Method for photovoltaic module el image processing and calculating module power degradation

Abstract

This invention provides a method for processing photovoltaic (PV) module EL images and calculating module power attenuation. The method involves capturing EL images of the PV module using a CCD camera (black and white images); converting the black and white images into a heatmap using image processing software; qualitatively observing light changes in the EL image within the heatmap; adding a standard ruler to the heatmap to directly compare light intensity in different areas of the EL image to determine the basic performance of the PV module; calculating the average fluorescence intensity of the Red Hot heatmap; and converting the fluorescence intensity data into PV module power attenuation data to determine the PV module's performance. This method allows for a direct, qualitative, and quantitative assessment of the basic performance of PV modules.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic technology, and more specifically to a method for processing photovoltaic module EL images and calculating module power attenuation. Background Technology

[0002] Solar energy is an inexhaustible and clean renewable energy source for humankind. Among the effective utilization of solar energy, the photovoltaic (PV) conversion of solar energy is the fastest-growing and most dynamic research field in recent years. To promote solar cells as an excellent low-carbon energy source, it is essential to improve their quality to meet customer requirements. Furthermore, to improve the quality of solar cells, EL testing is necessary at key stages of module production.

[0003] Electroluminescence (EL) defect detection is a crucial method for detecting and monitoring defects in solar cells caused by processes or materials themselves. Analysis of EL images can effectively identify potential problems in various stages of silicon wafer diffusion, passivation, printing, and sintering, playing a vital role in improving processes, increasing efficiency, and stabilizing production. Therefore, EL is considered the "eyes" of solar cell production lines and is currently widely used to inspect for latent defects in photovoltaic modules. EL stands for Electro Luminescence, also known as electron emission detection. The principle of EL technology is based on applying a forward bias voltage to a crystalline silicon solar cell, injecting a large number of non-equilibrium carriers into the cell. EL relies on the continuous recombination of these injected non-equilibrium carriers from the diffusion region to emit photons. These photons are captured by a CCD camera, processed by a computer, and displayed to detect problems within the solar cell. Electrons in the conduction band are metastable and will eventually transition to the valence band, either spontaneously or under external stimulation, and recombine with a hole in the valence band. During recombination, a photon is released, and when the number of photons is large, an EL image is formed.

[0004] In this technical field, the basic black and white images captured by CCD cameras are currently widely used. Directly using black and white images for comparison processing of EL images has many problems, such as the inability to intuitively perceive changes in light intensity between images and the inability to quantitatively analyze changes in light intensity after processing such as aging and load. Summary of the Invention

[0005] The technical problem this invention aims to solve is the numerous issues that arise when comparing EL images from black-and-white images captured directly by a CCD camera. These include the inability to visually perceive changes in light intensity between images, the inability to quantitatively analyze light intensity to determine component power degradation, and the difficulty in comparing image changes after processing such as aging and load. This invention provides a method for processing EL images of photovoltaic modules and calculating component power degradation.

[0006] The technical solution adopted by this invention to solve its technical problem is: a method for processing EL images of photovoltaic modules and calculating module power attenuation, comprising the following steps:

[0007] S1: Use a CCD camera to capture the EL image of the photovoltaic module, and the EL image is a black and white image.

[0008] S2: Using image processing software, convert the black and white image obtained in step S1 into a Red Hot thermal image, and qualitatively observe the light changes in the EL image in the Red Hot thermal image.

[0009] S3: Using image processing software, add a standard ruler to the Red Hot thermal image obtained in step S2. Based on the standard ruler, the intensity of light in different areas of the EL image can be directly compared visually to determine the basic performance of the photovoltaic module. If the light in a certain area is strong, it means that the battery module releases more photons under the same current, and its reverse process (absorption of photons to generate electricity) has a higher power output.

[0010] S4: Using image processing software, calculate the average fluorescence intensity of the Red Hot heatmap. The calculation formula is: Average fluorescence intensity = Total fluorescence intensity of the calculated area / Calculated area.

[0011] S5: The comparison of fluorescence intensity data in the EL image calculated in step S4 is converted into photovoltaic module power degradation data. The performance of the photovoltaic module is judged by the power degradation data. The power degradation of the module is judged by the change in light intensity. If the module has degradation, it means that its performance has declined. This helps to quickly judge the module's weather resistance to the environment after the aging test when the power test cannot be completed.

[0012] Furthermore, the image processing software includes, but is not limited to, imagej, scikit-image, NumPy, SciPy, PIL, MATLAB, and other image processing software. A single software or a combination of multiple software can be used.

[0013] Furthermore, step S4 specifically includes: using image processing software to calculate the fluorescence value of a portion of the Red Hot heatmap; or using a selection tool to quantitatively calculate the fluorescence value of a specific area in the image. The calculation principle and formula are: average fluorescence intensity = total fluorescence intensity of the calculated area / calculated area.

[0014] Compared with the prior art, the method for EL image processing and power attenuation calculation of photovoltaic modules provided by the present invention has the following advantages and functions:

[0015] ① Using simple image processing techniques, converting a black and white image into a Red Hot image can more intuitively reveal the changes in light in the EL image.

[0016] ② Using simple image processing technology, a standard ruler is added to the Red Hot heatmap. By visually comparing the light intensity in different areas of the image, the basic performance of the component can be judged.

[0017] ③ Using simple image processing technology, the Red Hot heatmap is analyzed, and the average fluorescence intensity is calculated by software. The required area light intensity is directly calculated using quantitative analysis methods: Average fluorescence intensity = Total fluorescence intensity of the calculated area / Calculated area.

[0018] ④ Using simple image processing techniques, the comparison of fluorescence intensity data in EL images is converted into component power attenuation data. Attached Figure Description

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Figure 1 This is a schematic diagram illustrating the process of converting a black-and-white image into a heatmap.

[0021] Figure 2 This is a schematic diagram illustrating the process of adding standard cards to a black-and-white image or heatmap.

[0022] Figure 3 This is a schematic diagram illustrating the calculation process of average fluorescence intensity in a black-and-white image or a thermal image.

[0023] Figure 4 This is a comparison chart of power attenuation in EL images before and after aging.

[0024] Figure 5 This is a graph showing the relationship between average fluorescence intensity decay and component power decay. Detailed Implementation

[0025] The present invention will now be described in detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0026] like Figure 1 As shown, the present invention provides a method for processing photovoltaic module EL images and calculating module power attenuation, which uses ImageJ image processing software to implement the operations in each step, specifically including the following steps:

[0027] S1: The EL image of the photovoltaic module is captured by a CCD camera, and the EL image is a black and white image;

[0028] S2: Using ImageJ image processing technology, the black and white image is converted into a Red Hot heatmap. The changes in light in the EL image are then qualitatively observed within the Red Hot heatmap, providing a more intuitive understanding of these changes. The specific steps include:

[0029] S2.1: Download and install the official software from the ImageJ website, and then open the EL image to be processed in the software.

[0030] S2.2: In the main menu bar, select the "image" option, then select the "lookup tables" option from the drop-down menu. Next, in the sub-menu bar, select "Red Hot" to convert the black and white image into a Red Hot heatmap, as shown below. Figure 1 .

[0031] S3: Using simple ImageJ image processing technology, add a standard ruler to the Red Hot thermal image obtained in step S2. Based on the standard ruler, the basic performance of the photovoltaic module can be judged by visually comparing the light intensity in different areas of the EL image. This specifically includes the following steps:

[0032] S3.1: In the ImageJ image processing software, open the Red Hot heatmap of the EL image to be processed.

[0033] S3.2: In the main menu bar, select the Analyze option; in the drop-down menu, select Tools; and in the submenu bar, select the Calibration Bar option. For example... Figure 2 As shown, by adding a standard ruler to the Red Hot heatmap, the light intensity in different areas of the graph can be directly compared visually to determine the basic performance of the components.

[0034] S4: Using simple ImageJ image processing technology, the average fluorescence intensity of the Red Hot heatmap is calculated by software. The required area fluorescence intensity is directly calculated using quantitative analysis methods: Average fluorescence intensity = Total fluorescence intensity of the calculated area / Calculated area. This includes the following steps:

[0035] S4.1: In the ImageJ image processing software, open the Red Hot heatmap of the EL image to be processed.

[0036] S4.2: Select the Analyze option in the main menu bar, and then select Measure from the drop-down menu to calculate the fluorescence value of a portion of the RedHot heatmap; or use the selection tool to quantitatively calculate the fluorescence value of a specific area in the image. The calculation principle and formula are: Average fluorescence intensity = Total fluorescence intensity of the calculated area / Calculated area. Figure 3 As shown, the average fluorescence intensity is calculated by software, which is a direct calculation of the required area light intensity using quantitative analysis methods.

[0037] In this embodiment, four regions are selected to calculate the fluorescence values ​​of partial points in the entire EL image of the photovoltaic module: such as... Figure 4 The figures show the average fluorescence intensities of F1, F2, F3, and F4, respectively. Alternatively, the fluorescence values ​​of specific regions in the image can be quantitatively calculated using the selection tool, resulting in S1, S2, S3, and S4. The calculation principle and formula are: Average fluorescence intensity = Total fluorescence intensity of the calculated area / Calculated area. Calculating the average fluorescence intensity using software directly yields the required area light intensity through quantitative analysis.

[0038] S5: Using simple ImageJ image processing techniques, the contrast of fluorescence intensity data in EL images is converted into component power attenuation data. This includes the following steps:

[0039] Based on the EL (Elasticity Index) graphs of the component samples before and after aging tests such as DH1000, DH2000, UV60, and UV120, measured at a fixed voltage, the average fluorescence intensity difference in a specific area of ​​the overall component before and after aging is calculated as follows: ΔQ = Q1 - Q2. The formulas are: Q1 = (EL before aging)(F1 + F2 + F3 + F4) / 4, Q2 = (EL after aging)(F1 + F2 + F3 + F4) / 4 or Q1 = (EL before aging)(S1 + S2 + S3 + S4) / 4, Q2 = (EL after aging)(S1 + S2 + S3 + S4) / 4.

[0040] like Figure 5As shown in Table 1, the attenuation of the average fluorescence intensity of the EL component is converted into power attenuation. After comparing multiple sets of experimental data, the average fluorescence intensity of the EL image and the component power attenuation satisfy the formula: Component power attenuation = K1(ΔQ)2 + K2(ΔQ) + R, where -0.002≤K1≤0.001, 0.1≤K1≤0.3, and 0.1≤R≤0.3.

[0041] Table 1. Average fluorescence intensity and power decay data before and after aging.

[0042]

[0043] Based on the comparison of experimental results, when K1 = -0.00416, K2 = 0.225, and R = 0.16667, the photovoltaic module power degradation is closest to the current formula: Module power degradation = -0.00416(ΔQ). 2 +0.225(ΔQ)+0.16667 shows that the change in average fluorescence intensity in the EL image can also be indirectly converted into the component power decay.

[0044] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the scope of the present invention. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for photovoltaic module EL image processing and calculating power degradation of a module, characterized by: The method comprises the following steps: S1: using a CCD camera to take an EL image of a photovoltaic module, and the EL image is a black and white image; S2: using image processing software to convert the black and white image obtained in step S1 into a Red Hot thermal map, and qualitatively observing the light changes in the EL image in the Red Hot thermal map; S3: using image processing software to add a standard ruler to the Red Hot thermal map obtained in step S2, and based on the standard ruler, the light intensity in different regions of the EL image can be directly compared by visual observation to judge the basic performance of the photovoltaic module; S4: using image processing software to calculate the average fluorescence intensity of the Red Hot thermal map, and the calculation formula is: average fluorescence intensity = total fluorescence intensity of the calculated area / area; S5: converting the comparison of the picture fluorescence intensity data in the EL image calculated in step S4 into photovoltaic module power attenuation data to judge the performance of the photovoltaic module through the power attenuation data; Using image j image processing technology, the comparison of the picture fluorescence intensity data in the EL image is converted into module power attenuation data, which comprises the following steps: According to the EL images of the module sample before and after the aging test at a fixed voltage, the average fluorescence intensity difference of the specific region of the overall module before and after aging is calculated: ΔQ = Q1-Q2, wherein the formula is: Q1=(F1+F2+F3+F4) / 4, Q2=(F1+F2+F3+F4) / 4 or Q1=(S1+S2+S3+S4) / 4, Q2=(S1+S2+S3+S4) / 4; The decay of the average fluorescence intensity of the component EL is converted into the decay of the power, the average fluorescence intensity of the EL picture and the decay of the component power satisfy the formula: component power decay = K1(ΔQ) + K2(ΔQ) + R, wherein -0.002≤K1≤0.001, 0.1≤K1≤0.3, 0.1≤R≤0.

3. 2 +K2(ΔQ) + R, wherein -0.002≤K1≤0.001, 0.1≤K1≤0.3, 0.1≤R≤0.

3. Wherein, ΔQ is the average fluorescence intensity difference of the specific region of the overall module before and after aging, Q1 is the average fluorescence intensity before aging, and Q2 is the average fluorescence intensity before aging; F1, F2, F3 and F4 are respectively the average fluorescence intensity of four partial regions corresponding to the points in the EL image of the photovoltaic module, and S1, S2, S3 and S4 are respectively the fluorescence values corresponding to four specific regions in the EL image of the photovoltaic module; in the calculation of Q1, F1, F2, F3 and F4 or S1, S2, S3 and S4 are all EL corresponding values before aging, and in the calculation of Q2, F1, F2, F3 and F4 or S1, S2, S3 and S4 are all EL corresponding values after aging.

2. The method for photovoltaic module EL image processing and calculating power degradation of a module of claim 1, wherein: The image processing software includes one or more of image j image processing software, scikit-image, Numpy, Scipy, PIL, and MATLAB.

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