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PMU data detection method based on K-means clustering

A data detection and K-means technology, applied in data processing applications, instruments, character and pattern recognition, etc., can solve problems such as spectrum leakage, error problems, PMU data accuracy impact, etc.

Pending Publication Date: 2020-04-03
NORTH CHINA ELECTRIC POWER UNIV (BAODING) +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, the ferromagnetic resonance and transient response problems of capacitive voltage transformers under dynamic conditions, the saturation problem of current transformers, the error problems caused by factors such as spectrum leakage and frequency fluctuations in the PMU algorithm, etc., all affect the accuracy of PMU data. influences

Method used

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  • PMU data detection method based on K-means clustering
  • PMU data detection method based on K-means clustering
  • PMU data detection method based on K-means clustering

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Experimental program
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Embodiment Construction

[0030] figure 1 It is a flowchart of the present invention, comprising the following steps:

[0031] Step 1: Obtain the data of the PMUs at both ends of the line, and extract the positive sequence components.

[0032] Step 2: Carry out K-means clustering on the line data with the active power transmitted by the line as the y-axis and the phase angle difference between the two ends of the line as the x-axis. For the step-type data deviation, two categories can be clearly obtained.

[0033] Step 3: For these two categories, use the criterion to distinguish, and the data that satisfies the two criteria at the same time is the correct data, which can be applied to the advanced application of PMU.

[0034] The method of the present invention is demonstrated below with examples.

[0035] This embodiment uses PSCAD to build a 220kV simulation system, such as figure 2 As shown, the positive sequence parameters of the single-circuit distribution line L1 are identified. The 220kV l...

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Abstract

The invention provides a PMU data detection method based on K-means clustering. According to the detection method, phase angle bad data under a condition that PMU data has the step type deviation canbe detected, so that available good data can be distinguished. The method comprises the following steps: firstly, obtaining PMU measurement data of a line in a period of time, and calculating a positive sequence component; secondly, clustering the data with the line transmission active power as the y axis and the line phase angle difference as the x axis by using K-means clustering; and finally, screening the clusters by using a criterion, and selecting correct data.

Description

technical field [0001] The invention belongs to the field of power system operation control and protection, and in particular relates to a PMU data detection method based on K-means clustering. Background technique [0002] At present, PMU data has become one of the important data sources of smart grid. Based on PMU / WAMS, a series of advanced applications have been carried out, such as parameter identification, state estimation, power system monitoring and control, etc. The characteristic of PMU is that it can provide phasor measurement data with consistent time scale. The accuracy of PMU data is the basis of various advanced applications. However, the field measured PMU data shows that some PMU phase angle measurement data have quality problems; at the same time, studies have shown that factors such as time synchronization, power transformers, PMU algorithms, and malicious attacks may cause deviations in the measured PMU data. In terms of time synchronization, existing st...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q50/06
CPCG06Q50/06G06F18/23213
Inventor 薛安成冷爽劳永钊阚晓骢危国恩
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)