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Power grid equipment state abnormity monitoring method and system based on big data

A technology for grid equipment and abnormal monitoring, applied in database indexing, data processing applications, structured data retrieval, etc., can solve problems such as not being able to adapt to the development requirements of extra-large power grids, and achieve the goals of ensuring safe and stable operation, improving efficiency, and lowering professional thresholds Effect

Pending Publication Date: 2019-07-19
ANHUI ELECTRIC POWER FUYANG POWER SUPPLY +1
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  • Application Information

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Problems solved by technology

[0002] With the construction of UHV power grids and the rapid development of new energy sources, major changes have taken place in the operation characteristics of power grids. The online monitoring and fault diagnosis methods of power grid equipment status based on traditional data processing technology can no longer meet the development requirements of the integrated operation of extra large power grids.

Method used

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  • Power grid equipment state abnormity monitoring method and system based on big data
  • Power grid equipment state abnormity monitoring method and system based on big data
  • Power grid equipment state abnormity monitoring method and system based on big data

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Embodiment 1

[0052] Such as Figure 1-3 As shown, a method for monitoring anomalies in the status of power grid equipment based on big data in this embodiment includes the following steps:

[0053]S1. Data collection, connecting the data related to the operation status of the grid equipment to the data processing center as the basis for subsequent processing and analysis; the operation status data of the grid equipment comes from the time series database, real-time database, and commercial database in the grid dispatching control system; Among them, the data related to the equipment status includes three categories: steady-state data (switch displacement, accident total signal, protection action signal, etc.), dynamic data (synchronized phasor data collected in real time by the PMU device) and transient data (fault recording). ; Wherein the mode of data access includes ETL tools and stream computing, and the ETL tools are mainly used for extracting, converting and loading data of commercia...

Embodiment 2

[0069] The present invention also discloses a big data-based abnormality monitoring system for power grid equipment. The system includes the following modules:

[0070] Data acquisition module: used to connect the data related to the operation state of the power grid equipment to the data processing center as the basis for subsequent processing and analysis; in the data acquisition module: the data of the operation state of the power grid equipment comes from the time sequence In databases, real-time databases, and commercial databases; the data related to equipment status includes steady-state data (switch displacement, total accident signal, protection action signal, etc.), dynamic data (synchrophasor data collected in real time by PMU devices) and transient state data. Three categories of data (fault recording); the data access methods include ETL tools and flow computing, and the ETL tools are mainly used for the extraction, conversion and loading of commercial databases an...

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Abstract

The invention discloses a power grid equipment state abnormity monitoring method and system based on big data, and the method comprises the steps: data collection: enabling the data related to the operation state of power grid equipment to be accessed to a data processing center, and enabling the data to serve as a basis for subsequent processing and analysis; data preprocessing: preprocessing theoperation state data of the power grid equipment through data cleaning, data classification, data fusion and data normalization; and equipment state abnormity analysis: constructing a high-dimensional random matrix, drawing and observing a state related curve graph and an annular graph, and judging the equipment state abnormity. The method and system can timely discover the abnormity of the operation state of the power grid equipment, assist state monitoring and abnormity identification of the power grid equipment, and guarantee the safe and stable operation of the power grid. Structured datacleaning and analysis are carried out by adopting a partial mathematical modeling mode based on a high-dimensional random matrix, the topological structure and parameter information of the power system do not need to be known during analysis, the professional threshold of data analysis and mining is reduced, and meanwhile the abnormal recognition efficiency is improved.

Description

technical field [0001] The invention relates to the field of electric power system dispatching automation, in particular to a method and system for monitoring abnormal state of power grid equipment based on big data. Background technique [0002] With the construction of UHV power grids and the rapid development of new energy sources, major changes have taken place in the operating characteristics of power grids. The online monitoring and fault diagnosis methods of power grid equipment status based on traditional data processing technology can no longer meet the development requirements of the integrated operation of extra large power grids. At the same time, with the improvement of power grid collection and monitoring capabilities, the grid operation history data, SCADA data, and status monitoring data stored in the main station of the smart grid dispatching control system show a variety of data forms, large volume, multiple dimensions, and low value density. Such as the ch...

Claims

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Application Information

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IPC IPC(8): G06F16/215G06F16/22G06F16/2458G06Q50/06
CPCG06F16/215G06F16/2291G06F16/2465G06Q50/06
Inventor 胡松陈琼芳孙治华马骏刘素芳范宏宗薇薇李华军周晓梅张莹莹贾德伟李婷婷李昊刘健王冬冬
Owner ANHUI ELECTRIC POWER FUYANG POWER SUPPLY
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