Detection and assessment of unbalanced conditions in an early stages are of utmost importance for reliable and smooth operation of a grid-connected wind system. This article presents fault assessment in the grid-connected wind system. For this purpose, the grid-connected wind system has been simulated in MATLAB. All symmetrical and unsymmetrical faults have been considered for three different wind systems. The system current signal has been taken and normalized, then using discrete wavelet transform (DWT)-based statistical parameter analysis, unbalanced conditions have been detected. Total harmonic distortion (THD), interharmonics groups, and Stockwell transform (S-transform) based statistical parameter analysis has also been used for total assessment of unbalanced conditions, like presence of harmonics, classification of faults, etc. This article emphasizes fast detection and classification of all unbalanced conditions of the grid-connected wind system. Then, severity of different unbalanced conditions has been assessed by investigating the presence of harmonics using advanced signal-processing-based approach.

中文翻译：

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基于离散小波变换和斯托克韦尔变换的统计参数估计在并网风电系统故障分析中的应用

在早期阶段检测和评估不平衡状况对于并网风力发电系统的可靠和平稳运行至关重要。本文介绍了并网风系统中的故障评估。为此，已经在MATLAB中模拟了并网风系统。对于三种不同的风力系统，已经考虑了所有对称故障和非对称故障。已获取系统电流信号并对其进行了归一化，然后使用基于离散小波变换（DWT）的统计参数分析，已检测到不平衡状况。基于总谐波失真（THD），间谐波组和斯托克韦尔变换（S-transform）的统计参数分析也已用于不平衡条件的总评估，例如谐波的存在，故障的分类等。本文强调对并网风力系统的所有不平衡状况进行快速检测和分类。然后，通过使用基于高级信号处理的方法调查谐波的存在，来评估不同不平衡条件的严重性。