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A Probabilistic Three-Phase Time Domain Electric Arc Furnace Model based on analytical method | ||
| AUT Journal of Electrical Engineering | ||
| مقاله 1، دوره 47، شماره 1، تیر 2015، صفحه 1-10 اصل مقاله (683.02 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/eej.2015.515 | ||
| نویسندگان | ||
| M. Torabian Esfahani1؛ B. Vahidi* 2 | ||
| 1PhD. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| 2Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| چکیده | ||
| An electric arc furnace (EAF) is known as nonlinear and time variant load that causes power quality (PQ) problems such as, current, voltage and current harmonics, voltage flicker, frequency changes in power system. One of the most important problems to study the EAF behavior is the choice of a suitable model for this load. Hence, in this paper, a probabilistic three-phase model is proposed based on recovered hidden Markov model (RHMM) in time domain. To recover the HMM , the coupling factor is proposed. This factor estimates the past observations and considers the effects of all observations in different states. Regarding to the intense fluctuations of various parameters of EAF, this factor can improve the EAF model in different operating stages. This subject causes that the proposed model is closed to the actual model. To train the RHMM, actual measured samples are used. Likewise, different parameters of EAF' power system as, flexible cables, electrode, busbar are exactly considering to achieve an accurate model. Comparing the results of experimental and proposed model indicates the accuracy of the proposed model. | ||
| کلیدواژه‌ها | ||
| Recovered Hidden Markov Model؛ Electric Arc Furnace؛ Voltage Flicker؛ Power Quality parameters | ||
| عنوان مقاله [English] | ||
| A Probabilistic Three-Phase Time Domain Electric Arc Furnace Model based on analytical method | ||
| نویسندگان [English] | ||
| M. Torabian Esfahani1؛ B Vahidi2 | ||
| 1PhD. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| 2Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| چکیده [English] | ||
| An electric arc furnace (EAF) is known as nonlinear and time variant load that causes power quality (PQ) problems such as, current, voltage and current harmonics, voltage flicker, frequency changes in power system. One of the most important problems to study the EAF behavior is the choice of a suitable model for this load. Hence, in this paper, a probabilistic three-phase model is proposed based on recovered hidden Markov model (RHMM) in time domain. To recover the HMM , the coupling factor is proposed. This factor estimates the past observations and considers the effects of all observations in different states. Regarding to the intense fluctuations of various parameters of EAF, this factor can improve the EAF model in different operating stages. This subject causes that the proposed model is closed to the actual model. To train the RHMM, actual measured samples are used. Likewise, different parameters of EAF' power system as, flexible cables, electrode, busbar are exactly considering to achieve an accurate model. Comparing the results of experimental and proposed model indicates the accuracy of the proposed model. | ||
| کلیدواژه‌ها [English] | ||
| Recovered Hidden Markov Model, Electric Arc Furnace, Voltage Flicker, Power Quality parameters | ||
| مراجع | ||
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[1] M. Alonso, M. Donsion, “An Improved Time Domain Arc Furnace Model for Harmonic Analysis”, IEEE Trans. Power Del., vol. 19, No. 1, pp.367- 373, 2004. [2] S. G. Deaconu, N. Popa, A. I. Toma, M. Topor, “Modeling and Experimental Analysis for Modernization of 100-t EAF”, IEEE Trans. on Ind. App. vol. 46, No. 6, pp.2259- 2266, 2010. [3] S. M. Mousavi Agah, S. H. Hosseinian, H. Askarian Abyaneh, N. Moaddabi, “Parameter Identification of Arc Furnace Based on Stochastic Nature of Arc Length Using Two-Step Optimization Technique”, IEEE Trans. on Power Del., vol. 25, No. 4, pp. 2859- 2867, 2010. [4] I. Vervenne, K. Van Reusel, R. Belmans, “Electric Arc Furnace Modeling from a “Power Quality” Point of View”, Electrical Power Quality Utilization IEEE Int. Conf., pp. 1-6, 2007. [5] W. Ting, S. Wennan, Z. Yao, “A New Frequency Domain Method for the Harmonic Analysis of Power Systems with Arc Furnace”, Advances in Power System Control, Operation and Management IEEE Int. Conf., pp. 552- 555, 1997. [6] L. F. Beites, J. G. Mayordomo, A. Hernandes, R. Asensi, “Harmonics, Interharmonic, Unbalances of Arc Furnaces: a New Frequency Domain approach”, IEEE Trans. Power Del., vol. 16, No. 4 pp. 661- 668, 2001. [7] L. F. Pak, V. Dinavahi, G. Chang, M. Steurer, P. F. Ribeiro, “Real-Time Digital Time- Varying Harmonic Modeling and Simulation Techniques”, IEEE Trans. Power Del., vol. 22, No. 2 pp. 1218- 1227, 2007. [8] M. Torabian Esfahani, B. Vahidi, “A New Stochastic Model of Electric Arc Furnace Based on Hidden Markov Model: A Study of Its Effects on Power System”, IEEE Trans. Power Del., vol. 27, No. 4 pp. 1893- 1901, 2012. [9] D. Grabowski, J. Walczak, ”Deterministic model of electric arc furnace – a closed form solution”, COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering vol. 32 No. 4, pp. 1428- 1436, 2013. [10] Y. Hsu, K. H. Chen, P. Huang, Ch. Lu, “Electric Arc Furnace Voltage Flicker Analysis and Prediction” IEEE Trans. on Ins. and Meas., vol. 60, No. 10, pp.3360- 3369, 2011. [11] A. M. Gonzalez, A. M. S. Roque, J. Garcia-Gonzalez, “Modeling and Forecasting Electricity Prices with Input/Output Hidden Markov Models”, IEEE Trans. Power System, vol. 20, No. 1 pp. 13– 24, 2005. [12] E. Altıntas, O. Salor, I. Cadirci, M. Ermis, “A New Flicker Contribution Tracing Method Based on Individual Reactive Current Components of Multiple EAFs at PCC”, IEEE Trans. Ind. Appl., vol. 46, No. 5, pp.1746- 1754, 2010. [13] Testing and Measurement Techniques– Flickermeter, Functional and Design Specifications, IEC Standard, IEC 61000-4-15. | ||
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