Design and implementation of energy reshaping based fuzzy logic control for optimal power extraction of PMSG wind energy converter

Frontiers in Energy Research(2022)

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摘要
Given the greater penetration of wind power, the impact of wind generators on grid electricity reliability imposes additional requirements. One of the most common technologies in wind power generating schemes is the permanent magnet synchronous generator (PMSG) converter. However, the controller calculation is difficult due to the nonlinear dynamical and time-varying characteristics of this type of conversion system. This study develops a unique intelligent controller approach based on the passivity notion that tracks velocity and maintains it functioning at the optimum torque. To address the robustness issues encountered by traditional generator-side converter (MSC) strategies such as proportional-integral (PI), this suggested scheme integrates a passivity-based procedure with a fuzzy logic control (FLC) methodology for a PMSG-based wind power converter. The suggested controller is distinguished by the fact that the nonlinear features are compensated in a damped manner rather than canceled. To achieve the required dynamic, the fuzzy controller is used, which ensures quick convergence and global stability of the closed loop system. The development of the maximum power collected, the lowered fixed gains, and the real-time application of the control method are the primary contributions and novelties. The primary objectives of this project are to manage DC voltage and attain adequate reactive power levels in order to provide dependable and efficient electricity to the grid. The proposed scheme is being used to regulate the MSC, while the grid-side employs a traditional proportional-integral method. The efficiency of the suggested technique is investigated numerically using MATLAB/Simulink software. Furthermore, the processor-in-the-loop (PIL) tests are carried out to demonstrate that the suggested regulator is practically implementable.
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关键词
renewable energy systems, fuzzy logic control, processor-in-the loop (PIL) experiments, nonlinear control, power extraction
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