Big data fault detection and positioning method for power distribution network

A distribution network fault and fault detection technology, which is applied to the fault location, fault detection according to the conductor type, and electrical measurement, can solve the inaccurate estimation of the covariance matrix of the received data, increase the practicability of the limited algorithm, and difficult distribution network faults Real-time diagnosis and positioning of problems

Active Publication Date: 2016-06-22
JILIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It is used to solve the problem that in the case of a large number of PMUs, the estimation of the covariance matrix of the received data is inaccurate, the increase of the data dimension limits the practicability of the algorithm, and it is difficult to diagnose and locate the distribution network fault in real time

Method used

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  • Big data fault detection and positioning method for power distribution network
  • Big data fault detection and positioning method for power distribution network
  • Big data fault detection and positioning method for power distribution network

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0068] Include the following steps:

[0069] (1): Arrange PMUs according to the topological structure of the distribution network to form a big data measurement device for the distribution network;

[0070] The PMU is laid out according to the topological structure of the distribution network, and the resulting measurement device is as follows: figure 1 As shown, its characteristic is that PMUs are evenly distributed in the entire distribution network;

[0071] (2): The measuring device in the application step (1) receives the distribution network voltage data;

[0072] Place a PMU device in the required detection area to receive the PMU data of each area respectively, and send the obtained raw data to the local phase data concentrator, and then aggregate the data of each local data concentrator and send it to the company data concentrator , and store it;

[0073] (3): Preprocessing the received data;

[0074] Calculate the average value v of the received voltage data u, a...

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Abstract

The invention provides a big data fault detection and positioning method for a power distribution network, and belongs to the field of intelligent power grids. The method comprises the steps: receiving voltage sampling data of the power distribution network through employing PMUs (Phasor Measurement Units); carrying out the preprocessing of voltages received by all PMUs, and constructing a receiving matrix; obtaining an unbiased estimated value of a receiving data covariance matrix through employing a random matrix theory; carrying out the eigenvalue decomposition of the covariance matrix, and obtaining a corresponding principal component; calculating a linear regression coefficient through employing PCA (Principal Component Analysis); comparing a relative approximation error and a threshold value, and achieving the fault detection and positioning of the power distribution network. The method provided by the invention solves a problem that the conventional covariance matrix estimation is biased under the measurement of a plurality of PMUs, and can achieve the real-time fault detection and positioning of the power distribution network.

Description

technical field [0001] The invention belongs to the field of smart grids, and in particular relates to a method for detecting and locating big data faults in distribution networks. Background technique [0002] The distribution network is a network that supplies power to end users, and is the main link in power generation, transmission, distribution, and consumption of power systems to supply power to users. The distribution network is at the end of the power system, and its wide geographical distribution, large-scale power grid, various types of equipment, various network connections, and variable operation modes make the analysis of its operating status difficult and complex. In the smart grid system, with the widespread use of the synchronous measurement unit (PhasorMeasurementUnit, PMU), the real-time processing of grid operation data has attracted widespread attention. [0003] Significant progress has been made in the monitoring, monitoring and control of power grids ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/00G01R31/02G01R31/08
CPCG01R31/00G01R31/086G01R31/50Y02E40/70Y02E60/00Y04S10/00Y04S10/22Y04S10/52
Inventor 孙晓颖刘国红陈若男陈建于海洋温艳鑫
Owner JILIN UNIV
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