配电系统中基于三腿VSC的DVR的神经网络控制

J. Bangarraju, V. Rajagopal, A. Jayalaxmi
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引用次数: 4

摘要

本文研究了配电系统中基于DVR的三支路电压源变换器(VSC)的神经网络控制,以缓解电压的暂降、膨胀和谐波等问题。所提出的神经网络控制是基于最小均方算法,即自适应线性元来提取负载电压的基元分量。基于三支路VSC的DVR的参考信号是从参考负载电压中提取的。DVR的神经网络控制能够通过变负载控制自支撑其直流母线。神经网络控制的主要优点是消除了滤波,提高了DVR的性能。该DVR与源电压串联注入电压,在额定电压下调节电压。通过MATLAB/SIMULINK的计算机仿真研究,验证了所提出的基于神经网络控制的DVR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network control for three-leg VSC based DVR in distribution system
This paper deals with neural network control for three-leg Voltage Source Converter (VSC) based DVR in distribution system to mitigate voltage sag, swell and harmonics etc. The proposed neural network control is based on the least mean-square algorithm which is known as adaptive linear element to extract the fundamental component of load voltages. The reference signals for three-leg VSC based DVR are extracted from reference load voltages. The neural network control for DVR is able to self-support its dc bus through the control under varying loads. The main advantage of neural network control is to eliminate filter and which improves performance of DVR. The proposed DVR injects voltages in series with source voltage to regulate voltage at rated voltage. The proposed neural network control based DVR is validated through computer simulation studies using MATLAB/SIMULINK.
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