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Model predictive control with finite control set for variable-speed wind turbines

机译:带有有限控制集的变速风力发电机模型预测控制

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The existing model predictive control (MPC) algorithm for variable-speed wind turbines (WTs) is using continuous control set and solved by a quadratic programming method. Its main drawbacks are the heavily computational burden and the difficulty to implement. This paper introduces an alternative MPC method by using finite control set, which is used in controlling WTs at the first attempt. To do this, first of all, the WT's nonlinear model is linearized with information provided by a non-standard extended Kalman filter. Secondly, a discrete-time linear model of the system is used to predict the future value of the interested state variable for possible control sets. In view of the fact that control objectives are different within two operation zones partitioned by wind speed, two quality functions are predefined. One quality function evaluates the optimal generator speed tracking error together with the penalty of torque actuator action at below rated wind speed, while the other evaluates the rated generator speed tracking error and the penalty of pitch actuator action at above rated wind speed. Then, the corresponding control set which minimizes the quality function is selected. Finally, some simulation results are demonstrated to visualize the effectiveness and feasibility of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.
机译:现有的变速风力涡轮机模型预测控制(MPC)算法使用的是连续控制集,并通过二次规划方法求解。它的主要缺点是繁重的计算负担和难以实施。本文介绍了一种使用有限控制集的MPC替代方法,该方法最初用于控制WT。为此,首先,使用非标准扩展卡尔曼滤波器提供的信息对WT的非线性模型进行线性化。其次,系统的离散时间线性模型用于预测可能的控制集的感兴趣状态变量的未来值。考虑到在由风速划分的两个运行区域内控制目标不同的事实,预定义了两个质量函数。一个质量函数评估最佳发电机转速跟踪误差,以及低于额定风速时转矩执行器动作的损失,而另一个函数评估额定发电机速度跟踪误差以及高于额定风速时变桨执行器动作的损失。然后,选择使质量函数最小的相应控制集。最后,通过仿真结果证明了该方法的有效性和可行性。 (C)2017 Elsevier Ltd.保留所有权利。

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