电力系统及其自动化学报2026，Vol.38Issue(8)：102-112,124,12.DOI:10.19635/j.cnki.csu-epsa.001731
计量时序驱动的台区变压器异常监测方法
Metering Time-series Driven Method for Anomaly Monitoring of Distribution Transformers
摘要
Abstract
The health states of distribution transformers are critical to the safe operation and regulation efficiency of dis-tribution networks.To address the challenge that the traditional methods struggle to map the transformers'health states due to data quality issues and limited characterization dimensions,a metering time-series driven anomaly monitoring method for distribution transformers is proposed in this paper.First,a multi-dimensional evaluation index system is con-structed based on the metering data,and the health levels are classified accordingly.Second,an adaptive sliding window is introduced to achieve the optimal sample segmentation,and the feature is extracted in depth with the combination of Bayesian optimization algorithm and temporal convolutional network-bidirectional long short-term memory network.In addition,a health baseline is also constructed.Finally,a dual-threshold strategy is employed to implement joint deter-mination of indicator residuals between the measured data and the health baseline,significantly improving the accuracy of anomaly detection.The validation results based on actual distribution substations demonstrate that the proposed meth-od can effectively identify the trend anomalies caused by health degradation in metering data streams,achieving an im-provement of 8.9%in the detection accuracy compared with the traditional threshold criterion method.This method en-ables rapid assessment of transformer conditions and provides a technically feasible solution with high engineering adaptability for anomaly monitoring of equipment in smart distribution networks.关键词
计量数据/自适应滑动窗口/时间卷积网络/双向长短时记忆网络/变压器异常监测Key words
metering data/adaptive sliding window/temporal convolutional network/bidirectional long short-term memory network/transformer anomaly monitoring分类
信息技术与安全科学引用本文复制引用
姚俊,许星煜,陶海洋,武韶辉,妥振文,赵永臻..计量时序驱动的台区变压器异常监测方法[J].电力系统及其自动化学报,2026,38(8):102-112,124,12.基金项目
国网甘肃省电力公司科技项目(522706250005). （522706250005）
