Rapid detection method for power load abnormal data based on empirical mode decomposition

An empirical mode decomposition and power load technology, applied in data processing applications, instruments, calculations, etc., can solve problems such as load drastic changes, load data collection and transmission errors, load curve fluctuations, etc., to achieve high accuracy and operability High and fast detection and mining effects

Inactive Publication Date: 2015-12-30
STATE GRID CORP OF CHINA +2
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Problems solved by technology

However, in some special cases, there will be huge fluctuations in the load curve, and the huge fluctuations in the load data may be caused by errors in collection and transmission, or may indicate drastic changes in the load

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  • Rapid detection method for power load abnormal data based on empirical mode decomposition
  • Rapid detection method for power load abnormal data based on empirical mode decomposition
  • Rapid detection method for power load abnormal data based on empirical mode decomposition

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Embodiment Construction

[0031] The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following descriptions are only examples and not intended to limit the scope of the invention and its application.

[0032] figure 1 is a flowchart of the present invention. figure 1 Among them, the method provided by the invention comprises the following steps:

[0033] Step 1: Data preprocessing, establish training sample set and test sample set.

[0034] For the selected data of the embodiment, firstly, the missing data in the collected data is eliminated, and the entire sample set is arranged in time sequence to establish an initial sample set. Divide the initial sample set into training sample set and test sample set. Among them, the training sample set is used to establish the abnormal data detection model of electric load and estimate the model parameters, and the test sample set is the sample data segment to be detected....

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Abstract

The invention provides a rapid detection method for power load abnormal data based on empirical mode decomposition for solving the problems that in the prior art, results obtained by developing abnormal data detection and mining are few and are scattered, and no universal algorithm for abnormal data detection exists due to varieties and complexity of abnormal data. Accordingly, the detection method for power load abnormal data is high in accuracy and operability, and rapid detection and mining of the power load abnormal data under a large sample are achieved.

Description

technical field [0001] The invention belongs to the technical field of electric load abnormal data detection, and in particular relates to a rapid detection method for large sample electric load abnormal data. Background technique [0002] Under normal circumstances, the load of the power grid presents a certain regular trend. However, in some special cases, there will be huge fluctuations in the load curve, and the huge fluctuations in the load data may be caused by errors in collection and transmission, or may indicate drastic changes in load. Therefore, it is very important to analyze, excavate and predict the drastic changes in load data. It can give the dispatch management department an estimate in advance, so as to formulate the operation management method and the sequence table of the power limit in case of emergency, so as to prevent Grid collapse and disintegration. [0003] It is difficult to carry out abnormal data detection and mining, and the results obtained ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06
Inventor 徐向东王倩秦睿宋曦王晶刘志远张驯李志茹
Owner STATE GRID CORP OF CHINA
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