| Development of signal processing techniques provides new tools for study of power system automation. Traditional Fourier analysis and Wavelet analysis are used widely in various fields such as protective relay and power system control. This dissertation primarily engages in application of Mathematical Morphological. Firstly, Mathematical Morphological technique including its origin, development and recent application cases on various aspects of power systems are introduced in the dissertation. Several problems on digital protection and detection of power quality are discussed in details. Mathematical morphology (MM) is developed from set theory and integral geometry, and is concerned with the shape of a signal waveform completely in the time domain rather than the domain frequency. MM has been widely used in the areas of image processing, machine vision and pattern recognition. The mathematical calculation involved in MM includes only addition, subtraction, maximum, and minimum operations. When acting upon complex shapes of signal, MM operations are capable of decomposing a signal into meaningful parts and separating them from the background, as well as preserving the main shape characteristics. This dissertation discusses the applications of MM in power systems, especially in relays and detection of power quality disturbance. The novel approach for detection of power quality disturbance based on MM proposed in this dissertation can detect, locate and simply classify the power quality disturbances with white noise. The approach to Ultra-High-Speed (UHS) direction protection of a power transmission line based on MM in this dissertation can identify the fault direction from traveling wave signals mingled with intense noise interference. A fault phase selector based on MM transformation is proposed in this dissertation. A MM filter is proposed to detect the faint second changes of sequence currents and implement accelerated trip of power transmission lines in this dissertation.
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