Abstract
The effect of the Power Quality events can be devastating if not properly managed. To manage such PQ events effective detection and classification techniques must be developed. There are various mathematical models that can be used in the detection and classification of the events which could vary from Dip, Swell, Interruption, and Harmonic distortion. The paper is based on the classification of Voltage Dip, Voltage Swell and Voltage Interruption using the STFT as the method of the detection of the triggering point and using such synthetic signal to train the Naïve Bayes classifier to develop a classifier that is capable of classifying waveform signals that has such disturbances in them.
Highlights
Efficient power delivery is the concern of every electric power provider all over the world, the term PowerQuality (PQ) analysis cannot be over emphasized
Swell and Voltage Interruption using the Short Time Fourier Transform (STFT) as the method of the detection of the triggering point and using such synthetic signal to train the Naïve Bayes classifier to develop a classifier that is capable of classifying waveform signals that has such disturbances in them
The correct classification of power quality disturbance is the premise and the basis of governance and control of power quality events, and the usual approach is primarily based on the transformation and reconstruction of the original waveform, extracting classification features, impelling a large number of signal processing methods applied to the detection of the power quality events
Summary
Efficient power delivery is the concern of every electric power provider all over the world, the term Power. The electrical power system is expected to deliver undistorted sinusoidal rated voltage and current continuously at rated frequency to the consumers. Power Quality problem is defined as any power problem manifested in voltage, current, or frequency deviation that results in failure or malfunction of customer equipment [3] [5] [13]. Power Quality is something both the supplier of utility, the equipment manufacturer, and the end user has to deal with has it has to deal with the quality of the power supplied and how it is been used. To the Utility suppliers, Power Quality initially refers to the quality of the service delivered that is its reliability. Used feature extraction methods is Wavelet Transform (WT), Fourier Transform (FT), Hilbert. Bayesian classification and decision making is based on probability theory and the principle of choosing the most probable or the lowest risk (expected cost) option [11]
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