高压直流变流器在线故障检测新方法

J. Moshtagh, M. Jannati, H. Baghaee, E. Nasr
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引用次数: 26

摘要

提出了一种利用神经网络进行高压直流输电系统故障检测的新方法。该方法首先利用自适应线性神经元快速导出整流侧电压波形的谐波;然后,利用所提出的判据对直流线路故障、交流系统故障和变流器故障等不同类型的故障进行了检测。在所研究的直流输电系统中,对整流器及其控制器和所需滤波器进行了完整的建模。在MATLAB/Simulink环境下,对所提出的判据在高压直流系统上进行了计算机仿真。仿真结果表明,该方法可用于高压直流系统的在线故障检测。
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A novel approach for online fault detection in HVDC converters
A novel approach for fault detection in high voltage DC transmission systems using neural networks is presented. In the presented method, at first, Harmonics of voltage waveform in rectifier side are derived rapidly by using an adaptive linear neuron. Then, different types of faults including DC line fault, AC system fault and converter's faults are detected property using proposed criterion. In the under study voltage DC transmission systems system, rectifier and its controllers and required filters is modeled completely. A proposed criterion is tested on a high voltage DC system by computer simulation performed in MATLAB/Simulink environment. Simulation resulted demonstrates that the proposed approach can be used for online fault detection in high voltage DC systems.
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