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Photovoltaic power abnormal data recognition method and apparatus, and terminal device

A technology of abnormal data and abnormal power, applied in the computer field, can solve the problem of large identification error of abnormal data of photovoltaic power, and achieve the effect of improving flexibility and adaptability, ensuring rationality and improving accuracy

Pending Publication Date: 2021-03-19
XINAO SHUNENG TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of this, the present invention provides a method, device, and terminal equipment for identifying abnormal photovoltaic power data to solve the problem of large identification errors in photovoltaic power abnormal data in photovoltaic power plants that fail to monitor solar irradiance in real time in the prior art

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  • Photovoltaic power abnormal data recognition method and apparatus, and terminal device
  • Photovoltaic power abnormal data recognition method and apparatus, and terminal device
  • Photovoltaic power abnormal data recognition method and apparatus, and terminal device

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no. 1 example

[0051] figure 1 It is a flow chart of the recognition method of the photovoltaic power abnormality data provided in an embodiment of the present invention.

[0052] Such as figure 1 As shown, the recognition method of the photovoltaic power abnormal data includes steps S110-S150:

[0053] S110, get the photovoltaic power of the photovoltaic station at different times, obtain the timing power data set;

[0054] S120, using the K-Means clustering algorithm to cluster the timing power data set to obtain a clustering data set, the clustering data set includes a cluster center and a data point corresponding to each of the clusterings;

[0055] S130, based on the cluster data set, calculate the deviation of the center of the data point and the data point, to obtain a deviation data set;

[0056] S140, using DBSCAN to cluster the deviation data set to obtain an abnormal data distance threshold;

[0057] S150, based on the cluster center and the abnormal data distance threshold, the de...

no. 2 example

[0090] Based on the same inventive concept as the method in the first embodiment, the present embodiment also provides an identification device for photovoltaic power abnormal data.

[0091] Figure 6 A flow chart of the recognition apparatus of the photovoltaic power exception data provided by the present invention.

[0092] Such as Figure 6 As shown, the display device 6 includes: 61 Timing power dataset acquisition module, 62 cluster data set acquisition module, 63 deviation data set acquisition module, 64 abnormal distance threshold acquisition module, and 65 abnormal data set acquisition module.

[0093] Among them, the timing power dataset acquisition module is configured to obtain photovoltaic power of the photovoltaic power station at different times, obtain the timing power data set;

[0094] The cluster data set acquisition module is configured to use the K-Means cluster algorithm to cluster the timing power data set to obtain a cluster data set, the clustering data se...

no. 3 example

[0118] The above methods and apparatuses can be applied to terminal devices such as table-top computers, notebooks, handheld computers, and cloud servers.

[0119] Figure 7 A schematic diagram of a terminal device that can apply the above method and apparatus is provided in an embodiment of the present invention, as shown, including memory 71, processor 70, and in the memory 71 and can be A computer program 72 operated on the processor 70, the processor 70 performs the step of implementing an identification method of the photovoltaic power abnormal data when the computer program 72 is executed. E.g Figure 6 The functions shown in modules 61 to 65 are shown.

[0120] The device 7 can be a computing device such as a cloud server. The terminal device can include, but is not limited to, processor 70, the memory 71. Those skilled in the art will appreciate that Figure 7 It is only an example of the device 7, and does not constitute a defined to the terminal device 7, which may includ...

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Abstract

The invention is suitable for the field of computers, and provides a photovoltaic power abnormal data recognition method and device, and terminal equipment. The method comprises the steps: obtaining the photovoltaic power of a photovoltaic power station at different time, and obtaining a time sequence power data set; clustering the time sequence power data set by adopting a Kmeans clustering algorithm to obtain a clustering data set; based on the clustering data set, calculating the deviation of the data points and the clustering centers corresponding to the data points to obtain a deviation data set; clustering the deviation data set by adopting DBSCAN to obtain an abnormal data distance threshold value; and based on the clustering center and the abnormal data distance threshold, classifying the deviation data set to obtain an abnormal data set. According to the method, the photovoltaic power abnormal data is recognized through the Kmeans and DBSCAN second-order clustering algorithm,and the flexibility and the adaptability of abnormal recognition are improved by utilizing data features in the global dimension.

Description

Technical field [0001] The present invention belongs to the field of computer, and more particularly to a method, apparatus, and terminal device of photovoltaic power abnormal data. Background technique [0002] During the actual operation of the photovoltaic power station, communication, data acquisition equipment failure and human factors will make the measurement data abnormally, and the data abnormality caused by different abnormal incentives is different. At the same time, meteorological factors such as solar radiation illumination, temperature and humidity. Resulting in a certain volatility, abnormal data and normal fluctuations are easily confused. High quality photovoltaic power data is based on photovoltaic research, so it is necessary to identify photovoltaic power abnormal data. For photovoltaic power plants that fail to monitor solar radiation illuminances, the photovoltaic power abnormal data is difficult to identify and cleaning through artificial methods, while man...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F16/28
CPCG06F16/285G06F18/2321G06F18/23213Y02E10/50
Inventor 陈鑫王晓晨牛辰庚
Owner XINAO SHUNENG TECH CO LTD
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