Power Quality Enhancement in Electric Arc Furnace Using Matrix Converter and Static VAR Compensator

Author:

Jebaraj Bharath Singh,Bennet Jaison,Kannadasan RajuORCID,Alsharif Mohammed H.ORCID,Kim Mun-KyeomORCID,Aly Ayman A.,Ahmed Mohamed H.

Abstract

In recent years, non-linear loads on the distribution side are increasing rapidly. Notably, the electric arc furnace (EAF) is the most used non-linear load due to its diverse applications for industrial needs. However, EAF has some disadvantages like uneven distribution of heat inside the furnace, release of unwanted gases, increased level of harmonics, and Flickers in voltages. Specifically, power quality concerns are more and need comprehensive solutions. In this work, a matrix converter (MC) along with static VAR compensator (SVC) is proposed, and the hybrid exponential-hyperbolic furnace model is adapted in MATLAB platform. Simulations are carried out for different cases and the observed results are compared with existing methodologies. It was perceived that the power quality parameters such as peak current and voltages, total harmonic distortions (THDs), voltage flickers, and power factors are enhanced compared with existing methodologies. Precisely, the THD of current and voltage attains a prime rate of about 2.85% and 29.54%, respectively. Moreover, the proposed model’s voltage flicker and power factor offer a grander scale of about 1.26% and 0.9975, respectively. The enhanced scheme provides more significant advantages to the large-scale steel manufacturing plant with EAF.

Funder

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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1. New directions in electric arc furnace modeling;Archives of Electrical Engineering;2024-01-02

2. Application of long short-term memory neural networks for electric arc furnace modeling;Applied Soft Computing;2023-09

3. Analysis of correlations between electric arc furnace model coefficients;2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe);2023-06-06

4. A Comprehensive Evaluation of Different Power Quantities in DC Electric Arc Furnace Power Supplies;Energies;2023-05-04

5. Application of Artificial Neural Networks in Electric Arc Furnace Modeling;Artificial Intelligence and Soft Computing;2023

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