A method for the rapid computing efficiency of a colored photovoltaic

Abstract

The present invention discloses a method for the rapid calculation efficiency of color photovoltaic technology, which comprises the following steps: Data preprocessing stage: Receive the picture uploaded by the user, analyze it, remove noise and irrelevant elements, convert the picture from the conventional color space to the RGB color space for subsequent photovoltaic efficiency simulation, perform color analysis on the picture, extract key color information, and assign a unique number to each color; Photovoltaic efficiency simulation stage: According to the simulation parameters set by the user, construct a simulation environment for photovoltaic modules. For each extracted key color, simulate the photovoltaic conversion process of sunlight irradiating on it, and calculate the corresponding photovoltaic conversion efficiency. According to the distribution and proportion of colors in the picture, the present invention solves the problems that the existing method for calculating the operation efficiency of color photovoltaic has a long calculation time, many process flows, and limited applicability.

Description

Technical Field

[0001] The present invention relates to the technical field of colored photovoltaics, and more particularly to a method for rapidly calculating the efficiency of colored photovoltaics. Background Art

[0002] With the booming development of the photovoltaic industry, the wide application fields of photovoltaic modules are constantly expanding. Among them, facade photovoltaics are popular in various industries due to their energy-saving and environmental protection characteristics. However, the special nature of facade photovoltaics in the building facade position results in their power generation efficiency being restricted by shading, making it difficult for them to obtain sufficient sunlight, thus leading to a low power generation efficiency. Although colored photovoltaic modules have become a way to improve the aesthetics and environmental protection of buildings, the power generation efficiency of traditional colored photovoltaic modules is usually about 10% lower than that of ordinary crystalline silicon modules, and the three-dimensional visual effect at night is limited.

[0003] However, the existing method for calculating the operation efficiency of colored photovoltaics takes a long time to obtain results, has many process flows, and has limited applicability. Summary of the Invention

[0004] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the present invention, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0005] Therefore, the purpose of the present invention is to provide a method for rapidly calculating the efficiency of colored photovoltaics, which can solve the problems that the existing method for calculating the operation efficiency of colored photovoltaics takes a long time to obtain results, has many process flows, and has limited applicability.

[0006] To solve the above technical problems, the present invention provides a method for rapidly calculating the efficiency of colored photovoltaics, adopting the following technical solutions: The method includes the following steps:

[0007] a) Data preprocessing stage: Receive the picture uploaded by the user, analyze it, remove noise and irrelevant elements, convert the picture from the conventional color space to the RGB color space for subsequent photovoltaic efficiency simulation, perform color analysis on the picture, extract key color information, and assign a unique number to each color;

[0008] b) Photovoltaic efficiency simulation stage: According to the simulation parameters set by the user, construct a simulation environment for the photovoltaic module. For each extracted key color, simulate the photovoltaic conversion process of sunlight irradiating on it, calculate the corresponding photovoltaic conversion efficiency, and calculate the predicted power generation efficiency of the overall photovoltaic module according to the distribution and proportion of the color in the picture;

[0009] c) Hot spot phenomenon prediction stage: Using electroluminescence imaging technology, simulate the current distribution in the photovoltaic module, analyze the areas where hot spots may occur based on the simulated current distribution data, and evaluate its impact on the performance of the photovoltaic module;

[0010] d) Color optimization stage: Use intelligent algorithms to optimize the colors in the picture to improve the overall power generation efficiency of the photovoltaic module and reduce the occurrence of hot spot phenomena. During the optimization process, it can be adjusted according to the goals set by the user. After optimization, generate the optimized picture and display it to the user for viewing and confirmation;

[0011] e) Result output and feedback stage: Output information such as the optimized picture, predicted power generation efficiency, and hot spot phenomenon prediction results to the user, provide a user feedback mechanism, allow the user to evaluate the optimization results and put forward improvement suggestions, and continuously improve and optimize the system according to the user feedback;

[0012] f) System verification and testing stage: Apply the optimized picture to the actual photovoltaic module and conduct actual tests to verify the accuracy of the prediction results. According to the test results, make necessary adjustments and improvements to the system to improve the prediction accuracy and reliability of the system.

[0013] Optionally, in step a), the method for RGB color arrangement operation is to initialize the RGB color space, covering all possible values from 0 to 255, and use a loop or recursive method to generate all possible RGB color combinations, totaling 256×256×256 = 16777216 different color combinations.

[0014] By adopting the above technical solution, number each color combination for subsequent query and operation.

[0015] Optionally, in step b), the method for photovoltaic efficiency simulation is to establish a model that simulates sunlight irradiating on the photovoltaic module, including spectral distribution and incident angle parameters. For each RGB color combination, simulate the photovoltaic conversion process of sunlight irradiating on it, predict the power generation efficiency of the photovoltaic module after spraying a specific pattern, and control the error within ±1%.

[0016] By adopting the above technical solution, calculate the photovoltaic conversion efficiency of each color combination according to the photovoltaic conversion efficiency formula.

[0017] Optionally, in step c), the method for hot spot phenomenon prediction is to use electroluminescence imaging technology to simulate the current distribution in the photovoltaic module, analyze the current distribution data, and predict the areas where hot spots may occur.

[0018] By adopting the above technical solution, evaluate the impact of each color combination on the hot spot phenomenon according to the prediction results.

[0019] Optionally, in step d), the method for color optimization is to evaluate the performance of each color combination based on the results of photovoltaic efficiency simulation and hot spot phenomenon prediction, and use intelligent algorithms to optimize the color arrangement and combination to improve the overall power generation efficiency.

[0020] By adopting the above technical solution, the color difference value of the picture is adjusted to further optimize the performance and avoid the hot spot phenomenon.

[0021] Optionally, in step e), the method for accurate color rendering is to use color management technology to simulate the accurate color after spraying and combining with the photovoltaic module.

[0022] By adopting the above technical solution, the simulation results are presented in a visual form so that customers can intuitively see the actual effect of the selected picture on the photovoltaic module.

[0023] Optionally, in step a), a data processing unit is used to process the data in the data preprocessing stage.

[0024] By adopting the above technical solution, the data is preprocessed, such as image denoising, color space conversion, etc., and the processed data is passed to the simulation operation unit for optimization operation.

[0025] Optionally, in step b) and step c), the simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. The photovoltaic efficiency simulation module is used to process the data in the photovoltaic efficiency simulation stage, and the hot spot phenomenon prediction module is used to process the data in the hot spot phenomenon prediction stage.

[0026] By adopting the above technical solution, based on the data provided by the data processing unit, the simulation operations of the photoelectric conversion efficiency and the hot spot phenomenon are carried out, and the operation results are passed to the optimization unit for further processing.

[0027] Optionally, in step d), the optimization unit is used to process the data in the color optimization stage.

[0028] By adopting the above technical solution, the color difference value of the picture is adjusted to further optimize the performance, and the optimized data is passed to the display unit for display.

[0029] Optionally, in step e), the display unit is used to process the data in the result output and feedback stage.

[0030] By adopting the above technical solution, an intuitive interface is provided to facilitate users to view and select the optimized color combination, and customized display settings can be made according to user requirements.

[0031] In summary, the present invention includes at least one of the following beneficial effects: The method and system for rapid calculation of the efficiency of color photovoltaic proposed by the present invention can calculate the efficiency of color photovoltaic quickly and accurately, greatly saving calculation time and resources. And due to the fast operation speed, the data of this method and system can be updated in real time, and the changes in the efficiency of color photovoltaic can be reflected in a timely manner. This method and system usually have an intuitive user interface and easy-to-operate functions, enabling users to easily calculate and analyze the efficiency of color photovoltaic. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0033] Figure 1 It is a flowchart of the operation method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The following will further elaborate on the present invention in conjunction with the attached Figure 1 for a more detailed description.

[0035] Example 1. Referring to Figure 1 , in this embodiment, in order to solve the problems of the existing long time to obtain the result of calculating the operation efficiency of color photovoltaic and the large number of process flows with limited applicability, the present invention discloses a method for rapid calculation of the efficiency of color photovoltaic, which includes the following steps:

[0036] a) Data preprocessing stage: Receive the picture uploaded by the user, analyze it, remove noise and irrelevant elements, convert the picture from the conventional color space (such as SRGB) to the RGB color space for subsequent photovoltaic efficiency simulation, perform color analysis on the picture, extract key color information, and assign a unique number to each color; in step a), the method of RGB color arrangement operation is to initialize the RGB color space, covering all possible values from 0 to 255, and use a loop or recursive method to generate all possible RGB color combinations, with a total of 256×256×256 = 16777216 different color combinations. In step a), the data processing unit is used to process the data in the data preprocessing stage, number each color combination for subsequent query and operation, preprocess the data, such as image denoising, color space conversion, etc., and transfer the processed data to the simulation operation unit for optimized operation;

[0037] b) Photovoltaic efficiency simulation stage: According to the simulation parameters set by the user (such as solar spectral distribution, incident angle, etc.), construct a simulation environment for the photovoltaic module. For each extracted key color, simulate the photovoltaic conversion process of sunlight irradiating on it, calculate the corresponding photovoltaic conversion efficiency, and calculate the predicted power generation efficiency of the overall photovoltaic module according to the distribution and proportion of the color in the picture. In step b), the method of photovoltaic efficiency simulation is to establish a model that simulates sunlight irradiating on the photovoltaic module, including spectral distribution and incident angle parameters. For each RGB color combination, simulate the photovoltaic conversion process of sunlight irradiating on it, predict the power generation efficiency of the photovoltaic module after spraying a specific pattern, and control the error within ±1%. According to the photovoltaic conversion efficiency formula, calculate the photovoltaic conversion efficiency of each color combination;

[0038] c) Hot spot phenomenon prediction stage: Use electroluminescence imaging technology (EL) to simulate the current distribution in the photovoltaic module. According to the simulated current distribution data, analyze the areas where hot spots may occur and evaluate their impact on the performance of the photovoltaic module. In step c), the method of hot spot phenomenon prediction is to use electroluminescence imaging technology to simulate the current distribution in the photovoltaic module, analyze the current distribution data, and predict the areas where hot spots may occur. In steps b) and c), the simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. In the photovoltaic efficiency simulation stage, the photovoltaic efficiency simulation module is used to process the data, and in the hot spot phenomenon prediction stage, the hot spot phenomenon prediction module is used to process the data. According to the prediction results, evaluate the impact of each color combination on the hot spot phenomenon. The simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. In the photovoltaic efficiency simulation stage, the photovoltaic efficiency simulation module is used to process the data, and in the hot spot phenomenon prediction stage, the hot spot phenomenon prediction module is used to process the data;

[0039] d) Color optimization stage: Use intelligent algorithms to optimize the colors in the picture to improve the power generation efficiency of the overall photovoltaic module and reduce the occurrence of hot spot phenomena. During the optimization process, adjustments can be made according to the goals set by the user (such as maximizing power generation efficiency, minimizing the impact of hot spots, etc.). After optimization, generate an optimized picture and display it to the user for viewing and confirmation. In step d), the method of color optimization is to evaluate the performance of each color combination according to the results of photovoltaic efficiency simulation and hot spot phenomenon prediction, and use intelligent algorithms to optimize the color arrangement combination to improve the overall power generation efficiency. In step d), the color optimization stage uses an optimization unit to process the data, adjust the color difference value of the picture to further optimize the performance and avoid hot spot phenomena, adjust the color difference value of the picture to further optimize the performance, and transfer the optimized data to the display unit for display;

[0040] e) Result Output and Feedback Phase: Output information such as the optimized image, predicted power generation efficiency, and prediction results of hot spot phenomena to the user, provide a user feedback mechanism, allow the user to evaluate the optimization results and put forward improvement suggestions, and continuously improve and optimize the system according to the user feedback. In step e), the method for accurate color rendering is to use color management technology to simulate the accurate color after spraying and combined with the photovoltaic module. In step e), the result output and feedback phase uses a display unit to process the data and display the simulation results in a visual form so that the customer can intuitively see the actual effect of the selected image on the photovoltaic module, provide an intuitive interface, facilitate the user to view and select the optimized color combination, and can perform customized display settings according to user needs;

[0041] f) System Verification and Testing Phase: Apply the optimized image to an actual photovoltaic module and conduct actual tests to verify the accuracy of the prediction results. According to the test results, make necessary adjustments and improvements to the system to improve the prediction accuracy and reliability of the system.

[0042] Based on the above features, the working principle of this embodiment is as follows: This method not only focuses on the overall energy efficiency of the photovoltaic power generation system but also delves into details such as component efficiency and system efficiency to ensure the comprehensiveness and accuracy of the evaluation. It emphasizes the full collection and fine processing of various data of the photovoltaic power generation system to ensure the accuracy and reliability of the data basis for the evaluation. By establishing a mathematical model that can describe the system performance and using methods such as the modified simplified model, dynamic model, and semi - empirical model, the accurate evaluation of the energy efficiency of the photovoltaic power generation system is achieved. The real - time monitoring and data analysis methods among them can evaluate the operating status and fault risks of the system in real time and provide timely data support for the optimization of the system;

[0043] The data collection and processing methods mentioned, especially the fine processing of data analysis, denoising, and calibration, are important bases for ensuring the accuracy of the evaluation. The energy efficiency evaluation model established in the proposal and the algorithms used, such as the modified simplified model, dynamic model, and semi - empirical model, are the key technologies for achieving the accurate evaluation of the energy efficiency of the photovoltaic power generation system. The real - time monitoring and data analysis methods mentioned in the proposal, as well as the methods of using sensors and monitoring devices to monitor and optimize the performance of the photovoltaic power generation system, are important technical means for ensuring the efficient operation of the system.

[0044] The above are all preferred embodiments of the present invention. Without limiting the protection scope of the present invention accordingly, therefore: All equivalent changes made according to the structure, shape, and principle of the present invention shall be covered within the protection scope of the present invention.

Claims

1. A method for rapid calculation of color photovoltaic performance, characterized in that: The method comprises the following steps: a) Data preprocessing stage: receiving pictures uploaded by users, analyzing them, removing noise and irrelevant elements, converting pictures from conventional color space to RGB color space for subsequent photovoltaic efficiency simulation, performing color analysis on pictures, extracting key color information, and assigning a unique number to each color; b) Photovoltaic efficiency simulation stage: According to the simulation parameters set by the user, a simulation environment of the photovoltaic module is constructed. For each extracted key color, the photoelectric conversion process of sunlight shining on it is simulated, and the corresponding photoelectric conversion efficiency is calculated. According to the distribution and proportion of the colors in the picture, the predicted power generation efficiency of the entire photovoltaic module is calculated; c) Hot spot prediction stage: Use electroluminescence imaging technology to simulate the distribution of current in photovoltaic modules. Based on the simulated current distribution data, analyze the areas where hot spots may occur and evaluate their impact on the performance of photovoltaic modules. d) Color optimization stage: Use intelligent algorithms to optimize the colors in the image to improve the power generation efficiency of the overall photovoltaic module and reduce the occurrence of hot spots. During the optimization process, adjustments can be made according to the goals set by the user. After the optimization is completed, the optimized image is generated and displayed to the user for review and confirmation; e) Result output and feedback stage: Output optimized images, predicted power generation efficiency, hot spot prediction results and other information to users, provide user feedback mechanism, allow users to evaluate the optimization results and put forward improvement suggestions, and continuously improve and optimize the system based on user feedback; f) System verification and testing phase: Apply the optimized images to actual PV modules and conduct actual tests to verify the accuracy of the prediction results. Based on the test results, make necessary adjustments and improvements to the system to improve the prediction accuracy and reliability of the system.

2. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step a), the method for calculating the RGB color arrangement is to initialize the RGB color space, cover all possible values ​​from 0 to 255, and use a loop or recursive method to generate all possible RGB color combinations, totaling 256×256×256=16777216 different color combinations.

3. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step b), the method for simulating photovoltaic efficiency is to establish a model simulating sunlight irradiating on the photovoltaic module, including spectral distribution and incident angle parameters. For each RGB color combination, the photoelectric conversion process of sunlight irradiating thereon is simulated to predict the power generation efficiency of the photovoltaic module after spraying a specific pattern, and the error is controlled within ±1%.

4. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step c), the method for predicting the hot spot phenomenon is to use electroluminescence imaging technology to simulate the distribution of current in the photovoltaic module, analyze the current distribution data, and predict the area where the hot spot may occur.

5. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In step d), the color optimization method is to evaluate the performance of each color combination based on the results of photovoltaic efficiency simulation and hot spot phenomenon prediction, and use intelligent algorithms to optimize the color arrangement and combination to improve the overall power generation efficiency.

6. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step e), the method for accurate color presentation is to use color management technology to simulate the accurate color of the photovoltaic module after spraying.

7. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step a), a data processing unit is used to process the data in the data preprocessing stage.

8. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In step b) and step c), the simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. The photovoltaic efficiency simulation module is used to process data in the photovoltaic efficiency simulation stage, and the hot spot phenomenon prediction module is used to process data in the hot spot phenomenon prediction stage.

9. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step d), the color optimization stage uses an optimization unit to process the data.

10. The method for rapid color photovoltaic computing performance according to claim 1, characterized in that: In the step e), the display unit is used to process the data during the result output and feedback stage.

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