变速风力发电系统双馈感应发电机的神经网络控制

Nanami Gana Lantewa, N. Magaji
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引用次数: 2

摘要

提出了基于人工神经网络的双馈感应发电机(DFIG)风力发电系统的人工智能控制器。为了保持恒定的有功功率基于PI控制器的概念。该人工神经网络控制器是基于变转速风力发电机转子回路设计的。建立了有功功率和无功功率控制律来控制DFIG的转子电压,并将两种功率的误差信号作为神经网络控制器的输入;这种方法消除了电流内环的使用和对任何磁通分量的估计。为了进行比较,开发了基于pi的矢量控制器。基于动态性能的仿真结果表明,基于神经网络的转子环控制器优于传统的PI控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Control of Doubly Fed Induction Generator of Variable Speed Wind Turbine System using Neural Network
This paper presents artificial intelligent controller based on Artificial Neural Network (ANN) for Doubly Fed Induction Generator (DFIG) wind turbine system. For the purpose of maintaining constant active power based on PI controller concepts. The ANN controller is based on rotor loop design for a variable speed wind turbine. An active power and reactive control law are created for controlling the rotor voltages of DFIG, and error signals for both the two powers act as the input to ANN Controller; this approach eliminates the use of current inner-loops and estimation of any flux components. For the purpose of comparison PI-based vector controller is developed. The simulation results based on dynamic performance indicate the superiority of ANN based rotor loop controller over the conventional PI controller.
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