Comparison of a Dynamic Model of Electric Arc Furnace with Actual Operation Data for Voltage Flicker Analysis in Electrical Power Network

Yıl 2023, Cilt: 38 Sayı: 3, 725 - 738, 18.10.2023

Tahsin Köroğlu

https://doi.org/10.21605/cukurovaumfd.1377734

Öz

Electric arc furnaces (EAFs) used in the iron and steel manufacturing industry for melting and refining scrap metals are one of the most disturbing loads that exhibit unbalanced and highly nonlinear characteristics. Serious voltage fluctuations occur in the power system as a result of the rapid change in the current drawn from the grid by the EAF. Voltage fluctuations lead to a power quality problem known as flicker, which is defined as observable changes in light sources that affect the production environment, cause eye fatigue in personnel, and lower the work concentration levels. To investigate the voltage flicker problem, an accurate mathematical model describing the behavior of the EAF load is required. In this study, a dynamic EAF model that can be adjusted to different operating conditions has been developed in the time domain. The electric arc voltage has been modeled as an externally controllable voltage source. The instantaneous arc voltage has been expressed as a function of the arc length independent of the current. The arc resistance, which varies with time and is nonlinear, has also been calculated with differential equations using the instantaneous arc voltage value. To measure the short-term flicker severity index caused by the EAF in the power system, a flicker meter in compliance with the International Electrotechnical Commission (IEC) 61000-4-15 standard has been designed. The current-voltage characteristics of the EAF, its effect on the power system, and the flicker severity occurring at the point of common coupling (PCC) have been analyzed with simulation studies using the PSCAD/EMTDC software. Besides, the simulation results of the dynamic model of the EAF have been compared with the results obtained from the model based on the measured field data.

Anahtar Kelimeler

Electric arc furnace, Flicker, Power quality, Flickermeter

Elektrik Güç Şebekesi’nde Gerilim Titreşim Analizi için Elektrik Ark Ocağının Dinamik Modeli ile Gerçek Çalışma Verilerinin Karşılaştırılması

Öz

Demir-çelik imalat sanayinde hurda metallerin ergitilmesi ve rafine edilmesi için kullanılan elektrik ark ocakları (EAF'leri), dengesiz ve oldukça doğrusal olmayan özellikler sergileyen en rahatsız edici yüklerden biridir. EAF'nin şebekeden çektiği akımın hızla değişmesi sonucu güç sisteminde ciddi gerilim dalgalanmaları meydana gelir. Gerilim dalgalanmaları, ışık kaynaklarında üretim ortamını etkileyen gözlemlenebilir değişiklikler olarak tanımlanan, personelde göz yorgunluğuna ve iş konsantrasyon düzeylerinin düşmesine neden olan ve kırpışma olarak bilinen bir güç kalitesi sorununa yol açar. Gerilim kırpışma problemini araştırmak için, EAF yükünün davranışını açıklayan doğru bir matematiksel modele ihtiyaç vardır. Bu çalışmada, zaman domeninde farklı çalışma koşullarına göre ayarlanabilen dinamik bir EAF modeli geliştirilmiştir. Elektrik ark gerilimi, harici olarak kontrol edilebilen bir gerilim kaynağı olarak modellenmiştir. Anlık ark gerilimi, akımdan bağımsız olarak ark uzunluğunun bir fonksiyonu olarak ifade edilmiştir. Zamanla değişen ve doğrusal olmayan ark direnci de anlık ark gerilimi değeri kullanılarak diferansiyel denklemlerle hesaplanmıştır. Güç sisteminde EAF'nin neden olduğu kısa süreli kırpışma şiddeti indeksini ölçmek için Uluslararası Elektroteknik Komisyonu (IEC) 61000-4-15 standardına uygun bir kırpışma ölçer tasarlanmıştır. EAF'nin akım-gerilim karakteristiği, güç sistemine etkisi ve ortak bağlantı noktasında (PCC) oluşan kırpışma şiddeti, PSCAD/EMTDC yazılımı kullanılarak simülasyon çalışmaları ile analiz edilmiştir. Ayrıca, EAF'nin dinamik modelinin simülasyon sonuçları, ölçülen saha verilerine dayalı modelden elde edilen sonuçlarla karşılaştırılmıştır.

Anahtar Kelimeler

Elektrik ark ocağı, Kırpışma, Güç kalitesi, Kırpışma ölçer

Kaynakça

• 1. Alves, M.F., Peixoto, Z.M.A., Garcia, C.P., Gomes, D.G., 2010. An Integrated Model for the Study of Flicker Compensation in Electrical Networks. Electric Power Systems Research, 80(10), 1299-1305.
• 2. Balouji, E., Bäckström, K., McKelvey, T., Salor, Ö., 2020. Deep-Learning-Based Harmonics and Interharmonics Predetection Designed for Compensating Significantly Time-Varying EAF Currents. IEEE Transactions on Industry Applications, 56(3), 3250-3260.
• 3. Göl, M., Salor, Ö., Alboyacı, B., Mutluer, B., Çadırcı, I., Ermis, M., 2010. A New Field-Data-Based EAF Model for Power Quality Studies. IEEE Transactions on Industry Applications, 46(3), 1230-1242.
• 4. Thales, A.C.M., Virna, C.O., 2022. Survey on the Electric Arc Furnace and Ladle Furnace Electric System. Ironmaking & Steelmaking, 49(10), 976-994.
• 5. Altıntaş, E., Salor, Ö., Çadırcı, I., Ermis, M., 2010. A New Flicker Contribution Tracing Method Based on Individual Reactive Current Components of Multiple EAFs at PCC. IEEE Transactions on Industry Applications, 46(5), 1746-1754.
• 6. Logoglu, E.U., Salor, O., Ermis, M., 2019. Real-Time Detection of Interharmonics and Harmonics of AC Electric Arc Furnaces on GPU Framework. IEEE Transactions on Industry Applications, 55(6), 6613-6623.
• 7. Hay, T., Visuri, V.-V., Aula, M., Echterhof, T., 2021. A Review of Mathematical Process Models for the Electric Arc Furnace Process. Steel Research International, 92(3), 2000395.
• 8. Seker, M., Memmedov, A., Huseyinov, R. Kockanat, S., 2017. Power Quality Measurement and Analysis in Electric Arc Furnace for Turkish Electricity Transmission System. Elektronika Ir Elektrotechnika, 23(6), 25-33.
• 9. Göl, M., 2009. A New Field-Data Based EAF Model Applied to Power Quality Studies. M.Sc. Thesis, Middle East Technical University, Institute of Natural and Applied Sciences, Department of Electrical and Electronics Engineering, Ankara, 88.
• 10. Mayordomo, J.G., Beites, L.F., Asensi, R. Izzeddine, M., Zabala, L., Amantegui, J., 1997. A New Frequency Domain Arc Furnace Model for Iterative Harmonic Analysis. IEEE Transactions on Power Delivery, 12(4), 1771-1778.
• 11. Beites, L.F, Mayordomo, J.G., Hernandes, A., Asensi, R., 2001. Harmonics, Inter Harmonic, Unbalances of Arc Furnaces: A New Frequency Domain Approach. IEEE Transactions on Power Delivery, 16(4), 661-668.
• 12. Hooshmand, R., Banejad, M., Esfahani, M.T., 2008. A New Time Domain Model for Electric Arc Furnace. Journal of Electrical Engineering, 59(4), 195-202.
• 13. Wang, F., Jin, Z., Zhu, Z., Wang, X., 2005. Application of Extended Kalman Filter to the Modelling of Electric Arc Furnace for Power Quality Issues. International Conference on Neural Networks and Brain, Beijing, 991-996.
• 14. Pak, L.-F., Dinavahi, V., 2007. Real-Time Digital Time-Varying Harmonic Modelling and Simulation Techniques. IEEE Transactions on Power Delivery, 22(2), 1218-1227.
• 15. Bellido, R.C., Gomez, T., 1997. Identifcation and Modelling of a Three Phase Arc Furnace for Voltage Disturbance Simulation. IEEE Transactions on Power Delivery, 12(4), 1812-1817.
• 16. Mokhtari, H., Hejri, M., 2002. A New Three Phase Time-Domain Model for Electric Arc Furnaces Using MATLAB. IEEE/PES Transmission and Distribution Conference and Exhibition, Yokohama, 2078-2083.
• 17. Golestani, S., Samet, H., 2016. Generalised Cassie–Mayr Electric Arc Furnace Models. IET Generation, Transmission & Distribution, 10(13), 3364-3373.
• 18. Plata, E.A.C., Farfan, A.J.U., Marin, O.J.S., 2015. Electric Arc Furnace Model in Distribution Systems. IEEE Transactions on Industry Applications, 51(5), 4313-4320.
• 19. Teklic, A.T., Filipovic-Grcic, B., Pavic, I., 2017. Modelling of Three-Phase Electric Arc Furnace for Estimation of Voltage Flicker in Power Transmission Network. Electric Power Systems Research, 146, 218-227.
• 20. Ting, W., Wennam, S. Yao, Z., 1997. A New Frequency Domain for the Harmonic Analysis of Power System with Arc Furnace. Fourth International Conference on Advances in Power System Control, Operation and Management, (APSCOM), Hong Kong, 552-555.
• 21. Zheng, T., Makram, E.B., 2000. An Adaptive Arc Furnace Model. IEEE Transactions on Power Delivery, 15(3), 931-939.
• 22. Esfahani, M.T., Vahidi, B., 2012. New Stochastic Model of Electric Arc Furnace Based on Hidden Markov Model: A Study of Its Effects on the Power System. IEEE Transactions on Power Delivery, 27(4), 1893-1901.
• 23. Lozynskyy, A., Kozyra, J., Łukasik, Z., Kuśmińska-Fijałkowska, A., Kutsyk, A., Paranchuk, Y., Kasha, L., 2022. A Mathematical Model of Electrical Arc Furnaces for Analysis of Electrical Mode Parameters and Synthesis of Controlling Influences. Energies, 15(5), 1623, 1-19.
• 24. Lee, C., Kim, H., Lee, E.-J., Baek, S.-T., Shim, J.W., 2021. Measurement-Based Electric Arc Furnace Model Using Ellipse Formula. IEEE Access, 9, 155609-155621.
• 25. Brusa, E.G.M., Morsut, S., 2015. Design and Structural Optimization of the Electric Arc Furnace Through a Mechatronic-Integrated Modeling Activity. IEEE/ASME Transactions on Mechatronics, 20(3), 1099-1107.
• 26. Chen, C-I., Chen, Y-C., 2015. A Neural-Network-Based Data-Driven Nonlinear Model on Time- and Frequency-Domain Voltage–Current Characterization for Power-Quality Study. IEEE Transactions on Power Delivery, 30(3), 1577-1584.
• 27. Segura, R.G., Castillo, J.V., Chavez, F.M., Gandara, O.L., Aguilar, J.O., 2017. Electric Arc Furnace Modeling with Artificial Neural Networks and Arc Length with Variable Voltage Gradient. Energies, 10, 1424, 1-11.
• 28. Chang, G.W., Shih, M-F., Chen, Y-Y., Liang, Y-J., 2014. A Hybrid Wavelet Transform and Neural Network-Based Approach for Modelling Dynamic Voltage-Current Characteristics of Electric Arc Furnace. IEEE Transactions on Power Delivery, 29(2), 815-824.
• 29. Klimas, M., Grabowski, D., 2023. Application of Long Short-Term Memory Neural Networks for Electric Arc Furnace Modeling. Applied Soft Computing, 145, 110574.
• 30. Babaei, Z., Samet, H., Jalil, M., 2023. An Innovative Approach Considering Active Power and Harmonics for Modeling the Electric Arc Furnace Along With Analyzing Time-Varying Coefficients Based on ARMA Models. International Journal of Electrical Power and Energy Systems, 153, 109377.
• 31. Illahi, F., El-Amin, I., Mukhtiar, M.U., 2018. The Application of Multiobjective Optimization Technique to the Estimation of Electric Arc Furnace Parameters. IEEE Transactions on Power Delivery, 33(4), 1727-1734.
• 32. Saboohi, Y., Fathi, A., Skrjanc, I., Logar, V., 2019. Optimization of the Electric Arc Furnace Process. IEEE Transactions on Industrial Electronics, 66(10), 8030-8039.
• 33. Nooshabadi, A.M.E., Sadeghi, S., Hashemi-Dezaki, H., 2022. Optimal Electric Arc Furnace Model’s Characteristics Using Genetic Algorithm and Particle Swarm Optimization and Comparison of Various Optimal Characteristics in DIgSILENT and EMTP-RV. International Transactions on Electrical Energy Systems, 9952315, 1-20.
• 34. Cassie, A.M., 1939. A New Theory of Rupture and Circuit Severity. CIGRÉ Technical Report 102, Paris, 14.
• 35. Larsson, T., 1998. Voltage Source Converters for Mitigation of Flicker Caused by Arc Furnaces. Ph.D. Thesis, KTH, Superseded Departments, Electric Power Systems, 203.
• 36. IEC Standard 61000-4-15:2010. Electromagnetic Compatibility (EMC) - Part 4-15: Testing and Measurement Techniques - Flickermeter - Functional and Design Specifications, 83.
• 37. Hooshyar, A., El-Saadany, E.F., 2013. Development of a Flickermeter to Measure Non-Incandescent Lamps Flicker. IEEE Transactions on Power Delivery, 28(4), 2103-2115.
• 38. Wiczynski, G., 2012. Inaccuracy of Short-Term Light Flicker Pst Indicator Measuring with a Flickermeter. IEEE Transactions on Power Delivery, 27(2), 842-848.
• 39. Bertola, A., Lazaroiu, G.C., Roscia, M., Zaninelli, D., 2004. A Matlab-Simulink Flickermeter Model for Power Quality Studies. 11th International Conference on Harmonics and Quality of Power, IEEE, Lake Placid, NY, USA, 734-738.
• 40. Onal, Y., Gerek, O.N., Ece, D.G., 2016. Empirical Mode Decomposition Application for Short-Term Flicker Severity. Turkish Journal of Electrical Engineering & Computer Sciences, 24, 499-509.
• 41. Kołek, K., Firlit, A., Piatek, K., Chmielowiec, K., 2021. Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters. Energies, 14, 1589.