A measurement method based on the wavelet transform for power quality analysis

TLDR

The paper reports and briefly discusses the theoretical background of power quality analysis in electrical power systems. The study presents a measurement method for power quality analysis in electrical power systems and aims to enable future implementation in real‑time measurement equipment and offline analysis tools. The method evolves an iterative procedure that automatically detects, localizes, and estimates the most relevant disturbances by applying the continuous wavelet transform to the sampled signal and decomposing it into optimized frequency subbands using the discrete time wavelet transform. The method achieves high noise rejection and agile disturbance classification, as demonstrated by case studies that highlight its performance.

Abstract

The paper presents a measurement method for power quality analysis in electrical power systems. The method is the evolution of an iterative procedure already set up by the authors and allows the most relevant disturbances in electrical power systems to be detected, localized and estimated automatically. The detection of the disturbance and its duration are attained by a proper application, on the sampled signal, of the continuous wavelet transform (CWT). Disturbance amplitude is estimated by decomposing, in an optimized way, the signal in frequency subbands by means of the discrete time wavelet transform (DTWT). The proposed method is characterized by high rejection to noise, introduced by both measurement chain and system under test, and it is designed for an agile disturbance classification. Moreover, it is also conceived for future implementation both in a real-time measurement equipment and in an off-line analysis tool. In the paper firstly the theoretical background is reported and briefly discussed. Then, the proposed method is described in detail. Finally, some case-studies are examined in order to highlight the performance of the method.