Wavelet Analysis and Transient Signal Processing Applications for Power Systems E-Book

Zhengyou He

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 381

Veröffentlichungsjahr: 2016

Beschreibung

An original reference applying wavelet analysis to power systems engineering

• Introduces a modern signal processing method called wavelet analysis, and more importantly, its applications to power system fault detection and protection
• Concentrates on its application to the power system, offering great potential for fault detection and protection
• Presents applications, examples, and case studies, together with the latest research findings
• Provides a combination of the author’s tutorial notes from electrical engineering courses together with his own original research work, of interest to both industry and academia

Leseprobe

WAVELET ANALYSIS AND TRANSIENT SIGNAL PROCESSING APPLICATIONS FOR POWER SYSTEMS

Zhengyou He

Southwest Jiaotong University, China

This edition first published 2016© 2016 China Electric Power Press. All rights reserved.

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Library of Congress Cataloging-in-Publication Data

Names: He, Zhengyou, author.Title: Wavelet analysis and transient signal processing applications for power systems / Zhengyou He.Description: Singapore; Hoboken, NJ: John Wiley & Sons, 2016. | Includes bibliographical references and index.Identifiers: LCCN 2016003740 | ISBN 9781118977002 (cloth) | ISBN 9781118977033 (epub)Subjects: LCSH: Wavelets (Mathematics) | Signal processing.Classification: LCC QA403.3 .H4 2016 | DDC 621.3101/515723–dc23LC record available at http://lccn.loc.gov/2016003740

Cover Image: saicle/Getty

Preface

The fault-generated voltage and current contain abundant fault information, such as time of fault occurrence, fault location, fault direction, and so on. This information varies according to different fault conditions. It is important to analyze the fault transient signal and extract the fault features for fast protection, fault type identification, and fault location.

As a new branch of mathematics, wavelet analysis has made many achievements in seismic exploration, atmospheric and ocean wave analysis, speech synthesis, image processing, computer vision, and data compression, among others. With the fast development of computers and the application of large-scale scientific computing, wavelet analysis has been applied to power systems, especially in transient signal analysis.

This book provides the research results from recent years and the author’s many years of teaching experience in wavelet theory for engineering applications. A primary study of wavelet analysis theory applied to analyzing transient signals in power systems was carried out. This book is organized into 12 chapters: Chapter 1 briefly introduces the evolution from Fourier transform to time–frequency analysis and wavelet transform and gives a review about wavelet transform application in transient signal processing of power systems. Chapter 2 summarizes the fundamental theory of wavelet transform, including the author’s many years of teaching experience. Chapter 3 introduces the wavelet singularity detection theory and noise elimination capacity of wavelet transform. Chapter 4 presents the sampling techniques in wavelet analysis of transient signals, wavelet sampling in direct wavelet transform, and pre-sampling in indirect wavelet transform. Chapter 5 provides the method for selecting wavelet bases for transient signal analysis of power systems based on large simulations and validations. The guidance principle is provided, aimed at selecting the right wavelet basis for different conditions, such as detection of a high-order singular signal, detection of weak transients of low-frequency carriers, detection of transients in narrow-band interference, data compression, de-noising of transients, and location of transients. Chapter 6 introduces the construction method of practical wavelets in power system transient signal analysis. The construction and application of a class of M-band wavelets, recursive wavelets, and optimal wavelets are presented. Chapter 7 describes the wavelet post-analysis methods put forward by the author in detail and presents several typical post-analysis methods. Chapters 8 to 11 introduce the application of wavelet analysis in different power system fields. Chapter 12 introduces the definitions and physical significances of six wavelet entropies on the basis of traditional wavelet entropy. Meanwhile, the applications of six wavelet entropies in detection and identification of power systems transient signals have been presented.

The book is written by Prof. Zhengyou He, with the guidance of the author’s doctoral supervisor, Qingquan Qian. Dr Jing Zhao, Dr Xiaopeng Li, Master Haishen Zhang, Master Wen He, and Master Shu Zhang also contributed to the compilation and arrangement of this book. Some research of doctoral candidates and master’s degree candidates instructed or aided by the author (e.g., Dr Zhigang Liu, Dr Linyong Wu, Dr Ling Fu, Dr Ruikun Mai, Dr Sheng Lin, Dr Jianwei Yang, and PhD candidate Yong Jia) are included in this book. The author hereby thanks the teachers and students above for their contribution.

The book is supported by the National Natural Science Foundation of China (No. 50407009, “Wavelet Entropy Theory and Its Application in Power System Fault Detection and Classification”; and No. 50877068, “Research on Multi-source Power System Fault Diagnosis Method and System Based on Information Theory”), New Century Excellent Talents in University of Ministry of Education of China (No. NCET-06-0799, “Theory and Application of Power System Fault Diagnosis System Based on Information Theory”), Sichuan Province Youth Fund Projects (No. 06ZQ026-012, “Generalization of Information Entropy and Its Application on Power Grid Fault Diagnosis”), and Research Fund for the Doctoral Program of Higher Education of China (No. 200806130004, “A Novel Method for Transmission Line Fault Location Based on Single Ended Traveling Wave Natural Frequency”). This work is also supported by the Electrical Engineering School of Southwest Jiaotong University and colleagues of the National Rail Transit Electrification and Automation Engineering Technique Research Center. The author greatly acknowledges their help.

Sincere thanks also go to the researchers and experts whose research is referred to or cited in this book.

1Introduction

1.1 From Fourier transform to wavelet transform

1.1.1 Fourier transform [1]

Information in the time domain and frequency domain is the basic characteristic of the description of a signal x(t). Information in the time domain is easy to observe, whereas information in the frequency domain is not observable unless the signal transforms. Fourier first proposed the method to get frequency domain information when he was researching an equation of heat conduction. Moreover, he suggested transforming the equation of heat conduction from the time domain to the frequency domain, which is the famous Fourier transform concept. The definition of Fourier transform of a continuous signal () is