Abstract
Energization of an unloaded transmission line produces switching transient overvoltages, the magnitude and shape of which are highly dependent on the point-on-wave at which the switching operation is initiated. These transients can impose dielectric stress on insulation and associated equipment in some circumstances – depending on the transient amplitude, spectral content and location – and therefore may affect system reliability. Accurate estimation of their magnitude is therefore essential for effective insulation coordination, transient suppression, and protection system design. This paper presents a multiresolution analysis-based algorithm for accurately estimating the magnitude of switching transient overvoltages during transmission line energization. New analytical expressions are derived for the efficient extraction and characterization of transient components, providing improved accuracy and computational efficiency compared to conventional methods. The proposed method decomposes the recorded transient waveform into approximation and detail components using the Haar wavelet and its associated scaling function. The Haar wavelet is selected for its orthogonality, compact support, and computational efficiency, enabling rapid and precise time-frequency localization of transient phenomena. By isolating the high-frequency components associated with switching events, the algorithm provides an accurate estimation of the peak overvoltage magnitude. Simulation results verify the effectiveness of the proposed MRA-based approach in accurately estimating transient overvoltages with reduced computational burden compared to conventional time-domain and frequency-domain methods. The findings confirm that the technique provides a robust and efficient framework for the analysis and quantification of switching transients in high-voltage transmission systems, thereby enhancing system protection and insulation design.