基于变分模态分解和压缩感知的电力系统宽频振荡监测方法

随着“双碳”目标的提出,未来电力系统会有更高比例可再生能源及电力电子设备并网,会引发电力系统新型宽频振荡问题。因此针对电力系统宽频振荡“高噪声”和“宽频带”的特点,提出一种基于变分模态分解和压缩感知的自适应宽频振荡监测方法。对变分模态分解(variational mode decomposition, VMD)方法进行改进,自适应确定模态分解数,抑制噪声分量并监测识别振荡信号的有效信息。若监测到宽频振荡,将降噪处理后的宽频振荡数据通过压缩感知(compressed sensing, CS)方法上传,在调度中心对压缩数据进行重构,精确恢复宽频振荡信号,方便调度主站后续分析处理。算例表明所提方法可在高强度随机噪声的情况下保持宽频振荡监测的质量,克服高速采样后数据传输带宽的限制,并在实际电力系统宽频振荡信号监测中有良好应用。

Monitoring method of power system wide-band oscillation based on variational mode decomposition and compressive sensing

With the proposal of the "double carbon" goal, a higher proportion of renewable energy and power electronic equipment will be connected to the grid in the future. This will cause the problem of wide-band oscillation. Therefore, according to the characteristics of "strong noise" and "wide band", a monitoring method of power system wide-band oscillation based on variational mode decomposition and compressive sensing is proposed. The variational mode decomposition (VMD) method is improved to adaptively determine the number of mode decompositions, reduce noise and monitor the effective information of the oscillation signal. If the wide-band oscillation is detected, the wide-band oscillation data after noise reduction is uploaded by a compressed sensing (CS) method. The compressed data is reconstructed in the dispatching center to accurately recover the wide-band oscillation signal. This is convenient for the subsequent analysis of the dispatching station. Numerical examples show that the proposed method can maintain the quality of wide-band oscillation monitoring when there is high-intensity random noise, overcome the limitation of data transmission bandwidth after high-speed sampling, and has a good application to wide-band oscillation signal monitoring of an actual power system. This work is supported by the Youth Fund of National Natural Science Foundation of China (No. 52107113).