计及物理参数变化的交流电弧炉全过程模型

doi:10.19595/j.cnki.1000-6753.tces.250767

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Abstract The actual process operation of an electric arc furnace (EAF) shows a phased characteristic in terms of time sequence, but the electrical parameter fluctuations it causes run through the entire smelting process. Existing research mainly focuses on the power quality issues generated during the melting period, failing to effectively associate the multi-stage physical parameter changes with the electrical characteristic modeling throughout the entire process. The proposed AC EAF full-process model considering physical parameter changes in this paper mainly conducts physical process mechanism analysis from two aspects: the microscopic dynamic behavior inside the arc and the evolution law of the external morphology.
In terms of microscopic dynamic behavior, arc discharge fundamentally constitutes a gas ionization process where the gaseous medium serves as both energy carrier and charge transport medium, with variations in its composition and concentration significantly influencing discharge characteristics; during EAF smelting operations, oxygen injection and reductant addition processes continuously alter arc zone gas concentrations while adjusting molten steel composition, thereby affecting microscopic particle dynamics within the arc. Regarding macroscopic morphological evolution, the influence of self-magnetic compression forces from arc current on radial force equilibrium is considered through magnetic compression force balance equations to analyze current effects on arc radius, while further examining the influence mechanisms of arc external characteristics across operational phases and segmented operational behavior on the arc, ultimately establishing a functional relationship for full-length arc variation to reflect governing mechanisms of external arc characteristics.
The gas concentration needs to be detected using an infrared gas analyzer. However, the intense dynamic characteristics of the smelting process have led to the fact that the length of the electric arc has not yet been determined in a definite form. Therefore, based on the concentration relationships of N₂, O₂, CO₂, and CO discovered by the infrared gas analyzer and combined with the oxidation-reduction reaction laws within the EAF, this paper constructs a gas concentration change curve through iterative time periods to characterize the three-stage decarburization process. Given the positive correlation between arc length and arc voltage, this paper analyzes the electrode operation methods and dynamic characteristics of the molten pool in different smelting stages to reveal the internal mechanism of arc length changes, and then modulates the range of arc length changes based on the fluctuation of arc voltage. The mechanism-data combination method is used to determine the gas concentration change curve and the arc length change function for each period during the EAF smelting process.
This model was verified using the actual measurement data of a 55-ton EAF to test its accuracy and applicability throughout the entire smelting process. The results show that by combining the temporal changes in gas concentration and the phased evolution of arc length during each smelting stage, the actual operating state of the AC arc furnace in each stage can be described more precisely. Further, by verifying the influence of various gas concentrations that may occur during the oxidation and reduction periods on the electrical energy quality of the arc furnace, it was found that the gas concentration at specific time periods can effectively characterize the electrical energy quality characteristics of that period. This proves that considering the combined effects of gas concentration and arc length changes on arc characteristics is closer to the physical reality of arc furnace smelting.

Key words： Full-process AC electric arc furnace gas concentration inside the furnace process operations arc length variation function load model

Received: 09 May 2025

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TM748.41

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	Zhang Yi
	Liu Shiqi
	Xu Yuncong
	Sun Shouquan
	Ou Jieyu

Cite this article:

Zhang Yi,Liu Shiqi,Xu Yuncong等. A Full-Process Model of AC Electric Arc Furnace Considering Variations in Physical Parameters[J]. Transactions of China Electrotechnical Society, 2026, 41(9): 3115-3128.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.250767 OR https://dgjsxb.ces-transaction.com/EN/Y2026/V41/I9/3115

[1] 张逸, 孙守铨, 廖思阳, 等. 基于机理数据混合驱动的钢铁企业生产短流程功率模型[J]. 中国电机工程学报, 2025, 45(18): 7098-7110.
Zhang Yi, Sun Shouquan, Liao Siyang, et al.A mechanism-data hybrid-driven power model for short-process steel production[J]. Proceedings of the CSEE, 2025, 45(18): 7098-7110.
[2] 林才华, 张逸, 邵振国, 等. 用于低频非平稳间谐波研究的超高功率电弧炉模型[J]. 中国电力, 2020, 53(11): 1-8.
Lin Caihua, Zhang Yi, Shao Zhenguo, et al.An ultra-high-power electric arc furnace model for low-frequency non-stationary inter-harmonics studies[J]. Electric Power, 2020, 53(11): 1-8.
[3] 李戎, 李建文, 李永刚, 等. 结合特征根及模态分析法的逆变器多机并网系统谐波扰动响应分析[J]. 电工技术学报, 2024, 39(14): 4519-4534.
Li Rong, Li Jianwen, Li Yonggang, et al.Analysis of harmonic disturbance response of multi-inverter grid-connected system combining characteristic root and modal analysis method[J]. Transactions of China Electrotechnical Society, 2024, 39(14): 4519-4534.
[4] 赵旭东, 王艺博, 王博闻, 等. 考虑差异化工业高载能负荷灵活性挖掘的市场实施及调度模型研究综述[J]. 电工技术学报, 2025, 40(7): 2043-2062, 2161.
Zhao Xudong, Wang Yibo, Wang Bowen, et al.Review of market implementation and scheduling models considering the flexibility extraction of differentiated industrial energy-intensive loads[J]. Transactions of China Electrotechnical Society, 2025, 40(7): 2043-2062, 2161.
[5] 张逸, 李渴, 邵振国, 等. 基于数据关联性分析的工业用户电能质量特征识别[J]. 电工技术学报, 2023, 38(13): 3512-3526.
Zhang Yi, Li Ke, Shao Zhenguo, et al.Power quality characteristics identification of industrial users based on data correlation analysis[J]. Transactions of China Electrotechnical Society, 2023, 38(13): 3512-3526.
[6] 王晶, 束洪春, 林敏, 等. 用于动态电能质量分析的交流电弧炉的建模与仿真[J]. 电工技术学报, 2003, 18(3): 53-58.
Wang Jing, Shu Hongchun, Lin Min, et al.Modeling and simulation of AC arc furnace for dynamic power quality studies[J]. Transactions of China Electrotechnical Society, 2003, 18(3): 53-58.
[7] 王育飞, 潘艳霞, 姜建国. 基于MATLAB的交流电弧炉随机模型与仿真[J]. 高电压技术, 2008, 34(5): 973-977.
Wang Yufei, Pan Yanxia, Jiang Jianguo.Stochastic model of AC electric arc furnace based on MATLAB[J]. High Voltage Engineering, 2008, 34(5): 973-977.
[8] 王琰, 毛志忠, 李妍, 等. 用于电压波动研究的交流电弧炉电弧模型[J]. 电网技术, 2010, 34(1): 36-40.
Wang Yan, Mao Zhizhong, Li Yan, et al.An electric arc model of AC electric arc furnace for research on voltage fluctuation[J]. Power System Technology, 2010, 34(1): 36-40.
[9] Ozgun O, Abur A.Flicker study using a novel arc furnace model[J]. IEEE Transactions on Power Delivery, 2002, 17(4): 1158-1163.
[10] Carpinelli G, Iacovone F, Russo A, et al.Chaos-based modeling of DC arc furnaces for power quality issues[J]. IEEE Transactions on Power Delivery, 2004, 19(4): 1869-1876.
[11] 王育飞, 姜建国. 用于电能质量研究的新型交流电弧炉混沌模型[J]. 中国电机工程学报, 2008, 28(10): 106-110.
Wang Yufei, Jiang Jianguo.A novel chaotic model of AC electric arc furnace for power quality study[J]. Proceedings of the CSEE, 2008, 28(10): 106-110.
[12] 徐瑞阳. 电弧炉电气系统建模及无功补偿方法研究[D]. 武汉: 华中科技大学, 2023.
Xu Ruiyang.Research on modeling and reactive power compensation for electric arc furnace[D]. Wuhan: Huazhong University of Science and Technology, 2023.
[13] 张逸, 林才华, 邵振国, 等. 基于电子连续性方程的新型交流电弧炉通用模型[J]. 中国电机工程学报, 2021, 41(21): 7425-7434.
Zhang Yi, Lin Caihua, Shao Zhenguo, et al.A novel general model of AC electric arc furnace based on electron continuity equation[J]. Proceedings of the CSEE, 2021, 41(21): 7425-7434.
[14] 徐云聪, 张逸, 林才华, 等. 基于电气特性-物理参数耦合的交流电弧炉模型[J]. 电工技术学报, 2024, 39(6): 1643-1655.
Xu Yuncong, Zhang Yi, Lin Caihua, et al.AC arc furnace model based on coupling of electrical and physical parameters[J]. Transactions of China Electro-technical Society, 2024, 39(6): 1643-1655.
[15] 田博涵, 陈兆平. 电弧炉炼钢动态模型的建立与评价[J]. 炼钢, 2024, 40(6): 23-27.
Tian Bohan, Chen Zhaoping.Establishment and evaluation of dynamic model for electric arc furnace steelmaking[J]. Steelmaking, 2024, 40(6): 23-27.
[16] 李青. 直流电弧炉电弧加热废钢熔化过程数学模型及其数值模拟[J]. 工业加热, 2005, 34(4): 5-11.
Li Qing.Mathematical model and numerical modeling of scrap melting process heating by electric arc in DC EAF[J]. Industrial Heating, 2005, 34(4): 5-11.
[17] 李青, 洪新, 郑少波. 炼钢电弧炉过程动态模型与仿真[J]. 钢铁研究, 2001, 29(1): 20-25.
Li Qing, Hong Xin, Zheng Shaobo.Dynamic model & simulation of EAF process[J]. Reseach on Iron and Steel, 2001, 29(1): 20-25.
[18] 廖延涛, 胡骏, 张海龙, 等. 用于电能质量预测分析的交流电弧炉时变参数模型[J]. 电气技术, 2016, 17(3): 41-46.
Liao Yantao, Hu Jun, Zhang Hailong, et al.Time-varying parameter model of AC electrical arc furnace for power quality predictions and analysis[J]. Electrical Engineering, 2016, 17(3): 41-46.
[19] 方昕玥, 王斌, 喻敏, 等. 交流电弧炉的间谐波检测及状态判断[J]. 电测与仪表, 2020, 57(13): 137-143.
Fang Xinyue, Wang Bin, Yu Min, et al.Inter-harmonic detection and state judgment of AC arc furnace[J]. Electrical Measurement & Instrumentation, 2020, 57(13): 137-143.
[20] 李丹. 电弧炉冶炼过程建模及用氧制度优化[D]. 沈阳: 东北大学, 2008.
Li Dan.Modeling of smelting process and optimization of oxygen blowing in electric arc furnace[D]. Shenyang: Northeastern University, 2008.
[21] 张奇. 电弧炉炼钢技术发展探讨[J]. 山西冶金, 2025, 48(2): 91-93.
Zhang Qi.Discussion on the development of electric arc furnace steelmaking technology[J]. Shanxi Metallurgy, 2025, 48(2): 91-93.
[22] 陈思源. 基于数据驱动的配电网谐波源识别和建模方法研究[D]. 武汉: 华中科技大学, 2022.
Chen Siyuan.Research on harmonic source identification and modeling method of distribution network based on data driven[D]. Wuhan: Huazhong University of Science and Technology, 2022.
[23] Underwood T, Roy S, Glaz B.Physics based lumped element circuit model for nanosecond pulsed dielectric barrier discharges[J]. Journal of Applied Physics, 2013, 113(8): 083301.
[24] 李刚, 肖剑桥, 阎对丰, 等. 气体电弧在不同气体介质中电子数密度的汤逊散射诊断研究[J]. 高压电器, 2024, 60(2): 163-168, 191.
Li Gang, Xiao Jianqiao, Yan Duifeng, et al.Research on Thomson scattering diagnosis of electron number density of gas arc in different gas medium[J]. High Voltage Apparatus, 2024, 60(2): 163-168, 191.
[25] 梅振青. 基于特里切尔脉冲的传感器特性数值模拟[D]. 北京: 北京石油化工学院, 2023.
Mei Zhenqing.Simulation study of sensor characteristics based on Trichel pulses[D]. Beijing: Beijing Institute of Petrochemical Technology, 2023.
[26] 王丰华. 电弧炉建模研究及其应用[D]. 上海: 上海交通大学, 2006.
Wang Fenghua.Study of modeling the electric arc furnace and its application[D]. Shanghai: Shanghai Jiao Tong University, 2006.
[27] 陈芳, 荣娜, 胡晓. 直流电压下局部放电数值模拟方法研究综述[J]. 绝缘材料, 2024, 57(4): 1-12.
Chen Fang, Rong Na, Hu Xiao.Review of numerical simulation methods for partial discharge under DC voltage[J]. Insulating Materials, 2024, 57(4): 1-12.
[28] 何春来, 朱荣, 董凯, 等. 基于烟气成分分析的电弧炉炼钢脱碳模型[J]. 北京科技大学学报, 2010, 32(12): 1537-1541.
He Chunlai, Zhu Rong, Dong Kai, et al.Decarburization model of EAF steelmaking based on fume composition detecting[J]. Journal of University of Science and Technology Beijing, 2010, 32(12): 1537-1541.
[29] Raizer Y P.Gas Discharge Physics[M]. Berlin: Springer, 1991.
[30] 刘小河, 程少庚, 苏文成. 电弧炉电气系统的谐波分析研究[J]. 电工技术学报, 1994, 9(2): 21-26, 10.
Liu Xiaohe, Cheng Shaogeng, Su Wencheng.Harmonic analysis of electric systems of arc furnace[J]. Transactions of China Electrotechnical Society, 1994, 9(2): 21-26, 10.
[31] 过增元, 赵文华. 电弧和热等离子体[M]. 北京: 科学出版社, 1986.
[32] Abid F, Niayesh K, Jonsson E, et al.Arc voltage characteristics in ultrahigh-pressure nitrogen including supercritical region[J]. IEEE Transactions on Plasma Science, 2018, 46(1): 187-193.
[33] Pauna H, Willms T, Aula M, et al.Electric arc length-voltage and conductivity characteristics in a pilot-scale AC electric arc furnace[J]. Metallurgical and Materials Transactions B B-Process Metallurgy and Materials Processing Science, 2020, 51(4): 1646-1655.
[34] 董中奇, 时彦林. 电弧炉炼钢生产[M]. 北京: 冶金工业出版社, 2013.
[35] 赵舸, 胡砚斌, 王雪明, 等. 电炉铁水比对供氧量及其利用系数的影响研究[J]. 山东冶金, 2023, 45(4): 22-24.
Zhao Ge, Hu Yanbin, Wang Xueming, et al.The effect of high hot metal charging rate on oxygen consumption and utilization coefficient in EAF[J]. Shandong Metallurgy, 2023, 45(4): 22-24.
[36] 董凯, 朱荣, 刘文娟, 等. 电弧炉炉气成分的影响因素[J]. 北京科技大学学报, 2011, 33(增刊1): 77-82.
Dong Kai, Zhu Rong, Liu Wenjuan, et al.Influencing factors of EAF off-gas composition[J]. Journal of University of Science and Technology Beijing, 2011, 33(S1): 77-82.
[37] 廖延涛. 炼钢交流电弧炉电能质量问题的分析与治理研究[D]. 南京: 南京师范大学, 2016.
[38] 万聪聪. 基于故障限流器的电弧炉电压波动和闪变抑制器研究[D]. 武汉: 武汉大学, 2019.
Wan Congcong.Research on voltage fluctuation and flicker suppressor of electric arc furnace based on fault current limiter[D]. Wuhan: Wuhan University, 2019.
[39] 宋竟绮, 郝瑞祥, 袁帆, 等. 基于空心电极的三相交流电弧等离子体炬建模与实验研究[J]. 电工技术学报, 2025, 40(13): 4125-4137, 4179.
Song Jingqi, Hao Ruixiang, Yuan Fan, et al.Modeling and experimental research on three-phase AC arc plasma torch based on hollow electrode[J]. Transactions of China Electrotechnical Society, 2025, 40(13): 4125-4137, 4179.
[40] 盛德杰, 王尧, 邢云琪, 等. 基于磁流体动力学仿真的低压交流串联故障电弧致火风险研究[J]. 电工技术学报, 2025, 40(10): 3326-3338.
Sheng Dejie, Wang Yao, Xing Yunqi, et al.Research on fire risk of low voltage AC series fault arc based on magnetohydrodynamics simulation[J]. Transac-tions of China Electrotechnical Society, 2025, 40(10): 3326-3338.
[41] 张毅恒. 计及负荷指标特性的电能质量综合评估方法研究与应用[D]. 合肥: 安徽大学, 2022.
Zhang Yiheng.Research and application of a comprehensive power quality evaluation method considering load-indicator characteristics[D]. Hefei: Anhui University, 2022.