Data Compression Algorithm of Power System

Abstract

Data compression refers to the use of software performance to improve system utilization without increasing hardware costs. Therefore, in the process of transmitting a large amount of power data, only an appropriate data compression algorithm can reduce the cost of data storage and communication and meet the user's requirements for high-speed data transmission. Aiming at the reconstruction and coding of power data signals, this paper proposes a Huffman compression algorithm, which can compress power energy signals and power quality disturbance signals. As a result, experiments show that the mean square error of the Huffman compression algorithm is small, the signal-to-noise ratio is large, and the compression effect is good. In view of the characteristics of redundant information of power data, this paper proposes a dictionary-based compression algorithm to compress it by searching for redundant feature formats. The advantage of this data compression method is that it can be well compressed according to the characteristics of redundant information in power system data format and units, and the compressed text can keep good format and original useful data. The measured compression ratio of this algorithm is not less than 30%. On the premise that the compression effect is good, the amount of program consumed is relatively small compared to the entire test data, and it is easy to implement on the hardware of the store's data processing system. Data compression reduces the occupation of data storage space, thereby reducing the time required to transmit data.