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Electric arc furnace (EAF) is one of the most disturbing loads in the power system as it is highly time‐varying and nonlinear. In this paper, new models based on the instantaneous EAF voltage and current, recorded from EAFs in Mobarakeh steel company in Isfahan/Iran are proposed. The focus of this paper is on developing efficient models based on the Schwarz model where three modified types are proposed. The original Schwarz model has four constant parameters. Unlike the original Schwarz model which uses invariant parameters, the time‐varying nature of the arc's parameters is considered in the proposed models. The first modified model has two constant model orders and two time‐varying coefficients. Additionally, to further enhance the model's accuracy, in the second modified model, six parameters include three constant model orders, and three time‐varying coefficients exist. The third model uses all the original model's parameters as time‐series parameters. The parameters of the time‐varying model are derived using autoregressive moving average (ARMA) models. The accuracy of the proposed model is evaluated by calculating the active power, harmonics, instantaneous flicker, and short‐term flicker. Finally, three MATLAB codes are provided to generate the model parameters time series. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study deals with a new approach to tackle the challenges encountered in the filters-based reactive power calculation techniques utilized in the control system of static VAr compensators. In this approach, step and time-varying responses are improved by a combination of differential and filter-based methods. Then, optimum values of the main parameters of the low-pass and band-stop filters are determined considering three criteria: accuracy, speed, and capability for following the time-varying loads. To assess the performance of the proposed method, a new objective function is introduced, calculated for two sets of signals, captured from a real field in Mobarakeh Steel Company in Isfahan/Iran. Then, the proposed and the other reactive power calculation methods are assessed in practice and simulation. Also, the algorithm is implemented using a TMDSCNCD28335 as the processor to assess the real-time feasibility of the method. To do so, the reactive power variation of an electrical arc furnace is emulated in a prototype test bench and the algorithm is run in real-time by the processor during the system operation. [ABSTRACT FROM AUTHOR]

• Two improved types of accurate models based on the Schavemaker model are developed. • Unlike the original Schavemaker model which uses invariant parameters, the time-varying nature of the arc's parameters is considered in the proposed models. • The first improved model has time-varying coefficients. • In the second improved model, a new term has been added to the schavemaker model that includes time-varying coefficients. • A large number of the actual data are used. Electric arc furnace (EAF) is more and more applied in large industrial systems and represent one of the major sources of perturbations for the power system because it is highly non-linear and time-varying. New models are suggested in this research based on instantaneous EAF voltage and current measurements taken from EAFs at the Mobarakeh steel mill in Isfahan, Iran. This paper aims to develop two improved types of accurate models based on the Schavemaker model. The original Schavemaker model has three constant parameters. Unlike the original Schavemaker model which uses invariant parameters, the time-varying nature of the arc's parameters is considered in the proposed models. The first improved model has time-varying parameters. Additionally, to further enhance the model's accuracy, in the second improved model, a term has been added to the schavemaker model that includes time-varying parameters. Compared to the original Schavemaker model, all of the developed Schavemaker models are more precise. Finally, auto-regressive moving average (ARMA) models are used to attain the time variation characteristic of the parameters. [ABSTRACT FROM AUTHOR]