基于PSO_SVM算法的输电线路覆冰舞动预测模型

PDF(1810 KB)

振动与冲击 ›› 2023, Vol. 42 ›› Issue (3) : 280-286.

论文

邹红波1,2，宋家乐1,2，刘媛2，段治丰2，张馨煜2，宋璐2

作者信息 +

Prediction model of galloping of iced transmission lines based on PSO-SVM algorithm

ZOU Hongbo1,2, SONG Jiale1,2, LIU Yuan2, DUAN Zhifeng2, ZHANG Xinyu2, SONG Lu2

Author information +

文章历史 +

摘要

输电线路舞动往往会导致金具磨损、闪络、断线等电力事故，对电力系统的安全具有很大的负面影响。利用ANSYS软件模拟不同档距、风速等状态下覆冰四分裂导线在平均风与脉动风作用下的动态响应，进而根据模拟获得的数据集和PSO_SVM（particle swarm optimization—support vector machines）算法构建了四分裂导线覆冰舞动预警模型，将档距、风速、初始风攻角作为模型的输入，覆冰导线是否舞动作为输出。同时，为验证该预测模型的实用性及有效性，将PSO_SVM模型与其他智能算法如BP(back propagation)、支持向量机（support vector machine，SVM）、遗传算法优化支持向量机（genetic algorithm—optimization support vector，GA_SVM）模型的预测结果进行比较，结果表明PSO_SVM模型的预测结果精度更高，对输电线路覆冰舞动预警具有一定的参考意义。

Abstract

The galloping of transmission lines often leads to electrical accidents such as wear of fittings, flash-over, and disconnection, which has a great negative impact on the safety of the power system. The dynamic response of the iced quad bundle conductor under the action of average wind and fluctuating wind was simulated by ANSYS software under the conditions of different spans, wind speeds, etc. Then, the early warning model was constructed based on the PSO_SVM（particle swarm optimization—support vector machines） algorithm and the data set obtained from the simulation, which takes the span, wind speed and initial wind angle of attack as the input, and whether galloping as the output. At the same time, the prediction results of the PSO_SVM model are compared with those of other intelligent algorithms such as BP(back propagation), SVM（support vector machine）, and GA_SVM（genetic algorithm—optimization support vector） models to verify the practicability and effectiveness of the prediction model. It is proved that the prediction results of the PSO_SVM model have higher accuracy, which has a certain reference significance for the early warning of the galloping of iced transmission lines.

导出引用

邹红波1,2，宋家乐1,2，刘媛2，段治丰2，张馨煜2，宋璐2. 基于PSO_SVM算法的输电线路覆冰舞动预测模型[J]. 振动与冲击, 2023, 42(3): 280-286

ZOU Hongbo1,2, SONG Jiale1,2, LIU Yuan2, DUAN Zhifeng2, ZHANG Xinyu2, SONG Lu2. Prediction model of galloping of iced transmission lines based on PSO-SVM algorithm[J]. Journal of Vibration and Shock, 2023, 42(3): 280-286

参考文献

[1] Diana G, Manenti A, Melzi S. Energy method to compute the maximum amplitudes of oscillation due to galloping of iced bundled conductors[J]. IEEE Transactions on Power Delivery, 2020, 36(5): 2804-2813.
[2] He M, Macdonald J H G. An analytical solution for the galloping stability of a 3 degree-of-freedom system based on quasi-steady theory[J]. Journal of Fluids and Structures, 2016, 60: 23-36.
[3] 寻凯, 尹洪, 刘海英. 不同绞向组合覆冰分裂导线稳定性及其舞动特性[J]. 高电压技术, 2021, 47(7): 2506-2513.
XUN Kai, YIN Hong, LIU Haiying. Stability and Galloping Characteristic of Iced Bundled Conductor with the Combination in Various Directions of Lay[J]. High Voltage Engineering, 2021, 47(07): 2506-2513.
[4] Cai M, Yan B, Lu X, et al. Numerical simulation of aerodynamic coefficients of iced-quad bundle conductors[J]. IEEE Transactions on Power Delivery, 2015, 30(4): 1669-1676.
[5] 向玲,张悦,唐亮.覆冰四分裂导线的气动特性和舞动特性分析[J].中国工程机械学报,2019,17(04):297-303.
XIANG Ling, ZHANG Yue, TANG Liang. Analysis for aerodynamic characteristics and galloping behaviors of iced quad bundle conductor[J]. CHINESE JOURNAL OF CONSTRUCTION MACHINERY, 2019, 17(04): 297-303.
[6] 向玲,周晨光,唐亮.不同档距四分裂线路的防舞仿真分析[J].中国工程机械学报,2019,17(02):127-133.
XIANG Ling, ZHOU Chenguang, TANG Liang. Simulation of different span quad bundle transmission line’s anti-galloping[J]. CHINESE JOURNAL OF CONSTRUCTION MACHINERY, 2019, 17(02): 127-133.
[7] 王黎明,王琼,陆佳政,等.500 kV覆冰四分裂导线舞动特性[J].高电压技术,2019,45(07):2284-2291.
WANG Liming, WANG Qiong, LU Jiazheng, et al. Galloping Characteristics of 500 kV Iced Quad Bundle Conductor[J]. High Voltage Engineering, 2019, 45(07): 2284-2291.
[8] Zhou L, Yan B, Zhang L, et al. Study on galloping behavior of iced eight bundle conductor transmission lines[J]. Journal of Sound and Vibration, 2016, 362: 85-110.
[9] 伍川,叶中飞,严波,等.考虑导线偏心覆冰对四分裂导线舞动的影响[J].振动与冲击,2020,39(01):29-36.
WU Chuan, YE Zhongfei, YAN Bo, et al. Effects of conductor eccentric icing on quad-bundle conductor galloping[J]. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(01): 29-36.
[10] Yang L, Li L, Guo J, et al. Galloping early warning technology of transmission lines based on rbf neural network[C]//2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2019: 2374-2378.
[11] Zhang L, Zhao B, Han J, et al. Forecast on Failure Characteristics of Transmission Line Galloping Based on Neural Networks Method[C]//2019 6th International Conference on Information Science and Control Engineering (ICISCE). IEEE, 2019: 292-296.
[12] 褚双伟,熊小伏,刘善峰,等.计及输电线路舞动预测的电网短期风险评估[J].电力系统保护与控制,2018,46(09):86-93.
CHU Shuangwei, XIONG Xiaofu, LIU Shanfeng, et al. Short-term risk assessment of power grid considering galloping prediction of transmission lines[J]. Power System Protection and Control, 2018, 46(09): 86-93.
[13] Wang J, Xiong X, Zhou N, et al. Early warning method for transmission line galloping based on SVM and AdaBoost bi-level classifiers[J]. IET Generation, Transmission & Distribution, 2016, 10(14): 3499-3507.
[14] Lee J, Jung H Y, Koo J R, et al. Prediction of galloping accidents in power transmission line using logistic regression analysis[J]. Journal of Electrical Engineering & Technology, 2017, 12(2): 969-980.
[15] Cheng Y, Han J, Liu B, et al. A prediction method for galloping of transmission lines based on improved neural network[J]. International Journal of Mechanical Engineering and Applications, 2018, 4(4): 126-133.
[16] Wei Y, Gao X. Transmission Line Galloping Prediction Based on GA-BP-SVM Combined Method[J]. IEEE Access, 2021, 9: 107680-107687.
[17] 程永锋,汉京善,刘彬,等.基于Bagging算法构造强分类器的one class SVM导线舞动预测应用[J].振动与冲击,2020,39(09):152-158.
CHENG Yongfeng, HAN Jingshan, LIU Bin, et al. Prediction of transmission line galloping by one class SVM based on the Bagging algorithm for constructing a strong classifier[J]. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(09): 152-158.
[18] 王津宇,李哲,刘善峰,等.基于风险系数的输电线路覆冰舞动预警方法[J].高压电器,2019,55(09):194-199.
WANG Jinyu, LI Zhe, LIU Shanfeng, et al. Early Warning Method of Iced Transmission Line Galloping Based on Risk Coefficient[J]. High Voltage Apparatus, 2019, 55(09): 194-199.
[19] 徐文宝,周建华.基于改进模糊层次综合评判法的输电线路舞动预警[J].电力工程技术,2021,40(05):107-113.
XU Wenbao, ZHOU Jianhua. Early warning of transmission line galloping based on improved fuzzy hierarchical comprehensive evaluation method[J]. Electric Power Engineering Technology, 2021, 40(05): 107-113.
[20] 卢明,赵书杰,刘振声,等.基于灰色投影优化随机森林算法的输电线路舞动预警方法[J].电测与仪表,2020,57(09):45-51+57.
Lu Ming, Zhao Shujie, Liu Zhensheng, et al. Early warning method of transmission line galloping based on random forest optimized by grey relation projection[J]. Electrical Measurement ＆ Instrumentation, 2020, 57(09): 45-51+57.
[21] 李清,杨晓辉,刘振声,等.基于灰色聚类分析的输电线路舞动分级预警方案[J].电测与仪表,2020,57(17):45-51.
Li Qing, Yang Xiaohui, Liu Zhensheng, et al. Graded warning scheme of transmission line galloping based on grey clustering analysis[J]. Electrical Measurement ＆ Instrumentation, 2020, 57(17): 45-51.
[22] 王琼,王黎明,卢明,等.覆冰四分裂导线风洞试验与舞动研究[J].高电压技术,2019,45(05):1608-1615.
WANG Qiong, WANG Liming, LU Ming, et al. Study on Wind Tunnel Test and Galloping of Iced Quad Bundle Conductor[J]. High Voltage Engineering, 2019, 45(05): 1608-1615.
[23] 肖白,赵晓宁,姜卓,等.利用模糊信息粒化与支持向量机的空间负荷预测方法[J].电网技术,2021,45(01):251-260.
XIAO Bai, ZHAO Xiaoning, JIANG Zhuo, et al. Spatial Load Forecasting Method Using Fuzzy Information Granulation and Support Vector Machine[J]. Power System Technology, 2021, 45(01): 251-260.
[24] 张锦东,郭小农,罗晓群,等.基于粒子群算法的改进模态参数识别方法[J].振动与冲击,2022,41(02):255-264.
ZHANG Jindong, GUO Xiaonong, LUO Xiaoqun, et al. Improved modal parameter identification method based on particle swarm optimization[J]. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(02): 255-264.
[25] Zhao S, Zhao Z. A comparative study of landslide susceptibility mapping using SVM and PSO-SVM models based on grid and slope units[J]. Mathematical Problems in Engineering, 2021, 2021.
[26] 任娟娟,杜威,叶文龙,等.基于PSO-SVM的板式无砟轨道CA砂浆脱空损伤识别[J].中南大学学报(自然科学版),2021,52(11):4021-4031.
REN Juanjuan, DU Wei, YE Wenlong, et al. Contact loss identification of CA mortar in prefabricated slab track based on PSO−SVM[J]. Journal of Central South University (Science and Technology), 2021, 52(11): 4021-4031.