| 引用本文: | 李鑫瑜,邓 丰,张 振,蒋素霞,毕岚溪.基于L1正则化反演的电压行波高精度检测方法[J].电力系统保护与控制,2023,51(22):167-176.[点击复制] |
| LI Xinyu,DENG Feng,ZHANG Zhen,JIANG Suxia,BI Lanxi.High precision detection method for a voltage traveling wave based on L1 regularization inversion[J].Power System Protection and Control,2023,51(22):167-176[点击复制] |
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| 摘要: |
| 针对电压行波传感器二次侧故障行波信号不能真实反映电网一次行波波形特征的问题，提出了一种基于L1正则化反演的电压行波高精度检测方法。首先，分析了行波传感器的非理想传变特性，揭示了一、二次行波信号的波形差异性。在此基础上，提出利用小波包变换对观测信号进行多尺度分解，并对各频段信号分别进行反演的方法，从而减小由行波传感器引起的畸变误差。其次，在反演模型中引入L1正则化约束对模型进行稀疏性刻画，使反演结果更能体现真实故障波形特征。最后，利用快速迭代收缩阈值算法(fast iterative shrinkage-thresholding algorithm, FISTA)进行迭代求解，将各分量的反演波形线性叠加，实现故障行波信号的精确还原。仿真和实验结果表明：与直接反演相比，所提方法能够实现故障行波在时域和频域上的高精度真实测量，在微弱故障和噪声环境下也能获得较为精确的反演结果，具有一定的工程应用价值。 |
| 关键词: 高精度检测 波形反演 行波传感器 L1正则化 多尺度 |
| DOI：10.19783/j.cnki.pspc.230189 |
| 投稿时间：2023-02-26修订日期：2023-08-05 |
| 基金项目:国家自然科学基金项目资助(52077008)；湖南省自然科学基金杰出青年项目资助(2022JJ10048) |
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| High precision detection method for a voltage traveling wave based on L1 regularization inversion |
| LI Xinyu1,DENG Feng1,ZHANG Zhen2,JIANG Suxia1,BI Lanxi1 |
| (1.College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114,
China; 2. Guangzhou Power Supply Bureau, CSG Guangdong Electric Power Company, Guangzhou 510620, China) |
| Abstract: |
| There is a problem that the fault traveling wave signal of the secondary side of a voltage traveling wave sensor cannot truly reflect the characteristics of the primary traveling wave of the power grid. Thus this paper proposes a high-precision detection method for a voltage traveling wave based on L1 regularization inversion. First, the nonideal transmission characteristics of the traveling wave sensor are analyzed. Then a method of multi-scale decomposition of the observed signal using wavelet packet transform and inversion of the signals in each frequency band is proposed to reduce the distortion error caused by the traveling wave sensor. Second, an L1 regularization constraint is introduced into the inversion model to describe its sparsity, so that the inversion results can better reflect the characteristics of real fault waveforms. Finally, FISTA is used to solve the problem iteratively, and the fault traveling wave signal can be obtained by linear superposition of the inversion waveforms of each component. The outcome of the simulations and experiments demonstrate that, compared with direct inversion, this method can achieve high-precision real measurement of a fault traveling wave in the time and frequency domains, and can obtain more accurate inversion results even in a weak fault and noise environment. This offers value for engineering application. |
| Key words: high precision detection waveform inversion traveling wave sensor L1 regularization multi-scale |
