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作 者:谭风雷 朱超 徐刚 陈昊 何嘉弘 TAN Fenglei;ZHU Chao;XU Gang;CHEN Hao;HE Jiahong(State Grid Jiangsu Electric Power Co.,Ltd.Maintenance Branch Company,Nanjing 211102,China;Department of Electrical Engineering,Southeast University,Nanjing 210096,China)
机构地区:[1]国网江苏省电力有限公司检修分公司,南京211102 [2]东南大学电气工程学院,南京210096
出 处:《高电压技术》2022年第1期298-306,共9页High Voltage Engineering
基 金:国家自然科学基金(51807028)。
摘 要:针对特高压变压器顶层油温预测精度低的问题,提出一种基于解耦分析和欧式距离的特高压变压器顶层油温预测方法,该方法采用通径分析原理实现各因素变量的解耦分析。首先采用横向分析与纵向分析,计算温度、湿度、风速、气压、降雨量、光照强度、横向日期、纵向时刻以及负荷等9种因素变量的直接通径系数,选择得到特高压变压器顶层油温的主要影响因素变量。然后采用基于直接通径系数加权优化的欧式距离分析气象、时间和负荷3种因素的相关度,利用线性加权原理得到综合相关度。最后在充分研究基于综合相关度选择相似时刻步骤的基础上,利用支持向量机和线性加权法实现特高压变压器顶层油温的预测。算例结果表明:该方法预测特高压主体变顶层油温的平均误差为2.19%,预测特高压调补变顶层油温的平均误差为2.50%,具有较高的预测精度,验证了方法的有效性与可行性。To solve the problems of low accuracy in forecasting ultra-high-voltage(UHV)transformer top oil temperature,a method of forecasting UHV transformer top oil temperature based on decoupling analysis and Euclidean distance is proposed,in which the path analysis is adopted to realize the decoupling analysis of various factors.Firstly,the direct path coefficients of 9 factors,including temperature,humidity,wind speed,air pressure,rainfall,light intensity,horizontal date,vertical time,and load,are calculated by horizontal analysis and vertical analysis,and the main factors affecting UHV transformer top oil temperature are selected.Then,the correlation of three factors,including weather,time,and load,are analyzed by using Euclidean distance based on weighted optimization of direct path coefficients,and the comprehensive correlation is obtained by using linear weighting principle.Finally,on the basis of fully researching the steps of selecting similar hour based on comprehensive correlation,the method of UHV transformer top oil temperature forecasting is realized by using the support vector machine and linear weighting method.The results show that the average error of the method for forecasting UHV main transformer top oil temperature is 2.19%,and forecasting UHV regulator transformer top oil temperature is 2.50%.The method has high forecasting accuracy,which verifies its feasibility and validity.
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