Abstract
Abstract Low voltage cable is primarily connected from the transmission system to several household applications. It is quite common that switching transient in the power system during the energization of the high voltage and low voltage cables have a very crippling effect on the cable as well as the power system components. Hence, an experiment has been performed in the laboratory with a low voltage cable-connected motor system. The experimental results have been validated in the simulation platform, and they are capable of predicting the transient behavior during power cable energization. The effect of transients on power cables during the energization of devices has been investigated in this study in the form of voltage, current, and frequency. Discrete wavelet transform is implemented for the decomposition of the transient current. The generated approximation signal is used to quantify the severity during switching transient condition.
Highlights
The power distribution network faces many challenging tasks due to rapid urbanization and huge demand for reliable, uninterrupted power supply
discrete wavelet transform (DWT) helps in selecting a very high frequency for mother wavelet to avoid overlapping between close bands
To study the effect on switching transients of a cableconnected motor system, application of wavelet transform has been focused. This DWT mainly selects the suitable wavelet for switching transient and extracts its high-frequency component
Summary
The power distribution network faces many challenging tasks due to rapid urbanization and huge demand for reliable, uninterrupted power supply. It is a challenging task to model and analyze the switching transient phenomena with a LV cable It helps the power engineer for doing power quality assessment and for studying fault analysis, proper circuit breaker operation, protection of electronic devices, and health monitoring of the network. Severity quantification of the switching transient has been performed by determining the detailed and approximate coefficient of the current signal implementing discrete wavelet transform (DWT). DWT [20,21] and fast Discrete S transform [19] are widely used methods to extract essential features from the current and voltage signals. The model employs a multi-resolution approach of DWT to extract classification features This DWT helps in the decomposition and reconstruction of various transient signals.
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