Analysis of RMS Measurements Based on the Wavelet Transform

• Published in: Journal of control, automation & electrical systems automation & electrical systems, 2021-12, Vol.32 (6), p.1588-1602
• Main Authors: Coelho, Rodrigo de Almeida, Brito, Núbia Silva Dantas
• Format: Article
• Language: English
• Subjects: Control; Control and Systems Theory; Discrete Wavelet Transform; Electric filters; Electric potential; Electric power systems; Electrical Engineering; Electromagnetic wave filters; Engineering; Fourier transforms; Frequency analysis; Frequency ranges; Frequency response; Frequency variation; Harmonic distortion; Mechatronics; Robotics; Robotics and Automation; Signal monitoring; Voltage; Waveforms; Wavelet transforms
• ISSN: 2195-3880; 2195-3899
• DOI: 10.1007/s40313-021-00770-5

The monitoring of voltage and current signals in the electric power system (EPS) is a fundamental step for studies on power quality. Thus, the root mean square (RMS) value of a signal is one of the crucial quantities in the analysis of EPS. In the presence of distortions, voltage and current signals are discrepant from the sinusoidal waveform, which motivates the monitoring of signals’ harmonic distortion. Therefore, it is necessary to perform a correct estimation of RMS values in each frequency component that composes the signals. This work presents a study aiming to evaluate the application of Stationary Discrete Wavelet Transform (SDWT) and Stationary Discrete Wavelet Packet Transform (SDWPT) for estimation of RMS values in different frequency ranges. From synthetic signals, the accuracy of the estimation of RMS values obtained via SDWT and SDWPT is analyzed. Additionally, the performance of SDWT and SDWPT was compared to Discrete Fourier Transform (DFT). The effects of mother wavelet choice are assessed from the frequency response of wavelet filters. Furthermore, the effects of the sampling frequency choice, magnitude variation, and noisy conditions on the estimation of RMS values are also evaluated. The results indicate the existence of discrepancies between estimated values via SDWT and SDWPT and exact values when the estimation is applied to individual frequency components. In contrast, as the DFT analyzes each frequency component individually, its performance was superior to that of the SDWT and SDWPT to estimate RMS values.