Novel Time-Domain Modeling Approaches of Electric Arc Furnace Using Enhanced Cassie-Mayr and ARMAX Models

Most nations, advanced and developing, use electric arc furnaces. Smelting and purifying many metals requires the Electric Arc Furnace (EAF). Unfortunately, electric arc furnaces have many problems of power quality that affect nearby loads. Thus, a model that accurately depicts electric arc furnace operation is necessary to describe this process. Two time-domain modeling methods are introduced and compared in this work. The Cassie-Mayr Time Domain correlation for arc furnaces was used to improve existing models and computational efficiency. Models accurately simulate Electric Arc Furnace behavior. The magnitudes and dynamics of arc voltage and current can be used to study the events. This study validates Electric Arc Furnaces’ famed non-linear and stochastic properties. This study introduces a unique black-box model for the EAF based on AutoRegressive Moving Average with eXogenous inputs (ARMAX) and improves the existing Cassie-Mayr model by reducing the use of differential equations to simulate EAF behavior.