电力系统信号与数据的压缩传感技术综述

发布时间：2018-07-06 06:42

本文选题：智能电网 + 电力系统　；参考：《仪器仪表学报》2017年08期

【摘要】：随着智能电网建设及电力系统自动化、智能化水平的不断提高,电力系统信号分析与数据处理方法在电力系统中的重要作用进一步凸显。压缩传感(CS)是一种基于信号的稀疏特性,将利用奈奎斯特采样定理的信号采样过程转化为基于优化计算恢复信号的观测过程的新兴信号处理方式,并广泛应用于信号/图像处理、医疗成像与无线通信等领域。基于压缩传感的电力系统信号分析与数据处理方法具有采样速率低、高压缩比,以及便于提取信号特征等优点,因而,在电力系统中具有广泛的应用前景。描述了压缩传感理论框架,并对该理论在电力系统信号分析与数据处理中的应用进行详细综述,其中主要围绕电能质量分析、故障分析、电力系统模态识别、电力系统预测、数据传输,以及智能电网等方面进行评述,并结合压缩传感在电力系统信号分析与数据处理领域的发展状况,对其发展前景进行展望。
[Abstract]:With the development of smart grid and automation of power system, the importance of signal analysis and data processing in power system is becoming more and more important. Compression sensing (CS) is a new signal processing method, which is based on the sparse characteristic of signals. The signal sampling process based on Nyquist's sampling theorem is transformed into a new signal processing method based on the optimal calculation of the observation process of recovered signals. And widely used in signal / image processing, medical imaging and wireless communication and other fields. The power system signal analysis and data processing method based on compression sensing has the advantages of low sampling rate, high compression ratio and easy to extract signal features, so it has a wide application prospect in power system. This paper describes the theoretical framework of compression sensing, and summarizes the application of the theory in the signal analysis and data processing of power system in detail. It mainly focuses on power quality analysis, fault analysis, power system modal identification, power system prediction, and so on. The data transmission and smart grid are reviewed, and the development of compression sensing in the field of power system signal analysis and data processing is discussed.
【作者单位】：东北电力大学信息工程学院;
【基金】：国家自然科学基金(51507029) 吉林省科技厅项目(20160520089JH)资助
【分类号】：TM711

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