双馈风电机组的自适应神经网络保性能虚拟同步机控制

Adaptive Neural Performance-guaranteed VSG Control for DFIG-based Wind Power Generators

  • 摘要: 近年来,可再生能源的电网渗透率逐年提升,电网对可再生能源参与一次、二次调频的需求也愈加紧迫,虚拟同步机技术(VSG)应运而生.VSG能够赋予新能源机组主动参与电网调频的能力,然而当VSG应用于双馈感应风力发电机(DFIG)时,存在动态过程中转子电流超出转子侧变流器(RSC)容量的风险.本文提出一种应用于DFIG的保性能虚拟同步控制器,通过使用误差映射函数将输出受限的系统转化为等价的不受限系统,并使用李亚普诺夫方法设计保性能控制器,保证转子电流在调频、故障穿越等强动态过程中不超过任意人为设定的限制;此外,利用神经网络自适应策略,对发电机组中的不确定动态特性进行补偿,从而获得理想的控制效果.最后,本文通过大量仿真验证了所提控制策略在调频能力、转子电流控制和应对参数偏差等方面的控制性能.

     

    Abstract: The penetration of renewable energies has been growing rapidly in recent years. Thus, the need to utilize renewables in grid primary/secondary frequency regulation has become very urgent. Within this context, the virtual synchronous generator (VSG)technique is proposed. With VSG, renewable generators are endued with the ability of actively participating in grid frequency regulation; however, there exists a risk of the rotor currents exceeding the limit of rotor-side converter (RSC)during dynamics when the VSG is applied to doubly-fed induction generator (DFIG)-based wind turbines. A performance-guaranteed VSG controller for DFIGs is proposed. An error mapping function is used to transform the system with output constraints into an equivalent unconstrained one, and performance-guaranteed controllers are designed using Lyapunov synthesis. The controller can guarantee that the rotor current is within any predefined limits during strong dynamics, such as the frequency regulating process and fault ride-through. Moreover, neural network adaptive methods are utilized to compensate uncertain DFIG dynamics; thus, satisfactory control effects are achieved. Finally, through numerous simulations, the frequency regulating ability, the rotor current control effect, and the performance against parameter deviations of our controller are verified.

     

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