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首页> 外文期刊>Electric Power Components and Systems >Design of Novel Intelligent Controller for Doubly-Fed Induction Generator-Driven Wind Turbine to Improve Transient Control Performance
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Design of Novel Intelligent Controller for Doubly-Fed Induction Generator-Driven Wind Turbine to Improve Transient Control Performance

机译：用于双馈感应发电机驱动风力涡轮机的新型智能控制器设计，提高瞬态控制性能

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摘要

This paper presents a design for the novel intelligent control (NIC) of the stabilization of a doubly fed induction generator (DFIG)-based wind turbine. The intelligent control scheme was developed to control the rotor side voltage source converter that allowed independent control of the generated active and reactive power as well as the rotor speed to track the maximum power point (MPP). Moreover, the NIC was used to reduce the interaction between the real and reactive power flow and improve the performance. The proposed NIC consisted of an improved recurrent fuzzy neural network (IRFNN) and ant colony optimization with genetic algorithms (GACO). GACO was adopted to adjust the learning rates to improve the online learning capability of the IRFNN. Furthermore, an NIC controller was proposed for both the rotor and stator side converters to improve the steady-state and transient voltage stability of the DFIG system for different operating conditions. In addition, the method is highly simple to implement. Finally, the proposed approach stabilized the internal dynamics through rotor voltage control and improved the dynamic behavior of the DFIG after clearing a fault.
机译：本文介绍了一种新型智能控制（NIC）稳定的双馈感应发电机（DFIG）的风力涡轮机的设计。开发了智能控制方案，以控制转子侧电压源转换器，其允许独立地控制产生的主动和无功电源以及转子速度以跟踪最大功率点（MPP）。此外，NIC用于减少实际和无功功率流动之间的相互作用，提高性能。所提出的NIC由改进的经常性模糊神经网络（IRFNN）和遗传算法（GACO）组成。采用Gaco来调整学习率，以改善IRFNN的在线学习能力。此外，提出了一种NIC控制器，用于转子和定子侧转换器，以改善DFIG系统的稳态和瞬态电压稳定性，用于不同的操作条件。此外，该方法实现高度简单。最后，所提出的方法通过转子电压控制稳定内部动力学，并在清除故障后改善了DFIG的动态行为。

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