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首页> 外文会议>2016 International Conference on Electrical Power and Energy Systems >Neuro fuzzy based PsQS controller for Doubly Fed Induction Generator with wind turbine
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Neuro fuzzy based PsQS controller for Doubly Fed Induction Generator with wind turbine

机译：风力发电机双馈异步发电机的基于神经模糊的Ps＆QS控制器

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摘要

Doubly Fed Induction Generator is especially used as wind power generators. This paper presents a control system which is based on neuro fuzzy because conventional PI controller based system does not operate satisfactorily as the operating point change. The proposed controller allows regulation in the active and reactive power efficiency. In this it takes the inputs as slip frequency, reactive power and active power to produce the voltage equal to cascaded arrangement speed. The proposed controller improves the low voltage ride and also voltage profile until the converter retrieves the normal operation. As the wind turbine of speed is variable time to time. This causes fluctuations in the output of Doubly fed induction generator and also affects the active & reactive power. If the reactive power changes then the power factor will also be affected. Unlike existed controller, in this the reactive power along with wind turbine speed is considered as inputs to the controller to maintain better power factor. The proposed model is implemented in Matlab/Simulink. The percentage THD of the voltage profiles is reduced.
机译：双馈感应发电机特别用作风力发电机。本文提出了一种基于神经模糊的控制系统，因为传统的基于PI控制器的系统不能随着工作点的变化而令人满意地运行。提出的控制器允许调节有功和无功功率效率。在这种情况下，将输入作为转差频率，无功功率和有功功率来产生等于级联布置速度的电压。所提出的控制器改善了低电压行驶并改善了电压曲线，直到转换器恢复正常运行为止。由于风力涡轮机的速度是不时变化的。这会引起双馈感应发电机的输出波动，并影响有功和无功功率。如果无功功率发生变化，那么功率因数也会受到影响。与现有的控制器不同，在这种情况下，无功功率与风力发电机的转速一起被视为控制器的输入，以保持更好的功率因数。该模型在Matlab / Simulink中实现。电压曲线的总谐波失真百分比降低。

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