Research On Power Quality Transient Disturbances Based On Fractal And Lifting Complex Wavelet

In modern power system, along with the widespread application of nonlinear loads and increasingly development of sensitive electronic equipment in the power grid, the pollution problems for transient power quality are becoming more and more serious. Transient power quality must be improved in order to ensure that all electrical equipments can operate properly and reliably. Therefore, it is very necessary that we depthly study the theory and the detection analysis techniques related to the transient power quality.Since the transient power quality disturbance signal are usually some non-stationary signals, and have with shorter duration and strong randomness of perturbation, the detection of transient power quality is very difficult, therefore, it is the premature reason of the analysis and detection method for transient power quality. How to acquire these features quickly and accurately from the massive amount of power quality disturbance signal and to carry out correct classification and analysis, more and more researcher have obtained some method and deepen relative study. In order to accurately detect the disturbances of transient power quality, and efficiently improve power quality, researchers at home and abroad have investigated depthly these problems and then obtained a lots of research results, which propose many kinds of detection methods, for examples, Wavelet Transform, S transform, Short Time Fourier Transform (STFT) have been constructed for transient power quality. Based on analysis of existing relevant literatures and previous studies, this thesis improves efficiently and feasibly some detection methods for transient power quality. The main research and innovation work are as follows:(1) Aim to the characteristic of many kinds of disturbance, we utilize singularity of the disturbance signal, and propose an information overlay method based on multi-fractal singularity spectrum analysis and information entropy of transient disturbances. Furthermore, MATLAB simulation results show that the method can be detect effectively the individual and superimposition disturbance signal, and the approach of superposition transient disturbance detection offers a new idea.(2) In order to meet the requirements of real-time detection, a multi-resolution analysis method for transient power quality is proposed based on wavelet fractal approach. Furthermore, MATLAB simulation results show that:the above algorithm has better adaptability and robustness of the identification of transient power quality disturbances, and can identify non-coincident minor power quality disturbances. Moreover, the proposed wavelet fractal algorithm can calculate simply and be executed concurrently, and then is beneficial to the hardware implementation. Therefore, the algorithm can be used to analyze the power quality transient disturbance.(3) In order to meet the requirements of the transient disturbance detection accuracy for power quality transient disturbance signal including noise with rich characteristics, this thesis proposes a MAP wavelet-based power quality transient disturbance signal denoising analytical methods, and compares detailedly to some other existing denoising algorithms. Furthermore, MATLAB simulation results show that:the above algorithm has a good denoising effect and capability for transient power quality disturbance signal, which can effectively filter out noise with very small amplitude from power quality signal. Moreover, the proposed MAP wavelet denoising algorithm is simple and then is conducive to the hardware implementation. In practice, this algorithm can effectively filter out noise from transient power quality disturbance signal.(4) Since that the complex wavelet contains rich amplitude and phase information and to enhance the lifting wavelet algorithm is simple, we construct a novel complex wavelet method that can be used to the detection and localization of transient power quality disturbances. Similarly, MATLAB simulation results show that:the method is to locate the disturbance signal and analyze the amplitude value by take fully advantage of the amplitude and phase information obtained from the complex wavelet transform based on lifting wavelet. Meanwhile, the proposed lifting-complex wavelet algorithm has good real-time performance, simpler structure, and higher accuracy.In addition, on the basis of the above algorithms/schemes, a large number of MATLAB simulation are given, and some real applications to the fault location and the voltage drop for the actual power of the power system fault signal are given to demonstrate that the present results carries out accurate width analysis with exact position and shorter time-consuming, and have good effect for the real-world power quality transient disturbance signal.