基于神经网络的工业微电网电压源变换器控制方法

Jinbang Xu, Zhizhuo Wu, Xuan Yang, Jie Ye, A. Shen
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引用次数: 4

摘要

近年来,随着电网电流谐波问题越来越受到人们的关注,人们研究了多种脉宽调制电压源变换器(PWM-VSC)的控制方案。传统的PI控制器显示出对负载和系统参数变化的敏感性等局限性。在负荷急剧变化的情况下,甚至系统的稳定性也会受到威胁。本文考虑了工业微电网VSC的实际情况,采用基于人工神经网络(ANN)的控制方法解决了VSC的控制问题。同时,介绍了一种在线参数整定算法,该算法具有自整定和系统特性辨识的优点。通过基于SABER软件的仿真验证了所提出的控制方案。仿真结果表明了该方法的优越性和参数整定过程的性能。
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ANN-based Control Method Implemented in a Voltage Source Converter for Industrial Micro-grid
With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter (PWM-VSC) have been investigated. Conventional PI controller has shown limitations such as sensitivity to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid (MG) is considered and an Artificial neural network (ANN) based control method is employed to solve the problem. Meanwhile, an on-line parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation based on SABER software. The simulation results have shown the advantage of the proposed method and the performance of the parameter tuning session.
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