An efficient power control scheme for electric arc furnaces using online estimation of flexible cable inductance

This paper proposes a method for efficient power control of Electric Arc Furnaces (EAFs) based on the estimation of the instantaneous value of the flexible cable inductance. In this method, the displacements of the graphite electrodes regulating arc voltages are controlled using instant values of inductances at the secondary side of the EAF in three phases. For on-line estimation of inductance values, an artificial neural network is trained, using a random set of data obtained from an appropriate inductance simulator. The performance of the proposed method is examined by comparing the thermal energy efficiency of a typical EAF for two control schemes, namely, constant and varying flexible cable inductances. It is shown that the proposed method significantly improves the efficiency with negligible changes in harmonic generation and unbalance operation of the EAF.