风力发电机组的非线性自适应控制方法研究

发布时间：2018-03-16 11:38

本文选题：风力发电机组　切入点：控制策略　出处：《河北工程大学》2017年硕士论文　论文类型：学位论文

【摘要】：人类赖以生存的自然环境正在因为过度使用煤炭、石油等资源而遭受破坏。针对这个亟待解决的问题,新型可持续利用的能源——风能,越来越受到人们的关注。风能的利用可以有效缓解不可再生资源的消耗且不会产生有害气体,符合可持续发展的要求。风力发电机组的变桨系统复杂且由风切变、塔影效应等引起的随机干扰,使系统表现出非线性特性。面对复杂多变的非线性系统,传统的PD控制已不能做到快速最优地实时进行参数整定。因此,设计对风机系统参数未知或受到外界干扰时控制系统能适应对象和扰动动态特性变化的自适应控制器很重要。针对风力发电机组在外界不定因素干扰的情况下稳定性差的问题,通过用自适应鲁棒控制方法,对风力发电机功率输出稳定追踪问题进行了研究和验证。首先分析了现有的各种风力发电机组,并对其运行原理进行了详细的阐述;然后对其各个系统建立了具有不确定项的非线性数学模型,采用自适应鲁棒自调节的方法设计自适应律和控制器。最后,实验证明风机系统在参数变化或受到外界干扰影响时,所设计的自适应控制器能使系统快速地追踪到期望曲线且比PD控制的精度高。针对自适应控制器中气动转矩是已知的,但在实际运用中很难获得精确表示的问题,通过加入神经网络控制,构成能够对未知参数逼近的神经网络自适应控制算法。该算法可以使系统不再依赖结构参数,快速跟踪转速,获得最优功率曲线。仿真验证该算法可以满足要求。
[Abstract]:The natural environment on which human beings depend is being destroyed by the overuse of coal, oil and other resources. The use of wind energy can effectively reduce the consumption of non-renewable resources and will not produce harmful gases, which is in line with the requirements of sustainable development. The variable propeller system of wind turbines is complex and wind shear. The random interference caused by the tower shadow effect makes the system show nonlinear characteristics. In the face of complex nonlinear systems, the traditional PD control can no longer achieve fast and optimal parameter tuning in real time. It is very important to design an adaptive controller which can adapt to the change of the object and the dynamic characteristic of disturbance when the parameters of fan system are unknown or disturbed by external disturbance. By using adaptive robust control method, the power output stability tracking problem of wind turbine is studied and verified. Firstly, various existing wind turbines are analyzed, and their operation principles are described in detail. Then, the nonlinear mathematical models with uncertain terms are established for each system, and adaptive law and controller are designed by using adaptive robust self-regulation method. Finally, the experiment proves that the fan system is affected by external disturbance or parameter change. The designed adaptive controller can track the desired curve quickly and has higher precision than PD control. The aerodynamic torque in the adaptive controller is known, but it is difficult to obtain accurate representation in practical application. By adding neural network control, a neural network adaptive control algorithm which can approach unknown parameters is constructed. The optimal power curve is obtained and the simulation results show that the algorithm can meet the requirements.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273;TM315

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