虚实融合的变压器内绝缘状态孪生方法

doi:10.19595/j.cnki.1000-6753.tces.231839

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (37572 KB) HTML
输出: BibTeX | EndNote (RIS)

摘要发展数字孪生变压器对支撑高端电力装备智能化、数字化、可视化运维具有重要意义。然而,由于目前变压器缺乏相应的数字孪生能力,实现变压器的数字孪生还面临巨大挑战。为此,该文开展了虚实融合的变压器内绝缘状态孪生方法研究。首先计算了温度场和水分分布;然后建立了改进水分平移因子的聚合度分布动态推演模型;最后通过Delaunay三角网实现了任意时刻聚合度分布的可视化。结果表明,水分分布主要集中在纸板和底部固体绝缘处,第48年含水量最高值约为3.2%;聚合度分布规律与CIGRE报告基本相符,最低值位于低压绕组热点温度区域,第48年为252.15,验证了该方法的有效性和合理性。该文可实现变压器内绝缘老化状态参量分布评估,为后续全面构建变压器数字孪生体奠定了基础。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	罗豪
	成立
	杨丽君
	赵学童
	张永泽

关键词 ：虚实融合, 变压器, 数字孪生, 状态参量, 分布监测

Abstract：The national development plan calls for the digital and intellectual transformation of power enterprises to support the construction of new power systems. Power transformer as the core equipment of the power grid, its operational reliability is related to the safety of the entire power grid, therefore, the development of digital twin transformer is of great significance to support the intelligent, digital, visualized operation and maintenance of high-end power equipment. However, there are still significant challenges for transformers due to the lack of corresponding digital twin capabilities, such as insufficient sensors, unknown parametric mechanism, and lack of post-processing techniques. For this reason, this paper carries out a research on a state twinning method for transformer internal insulation by virtual-real fusion.
Firstly, the internal temperature field distribution of the transformer is the data basis for calculating the state parameter distribution. Considering the complex multi-physical field coupling effect of the transformer, the calculated losses are used as the heat source of the temperature field simulation for the multi-physical field coupling calculation, and the temperature field distribution corresponding to the real-time load change is derived based on the load rate monitored in the field. Secondly, the temperature field distribution of virtual calculation and the moisture in oil data of physical monitoring are combined to analyze the distribution law of moisture in paper at each local location inside the transformer. Based on the relationship between the total moisture content in the paper of multiple transformers in the field and the operation time, an empirical formula is established, and the oil-paper equilibrium equation and the law of moisture diffusion are utilized to determine the content and distribution. Thirdly, considering the effect of moisture distribution on the moisture translational factor, a dynamic derivation model of degree of polymerization distribution based on the joint action of time-temperature-moisture distribution is established, and the results of the degree of polymerization distribution of the insulating cardboard inside the transformer are obtained. Finally, due to the fact that the multi-physics field simulation calculation results and the dynamic deduction numerical results are discrete point data, this paper adopts the point-by-point insertion method of Delaunay triangular mesh for the continuity of the discrete data, and the state parameter data obtained by virtual-realistic fusion calculation are visualized in this paper.
The results show that the moisture distribution calculated by virtual-real fusion is mainly concentrated in the laminated cardboard on both sides and the bottom of the solid insulation, with the highest moisture content of about 3.2% in the 48th year, which is greatly influenced by the temperature field distribution and environmental factors. The rule of the degree of polymerization distribution in the windings is in general agreement with the measurements reported by CIGRE, and the lowest value is located in the hot spot temperature region of the low-voltage windings, with a value of 252.15 in the 48th year, which verifies the validity and reasonableness of the methodology. This study realizes the assessment of the parametric distribution for the aging state parameter inside the transformer insulation, and lays the foundation for the subsequent comprehensive construction of the digital twin of the transformer.

Key words： Virtual-real fusion transformer digital twin state parameter distributed monitoring

收稿日期: 2023-11-03

PACS:

TM83

基金资助:国家重点研发计划资助项目（2021YFB2401700）

作者简介: 罗豪男,1997年生,博士研究生,研究方向为电力设备先进数字孪生技术、电气设备寿命评估。E-mail：haoluo@cqu.edu.cn

引用本文:

罗豪, 成立, 杨丽君, 赵学童, 张永泽. 虚实融合的变压器内绝缘状态孪生方法[J]. 电工技术学报, 2024, 39(23): 7628-7638. Luo Hao, Cheng Li, Yang Lijun, Zhao Xuetong, Zhang Yongze. State Twinning Method of Transformer Internal Insulation by Virtual-Real Fusion. Transactions of China Electrotechnical Society, 2024, 39(23): 7628-7638.

链接本文:

https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.231839 https://dgjsxb.ces-transaction.com/CN/Y2024/V39/I23/7628

[1] 工业和信息化部. “十四五” 信息化和工业化深度融合发展规划[Z].2021-11-17.
[2] 肖祥武, 王丰, 王晓辉, 等. 面向工业互联网的智慧电厂仿生体系架构及信息物理系统[J]. 电工技术学报, 2020, 35(23): 4898-4911.
Xiao Xiangwu, Wang Feng, Wang Xiaohui, et al.Bionic structure and cyber-physical system for intelligent power plant oriented to the industrial Internet[J]. Transactions of China Electrotechnical Society, 2020, 35(23): 4898-4911.
[3] Tuegel E J, Ingraffea A R, Eason T G, et al.Reengineering aircraft structural life prediction using a digital twin[J]. International Journal of Aerospace Engineering, 2011, 2011: 154798.
[4] 江悦, 沈小军, 吕洪, 等. 碱性电解槽运行特性数字孪生模型构建及仿真[J]. 电工技术学报, 2022, 37(11): 2897-2908.
Jiang Yue, Shen Xiaojun, Lü Hong, et al.Construction and simulation of operation digital twin model for alkaline water electrolyzer[J]. Transactions of China Electrotechnical Society, 2022, 37(11): 2897-2908.
[5] 杨帆, 吴涛, 廖瑞金, 等. 数字孪生在电力装备领域中的应用与实现方法[J]. 高电压技术, 2021, 47(5): 1505-1521.
Yang Fan, Wu Tao, Liao Ruijin, et al.Application and implementation method of digital twin in electric equipment[J]. High Voltage Engineering, 2021, 47(5): 1505-1521.
[6] 王伟杰, 雍明超, 黄金魁, 等. 高压设备数字孪生体构建及状态分析技术研究[J]. 高压电器, 2023, 59(11): 119-128.
Wang Weijie, Yong Mingchao, Huang Jinkui, et al.Research on construction of condition analysis technology of digital twin for high voltage equipment[J]. High Voltage Apparatus, 2023, 59(11): 119-128.
[7] 杨童亮, 胡东, 唐超, 等. 基于SMA-VMD-GRU模型的变压器油中溶解气体含量预测[J]. 电工技术学报, 2023, 38(1): 117-130.
Yang Tongliang, Hu Dong, Tang Chao, et al.Prediction of dissolved gas content in transformer oil based on SMA-VMD-GRU model[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 117-130.
[8] 江军, 张文乾, 李波, 等. 电力变压器油中溶解气体离群值识别和数据重构[J/OL]. 电工技术学报, 2023: 1-13[2023-12-20]. https://doi.org/10.19595/j.cnki.1000-6753.tces.231033.
Jiang Jun, Zhang Wenqian, Li Bo, et al. Outlier detection and data reconstruction of dissolved gas in oil for power transformers[J/OL]. Transactions of China Electrotechnical Society, 2023: 1-13[2023-12-20]. https://doi.org/10.19595/j.cnki.1000-6753.tces.231033.
[9] 刘云鹏, 黎晏霖, 李欢, 等. 基于布里渊光时域峰值边沿分析的变压器绕组局部热点检测[J]. 电工技术学报, 2024, 39(11): 3486-3498.
Liu Yunpeng, Li Yanlin, Li Huan, et al.Local hot spot detection of transformer windings based on Brillouin optical time domain peak edge analysis[J]. Transactions of China Electrotechnical Society, 2024, 39(11): 3486-3498.
[10] 曲岳晗, 赵洪山, 程晶煜, 等. 基于物联感知数据和张量融合的电力变压器绕组绝缘劣化评估方法[J]. 电工技术学报, 2024, 39(4): 1208-1220.
Qu Yuehan, Zhao Hongshan, Cheng Jingyu, et al.Evaluation method for power transformer winding insulation degradation based on IoT sensing data and tensor fusion[J]. Transactions of China Electrotechnical Society, 2024, 39(4): 1208-1220.
[11] 西门子低压——西门子面向输电业务的数字化产品落地中国[EB/OL]. (2019-11-26)[2023-11-03]. http://www.siemensyzs.gongboshi.com/news/itemid-64575. shtml.
[12] ABB电力世界. ABB新品发布！全球首台数字化电力变压器来了[J]. 中国机电工业, 2018(6): 24.
[13] Coutinho C P, Tavares S M O, Gonçalves F, et al. Transformer 4.0: digital revolution of power transformers[EB/OL]. (2020-07-01)[2023-11-03]. https://www.mitportugal.org/research/flagship-projects/transformer-4p0-digital-revolution-of-power-transformers/.
[14] Ansys Inc. Ansys Twin Builder: simulation-based & hybrid analytics[EB/OL]. (2022-03-30)[2023-11-03]. https://www.ansys.com/content/dam/product/digital-twin/twin-builder/ansys-twin-builder-technical-datasheet.pdf.
[15] 宋振龙, 孙凤伟, 陈锋, 等. 网络化智能传感器及其在航空航天领域中的应用[J]. 电子测试, 2009(9): 10-13, 53.
Song Zhenlong, Sun Fengwei, Chen Feng, et al.Intelligent sensor in network and its application in aeronautics and space domain[J]. Electronic Test, 2009(9): 10-13, 53.
[16] 谭又博, 余小玲, 臧英, 等. 谐波电流对换流变压器绕组损耗及温度分布特性的影响[J]. 电工技术学报, 2023, 38(2): 542-553.
Tan Youbo, Yu Xiaoling, Zang Ying, et al.The influence of harmonic current on the loss and temperature distribution characteristics of a converter transformer winding[J]. Transactions of China Electrotechnical Society, 2023, 38(2): 542-553.
[17] 刘刚, 郝世缘, 朱章宸, 等. 基于动态模态分解-自适应变步长油浸式电力变压器绕组瞬态温升快速计算方法[J]. 电工技术学报, 2024, 39(12): 3895-3906.
Liu Gang, Hao Shiyuan, Zhu Zhangchen, et al.Research on rapid calculation method of transient temperature rise of winding of dynamic mode decomposition-adaptive time stepping oil-immersed power transformer[J]. Transactions of China Electrotechnical Society, 2024, 39(12): 3895-3906.
[18] Gielniak J, Graczkowski A, Moranda H, et al.Moisture in cellulose insulation of power transformers-statistics[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2013, 20(3): 982-987.
[19] García B, Villarroel R, García D.A multiphysical model to study moisture dynamics in transformers[J]. IEEE Transactions on Power Delivery, 2019, 34(4): 1365-1373.
[20] Zhou Lijun, Wu Guangning, Liu Jun.Modeling of transient moisture equilibrium in oil-paper insulation[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2008, 15(3): 872-878.
[21] 杨丽君, 邓帮飞, 廖瑞金, 等. 应用时-温-水分叠加方法改进油纸绝缘热老化寿命模型[J]. 中国电机工程学报, 2011, 31(31): 196-203.
Yang Lijun, Deng Bangfei, Liao Ruijin, et al.Improvement of lifetime model on thermal aging of oil-paper insulation by time-temperature-moisture superposition method[J]. Proceedings of the CSEE, 2011, 31(31): 196-203.
[22] 赵洪山, 常杰英, 曲岳晗, 等. 基于二元非线性Wiener随机过程的变压器油纸绝缘剩余寿命预测方法[J]. 电工技术学报, 2023, 38(15): 4040-4049.
Zhao Hongshan, Chang Jieying, Qu Yuehan, et al.Residual life prediction method of transformer oil-paper insulation based on binary nonlinear Wiener random process[J]. Transactions of China Electrotechnical Society, 2023, 38(15): 4040-4049.
[23] 赵鑫, 田志峰, 钱卫东, 等. 基于Delaunay三角剖分算法高效构建舰船后处理模型的研究[J]. 现代信息科技, 2018, 2(6): 84-88.
Zhao Xin, Tian Zhifeng, Qian Weidong, et al.The research on post-processing mode establishing of ship based on Delaunay triangled algorithm method[J]. Modern Information Technology, 2018, 2(6): 84-88.
[24] CIGRE WG A2.45. Transformer post-mortem analysis[R]. Paris: CIGRE, 2018.
[25] Wang Junhong, Liao Ruijin, Cheng Li, et al.Effects of winding vibration on the mechanical-thermal aging properties of insulating paper[J]. IEEE Access, 2020, 8: 67912-67920.