As the automation and intelligence for power grid and power system improves continuously, the function of power system signal analysis and data processing methods is further highlighted. Compressed sensing is a new signal processing method based on signal sparseness, which transforms the signal sampling process using Nyquist sampling theorem into the observation process based on optimized computation for restoring signal. It is widely used in signal / image processing, medical treatment imaging, wireless communication and etc. Compressed sensingbased power system signal analysis and data processing method has the advantages of low sampling rate, high compression ratio, easy to extract signal characteristics and etc. Therefore, it has a wide application prospect in power system. The main purpose of this paper is to provide a theoretical framework of compressed sensing, and to summarize its applications in power system signal analysis and data processing. The main aspects are as follows: power quality analysis, fault analysis, power system modal identification, power system prediction, data transmission, smart grid and etc, and combined with the development of compressed sensing in power system signal analysis and data processing, its development prospect is expected.