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An Intelligent Backup Scheme for Current Source Converter-High Voltage Direct Current Systems Based on Artificial Neural Networks

机译:基于人工神经网络的电流源-高压直流系统智能备份方案

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摘要

This paper presents an intelligent and integrated backup scheme based on artificial neural networks for current source converter-high voltage direct current (CSC-HVDC) systems. Taking advantage of the properties of ANNs to identify and classify patterns, the proposed scheme is able to detect and correctly locate a fault occurring either at the rectifier substation, the DC line or at the inverter substation. In this scheme, only local signals are used at the rectifier substation and no communication link is necessary, thus improving the system's protection reliability and reducing the required capital cost. Moreover, the proposed scheme could be promptly applicable in practical situations, as the hardware requirements and response times are not critical issues. All steps of the proposed scheme for the aforementioned purpose are accurately discussed in addition to all the information about the CSC-HVDC system under analysis. Finally, a detailed analysis of the influence of the main fault parameters on the algorithm's performance is also conducted.
机译:本文提出了一种基于人工神经网络的智能集成备份方案,用于电流源转换器-高压直流(CSC-HVDC)系统。利用人工神经网络的特性来识别和分类模式,所提出的方案能够检测并正确定位在整流子站,直流线路或逆变器子站发生的故障。在该方案中,整流子站仅使用本地信号,并且不需要通信链路,从而提高了系统的保护可靠性并降低了所需的投资成本。而且,由于硬件要求和响应时间不是关键问题,因此所提出的方案可以在实际情况中迅速应用。除了有关正在分析的CSC-HVDC系统的所有信息之外,还准确地讨论了用于上述目的的建议方案的所有步骤。最后,还详细分析了主要故障参数对算法性能的影响。

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