Method for quickly calculating efficiency of color photovoltaic system

Abstract

The invention discloses a color photovoltaic fast operation efficiency method in the technical field of color photovoltaics, which comprises the following steps: a data preprocessing stage: receiving a picture uploaded by a user, analyzing the picture, removing noisy points and irrelevant elements, converting the picture from a conventional color space to an RGB color space, and carrying out data preprocessing; the method comprises the following steps: firstly, carrying out color analysis on a picture, extracting key color information, and distributing a unique number for each color; and a photovoltaic efficiency simulation stage: constructing a simulation environment of the photovoltaic module according to simulation parameters set by a user, simulating a photoelectric conversion process of sunlight irradiating on each extracted key color, calculating corresponding photoelectric conversion efficiency, and calculating the photovoltaic efficiency according to the distribution and proportion of the colors in the picture. According to the method, the problems that the time for calculating the color photovoltaic operation efficiency to obtain the result is long, the technological process is more, and the applicability is limited in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of color photovoltaics, and in particular to a method for quickly calculating the performance of color photovoltaics. Background Art

[0002] With the booming development of the photovoltaic industry, the wide application areas of photovoltaic modules are constantly expanding. Among them, facade photovoltaics are welcomed by all walks of life due to their energy-saving and environmentally friendly characteristics. However, the special nature of facade photovoltaics on the facade of the building leads to the limitation of its power generation efficiency due to shading, making it difficult to obtain sufficient light, resulting in 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 stereoscopic visual effect at night is limited.

[0003] However, the existing calculation results of color photovoltaic computing efficiency take a long time to obtain, involve many process flows, and have limited applicability. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of the present invention to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] Therefore, the purpose of the present invention is to provide a method for rapid calculation of color photovoltaic performance, which can solve the problems of long time to obtain results of the existing calculation of color photovoltaic performance, more process flows and limited applicability.

[0006] In order to solve the above technical problems, the present invention provides a method for color photovoltaic fast computing efficiency, which adopts the following technical solution: the method comprises the following steps:

[0007] 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;

[0008] 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;

[0009] 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.

[0010] 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;

[0011] 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;

[0012] 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.

[0013] Optionally, in 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.

[0014] By adopting the above technical solution, each color combination is numbered for subsequent query and calculation.

[0015] Optionally, in step b), the method for simulating photovoltaic efficiency is to establish a model for simulating sunlight irradiating on photovoltaic modules, including spectral distribution and incident angle parameters, and for each RGB color combination, simulate the photoelectric conversion process of sunlight irradiating thereon, 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, the photoelectric conversion efficiency of each color combination is calculated according to the photoelectric conversion efficiency formula.

[0017] Optionally, in 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.

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

[0019] Optionally, in step d), the method of 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 an intelligent algorithm 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 image is adjusted to further optimize the performance and avoid the hot spot phenomenon.

[0021] Optionally, in 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.

[0022] By adopting the above technical solution, the simulation results are displayed 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 during 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, and 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.

[0026] By adopting the above technical solution, simulation calculations of the photoelectric conversion efficiency and the hot spot phenomenon are performed according to the data provided by the data processing unit, and the calculation results are transmitted to the optimization unit for further processing.

[0027] Optionally, in step d), an optimization unit is used to process data during 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 transmitted to the display unit for display.

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

[0030] By adopting the above technical solution, an intuitive interface is provided, which is convenient for users to view and select optimized color combinations, and customized display settings can be made according to user needs.

[0031] In summary, the present invention includes at least one of the following beneficial effects: the color photovoltaic fast calculation efficiency method and system proposed in the present invention can quickly and accurately calculate the color photovoltaic efficiency, greatly saving calculation time and resources, and due to the fast calculation speed, the method and system can also update data in real time and promptly respond to changes in color photovoltaic efficiency. The method and system usually have an intuitive user interface and easy-to-operate functions, so that users can easily calculate and analyze color photovoltaic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0033] Figure 1 It is a flow chart of the operation method of the present invention. DETAILED DESCRIPTION

[0034] The following is combined with Figure 1 The present invention is described in further detail.

[0035] Embodiment 1, refer to Figure 1 In this embodiment, in order to solve the problem that the existing calculation of color photovoltaic computing efficiency takes a long time to obtain the result, there are many process flows, and the applicability is limited, the present invention discloses a method for quickly calculating the color photovoltaic computing efficiency, which includes the following steps:

[0036] a) Data preprocessing stage: receiving pictures uploaded by users, analyzing them, removing noise and irrelevant elements, converting pictures from conventional color space (such as SRGB) 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; in step a), the method for calculating the RGB color arrangement mode 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; in step a), the data preprocessing stage uses a data processing unit to process the data, numbers each color combination for subsequent query and calculation, preprocesses the data, such as image denoising, color space conversion, etc., and passes the processed data to the simulation calculation unit for optimization calculation;

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

[0038] c) Hot spot phenomenon prediction stage: using electroluminescence imaging technology (EL) to simulate the distribution of current in photovoltaic modules, analyzing the areas where hot spots may occur based on the simulated current distribution data, and evaluating the impact on the performance of photovoltaic modules. 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 photovoltaic modules, analyze the current distribution data, and predict the areas where hot spots may occur. In the steps b) and c), the simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. The photovoltaic efficiency simulation stage uses the photovoltaic efficiency simulation module to process data, and the hot spot phenomenon prediction stage uses the hot spot phenomenon prediction module to process data. According to the prediction results, the impact of each color combination on the hot spot phenomenon is evaluated. The simulation operation unit includes a photovoltaic efficiency simulation module and a hot spot phenomenon prediction module. The photovoltaic efficiency simulation stage uses the photovoltaic efficiency simulation module to process data, and the hot spot phenomenon prediction stage uses the hot spot phenomenon prediction module to process 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 the optimization is completed, an optimized picture is generated and displayed to the user for review and confirmation. In the 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 color arrangement and combination to improve the overall power generation efficiency. In the step d), the color optimization stage uses an optimization unit to process data, adjust the color difference value of the picture to further optimize performance and avoid hot spot phenomena, adjust the color difference value of the picture to further optimize performance, and pass the optimized data to the display unit for display;

[0040] e) Result output and feedback stage: output the optimized pictures, predicted power generation efficiency, hot spot phenomenon prediction results and other information 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 based on user feedback. In the step e), the method of accurate color presentation is to use color management technology to simulate the accurate color combined with the photovoltaic module after spraying. In the step e), the display unit is used to process the data in the result output and feedback stage, and the simulation results are displayed in a visual form, so that the customer can intuitively see the actual effect of the selected picture on the photovoltaic module, provide an intuitive interface, and facilitate users to view and select the optimized color combination, and can customize the display settings according to user needs;

[0041] 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.

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

[0043] The data collection and processing methods mentioned, especially the refined processing of data analysis, denoising and calibration, are important foundations 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 key technologies for achieving accurate evaluation of the energy efficiency of photovoltaic power generation systems. 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 photovoltaic power generation systems, are important technical means to ensure the efficient operation of the system.

[0044] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in 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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