Research On Data Compression Algorithm And Communication Network Simulation In Power System

Power data compression is a new research topic for power system. It becomes more and more important with the extension of power grid, the development of power information system, and the application of wide area information. Nowadays many new automatic supervisory control and relay protection devices are used in power system. On one hand, they improve the standard of automation and information of power system operation and management. On the other hand, they generate large amount of data and have increasing demand for remote communication, which brings heavy burden to the data communication and storage of power system. Data compression is an efficient method to deal with the problem. The research and application of data compression technology is of great importance for reducing the data storage burden, improving the real-time index of power communication, accelerating the power information development, as well as improving the standard of power system operation and management.Based on the achievement of former researchers, the paper manages to investigate power data compression from the view of power system, and put much attention to the characteristics of power waveform data acquired from digital sampling. After studying in detail the theory and application of data compression, the paper proposes novel methods for both lossless and lossy power data compression. Finally, with the help of advanced communication network simulation software, the paper simulates the power communication network, and analyzes the effect of data compression.The paper first analyzes the application of Huffman lossless data compression algorithm in power system, and points out that the compression ratio of Huffman algorithm is low. By studying the magnitude and probability characteristics of power waveform data, as well as the information entropy of information theory, the paper shows the application of different character codes could influence the compression ratio. Then the paper performs theoretical deduction, and validates the advantage of hexadecimal characters over decimal characters for improving compression ratio of Huffman algorithm for power waveform data.In order to greatly improve the compression ratio of lossless data compression, the paper takes the advantage of delta modulation method that is usually used for the lossy compression of voice signal, and proposes a high-order delta modulation algorithm suitable for power waveform data, and it is improved to become a lossless compression algorithm with high compression ratio. The proposed algorithm applies high-order differential and reducing operation that requires little computation. It effectively reduces the magnitude of power data, so it could reduce the number of characters and bits required for compression coding. The proposed algorithm is particularly suitable for dealing with the digital sampling data that is provided by modern power devices with high sampling frequency, and it can output high-order differential data series suitable for the combined application of Huffman compression algorithm.In the field of power data lossy compression, the paper studies the wavelet packet compression method and points out its shortcomings. The study of various entropy functions for searching the best wavelet packet tree is emphasized, since it will help make the best use of the features and advantages of wavelet packet method over wavelet method. The paper finds that the best wavelet packet tree found by the commonly used Shannon entropy has poor compression effect, and the threshold entropy is better. Based on the findings and the thought of TCM (Trellis Code Modulation), the paper tries to achieve global optimization instead of local optimization for each step of wavelet packet compression algorithm, and proposes a wavelet packet unified threshold compression method. The proposed method uses the same threshold for both steps of searching the best wavelet packet tree and reserving the necessary wavelet packet coefficients, so it ensures the best wavelet packet tree found is also the tree with least amount of wavelet packet coefficients. Thus it achieves high compression ratio with little error. Simulation shows the proposed method achieves the highest compression ratio and the error is small, comparing with the results derived from the wavelet compression algorithm with the five entropy functions provided by MATLAB.In view of the present power communication network and the requirement of wide area information communication, the paper makes use of the advanced communication network simulation software OPNET, and simulates power data communication of both local network inside substations and wide area network among substations. The communication of power quality data and relay protection data are taken as examples to analyze the communication performance of different types of communication networks, to calculate the time delay indexes, and performs quantitative analysis to the effect of data compression technology for improving the real-time property of power system communication.