A New Stochastic Model of Electric Arc Furnace Based on Hidden Markov Model: A Study of Its Effects on the Power System

Electric arc furnaces (EAFs) are nonlinear and time-variant loads that cause severe fluctuations of current, voltage, and current harmonics, voltage flicker, frequency changes, etc. The requirement is to present an accurate model to analyze the function of these types of loads. In this paper, a new model based on hidden Markov model theory is presented for an electric arc. For this purpose, the characteristic of the arc voltage-current is divided into four regions. Then, on the basis of actual measured samples of an electric arc in several functioning cycles of EAF, different operating points are generated in the form of statistical probability, corresponding to hidden Markov theory in the aforementioned four regions. The arc model is designed in the form of a current-dependent voltage source. Therefore, the proposed model is without linear approximation and corresponds to the actual state. Also, in order to be accurate in flicker modeling, a voltage is randomly considered for the arc model. After designing the aforementioned model, the effects resulting from this electric load in the power system are studied and analyzed. The simulation results are compared with the measured arc to show the accuracy and soundness of the model.