首页> 外文会议>Power and Energy Engineering Conference (APPEEC), 2010 >Control Strategy of Maximum Wind Energy Capture of Direct-Drive Wind Turbine Generator Based on Neural-Network
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Control Strategy of Maximum Wind Energy Capture of Direct-Drive Wind Turbine Generator Based on Neural-Network

机译:基于神经网络的直驱风力发电机最大风能捕获控制策略

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The wind power varies mainly depending on the wind speed. Many methods have been proposed to track the maximum power point (MPPT) of the wind, such as the fuzzy logic (FL), artificial neural network (ANN) and Neuro-Fuzzy. In this paper, a variable speed wind generator MPPT based on artificial neural network (ANN) is presented. It is designed as a combination of the generator speed forecasting model and neural network. The ANN is used to predict the optimal speed rotation using the variation of the wind speed and the generator speed as the inputs. The wind energy control system employs a permanent magnet synchronous generator connected to a DC bus using a power converter is presented. The performance of the control system with the proposed ANN controller is tested for wind speed variation. System simulation results have confirmed the functionality and performance of this method.
机译:风力主要因风速而异。已经提出了许多方法以跟踪风的最大功率点(MPPT),例如模糊逻辑(FL),人工神经网络(ANN)和神经模糊。本文提出了一种基于人工神经网络(ANN)的变速风力发生器MPPT。它被设计为发电机速度预测模型和神经网络的组合。 ANN用于使用风速的变化和发电机速度作为输入来预测最佳速度旋转。风能控制系统采用连接到DC总线的永磁同步发电机使用功率转换器。测试控制系统的性能与所提出的ANN控制器进行风速变化。系统仿真结果已经确认了这种方法的功能和性能。

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