Combined RBFN based MPPT and d-axis stator current control for permanent magnet synchronous generators

This paper proposes a new radial basis function neural network maximum power point tracking controller based on a differential evolution algorithm for machine side converter of permanent magnet synchronous generator wind turbine under variable wind speed. Direct axis stator current control methods o...

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Bibliographic Details
Main Authors: Anh Nguyen, Tuan Ngoc (Author), Pham, Duy Cong (Author), Minh, Luu Hoang (Author), Chan Thanh, Nguyen Huu (Author)
Other Authors: The authors would like to thank Industrial University of Ho Chi Minh City, Vietnam for providing the funding for this research (Contributor)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2021-12-01.
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Summary:This paper proposes a new radial basis function neural network maximum power point tracking controller based on a differential evolution algorithm for machine side converter of permanent magnet synchronous generator wind turbine under variable wind speed. Direct axis stator current control methods of permanent magnet synchronous machine are reviewed shortly. A combined radial basis function neural network-based network maximum power point tracking method and d axis stator current control techniques including zero d axis stator current, unity power factor, and constant stator flux-linkage have been implemented to control the machine side converter of permanent magnet synchronous generator wind turbine. The dynamic performance of the proposed approach is assessed under different operating conditions through a simulation model based on MATLAB. It has been seen that the radial basis function neural network controller can not only track well the maximum power point but also can be reduced costly.
Item Description:https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21358