Nonlinear Model Predictive Control for DFIG-based Wind Power Generation
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摘要: 在现代风力发电厂中, 需对双馈式风力发电机(Doubly fed induction generator, DFIG)进行有效控制来确保高效率和高负荷跟踪能力. 风力发电厂包含很多不确定因素和非线性因素, 传统的线性控制器往往难以奏效. 本文针对双馈式风力发电机的功率控制提出了一种非线性模型预测控制方法. 文中的目标函数考虑了现实约束下的经济因素和设定值跟踪能力, 同时降低机组磨损和机械疲劳. 预测值可基于输入输出反馈线性化(Input-output feedback linearization, IOFL)策略来计算. 仿真实验结果验证了所构造的非线性模型预测控制器的有效性.Abstract: Reliable control of the doubly fed induction generator (DFIG) is necessary to ensure high efficiency and high load-following capability in the operation of modern wind power plant. It is often difficult for conventional linear controllers to achieve this goal as wind power plants are nonlinear and contain many uncertainties. This paper proposes a nonlinear model predictive controller for the power control of DFIG. It not only considers both the economic and tracking factors under realistic constraints, but also reduces wear and tear of the generating units. With the nonlinear DFIG, the prediction can be calculated based on the input-output feedback linearization (IOFL) scheme. Simulation results are presented to validate the proposed controller.
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