基于鲁棒回归平滑的自适应次/超同步分量检测方法

Zongshuai Jin, Hengxu Zhang, Fang Shi, Weisheng Liu, Yuanlong Liu
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引用次数: 0

摘要

基于变流器的可再生能源和非线性负荷的渗透日益增加,迫切需要开发一种自适应监测亚/超同步组件的检测方法,以进一步检测数百或数千台变流器共存和合作的潜在风险。提出了一种基于鲁棒回归平滑滤波(RRSF)的增强自适应次/超同步分量检测方法。仿真试验表明,该方法能够检测到噪声信号中时变的次/超同步分量,信噪比为0 dB,对背景噪声的有色特性具有较强的鲁棒性。
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Adaptive Sub/Super-synchronous Components Detection Method Based on Robust Regression Smoothing
The increasing penetrations of converter-based renewable energy resources and nonlinear loads make it urgent to develop a detection method to adaptively monitor the sub/super-synchronous components to further detect the potential risk of the co-existence and cooperation of hundreds or thousands of converters. This paper proposes an enhanced adaptive sub/super-synchronous components detection method based on robust regression smoothing filtering (RRSF). According to simulation tests, the proposed method can detect the time-varying sub/super-synchronous components in the noisy signals with SNR of 0 dB and is robust to the colored property of background noise.
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