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An accurate model of electric arc furnaces (EAFs) is required to analyse their impact on the system's power quality. One of the well‐known approaches to model EAF is using the power balance equation. This model has two terms, each one has a coefficient named the model parameter. Also, both terms are powered to values, which are called model orders. So, the model includes two model parameters and two model orders. Model orders highly affect the modelling precision. The optimum model orders have not been obtained yet in previous studies. Here, based on many actual records from EAFs, the best model orders for refining, melting, and scrapping stages are attained. Unlike the original power balance equation which has constant model parameters, the first proposed model uses the attained optimal model orders with the time‐varying model parameters. In the second proposed model, the model orders are also considered time‐varying. Model parameters, which are updated every 10 ms, are obtained using autoregressive moving average (ARMA) models. The correctness of the models is assessed by calculating some important electric quantities using the actual data and the proposed models. Finally, the time‐varying parameters are generated using two MATLAB codes. [ABSTRACT FROM AUTHOR]

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]

• Four new indices are defined to quantize branches responsibility to sag/swell and flicker. • The indices are calculated using a cumulative approach in real-time, so the decision can be made upon a long-time duration. • The indices are based on the RMS values of the voltage and current which can be communicated every cycle. • The calculation algorithms are implemented in a recursive way to minimize the computational burden. The purpose of this study is to find simple cost-efficient algorithms for real-time quantizing the responsibility for power quality issues in every branch in an industrial network. The study is focused on voltage sag/swell and flicker which are caused by the time variation characteristics of loads. Here by using the RMS values of the voltage and current, four indices are defined. Cumulative-recursive equations are used to reduce the computation load and to be able to evaluate the power quality problems in real-time. Two indices quantize the loads' responsibility in sag/swell events. The duration of the sag/swell events is considered in the second index. Two indices are proposed for flicker. The first flicker index is based on the FFT of the flicker powers in the individual flicker frequencies. The second flicker index is based on the FFT of the calculated time-varying load admittance corresponding to flicker range frequencies. The load variation coherency of the different branches affects the first flicker index while it has no impact on the second one. The performance of the proposed indices is tested using simulation data, actual records from electric arc furnace and a wind farm, and a laboratory test. Results reveal that the proposed indices efficiently quantize branches' responsibility in the sag/swell and flicker events. The sag/swell indices increase after every event caused by the responsible branch in proportion with the event depth and duration. The flicker indices increase in proportion to the flicker powers according to IEC868 flicker sensitivity coefficients. [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]

Electric arc furnace (EAF) is one of the largest non‐linear loads in power systems. It is highly time‐varying which leads to low‐frequency voltage fluctuations in the system, called flicker. Static VAr compensator (SVC) is always used in EAF plants to compensate the reactive power and reduce voltage fluctuations. The reactive power calculation unit is one of the most important units in SVC control system. Since SVC can only compensate the fundamental component, the calculated reactive power should not be sensitive to other harmonics. On the other hand, since the reactive power changes every half cycle, its calculation should be fast enough to track the changes. Hence, a calculation method with minimum delay and lowest harmonic sensitivity should be utilised to achieve an effective compensation. Among different already proposed methods for calculation of reactive power, differential method has the lowest delay. However, it is very sensitive to harmonics. In this study, Kalman filter is used to extract the fundamental components of voltage and current with a little delay and then they are used as inputs for the differential method. The proposed method is evaluated using some simulation signals and practical records from several EAFs in Mobarekeh steel company in Esfahan – Iran. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) is one of the largest loads in the power systems. Unfortunately, it is highly non‐linear and time varying which causes power quality problems such as harmonics and flicker. Therefore, having an accurate EAF model is necessary. Cassie model is one of the most utilised EAF models in the related fields. However, actual data from electrical system of Mobarakeh Steel Company in Isfahan/Iran show that this model is unable to take into account some important quantities such as the active power and harmonics. Hence, as the first step in this study, different Cassie–Mayr model variants (include the Cassie model) are investigated and the best variant is attained. A novel procedure using large number of recorded actual data is utilised for the models assessment. In the second step, two generalised types of the original Cassie–Mayr model are proposed. Both the generalised types are more accurate than the best‐selected Cassie–Mayr variant. All the proposed models have time‐varying parameters. Their time‐varying nature is studied and by analysing the time series, the proper auto regressive moving average models are attained for every parameter. [ABSTRACT FROM AUTHOR]

In this study main reactive power calculation methods are evaluated and compared. Furthermore, a novel simple method that can be used for calculation of reactive power in electric arc furnace (EAF) plants is proposed. The focus here is on their application in the control system of static VAr compensators (SVCs). SVC can compensate only the fundamental harmonic component. So the reactive power signal used in the control system should be sensitive only to the main harmonic component. In addition, the reactive power calculation should be fast enough that SVC can follow the quick changes of the load to mitigate the flicker efficiently. To compare various reactive power calculation methods and to evaluate the proposed method, the simulated known loads are used beside huge amount of practical data recorded in Mobarakeh Steel Company in Isfahan/Iran. Results show the proposed method has the best performance for SVC control system. [ABSTRACT FROM AUTHOR]

In electrical arc furnaces (EAFs), an unstable arc leads to unfavorable operation of the EAF, which can be rectified by using series reactors. Installation of the series inductor affects some electrical parameters of the EAF, such as arc stability, power factor, arc length, and the EAF efficiency. Furthermore, it reduces the effective transferred power to the EAF. To achieve desired transferred power after installation of the series reactors, the secondary voltage of the EAF transformer should be increased. However, after any tap changing of the EAF transformer, arc stability and other relevant parameters are affected. So the impact on the EAF electrical magnitudes caused by changes in the series reactor and in the EAF transformer tap should be simultaneously studied. This research deals with a new method for optimal setting of the series reactor and EAF transformer tap to achieve the EAF best performance. Using a nonlinear model for the EAF, its electrical characteristics, at nominal transformer current and for all of the possible transformer and reactor taps, are calculated and the results are tabulated. Using these tables, the optimal setpoint for transformer and series reactor taps is determined in different conditions. Finally, the method is investigated from an economic point of view. [ABSTRACT FROM AUTHOR]

The time varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations, which produces the effect known as flicker. Employing reactive power compensation devices such as static VAr compensator (SVC) is one of the main approaches to mitigate this phenomenon. By utilising prediction methods to forecast EAFs reactive power consumption for a half‐cycle ahead, performance of SVC can be enhanced substantially. This study proposes a rolling Grey model and a Grey–Markov method to predict the actual reactive power of Mobarakeh Steel Company, Isfahan/Iran. To investigate the efficiency of the proposed methods the results are compared with the results of EAFs reactive power compensation when no prediction method is employed. Furthermore, autoregressive moving average (ARMA) models with updating coefficients, which are studied in the literature are used to predict EAF reactive power. Various methods for updating ARMA coefficients including normalised least mean square, recursive least square method and an online genetic algorithm are used. By comparing the indices which are defined using the concept of flicker frequency and power spectral density, the superiority of Grey–Markov and rolling Grey model over the aforementioned prediction methods is investigated. [ABSTRACT FROM AUTHOR]

• A hybrid time-frequency model for EAF. • A four-winding model for the EAF's transformer. • Modeling of the tap changer mechanism. • An efficient differential protection algorithm. This paper deals with the modeling of EAF feeding system taking into account the tap transition for assessment of a suggested scheme of differential protection. There are several challenges in the implementation of the differential protection in the EAF transformer which reveal the importance of the system modeling. Large current in the secondary side of the transformer, similarity of normal and fault conditions, and frequent tap variation in the transformer during the melting procedure are the most serious concerns. Considering the mechanism of the tap changers, the new tap setting is readjusted in the algorithm to prevent mal-operation of the protection. These challenges can be rectified by suitable modeling of EAF feeding system and an efficient differential protection scheme. To this end, the EAF as an electrical load, the EAFs' transformer, and the mechanism of the tap changing are properly modeled in this work. The proposed model of the EAF is based on real recorded data from EAFs used in a steel company, to fully simulate the nonlinear and time-variant characteristics of this electrical load. The proposed models of the EAFs' transformer and tap changer enable us to simulate different tap variations and internal faults in the system. The performance of the suggested differential protection algorithm is evaluated using plenty of simulations in different conditions of the system. [ABSTRACT FROM AUTHOR]

Summary: Delays in reactive power measurement and thyristor ignition limit SVC performance in flicker mitigation of electric arc furnaces (EAFs). To overcome this limitation, prediction methods can be employed to forecast the EAF reactive power for half cycle ahead, used as a reference signal of the SVC. The utilized prediction methods in this area can be divided into linear and black‐box approaches. However, the linear approaches cannot extract the nonlinear governed relations, and using a black‐box model is not efficient for linear relations. A Gray‐ANN method is proposed here to take the advantages of the two mentioned approaches. Results from indices based on actual records of Mobarakeh Steel Company confirm superiorities of the proposed method over previously utilized prediction methods in this application. Furthermore, SVC's flicker mitigation ability is evaluated using the actual data. The results confirm the significant reduction of flicker compared with the regular system. [ABSTRACT FROM AUTHOR]