A grid fault diagnosis method based on multi-element grid database

A technology for power grid faults and diagnosis methods, which is applied in database models, electrical digital data processing, structured data retrieval, etc. The effect of reporting rate and improving accuracy

Active Publication Date: 2021-11-19
STATE GRID SHAANXI ELECTRIC POWER RES INST +3
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The grid scale is getting bigger and bigger, and various energy structures are becoming more and more complex. The traditional fault diagnosis function based on a single data source can no longer meet the needs of grid fault diagnosis. A new grid fault diagnosis method is urgently needed.

Method used

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  • A grid fault diagnosis method based on multi-element grid database
  • A grid fault diagnosis method based on multi-element grid database
  • A grid fault diagnosis method based on multi-element grid database

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Embodiment Construction

[0032] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0033] see figure 1 with figure 2 , a kind of grid fault diagnosis method based on multi-element grid database of the present invention, realizes according to the following steps:

[0034] Step 1. Extract fault data from the database, and establish a fault sample training feature matrix; each fault category in the fault sample training feature matrix is ​​in one-to-one correspondence with its sample feature data.

[0035] Step 1 specifically includes:

[0036] In the multi-element power grid, the fault data is ex...

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Abstract

The invention discloses a power grid fault diagnosis method based on a multi-element grid database, comprising: collecting fault data of a multi-element power grid, establishing a fault sample training feature matrix according to the fault data; obtaining the test data Y to be diagnosed through the minimum norm constraint, obtaining Sparse coefficient x; obtain the test sample data according to the sparse coefficient x, calculate the minimum residual error between the test sample data and each fault sample feature data in the fault sample training feature matrix, compare the minimum value of the minimum residual error, determine the fault category, and complete Grid fault diagnosis. The power grid fault diagnosis method of the invention can improve the accuracy of fault diagnosis and reduce the rate of fault false alarms.

Description

technical field [0001] The invention belongs to the technical field of multiple grid fault diagnosis, and in particular relates to a grid fault diagnosis method based on a multiple grid database. Background technique [0002] Energy conservation and emission reduction is a common challenge and an important issue facing the world. The Chinese government attaches great importance to energy conservation and emission reduction in the power industry, and proposes to implement energy-saving power generation dispatching in the power field to improve energy efficiency in the power industry, reduce environmental pollution, and promote energy conservation. and power structure adjustment, wind power and photovoltaics are the most mature intermittent energy utilization methods. Northwest is a key development area for new energy power generation. With the rapid development of wind power, photovoltaic and other new energy power generation in Northwest Power Grid, the power structure has u...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/00G01R31/50G06F16/2458G06F16/28
CPCG01R31/00G01R31/50
Inventor 解振学吴子豪王永庆王磊黑新宏王若谷魏昊焜尚渭萍张燕平师鹏李明田刚旗李华李广万天虎白欢周艺环张小平王辰曦唐露甜李高阳杜楠梁勇赵嘉刘桐
Owner STATE GRID SHAANXI ELECTRIC POWER RES INST
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