Monitoring Method of Optical Fiber Composite Overhead Ground Wire Icing Thickness Based on Temperature Hysteresis Effect
Xu Zhiniu1, Song Shipeng2, Zheng Yuetian1, Zhang Zhengxian1, Zhao Lijuan1, Ji Kunpeng3, Ma Jiajun4
1. School of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 China; 2. State Grid Henan Electric Power Company UHV Company Zhengzhou 450000 China; 3. State Grid Electric Power Engineering Research Institute Co. Ltd Beijing 100069 China; 4. Ordos Power Supply Company of Inner Mongolia Power Co. Ltd Ordos 017010 China
Abstract：Transmission line icing accident is one of the main threats to the normal operation of power system, and its effective monitoring and prevention has become an important issue to ensure the safety of power grid. Distributed optical fiber sensing technology has the advantages of long monitoring distance, high measurement accuracy, and strong resistance to electromagnetic interference. The monitoring of transmission line icing based on this technology is a current research hotspot. However, there are still the following key problems: (1) Most of the research results lack experimental validation. (2) There is no research on the comparison and selection of the temperature lag parameters of icing monitoring. (3) There is also little research on the influence of some key factors on the effectiveness of icing monitoring in practical applications. In this work, based on the experiment and temperature field model of iced transmission line, the monitoring method of transmission line icing based on the lag parameters of temperature is investigated. In this work, the WAVE method is used to simulate the variation of real environmental temperature with time, a three-dimensional temperature field model for optical fiber composite overhead ground wire (OPGW) during icing is established, and the icing experiments in an artificial climate chamber based on the Brillouin optical time domain reflectometer (BOTDR) is conducted. These experiments validate the model, and meanwhile, the lag characteristic of line temperature is validated through both simulations and experiments. In fact, the temperature lag characteristic is measured according to the Brillouin frequency shift. The Brillouin frequency shift is linear to the temperature and strain of the optical fiber. According to the practical situation of transmission line, the optical fiber strain caused by the ice is essentially constant as time increases. Therefore, the influence of the optical fiber strain on the temperature lag characteristic can be neglected. The temperature lag characteristic of the optical fiber is solely related to the optical fiber temperature. On this basis, three temperature lag parameters are proposed: the phase difference between the optical fiber and environmental temperature curves, the change rate of heating rate, and the change rate of fluctuation amplitude. Through modeling research based on the validated temperature field model, the values of the three parameters at different icing thicknesses are obtained, and the corresponding icing thickness estimation formulas are respectively obtained via fitting. The model is used to analyze the effects of environmental temperature variation and optical fiber temperature measurement error on the three parameters. Furthermore, through the optical fiber temperature measurement based on BOTDR, noisy optical fiber temperature data are acquired. Based on this data, the impact of the temperature measurement error on the calculation accuracy of the above three formulas is investigated and a compared. The conclusions are as follows: (1) The mean value and fluctuation amplitude of environmental temperature have relatively small effects on the phase difference, the variation in maximum change of rate and amplitude between the optical fiber and the ambient temperature curves, which can be ignored and the proposed formulas of three parameters can be used to estimate the ice thickness. (2) The optical fiber temperature measurement error has a significant influence on the change rate of heating rate and the change rate of fluctuation amplitude, but has a minor impact on the phase difference. The icing estimation based on the phase difference of temperature curves achieves the highest accuracy. And if the temperature lag parameters are improperly selected, the error in icing thickness estimation can differ by up to 8 times.
[1] Rui Xiaoming, Ji Kunpeng, Li Lin, et al.Dynamic response of overhead transmission lines with eccentric ice deposits following shock loads[J]. IEEE Transactions on Power Delivery, 2017, 32(3): 1287-1294. [2] 牛涛, 黄骞谦, 方斯顿, 等. 基于多光谱卫星遥感的输电网冰灾场景时序建模与韧性提升策略优化[J]. 电工技术学报, 2025, 40(13): 4200-4215, 4305. Niu Tao, Huang Qianqian, Fang Sidun, et al.Temporal modeling of ice disaster scenarios and optimization of resilience enhancement strategies in power transmis-sion network based on multispectral satellite remote sensing data[J]. Transactions of China Electrotechnical Society, 2025, 40(13): 4200-4215, 4305. [3] Han Shunjie, Li Dongqi, Li Keyu, et al.Analysis and study of transmission line icing based on grey correlation Pearson combinatorial optimization support vector machine[J]. Measurement, 2024, 236: 115086. [4] 蒋兴良, 孟志高, 张志劲, 等. OPGW临界融冰电流及其影响因素[J]. 电工技术学报, 2016, 31(9): 174-180. Jiang Xingliang, Meng Zhigao, Zhang Zhijin, et al.Critical ice-melting current of ice-covered OPGW and its impacting factors[J]. Transactions of China Electrotechnical Society, 2016, 31(9): 174-180. [5] 曾伟, 蒋兴良, 杨国林, 等. 基于记忆合金双程形状记忆效应的导线雾凇防冰方法及现场试验[J]. 电工技术学报, 2024, 39(7): 2174-2183. Zeng Wei, Jiang Xingliang, Yang Guolin, et al.Research on anti-icing method for fog freezing and field test of wires based on two-way shape memory effect of memory alloy[J]. Transactions of China Electrotechnical Society, 2024, 39(7): 2174-2183. [6] 王增平, 曹辰, 王彤. 覆冰区域电网线路停运事故的评估方法[J]. 电工技术学报, 2025, 40(19): 6151-6166. Wang Zengping, Cao Chen, Wang Tong.Assessment method for outages of iced regional power grid lines[J]. Transactions of China Electrotechnical Society, 2025, 40(19): 6151-6166. [7] Li Ran, Zhang Zhijin, Jiang Xingliang, et al.An online monitoring device for twist angle of iced single conductor of transmission line[J]. IEEE Sensors Journal, 2025, 25(9): 14850-14859. [8] Qin Zhuoke, Jia Bin, Shen Xiahui, et al.A monitoring method for the ice shape and the freeze-thaw process of ice accretion on transmission line based on circular FBG plane principal strain sensor[J]. IEEE Sensors Journal, 2025, 25(13): 24265-24275. [9] 范晓舟, 袁洁平, 薛峰, 等. 基于简支绕组横梁算法的变压器绕组形变矢量化监测模型[J]. 电工技术学报, 2025, 40(5): 1639-1651. Fan Xiaozhou, Yuan Jieping, Xue Feng, et al.Vectorization monitoring model of transformer winding deformation based on simply supported winding beam algorithm[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1639-1651. [10] Liu Shuaiqi, Yu Feihong, Hong Rui, et al.Advances in phase-sensitive optical time-domain reflectometry[J]. Opto-Electronic Advances, 2022, 5(3): 200078. [11] 尚秋峰, 王若楠. 基于GADF-GCBAM-ResNet的DAS周界安防信号识别方法[J]. 光通信技术, 2026, 50(4): 60-64. Shang Qiufeng, Wang Ruonan.A method for perimeter security signal recognition based on GCBAM-ResNet and DAS[J]. Optical Communication Technology, 2026, 50(4): 60-64. [12] Guo Haohan, Liu Kun, Li Yuanyao, et al.Single-ended > 100-km distributed vibration sensor based on OFDR using Pearson correlation coefficient[J]. IEEE Sensors Journal, 2025, 25(9): 15143-15154. [13] Nilakanta Meitei S, Borah K, Chatterjee S.Review on monitoring of transformer insulation oil using optical fiber sensors[J]. Results in Optics, 2023, 10: 100361. [14] Ding Zhewen, Zhang Xuping, Zou Ningmu, et al.Phi-OTDR based on-line monitoring of overhead power transmission line[J]. Journal of Lightwave Technology, 2021, 39(15): 5163-5169. [15] Buchmayer F, Monsberger C M, Lienhart W.Advantages of tunnel monitoring using distributed fibre optic sensing[J]. Journal of Applied Geodesy, 2021, 15(1): 1-12. [16] 郝艳捧, 毛典明, 成延庭, 等. BOTDR监测OPGW覆冰最小临界厚度试验方法[J]. 高电压技术, 2025, 51(7): 3191-3200. Hao Yanpeng, Mao Dianming, Cheng Yanting, et al.Test method for minimum critical thickness of ice coating on OPGW based on BOTDR monitoring[J]. High Voltage Engineering, 2025, 51(7): 3191-3200. [17] 董乃臻, 肖海, 刘云鹏, 等. 基于分布式动态应变传感的光纤复合相线脱冰跳跃监测技术[J]. 电工技术学报, 2026, 41(7): 2484-2497. Dong Naizhen, Xiao Hai, Liu Yunpeng, et al.De-icing jump monitoring technology of optical fiber composite phase conductor based on distributed dynamic strain sensing[J]. Transactions of China Electrotechnical Society, 2026, 41(7): 2484-2497. [18] 张旭苹, 张益昕, 王亮, 等. 分布式光纤传感技术研究和应用的现状及未来[J]. 光学学报, 2024, 44(1): 0106001. Zhang Xuping, Zhang Yixin, Wang Liang, et al.Current status and future of research and applications for distributed fiber optic sensing technology[J]. Acta Optica Sinica, 2024, 44(1): 0106001. [19] 吴春芳, 陈云, 黄韬, 等. 电力电缆状态感知与检测技术研究综述[J]. 高压电器, 2024, 60(10): 86-103. Wu Chunfang, Chen Yun, Huang Tao, et al.Overview of condition sensing and detection technology for power cables[J]. High Voltage Apparatus, 2024, 60(10): 86-103. [20] 吴念, 王海涛, 张宗峰, 等. 基于OPGW的输电线路覆冰广域监测方法[J]. 中国电力, 2017, 50(5): 65-70. Wu Nian, Wang Haitao, Zhang Zongfeng, et al.Research of transmission line icing wide-area monitoring based on OPGW[J]. Electric Power, 2017, 50(5): 65-70. [21] 覃兆宇, 刘卫新, 潘哲哲, 等. 光纤布里渊分布式输电线路覆冰识别技术[J]. 光电工程, 2016, 43(10): 6-11. Qin Zhaoyu, Liu Weixin, Pan Zhezhe, et al.Optical Brillouin distributed ice-coating identification technology on transmission line[J]. Opto-Electronic Engineering, 2016, 43(10): 6-11. [22] Sun Jinxiang, Zhang Zhiguo, Li Yuemei, et al.Distributed transmission line ice-coating recognition system based on BOTDR temperature monitoring[J]. Journal of Lightwave Technology, 2021, 39(12): 3967-3973. [23] Zou Xiaoming, Liu Xinzhan, He Yi, et al.Ice thickness estimation method of overhead line based on distributed optical fiber temperature sensing[C]// Proceedings of the Sixth International Conference on Energy Engineering and Environmental Protection, Sanya, China, 2021: 012071. [24] 徐志钮, 李先锋, 郭一帆, 等. 基于温度滞后相位的输电线路覆冰监测方法[J]. 电力工程技术, 2022, 41(6): 91-100. Xu Zhiniu, Li Xianfeng, Guo Yifan, et al.Icing monitoring method of transmission lines based on temperature lagging phase[J]. Electric Power Engineering Technology, 2022, 41(6): 91-100. [25] Luo Jianbin, Hao Yanpeng, Ye Qing, et al.Development of optical fiber sensors based on Brillouin scattering and FBG for on-line monitoring in overhead transmission lines[J]. Journal of Lightwave Technology, 2013, 31(10): 1559-1565. [26] 范鹏, 刘春翔, 姜德华, 等. OPGW受拉力时光纤的应变分析[J]. 电线电缆, 2015, 58(4): 10-13, 25. Fan Peng, Liu Chunxiang, Jiang Dehua, et al.Stress and strain analysis of the optical fibers in an OPGW[J]. Electric Wire & Cable, 2015, 58(4): 10-13, 25. [27] Zunec M, Ticar I, Jakl F.Determination of current and temperature distribution in overhead conductors by using electromagnetic-field analysis tools[J]. IEEE Transactions on Power Delivery, 2006, 21(3): 1524-1529. [28] Ashfaq A, Khalique U, Nadeem A, et al.Comprehensive analysis of temperature distribution in OPGW cable considering ramifications of short circuit current[J]. Scientific Reports, 2025, 15: 21949. [29] Reicosky D C, Winkelman L J, Baker J M, et al.Accuracy of hourly air temperatures calculated from daily minima and maxima[J]. Agricultural and Forest Meteorology, 1989, 46(3): 193-209.
2026, Vol. 41 
