A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

With the rapid development of smart grid (SG) technologies, massive system data has been generated for SG for grid operation status monitoring and fault warning, this massive integrated data has brought great challenges for data transmission and storage. Thus, the breakthrough of data compression technology has become more and more important for data processing, this proposal, a lossless data compression method is proposed. The proposed method improves the Lempel-Ziv-Welch (LZW) algorithm. Specifically, the proposed method employs a parallel search approach to search the index of the dictionary globally by dividing the dictionary into several small dictionaries of different sizes and bit widths. In addition, the dynamic variable-length coding method is used as the output code which can offer flexible bit widths instead of fixed values, and the optimal dictionary partition combination and size parameters are selected to construct dictionaries. At last, the improved algorithm is cascaded with Huffman algorithm to form the proposed data compression algorithm. The data compression efficiency has been successfully verified by comparing with conventional Huffman and LZW data compression algorithms through data simulation, and it is observed to offer a better compression ratio than those methods with only LZW algorithm or Huffman algorithm, and save storage space effectively. More than this, the proposed method has realized lossless compression for power system data and guaranteed the integrity of the data, which will have better applicability for dealing with any similar information data.