基于LSTM模型的变压器顶层油温预测方法  

Prediction Method of Transformer Top Oil Temperature Based on LSTM Model

作　　者：董雪情 荆澜涛 田瑞 董向阳 DONG Xueqing;JING Lantao;TIAN Rui;DONG Xiangyang(School of Electric Power,Shenyang Institute of Engineering,Shenyang 110136,China;EHV Transmission Company,State Grid Liaoning Electric Power Co.,Ltd.,Shenyang 110002,China;Liaoyang Power Supply Company,State Grid Liaoning Electric Power Co.,Ltd.,Liaoyang 111000,China)

机构地区：[1]沈阳工程学院电力学院,沈阳110136 [2]国网辽宁省电力有限公司超高压分公司,沈阳110002 [3]国网辽宁省电力有限公司辽阳供电公司,辽宁辽阳111000

出　　处：《电力学报》2023年第1期38-45,共8页Journal of Electric Power

基　　金：国网吉林省电力有限公司检修公司科技项目(SGJLJX00YJJS2000301)。

摘　　要：变压器油温是直接反映变压器散热性能的指标,准确预测变压器顶层油温有利于监测其运行情况。通过分析传统变压器顶层油温数学模型,综合考虑负载率与环境温度对油温的影响,确定以负荷数据峰值与谷值的有功功率、无功功率和环境温度作为特征量,提出了一种基于长短时记忆(Long Short Term Memory Network,LSTM)网络算法的变压器顶层油温预测模型。以变电站真实数据做实例仿真分析,训练所提的LSTM预测模型,并选取5个随机样本进行预测;同时,分别搭建BP神经网络(BPNN)和循环神经网络(RNN)预测模型对相同样本做预测,并截取前30时刻预测数据与LSTM模型的预测值做对比。仿真结果表明,基于LSTM的温度预测模型的计算精度最高,误差率控制在5%以内,预测值与实际值变化趋势基本一致。该模型可有效实现变压器顶层油温的预测。Transformer oil temperature is an index that directly reflects the heat dissipation performance of trans⁃former.Accurate prediction about top oil temperature of the transformer is instrumental in monitoring its opera⁃tion.By analyzing the traditional mathematical model of top oil temperature of the transformer,considering the influence of load rate and ambient temperature on oil temperature,and determining the active power,reactive power and ambient temperature of load data peak and valley as the characteristic quantity,a prediction model of transformer top oil temperature based on long short term memory(LSTM)network is proposed.Taking the re⁃al data of substation as an example,the proposed LSTM prediction model is trained,and 5 random samples is selected for prediction;the BP neural network(BPNN)and the recurrent neural network(RNN)prediction models are built respectively to predict the same samples and intercept the prediction data of the first 30 min⁃utes,and compared with the LSTM model.The simulation results show that the temperature prediction model based on LSTM has the highest calculation accuracy,the error rate is controlled within 5%,the predictive val⁃ue is basically consistent with the actual value,and the temperature prediction can be effectively realized.

关 键 词：变压器 顶层油温预测 长短时记忆网络 机器学习 

分 类 号：TM411[电气工程—电器]