Power monitoring information intelligent extraction and classification processing method

Abstract

The invention relates to a power monitoring information intelligent extraction and classification processing method. The method comprises the following steps of S1, extracting information of a monitoring system, and finding an accident and abnormal information table from an EMS database; S2, screening the monitoring information; S3, acquiring result information screened and defined in the step S2,acquiring alarm contents, segmenting the alarm contents according to rules, and extracting alarm time, a plant station name, an information name, an action type and an interval ID; S4, judging a state of an interval according to the acquired interval ID, and shielding information of a cold standby state interval; S5, further shielding information which does not need to be processed by editing a logical relationship between keywords; and S6, storing the information and displaying a result: storing the screened and processed information in a server, and displaying the screening result. According to the method, accidents and the abnormal information in the monitoring system are extracted in real time and are displayed in a classified way, so that the processing efficiency is improved.

Description

Technical field [0001] The invention relates to the technical field of monitoring big data processing, in particular to a method for intelligently extracting and classifying power monitoring information. Background technique [0002] With the full implementation of the integration of regulation and control in Guangdong Power Grid, monitors need to manage the massive data of the entire region's power grid, and ensure the timely elimination of defects and ensure the safe and stable operation of the power grid by filling in, statistics, analyzing, and tracking monitoring data. However, the monitoring system can only be seen and cannot be moved. All data entry is done manually on the office computer. The statistical analysis methods are backward and often need to work overtime to complete, which consumes a lot of time and energy. Sometimes the data cannot be guaranteed. accuracy. [0003] In particular, during a thunderstorm, the power grid has multiple faults in a short period of tim...

AI Technical Summary

Problems solved by technology

However, the monitoring system can only be viewed but cannot be moved. All data entry is manually edited on the office computer. The statistical analysis method is backward and often requires overtime work, which consumes a lot of time and energy. Sometimes the data cannot be guaranteed. accuracy

[0003] In particular, during thunderstorms, multiple faults occur in the power grid in a short period of time, and a large amount of data washes out the warning window. We not only need to filter out useful accident and abnormal information from the numerous information in the warning window, but also judge and deal with the accident within a certain period of time. Stare at the screen and manually record one by one to prevent the omission of abnormal information. Multiple tasks overlap each other, often in a hurry, and there is a risk of missing monitoring

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