Power grid equipment data flow cleaning method based on association rules

A technology of power grid equipment and data flow, applied in the direction of electric digital data processing, data processing application, digital data information retrieval, etc., can solve the problem of increasing the complexity and economic cost of power grid maintenance, maintenance and scheduling work, large errors, and affecting the power system Operation and other issues

Pending Publication Date: 2019-08-30
NORTHEAST DIANLI UNIVERSITY
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Problems solved by technology

[0002] At present, the online data flow cleaning for power grid equipment in power system has always been one of the important functions of power system state estimation, and the existence of bad data in the data makes it impossible to realize accurate and effective monitoring of power grid equipment
However, when performing online data monitoring on power grid equipment, there may be abnormalities in data acquisition equipment,

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  • Power grid equipment data flow cleaning method based on association rules
  • Power grid equipment data flow cleaning method based on association rules
  • Power grid equipment data flow cleaning method based on association rules

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Embodiment Construction

[0072] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0073] In the data flow formed by the collection of online monitoring data sequences of various grid equipment, the causes of abnormal data can be divided into two categories: bad data generated by abnormal collection equipment, or abnormal data formed by grid equipment failure. The invention mainly screens and cleans the bad data formed by the abnormality of the collection equipment, and retains the abnormal data of the equipment.

[0074] refer to figure 1 ,Such as figure 1 As shown, an association rule-based method for cleaning data streams of power grid equipment includes the following steps:...

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Abstract

The invention discloses a power grid equipment data flow cleaning method based on an association rule, which comprises the following steps of: calculating association strength of historical data of each data sequence in a data flow by utilizing an Apriorri algorithm, and outputting an association relationship among different data sequences; using an abnormal data screening algorithm based on a sliding time window to detect the data sequences with weak correlation strength one by one; carrying out abnormal data identification processing on the data sequence with higher correlation degree at thesame time; and applying the neural networks with multiple wavelet basis functions to data cleaning to complete combined prediction. The data flow cleaning method is accurate in power grid equipment risk assessment and stable and reliable in data.

Description

technical field [0001] The invention relates to data processing of grid equipment, in particular to a method for cleaning data flow of grid equipment based on association rules. Background technique [0002] At present, online data flow cleaning for power grid equipment in power system has always been one of the important functions of power system state estimation, and the existence of bad data in the data makes it impossible to realize accurate and effective monitoring of power grid equipment. However, in the online data monitoring of power grid equipment, there may be abnormalities in data acquisition equipment, operational errors or blockage of data transmission channels, etc., resulting in bad data with large errors. Because the emergence of bad data caused by the above reasons causes a large deviation in the assessment of the risk of power grid equipment, which in turn increases the complexity and economic cost of power grid maintenance, overhaul and dispatch work, thus...

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Application Information

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IPC IPC(8): G06F16/215G06F16/2458G06Q10/06G06Q50/06
CPCG06F16/215G06F16/2462G06F16/2474G06Q10/0635G06Q10/0639G06Q50/06
Inventor 娄建楼王磊时丹丹曲朝阳张鹏梁丰
Owner NORTHEAST DIANLI UNIVERSITY
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