基于大数据的数字化电网中台业务运行态势自动化感知方法

Big Data-Based Automatic Sensing Method for Business Operation Situation of Mid-Stations in Digital Power Grid

随着电网运行的数字化转型,传统方法的感知功能对中台业务运行态势的要素提取不充分,导致对中台业务运行态势数据的正确检测率较低,影响了数据量的感知,因此研究基于大数据的数字化电网中台业务运行态势自动化感知方法。基于大数据提取中台业务运行态势要素,综合多项检测信息。采用模糊层次法评估运行态势,整体把握中台业务的运行态势情况。建立数字化中台业务运行态势自动化感知模型,揭示中台业务运行态势的变化趋势。经实验论证分析,本文方法的正确检测率较高,与传统方法相比具有更好的感知功能。

With the digital transformation of power grid operation,the perception function of traditional methods is insufficient to extract the elements of the business operation situation of China and Taiwan,resulting in the correct detection rate of the business operation situation data of the China and Taiwan business is not high enough,which affects the perception of data volume.Research A big data-based automatic sensing method of the business operation situation in the middle of the digital power grid.Based on big data,it extracts the elements of the business operation situation of China and Taiwan,and integrates multiple detection information.Fuzzy analytic hierarchy process evaluates the operation situation,and overall grasps the operation situation of the middle and taiwan business.Establish an automated perception model of digital middle and Taiwan business operation situation to reveal the trend of changes in the operation situation of the middle and Taiwan business.After experimental demonstration and analysis,the correct detection rate of the method in this paper is higher,and compared with the traditional method,it has a better perception function.