A New Field-Data-Based EAF Model for Power Quality Studies

Göl, Murat; Salor, Özgül; Alboyacı, Bora; Mutluer, B.; Çadırcı, I.; Ermiş, M.

doi:10.1109/tia.2010.2046280

Cited by 38 publications

(15 citation statements)

References 4 publications

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“…Given the limitations of the above-mentioned mechanism modeling methods, some data-driven modeling methods for EAF harmonic models were proposed. For example, the EAF harmonic model based on field measurements of voltages and currents was proposed [13,14]. However, these methods ignore the interactions between harmonic currents and harmonic voltages and would result in a calculation error.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Compartmental Modeling Method for Harmonic Analysis—A Study of the Electric Arc Furnace

Shao

Chen

2019

Energies

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The electric arc furnace (EAF) contributes to almost one-third of the global iron and steel industry, and its harmonic pollution has drawn attention. An accurate EAF harmonic model is essential to evaluate the harmonic pollution of EAF. In this paper, a data-driven compartmental modeling method (DCMM) is proposed for the multi-mode EAF harmonic model. The proposed DCMM considers the coupling relationship among different frequencies of harmonics to enhance the modeling accuracy, meanwhile, the dimensions of the harmonic dataset are reduced to improve computational efficiency. Furthermore, the proposed DCMM is applicable to establish a multi-mode EAF harmonic model by dividing the multi-mode EAF harmonic dataset into several clusters corresponding to the different modes of the EAF smelting process. The performance evaluation results show that the proposed DCMM is adaptive in terms of establishing the multi-mode model, even if the data volumes, number of clusters, and sample distribution change significantly. Finally, a case study of EAF harmonic data is conducted to establish a multi-mode EAF harmonic model, showing that the proposed DCMM is effective and accurate in EAF modeling.

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Section: Introductionmentioning

confidence: 99%

Data-Driven Compartmental Modeling Method for Harmonic Analysis—A Study of the Electric Arc Furnace

Shao

Chen

2019

Energies

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“…Therefore, the EAF shows stochastic behaviors at each charge period because of the mentioned variations. 8,9 In this regard, numerous models have been developed for the EAF. [10][11][12][13][14][15][16][17][18] Some of these models have been developed using the voltage-current characteristics (VIC).…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the transformer tap is adjusted by the operator to control the power, and the impedance of the flexible cable is subject to change because of the electrode movements during the EAF operation. Therefore, the EAF shows stochastic behaviors at each charge period because of the mentioned variations . In this regard, numerous models have been developed for the EAF …”

Section: Introductionmentioning

confidence: 99%

Parameters estimation of electric arc furnace based on an analytical solution of power balance equation

Alkaran

Vatani

Sanjari

et al. 2016

Int. Trans. Electr. Energ. Syst.

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Summary A closed‐form solution for power balance equation of electric arc furnace (EAF) is proposed in this paper based on field measurements of the instantaneous furnace voltage and current. The method is developed based on an analytical solution of power balance equation in general case. The closed‐form solution is dependent on the EAF parameters, which should be found by parameter identification procedure carrying out by minimization of an appropriate objective function. The minimization is performed by means of a calculus‐based optimization method, namely, interior‐point method. The validity of the proposed method is verified by comparing its results with those of the field measurements. The results show quite satisfactory correlation between the proposed method and the actual EAF operation.

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“…Therefore, it is essential to suggest a suitable model for EAFs that can create the expected effects in a power system. So far, numerous models of EAF have been presented by different researchers [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Electric arc furnace power quality improvement by applying a new digital and predicted-based TSC control

Esfahani¹,

Vahidi

2016

Turk J Elec Eng & Comp Sci

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Static VAR compensators (SVC) can improve some of the power quality (PQ) indices such as voltage flicker, unbalances, and power factors in power systems if properly controlled. Different nonlinear and time-varying loads generate these parameters. One of the great nonlinear loads is the electric arc furnace (EAF), which causes waveform distortions, voltage unbalances, and fluctuations. In this paper, a new digital and prediction-based control for thyristor switched capacitors (TSCs) was proposed to compensate an actual steel industrial plant. The digital control was based on generating adequate synchronous pulses, calculating required suitable susceptance, and measuring correct reactive power. The proposed TSC improved the PQ by means of the feedback from voltage and power factor. A predictive method based on time series and recursive least square with dynamic learning factor was then applied to estimate EAF reactive power in the future so that the TSC performance was enhanced by reducing the natural time delay. A band-pass harmonic filter was designed to compensate the load current harmonics and to protect the capacitor banks in the TSC.Finally, the suggested TSC was implemented in a steel industrial plant as an actual power system with 2 EAFs. The modeling and experimental results indicate the effectiveness of the proposed TSC.

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A New Field-Data-Based EAF Model for Power Quality Studies

Cited by 38 publications

References 4 publications

Data-Driven Compartmental Modeling Method for Harmonic Analysis—A Study of the Electric Arc Furnace

Data-Driven Compartmental Modeling Method for Harmonic Analysis—A Study of the Electric Arc Furnace

Parameters estimation of electric arc furnace based on an analytical solution of power balance equation

Electric arc furnace power quality improvement by applying a new digital and predicted-based TSC control

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