基于WRBF网络的智能电网PMSG控制策略

2011 16th International Conference on Intelligent System Applications to Power Systems Pub Date : 2011-11-18 DOI:10.1109/ISAP.2011.6082233

Chiung-Hsing Chen, Chih-Ming Hong, Ting-Chia Ou

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引用次数: 6

摘要

智能电网发电系统可以根据风速实时调节风机转速，实现最大功率点跟踪(MPPT)。针对变速风力发电系统中的永磁同步发电机(PMSG)，提出了一种基于Wilcoxon径向基函数神经网络(WRBFN)的MPPT策略。所提出的MPPT策略采用爬坡搜索(HCS)方法，因此不受水轮机和发电机特性的影响。设计了一种高性能的在线训练WRBFN，用于带反向传播学习算法的PMSG调节控制器。

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WRBF network based control strategy for PMSG on smart grid

The rotation speed of turbines can be adjusted in the real time according to wind speed for maximum power point tracking (MPPT) in power generation systems on smart grid. In this paper, a Wilcoxon radial basis function neural (WRBFN) network based MPPT strategy is proposed for permanent magnet synchronous generator (PMSG) on variable speed wind turbine generation systems. The proposed MPPT strategy adopts a hill climbing searching (HCS) method, and thus is independent of the turbine and generator characteristics. The design of a high-performance on-line training WRBFN is used for a PMSG with back-propagation learning algorithm regulating controller.

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2011 16th International Conference on Intelligent System Applications to Power Systems

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