Voltage flicker recognition due to Electric Arc Furnaces via wavelet transform applications

Abstract

Electric Arc Furnaces (EAFs), widely used for steel production industries, are highly nonlinear time-variant disturbing loads because of the random change of the electric arc length results in arc voltage and furnace/supply current fluctuations. Consequently, Power Quality (PQ) problems such as undesirable variations of reactive power, poor power factor, harmonics, and voltage flickers may appear. The main objective of this paper is to provide the wavelet transform method for EAF to perform particular studies for Voltage Flicker Recognition. For this purpose, the mathematical equations and the dynamic model of the EAF voltage flicker are developed. Both Discrete Wavelet Transform (DWT) and Continuous Wavelet Transform (CWT) are employed to detect flicker fluctuations, estimate its duration, magnitude to eliminate the expected fluctuations. Despite nonlinearities and harmonics often encountered in EAFs, a comprehensive comparison between DWT and CWT approaches are exhibited towards enhancing PQ problems. Simulations results, via MATLABTM/Simulink, reveal that the proposed Daubechie's DWT can be successfully used for ensuring significant decision for flicker compared to the Daubechie's CWT approach. It is evident to mention that, the results of this study open the way to explore a new standard based on Wavelet Transform (WT) for voltage flicker recognition.