器的风力发电系统确实具有较好的动态性能、收敛速度和静态误差.     

基于微粒群算法的永磁同步发电机滑模控制

为了改善直驱永磁同步风力发电机控制系统的控制性能,设计了一种滑模控制器。运用Matlab/Simulink建立了直驱型永磁同步风力发电机的仿真模型。提出外环采用转速闭环控制控制策略,用于跟踪最佳转速,以实现风力发电系统的最大功率跟踪控制。针对转速闭环控制采用一种新型的趋近律设计了滑模控制器,并用微粒群优化算法对控制器参数进行寻优。所设计的控制器性能与比例积分（PI）控制器进行了对比,结果表明优化参数后的滑模控制器拥有更好的控制效果,同时也表明采用 PSO 算法进行控制器设计是有效、可行的。     

模糊控制在风力水力互补发电中的应用

设计了基于模糊控制器的风力水力互补发电系统,并利用MATLAB软件中的Simulink工具箱对该系统进行了建模仿真,取得了良好的效果。仿真结果表明,基于模糊控制器的风力水力互补发电系统可以很好地解决风力发电波动性大的问题,为风电的大规模应用提供了可行的解决方案。     

基于精确线性化的永磁同步风力发电机滑模控制

针对直驱永磁同步风力发电机的最佳转速跟踪控制,提出了基于精确线性化模型的滑模控制策略及其设计方法,运用Matlab/Simulink建立了直驱型永磁同步风力发电机的仿真模型,并对不同风况下运行的机组进行了仿真分析。结果表明该控制器能在较宽的风速范围内有效提高系统的鲁棒性。     

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 Kalman filter. Intelligent control schemes proposed in the paper mchde 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.     

基于二阶滑模控制的变速双馈风力发电系统最大功率点跟踪

本文提出一种超螺旋二阶滑模控制方案同时实现双馈变速风力发电系统最大风能捕获和无功功率调节.通过设计两个二阶滑模控制器,实现控制目标,降低机械磨损,提高控制精度,通过调节发电机转子电压,跟踪风机最优转速和转子电流设定值,实现额定风速以下的最大风能捕获和无功功率调节.采用二次型李雅普诺夫函数确定控制参数范围、确保系统有限时间稳定性.1.5 MW风机系统仿真实验验证所提方案有效性.     

风力发电机组的变论域自适应模糊控制

建立了变速变浆距风力发电机组的简化模型。在此基础上，将变论域自适应模糊控制应用到风力发电机组的转速和浆距控制系统中，改善风力发电机组的风能捕获性能。变论域自适应模糊控制器在保持规则形式不变的前提下。论域随着误差的变化而变化。这种控制器不但具有经典模糊控制的优点，如不需要精确的数学模型，产生非线性控制动作，良好的动态性能等．而且具有较高的控制精度。仿真结果证明该方法改善了风力发电机组的控制性能。     

直驱式永磁风力发电机软并网与功率调节的控制集成

为实现直驱式永磁同步风力发电机无冲击并网与风能最大跟踪控制, 设计了一种软并网与功率调节一体化的控制集成装置. 基于广义功角特性, 提出了一种对逆变器输出功率进行直接控制, 从而实现最大风能跟踪的控制策略. 新的控制策略可使发电机的转速按所期待的动态运动, 因而具有良好的静态与动态性能. 另外, 该控制律中对电机参数具有很强的鲁棒性, 因而该控制器能适应各种不同参数的同步风力发电机, 成为同步风力发电并网与功率调节的独立装置.     

A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage

The optimal control of large-scale wind turbine has become a critical issue for the development of renewable energy systems and their integration into the power grid to provide reliable, secure and efficient electricity, despite any possible constraints such as sudden changes in wind speed. This paper deals with the modeling and control of a hybrid system integrating a permanent magnet synchronous generator (PMSG) in variable speed wind turbine (VSWT) and batteries as energy storage system (BESS). Moreover a new supervisory control system for the optimal management and robust operation of a VSWT and a BESS is described and evaluated by simulation under wind speed variation and grid demand changes. In this way, the proposed coordinated controller has three subsystems (generator side, BESS side and grid side converters). The main function of the first one is to extract the maximum wind power through controlling the rotational speed of the PMSG, for this a maximum power point tracking algorithm based on fuzzy logic control and a second-order sliding mode control (SOSMC) theory is designed. The task of the second one is to maintain the required direct current (DC) link voltage level of the PMSG through a bidirectional DC/DC converter, whereas in the last, a (SOSMC) is investigated to achieve smooth regulation of grid active and reactive powers quantities, which provides better results in terms of attenuation of the harmonics present in the grid courant compared with the conventional first-order sliding controller. Extensive simulation studies under different conditions are carried out in MATLAB/Simulink, and the results confirm the effectiveness of the new supervisory control system.

     

An optimal fuzzy PI controller to capture the maximum power for variable-speed wind turbines

Wind energy conversion systems can work by fixed and variable speed using the power electronic converters. The variable-speed type is more desirable because of its ability to achieve maximum efficiency at all wind speeds. The main operational region for wind turbines according to wind speed is divided into partial load and full load. In the partial-load region, the main goal is to maximize the power captured from the wind. This goal can be achieved by controlling the generator torque such that the optimal tip speed ratio is tracked. Since the wind turbine systems are nonlinear in nature and due to modeling uncertainties, this goal is difficult to be achieved in practice. The proportional-integral (PI) controller, due to its robustness and simplicity, is very often used in practical applications, but finding its optimal gains is a challenging task. In this paper, to cope with nonlinearities and at the same time modeling uncertainties of wind turbines, a PI torque controller is proposed such that its optimal gains are derived via a novel scheme based on particle swarm optimization algorithm and fuzzy logic theory. The proposed method is applied to a 5-MW wind turbine model. The simulation results show the effectiveness of the proposed method in capturing maximum power in the partial-load region while coping well with nonlinearities and uncertainties.     

并网运行的直驱风力发电系统建模及仿真研究

在PSCAD/EMTDC中建立了包含风速、风力机、直驱同步发电机、轴系扭振模块、变流器及其控制部分的并网直驱风力发电系统模型,提出了基于最大风能跟踪控制结合变桨距控制的策略,研究了在变风速输入和网侧出现单相短路故障时直驱型风力发电系统的动态响应特性,仿真结果表明了并网直驱风力发电系统模型及其控制策略的正确性和可行性。     

变论域自适应模糊控制在航机发电中的应用

航机发电系统是一个时变、非线性、强干扰、模型复杂,燃料供应不确定性大的复杂系统,应用传统的控制方法往往难于达到满意的控制效果.变论域自适应模糊控制具有对模型无准确要求、响应快速、精度高、鲁棒性好、适应性强等优点.本文将变论域自适应模糊控制器用于航机发电机组的调节与控制中.首先详细的论述了控制器的结构设计、伸缩因子的选择方法,然后给出了具体的控制算法;最后给出的现场试验及试运行结果表明该控制算法在航机发电中切实可行,效果令人满意.     

An observer-based blade-pitch controller of wind turbines in high wind speeds

The paper focuses on variable-rotor-speed/variable-blade-pitch wind turbines operating in the region of high wind speeds, where blade pitch and generator torque controllers are aimed at limiting the turbine's energy capture to the rated power value. Coupled design is described of an observer-based blade-pitch control input and a generator torque controller, both of which not requiring the availability of wind speed measurements. Closed loop convergence of the overall control system is proved. The proposed control solution has been validated on a 5-MW three-blade wind turbine using the National Renewable Energy Laboratory (NREL) wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code.