Photovoltaic heat energy conversion evaluation method and system

Abstract

According to the photovoltaic heat energy conversion evaluation method and system provided by the invention, the photovoltaic heat energy conversion efficiency characteristic evaluation is carried out on the photovoltaic heat energy conversion efficiency description data set; a first photovoltaic heat energy conversion efficiency characteristic evaluation network corresponding to a photovoltaic heat energy conversion efficiency characteristic can be intelligently selected according to the photovoltaic heat energy conversion efficiency characteristic of a heat energy conversion efficiency analysis result set in a photovoltaic heat energy conversion efficiency description data set; therefore, the photovoltaic heat energy conversion efficiency characteristics in the photovoltaic heat energy conversion efficiency description data set can be accurately evaluated. The method can be applied to evaluation of photovoltaic heat energy conversion efficiency characteristics of various factors, so that an electric energy conversion efficiency type set containing model photovoltaic heat energy conversion efficiency characteristics and photovoltaic heat energy conversion efficiency characteristics of various set factors at the same time can be evaluated by using the photovoltaic heat energy conversion efficiency evaluation method; and the accuracy of electric energy conversion efficiency type photovoltaic heat energy conversion efficiency characteristic evaluation can be considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric energy conversion evaluation, in particular to a photovoltaic thermal energy conversion evaluation method and system. BACKGROUND

[0002] ‌Photovoltaic power generation is a technology that converts solar energy into electricity directly by photovoltaic effect. Photovoltaic power generation system mainly consists of solar panels (components), controllers and inverters, which are mainly composed of electronic components and do not involve mechanical components, so the equipment is refined, reliable and stable, with long service life and easy installation and maintenance.‌ At present, the evaluation of photovoltaic power generation capacity is a very important work. The specific installation position of the equipment can be determined only when the amount of power generation is determined, so as to ensure the value of the equipment and avoid loss. However, how to ensure the evaluation of thermal energy conversion is a technical problem difficult to solve at present. SUMMARY

[0003] To improve the technical problems in the related art, the present application provides a photovoltaic thermal energy conversion evaluation method and system.

[0004] In a first aspect, a photovoltaic thermal energy conversion evaluation method is provided, comprising: analyzing and processing the obtained photovoltaic thermal energy conversion efficiency description data set to determine a thermal energy conversion efficiency analysis result set containing photovoltaic thermal energy conversion efficiency characteristics; evaluating the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set to determine the photovoltaic thermal energy conversion efficiency characteristic factors of the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set; determining the first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic thermal energy conversion efficiency characteristic factors in a plurality of trained first photovoltaic thermal energy conversion efficiency characteristic evaluation networks, wherein each of the first photovoltaic thermal energy conversion efficiency characteristic evaluation networks corresponds to a set photovoltaic thermal energy conversion efficiency characteristic factor; evaluating the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set by using the first photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic thermal energy conversion efficiency evaluation result.

[0005] In the present application, the analysis and processing of the obtained photovoltaic thermal energy conversion efficiency description data set to determine a thermal energy conversion efficiency analysis result set containing photovoltaic thermal energy conversion efficiency characteristics comprises: loading the photovoltaic thermal energy conversion efficiency description data set to the trained photovoltaic thermal energy conversion efficiency feature recognition network to obtain a recognition result corresponding to the photovoltaic thermal energy conversion efficiency description data set, wherein the recognition result is used to represent whether the corresponding thermal energy conversion efficiency analysis result set corresponds to the photovoltaic thermal energy conversion efficiency feature; deriving the recognition result to determine a thermal energy conversion efficiency analysis result set corresponding to the photovoltaic thermal energy conversion efficiency feature of the part feature; In combination with the recognition result, at least one constraint boundary is surrounded in the photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set, and each constraint boundary contains one or several thermal energy conversion efficiency analysis result sets corresponding to the photovoltaic thermal energy conversion efficiency feature.

[0006] In the present application, before the factor evaluation of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set, the method further comprises: determining the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set; In response to the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set not being the first set direction, adjusting the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature other than the first set direction to the first set direction.

[0007] In the present application, before the factor evaluation of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set, the method further comprises: dividing the thermal energy conversion efficiency analysis result set into a plurality of photovoltaic thermal energy conversion efficiency feature factors.

[0008] In the present application, the dividing of the thermal energy conversion efficiency analysis result set into a plurality of photovoltaic thermal energy conversion efficiency feature factors comprises: determining a sample ratio according to the sample factor data amount for loading to the factor classification network; combining the sample ratio and the data amount of the thermal energy conversion efficiency analysis result set to determine a division data amount; combining the division data amount to divide the thermal energy conversion efficiency analysis result set to generate the plurality of photovoltaic thermal energy conversion efficiency feature factors.

[0009] In the present application, the combining of the division data amount to divide the thermal energy conversion efficiency analysis result set to generate the plurality of photovoltaic thermal energy conversion efficiency feature factors comprises: dividing the thermal energy conversion efficiency analysis result set based on the divided data volume to generate a plurality of divided electric energy conversion efficiency category sets with the same data volume; Determine whether each of the divided electric energy conversion efficiency type sets meets the sample ratio, determine several of the divided electric energy conversion efficiency type sets that meet the sample ratio as the photovoltaic thermal energy conversion efficiency characteristic factors, and debug the divided electric energy conversion efficiency type sets that do not meet the sample ratio and determine them as the photovoltaic thermal energy conversion efficiency characteristic factors.

[0010] In the present application, the photovoltaic-thermal-energy conversion efficiency characteristic factor evaluation of the photovoltaic-thermal-energy conversion efficiency characteristics within the thermal-energy conversion efficiency analysis result set is performed to determine the photovoltaic-thermal-energy conversion efficiency characteristic factor of the photovoltaic-thermal-energy conversion efficiency characteristics within the thermal-energy conversion efficiency analysis result set, including: Loading the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors into the trained factor classification network, performing factor classification on the photovoltaic-thermal energy conversion efficiency characteristics within the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors, and obtaining a plurality of pre-classification results corresponding to the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors; Performing depolarization processing on the plurality of pre-classification results to obtain depolarization processing values ​​of each set photovoltaic thermal energy conversion efficiency characteristic factor; In combination with the depolarization processing value, the photovoltaic-thermal energy conversion efficiency characteristic factor with the largest credibility coefficient is determined as the photovoltaic-thermal energy conversion efficiency characteristic factor of the photovoltaic-thermal energy conversion efficiency characteristic in the thermal energy conversion efficiency analysis result set.

[0011] In the present application, the first photovoltaic-thermal energy conversion efficiency characteristic evaluation network includes a model photovoltaic-thermal energy conversion efficiency characteristic evaluation network, and the model photovoltaic-thermal energy conversion efficiency characteristic evaluation network is generated according to the following model training steps: Obtaining a model training example set, the model training example set including a plurality of model training examples of multiple photovoltaic-thermal energy conversion efficiency characteristic factors, the model training examples including photovoltaic-thermal energy conversion efficiency characteristic region electric energy conversion efficiency type and corresponding photovoltaic-thermal energy conversion efficiency characteristic content label; Loading the model training example into the feature extraction unit of the model photovoltaic-thermal energy conversion efficiency feature evaluation network to obtain a first model electric energy conversion efficiency type feature distribution and a first model photovoltaic-thermal energy conversion efficiency feature feature distribution; loading the first model photovoltaic thermal energy conversion efficiency characteristic distribution into a core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to determine a core content attention index, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the core content attention index; loading the first model photovoltaic thermal energy conversion efficiency characteristic distribution into a core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to determine a core content attention index, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the core content attention index; determining a first distribution evaluation index in combination with the first model photovoltaic thermal energy conversion efficiency characteristic distribution and the second model photovoltaic thermal energy conversion efficiency characteristic distribution, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the first distribution evaluation index.

[0012] In the present application, the first photovoltaic thermal energy conversion efficiency characteristic evaluation network further comprises a setting factor photovoltaic thermal energy conversion efficiency characteristic evaluation network, which is generated based on the model photovoltaic thermal energy conversion efficiency characteristic evaluation network according to the following debugging training steps: obtaining a debugging training example set, the debugging training example set comprising a plurality of debugging training examples of setting photovoltaic thermal energy conversion efficiency characteristic factors, the debugging training examples comprising photovoltaic thermal energy conversion efficiency characteristic region electric energy conversion efficiency categories and corresponding photovoltaic thermal energy conversion efficiency characteristic content labels; loading the debugging training examples into a feature extraction unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a first debugging electric energy conversion efficiency category characteristic distribution and a first debugging photovoltaic thermal energy conversion efficiency characteristic distribution; loading the first debugging electric energy conversion efficiency category characteristic distribution into a core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second core content attention index, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the second core content attention index; loading the first debugging electric energy conversion efficiency category characteristic distribution into a core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second core content attention index, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the second core content attention index; The second distribution condition evaluation index is determined in combination with the first debugging photovoltaic thermal energy conversion efficiency characteristic distribution condition and the second debugging photovoltaic thermal energy conversion efficiency characteristic distribution condition, and the model photovoltaic thermal energy conversion efficiency characteristic evaluation network is iteratively debugged in combination with the second distribution condition evaluation index, so as to generate the set factor photovoltaic thermal energy conversion efficiency characteristic evaluation network.

[0013] In a second aspect, a photovoltaic thermal energy conversion evaluation system is provided, which comprises a processor and a memory in communication with each other. The processor is configured to read a computer program from the memory and execute the computer program to implement the method described above.

[0014] The photovoltaic thermal energy conversion evaluation method and system provided in the embodiments of the present application can intelligently select the first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic thermal energy conversion efficiency characteristic of the thermal energy conversion efficiency analysis result set in the photovoltaic thermal energy conversion efficiency description data set when evaluating the photovoltaic thermal energy conversion efficiency characteristic of the thermal energy conversion efficiency analysis result set in the photovoltaic thermal energy conversion efficiency description data set, so as to accurately evaluate the photovoltaic thermal energy conversion efficiency characteristic in the photovoltaic thermal energy conversion efficiency description data set. The photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiments of the present application can be applied to the evaluation of various factor photovoltaic thermal energy conversion efficiency characteristics, so that the photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiments of the present application can be used to evaluate the power conversion efficiency type set containing the model photovoltaic thermal energy conversion efficiency characteristic and the photovoltaic thermal energy conversion efficiency characteristic of multiple set factors, and the accuracy of the photovoltaic thermal energy conversion efficiency characteristic evaluation of the power conversion efficiency type can be taken into account. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0016] Figure 1 A flow chart of a photovoltaic thermal energy conversion evaluation method provided by the embodiments of the present application. DETAILED DESCRIPTION

[0017] In order to better understand the above technical solutions, the following will be described in detail by the drawings and specific embodiments of the technical solutions of the present application. 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, and are not limitations on the technical solutions of the present application. In the case of no conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0018] Please refer to Figure 1 , which shows a photovoltaic thermal energy conversion evaluation method, which can include the technical solutions described in the following steps S110-S140.

[0019] S110: analyzing and processing the obtained photovoltaic thermal energy conversion efficiency description data set to determine a thermal energy conversion efficiency analysis result set containing photovoltaic thermal energy conversion efficiency characteristics.

[0020] For example, the power conversion efficiency category can be obtained by checking with related monitoring equipment or manually.

[0021] Here, the photovoltaic thermal energy conversion efficiency description data set can be real-time power conversion efficiency category or historical power conversion efficiency category. In some embodiments, the photovoltaic thermal energy conversion efficiency evaluation on the obtained photovoltaic thermal energy conversion efficiency description data set can be the processing of the obtained photovoltaic thermal energy conversion efficiency description data set. It should be understood that the obtained photovoltaic thermal energy conversion efficiency description data set can be the initial power conversion efficiency category, or it can be obtained from the remaining initial power conversion efficiency category. Further, the obtained initial power conversion efficiency category can include: the initial power conversion efficiency category obtained from the existing stored power conversion efficiency category of the electronic device; or the initial power conversion efficiency category intercepted from the database.

[0022] Here, the analysis and processing of the obtained photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature should at least be understood as distinguishing the region where the photovoltaic thermal energy conversion efficiency feature is located from the region where the non-photovoltaic thermal energy conversion efficiency feature is located in the electric energy conversion efficiency category.

[0023] In an alternative embodiment, such as in the step S110, the analysis and processing of the obtained photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature can include: using a trained photovoltaic thermal energy conversion efficiency feature recognition network to analyze and process the obtained photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature.

[0024] In an alternative embodiment, the analysis and processing of the obtained photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature can further include: S111: loading the photovoltaic thermal energy conversion efficiency description data set to the trained photovoltaic thermal energy conversion efficiency feature recognition network to obtain the recognition result corresponding to the photovoltaic thermal energy conversion efficiency description data set; In the embodiment of the present application, the recognition result is used to represent whether the corresponding thermal energy conversion efficiency analysis result set corresponds to the photovoltaic thermal energy conversion efficiency feature.

[0025] S112: performing derivative processing on the recognition result to determine the thermal energy conversion efficiency analysis result set corresponding to the photovoltaic thermal energy conversion efficiency feature of the partial feature; In the embodiment of the present application, the derivative processing is one of the morphological electric energy conversion efficiency category processing operations, which aims to strengthen the target region in the electric energy conversion efficiency category and make it communicate with the surrounding regions. For example, in the above step S112, the derivative processing is performed on the recognition result to communicate the photovoltaic thermal energy conversion efficiency feature region in the response division to form the thermal energy conversion efficiency analysis result set. After the above derivative processing, the abnormal information between the photovoltaic thermal energy conversion efficiency feature regions can be effectively eliminated, so that the text region becomes a complete whole, which can improve the overall division effect and improve the evaluation effect of the subsequent step.

[0026] S113: according to the recognition result, at least one constraint boundary is surrounded in the photovoltaic thermal energy conversion efficiency description data set to determine the thermal energy conversion efficiency analysis result set, and each constraint boundary contains one or several corresponding thermal energy conversion efficiency analysis result sets with photovoltaic thermal energy conversion efficiency features.

[0027] In a specific embodiment of the present application, after the photovoltaic thermal energy conversion efficiency description data set is loaded into the trained photovoltaic thermal energy conversion efficiency feature recognition network, the trained photovoltaic thermal energy conversion efficiency feature recognition network will make a prediction: first, as described in step S111 above, the recognition result corresponding to the photovoltaic thermal energy conversion efficiency description data set will be output; then, as described in step S112 above, the recognition result will be derived and some nearby areas will be connected to determine the thermal energy conversion efficiency analysis result set corresponding to part of the features of the photovoltaic thermal energy conversion efficiency feature; optionally, the deinterference operation can also be performed to remove some noise; finally, as described in step S113 above, the maximum enclosing region algorithm can be used to enclose at least one constraint boundary in the photovoltaic thermal energy conversion efficiency description data set according to the recognition result to determine the thermal energy conversion efficiency analysis result set, and each constraint boundary contains one or several thermal energy conversion efficiency analysis results corresponding to the photovoltaic thermal energy conversion efficiency feature, thereby determining the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature in the photovoltaic thermal energy conversion efficiency description data set.

[0028] S120: Factor evaluation is performed on the photovoltaic thermal energy conversion efficiency features in the thermal energy conversion efficiency analysis result set to determine the photovoltaic thermal energy conversion efficiency feature factors of the photovoltaic thermal energy conversion efficiency features in the thermal energy conversion efficiency analysis result set.

[0029] It should be understood that the photovoltaic thermal energy conversion efficiency feature factor refers to the writing factor of the photovoltaic thermal energy conversion efficiency feature, which is a different concept from the electric energy conversion efficiency category scenario.

[0030] In some embodiments, before the factor evaluation is performed on the photovoltaic thermal energy conversion efficiency features in the thermal energy conversion efficiency analysis result set, the method further comprises: S360: The thermal energy conversion efficiency analysis result set is divided into a plurality of photovoltaic thermal energy conversion efficiency feature factors; Based on this, the present application can improve the robustness of the network to thermal energy conversion efficiency analysis result sets of different data amounts by dividing the collected thermal energy conversion efficiency analysis result set into a plurality of photovoltaic thermal energy conversion efficiency feature factors and then evaluating the photovoltaic thermal energy conversion efficiency features in the divided electric energy conversion efficiency category, thereby improving the accuracy of factor type evaluation.

[0031] In an independently implemented embodiment, the above step S360 can further comprise the following steps: S161: Determine the sample ratio according to the sample factor data amount loaded into the factor classification network.

[0032] In an independently implemented embodiment, such as in step S161 described above, the sample factor data amount for loading into the factor classification network can be determined first, and then a sample ratio is determined based on the sample data amount, which will be used in subsequent steps, such as in subsequent step S162.

[0033] It should be understood that the sample factor data amount of the factor classification network in the embodiments of the present application can be other numerical values, and the sample ratio determined therefrom can also be other numerical values, which are not limited herein.

[0034] S162: Determine the division data amount according to the sample ratio and the data amount of the set of thermal energy conversion efficiency analysis results.

[0035] In an independently implemented embodiment, such as in step S162 described above, after obtaining the sample ratio, the actual division data amount can be determined based on the sample ratio and the data amount of the set of thermal energy conversion efficiency analysis results to be evaluated, such as obtaining the division pixel data amount.

[0036] S163: Divide the set of thermal energy conversion efficiency analysis results according to the division data amount to generate a plurality of photovoltaic thermal energy conversion efficiency characteristic factors.

[0037] In an independently implemented embodiment, step S163 described above can include the following steps: S1631: Divide the set of thermal energy conversion efficiency analysis results according to the division data amount to generate a plurality of sets of divided power conversion efficiency categories with the same data amount.

[0038] In the embodiments of the present application, after dividing the set of thermal energy conversion efficiency analysis results according to the division data amount, a plurality of sets of divided power conversion efficiency categories with the same data amount can be obtained. It should be understood that during the division process, the total photovoltaic thermal energy conversion efficiency characteristic content in the set of thermal energy conversion efficiency analysis results will not be reduced or increased, and the plurality of sets of divided power conversion efficiency categories with the same data amount can still restore the set of power conversion efficiency category information of the set of thermal energy conversion efficiency analysis results after integration.

[0039] S1632: Determine whether each of the sets of divided power conversion efficiency categories meets the sample ratio, and determine a plurality of sets of divided power conversion efficiency categories that meet the sample ratio as the photovoltaic thermal energy conversion efficiency characteristic factors, and debug the sets of divided power conversion efficiency categories that do not meet the sample ratio and determine them as the photovoltaic thermal energy conversion efficiency characteristic factors.

[0040] In the embodiment of the present application, for example, in the step S1632, it is determined whether each of the divided power conversion efficiency category sets obtained by the above steps, for example, each of the divided power conversion efficiency category sets obtained by the step S1631, satisfies the sample proportion, and several divided power conversion efficiency category sets satisfying the sample proportion are determined as the photovoltaic thermal energy conversion efficiency characteristic factors, and for the divided power conversion efficiency category sets not satisfying the sample proportion, the divided power conversion efficiency category sets are debugged under the condition that the height is unchanged, so as to satisfy the sample proportion, for example, the divided power conversion efficiency category sets not satisfying the sample proportion can be debugged by using a blank area not containing the photovoltaic thermal energy conversion efficiency characteristic content, and the divided power conversion efficiency category sets after debugging are also determined as the photovoltaic thermal energy conversion efficiency characteristic factors.

[0041] Step S170: loading the several photovoltaic thermal energy conversion efficiency characteristic factors into the trained factor classification network to determine the photovoltaic thermal energy conversion efficiency characteristic factors of the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set.

[0042] In an independently implemented embodiment, the step S170 can include the following steps: S171: loading the several photovoltaic thermal energy conversion efficiency characteristic factors into the trained factor classification network, respectively classifying the photovoltaic thermal energy conversion efficiency characteristics in the several photovoltaic thermal energy conversion efficiency characteristic factors by factors to obtain several pre-classification results corresponding to the several photovoltaic thermal energy conversion efficiency characteristic factors respectively.

[0043] In an independently implemented embodiment, as in the step S171, the obtained several photovoltaic thermal energy conversion efficiency characteristic factors, for example, the several photovoltaic thermal energy conversion efficiency characteristic factors obtained by the steps S163 and S1631-S1633 are determined as a batch to be loaded into the trained factor classification network, and then the photovoltaic thermal energy conversion efficiency characteristics in each of the photovoltaic thermal energy conversion efficiency characteristic factors contained in the batch are classified by factors to obtain several pre-classification results corresponding to the several photovoltaic thermal energy conversion efficiency characteristic factors.

[0044] S172: processing each pre-classification result by Depolarization to obtain a Depolarization processing value of each set photovoltaic thermal energy conversion efficiency characteristic factor.

[0045] S173: determining, according to the Depolarization processing value, the set photovoltaic thermal energy conversion efficiency characteristic factor corresponding to the maximum confidence coefficient as the photovoltaic thermal energy conversion efficiency characteristic factor of the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set.

[0046] In an independently implemented embodiment, the loading of the plurality of photovoltaic thermal energy conversion efficiency feature factors into the trained factor classification network, the factor classification of the photovoltaic thermal energy conversion efficiency features in each photovoltaic thermal energy conversion efficiency feature factor, and the obtaining of the pre-classification result can specifically include: loading the plurality of photovoltaic thermal energy conversion efficiency feature factors into a fully connected unit to obtain a first feature distribution.

[0047] In the embodiment of the present application, the plurality of photovoltaic thermal energy conversion efficiency feature factors are loaded into a fully connected unit to obtain a first feature distribution, wherein the first feature distribution can be a series of feature vectors extracted from different levels of networks of the fully connected unit, and each feature vector captures information of different abstract levels of the electric energy conversion efficiency category. For example, the plurality of photovoltaic thermal energy conversion efficiency feature factors can be loaded into a fully connected unit to obtain a first feature vector sequence.

[0048] Step S130: determining a first photovoltaic thermal energy conversion efficiency feature evaluation network corresponding to the photovoltaic thermal energy conversion efficiency feature factor in the plurality of trained first photovoltaic thermal energy conversion efficiency feature evaluation networks, wherein each first photovoltaic thermal energy conversion efficiency feature evaluation network corresponds to a set photovoltaic thermal energy conversion efficiency feature factor.

[0049] In the embodiment of the present application, the set first photovoltaic thermal energy conversion efficiency feature evaluation network can include a model photovoltaic thermal energy conversion efficiency feature evaluation network trained for a model photovoltaic thermal energy conversion efficiency feature factor photovoltaic thermal energy conversion efficiency feature evaluation scene and a set photovoltaic thermal energy conversion efficiency feature factor photovoltaic thermal energy conversion efficiency feature evaluation network specially trained for a set photovoltaic thermal energy conversion efficiency feature factor photovoltaic thermal energy conversion efficiency feature evaluation scene, wherein the number of the set photovoltaic thermal energy conversion efficiency feature factor photovoltaic thermal energy conversion efficiency feature evaluation networks can be one or a plurality, which is not limited herein. After detecting the photovoltaic thermal energy conversion efficiency feature factor in the set of thermal energy conversion efficiency analysis results, the set first photovoltaic thermal energy conversion efficiency feature evaluation network suitable for evaluating the photovoltaic thermal energy conversion efficiency feature of the photovoltaic thermal energy conversion efficiency feature factor is called to determine the first photovoltaic thermal energy conversion efficiency feature evaluation network.

[0050] In an alternative embodiment, the set first photovoltaic thermal energy conversion efficiency feature evaluation network can include a model photovoltaic thermal energy conversion efficiency feature evaluation network, which can be obtained through iterative training according to the following model training steps: S1310: Obtain a model training example set, the model training example set comprising a plurality of photovoltaic thermal energy conversion efficiency characteristic factors, the model training example comprising a photovoltaic thermal energy conversion efficiency characteristic region electric energy conversion efficiency category and a corresponding photovoltaic thermal energy conversion efficiency characteristic content label.

[0051] S1320: Load the model training example to the feature extraction unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a first model electric energy conversion efficiency category feature distribution and a first model photovoltaic thermal energy conversion efficiency characteristic feature distribution.

[0052] In the embodiment of the present application, the model training example can be loaded to the feature extraction unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to extract the electric energy conversion efficiency category feature and the photovoltaic thermal energy conversion efficiency characteristic feature of the model training example to obtain the first model electric energy conversion efficiency category feature distribution and the corresponding first model photovoltaic thermal energy conversion efficiency characteristic feature distribution.

[0053] S1330: Load the first model electric energy conversion efficiency category feature distribution to the core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to determine a first core content attention index, and iteratively debug the model photovoltaic thermal energy conversion efficiency characteristic evaluation network according to the first core content attention index.

[0054] In the embodiment of the present application, the first model electric energy conversion efficiency category feature distribution can be loaded to the core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network, and the first core content attention index can be determined by a loss function. For example, the electric energy conversion efficiency category feature distribution of any factor can be loaded to the full connection unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network, wherein the network of different levels of the full connection unit extracts a series of feature vector sequences of the photovoltaic thermal energy conversion efficiency characteristic factor training data, and each feature vector captures information of different abstract levels of the photovoltaic thermal energy conversion efficiency characteristic factor data.

[0055] S1340: Load the first model electric energy conversion efficiency category feature distribution to the self-core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second model electric energy conversion efficiency category feature distribution, and load the second electric energy conversion efficiency category feature distribution to the decision unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second model photovoltaic thermal energy conversion efficiency characteristic feature distribution.

[0056] S1350: Determine a first distribution condition evaluation index according to the first model photovoltaic thermal energy conversion efficiency feature distribution condition and the second model photovoltaic thermal energy conversion efficiency feature distribution condition, and iteratively debug the model photovoltaic thermal energy conversion efficiency feature evaluation network according to the first distribution condition evaluation index.

[0057] In an independently implemented embodiment, the first photovoltaic thermal energy conversion efficiency feature evaluation network can include a set factor photovoltaic thermal energy conversion efficiency feature evaluation network, which is designed to evaluate photovoltaic thermal energy conversion efficiency features of a set factor.

[0058] In an independently implemented embodiment, the set factor photovoltaic thermal energy conversion efficiency feature evaluation network is generated based on the model photovoltaic thermal energy conversion efficiency feature evaluation network according to the following debugging training steps: S1510: Obtain a debugging training example set, which includes a plurality of debugging training examples of a set photovoltaic thermal energy conversion efficiency feature factor, and the debugging training examples include photovoltaic thermal energy conversion efficiency feature regional electric energy conversion efficiency categories and corresponding photovoltaic thermal energy conversion efficiency feature content labels.

[0059] In the embodiment of the present application, for example, in the above step S1510, unlike the aforementioned model training, all the training examples in the debugging training example set used when debugging training is performed are of the same set photovoltaic thermal energy conversion efficiency feature factor.

[0060] S1520: Load the debugging training examples to the feature extraction unit of the model photovoltaic thermal energy conversion efficiency feature evaluation network, and obtain a first debugging electric energy conversion efficiency category feature distribution condition and a first debugging photovoltaic thermal energy conversion efficiency feature feature distribution condition.

[0061] S1530: Load the first debugging electric energy conversion efficiency category feature distribution condition to the core content attention unit of the model photovoltaic thermal energy conversion efficiency feature evaluation network to obtain a second core content attention index, and iteratively debug the model photovoltaic thermal energy conversion efficiency feature evaluation network according to the second core content attention index.

[0062] S1540: Load the first debugging electric energy conversion efficiency category feature distribution condition to the self core content attention unit of the model photovoltaic thermal energy conversion efficiency feature evaluation network to obtain a second debugging electric energy conversion efficiency category feature distribution condition, and load the second debugging electric energy conversion efficiency category feature distribution condition to the decision unit of the model photovoltaic thermal energy conversion efficiency feature evaluation network to obtain a second debugging photovoltaic thermal energy conversion efficiency feature feature distribution condition.

[0063] S1550: Obtain a second distribution condition evaluation index according to the first debugging photovoltaic thermal energy conversion efficiency characteristic feature distribution condition and the second debugging photovoltaic thermal energy conversion efficiency characteristic feature distribution condition, and iteratively debug the model photovoltaic thermal energy conversion efficiency characteristic evaluation network according to the second distribution condition evaluation index to generate a set factor photovoltaic thermal energy conversion efficiency characteristic evaluation network.

[0064] The detailed description of the above steps S1520-S1540 can refer to the foregoing steps S1320-S1350, with the difference being that the training examples used all belong to the same set photovoltaic thermal energy conversion efficiency characteristic factor training examples, i.e., belong to the same set photovoltaic thermal energy conversion efficiency characteristic factor photovoltaic thermal energy conversion efficiency characteristic region electrical energy conversion efficiency category and corresponding photovoltaic thermal energy conversion efficiency characteristic content label.

[0065] Step S140: Evaluate the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set using the first photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic thermal energy conversion efficiency evaluation result.

[0066] In an independently implemented embodiment, the evaluation of the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set using the first photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic thermal energy conversion efficiency evaluation result specifically includes: Step S141: Load the thermal energy conversion efficiency analysis result set to a fully connected unit to obtain an electrical energy conversion efficiency category characteristic distribution condition corresponding to the thermal energy conversion efficiency analysis result set; In the embodiment of the present application, the thermal energy conversion efficiency analysis result set is loaded to the fully connected unit to obtain the electrical energy conversion efficiency category characteristic distribution condition corresponding to the thermal energy conversion efficiency analysis result set, wherein the electrical energy conversion efficiency category characteristic distribution condition corresponding to the thermal energy conversion efficiency analysis result set can be a series of feature vector sequences extracted from different levels of networks of the fully connected unit, and each feature vector captures information at different levels of abstraction of the thermal energy conversion efficiency analysis result set. For example, in the above step S141, a plurality of thermal energy conversion efficiency analysis result sets can be loaded to the fully connected unit to obtain the electrical energy conversion efficiency category characteristic vector sequence corresponding to the thermal energy conversion efficiency analysis result set.

[0067] Step S142: Load the electrical energy conversion efficiency category characteristic distribution condition to a self-core content attention unit to obtain a first derived feature distribution condition; Step S143: Load the first derived feature distribution condition to a decision unit to obtain a second derived feature distribution condition; Step S144: Compress the second derived feature distribution condition by a compression unit to determine the evaluated photovoltaic thermal energy conversion efficiency characteristic.

[0068] In the embodiments of the present application, the compression unit converts the high-dimensional feature representation into understandable output. For example, in the step S144 described above, the compression unit can convert the second derived feature distribution back into the corresponding photovoltaic thermal energy conversion efficiency feature information to determine the evaluated photovoltaic thermal energy conversion efficiency feature.

[0069] In some embodiments of the present application, the step S360 described above can be further preceded by: Step a210: determining the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature in the set of thermal energy conversion efficiency analysis results In the embodiments of the present application, the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature in the set of thermal energy conversion efficiency analysis results is mainly divided into a positive direction and an inverted direction.

[0070] Step a220: in response to the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature in the set of thermal energy conversion efficiency analysis results not being the first set direction, adjusting the photovoltaic thermal energy conversion efficiency feature direction of the photovoltaic thermal energy conversion efficiency feature other than the first set direction to the first set direction.

[0071] In the embodiments of the present application, the first set direction can be the positive direction of the photovoltaic thermal energy conversion efficiency feature in the set of thermal energy conversion efficiency analysis results, and the second set direction can be the inverted / inverted direction of the photovoltaic thermal energy conversion efficiency feature in the set of thermal energy conversion efficiency analysis results. The first set direction and the second set direction are only determined as an example, and are not determined as a limitation of the present application. Those skilled in the art can freely set the first set direction and the second set direction according to their needs.

[0072] In some embodiments, the determination of the photovoltaic thermal energy conversion efficiency feature direction in the set of thermal energy conversion efficiency analysis results specifically includes: Step S151: extracting a text line area in the set of thermal energy conversion efficiency analysis results.

[0073] Step S152: performing direction detection on the text line area to obtain a corresponding text line direction, and determining the text line direction as the photovoltaic thermal energy conversion efficiency feature direction.

[0074] In some embodiments of the present application, the step S140 described above can be further preceded by: Step S120: determining the disaster level direction of the set of thermal energy conversion efficiency analysis results.

[0075] Step S130: in response to the disaster level direction of the set of thermal energy conversion efficiency analysis results not being the second set direction, adjusting the disaster level direction of the set of thermal energy conversion efficiency analysis results other than the second set direction to the second set direction.

[0076] In some embodiments, the offline training process can include the training of four network tasks: a model photovoltaic thermal energy conversion efficiency feature detection network training, responsible for detecting the thermal energy conversion efficiency analysis results appearing in the factor; a photovoltaic thermal energy conversion efficiency feature direction classification network training, responsible for judging the direction of the thermal energy conversion efficiency analysis results set; a photovoltaic thermal energy conversion efficiency feature factor classification network training, responsible for evaluating the font factor of the thermal energy conversion efficiency analysis results set; and a pre-training of a model photovoltaic thermal energy conversion efficiency feature evaluation network and a debugging training of a set factor photovoltaic thermal energy conversion efficiency feature evaluation network, both of which are responsible for evaluating the photovoltaic thermal energy conversion efficiency feature content of the thermal energy conversion efficiency analysis results set.

[0077] In the embodiment of the present application, by analyzing and processing the obtained photovoltaic thermal energy conversion efficiency description data set, the thermal energy conversion efficiency analysis result set containing the photovoltaic thermal energy conversion efficiency feature is determined; the photovoltaic thermal energy conversion efficiency feature factor of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set is determined by factor evaluation; then the first photovoltaic thermal energy conversion efficiency feature evaluation network corresponding to the photovoltaic thermal energy conversion efficiency feature factor of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set is called according to the photovoltaic thermal energy conversion efficiency feature factor of the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set; and finally the first photovoltaic thermal energy conversion efficiency feature evaluation network is used to evaluate the photovoltaic thermal energy conversion efficiency feature in the thermal energy conversion efficiency analysis result set, so as to obtain the photovoltaic thermal energy conversion efficiency evaluation result; so that the electronic device can intelligently select the first photovoltaic thermal energy conversion efficiency feature evaluation network for the photovoltaic thermal energy conversion efficiency feature of the thermal energy conversion efficiency analysis result set in the photovoltaic thermal energy conversion efficiency description data set when evaluating the photovoltaic thermal energy conversion efficiency feature of the photovoltaic thermal energy conversion efficiency description data set, and accurately evaluate the photovoltaic thermal energy conversion efficiency feature in the photovoltaic thermal energy conversion efficiency description data set. Based on this, the photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiment of the present application can be applied to the evaluation of various factor photovoltaic thermal energy conversion efficiency features, so that the evaluation network corresponding to the photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiment of the present application can be used for the evaluation of various photovoltaic thermal energy conversion efficiency features, ensuring the reliability of the network. Therefore, the embodiment of the present application can take into account the accuracy of the photovoltaic thermal energy conversion efficiency feature evaluation of the electric energy conversion efficiency.

[0078] It needs to be understood that the photovoltaic thermal energy conversion efficiency characteristic factors corresponding to different sets of thermal energy conversion efficiency analysis results can be the same or different. In the same set of photovoltaic thermal energy conversion efficiency description data, there can be several sets of thermal energy conversion efficiency analysis results corresponding to several photovoltaic thermal energy conversion efficiency characteristic factors, so that the photovoltaic thermal energy conversion efficiency characteristic evaluation in the corresponding set of thermal energy conversion efficiency analysis results can be performed by calling the photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic thermal energy conversion efficiency characteristic factor, thereby improving the accuracy of the photovoltaic thermal energy conversion efficiency characteristic evaluation. At the same time, since it can be suitable for various photovoltaic thermal energy conversion efficiency characteristic factors, the reliability of the photovoltaic thermal energy conversion efficiency characteristic evaluation can be improved.

[0079] On the basis of the above, a photovoltaic thermal energy conversion evaluation device is provided, which comprises: a region determination module for analyzing and processing the obtained set of photovoltaic thermal energy conversion efficiency description data to determine a set of thermal energy conversion efficiency analysis results containing photovoltaic thermal energy conversion efficiency characteristics; a factor determination module for evaluating the photovoltaic thermal energy conversion efficiency characteristic factor of the photovoltaic thermal energy conversion efficiency characteristic in the set of thermal energy conversion efficiency analysis results to determine the photovoltaic thermal energy conversion efficiency characteristic factor of the photovoltaic thermal energy conversion efficiency characteristic in the set of thermal energy conversion efficiency analysis results; a network determination module for determining the first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic thermal energy conversion efficiency characteristic factor in a plurality of trained set first photovoltaic thermal energy conversion efficiency characteristic evaluation networks, wherein each set of the set first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponds to a set photovoltaic thermal energy conversion efficiency characteristic factor; a result evaluation module for evaluating the photovoltaic thermal energy conversion efficiency characteristic in the set of thermal energy conversion efficiency analysis results by using the first photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic thermal energy conversion efficiency evaluation result.

[0080] On the basis of the above, a photovoltaic thermal energy conversion evaluation system is shown, which comprises a processor and a memory in communication with each other. The processor is used to read a computer program from the memory and execute it to realize the above-mentioned method.

[0081] On the basis of the above, a computer readable storage medium is also provided, on which a computer program is stored, which realizes the above-mentioned method when running.

[0082] In summary, based on the above scheme, by analyzing and processing the obtained photovoltaic thermal energy conversion efficiency description data set, a thermal energy conversion efficiency analysis result set containing photovoltaic thermal energy conversion efficiency characteristics is determined; the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set are evaluated for photovoltaic thermal energy conversion efficiency characteristic factors to determine the photovoltaic thermal energy conversion efficiency characteristic factors of the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set; the photovoltaic thermal energy conversion efficiency characteristic factors are determined in a plurality of trained first photovoltaic thermal energy conversion efficiency characteristic evaluation networks, wherein each first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponds to a set photovoltaic thermal energy conversion efficiency characteristic factor; finally, the photovoltaic thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set are evaluated using the first photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic thermal energy conversion efficiency evaluation result. The photovoltaic thermal energy conversion efficiency evaluation method disclosed in the embodiment of the present application enables intelligent selection of the first photovoltaic thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic thermal energy conversion efficiency characteristics of the thermal energy conversion efficiency analysis result set in the photovoltaic thermal energy conversion efficiency description data set when evaluating the photovoltaic thermal energy conversion efficiency characteristics of the thermal energy conversion efficiency analysis result set in the photovoltaic thermal energy conversion efficiency description data set, so as to accurately evaluate the photovoltaic thermal energy conversion efficiency characteristics in the photovoltaic thermal energy conversion efficiency description data set. The photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiment of the present application can be applied to the evaluation of various factor photovoltaic thermal energy conversion efficiency characteristics, so that the photovoltaic thermal energy conversion efficiency evaluation method provided in the embodiment of the present application can be used to evaluate a power conversion efficiency category set containing both model photovoltaic thermal energy conversion efficiency characteristics and various set factors, and the accuracy of the photovoltaic thermal energy conversion efficiency characteristic evaluation of the power conversion efficiency category can be taken into account.

[0083] It should be appreciated that the systems and modules thereof described above can be implemented in a number of ways. For example, in some embodiments, the systems and modules thereof can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using specialized logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the methods and systems described above can be implemented using computer-executable instructions and / or in processor control code, for example, provided on a carrier medium such as a disk, CD or DVD-ROM, programmable memory such as read-only memory (firmware), or data carrier such as an optical or electrical signal carrier. The systems and modules thereof of the present application can be implemented not only in hardware circuitry such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also in software, for example, executed by various types of processors, and in a combination of the above (e.g., firmware).

[0084] It should be noted that different embodiments can produce different beneficial effects, and in different embodiments, the beneficial effects that can be produced can be any one or a combination of the above, or any other beneficial effects that can be obtained.

Claims

1. A photovoltaic thermal energy conversion evaluation method, characterized in that: The method comprises: Analyzing and processing the acquired photovoltaic-thermal energy conversion efficiency description data set to determine a thermal energy conversion efficiency analysis result set containing photovoltaic-thermal energy conversion efficiency characteristics; performing a photovoltaic-thermal-energy conversion efficiency characteristic factor evaluation on the photovoltaic-thermal-energy conversion efficiency characteristics within the thermal-energy conversion efficiency analysis result set, and determining the photovoltaic-thermal-energy conversion efficiency characteristic factor of the photovoltaic-thermal-energy conversion efficiency characteristics within the thermal-energy conversion efficiency analysis result set; Determining a first photovoltaic-thermal energy conversion efficiency characteristic evaluation network corresponding to the photovoltaic-thermal energy conversion efficiency characteristic factor from a plurality of trained set first photovoltaic-thermal energy conversion efficiency characteristic evaluation networks, wherein each set first photovoltaic-thermal energy conversion efficiency characteristic evaluation network corresponds to a set photovoltaic-thermal energy conversion efficiency characteristic factor; The photovoltaic-thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set are evaluated using the first photovoltaic-thermal energy conversion efficiency characteristic evaluation network to obtain a photovoltaic-thermal energy conversion efficiency evaluation result.

2. The method according to claim 1, characterized in that The analyzing and processing of the acquired photovoltaic-thermal energy conversion efficiency description data set to determine a thermal energy conversion efficiency analysis result set containing photovoltaic-thermal energy conversion efficiency characteristics includes: Loading the photovoltaic-thermal energy conversion efficiency description data set into the trained photovoltaic-thermal energy conversion efficiency feature recognition network to obtain a recognition result corresponding to the photovoltaic-thermal energy conversion efficiency description data set, wherein the recognition result is used to indicate whether the corresponding thermal energy conversion efficiency analysis result set corresponds to a photovoltaic-thermal energy conversion efficiency feature; Performing derivative processing on the identification results to determine a set of thermal energy conversion efficiency analysis results corresponding to photovoltaic thermal energy conversion efficiency characteristics of some features; In combination with the identification results, at least one constraint boundary is enclosed in the photovoltaic-thermal energy conversion efficiency description data set and determined as a thermal energy conversion efficiency analysis result set, and each of the constraint boundaries contains one or several nearby thermal energy conversion efficiency analysis result sets corresponding to photovoltaic-thermal energy conversion efficiency characteristics.

3. The method according to claim 1, characterized in that Before performing factor evaluation on the photovoltaic-thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set, the method further includes: Determining a photovoltaic-thermal energy conversion efficiency characteristic direction of the photovoltaic-thermal energy conversion efficiency characteristic within the thermal energy conversion efficiency analysis result set; In response to the photovoltaic-thermal-energy conversion efficiency characteristic direction of the photovoltaic-thermal-energy conversion efficiency characteristic in the thermal-energy conversion efficiency analysis result set not being the first set direction, the photovoltaic-thermal-energy conversion efficiency characteristic direction of the photovoltaic-thermal-energy conversion efficiency characteristic not being the first set direction is adjusted to the first set direction.

4. The method according to claim 1, wherein Before performing factor evaluation on the photovoltaic-thermal energy conversion efficiency characteristics in the thermal energy conversion efficiency analysis result set, the method further includes: The thermal energy conversion efficiency analysis result set is divided into a number of photovoltaic thermal energy conversion efficiency characteristic factors.

5. The method according to claim 4, characterized in that The thermal energy conversion efficiency analysis result set is divided into a number of photovoltaic thermal energy conversion efficiency characteristic factors, including: Determine the sample proportion based on the amount of sample factor data used to load into the factor classification network; Determining the amount of divided data based on the sample ratio and the amount of data in the heat energy conversion efficiency analysis result set; The thermal energy conversion efficiency analysis result set is divided in combination with the divided data amount to generate the plurality of photovoltaic thermal energy conversion efficiency characteristic factors.

6. The method according to claim 5, characterized in that The step of dividing the thermal energy conversion efficiency analysis result set in combination with the divided data amount to generate the plurality of photovoltaic thermal energy conversion efficiency characteristic factors includes: dividing the thermal energy conversion efficiency analysis result set based on the divided data volume to generate a plurality of divided electric energy conversion efficiency category sets with the same data volume; Determine whether each of the divided electric energy conversion efficiency type sets meets the sample ratio, determine several of the divided electric energy conversion efficiency type sets that meet the sample ratio as the photovoltaic thermal energy conversion efficiency characteristic factors, and debug the divided electric energy conversion efficiency type sets that do not meet the sample ratio and determine them as the photovoltaic thermal energy conversion efficiency characteristic factors.

7. The method according to claim 6, characterized in that The performing photovoltaic-thermal-energy conversion efficiency characteristic factor evaluation on the photovoltaic-thermal-energy conversion efficiency characteristics in the thermal-energy conversion efficiency analysis result set to determine the photovoltaic-thermal-energy conversion efficiency characteristic factor of the photovoltaic-thermal-energy conversion efficiency characteristics in the thermal-energy conversion efficiency analysis result set includes: Loading the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors into a trained factor classification network, performing factor classification on the photovoltaic-thermal energy conversion efficiency characteristics within the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors, and obtaining a plurality of pre-classification results corresponding to the plurality of photovoltaic-thermal energy conversion efficiency characteristic factors; Performing depolarization processing on the plurality of pre-classification results to obtain depolarization processing values ​​of each set photovoltaic thermal energy conversion efficiency characteristic factor; In combination with the depolarization processing value, the photovoltaic-thermal energy conversion efficiency characteristic factor with the largest credibility coefficient is determined as the photovoltaic-thermal energy conversion efficiency characteristic factor of the photovoltaic-thermal energy conversion efficiency characteristic in the thermal energy conversion efficiency analysis result set.

8. The method according to claim 1, characterized in that The first photovoltaic-thermal energy conversion efficiency characteristic evaluation network includes a model photovoltaic-thermal energy conversion efficiency characteristic evaluation network, and the model photovoltaic-thermal energy conversion efficiency characteristic evaluation network is generated according to the following model training steps: Obtaining a model training example set, the model training example set including a plurality of model training examples of multiple photovoltaic-thermal energy conversion efficiency characteristic factors, the model training examples including photovoltaic-thermal energy conversion efficiency characteristic region electric energy conversion efficiency type and corresponding photovoltaic-thermal energy conversion efficiency characteristic content label; Loading the model training example into the feature extraction unit of the model photovoltaic-thermal energy conversion efficiency feature evaluation network to obtain a first model electric energy conversion efficiency type feature distribution and a first model photovoltaic-thermal energy conversion efficiency feature feature distribution; Loading the first exemplary electric energy conversion efficiency type characteristic distribution into the core content attention unit of the exemplary photovoltaic thermal energy conversion efficiency characteristic evaluation network to determine the core content attention index, and iteratively debugging the exemplary photovoltaic thermal energy conversion efficiency characteristic evaluation network based on the core content attention index; Loading the first exemplary electric energy conversion efficiency type characteristic distribution into the self-core content attention unit of the exemplary photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second exemplary electric energy conversion efficiency type characteristic distribution; loading the second electric energy conversion efficiency type characteristic distribution into the decision unit of the exemplary photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second exemplary photovoltaic thermal energy conversion efficiency characteristic distribution; A first distribution evaluation index is determined based on the first model photovoltaic-thermal energy conversion efficiency characteristic distribution and the second model photovoltaic-thermal energy conversion efficiency characteristic distribution, and the model photovoltaic-thermal energy conversion efficiency characteristic evaluation network is iteratively debugged based on the first distribution evaluation index.

9. The method according to claim 8, characterized in that The first photovoltaic-thermal energy conversion efficiency characteristic evaluation network further includes a set factor photovoltaic-thermal energy conversion efficiency characteristic evaluation network, which is generated based on the model photovoltaic-thermal energy conversion efficiency characteristic evaluation network according to the following debugging and training steps: Obtaining a debugging training example set, the debugging training example set including a plurality of debugging training examples for setting photovoltaic-thermal energy conversion efficiency characteristic factors, the debugging training examples including photovoltaic-thermal energy conversion efficiency characteristic region electric energy conversion efficiency types and corresponding photovoltaic-thermal energy conversion efficiency characteristic content labels; Loading the debugging training example into the feature extraction unit of the model photovoltaic-thermal energy conversion efficiency feature evaluation network to obtain the first debugging electric energy conversion efficiency type feature distribution and the first debugging photovoltaic-thermal energy conversion efficiency feature feature distribution; Loading the first debugged electric energy conversion efficiency type characteristic distribution into the core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain a second core content attention indicator, and iteratively debugging the model photovoltaic thermal energy conversion efficiency characteristic evaluation network in combination with the second core content attention indicator; The first debugging electric energy conversion efficiency type characteristic distribution is loaded into the self-core content attention unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain the second debugging electric energy conversion efficiency type characteristic distribution; the second debugging electric energy conversion efficiency type characteristic distribution is loaded into the decision unit of the model photovoltaic thermal energy conversion efficiency characteristic evaluation network to obtain the second debugging photovoltaic thermal energy conversion efficiency characteristic distribution; A second distribution evaluation index is determined in combination with the first debugging photovoltaic-thermal energy conversion efficiency characteristic distribution and the second debugging photovoltaic-thermal energy conversion efficiency characteristic distribution. The model photovoltaic-thermal energy conversion efficiency characteristic evaluation network is iteratively debugged in combination with the second distribution evaluation index to generate the set factor photovoltaic-thermal energy conversion efficiency characteristic evaluation network.

10. A photovoltaic thermal energy conversion evaluation system, characterized in that: The invention comprises a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute the computer program to implement the method according to any one of claims 1 to 9.

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