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Sensorless control of PMSG in WECS using artificial neural network

机译:人工神经网络在WECS中PMSG的无传感器控制

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This paper presents an artificial neural network (ANN) observer for a speed sensorless permanent magnet synchronous generator (PMSG) in wind energy conversion system (WECS). In order to perform maximum power point tracking control of the wind generation system, it is necessary to drive wind turbine at an optimal rotor speed. From the aspect of reliability and increase in cost, wind velocity sensor is not preferred too. Wind and rotor speeds sensorless operating methods for wind generation system using observer are proposed only by measuring phase voltages and currents. Maximum wind energy extraction is achieved by running the wind turbine generator in variable-speed mode. The robustness of the ANN against stator resistance variation is studied.
机译:本文提出了一种用于风能转换系统(WECS)中的无速度传感器永磁同步发电机(PMSG)的人工神经网络(ANN)观测器。为了执行风力发电系统的最大功率点跟踪控制,有必要以最佳转子速度驱动风力涡轮机。从可靠性和成本增加的角度来看,风速传感器也不是优选的。仅通过测量相电压和电流来提出使用观测器的风力发电系统的风速和转子速度无传感器运行方法。通过以变速模式运行风力涡轮发电机,可以最大程度地提取风能。研究了神经网络对定子电阻变化的鲁棒性。

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