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Multi-dimension and multi-level association rule based voltage sag predicting and analyzing method

A technology of voltage sag and predictive analysis, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as industrial production loss

Active Publication Date: 2013-11-20
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Actual monitoring was carried out on 550 power supply points, and the measurement results of industrial users showed that: on average, each user had 38 voltage sags per month per phase, that is, voltage sags occurred on average every day, causing serious losses to industrial production

Method used

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  • Multi-dimension and multi-level association rule based voltage sag predicting and analyzing method

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] The sample sag data source of this embodiment is to select 4052 voltage sag records from 2008 to 2012 in a provincial power quality monitoring system, and the sample includes 10 regions and 66 monitoring points. By setting different min_sup and min_conf, the corresponding strong association rules in the sag sample set can be mined, and the sag association rule base of the sample set can be constructed. Assuming several sets of prediction conditions, the possible dip prediction results can be obtained based on the rule base.

[0037] The implementation steps based on this sample are as follows:

[0038] 1. Select the mining dimension: the area where the monitoring point is located, the voltage level, the load type, the season of sag occurrence, the week of occurrence, the time period of occurrence, and the cause of sag;

[0039] 2. Discretization and hierarchical processing of sample data:

[0040] 1) Monitoring points are stratified by 10 areas: 0, 1, 2, 3, 4, 5, 6, 7...

Embodiment 2

[0059] The sample data of this embodiment is the same as that of Embodiment 1. Select monitoring points, voltage levels, load types, and sag reasons as mining dimensions.

[0060] Based on this sample, the implementation steps of the voltage sag prediction analysis method based on multi-dimensional and multi-layer association rules are as follows:

[0061] 1. Select the mining dimension: the area where the monitoring point is located, the voltage level, the load type, and the cause of the sag;

[0062] 2. Discretization and hierarchical processing of sample data:

[0063] 1) Monitoring points are stratified by 10 areas: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9;

[0064] 2) Voltage level: 0 (220V, 380V), 1 (10kV, 24), 2 (35kV), 3 (110kV), 4 (220kV), 5 (500kV, 800kV, 1000kV);

[0065] 3) Load type: 0 (normal), 1 (new energy), 2 (heavy load), 3 (sensitive user);

[0066] 4) Reasons for sag: 0 (short circuit), 1 (transformer put into operation), 2 (heavy load startup), 3 (new energy), 4 (...

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Abstract

The invention provides a multi-dimension and multi-level association rule based voltage sag predicting and analyzing method, belonging to the technical field of power quality analysis methods. The method comprises the steps of selecting the sag association rule mining dimension; discretizing historical data; mining a sag association rule according to the minimum support and minimum confidence degree; building a voltage sag association rule knowledge base; and matching the association rule to obtain the prediction conclusion. The method has the beneficial effects that the historical voltage sag association rules are mined, the strong association rules obtained after mining form the knowledge base, and the grid operation conditions probably occurring in the future serve as the prediction conditions and are input into the rule base to be matched, so that the voltage sag conditions probably occurring in the future can be obtained. The method is a major supplement to the existing intelligent power quality monitoring system, and has very great practical significance.

Description

technical field [0001] The invention relates to a voltage sag prediction and analysis method based on multi-dimensional and multi-layer association rules, and belongs to the technical field of power quality analysis methods. Background technique [0002] Power quality problems include two aspects: steady-state power quality and transient power quality. With the gradual advancement of electricity marketization and the development of industrial automation and national economic informatization, on the one hand, the nonlinear load in the distribution network poses a serious threat to the power quality of the power grid; on the other hand, in the distribution network, such as computer The high sensitivity of power consumption equipment to system interference has put forward high reliability, high transient stability, and high controllability requirements for power quality. According to monitoring data, 80% or more of existing power quality problems are caused by voltage sags. T...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 齐林海罗燕焦润海马素霞
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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