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Mechanical Sensorless Maximum Power Tracking Control for Direct-Drive PMSG Wind Turbines

机译:直驱式pmsG风力发电机无机械传感器最大功率跟踪控制

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摘要

Wind turbine generators (WTGs) are usually equipped with mechanical sensors to measure wind speed and rotor position for system control, monitoring, and protection. The use of mechanical sensors increases the cost and hardware complexity and reduces the reliability of the WTG systems. This paper proposes a mechanical sensorless maximum power tracking control for wind turbines directly driving permanent magnetic synchronous generators (PMSGs). In the proposed algorithm, the PMSG rotor position is estimated from the measured stator voltages and currents by using a sliding mode observer (SMO). The wind turbine shaft speed is estimated from the PMSG back electromotive force (EMF) using a model adaptive reference system (MRAS) observer. A back propagation artificial neural network (BPANN) is designed to generate the optimal shaft speed reference in real time by using the estimated turbine shaft speed and the measured PMSG electrical power. A control system is developed for the PMSG wind turbine to continuously track the optimal shaft speed reference to generate the maximum electrical power without using any wind speed or rotor position sensors. The validity of the proposed control algorithm is shown by simulation studies on a 3-kW PMSG wind turbine and experimental results on a practical 300-W PMSG wind turbine.
机译:风力发电机(WTG)通常配备机械传感器,以测量风速和转子位置,以进行系统控制,监视和保护。机械传感器的使用增加了成本和硬件复杂性,并降低了WTG系统的可靠性。本文提出了一种用于直接驱动永磁同步发电机(PMSG)的风力涡轮机的无机械传感器最大功率跟踪控制。在提出的算法中,通过使用滑模观测器(SMO)从测得的定子电压和电流中估算出PMSG转子位置。使用模型自适应参考系统(MRAS)观测器,根据PMSG反向电动势(EMF)估算风力涡轮机轴转速。反向传播人工神经网络(BPANN)设计为通过使用估算的涡轮轴转速和测得的PMSG电功率实时生成最佳轴转速参考。为PMSG风力涡轮机开发了一种控制系统,可在不使用任何风速或转子位置传感器的情况下,连续跟踪最佳轴速基准以生成最大电力。通过对3 kW PMSG风力发电机的仿真研究和在实际的300 W PMSG风力发电机上的实验结果证明了所提出的控制算法的有效性。

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