Power transmission and transformation suspicious data screening method and device based on random forest model

Abstract

The invention provides a power transmission and transformation suspicious data screening method and device based on a random forest model, and the method comprises the steps: S1, selecting data of multiple dimensions according to the category and periodicity rule of power transmission and transformation equipment, and building a data feature item; S2, distributing different weights for the data according to the sampling time, respectively marking known normal data and abnormal data as positive and negative samples, and dividing a data set into K parts; S3, training a random forest model by adopting a K-fold cross validation method, iteratively adjusting the number T of trees in the random forest by taking an average value of positive and negative sample accuracy as a target, and obtaininga value of T when an index is optimal; and S4, screening suspicious data by using the trained model. Power transmission and transformation equipment is used as an object to construct a suspicious datascreening object, a random forest model of an optimization training set is used for learning data rules from a large amount of historical sampling data, power transmission and transformation suspicious data identification and screening are achieved, the workload of manual screening is reduced, and the data quality of an electric power regulation and control system is improved.

Description

technical field [0001] The invention relates to a random forest model-based power transmission and transformation suspicious data screening method, which is used for correctness screening of power transmission and transformation sampling data in an automation system, and belongs to the technical field of power grids. Background technique [0002] With the continuous development of smart grids, the types and scales of basic data collection of power transmission and transformation equipment by modern power dispatching automation operation systems are also expanding. However, due to different infrastructure construction periods and different collection methods, the data quality levels are also different. Similarly, if special circumstances such as equipment failure occur, it is likely to cause missing or abnormal data to enter the data storage system. Correct and reliable sampling data is the basis for data analysis and mining of power system applications. In order to ensure th...

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Problems solved by technology

The advantage of this method is that it is simple and easy to operate, but the disadvantage is that the limit value is often a fixed value, which cannot consider the characteristics of periodic and seasonal changes in power data, and does not consider the correlation between multiple measurements of a device. characteristics, in addition, the limit value is also relatively weak to the perception of jumps

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