Active power distribution network fault risk early warning method and system based on data mining

A distribution network fault and data mining technology, applied in the field of distribution network, can solve the problem that new energy is susceptible to the influence of natural environment such as temperature and light, as well as the constraints of its own intermittent characteristics, the operation status of the distribution network system is not clear, and the output Uncertainty of the situation and other issues, to achieve the effect of fast speed, precise warning and high accuracy

Pending Publication Date: 2022-04-08
NANJING UNIV OF POSTS & TELECOMM +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] As a large number of new energy sources are connected to the grid, the traditional passive distribution network has begun to transform into an active distribution network; new energy is easily affected by the natural environment such as temperature and light, and is constrained by its own intermittent characteristics, and its output situation has great differences. Uncertainty; it causes uncertainty to the operation of the overall distribution network system, making it more complicated, and brings great challenges to the safety, stability and economy of the distribution network; at the same time, the coupling of various types of characteristic information is also There are certain risks, so the traditional distribution network fault risk early warning method can no longer meet the demand

Method used

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  • Active power distribution network fault risk early warning method and system based on data mining
  • Active power distribution network fault risk early warning method and system based on data mining
  • Active power distribution network fault risk early warning method and system based on data mining

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Embodiment 1

[0049] Such as figure 1 As shown, the embodiment of the present invention provides a data mining-based active distribution network fault risk early warning method, including the following steps:

[0050]S1. Obtain fault characteristics of the active distribution network, and process the fault characteristics to obtain fault data values.

[0051] Using PCA-Relief combination algorithm to identify and extract fault features.

[0052] The main factors causing the risk of failure are analyzed through the historical fault records and defect data of the active distribution network, and the PCA (Principal Component Analysis) method is used for data preprocessing.

[0053] Using SPSS data processing software to conduct principal component analysis on 50 groups of influencing factors of historical samples, 50 influencing factors correspond to 50 characteristic indicators, the analysis process is as follows:

[0054] a) Construct the original data matrix X for variable sampling n×p :...

Embodiment 2

[0129] A data mining-based active distribution network fault risk early warning system provided by an embodiment of the present invention includes:

[0130] Input acquisition module: used to obtain the fault characteristics of the active distribution network, and use the principal component analysis method to preprocess the fault characteristics to obtain the fault data value;

[0131] Early warning model operation module: used to input the fault data value into the pre-established early warning model, output the early warning index and its predicted value, and the early warning model is optimized by using the particle swarm optimization algorithm;

[0132] Assignment calculation module: used to assign the subjective weight and objective weight of the early warning index, and then use the combination algorithm of triangular fuzzy number analytic hierarchy process and entropy weight method to calculate the comprehensive evaluation index value;

[0133] Early warning module: it ...

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Abstract

The invention discloses an active power distribution network fault risk early warning method and system based on data mining, and belongs to the technical field of power distribution networks, and the method comprises the steps: obtaining fault features of an active power distribution network, and processing the fault features to obtain a fault data value; inputting the fault data value into a pre-established early warning model, and outputting an early warning index and a predicted value thereof; carrying out assignment on subjective weights and objective weights of the early warning indexes, and then calculating a comprehensive evaluation index value by adopting a combined algorithm of a triangular fuzzy number analytic hierarchy process and an entropy weight method; the comprehensive evaluation index value is compared with a preset risk grading standard threshold value, the obtained risk grade is an early warning result, and the relative error rate of the comprehensive evaluation index value and the early warning index prediction value is the early warning accuracy degree of the early warning model; the early warning speed is high, the early warning is more accurate, the incompleteness of a single assignment method is avoided, and the influence of coupling of various kinds of information is weakened.

Description

technical field [0001] The invention relates to a data mining-based fault risk early warning method and system for an active distribution network, belonging to the technical field of distribution networks. Background technique [0002] As a large number of new energy sources are connected to the grid, the traditional passive distribution network has begun to transform into an active distribution network; new energy is easily affected by the natural environment such as temperature and light, and is constrained by its own intermittent characteristics, and its output situation has great differences. Uncertainty; it causes uncertainty to the operation of the overall distribution network system, making it more complicated, and brings great challenges to the safety, stability and economy of the distribution network; at the same time, the coupling of various types of characteristic information is also There are certain risks, so the traditional distribution network fault risk early...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06K9/62G06N3/00
Inventor 岳东姚沪升窦春霞张智俊丁孝华赵景涛郑舒黄堃
Owner NANJING UNIV OF POSTS & TELECOMM
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