基于VSC-HVDC的海上风电场故障分类与定位的先进信号处理算法

Rehana Perveen
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引用次数: 0

摘要

本文通过s变换、集成经验模态分解(EEMD)和支持向量机(SVM)在RTDS平台上进行实时验证,快速可靠地检测交/直流故障。接下来进行分类,通过EMD和EEMD分解内禀模态函数提取特征,使用支持向量机技术进行清晰分类。仿真结果表明,即使在原始信号条件下,s变换和IMF1-H结合MPNN和LSSVM也能有效地检测和分类交/直流故障。本文还介绍了用行波法和EEMD法对连接OWF的高压直流电缆线路进行故障定位的方法。在MATLAB和RTDS(实时数字仿真)中,对通过电压源变换器-高压直流(vcs - hvdc)集成到陆上电网的海上风电场(OWF)系统进行了检测和分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced signal processing algorithm for fault classification and localization in VSC-HVDC based Offshore wind farm
This work provides real-time validation on the RTDS platform by the use of S-transform, Ensemble Empirical Mode Decomposition (EEMD), and SVM, for quick and reliable detection of AC/DC faults. Next for classification, features extracted through intrinsic mode function decomposed by EMD and EEMD and classified distinctly using support vector machine techniques. The simulation results reveal that S-transform and IMF1-H in association with MPNN and LSSVM can effectively detect and classify AC/DC faults even under raw signal conditions. This paper also presents the fault localization in the high-voltage direct current cable line connected to OWF by traveling wave and EEMD. The detection and classification are carried out on an offshore wind farm (OWF) system integrated to an onshore grid through a voltage source converter-high voltage direct current (VSC-HVDC) in MATLAB, as well as in RTDS(real time digital simulation).
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