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Transformer area line loss analysis method, device and system

An analysis method and line loss technology, applied in data processing applications, instruments, calculations, etc., can solve problems such as poor accuracy and inability to automatically determine line loss abnormalities, and achieve the effect of reasonable line loss classification

Inactive Publication Date: 2022-03-25
NARI INFORMATION & COMM TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can understand the line loss of the entire station area to a certain extent, but when the line loss is abnormal, it cannot automatically determine the abnormality of the line loss
[0003] Most of the methods for line loss analysis in the prior art refer to the big data analysis method of unsupervised learning to realize the line loss analysis of the station area. The advantage is that it is more intelligent and automatic than the existing actual solution, but it can only Analyze the total line loss in the station area, and the accuracy is not good

Method used

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  • Transformer area line loss analysis method, device and system
  • Transformer area line loss analysis method, device and system
  • Transformer area line loss analysis method, device and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0067] An embodiment of the present invention provides a line loss analysis method in a station area, including the following steps:

[0068] (1) Obtain a set of line loss training samples with labels;

[0069] (2) Obtain the line loss collection without labels;

[0070] (3) Calculate the Euclidean distance between each user line loss without a label and each piece of data in the line loss training sample set, and sort all the obtained Euclidean distances;

[0071] (4) For each user, select the previous Euclidean distance respectively, and calculate the corresponding Euclidean weight distance;

[0072] (5) For the classifications involved in k Euclidean distances, calculate the Euclidean distance weight sum corresponding to each classification;

[0073] (6) Use the Euclidean distance weight and the largest classification label as the classification of the unlabeled line loss data.

[0074] In a specific implementation manner of the embodiment of the present invention, the a...

Embodiment 2

[0111] Based on the same inventive concept as in Embodiment 1, an embodiment of the present invention provides a line loss analysis device in a station area, including:

[0112] The first obtaining module is used to obtain a set of line loss training samples with labels;

[0113] The second obtaining module is used to obtain a line loss set without labels;

[0114] The Euclidean distance calculation module is used to calculate the Euclidean distance between each user line loss without a label and each piece of data in the line loss training sample set, and sort all the obtained Euclidean distances;

[0115]The Euclidean weight distance calculation module is used to select the first k Euclidean distances for each user, and calculate the corresponding Euclidean weight distance;

[0116] The Euclidean distance weight and calculation module is used to calculate the Euclidean distance weight sum corresponding to each classification for the classifications involved in k Euclidean d...

Embodiment 3

[0120] Based on the same inventive concept as in Embodiment 1, an embodiment of the present invention provides a line loss analysis system in a station area, including:

[0121] processor;

[0122] a memory on which is stored a computer program executable on said processor;

[0123] Wherein, when the computer program is executed by the processor, the method according to any one of Embodiment 1 is realized.

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Abstract

The invention discloses a transformer area line loss analysis method, device and system. The method comprises the following steps: acquiring a line loss training sample set with labels; acquiring a line loss set without labels; calculating the Euclidean distance between the line loss of each user without labels and each piece of data in the line loss training sample set, and sorting all obtained Euclidean distances; for each user, respectively selecting first k Euclidean distances, and calculating a corresponding Euclidean weight distance; for the classifications related to the k Euclidean distances, calculating Euclidean distance weight sums corresponding to the classifications; and taking the classification label with the maximum Euclidean distance weight sum as the classification of the line loss data without the label. According to the invention, the artificial intelligence algorithm is used to effectively analyze the line loss condition of the users in the power distribution area, so that fine management of the power distribution area is facilitated.

Description

technical field [0001] The invention belongs to the technical field of line loss analysis in a station area, and in particular relates to a line loss analysis method, device and system in a station area. Background technique [0002] The line loss of the distribution station area is very important. It is the basis for the fine management of the station area. line loss calculation. The calculation method of the line loss in the station area is the total input power of the distribution transformer in the station area minus the total input power of each user, and the difference is the line loss in the station area. The difference divided by the input power of the transformer in the distribution station area is the total loss rate of the station area. This method can understand the line loss of the entire station area to a certain extent, but when the line loss is abnormal, it cannot automatically determine the abnormality of the line loss. [0003] Most of the methods for li...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/0639G06Q50/06G06F18/22G06F18/241G06F18/214
Inventor 施健胡游君邱玉祥刘军蔡世龙魏训虎潘安顺富思樊泽宇陈克朋周忠冉张文鹏李马峰张俊杰顾亚林刘皓邱文元李洋沈耀威万明万国栋魏芃鄂龙慧朱洪森李宁远韩冬徐顺旺史梦杰朱子葳张华锋周鹏张磊晁凯宋凯赵强吴垠杨勰张敏杰胡楠杨清松王玉敏刘赛甘岚高雪邹徐熹
Owner NARI INFORMATION & COMM TECH