摘要
本文作者研究基于卡尔曼滤波算法的油浸式变压器绕组热点温度预测模型,为有效分析此类变压器绝缘寿命提供依据。采集影响绕组热点温度的相关数据并构成基础数据库,构建变压器绕组线性离散热点温度模型,通过向该模型内叠加基础数据库内的噪声数据,获得热点温度的状态与测量方程,经由两种方程运算得出绕组的历史热点温度值,以此温度值作为输入参量,结合卡尔曼滤波算法构建变压器绕组热点温度预测模型,通过该模型中预测与校正两阶段的迭代运算,得到绕组热点温度的最佳实时预测结果输出。结果显示,该模型可预测出不同运行负载下的油浸式变压器绕组热点温度,得到平滑消噪且与实测数据相吻合的预测值;依据预测结果得知,变压器的绕组热点温度与季节、环境温度、负载均存在一定的相关性。
The prediction model of winding hot spot temperature of oil-immersed trans former based on Kalman filter algorithm is studied to provide a basis for effective analy sis of insulation life of this kind of transformer.Affect winding hot spot temperature relat ed data and database,based on linear discrete transformer winding hot spot tempera ture model was constructed,through to the database in the basis of noise data in the model,get hot spot temperature state and measurement equations,through two equa tions operation it is concluded that the history of the winding hot spot temperature,this temperature as input parameters,Combined with kalman filter algorithm to construct transformer winding hot spot temperature prediction model,through the model prediction and correction in two stages of the iterative calculation,the winding hot spot tempera ture of optimal output real-time prediction results,the results show that the model can predict under different operation load of oil-immersed transformer winding hot spot tem perature,get smoothing and denoising is consistent with experimental data and the pre dicted value;According to the prediction results,the winding hot spot temperature of the transformer has a certain correlation with the season,the environment temperature and the load.
作者
吕志华
顾雅青
LYU Zhihua;GU Yaqing(Shangdong Huayu University of Technology,Dezhou 253034,China)
出处
《变压器》
2024年第4期44-49,共6页
Transformer
基金
山东省教育厅“山东省高等教育本科教学改革研究项目”重点项目(Z2021212)。
关键词
油浸式变压器
卡尔曼滤波
绕组热点温度
Oil-immersed transformer
Kalman filter
Winding hot spot temperature
