高压开关柜热故障预警策略及其应用
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摘要
依据高压开关柜热故障的时域多样性,对于长期故障和即时故障,分别提出了改进的组合权重相似日方法和改进的等效电阻模型。改进的组合权重相似日方法利用熵权法及序关系分析法完成相似日的求取及权重系数的分配,避免了相似日求取的不合理问题,有效地提高了预测精度。改进的等效电阻模型嵌入动态阈值算法及空间相关分析法处理奇异点数据和特征信号,使故障信号分析更加准确。实验结果表明,所提方法和模型能够准确有效地预测载流故障发展的整体趋势,精度较高。
Based on the time-domain diversity of thermal faults of high voltage switch cabinet,an improved combined weight similarity day method is proposed for long-term failure prediction,while an improved equivalent resistance model is established for real-time fault prediction. The improved combined weight similarity day method adopts the entropy weight method and order relationship analysis method to complete the calculation of similar days and the allocation of weight coefficients,which avoids the irrationality problem of similar day calculation and effectively improves the prediction accuracy. The improved equivalent resistance model is embedded with the dynamic threshold algorithm and spatial correlation analysis method to deal with the singularity data processing and feature extraction,which makes the fault signal analysis more accurate. The experimental results show that the proposed method and model can effectively predict the overall trend of faulty development in the early stage of current carrying faults with high accuracy.
Based on the time-domain diversity of thermal faults of high voltage switch cabinet,an improved combined weight similarity day method is proposed for long-term failure prediction,while an improved equivalent resistance model is established for real-time fault prediction. The improved combined weight similarity day method adopts the entropy weight method and order relationship analysis method to complete the calculation of similar days and the allocation of weight coefficients,which avoids the irrationality problem of similar day calculation and effectively improves the prediction accuracy. The improved equivalent resistance model is embedded with the dynamic threshold algorithm and spatial correlation analysis method to deal with the singularity data processing and feature extraction,which makes the fault signal analysis more accurate. The experimental results show that the proposed method and model can effectively predict the overall trend of faulty development in the early stage of current carrying faults with high accuracy.
引文
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[16] 胡益,王晓茹,艾鹏,等.基于广域量测的交直流混联系统发生扰动后稳态频率预测算法[J].电力自动化设备,2018,38(11):35-42.HU Yi,WANG Xiaoru,AI Peng,et al.Prediction algorithm of steady-state frequency after disturbance for hybrid AC/DC power system based on wide area measurement[J].Electric Power Automation Equipment,2018,38(11):35-42.
[17] 都洪基,丁一.PLC智能化电力设备故障诊断系统[J].电力自动化设备,2002,22(7):69-70.DU Hongji,DING Yi.Intelligent diagnosis system based on PLC for electric power equipment[J].Electric Power Automation Equipment,2002,22(7):69-70.
[18] 孟晓,胡炎.变电站无线测温告警算法[J].电力系统自动化,2013,37(2):81-85.MENG Xiao,HU Yan.Algorithm of wireless temperature measurement and alarm in substations[J].Automation of Electric Power Systems,2013,37(2):81-85.
[2] 张慧源,顾宏杰,许力,等.基于最小二乘支持向量机的载流故障趋势预测[J].电力系统保护与控制,2012,40(10):20-27.ZHANG Huiyuan,GU Hongjie,XU Li,et al.Current-carrying fault prediction of electric equipment based on least squares support vector machine[J].Power System Protection and Control,2012,40(10):20-27.
[3] 刘宝英,杨仁刚.基于主成分分析的最小二乘支持向量机短期负荷预测模型[J].电力自动化设备,2008,38(11):13-17.LIU Baoying,YANG Rengang.Short-term load forecasting model based on LS-SVM with PCA[J].Electric Power Automation Equipment,2008,38(11):13-17.
[4] 胡少迪,许力.基于等效电阻分析的载流故障早期预警[J].仪器仪表学报,2016,37(1):216-220.HU Shaodi,XU Li.Early warning of current-carrying faults based on equivalent resistance analysis[J].Chinese Journal of Scientific Instrument,2016,37(1):216-220.
[5] 王德文,刘晓建.基于MapReduce的电力设备并行故障诊断方法[J].电力自动化设备,2014,34(10):116-120.WANG Dewen,LIU Xiaojian.Parallel fault diagnosis based on Map-Reduce for electric power equipments[J].Electric Power Automation Equipment,2014,34(10):116-120.
[6] 张慧源,沈军达,许力.电力设备温升模型及其在载流故障预测的应用[J].电机与控制学报,2013,17(7):82-85.ZHANG Huiyuan,SHEN Junda,XU Li.Temperature model of electrical equipment and its application in trend forecast for current-carrying fault[J].Electrical Machines and Control,2013,17(7):82-85.
[7] 杨锡运,刘欢,张彬,等.组合权重相似日选取方法及光伏输出功率预测[J].电力自动化设备,2014,34(9):119-123.YANG Xiyun,LIU Huan,ZHANG Bin,et al.Similar day selection based on combined weight and photovoltaic power output forecasting[J].Electric Power Automation Equipment,2014,34(9):119-123.
[8] 黄新波,孙钦东,张冠军,等.输电线路实时增容的理论计算与应用研究[J].高电压技术,2008,34(6):1138-1144.HUANG Xinbo,SUN Qindong,ZHANG Guanjun,et al.Theoretical calculation and application study on real-time capacity-increase of transmission lines[J].High Voltage Engineering,2008,34(6):1138-1144.
[9] 许力,竺鹏东,顾宏杰,等.基于变尺度PCA的电力设备载流故障早期预警[J].电力自动化设备,2012,32(5):147-151.XU Li,ZHU Pengdong,GU Hongjie,et al.Early warning of electric equipment current-carrying faults based on variable-scale principal component analysis[J].Electric Power Automation Equipment,2012,32(5):147-151.
[10] 张玲玲,杨明玉,梁武.微网用户短期负荷预测相似日选择算法[J].中国电力,2015,48(4):156-160.ZHANG Lingling,YANG Mingyu,LIANG Wu.Short term load forecasting based on similar days selection algorithm for microgrid users[J].Electric Power,2015,48(4):156-160.
[11] 王涛,彭云华,吴小亚.基于相关因素修正的短期电力负荷回归预测模型[J].电力系统及其自动化,2013,35(1):52-57.WANG Tao,PENG Yunhua,WU Xiaoya.The short electrical load regression forecasting model based on the dependent factors modifying[J].Automation of Electric Power Systems,2013,35(1):52-57.
[12] 张青山,段建东,叶兵,等.基于ZigBee的开关柜触头温度在线监测预警系统[J].高压电器,2015,51(4):29-35.ZHANG Qingshan,DUAN Jiandong,YE Bing,et al.Online tempe-rature monitoring system based on ZigBee for switch gear contacts[J].High Voltage Apparatus,2015,51(4):29-35.
[13] 王雁凌,吴梦凯.经济新常态下基于偏最小二乘回归的中长期负荷预测模型[J].电力自动化设备,2018,38(3):133-139.WANG Yanling,WU Mengkai.Medium and long term load forecasting model based on partial least-square regression under new normal economy[J].Electric Power Automation Equipment,2018,38(3):133-139.
[14] HUANG Xinbo,LI Hongbo,ZHU Yongcan,et al.A short-term ice accretion forecasting model for transmission lines with modified time series analysis by fireworks algorithm[J].IET Generation Transmission & Distribution,2016,643-646.
[15] 李洪涛,舒乃秋,孙国霞,等.气体绝缘开关设备母线接头过热失效的相似模型[J].中国电机工程学报,2014,34(24):4138-4144.LI Hongtao,SHU Naiqiu,SUN Guoxia,et al.Scale model of over-heat failure in gas-insulated switchgear bus contact[J].Proceedings of the CSEE,2014,34(24):4138-4144.
[16] 胡益,王晓茹,艾鹏,等.基于广域量测的交直流混联系统发生扰动后稳态频率预测算法[J].电力自动化设备,2018,38(11):35-42.HU Yi,WANG Xiaoru,AI Peng,et al.Prediction algorithm of steady-state frequency after disturbance for hybrid AC/DC power system based on wide area measurement[J].Electric Power Automation Equipment,2018,38(11):35-42.
[17] 都洪基,丁一.PLC智能化电力设备故障诊断系统[J].电力自动化设备,2002,22(7):69-70.DU Hongji,DING Yi.Intelligent diagnosis system based on PLC for electric power equipment[J].Electric Power Automation Equipment,2002,22(7):69-70.
[18] 孟晓,胡炎.变电站无线测温告警算法[J].电力系统自动化,2013,37(2):81-85.MENG Xiao,HU Yan.Algorithm of wireless temperature measurement and alarm in substations[J].Automation of Electric Power Systems,2013,37(2):81-85.