基于ELM与热模型的变压器顶层油温融合预测方法研究  

Research on Fusion Prediction of Transformer Top Oil Temperature Based on ELM and Thermal Model

作　　者：晏坤 甘景福 刘洪顺[2] 隋宜臻 贺鹏康 YAN Kun;GAN Jingfu;LIU Hongshun;SUI Yizhen;HE Pengkang(State Grid Jibei Electric Power Co.,Ltd.Tangshan Power Supply Company,Tangshan 063000,Hebei,China;School of Electrical Engineering,Shandong University,Jinan 250061,Shandong,China;Department of Electrical Engineering,North China Electric Power University,Baoding 071000,Hebei,China)

机构地区：[1]国网冀北电力有限公司唐山供电公司,河北唐山063000 [2]山东大学电气工程学院,山东济南250061 [3]华北电力大学电力工程系,河北保定071000

出　　处：《电气传动》2025年第4期82-90,共9页Electric Drive

基　　金：国家电网有限公司科技项目(5201031801CR);国网唐山供电公司科技项目(B3010322000N)。

摘　　要：提出一种采用极限学习机对IEEE导则中的变压器顶层油温热模型计算偏差进行预测和修正,从而实现对变压器顶层油温精确预测的融合预测方法。首先,介绍了变压器顶层油温热模型和极限学习机预测模型各自的特性。其次,为避免采用两级智能预测导致运算速度慢的问题,采用加权多点外推法结合负荷形态聚类算法预测变压器未来时段负载系数,作为模型的负荷预测级。最后,利用变压器顶层油温热模型获取相应的油温计算值,并利用极限学习机对计算值与实测值间的偏差进行预测,最终得到变压器顶层油温的精确预测值。搭建了仿真模型对所提方法进行了验证,仿真结果表明,所提预测方法平均预测误差率仅为0.59%,均方根误差仅为0.47℃,相比其他3种方法有更高的预测精度和稳定性,模型训练和预测时间分别只有1.21 ms和0.39 ms,证明了所提出和建立的融合预测模型具有较高的预测精度、稳定性和运算速度。A fusion prediction method was proposed to predict and correct the calculation deviation of the top transformer oil temperature model in IEEE guideline,so as to realize the more precise prediction of the transformer top oil temperature(TOT).Firstly,the characteristics of the transformer TOT model and the extreme learning machine(ELM)prediction model was introduced.Secondly,in order to avoid the problem of slow operation speed caused by double level intelligent prediction,the weighted multi-point extrapolation method combined with the load curve clustering algorithm was used to obtain the future load coefficient of the transformer which introduced as the load prediction level of the model.Finally,based on the calculation of thermal model,which the ELM was used to predict the deviation between the calculated value of thermal model and the measured value,and finally the accurate predicted value of the TOT of the transformer was obtained.The simulation platform was built and the simulation results show that the average prediction error rate of the proposed prediction method is only 0.59%,and the root mean square error is only 0.47℃.Compared with the other three methods,it has higher prediction accuracy and stability.The model training speed and prediction speed are only 1.21 ms and 0.39 ms,respectively,which proves that the fusion prediction model proposed and established has high prediction accuracy,stability and operation speed.

关 键 词：变压器顶层油温 极限学习机 热模型 融合预测 负荷形态聚类 

分 类 号：TM28[一般工业技术—材料科学与工程]