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- W4310971465 abstract "Current control of grid-connected converters may result in harmonic instability when grid impedance changes. To prevent this issue, current controller parameters can be tuned adaptively according to different short-circuit ratios (SCRs). It is thus important to estimate the grid impedance in real-time. Unlike traditional FFT-based impedance measurement methods, a more efficient estimation approach based on neural networks is proposed in this paper. This method does not require a fixed and relatively long sampling window, making it possible for real-time impedance measurement. Further, a step-by-step design method of the feedforward neural network (FNN) used for grid impedance estimation is developed. Time-domain simulation results validate the effectiveness of the approach. Based on the designed FNN, adaptive current control is implemented and verified through simulation." @default.
- W4310971465 created "2022-12-21" @default.
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- W4310971465 date "2022-10-17" @default.
- W4310971465 modified "2023-10-18" @default.
- W4310971465 title "Design of Neural Network for Adaptive Current Control with Different Short-Circuit Ratios" @default.
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- W4310971465 doi "https://doi.org/10.1109/iecon49645.2022.9968458" @default.
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