Abnormal electric quantity data identification method based on limit value learning

Abstract

The invention discloses an abnormal electric quantity data identification method based on limit value learning. The method comprises the following steps: analyzing abnormal electric quantity data to obtain the type and identification algorithm of the abnormal electric quantity data; then, analyzing and researching an OnClassSVM algorithm; learning the identification limit value of the abnormal electric quantity data to obtain a limit value learning table, checking the abnormal electric quantity data of the historical data through the limit value learning table, and then checking an outlier inthe historical data through analyzing a density-based clustering algorithm DBSCAN algorithm to realize abnormal electric quantity data identification based on limit value learning; finally, analyzingand researching the same density-based clustering algorithm LOF algorithm, combining the two density-based clustering algorithms to carry out an experiment, and carrying out outlier identification onthe multi-dimensional data to realize the multi-dimensional electric quantity data outlier identification based on the density clustering algorithm.

Description

technical field [0001] The invention belongs to the technical field of power data mining, and in particular relates to a method for identifying abnormal power data based on limit value learning. Background technique [0002] The significance of big data technology is to dig out its potential value through the analysis and processing of massive data, and apply it to future production and life. From a technical point of view, the current big data is mainly closely connected with cloud computing, because big data cannot be processed by a single computer, and distributed processing must be adopted. [0003] Due to reasons such as metering transformers, electric energy meters, collection terminal equipment, communication equipment, electromagnetic interference, and software protocol analysis in the traditional power data processing process, the collected original power data will be incomplete and unreliable, and the abnormal power data will be too high. Too much will lead to ina...

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a method for identifying abnormal electric quantity data based on limit value learning ("big data technology" involved in the present invention refers to the method used in the field of electric power systems) in view of the current situation of incomplete and unreliable electric quantity data The big data analysis technology method mainly refers to the data mining technology, and does not involve the big data technology in the relatively professional computer field), including the following steps:

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