Prediction of Arc Voltage of Electric Arc Furnace Based on Improved Back Propagation Neural Network

The Production of the quality steel is achieved by melting iron and steel scraps by utilizing electric power in an electric arc furnace, it acts as one of the major troublesome load in the electric power system due to high nonlinear and chaotic nature, thereby creating severe power quality disturbances to the interconnected network, therefor the need for model to describe the behavior of electric arc furnace in a simulation of electrical power system become significant, the relation between the arc voltage and arc current is pivotal in defining the characteristics of an electric arc furnace, in this paper, the Voltage and current characteristics based on real time data is discussed, then arc voltage prediction using improved back propagation neural network based on arc current under different zones of operation are simulated using MATLAB/SIMULINK, the results infer the validation of test results with the actual values and effectiveness of prediction by adoption of improved back propagation algorithm and efficient in terms of prediction with reduced errors. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.