Abstract
The emergence of power quality as a topical issue in power systems in the 1990s largely coincides with the huge advancements achieved in the computing technology and information theory. This unsurprisingly has spurred the development of more sophisticated instruments for measuring power quality disturbances and the use of new methods in processing and analyzing the measurements. Fourier theory was the core of many traditional techniques and it is still widely used today. However, it is increasingly being replaced by newer approaches notably wavelet transformand especially in the post-event processing of the time-varying phenomena. This paper reviews the use of wavelet transform approach in processing power quality data. The strengths, limitations, and challenges in employing the methods are discussed with consideration of the needs and expectations when analyzing power quality disturbances. Several examples are given and discussions are made on the various design issues and considerations, which would be useful to those contemplating adopting wavelet transform in power quality applications. A new approach of combining wavelet transform and rank correlation is introduced as an alternative method for identifying capacitor-switching transients.
Highlights
Power quality is an umbrella terminology covering a multitude of voltage disturbances and distortions in power systems [1, 2]
Pure sine wave time-frequency decomposition, it is usually how exact one can anticipate the frequency contents of a signal that influences the choice of technique, the associated design settings, and the subsequent implementation. These are the choice of mother wavelet, continuous wavelet transform (CWT) or discrete wavelet transform (DWT), and the number of expansion levels
Wavelet transform is more forgiving than other methods when the form of the signal is not clearly known
Summary
Power quality is an umbrella terminology covering a multitude of voltage disturbances and distortions in power systems [1, 2]. The majority of disruptions recognized as power quality problems involve electromagnetic phenomena that cause the supply voltage to deviate from its ideal characteristics of constant frequency (50/60 Hz), constant voltage magnitude (nominal values), and completely sinusoidal [1] These phenomena can be divided into two broad categories of time-varying and steady-state (or intermittent) events. Signal processing is generally called upon when there is a need to extract specific information from the raw data, which typically in power systems are the voltage and current waveforms. As power systems use AC (alternating current), the RMS (root-mean-square) quantity is the most commonly used measure for voltage magnitude It is meant for periodic waveform, it is often taken as a rough estimate of the nonperiodic or time-varying voltage variations. The conclusions and recommendations are given on which power quality phenomena WT is suitable for use and vice versa
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