面向多源异构的电力工程数据融合处理技术研究  

Research on power engineering data fusion processing technology for multi⁃source heterogeneity

作　　者：费英群 田林 FEI Yingqun;TIAN Lin(Huzhou Power Supply Company,State Grid Zhejiang Electric Power Co.,Ltd.,Huzhou 313000,China)

机构地区：[1]国网浙江省电力有限公司湖州供电公司,浙江湖州313000

出　　处：《电子设计工程》2025年第1期104-108,共5页Electronic Design Engineering

基　　金：浙江省科技计划项目(S2022RCDD2C0496)。

摘　　要：随着电力工程中自动化、信息化设备的日益增多,对电力工程数据的分析与处理能力有了更高的要求。针对这一问题,文中开展了面向多源异构的电力工程数据融合处理技术研究。通过预先设计好的数据框架进行关联操作,实现数据监测与处理分析。为了提高整体数据与局部数据之间的协调性,对融合数据进行边缘自适应增强处理,结合电力工程定值数据处理方法将样本数据分解为多个子数据集,利用神经网络模型分类融合,采用Reduce机制对融合后的数据进行合并处理,输出结果,从而提高数据融合的效率。以某地区电力工程数据集为样本进行的分析结果表明,所提方法在处理数据时具有更高的效率,产生的绝对误差仅为1.675%,且更适用于大容量数据的场景。With the increasing number of automation and information technology equipment in power engineering,there are higher requirements for the analysis and processing of power engineering data.In response to this issue,the article conducted research on power engineering data fusion processing technology for multi⁃source heterogeneity.By performing correlation operations in a pre designed data framework,data monitoring and processing analysis can be achieved.In order to improve the coordination between the overall data and local data,edge adaptive enhancement is applied to the fused data.The power engineering fixed value data processing method is integrated,and the sample data is decomposed into multiple sub datasets.A neural network model is used for classification and fusion,and the Reduce mechanism is used to merge and process the fused data,ultimately outputting results to improve the efficiency of data fusion.The analysis results of a power engineering dataset in a region show that the proposed method is more efficient in processing data,and the absolute error generated is only 1.675%,and it is more suitable for scenarios with large data volume.

关 键 词：多源异构 Reduce机制 数据融合 边缘自适应增强 

分 类 号：TP807[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]