Research On Key Technology Of Transient Power Quality Disturbance

In the modern electrical system, electronic and electrical equipments are widely used and various non-linear, impulsive and fluctuant loads are increasing largely, which makes the power quality of electrical system suffer more and more seriously. At the same time, the development of information technology has a high requirement on power quality and power supply reliability. Power quality detection and analysis is the prerequisites of finding and improving the problem. How to extract the characteristics of disturbance signal from mass data and classify them correctly becomes our first concern.The paper makes a summary on the influence brought by power quality problems and summarizes the standard and research of power quality at home and abroad. Several key issues, such as power quality disturbance detection, voltage sags analysis and characteristics extraction, transient disturbances analysis and characteristics extraction and power quality disturbance signal compression are comprehensively and thoroughly studied and analyzed in the thesis.The main contents and contributions are as follows:The paper proposes a new approach to detect and classify power quality disturbances by combining the improved S-transform with time-domain analysis. Improved S-transform is suitable for the analysis of power quality disturbances under noisy condition as it has excellent time-frequency resolution characteristics and has the ability to detect the disturbance correctly. Various voltage disturbances are generated as per IEEE Std.1159 using MATLAB. The comparison between the Wavelet-transform-based method and the S-transform-based method for power quality disturbance recognition is also provided. The simulation results show that the proposed method is effective and immune against noise. The proposed method is feasible and promising for real applications.The paper proposes a new approach for classification of power quality disturbance. Through the analysis and comparison among statistical information charts of different types of disturbance signal, it extracts corresponding feature parameter to form simple rule tree, then achieve the classification and recognition of temporary power quality problem according to classification procedure of "data preprocessing-feature extraction-classification tree", A new power quality disturbance compression method is proposed.'Through analyzing the local time-frequency characteristics of power system disturbance signals, the Least Maximum method is presented to overcome the threshold problem of the signal compression. Some factors such as decomposition level and frequency-band overlap, which have important effect on the compression results, are also studied in the paper. The test examples prove the validity of the new method, with which the local time-frequency characteristics can be kept and the compression ratio is rather large.