Wavelet based real-time monitoring of electrical signals in Distributed Generation (DG) integrated system

Abstract

In this paper, Hilbert-Huang Transform (HHT) and Discrete Wavelet Transform (DWT) based methods are employed on line to monitor the deviation in electrical quantities of the power system integrated with distributed generation. HHT employs an Empirical Mode Decomposition (EMD) method i.e. decomposition of the signal into Intrinsic Mode Functions (IMFs) in such a way that they are sorted from the highest frequency to the lowest frequency whereas, Wavelet Transform (WT) decomposes the signal into components that are indicative of signal details and trend. This paper presents a comparative analysis of HHT and DWT with the motive to provide the guidelines for deciding which one of these techniques is more suitable for Power Quality (PQ) event analysis in the case of Distributed Generation (DG) integrated system, in real-time domain. From the comparative analysis, it is observed that DWT is more precise in comparison with HHT in determining PQ events in real-time domain with high resolution. This work further explores the potential of WT for the real time application in measuring, monitoring, and analyzing the electrical signals during the occurrence of voltage sag, swell and harmonics. Real time implementation of WT necessitates signal sections to be serially processed. Towards the same, signal samples are collected in a buffer and then subjected to WT to extract the inherent details. The processing of the signal gives attributes that help in identifying the type of disturbance. Performance of the proposed method is tested through simulations on MATLAB/Simulink platform along with the experimental validation of the technique. Results reveal that the application of WT, in real time, can accurately detect the instant of disturbances with minimum delay to analyze the PQ issues.