Method for online restoring abnormal data of wind power plant

A technology for abnormal data and data repair, which is applied to the redundancy in the operation for data error detection and response error generation. , Improve the calculation speed and meet the effect of online detection and correction

Active Publication Date: 2014-03-12
STATE GRID CORP OF CHINA +3
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Problems solved by technology

At present, the mainstream abnormal data detection methods, such as neural network, data mining, statistics, feature selection, wavelet singularity detection, etc., all have a common disadvantage that the amount of data required for training is large, the calculation cost is high, and there is a greater impact on real-time detection. influences

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  • Method for online restoring abnormal data of wind power plant
  • Method for online restoring abnormal data of wind power plant
  • Method for online restoring abnormal data of wind power plant

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Embodiment Construction

[0033] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0034] Such as figure 1 as shown, figure 1 Flowchart of the online repair method for wind farm abnormal data; the online repair method for wind farm abnormal data of the present invention is based on high-frequency sampling data with a constant time interval. First, effective sliding window data is selected, and then only this part of the data is calculated, and filtered out Abnormal data and fix it. The calculation process ignores the data outside the sliding window, and combines the difference method, quantile method and certain constraint calculation methods. The calculation process is simple and efficient, and meets the requirements of online operation. Although this method is described by taking real-time data collected by wind farms as an example, this method is also applicable to online restoration of other high-frequency ...

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Abstract

The invention provides a method for online restoring abnormal data of a wind power plant. The method comprises the following steps of I, determining a processed data item according to the data of the wind power plant; II, selecting a starting point of the processed data item; III, acquiring a continuous differential data sequence by adopting a slide window differential method; IV, judging whether the data is the abnormal data or not by utilizing a quartile method; and V, determining a restored data set. By adopting the method, the requirement on online detecting and restoring the abnormal data can be met, the data quality can be effectively improved, the quality of the collected data can be guaranteed, and the influence of the abnormal source on the data analysis can be reduced.

Description

technical field [0001] The invention relates to a method in the technical field of new energy power generation and access, in particular to a method for online repair of abnormal data of a wind farm. Background technique [0002] In the process of real-time data collection of wind farms, due to external interference, communication errors, instrument aging or application itself, the collected data often contains a certain amount of abnormal data. Abnormal data may be biased or misleading in subsequent data processing. At present, the mainstream abnormal data detection methods, such as neural network, data mining, statistics, feature selection, wavelet singularity detection, etc., all have a common disadvantage that the amount of data required for training is large, the calculation cost is high, and there is a greater impact on real-time detection. influences. [0003] Since more and more applications require online analysis of real-time data, it is necessary to provide a si...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/14
Inventor 唐林郑太一黄越辉孙勇李鹏杨国新孙春飞许彦平
Owner STATE GRID CORP OF CHINA
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