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Accurate modelling of the Electric arc furnace (EAF) is necessary to study its impact on the power systems. Here, a new model for the EAF is presented in which both non-linearity and time-varying characteristics are taken into account. The model consists of seven parallel current sources which represent the fundamental and harmonic currents. Magnitude and phase of the fundamental harmonic and magnitude of the second to seventh harmonics are considered as time-varying which are updated every 0.01 s. To do so, the actual data recorded from eight EAFs in the Mobarakeh steel company (MSC), Isfahan, Iran are used. Autoregressive moving average (ARMA) models are employed to derive the parameters of the time-varying model. Also, different orders and coefficients of the ARMA model are considered at each run of the model, which enables the proposed model to predict the nonstationary and stochastic behaviours of the EAF over long-time periods. It is shown that the proposed combined time-varying-harmonic model can even model the generated interharmonics. To evaluate the accuracy of the proposed model, the derived power spectral density (PSD) of the EAF time-varying parameters, the instantaneous flicker, and shortterm flicker by the proposed model are compared with the actual recorded data.

Fault detection in induction motors has drawn growing attention due to importance of these motors in different industries. Analysis of motor currents is a common method for the fault detection. This method is preferred compared with other approaches because of its economic and technical superiorities. In this paper, a modified model of an induction motor including stator fault and a new technique are proposed for detection of stator winding faults. Firstly, Walsh-Hadamard transform is applied to stator currents. Then, variation of Walsh-Hadamard transform is used as the criterion for the detection. Plenty of simulation cases are utilized to evaluate the method. To enhance accuracy of the model, isolation layer resistance (Rf) is also taken into account. For further evaluation, a large number of experimental data were recorded from different experiments to assess the method in practice.

This paper deals with the utilization of printed circuit board Rogowski coils (PCBRCs) for differential protection of electric arc furnace (EAF) transformers in Mobarakeh Steel Company (MSC), Isfahan, Iran. Because of a high level of current (in the range of 100 kA) in the EAF transformers in the MSC, employment of differential protection is quite challenging. Conventional current transformers (CTs) cannot offer reliable performance for very high current levels. The PCBRCs are a branch of Rogowski coils (RCs) that can be manufactured with high precision using computer-aided design approaches and have the capability for the measurement of very large currents. In this study, we have designed and manufactured two sets of PCBRCs to measure current in the primary and secondary sides of the EAF's transformers in the MSC. The PCBRCs are followed by a signal condition circuit (SCC) which includes a low-pass filter, amplifier, and voltage-to-current (V-to-I) converter block. Thanks to the SCC, the high current of the transformers can be properly sensed and transmitted over a long cable that connects the PCBRCs to the relay. Furthermore, a novel model is suggested for the EAF that includes characteristics of both time and frequency domain models. The suggested model is developed using a large number of recorded data from the MSC and can model the non-linear and time-variant behaviours of the EAF. The proposed PCBRCs, SCC, and EAF modelling are evaluated by some simulations and experiments in the MSC.