Big data platform-based power data processing method

Abstract

The invention discloses a big data platform-based power data processing method. The method comprises the steps of obtaining application data in a power network; performing collection processing on the application data according to a preset mode, and after a data form is formed, sending and storing the processed collected data in a big data platform matched with the power network; in the big data platform, performing visualization processing on the collected data and performing real-time display; performing associative condition analysis on the collected data by adopting a clustering algorithm, and finding out key power nodes in the power network; and analyzing historical fault data in the power nodes by adopting an associative rule method, performing assessment and continuous tracking on the power nodes, and when operation of a node has a fault, performing prediction to obtain fault conditions of other nodes. According to the big data platform-based power data processing method, the power data collection and utilization efficiency can be improved and the fault point prediction can be accurately realized.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a power data processing method based on a big data platform. Background technique [0002] For the electric power industry, the rapid development of the smart grid has enabled the rapid integration of information and communication technology with the production of the power grid and the management of power companies in an unprecedented breadth and depth. The information and communication system has gradually become the central nerve of the smart grid, supporting the new The production of a generation grid and the advancement and development of grid management. With the gradual popularization of subsequent smart meters, grid business data will be further enriched and expanded from the perspective of timeliness. Based on the characteristics of large capacity and multiple classifications of big data, it has been further highlighted in the massive and real-time power grid bu...

AI Technical Summary

Problems solved by technology

However, most of the existing power network monitoring technologies simply collect sensor data distributed in the power network and display the information fed back by the sensors on the terminal, which is only the most basic process of data collection-display

This traditional monitoring technology is easy to understand and clear at a glance, but the disadvantage is that it is too simple and can only achieve a simple list of power data. There is no analysis process for the data, and it is impossible to analyze the hidden information in the data. It is undoubtedly a huge waste for the massive power grid business data that can be mined

[0004] Therefore, in the process of implementing the present application, the inventor found that the existing technology has the following defects: the utilization rate of power data is low due to the simple listing of data, and at the same time, it is impossible to mine the inherent correlation and meaning of power data, and then the power data can be used in the power grid. Failure points cannot be accurately predicted and analyzed during runtime

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