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An Artificial Intelligence-Based Fault Detection Method for Solar Panels

A solar panel and fault detection technology, which is applied in the monitoring of photovoltaic systems, electrical components, photovoltaic power generation, etc., can solve problems such as high cost, low efficiency, and inability to accurately determine the type of fault, so as to achieve targeted and improve detection efficiency effect

Active Publication Date: 2021-12-07
江苏裕荣光电科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the shortcomings of low efficiency, high cost and inability to accurately determine the type of fault in the prior art, the present invention provides a fault detection method for solar panels based on artificial intelligence, which can use the shape of the shadow area on the solar panel and the The change characteristics of the shaded area under different time series can accurately determine the type of rotation fault of the solar panel

Method used

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  • An Artificial Intelligence-Based Fault Detection Method for Solar Panels
  • An Artificial Intelligence-Based Fault Detection Method for Solar Panels
  • An Artificial Intelligence-Based Fault Detection Method for Solar Panels

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Embodiment 1

[0036] The artificial intelligence-based solar battery panel fault detection method provided by the present invention is aimed at a specific scenario: the set solar panel array, when generating power at maximum power, continuously performs Adjustment of altitude angle and azimuth angle; however, due to the environment and the use time of the power generation system, there may be a rotation fault during the rotation of the solar panels, so that there is mutual shading between the solar panels, and the maximum power generation cannot be obtained more effectively .

[0037] In order to realize the fault detection of the solar cell panel array, specifically, an artificial intelligence-based solar cell panel fault detection method provided in this embodiment, such as figure 1 As shown, the method includes the following steps:

[0038] Step 1, obtaining a solar panel array image, and preprocessing the solar panel array image to obtain grayscale image information;

[0039] Specific...

Embodiment 2

[0083] In this embodiment, on the basis of the fault of the solar cell panel judged in the first embodiment, the power generation of the solar cell panel is adjusted to minimize the impact of the rotation fault on the power generation and maximize the power generation.

[0084] Specifically, the solar panel array is adjusted according to the battery panel failure type and the affected related area obtained in the first embodiment, and the specific process is as follows:

[0085] 1) Obtain the data of the shadow area, shadow shape, initial adjustment angle and real-time solar panel array power of each solar panel, and form sequence data of all solar panel data, where the sequence data includes test set and training set;

[0086] Construct the regulation network model; use the training set to train the regulation network model, and obtain the trained regulation network model;

[0087] In this embodiment, the input to the network is performed after the sequence data is self-encod...

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Abstract

The invention relates to a fault detection method for solar panels based on artificial intelligence; it performs gray-scale processing on images collected by drones, extracts and numbers individual solar panels in the gray-scale image information, and obtains each The corner coordinate information of the solar panel; and then according to the corner coordinate information, obtain the vertical and horizontal slopes of the adjacent two edges of the corresponding solar panel; judge whether the slopes of any two adjacent solar panels are equal, and if the slopes are not equal, judge the solar energy There is a rotation fault in the battery panel; then extract the shadow area of ​​two adjacent solar panels, and obtain the shape characteristics of the shadow area of ​​each solar panel and / or the change characteristics of the shadow area under different timings; finally, according to the shape characteristics of the shadow area and / or the Judging the rotation fault category of the solar panel based on the change characteristics of the shaded area. That is to say, the solution of the present invention can accurately determine the type of rotation faults that occur on the solar battery panel.

Description

technical field [0001] The invention relates to the field of failures of solar panels, in particular to a method for detecting failures of solar panels based on artificial intelligence. Background technique [0002] Solar panels are devices that directly or indirectly convert solar radiation into electrical energy through photoelectric or photochemical effects by absorbing sunlight. The efficiency of solar panel arrays in absorbing sunlight is related to many factors, such as geographical location, climate, and light intensity. , the inclination angle of the panel, etc. Among them, the inclination angle of the battery panel has a great influence on its efficiency of absorbing solar energy. [0003] The angle and intensity of the sun's rays will vary between winter and summer. Therefore, in order to ensure that the power generation of the solar panels is as large as possible, the maximum annual power generation is achieved by adjusting the inclination and rotation angles of...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/136G06T5/00H02S50/10
CPCG06T7/0004G06T7/136H02S50/10G06T2207/10004G06T2207/20164G06T2207/20032G06T2207/30108G06T2207/20081G06T5/70Y02E10/50
Inventor 王丙涛倪菊如
Owner 江苏裕荣光电科技有限公司