Photovoltaic panel conversion power rapid detection method and system

Abstract

According to the photovoltaic panel conversion power rapid detection method and system provided by the invention, credible weights in solar energy conversion power analysis results corresponding to different photovoltaic panel conversion power detection networks are mapped into the same credible weight SQL database; therefore, the conditions that grammar errors occur in the real-time photovoltaic energy conversion information catalog represented by the spliced solar energy conversion power analysis results and the detection of the real-time photovoltaic energy conversion information is inaccurate due to different credible weight distribution conditions in a plurality of solar energy conversion power analysis results can be avoided; moreover, the capability of obtaining real-time photovoltaic energy conversion information description by a plurality of photovoltaic panel conversion power detection networks can be considered, the reliability of the obtained real-time photovoltaic energy conversion information catalog is ensured, and the real-time photovoltaic energy conversion information can be accurately detected. Therefore, the accuracy of target solar energy conversion power analysis result detection is ensured.

Description

Technical Field

[0001] This application relates to the technical field of rapid data detection. Specifically, it relates to a method and system for rapidly detecting the conversion power of a photovoltaic panel. Background Art

[0002] The conversion power of a photovoltaic panel refers to the power of converting solar radiant energy into electrical energy per unit area, usually expressed in watts per square meter (W / m²). The larger this value, the higher the conversion efficiency of the photovoltaic panel. The influencing factors of the conversion power of a photovoltaic panel: Illuminance: The higher the illuminance, the greater the conversion power of the photovoltaic panel. Temperature: The higher the temperature of the photovoltaic panel, the conversion power will decrease. Therefore, its heat dissipation effect needs to be considered during installation. Material: Different materials will affect the current output of the photovoltaic panel. Common materials include monocrystalline silicon, polycrystalline silicon, amorphous silicon, etc. Area: The larger the area, the higher the conversion power of the photovoltaic panel.

[0003] During the actual detection process, due to many interference factors, the conversion power of the photovoltaic panel cannot be accurately obtained. Therefore, a technical solution is urgently needed to overcome the above technical problems. Summary of the Invention

[0004] To improve the technical problems existing in the related art, this application provides a method and system for rapidly detecting the conversion power of a photovoltaic panel.

[0005] In the first aspect, a method for rapidly detecting the conversion power of a photovoltaic panel is provided, including: Processing the real-time photovoltaic energy conversion information through multiple photovoltaic panel conversion power detection networks respectively to obtain a first solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The first solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor at each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information; For each first solar energy conversion power analysis result, mapping the credible weights in the first solar energy conversion power analysis result to the target credible weight SQL database through the credible weights in the first solar energy conversion power analysis result to obtain a second solar energy conversion power analysis result; Stitching multiple second solar energy conversion power analysis results to obtain a stitched solar energy conversion power analysis result. The stitched solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor at each position of the power conversion influencing factor described in the target real-time photovoltaic energy conversion information; Obtaining a target solar energy conversion power analysis result through the stitched solar energy conversion power analysis result.

[0006] In this application, for each first solar energy conversion power analysis result, by means of the credible weight in the first solar energy conversion power analysis result, mapping the credible weight in the first solar energy conversion power analysis result to the target credible weight SQL database to obtain a second solar energy conversion power analysis result, including: Based on the first solar energy conversion power analysis result, determine a first credible weight and a first predicted credible index. The first credible weight is the minimum credible weight in the first solar energy conversion power analysis result, and the first predicted credible index is the predicted credible index of the maximum credible weight in the first solar energy conversion power analysis result and the first credible weight; Based on the target credible weight SQL database, determine a second credible weight and a second predicted credible index. The second credible weight is the minimum credible weight in the target credible weight SQL database, and the second predicted credible index is the predicted credible index of the maximum credible weight in the target credible weight SQL database and the second credible weight; Based on the multiple credible weights in the first solar energy conversion power analysis result, determine multiple third predicted credible indexes; for each third predicted credible index, determine the comparison result between the third predicted credible index and the first predicted credible index, determine the product of the comparison result and the second predicted credible index, and take the sum of the product and the second credible weight as the third credible weight. The third predicted credible index is the predicted credible index of any credible weight in the first solar energy conversion power analysis result and the first credible weight; Adjust each credible weight in the first solar energy conversion power analysis result to the corresponding third credible weight to obtain the second solar energy conversion power analysis result.

[0007] In this application, the obtaining of the target solar energy conversion power analysis result by means of the spliced solar energy conversion power analysis result includes: Based on the spliced solar energy conversion power analysis result and the multiple power conversion influencing factors, obtain multiple example photovoltaic energy conversion information catalogs and the credible weight corresponding to each example photovoltaic energy conversion information catalog. The credible weight corresponding to the example photovoltaic energy conversion information catalog indicates the credible weight obtained from the spliced solar energy conversion power analysis result for obtaining the template photovoltaic energy conversion information description. The power conversion influencing factors at the same position of the power conversion influencing factors in different example photovoltaic energy conversion information catalogs are not completely the same; Based on the credible weights of the multiple template photovoltaic energy conversion information descriptions, take the example photovoltaic energy conversion information catalog with the largest credible weight as the target solar energy conversion power analysis result.

[0008] In this application, obtaining the target solar conversion power analysis result by splicing the solar conversion power analysis results includes: Determining the power conversion influencing factors located at the positions of each power conversion influencing factor through the spliced solar conversion power analysis results and the multiple power conversion influencing factors, and forming the target solar conversion power analysis result with the determined power conversion influencing factors.

[0009] In this application, before splicing the multiple second solar conversion power analysis results to obtain the spliced solar conversion power analysis result, the method further includes: Determining a second quantity from the first quantities corresponding to the multiple second solar conversion power analysis results, where the second quantity is the largest first quantity among the first quantities corresponding to the multiple second solar conversion power analysis results, and the first quantity corresponding to the second solar conversion power analysis result indicates the number of positions of the power conversion influencing factors corresponding to the second solar conversion power analysis result; Based on the first quantity corresponding to the third solar conversion power analysis result being less than the second quantity, determining a third quantity, where the third quantity is the prediction credibility index of the second quantity and the first quantity corresponding to the third solar conversion power analysis result, and the third solar conversion power analysis result is a random one among the multiple second solar conversion power analysis results; Adding the credibility weights of each power conversion influencing factor in the multiple power conversion influencing factors at the target power conversion influencing factor positions of the third value to the third solar conversion power analysis result. After adding, the number of positions of the power conversion influencing factors corresponding to the third solar conversion power analysis result reaches the second quantity. The credibility weight of each power conversion influencing factor at the target power conversion influencing factor position is the first value. Among them, in the real-time photovoltaic energy conversion information catalog corresponding to the third solar conversion power analysis result after adding, the target power conversion influencing factor position is located after the positions of the remaining power conversion influencing factors.

[0010] In this application, splicing the multiple second solar conversion power analysis results to obtain the spliced solar conversion power analysis result is executed by a model, and the method further includes: Through the multiple photovoltaic panel conversion power detection networks, the template photovoltaic energy conversion information is processed respectively to obtain a fourth solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The fourth solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each power conversion influencing factor position described in the first real-time photovoltaic energy conversion information. The first real-time photovoltaic energy conversion information directory is the directory of the template photovoltaic energy conversion information. For each fourth solar energy conversion power analysis result, through the credible weights in the fourth solar energy conversion power analysis result, the credible weights in the fourth solar energy conversion power analysis result are mapped into the target credible weight SQL database to obtain a fifth solar energy conversion power analysis result. Through the model, multiple fifth solar energy conversion power analysis results are spliced to obtain a sixth solar energy conversion power analysis result. The sixth solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each power conversion influencing factor position described in the second real-time photovoltaic energy conversion information. The second real-time photovoltaic energy conversion information directory is the directory of the template photovoltaic energy conversion information. The model is configured through the example directory of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

[0011] In this application, the configuring of the model through the example directory of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result includes: Through the example directory, an example solar energy conversion power analysis result is determined. The example solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each power conversion influencing factor position described in the example. Among them, the credible weight of the power conversion influencing factor in the example directory at the corresponding power conversion influencing factor position is a second value, and the credible weights at the remaining power conversion influencing factor positions are third values. The model is configured through the example solar energy conversion power analysis result and the sixth solar energy conversion power analysis result.

[0012] In this application, for each fourth solar energy conversion power analysis result, the credible weight in the fourth solar energy conversion power analysis result is mapped to the target credible weight SQL database through the credible weight in the fourth solar energy conversion power analysis result, and the fifth solar energy conversion power analysis result is executed by a debugging model. Configuring the model through the example directory of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result includes: Configuring the model and the debugging model through the example directory of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

[0013] In this application, the method further includes: Extracting features of the template photovoltaic energy conversion information through the photovoltaic panel conversion power detection network to obtain the features of the template photovoltaic energy conversion information; Mining the features of the template photovoltaic energy conversion information through the photovoltaic panel conversion power detection network to obtain a seventh solar energy conversion power analysis result, where the seventh solar energy conversion power analysis result includes the credible weight of each power conversion influencing factor in the multiple power conversion influencing factors at each position of the power conversion influencing factor described in the third real-time photovoltaic energy conversion information, and the third real-time photovoltaic energy conversion information directory is the directory of the template photovoltaic energy conversion information; Configuring the photovoltaic panel conversion power detection network through the example directory of the template photovoltaic energy conversion information and the seventh solar energy conversion power analysis result.

[0014] In a second aspect, a photovoltaic panel conversion power rapid detection system is provided, including a processor and a memory that communicate with each other. The processor is configured to read and execute a computer program from the memory to implement the above method.

[0015] A method and system for quickly detecting the conversion power of a photovoltaic panel provided by an embodiment of the present application. Different photovoltaic panel conversion power detection networks have different abilities to obtain real-time photovoltaic energy conversion information descriptions. Therefore, when obtaining a real-time photovoltaic energy conversion information catalog of any real-time photovoltaic energy conversion information, multiple photovoltaic panel conversion power detection networks are used to process the same real-time photovoltaic energy conversion information to obtain a solar conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The credible weights in the solar conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are mapped into the same credible weight SQL database, and then the solar conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are spliced together, so as to use the spliced solar conversion power analysis result to obtain the final real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information. In this way, by mapping the credible weights in the solar conversion power analysis results corresponding to different photovoltaic panel conversion power detection networks into the same credible weight SQL database, it is possible to avoid the situation that the real-time photovoltaic energy conversion information catalog represented by splicing the solar conversion power analysis results has a syntax error and the real-time photovoltaic energy conversion information is detected inaccurately due to the different credible weight distribution situations in multiple solar conversion power analysis results, and it is possible to take into account the abilities of multiple photovoltaic panel conversion power detection networks to obtain real-time photovoltaic energy conversion information descriptions, ensure the reliability of the obtained real-time photovoltaic energy conversion information catalog, and accurately detect the real-time photovoltaic energy conversion information, thereby ensuring the accuracy of the target solar conversion power analysis result detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a flowchart of a method for quickly detecting the conversion power of a photovoltaic panel provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to better understand the above technical solutions, the technical solutions of the present application will be described in detail below through the drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solutions of the present application, rather than limitations on the technical solutions of the present application. Without conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0019] Please refer to Figure 1, which shows a method for quickly detecting the conversion power of a photovoltaic panel. This method may include the technical solutions described in steps 201 to 204 below.

[0020] 201. Process the real-time photovoltaic energy conversion information through multiple photovoltaic panel conversion power detection networks respectively to obtain a first solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The first solar energy conversion power analysis result includes the credibility weights of each power conversion influencing factor at each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information.

[0021] For example, the real-time photovoltaic energy conversion information can be the photovoltaic energy conversion information obtained by a monitoring device, specifically including: obtaining the electrical energy information of photovoltaic energy conversion under different scenarios.

[0022] The reason for setting multiple photovoltaic panel conversion power detection networks is that each photovoltaic panel conversion power detection network only needs to detect one type of photovoltaic energy conversion information, which can improve the detection accuracy and reduce interference.

[0023] The credibility weight at each position of each power conversion influencing factor can be understood as the reliability of the photovoltaic energy conversion rate at different positions under different influencing factors.

[0024] In an embodiment of the present application, the photovoltaic panel conversion power detection network is used to obtain the solar energy conversion power analysis result of the input real-time photovoltaic energy conversion information, so as to represent the real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information. Different photovoltaic panel conversion power detection networks have different capabilities of obtaining the description of the real-time photovoltaic energy conversion information. Therefore, for the same real-time photovoltaic energy conversion information, the solar energy conversion power analysis results obtained by different photovoltaic panel conversion power detection networks may be different. For example, for the same real-time photovoltaic energy conversion information, the data volumes of the solar energy conversion power analysis results obtained by different photovoltaic panel conversion power detection networks may be different. For another example, for the same real-time photovoltaic energy conversion information, the semantic coherence of the real-time photovoltaic energy conversion information description obtained through one photovoltaic panel conversion power detection network is good, and the context logic of the real-time photovoltaic energy conversion information description obtained through another photovoltaic panel conversion power detection network is more rigorous. Therefore, when obtaining the real-time photovoltaic energy conversion information catalog of any real-time photovoltaic energy conversion information, multiple photovoltaic panel conversion power detection networks are used to process the same real-time photovoltaic energy conversion information to obtain the solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. Then, the solar energy conversion power analysis results corresponding to the multiple photovoltaic panel conversion power detection networks are spliced together, so as to use the spliced solar energy conversion power analysis result to obtain the final real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information. In this way, the capabilities of different photovoltaic panel conversion power detection networks to obtain the description of the real-time photovoltaic energy conversion information can be taken into account, so as to ensure that the obtained real-time photovoltaic energy conversion information catalog can accurately detect the real-time photovoltaic energy conversion information and ensure the reliability of the description of the real-time photovoltaic energy conversion information.

[0025] Among them, the photovoltaic panel conversion power detection network is an arbitrary network model. For example, the photovoltaic panel conversion power detection network is DeepSeek (a kind of photovoltaic panel conversion power detection network). The real-time photovoltaic energy conversion information is any type of real-time photovoltaic energy conversion information. The first solar energy conversion power analysis result can be represented in any form. For example, the first solar energy conversion power analysis result is represented in the form of a queue. The rows of the queue correspond to multiple power conversion influencing factors respectively, and the columns of the queue correspond to the positions of each power conversion influencing factor. The multiple power conversion influencing factors are equivalent to the power conversion influencing factors in the data queue of the photovoltaic panel conversion power detection network. The data queue of the photovoltaic panel conversion power detection network covers as many power conversion influencing factors as possible, and all the power conversion influencing factors covered by any real-time photovoltaic energy conversion information are included in the data queue of the photovoltaic panel conversion power detection network.

[0026] In an embodiment of the present application, the first solar energy conversion power analysis result corresponding to the photovoltaic panel conversion power detection network is used to characterize the candidate real-time photovoltaic energy conversion information catalog corresponding to the photovoltaic panel conversion power detection network, and can reflect the credible weight of each power conversion influencing factor among multiple power conversion influencing factors at each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information. Each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information is used to carry the power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog. The number of positions of the power conversion influencing factors corresponding to the candidate real-time photovoltaic energy conversion information catalog is equivalent to the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog. That is, by filling each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information with the corresponding power conversion influencing factor, the candidate real-time photovoltaic energy conversion information catalog can be obtained. Moreover, since the capabilities of multiple photovoltaic panel conversion power detection networks to obtain real-time photovoltaic energy conversion information descriptions are different, among multiple first solar energy conversion power analysis results, the number of positions of the power conversion influencing factors corresponding to different first solar energy conversion power analysis results may be different.

[0027] 202. For each first solar energy conversion power analysis result, through the credible weight in the first solar energy conversion power analysis result, map the credible weight in the first solar energy conversion power analysis result to the target credible weight SQL database to obtain the second solar energy conversion power analysis result.

[0028] In an embodiment of the present application, the distribution of the credible weights in different first solar energy conversion power analysis results is different. Based on the different distribution of the credible weights in multiple first solar energy conversion power analysis results, if multiple first solar energy conversion power analysis results are directly spliced, the splicing effect will be poor due to the different distribution of the credible weights in multiple first solar energy conversion power analysis results, and then the resulting real-time photovoltaic energy conversion information catalog will have a syntax error and the detection of the real-time photovoltaic energy conversion information will be inaccurate. Therefore, based on obtaining multiple first solar energy conversion power analysis results, map the credible weight in each first solar energy conversion power analysis result to the target credible weight SQL database to obtain the second solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network, so that the credible weights in the obtained multiple second solar energy conversion power analysis results are all in the target credible weight SQL database, that is, the credible weights in multiple second solar energy conversion power analysis results are distributed in the same credible weight SQL database.

[0029] Among them, the target trusted weight SQL database is any numerical range. For example, the target trusted weight SQL database is a pre-set trusted weight SQL database. Another example is that the target trusted weight SQL database is the trusted weight SQL database corresponding to multiple first solar conversion power analysis results.

[0030] 203. Concatenate multiple second solar conversion power analysis results to obtain a concatenated solar conversion power analysis result. The concatenated solar conversion power analysis result includes the trusted weight of each power conversion influencing factor in each position of the power conversion influencing factor described in the target real-time photovoltaic energy conversion information among multiple power conversion influencing factors.

[0031] In the embodiment of the present application, since multiple second solar conversion power analysis results are used to represent the real-time photovoltaic energy conversion information catalog of the same real-time photovoltaic energy conversion information, and different second solar conversion power analysis results are obtained by different photovoltaic panel conversion power detection networks, by concatenating multiple second solar conversion power analysis results, the ability of different photovoltaic panel conversion power detection networks to obtain the description of real-time photovoltaic energy conversion information is taken into account, so that the concatenated solar conversion power analysis result can represent the real-time photovoltaic energy conversion information catalog of this real-time photovoltaic energy conversion information, and the target solar conversion power analysis result corresponding to the concatenated solar conversion power analysis result can accurately detect the real-time photovoltaic energy conversion information.

[0032] Among them, the concatenated solar conversion power analysis result can be represented in any form. For example, the concatenated solar conversion power analysis result is represented in the form of a queue. The rows of the queue correspond to multiple power conversion influencing factors respectively, and the columns of the queue correspond to each position of the power conversion influencing factor. The number of positions of the power conversion influencing factor corresponding to the target solar conversion power analysis result is the same as the number of positions of the power conversion influencing factor corresponding to any candidate real-time photovoltaic energy conversion information catalog. That is, among the candidate real-time photovoltaic energy conversion information catalogs corresponding to multiple photovoltaic panel conversion power detection networks, the data volume of the target real-time photovoltaic energy conversion information description is the same as the data volume of any candidate real-time photovoltaic energy conversion information description.

[0033] 204. Obtain the target solar conversion power analysis result through the concatenated solar conversion power analysis result.

[0034] In the embodiments of the present application, the spliced solar conversion power analysis result can reflect the credible weight of each power conversion influencing factor among multiple power conversion influencing factors at each position of the power conversion influencing factor described by the target real-time photovoltaic energy conversion information. By splicing the credible weights in the solar conversion power analysis result, it is possible to fill in the power conversion influencing factors for each position of the power conversion influencing factor described by the target real-time photovoltaic energy conversion information from among multiple power conversion influencing factors, so as to obtain the target solar conversion power analysis result.

[0035] In the solution provided by the embodiments of the present application, different photovoltaic panel conversion power detection networks have different abilities to obtain the description of real-time photovoltaic energy conversion information. Therefore, when obtaining the real-time photovoltaic energy conversion information catalog of any real-time photovoltaic energy conversion information, multiple photovoltaic panel conversion power detection networks are used to process the same real-time photovoltaic energy conversion information to obtain the solar conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The credible weights in the solar conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are mapped into the same credible weight SQL database, and then the solar conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are spliced, so as to use the spliced solar conversion power analysis result to obtain the final real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information. In this way, by mapping the credible weights in the solar conversion power analysis results corresponding to different photovoltaic panel conversion power detection networks into the same credible weight SQL database, it is possible to avoid the situation where the real-time photovoltaic energy conversion information catalog represented by the spliced solar conversion power analysis result has a syntax error and the detection of the real-time photovoltaic energy conversion information is inaccurate due to the different distributions of the credible weights in multiple solar conversion power analysis results, and it is possible to take into account the abilities of multiple photovoltaic panel conversion power detection networks to obtain the description of real-time photovoltaic energy conversion information, ensure the reliability of the obtained real-time photovoltaic energy conversion information catalog, and accurately detect the real-time photovoltaic energy conversion information, thereby ensuring the accuracy of the detection of the target solar conversion power analysis result.

[0036] Before splicing multiple second solar conversion power analysis results in the embodiments of the present application, the number of positions of the power conversion influencing factors corresponding to the multiple second solar conversion power analysis results and the covered credible weights will also be adjusted to make the number of positions of the power conversion influencing factors corresponding to the multiple second solar conversion power analysis results the same. The specific process is described in detail in the following embodiments.

[0037] Another method for quickly detecting the photovoltaic panel conversion power provided by the embodiments of the present application is executed by, and the method includes: 301. Through multiple photovoltaic panel conversion power detection networks, the real-time photovoltaic energy conversion information is processed respectively to obtain the first solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The first solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among multiple power conversion influencing factors at each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information.

[0038] For a possible embodiment, the real-time photovoltaic energy conversion information is the theme, and the photovoltaic panel conversion power detection network is a model configured for the theme. Each photovoltaic panel conversion power detection network is used to obtain the real-time photovoltaic energy conversion information catalog of the theme.

[0039] For example, these two photovoltaic panel conversion power detection networks are configured by the theme from different general photovoltaic panel conversion power detection networks. The general photovoltaic panel conversion power detection network is used to obtain the real-time photovoltaic energy conversion information catalog of any type of real-time photovoltaic energy conversion information. The general photovoltaic panel conversion power detection network is configured by the theme so that the configured photovoltaic panel conversion power detection network can accurately obtain the real-time photovoltaic energy conversion information catalog of the theme.

[0040] 302. For each first solar energy conversion power analysis result, through the credible weights in the first solar energy conversion power analysis result, the credible weights in the first solar energy conversion power analysis result are mapped into the target credible weight SQL database to obtain the second solar energy conversion power analysis result.

[0041] For a possible embodiment, the process of mapping the credible weights in any first solar power conversion power analysis result includes: determining a first credible weight and a first predicted credible index through the first solar power conversion power analysis result, where the first credible weight is the minimum credible weight in the first solar power conversion power analysis result, and the first predicted credible index is the predicted credible index of the maximum credible weight in the first solar power conversion power analysis result and the first credible weight; determining a second credible weight and a second predicted credible index through the target credible weight SQL database, where the second credible weight is the minimum credible weight in the target credible weight SQL database, and the second predicted credible index is the predicted credible index of the maximum credible weight in the target credible weight SQL database and the second credible weight; determining multiple third predicted credible indexes through multiple credible weights in the first solar power conversion power analysis result; for each third predicted credible index, determining the comparison result between the third predicted credible index and the first predicted credible index, determining the product of the comparison result and the second predicted credible index, and taking the sum of the product and the second credible weight as the third credible weight, where the third predicted credible index is the predicted credible index of any credible weight in the first solar power conversion power analysis result and the first credible weight; adjusting each credible weight in the first solar power conversion power analysis result to the corresponding third credible weight to obtain a second solar power conversion power analysis result.

[0042] Among them, the predicted credible index is understood as a loss value in this application.

[0043] Among them, multiple third predicted credible indexes correspond one by one to multiple credible weights in the first solar power conversion power analysis result. Taking the predicted credible index of each credible weight in the first solar power conversion power analysis result and the first credible weight as the third predicted credible index, multiple third predicted credible indexes can be obtained. The third credible weight is the credible weight obtained by mapping the credible weight in the first solar power conversion power analysis result to the target credible weight SQL database. For any credible weight in the first solar power conversion power analysis result, the third credible weight obtained through the third predicted credible index corresponding to this credible weight is the third credible weight corresponding to this credible weight.

[0044] In the embodiment of this application, for each credible weight in the first solar power conversion power analysis result, each credible weight can be mapped to the target credible weight SQL database in the above manner to obtain the third credible weight corresponding to each credible weight. Adjusting each credible weight in the first solar power conversion power analysis result to the corresponding third credible weight can obtain a second solar power conversion power analysis result, so as to indicate the credible weights of each power conversion influencing factor in each power conversion influencing factor position described in the candidate real-time photovoltaic energy conversion information among multiple power conversion influencing factors.

[0045] In the embodiment of the present application, by using the minimum credible weight and the maximum credible weight in the first solar power conversion analysis result, and the minimum credible weight and the maximum credible weight in the target credible weight SQL database, the credible weights in the first solar power conversion analysis result are mapped into the target credible weight SQL database, so as to ensure that the mapped credible weights can not only retain the magnitude relationship among multiple credible weights in the first solar power conversion analysis result, but also ensure that the credible weights in the second solar power conversion analysis result are in the target credible weight SQL database, thereby ensuring the reliability of the second solar power conversion analysis result.

[0046] It can be understood that in the embodiment of the present application, the credible weights in the first solar power conversion analysis result are mapped into the target credible weight SQL database by using the minimum credible weight in the first solar power conversion analysis result and the minimum credible weight in the target credible weight SQL database. In another embodiment, the credible weights in the first solar power conversion analysis result can also be mapped into the target credible weight SQL database by using the maximum credible weight in the first solar power conversion analysis result and the maximum credible weight in the target credible weight SQL database. For example, the maximum credible weight in the first solar power conversion analysis result is called the fourth credible weight, and the maximum credible weight in the target credible weight SQL database is called the fifth credible weight. Through multiple credible weights in the first solar power conversion analysis result, multiple fourth predicted credible indicators are determined. For each fourth predicted credible indicator, the comparison result between the fourth predicted credible indicator and the first predicted credible indicator is determined, and the product of the comparison result and the second predicted credible indicator is determined. The fifth credible weight and the predicted credible indicator of the product are used as the third credible weight. The fourth predicted credible indicator is the predicted credible indicator of the fourth credible weight and any credible weight in the first solar power conversion analysis result; each credible weight in the first solar power conversion analysis result is adjusted to the corresponding third credible weight to obtain the second solar power conversion analysis result.

[0047] Regarding a possible embodiment, step 302 includes: for each first solar power conversion analysis result, through a debugging model, the credible weights in the first solar power conversion analysis result are mapped into the target credible weight SQL database by using the credible weights in the first solar power conversion analysis result, so as to obtain the second solar power conversion analysis result.

[0048] 303. Determine a second quantity from among the first quantities corresponding to multiple second solar energy conversion power analysis results. The second quantity is the largest first quantity among the first quantities corresponding to the multiple second solar energy conversion power analysis results. The first quantity corresponding to a second solar energy conversion power analysis result indicates the number of power conversion influencing factor positions corresponding to the second solar energy conversion power analysis result.

[0049] In an embodiment of the present application, the number of power conversion influencing factor positions corresponding to a second solar energy conversion power analysis result is equivalent to the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog corresponding to the second solar energy conversion power analysis result. The first quantity is equivalent to the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog corresponding to the photovoltaic panel conversion power detection network. For the same real-time photovoltaic energy conversion information, the amount of data described by the real-time photovoltaic energy conversion information obtained by different photovoltaic panel conversion power detection networks may be different. That is, the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalogs obtained by different photovoltaic panel conversion power detection networks may be different. The second quantity is equivalent to the maximum amount of data described by the candidate real-time photovoltaic energy conversion information corresponding to multiple photovoltaic panel conversion power detection networks. Therefore, determine the largest first quantity from among the first quantities corresponding to the multiple second solar energy conversion power analysis results, so as to adjust the number of credible weights in the second solar energy conversion power analysis results through the largest first quantity, so that the amount of data described by the candidate real-time photovoltaic energy conversion information corresponding to the adjusted multiple second solar energy conversion power analysis results is the same.

[0050] 304. On the basis that the first quantity corresponding to the third solar energy conversion power analysis result is less than the second quantity, determine a third quantity. The third quantity is the predicted credibility index of the second quantity and the first quantity corresponding to the third solar energy conversion power analysis result. The third solar energy conversion power analysis result is a random one among the multiple second solar energy conversion power analysis results.

[0051] In an embodiment of the present application, among the multiple second solar energy conversion power analysis results, if the first quantity corresponding to any second solar energy conversion power analysis result is less than the second quantity, it indicates that the amount of data described by the candidate real-time photovoltaic energy conversion information corresponding to the second solar energy conversion power analysis result is less than the maximum amount of data. The third quantity is equivalent to the predicted credibility index of the amount of data described by the candidate real-time photovoltaic energy conversion information corresponding to the third solar energy conversion power analysis result and the maximum amount of data.

[0052] 305. In the third solar energy conversion power analysis result, add the confidence weights of each power conversion influencing factor among multiple power conversion influencing factors at the target power conversion influencing factor positions of the third value. The number of power conversion influencing factor positions corresponding to the added third solar energy conversion power analysis result reaches the second number, and the confidence weight of each power conversion influencing factor at the target power conversion influencing factor position is the first value. Among them, in the real-time photovoltaic energy conversion information directory corresponding to the added third solar energy conversion power analysis result, the target power conversion influencing factor position is located after the positions of the remaining power conversion influencing factors.

[0053] In the embodiments of the present application, the positions of each power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information are arranged in sequence in the candidate real-time photovoltaic energy conversion information directory. On the basis that the first number corresponding to the third solar energy conversion power analysis result is less than the second number, add the confidence weights of each power conversion influencing factor among multiple power conversion influencing factors at the target positions of the third value in the third solar energy conversion power analysis result, so that the data volume of the real-time photovoltaic energy conversion information described by the added third solar energy conversion power analysis result reaches the maximum data volume. In the real-time photovoltaic energy conversion information directory corresponding to the added third solar energy conversion power analysis result, the target power conversion influencing factor position is located after the positions of the remaining power conversion influencing factors, so that the initial information output by the photovoltaic panel conversion power detection network can be retained as much as possible when determining the real-time photovoltaic energy conversion information directory through the added third solar energy conversion power analysis result subsequently.

[0054] Among them, the first value is an arbitrary value. For example, the first value is 0.

[0055] In the embodiment of the present application, the first quantity corresponding to the second solar conversion power analysis result is equivalent to the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog corresponding to the photovoltaic panel conversion power detection network; for the same real-time photovoltaic energy conversion information, the data volume described by the real-time photovoltaic energy conversion information obtained by different photovoltaic panel conversion power detection networks may be different, that is, the number of power conversion influencing factors covered by the candidate real-time photovoltaic energy conversion information catalog obtained by different photovoltaic panel conversion power detection networks may be different, and the second quantity is equivalent to the maximum data volume described by the candidate real-time photovoltaic energy conversion information corresponding to multiple photovoltaic panel conversion power detection networks. Therefore, from the first quantities corresponding to multiple second solar conversion power analysis results, the largest first quantity is determined, so that on the basis that the first quantity corresponding to any second credible weight information is less than the largest first quantity, the credible weight quantity in the second solar conversion power analysis result is adjusted by the largest first quantity, so that the data volumes described by the candidate real-time photovoltaic energy conversion information corresponding to the adjusted multiple second solar conversion power analysis results are the same, and in the real-time photovoltaic energy conversion information catalog corresponding to the second solar conversion power analysis result after adding the credible weight, the position of the target power conversion influencing factor is behind the positions of the remaining power conversion influencing factors, so as to retain as much as possible the initial information output by multiple photovoltaic panel conversion power detection networks, so that when multiple second solar conversion power analysis results are spliced subsequently, the candidate real-time photovoltaic energy conversion information catalogs corresponding to multiple photovoltaic panel conversion power detection networks can be taken into account as much as possible, avoiding damage to the initial information output by the photovoltaic panel conversion power detection network, so as to be able to take into account the ability of each photovoltaic panel conversion power detection network to obtain the description of the real-time photovoltaic energy conversion information, so as to ensure that the subsequent obtained real-time photovoltaic energy conversion information catalog can accurately detect the real-time photovoltaic energy conversion information and can reflect the meaning expressed by the original real-time photovoltaic energy conversion information, thus ensuring the accuracy of the target solar conversion power analysis result detection.

[0056] 306. Splice multiple second solar conversion power analysis results to obtain a spliced solar conversion power analysis result, and the spliced solar conversion power analysis result includes the credible weights of each power conversion influencing factor among multiple power conversion influencing factors at each power conversion influencing factor position described in the target real-time photovoltaic energy conversion information.

[0057] In the embodiment of the present application, the credible weights in the real-time multiple second solar conversion power analysis results are in the same credible weight SQL database, and the data volumes described by the candidate real-time photovoltaic energy conversion information corresponding to the real-time multiple second solar conversion power analysis results are the same. Splice the multiple second solar conversion power analysis results to ensure the reliability of the spliced solar conversion power analysis result.

[0058] For a possible embodiment, step 306 includes: splicing a plurality of second solar conversion power analysis results to obtain splicing information, and splicing the splicing information to obtain a spliced solar conversion power analysis result.

[0059] In the embodiment of the present application, a plurality of second solar conversion power analysis results are first spliced so as to splice the splicing information, so that different second solar conversion power analysis results can be fully spliced, thereby ensuring the reliability of the spliced solar conversion power analysis result.

[0060] For a possible embodiment, step 306 includes: splicing a plurality of second solar conversion power analysis results through a model to obtain a spliced solar conversion power analysis result.

[0061] 307. Obtain a target solar conversion power analysis result by splicing the solar conversion power analysis result.

[0062] For a possible embodiment, step 307 includes the following two methods.

[0063] The first method: By splicing the solar conversion power analysis result and a plurality of power conversion influencing factors, obtain a plurality of sample photovoltaic energy conversion information directories and the corresponding credibility weights for each sample photovoltaic energy conversion information directory. The credibility weight corresponding to the sample photovoltaic energy conversion information directory indicates the credibility weight obtained by splicing the solar conversion power analysis result to obtain the template photovoltaic energy conversion information description. The power conversion influencing factors at the same position of the power conversion influencing factors in different sample photovoltaic energy conversion information directories are not completely the same; through the credibility weights of a plurality of template photovoltaic energy conversion information descriptions, use the sample photovoltaic energy conversion information directory with the largest credibility weight as the target solar conversion power analysis result.

[0064] In the embodiments of the present application, the spliced solar conversion power analysis result includes the credible weight of each power conversion influencing factor among multiple power conversion influencing factors at each position of the power conversion influencing factor described in the target real-time photovoltaic energy conversion information. Then, according to the spliced solar conversion power analysis result, in the process of determining the power conversion influencing factor for each position of the power conversion influencing factor described in the target real-time photovoltaic energy conversion information, multiple exemplary photovoltaic energy conversion information catalogs can be determined. And the power conversion influencing factors at the same position of the power conversion influencing factor in different exemplary photovoltaic energy conversion information catalogs are not completely the same. And through the credible weight of each power conversion influencing factor in each exemplary photovoltaic energy conversion information catalog at each position of the power conversion influencing factor, the credible weight of each template photovoltaic energy conversion information description is determined. The credible weight of the template photovoltaic energy conversion information description indicates the credible weight of obtaining the template photovoltaic energy conversion information description through the spliced solar conversion power analysis result, and can also reflect the reliability of the exemplary photovoltaic energy conversion information catalog in detecting the real-time photovoltaic energy conversion information, and can also reflect the reliability of the meaning reflected by the exemplary photovoltaic energy conversion information catalog, so as to use the exemplary photovoltaic energy conversion information catalog with the largest credible weight as the target solar conversion power analysis result to ensure that the target solar conversion power analysis result can accurately detect the real-time photovoltaic energy conversion information and can reflect the meaning expressed by the original real-time photovoltaic energy conversion information, thus ensuring the accuracy of the detection of the target solar conversion power analysis result.

[0065] For a possible embodiment involved, the process of determining the template photovoltaic energy conversion information description includes: determining a power conversion influencing factor for each position of the power conversion influencing factor respectively from multiple power conversion influencing factors, forming an exemplary photovoltaic energy conversion information catalog with the determined power conversion influencing factors, and determining the credible weight of the template photovoltaic energy conversion information description through the credible weight of the power conversion influencing factors covered by the exemplary photovoltaic energy conversion information catalog at each position of the power conversion influencing factor.

[0066] In the embodiments of the present application, by adopting the Viterbi algorithm, through multiple power conversion influencing factors and the spliced solar conversion power analysis result, multiple exemplary photovoltaic energy conversion information catalogs can be determined, and the credible weight of each template photovoltaic energy conversion information description can be determined to ensure the reliability of the obtained credible weight.

[0067] Optionally, the process of determining the credibility weight of the template photovoltaic energy conversion information description includes: determining the credibility weight of each power conversion influencing factor in the corresponding power conversion influencing factor position in the exemplary photovoltaic energy conversion information catalog from the parsed results of the spliced solar conversion power, and determining the target credibility weight corresponding to each power conversion influencing factor in the exemplary photovoltaic energy conversion information catalog; taking the product of the credibility weight of each power conversion influencing factor in the corresponding power conversion influencing factor position in the exemplary photovoltaic energy conversion information catalog and the target credibility weight corresponding to each power conversion influencing factor as the credibility weight of the template photovoltaic energy conversion information description. Among them, taking the power conversion influencing factor located at the position of the first power conversion influencing factor in the real-time photovoltaic energy conversion information catalog as an example, the target credibility weight of the credibility weight corresponding to this power conversion influencing factor indicates that on the basis of the power conversion influencing factor at the position of the second power conversion influencing factor that has been determined, this power conversion influencing factor is used as the credibility weight of the power conversion influencing factor located at the position of the first power conversion influencing factor, and the position of the second power conversion influencing factor is the previous power conversion influencing factor position of the position of the first power conversion influencing factor.

[0068] In the embodiments of the present application, for the exemplary photovoltaic energy conversion information catalog, not only the credibility weight of each power conversion influencing factor in the corresponding power conversion influencing factor position in the exemplary photovoltaic energy conversion information catalog is determined, but also the target credibility weight corresponding to each power conversion influencing factor is determined, so as to determine that on the basis of the power conversion influencing factor at the previous power conversion influencing factor position that has been determined, the power conversion influencing factor is used as the credibility weight of the power conversion influencing factor located at the next power conversion influencing factor position, and then taking the product of the determined credibility weights as the credibility weight of the template photovoltaic energy conversion information description, so that the credibility weight of the template photovoltaic energy conversion information description can reflect the semantic coherence and context relevance of the template photovoltaic energy conversion information description, and further reflect the matching degree between the exemplary photovoltaic energy conversion information catalog and the real-time photovoltaic energy conversion information, so that the credibility weight can reflect the quality of the template photovoltaic energy conversion information description and ensure the reliability of the credibility weight.

[0069] Optionally, the process of determining the target credibility weight corresponding to the power conversion influencing factor includes: determining the first word type to which the power conversion influencing factor located at the position of the first power conversion influencing factor in the real-time photovoltaic energy conversion information catalog belongs and the second word type to which the power conversion influencing factor located at the position of the second power conversion influencing factor belongs; querying the word type information through the first word type and the second word type, and taking the queried credibility weight as the target credibility weight corresponding to the power conversion influencing factor at the position of the first power conversion influencing factor.

[0070] The second method: By splicing the analysis results of the solar energy conversion power and multiple power conversion influencing factors, determining the power conversion influencing factors located at each position of the power conversion influencing factors, and forming the target solar energy conversion power analysis result with the determined power conversion influencing factors.

[0071] In the embodiments of the present application, by splicing the analysis results of the solar energy conversion power and multiple power conversion influencing factors, and in accordance with the order of each position of the power conversion influencing factors in the target solar energy conversion power analysis result, respectively determine the power conversion influencing factors at each position of the power conversion influencing factors, so as to ensure that the credible weight corresponding to the determined power conversion influencing factors is large enough. Furthermore, form the target solar energy conversion power analysis result with the determined power conversion influencing factors, so as to ensure that the target solar energy conversion power analysis result can accurately detect the real-time photovoltaic energy conversion information and can reflect the meaning expressed by the original real-time photovoltaic energy conversion information, thereby ensuring the accuracy of the detection of the target solar energy conversion power analysis result.

[0072] Optionally, for any position of the power conversion influencing factor, through the credible weights of multiple power conversion influencing factors at this position of the power conversion influencing factor, take the power conversion influencing factor corresponding to the maximum credible weight as the power conversion influencing factor located at this position of the power conversion influencing factor, and form the target solar energy conversion power analysis result with the determined power conversion influencing factors.

[0073] In the embodiments of the present application, for the credible weights of multiple power conversion influencing factors at the same position of the power conversion influencing factor, the larger the credible weight, the greater the credible weight of the power conversion influencing factor located at this position of the power conversion influencing factor. Therefore, through the credible weights of multiple power conversion influencing factors at this position of the power conversion influencing factor, take the power conversion influencing factor corresponding to the maximum credible weight as the power conversion influencing factor located at this position of the power conversion influencing factor, and form the target solar energy conversion power analysis result with the determined power conversion influencing factors, so as to ensure the reliability of the description of the determined target real-time photovoltaic energy conversion information.

[0074] In the solution provided by the embodiment of the present application, different photovoltaic panel conversion power detection networks have different capabilities of obtaining real-time photovoltaic energy conversion information descriptions. Therefore, when obtaining the real-time photovoltaic energy conversion information catalog of any real-time photovoltaic energy conversion information, multiple photovoltaic panel conversion power detection networks are used to process the same real-time photovoltaic energy conversion information to obtain the solar energy conversion power analysis results corresponding to each photovoltaic panel conversion power detection network. The credible weights in the solar energy conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are mapped into the same credible weight SQL database, and then the solar energy conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are spliced, so as to use the spliced solar energy conversion power analysis results to obtain the final real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information. In this way, by mapping the credible weights in the solar energy conversion power analysis results corresponding to different photovoltaic panel conversion power detection networks into the same credible weight SQL database, it is possible to avoid the situation that the real-time photovoltaic energy conversion information catalog represented by splicing the solar energy conversion power analysis results has a syntax error and the real-time photovoltaic energy conversion information is detected inaccurately due to the different credible weight distribution situations in multiple solar energy conversion power analysis results, and it is possible to take into account the capabilities of multiple photovoltaic panel conversion power detection networks to obtain real-time photovoltaic energy conversion information descriptions, ensure the reliability of the obtained real-time photovoltaic energy conversion information catalog, and accurately detect the real-time photovoltaic energy conversion information, thereby ensuring the accuracy of the target solar energy conversion power analysis result detection.

[0075] Another photovoltaic panel conversion power fast detection method provided by the embodiment of the present application is executed by, and the method includes: 601. Process the template photovoltaic energy conversion information through multiple photovoltaic panel conversion power detection networks respectively to obtain the fourth solar energy conversion power analysis results corresponding to each photovoltaic panel conversion power detection network. The fourth solar energy conversion power analysis results include the credible weights of each power conversion influencing factor in each power conversion influencing factor position described in the first real-time photovoltaic energy conversion information, and the first real-time photovoltaic energy conversion information catalog is the catalog of the template photovoltaic energy conversion information.

[0076] Among them, the template photovoltaic energy conversion information is any type of real-time photovoltaic energy conversion information. For example, the template photovoltaic energy conversion information is a topic or other types of real-time photovoltaic energy conversion information. The fourth solar energy conversion power analysis results can be represented in any form. For example, the fourth solar energy conversion power analysis results are represented in the form of a queue, the rows of the queue correspond to multiple power conversion influencing factors respectively, and the columns of the queue correspond to each power conversion influencing factor position.

[0077] In the embodiment of the present application, the fourth solar energy conversion power analysis result corresponding to the photovoltaic panel conversion power detection network is used to characterize the first real-time photovoltaic energy conversion information directory corresponding to the photovoltaic panel conversion power detection network, and can reflect the credible weights of each power conversion influencing factor among a plurality of power conversion influencing factors at each position of the power conversion influencing factors described in the first real-time photovoltaic energy conversion information. Each position of the power conversion influencing factors described in the first real-time photovoltaic energy conversion information is used to carry the power conversion influencing factors covered by the first real-time photovoltaic energy conversion information directory. The number of positions of the power conversion influencing factors corresponding to the first real-time photovoltaic energy conversion information directory is equivalent to the number of power conversion influencing factors covered by the first real-time photovoltaic energy conversion information directory. That is, by filling the corresponding power conversion influencing factors at each position of the power conversion influencing factors described in the first real-time photovoltaic energy conversion information, the first real-time photovoltaic energy conversion information directory can be obtained.

[0078] It can be understood that the process of obtaining the fourth solar energy conversion power analysis result corresponding to the photovoltaic panel conversion power detection network is the same as that of step 301 above, and will not be elaborated here.

[0079] 602. For each fourth solar energy conversion power analysis result, map the credible weights in the fourth solar energy conversion power analysis result to the target credible weight SQL database through the credible weights in the fourth solar energy conversion power analysis result to obtain the fifth solar energy conversion power analysis result.

[0080] 603. Through the model, splice a plurality of fifth solar energy conversion power analysis results to obtain the sixth solar energy conversion power analysis result. The sixth solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among a plurality of power conversion influencing factors at each position of the power conversion influencing factors described in the second real-time photovoltaic energy conversion information. The second real-time photovoltaic energy conversion information directory is the directory of the template photovoltaic energy conversion information.

[0081] 604. Configure the model through the example directory of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

[0082] In the embodiment of the present application, the example directory of the template photovoltaic energy conversion information is the real directory of the template photovoltaic energy conversion information, and the example directory can accurately detect the template photovoltaic energy conversion information. The sixth solar energy conversion power analysis result is obtained through a model, and the sixth solar energy conversion power analysis result is used to characterize the second real-time photovoltaic energy conversion information directory. Then, through the example directory and the sixth solar energy conversion power analysis result, the difference between the example directory and the second real-time photovoltaic energy conversion information directory can be determined to reflect the reliability of the model. Therefore, through the example directory and the sixth solar energy conversion power analysis result, the model is configured so that when the sixth solar energy conversion power analysis result is obtained again through the configured model, the second real-time photovoltaic energy conversion information directory represented by the sixth solar energy conversion power analysis result is similar enough to the example directory to improve the reliability of the model.

[0083] For a possible embodiment involved, step 604 includes: determining an example solar energy conversion power analysis result through the example directory. The example solar energy conversion power analysis result includes the credible weight of each power conversion influencing factor in each power conversion influencing factor position described in the example among multiple power conversion influencing factors. Among them, the credible weight of the power conversion influencing factor in the corresponding power conversion influencing factor position in the example directory is the second value, and the credible weight in the remaining power conversion influencing factor positions is the third value; configuring the model through the example solar energy conversion power analysis result and the sixth solar energy conversion power analysis result.

[0084] In the embodiment of the present application, the example solar energy conversion power analysis result is determined through the example directory so that the example solar energy conversion power analysis result can reflect the credible weight of each power conversion influencing factor in each power conversion influencing factor position described in the example, in order to compare the credible weights in the example solar energy conversion power analysis result with those in the sixth solar energy conversion power analysis result, and it is easier to determine the difference between the two. This difference can reflect the reliability of the model. Therefore, through the example solar energy conversion power analysis result and the sixth solar energy conversion power analysis result, the model is configured to improve the reliability of the model.

[0085] Optionally, the number of positions of power conversion influencing factors corresponding to the example directory is different from the number of positions of power conversion influencing factors corresponding to the second real-time photovoltaic energy conversion information directory. That is, for the example solar conversion power analysis result and the sixth solar conversion power analysis result, according to the above steps 303-305, the number of positions of power conversion influencing factors corresponding to the example solar conversion power analysis result and the covered credible weights are debugged, or the number of positions of power conversion influencing factors corresponding to the sixth solar conversion power analysis result and the covered credible weights are debugged, so that the number of positions of power conversion influencing factors corresponding to the example solar conversion power analysis result and the sixth solar conversion power analysis result is the same. Then, the model is configured through the debugged example solar conversion power analysis result and the sixth solar conversion power analysis result. Or, the model is configured through the example solar conversion power analysis result and the debugged sixth solar conversion power analysis result.

[0086] For a possible embodiment involved, taking the debugging of the example solar conversion power analysis result as an example, the process of configuring the model includes: determining a first prediction credibility index through the debugged example solar conversion power analysis result and the sixth solar conversion power analysis result, and configuring the model through the first prediction credibility index.

[0087] In the embodiment of the present application, the number of positions of power conversion influencing factors corresponding to the debugged example solar conversion power analysis result and the sixth solar conversion power analysis result is the same. The method of determining the prediction credibility index is adopted to represent the difference between the debugged example solar conversion power analysis result and the sixth solar conversion power analysis result, and the model is configured through the prediction credibility index to ensure the reliability of the model configuration.

[0088] It can be understood that the above embodiment is described by taking the configuration of the model through a template photovoltaic energy conversion information as an example. In another embodiment, according to the above method, the model is iteratively configured through multiple template photovoltaic energy conversion information and the example directory of the template photovoltaic energy conversion information. On the basis that the number of iterations reaches the iteration threshold, or on the basis that the predicted credibility index obtained in real time is less than the predicted credibility index threshold, the configuration of the model is stopped. Among them, the iteration threshold is any value, and the predicted credibility index threshold is any value.

[0089] For a possible embodiment, the process of obtaining the example description includes: obtaining template photovoltaic energy conversion information and model indication information, where the model indication information instructs the photovoltaic panel conversion power detection network to process the input real-time photovoltaic energy conversion information to obtain a real-time photovoltaic energy conversion information catalog; through the generation model, using the model indication information, processing the template photovoltaic energy conversion information to obtain a catalog of examples of the template photovoltaic energy conversion information.

[0090] In the embodiments of the present application, by debugging the catalog to ensure that the example catalog can accurately detect the template photovoltaic energy conversion information, the reliability of the example description is ensured.

[0091] Optionally, on the basis of obtaining multiple pieces of template photovoltaic energy conversion information, uniform sampling is performed on various types of template photovoltaic energy conversion information to balance the quantity of each type of template photovoltaic energy conversion information. In accordance with the above method, through the generation model, a catalog of each sampled template photovoltaic energy conversion information is obtained, and the obtained catalog is debugged manually, and the debugged catalog is used as the example catalog of the template photovoltaic energy conversion information.

[0092] The process of mapping the trust weight to the target trust weight SQL database is executed by the debugging model. Then, during the process of configuring the model, the debugging model is also configured simultaneously. That is, the process of configuring the model includes: configuring the model and the debugging model through the example catalog of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

[0093] In the embodiments of the present application, the sixth solar energy conversion power analysis result is obtained through the debugging model and the model, and the sixth solar energy conversion power analysis result is used to characterize the second real-time photovoltaic energy conversion information catalog. Then, through the example catalog and the sixth solar energy conversion power analysis result, the difference between the example catalog and the second real-time photovoltaic energy conversion information catalog can be determined to reflect the reliability of the debugging model and the model. Therefore, through the example catalog and the sixth solar energy conversion power analysis result, the model and the debugging model are configured so that when the sixth solar energy conversion power analysis result is obtained again through the configured model and debugging model, the second real-time photovoltaic energy conversion information catalog represented by the sixth solar energy conversion power analysis result is sufficiently similar to the example catalog to improve the reliability of the model.

[0094] For a possible embodiment, step 604 includes: determining the exemplary solar conversion power analysis result through the exemplary directory, where the exemplary solar conversion power analysis result includes the credible weight of each power conversion influencing factor among multiple power conversion influencing factors at each power conversion influencing factor position described in the exemplar, and the credible weight of the power conversion influencing factor in the exemplary directory at the corresponding power conversion influencing factor position is the second value, and the credible weight at the remaining power conversion influencing factor positions is the third value; configuring the model and the debugging model through the exemplary solar conversion power analysis result and the sixth solar conversion power analysis result.

[0095] In the embodiment of the present application, the exemplary solar conversion power analysis result is determined through the exemplary directory, so as to compare the exemplary solar conversion power analysis result with the sixth solar conversion power analysis result, and then determine the difference between the two, which can reflect the reliability of the model. Therefore, the model and the debugging model are configured through the exemplary solar conversion power analysis result and the sixth solar conversion power analysis result to improve the reliability of the model and the debugging model.

[0096] Before configuring the model in the embodiment of the present application, it is also necessary to configure the photovoltaic panel conversion power detection network. The configuration process of the photovoltaic panel conversion power detection network includes: extracting the features of the template photovoltaic energy conversion information through the photovoltaic panel conversion power detection network to obtain the features of the template photovoltaic energy conversion information; mining the features of the template photovoltaic energy conversion information through the photovoltaic panel conversion power detection network to obtain the seventh solar conversion power analysis result, where the seventh solar conversion power analysis result includes the credible weight of each power conversion influencing factor among multiple power conversion influencing factors at each power conversion influencing factor position described in the third real-time photovoltaic energy conversion information respectively, and the third real-time photovoltaic energy conversion information directory is the directory of the template photovoltaic energy conversion information; configuring the photovoltaic panel conversion power detection network through the exemplary directory of the template photovoltaic energy conversion information and the seventh solar conversion power analysis result.

[0097] Among them, the features of the template photovoltaic energy conversion information are used to characterize the template photovoltaic energy conversion information, and these features can be represented in any form. For example, the features are represented in the form of vectors. The fourth solar energy conversion power analysis result is the same as the above-mentioned first solar energy conversion power analysis result, and will not be elaborated here. In the embodiments of the present application, by processing the template photovoltaic energy conversion information through a photovoltaic panel conversion power detection network, the difference between the obtained sixth solar energy conversion power analysis result and the example directory can reflect the reliability of the model. Then, through the example directory of the template photovoltaic energy conversion information and the seventh solar energy conversion power analysis result, the photovoltaic panel conversion power detection network is configured so that when the seventh solar energy conversion power analysis result is obtained again through the configured photovoltaic panel conversion power detection network, the real-time photovoltaic energy conversion information directory represented by the seventh solar energy conversion power analysis result is similar enough to the example directory to improve the reliability of the photovoltaic panel conversion power detection network.

[0098] In the solution provided by the embodiments of the present application, a real-time photovoltaic energy conversion information directory of real-time photovoltaic energy conversion information is obtained through multiple photovoltaic panel conversion power detection networks, a debugging model, and a model. By splicing the real-time photovoltaic energy conversion information directories obtained by different photovoltaic panel conversion power detection networks for the same real-time photovoltaic energy conversion information, it is ensured that the obtained real-time photovoltaic energy conversion information directory can accurately detect the real-time photovoltaic energy conversion information, so as to ensure the reliability of the description of the real-time photovoltaic energy conversion information. Moreover, during the process of configuring the model, a self-learning method can be adopted to debug the model parameters of the model, so that the model has the ability to splice the real-time photovoltaic energy conversion information descriptions of the same real-time photovoltaic energy conversion information output by multiple photovoltaic panel conversion power detection networks, so as to ensure the splicing effect of the model.

[0099] In the solution provided by the embodiments of the present application, real-time photovoltaic energy conversion information solar conversion power analysis results of the same real-time photovoltaic energy conversion information are obtained through multiple photovoltaic panel conversion power detection networks, and the credible weights in the multiple real-time photovoltaic energy conversion information solar conversion power analysis results are mapped to the same area, so that the credible weight SQL databases corresponding to the multiple real-time photovoltaic energy conversion information solar conversion power analysis results are aligned, to avoid differences in the credible weight SQL databases corresponding to the multiple real-time photovoltaic energy conversion information solar conversion power analysis results from affecting the subsequent splicing effect, and the number of positions of the power conversion influencing factors corresponding to the multiple real-time photovoltaic energy conversion information solar conversion power analysis results is debugged, so that the real-time photovoltaic energy conversion information catalogs represented by the multiple real-time photovoltaic energy conversion information solar conversion power analysis results after debugging are the same. Furthermore, when splicing the multiple real-time photovoltaic energy conversion information solar conversion power analysis results after debugging, the initial information output by the photovoltaic panel conversion power detection network can be retained, thus avoiding artificial damage to the natural language expression in the output results of the multiple photovoltaic panel conversion power detection networks. The final real-time photovoltaic energy conversion information catalog of the real-time photovoltaic energy conversion information is obtained by splicing the solar conversion power analysis results, so that the real-time photovoltaic energy conversion information catalog can accurately detect the real-time photovoltaic energy conversion information, to ensure the reliability of the description of the real-time photovoltaic energy conversion information.

[0100] On this basis, a device for quickly detecting the conversion power of a photovoltaic panel is provided. The device includes: A first result obtaining module, configured to process real-time photovoltaic energy conversion information through multiple photovoltaic panel conversion power detection networks respectively, to obtain a first solar conversion power analysis result corresponding to each photovoltaic panel conversion power detection network, where the first solar conversion power analysis result includes the credible weight of each power conversion influencing factor in the multiple power conversion influencing factors at each position of each power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information; A second result module, configured to, for each first solar conversion power analysis result, map the credible weight in the first solar conversion power analysis result to the target credible weight SQL database through the credible weight in the first solar conversion power analysis result, to obtain a second solar conversion power analysis result; A result splicing module, configured to splice multiple second solar conversion power analysis results to obtain a spliced solar conversion power analysis result, where the spliced solar conversion power analysis result includes the credible weight of each power conversion influencing factor in the multiple power conversion influencing factors at each position of each power conversion influencing factor described in the target real-time photovoltaic energy conversion information; A result detection module, configured to obtain a target solar energy conversion power analysis result by splicing the solar energy conversion power analysis results.

[0101] On the basis described above, a rapid detection system for the conversion power of a photovoltaic panel is shown, including a processor and a memory that communicate with each other. The processor is configured to read and execute a computer program from the memory to implement the above method.

[0102] On the basis described above, a computer-readable storage medium is further provided, on which a computer program stored realizes the above method when running.

[0103] In summary, based on the above solution, different photovoltaic panel conversion power detection networks have different capabilities to obtain real-time photovoltaic energy conversion information descriptions. Therefore, when obtaining a real-time photovoltaic energy conversion information directory of any real-time photovoltaic energy conversion information, multiple photovoltaic panel conversion power detection networks are used to process the same real-time photovoltaic energy conversion information to obtain the solar energy conversion power analysis results corresponding to each photovoltaic panel conversion power detection network. The credible weights in the solar energy conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are mapped to the same credible weight SQL database, and then the solar energy conversion power analysis results corresponding to multiple photovoltaic panel conversion power detection networks are spliced, so as to use the spliced solar energy conversion power analysis results to obtain the final real-time photovoltaic energy conversion information directory of the real-time photovoltaic energy conversion information. In this way, by mapping the credible weights in the solar energy conversion power analysis results corresponding to different photovoltaic panel conversion power detection networks to the same credible weight SQL database, it is possible to avoid the situation that the real-time photovoltaic energy conversion information directory represented by the spliced solar energy conversion power analysis results has a syntax error and the real-time photovoltaic energy conversion information is detected inaccurately due to different credible weight distribution situations in multiple solar energy conversion power analysis results, and it is possible to take into account the capabilities of multiple photovoltaic panel conversion power detection networks to obtain real-time photovoltaic energy conversion information descriptions, ensure the reliability of the obtained real-time photovoltaic energy conversion information directory, and be able to accurately detect the real-time photovoltaic energy conversion information, thereby ensuring the accuracy of the target solar energy conversion power analysis result detection.

[0104] It should be understood that the systems and their modules shown above can be implemented in various ways. For example, in some embodiments, the systems and their modules can be implemented through hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or covered by processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and their modules of the present application can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the above hardware circuits and software (e.g., firmware).

[0105] It can be understood that different embodiments may produce different beneficial effects. In different embodiments, the possible beneficial effects can be any one or several combinations of the above, or any other possible beneficial effects that can be obtained.

Claims

1. A method for quickly detecting the conversion power of a photovoltaic panel, characterized in that, The method includes: Processing real-time photovoltaic energy conversion information respectively through a plurality of photovoltaic panel conversion power detection networks to obtain a first solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network, where the first solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among a plurality of power conversion influencing factors at each position of the power conversion influencing factor described in the candidate real-time photovoltaic energy conversion information; For each first solar energy conversion power analysis result, mapping the credible weights in the first solar energy conversion power analysis result to the target credible weight SQL database through the credible weights in the first solar energy conversion power analysis result to obtain a second solar energy conversion power analysis result; Stitching a plurality of second solar energy conversion power analysis results to obtain a stitched solar energy conversion power analysis result, where the stitched solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the plurality of power conversion influencing factors at each position of the power conversion influencing factor described in the target real-time photovoltaic energy conversion information; Obtaining a target solar energy conversion power analysis result through the stitched solar energy conversion power analysis result.

2. The method according to claim 1, wherein The step of, for each first solar energy conversion power analysis result, mapping the credible weights in the first solar energy conversion power analysis result to the target credible weight SQL database through the credible weights in the first solar energy conversion power analysis result to obtain a second solar energy conversion power analysis result includes: Determining a first credible weight and a first predicted credible index through the first solar energy conversion power analysis result, where the first credible weight is the minimum credible weight in the first solar energy conversion power analysis result, and the first predicted credible index is the predicted credible index of the maximum credible weight in the first solar energy conversion power analysis result and the first credible weight; Determining a second credible weight and a second predicted credible index through the target credible weight SQL database, where the second credible weight is the minimum credible weight in the target credible weight SQL database, and the second predicted credible index is the predicted credible index of the maximum credible weight in the target credible weight SQL database and the second credible weight; Determining a plurality of third predicted credible indexes through the plurality of credible weights in the first solar energy conversion power analysis result; for each third predicted credible index, determining the comparison result between the third predicted credible index and the first predicted credible index, determining the product of the comparison result and the second predicted credible index, and taking the sum of the product and the second credible weight as the third credible weight, where the third predicted credible index is the predicted credible index of any credible weight in the first solar energy conversion power analysis result and the first credible weight; Adjusting each credible weight in the first solar energy conversion power analysis result to the corresponding third credible weight to obtain the second solar energy conversion power analysis result.

3. The method according to claim 1, wherein Obtaining the target solar energy conversion power analysis result through the spliced solar energy conversion power analysis result includes: Obtaining a plurality of example photovoltaic energy conversion information catalogs and the corresponding credible weights of each example photovoltaic energy conversion information catalog through the spliced solar energy conversion power analysis result and the plurality of power conversion influencing factors. The credible weight corresponding to the example photovoltaic energy conversion information catalog indicates the credible weight of obtaining the template photovoltaic energy conversion information description through the spliced solar energy conversion power analysis result. The power conversion influencing factors at the same power conversion influencing factor position in different example photovoltaic energy conversion information catalogs are not completely the same; Using the credible weights of the plurality of template photovoltaic energy conversion information descriptions to take the example photovoltaic energy conversion information catalog with the largest credible weight as the target solar energy conversion power analysis result.

4. The method according to claim 1, characterized in that, Obtaining the target solar energy conversion power analysis result through the spliced solar energy conversion power analysis result includes: Determining the power conversion influencing factors at each power conversion influencing factor position through the spliced solar energy conversion power analysis result and the plurality of power conversion influencing factors, and forming the target solar energy conversion power analysis result with the determined power conversion influencing factors.

5. The method according to claim 1, wherein Before splicing the plurality of second solar energy conversion power analysis results to obtain the spliced solar energy conversion power analysis result, the method further includes: Determining a second quantity from the first quantities corresponding to the plurality of second solar energy conversion power analysis results. The second quantity is the largest first quantity among the first quantities corresponding to the plurality of second solar energy conversion power analysis results. The first quantity corresponding to the second solar energy conversion power analysis result indicates the number of power conversion influencing factor positions corresponding to the second solar energy conversion power analysis result; Based on the first quantity corresponding to the third solar energy conversion power analysis result being less than the second quantity, determining a third quantity. The third quantity is the predicted credible index of the second quantity and the first quantity corresponding to the third solar energy conversion power analysis result. The third solar energy conversion power analysis result is a random one among the plurality of second solar energy conversion power analysis results; Adding, to the third solar energy conversion power analysis result, the credible weight of each power conversion influencing factor in the plurality of power conversion influencing factors at the target power conversion influencing factor position of the third value. After the addition, the number of power conversion influencing factor positions corresponding to the third solar energy conversion power analysis result reaches the second quantity. The credible weight of each power conversion influencing factor at the target power conversion influencing factor position is the first value. Among them, in the real-time photovoltaic energy conversion information catalog corresponding to the third solar energy conversion power analysis result after the addition, the target power conversion influencing factor position is located after the positions of the remaining power conversion influencing factors.

6. The method according to claim 1, characterized in that, The splicing of the plurality of second solar energy conversion power analysis results to obtain the spliced solar energy conversion power analysis result is performed by a model. The method further includes: Through the multiple photovoltaic panel conversion power detection networks, the template photovoltaic energy conversion information is processed respectively to obtain the fourth solar energy conversion power analysis result corresponding to each photovoltaic panel conversion power detection network. The fourth solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each position of the power conversion influencing factor described in the first real-time photovoltaic energy conversion information. The first real-time photovoltaic energy conversion information catalog is the catalog of the template photovoltaic energy conversion information; For each fourth solar energy conversion power analysis result, through the credible weights in the fourth solar energy conversion power analysis result, the credible weights in the fourth solar energy conversion power analysis result are mapped into the target credible weight SQL database to obtain the fifth solar energy conversion power analysis result; Through the model, multiple fifth solar energy conversion power analysis results are spliced to obtain the sixth solar energy conversion power analysis result. The sixth solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each position of the power conversion influencing factor described in the second real-time photovoltaic energy conversion information. The second real-time photovoltaic energy conversion information catalog is the catalog of the template photovoltaic energy conversion information; The model is configured through the example catalog of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

7. The method according to claim 6, wherein The configuring the model through the example catalog of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result includes: Through the example catalog, the example solar energy conversion power analysis result is determined. The example solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at each position of the power conversion influencing factor described in the example. Among them, the credible weight of the power conversion influencing factor in the example catalog at the corresponding position of the power conversion influencing factor is the second value, and the credible weights at the positions of the remaining power conversion influencing factors are the third values; The model is configured through the example solar energy conversion power analysis result and the sixth solar energy conversion power analysis result.

8. The method according to claim 6, wherein The step of mapping the credible weights in the fourth solar energy conversion power analysis result into the target credible weight SQL database through the credible weights in the fourth solar energy conversion power analysis result to obtain the fifth solar energy conversion power analysis result is executed by the debugging model. The configuring the model through the example catalog of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result includes: The model and the debugging model are configured through the example catalog of the template photovoltaic energy conversion information and the sixth solar energy conversion power analysis result.

9. The method according to claim 1, characterized in that, The method further includes: Extract the features of the template photovoltaic energy conversion information through the photovoltaic panel conversion power detection network to obtain the features of the template photovoltaic energy conversion information; Through the photovoltaic panel conversion power detection network, mine the features of the template photovoltaic energy conversion information to obtain the seventh solar energy conversion power analysis result, where the seventh solar energy conversion power analysis result includes the credible weights of each power conversion influencing factor among the multiple power conversion influencing factors at the position of each power conversion influencing factor described in the third real-time photovoltaic energy conversion information, and the third real-time photovoltaic energy conversion information catalog is the catalog of the template photovoltaic energy conversion information; Configure the photovoltaic panel conversion power detection network through the example catalog of the template photovoltaic energy conversion information and the seventh solar energy conversion power analysis result.

10. A rapid detection system for the conversion power of a photovoltaic panel, characterized in that, It includes a processor and a memory that communicate with each other. The processor is used to read and execute a computer program from the memory to implement the method according to any one of claims 1-9.

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