Photovoltaic installation data processing method and system, electronic equipment and storage medium

Abstract

The invention discloses a photovoltaic installation data processing method and system, electronic equipment and a storage medium. The photovoltaic installation data processing method comprises the following steps: acquiring photovoltaic installation data; performing feature extraction on the photovoltaic installation data by using a pre-trained form filling model to obtain field data; and filling the field data into the target form to obtain a photovoltaic installation form. The technical problem that the filling efficiency and accuracy of the photovoltaic installation form are low is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a photovoltaic installation data processing method, system, electronic device and storage medium. Background Art

[0002] As global attention to environmental sustainability increases, photovoltaic power generation, as a clean, renewable energy solution, is becoming increasingly important in the energy market. The application process for new photovoltaic installation projects involves a lot of information collection and filling, including but not limited to project name, installation address, installed capacity, contract details, etc. The accuracy and completeness of this information is crucial for project approval and implementation. However, the current photovoltaic new installation application process mostly relies on manual processing, which is not only inefficient but also prone to human errors, especially when faced with massive data and high-frequency user applications. This problem is particularly prominent.

[0003] In order to solve the above problems, some form filling systems based on traditional automation technology have emerged in recent years. They mainly use preset rules and templates to partially automate the filling of new photovoltaic installation forms. Although these systems have reduced the burden on business personnel to a certain extent, they often lack the ability to process unstructured data, especially for the recognition and extraction of text information, and the efficiency and accuracy still need to be improved. In addition, these systems are usually unable to adapt to the rapidly changing needs of the photovoltaic industry, and lack flexibility and scalability.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] Embodiments of the present invention provide a photovoltaic application data processing method, system, electronic device and storage medium to at least solve the technical problem of low efficiency and accuracy in filling out photovoltaic application forms.

[0006] According to one aspect of an embodiment of the present invention, a method for processing photovoltaic application data is provided, comprising: obtaining photovoltaic application data; performing feature extraction on the photovoltaic application data using a pre-trained form filling model to obtain field data; and filling the field data into a target form to obtain a photovoltaic application form.

[0007] Optionally, the photovoltaic installation data includes at least: the name of the reported project, the installation address, the project parameters and the electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0008] Optionally, training of the form filling model includes: obtaining historical data, wherein the historical data includes reporting data and forms corresponding to the reporting data; constructing a training set and a validation set based on the historical data; using the training set to train a pre-built natural language processing model to obtain an initial model; and using the validation set to optimize the initial model to obtain the form filling model.

[0009] Optionally, a pre-trained form filling model is used to extract features from photovoltaic application data to obtain field data, including: preprocessing the photovoltaic application data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization; inputting the standard data into the form filling model for feature extraction to obtain multiple categories of features, wherein the multiple categories of features are used to correspond to multiple field types in the form; and determining the field data based on the multiple categories of features.

[0010] Optionally, the field data is filled into a target form to obtain a photovoltaic application form, including: according to the field data, using a preset matching model to determine a target form from multiple preset forms; and filling the field data into the target form to obtain a photovoltaic application form.

[0011] Optionally, the photovoltaic application data processing method also includes: using a preset verification strategy to verify the integrity of the photovoltaic application form to obtain a verification result; in response to the verification result indicating that the photovoltaic application form is incomplete, obtaining an empty field; based on the empty field, using the form filling model to extract features of the photovoltaic application data to obtain a supplementary field, wherein the supplementary field is used to fill in the empty field.

[0012] According to another aspect of an embodiment of the present invention, a photovoltaic application data processing system is also provided, including: an acquisition module for acquiring photovoltaic application data; an extraction module for performing feature extraction on photovoltaic application data using a pre-trained form filling model to obtain field data; and a filling module for filling the field data into a target form to obtain a photovoltaic application form.

[0013] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the photovoltaic installation data processing method in any one of the above items is executed when the program is running.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute any of the above-mentioned photovoltaic installation data processing methods.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the photovoltaic installation data processing method in any of the above items is implemented.

[0016] In an embodiment of the present invention, photovoltaic application data is obtained; a pre-trained form filling model is used to extract features of the photovoltaic application data to obtain field data; the field data is filled into a target form to obtain a photovoltaic application form. The present invention achieves the purpose of automatically filling in photovoltaic application data through a pre-trained form filling model, thereby achieving the technical effect of effectively improving the efficiency and accuracy of filling in photovoltaic application forms, thereby solving the technical problem of low efficiency and accuracy of filling in photovoltaic application forms. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a photovoltaic installation data processing method according to one embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of a photovoltaic installation data processing method according to one embodiment of the present invention;

[0020] Figure 3 It is a structural block diagram of a photovoltaic installation data processing system according to one embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present invention, an embodiment of a photovoltaic installation data processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system containing at least one set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] The method embodiment may also be performed in an electronic device, a similar control device or an electronic device including a memory and a processor. Taking an electronic device as an example, the electronic device may include one or more processors and a memory for storing data. Optionally, the electronic device may also include a communication device and a display device for communication functions. It will be understood by those skilled in the art that the above structural description is only illustrative and does not limit the structure of the above electronic device. For example, the electronic device may also include more or fewer components than the above structural description, or have a configuration different from the above structural description.

[0025] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a field-programmable gate array (FPGA), a neural-network processing unit (NPU), a tensor processing unit (TPU), an artificial intelligence (AI) type processor, and other processing devices. Among them, different processing units may be independent components or integrated into one or more processors. In some instances, the electronic device may also include one or more processors.

[0026] The memory can be used to store computer programs, such as storing a computer program corresponding to the photovoltaic installation data processing method in the embodiment of the present invention. The processor implements the photovoltaic installation data processing method by running the computer program stored in the memory. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the electronic device via a grid. Examples of the above-mentioned grid include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] Figure 1 is a flow chart of a photovoltaic installation data processing method according to one embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0028] Step S101, obtaining photovoltaic installation data.

[0029] Specifically, PV application data are obtained from different channels, which may come from online application forms, emails, phone records, scanned copies of paper documents, etc. The data forms of the obtained PV application data include but are not limited to structured data (such as database entries) and unstructured data (such as free text descriptions).

[0030] Step S102: Use the pre-trained form filling model to extract features from the photovoltaic installation data to obtain field data.

[0031] Specifically, the pre-trained form-filling model is a natural language processing model. The form-filling model has been trained on a large amount of photovoltaic application data and has strong language understanding and feature extraction capabilities.

[0032] The pre-trained form-filling model can extract semantic features from PV application data, which are essential for identifying and classifying key information of PV applications. Feature extraction strategies include identifying entities (such as applicant name, address, contact information), extracting key values ​​(such as installed capacity, expected power generation), and understanding text context (such as project description, contract terms). Through these strategies, the form-filling model can automatically locate and extract the required field data in the PV application form.

[0033] It should be noted that when processing PV application data, you may encounter abnormal situations such as missing information and ambiguous expressions, which cannot be directly handled by the pre-trained form filling model. Therefore, you can set a threshold to judge the completeness of the information, or use a rule-based filling strategy to supplement the missing information to deal with these abnormal situations.

[0034] Step S103, fill the field data into the target form to obtain a photovoltaic application form.

[0035] Specifically, using the pre-trained form filling model, the extracted field data can be automatically filled into the corresponding position of the target form. This process requires the model to understand the meaning of the field and the relevance of the data to ensure the logic and consistency of the filling. For example, the model can recognize that the "project address" field should be filled with address information, while the "contract validity period" field should be filled with the date.

[0036] Optionally, after the data is filled, automatic verification is performed to check the accuracy and completeness of the filled data to ensure that there are no omissions or errors. In addition, a correction interface can be provided to allow users or business personnel to review and modify the filling results to ensure that the final generated photovoltaic installation form is correct.

[0037] Specifically, when all field data are successfully filled and verified, a complete photovoltaic application form is generated. The form can be in any format, including but not limited to PDF, Word document or online form, for easy submission and archiving.

[0038] It should be noted that during the data filling process, some abnormal situations may occur, such as data type mismatch, missing field information, etc. Therefore, the form filling model should be able to handle these abnormalities intelligently, provide data correction suggestions or filling prompts, help users quickly solve problems, and avoid form generation failure.

[0039] In an embodiment of the present invention, photovoltaic application data is obtained; a pre-trained form filling model is used to extract features of the photovoltaic application data to obtain field data; the field data is filled into a target form to obtain a photovoltaic application form. The present invention achieves the purpose of automatically filling in photovoltaic application data through a pre-trained form filling model, thereby achieving the technical effect of effectively improving the efficiency and accuracy of filling in photovoltaic application forms, thereby solving the technical problem of low efficiency and accuracy of filling in photovoltaic application forms.

[0040] Optionally, in step S101, the photovoltaic installation data includes at least: the name of the installation project, the installation address, the project parameters and the electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0041] Specifically, the registered project name is the basic identification information of the photovoltaic project, which usually includes descriptive information such as the project location, project type (such as residential, commercial), and project scale. The project name not only helps photovoltaic service providers or power grid companies to quickly identify the nature of the project, but also facilitates subsequent project management and query.

[0042] Specifically, the installation address refers to the specific installation location of the photovoltaic system, including detailed street address, floor, installation surface, etc. This data is crucial for the design and installation of the photovoltaic system, because it directly affects the orientation, tilt angle, shadow analysis, etc. of the photovoltaic system, thereby affecting the power generation efficiency and system performance.

[0043] Specifically, the project parameters include: installed capacity, inverter model, battery type and bracket material. Among them, installed capacity refers to the total power generation capacity of the photovoltaic system, usually in kilowatts (KW) or megawatts (MW). This parameter is the basis for designing photovoltaic systems and calculating expected power generation, and is also the key for power grid companies to evaluate grid connection needs. The inverter is an important device that converts the direct current generated by photovoltaic panels into alternating current. The model of the inverter is directly related to the electrical performance and compatibility of the system and is key information for electrical design. The battery type refers to the type of battery used to store electrical energy in the photovoltaic system, including but not limited to lead-acid batteries, lithium-ion batteries, etc. The choice of battery affects the energy storage capacity and maintenance cost of the system. The bracket material of the photovoltaic panel determines the stability and durability of the photovoltaic system. Common materials include aluminum alloys, stainless steel, etc. The selection of bracket materials must take into account the environmental conditions (such as wind speed, corrosiveness) and cost factors of the installation site.

[0044] Specifically, electrical parameters include: expected power generation and cable specifications. Among them, the expected power generation is calculated based on factors such as the installed capacity of the photovoltaic system, the sunshine conditions of the installation site, and the efficiency of the photovoltaic panels. The expected power generation is the basis for evaluating the return on investment of photovoltaics and designing power output plans. Cable specifications include parameters such as cable size, material, and rated current, which directly affect the electrical safety and operating efficiency of the photovoltaic system.

[0045] Optionally, the training of the form filling model may include the following steps:

[0046] S201, obtaining historical data, wherein the historical data includes application data and a form corresponding to the application data;

[0047] Specifically, historical data comes from the company's internal database, historical registration records, completed photovoltaic project archives, etc. This includes a large amount of registration data, such as project name, installation address, installed capacity and other information, as well as the application examples of these data in the actual form filling process, that is, the completed photovoltaic registration form.

[0048] Optionally, the acquired historical data is preprocessed, including cleaning invalid or duplicate data, standardizing text formats, correcting erroneous information, etc., to ensure the quality of the data and provide a reliable foundation for model training.

[0049] S202, constructing a training set and a validation set based on historical data;

[0050] Specifically, a part of the historical data is randomly divided as a training set for model training; the other part is used as a validation set for model testing and optimization.

[0051] It should be noted that for each reported data, its correct position and format in the form need to be marked, that is, the corresponding label needs to be generated. This step may require manual participation, especially for complex or non-standard forms.

[0052] In addition, it is necessary to ensure that the data distribution in the training set and the validation set is balanced to avoid overfitting of the model on specific types of data and improve the generalization ability of the model.

[0053] S203, using the training set to train the pre-built natural language processing model to obtain an initial model;

[0054] Exemplarily, the pre-built natural language processing model may be a BERT (Bidirectional Encoder Representations from Transformers) model, which has been trained on a large-scale corpus and has good language understanding capabilities.

[0055] Specifically, a pre-built natural language processing model is used to extract key features from the reporting data in the training set, including but not limited to entity recognition, relationship extraction, text classification, etc., so that the model can understand the meaning and context of the data.

[0056] Specifically, through supervised learning, the pre-built natural language processing model is trained with labeled training set data to learn how to accurately fill in the application data into the form. This process involves adjusting the parameters of the model to minimize the difference between the predicted results and the actual labels, and finally obtaining the initial model.

[0057] S204, optimizing the initial model using the validation set to obtain a form filling model.

[0058] Specifically, the performance of the initial model is evaluated on the validation set, including indicators such as accuracy and recall, to determine the performance of the initial model on unseen data.

[0059] Specifically, according to the performance of the initial model on the validation set, the model's hyperparameters, such as learning rate, batch size, regularization coefficient, etc., are adjusted to optimize the model's performance. Through multiple iterations and parameter adjustments, the model parameters that enable the model performance to meet the preset requirements are determined, and then the form filling model is obtained.

[0060] Optionally, as time goes by and new projects are added, the training data can be updated regularly to ensure that the form filling model can adapt to the latest application requirements and form format changes.

[0061] Optionally, in step S102, using a pre-trained form filling model to extract features from photovoltaic installation data to obtain field data may include the following steps:

[0062] S301, preprocessing the photovoltaic installation data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization;

[0063] Specifically, text cleaning aims to clean up the noise in the original application data, including but not limited to removing irrelevant text, correcting typos, deleting special characters or HTML tags, etc. Text cleaning ensures the purity of the data and helps improve the recognition accuracy of the form filling model.

[0064] Specifically, the text standardization process includes unifying texts of different formats into a standard format, for example, unifying dates into the "year-month-day" format, unifying numbers into specific numerical representations, and converting text information into lowercase or unified spelling rules. The purpose of text standardization is to enable the form filling model to better understand the structure and content of the data, thereby improving the filling efficiency and accuracy of the form filling model.

[0065] After text cleaning and text standardization of photovoltaic application data, standard data is obtained and used as the input of the form filling model.

[0066] S302, inputting the standard data into the form filling model for feature extraction to obtain multiple types of features, wherein the multiple types of features are used to correspond to multiple field types in the form;

[0067] Specifically, the preprocessed photovoltaic application data will be input into the pre-trained form-filling model in a standardized text form. The pre-trained form-filling model will be used to perform deep learning on the input data. The form-filling model can understand the meaning of words from the context and extract multiple types of features from the photovoltaic application data, such as entity features, numerical features, date features, category features, etc.

[0068] Specifically, through feature extraction, the form filling model can identify features corresponding to specific field types, such as "installed capacity" corresponds to numerical features, "installation address" corresponds to text features, and "estimated power generation" corresponds to a combination of numerical and date features. These features will be used to guide the automatic filling of data to ensure that each field type can obtain the correct information.

[0069] S303, determining field data according to multiple types of features.

[0070] Specifically, the form filling model matches the extracted multi-category features with the names and types of the fields in the form to ensure that each feature can accurately correspond to the corresponding field in the form. For example, the numerical feature "installed capacity" will be mapped to the corresponding field in the form, while the text feature "installation address" will be mapped to the address field.

[0071] Optionally, in step S103, filling the field data into the target form to obtain a photovoltaic application form may include the following steps:

[0072] S401, determining a target form from a plurality of preset forms according to the field data and using a preset matching model;

[0073] Specifically, the preset matching model is trained by analyzing historical data and multiple form templates. The preset matching model is designed to understand the characteristics of different photovoltaic application projects and determine the most suitable form template accordingly.

[0074] Specifically, the field data extracted from the PV application data, such as project name, installation address, installed capacity, inverter model, etc., is input into the preset matching model. The preset matching model will compare the input field data with the preset multiple form templates, such as checking whether there is a field for installed capacity in the template and whether the format of the field matches the extracted features. Based on the comparison results, the preset matching model will assign a relevance score to each template. The higher the score, the higher the match between the template and the project data. Based on the scoring results, the preset matching model automatically selects the template with the highest relevance as the target form.

[0075] This process ensures that data is accurately filled into the most appropriate form, avoiding filling errors caused by mismatched form formats.

[0076] S402, filling the field data into the target form to obtain a photovoltaic application form.

[0077] Specifically, after the target form is determined, the field data is converted to the necessary format according to the format requirements of the target form fields. For example, the value of the installed capacity is converted from kilowatts to megawatts, or the installation address is adapted according to the specific field format in the form template.

[0078] Specifically, the converted field data is automatically filled into the corresponding fields of the target form to obtain the photovoltaic application form. This process involves further verification of the data, such as checking the rationality of the values, the compliance of the address, etc., to ensure the accuracy of the form filling.

[0079] Optionally, although the form filling model automatically completes the filling of the photovoltaic application form, in order to ensure the accuracy of the data, the business personnel or users can review the filled form and correct any possible errors or omissions to ensure the final quality of the form. After the user reviews and confirms that it is correct, the final photovoltaic application form is generated and saved in the database for subsequent approval, management and query. At the same time, the electronic and printed versions of the form are generated to meet different submission requirements.

[0080] Optionally, the photovoltaic installation data processing method may further include the following steps:

[0081] S501, using a preset verification strategy, verifying the integrity of the photovoltaic installation form to obtain a verification result;

[0082] Specifically, the preset verification strategy includes but is not limited to the following aspects: Checking required fields: Some fields in the form may be marked as required, and the verification strategy needs to check whether these fields have been filled in and whether the data format meets the requirements; Data consistency verification: Check whether the data in the filled-in fields in the form are consistent with each other, such as whether the address information is the same in multiple fields, whether the unit and value of the numeric field are reasonable, etc.; Rule check: Based on the business rules of photovoltaic registration, verify whether the form data meets specific conditions, for example, whether the installed capacity exceeds the grid capacity limit of the installation address.

[0083] Through the above validation strategy, it is possible to identify fields that are not filled in correctly or are missing, thus ensuring the integrity of the form.

[0084] S502, in response to the verification result indicating that the photovoltaic application form is incompletely filled out, obtaining an empty field;

[0085] Specifically, when the validation strategy finds that the form is incomplete, it automatically identifies and lists all the empty fields. These empty fields may be caused by missing original data, the model failing to correctly extract features, or the data format not meeting the requirements. The process of obtaining empty fields can ensure that subsequent filling operations are targeted and avoid duplicate or invalid filling.

[0086] S503, based on the empty fields, use the form filling model to extract features from the photovoltaic installation data to obtain supplementary fields, wherein the supplementary fields are used to fill in the empty fields.

[0087] Specifically, the form filling model is used again to conduct an in-depth analysis of the photovoltaic installation data, focusing on extracting features related to empty fields, obtaining supplementary fields, and filling in the empty fields. For example, if the "project estimated completion date" field is empty, the form filling model will try to extract information related to the project progress or duration from the data, and fill the corresponding information into the empty field as a supplementary field.

[0088] Optionally, for the supplementary fields, data formats are converted according to specific requirements of the target form, such as converting the extracted date information into a standard format of "year-month-day" and filling the converted supplementary field data into corresponding empty fields.

[0089] Optionally, Figure 2 is a schematic diagram of a photovoltaic installation data processing method according to one embodiment of the present invention. Figure 2 As shown, the photovoltaic installation data processing method may also include the following steps: collecting photovoltaic new installation project information data; based on the collected photovoltaic new installation project information data, analyzing the data format and form fields, and analyzing and judging the form structure; if the analysis and judgment results meet the preset requirements, using the preset form filling model to process the collected photovoltaic new installation project information data and extract data features; using the preset form filling model to automatically fill in the photovoltaic new installation project information data; verifying the filling results to verify whether the data is complete; if the filling is complete, generating the final photovoltaic installation form to complete the filling task.

[0090] In the embodiments of the present invention, a photovoltaic installation data processing system is also provided to implement the above embodiments and preferred implementation modes, which have been described and will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0091] Figure 3 is a structural block diagram of a photovoltaic installation data processing system 200 according to one embodiment of the present invention. Figure 3 As shown, the system includes: an acquisition module 201 for acquiring photovoltaic installation data; an extraction module 202 for extracting features from photovoltaic installation data using a pre-trained form filling model to obtain field data; and a filling module 203 for filling the field data into a target form to obtain a photovoltaic installation form.

[0092] Optionally, the photovoltaic application data acquired in the acquisition module 201 includes at least: the application project name, installation address, project parameters and electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0093] Optionally, the training of the form filling model in the extraction module 202 includes: obtaining historical data, wherein the historical data includes the reporting data and the form corresponding to the reporting data; constructing a training set and a validation set based on the historical data; using the training set to train a pre-built natural language processing model to obtain an initial model; and using the validation set to optimize the initial model to obtain the form filling model.

[0094] Optionally, the extraction module 202 is also used to: pre-process the photovoltaic installation data to obtain standard data, wherein the pre-processing includes text cleaning and text standardization; input the standard data into the form filling model for feature extraction to obtain multiple categories of features, wherein the multiple categories of features are used to correspond to multiple field types in the form; determine the field data based on the multiple categories of features.

[0095] Optionally, the filling module 203 is further used to: determine a target form from a plurality of preset forms according to the field data using a preset matching model; and fill the field data into the target form to obtain a photovoltaic application form.

[0096] Optionally, the extraction module 202 is also used to: use a preset verification strategy to verify the integrity of the photovoltaic application form to obtain a verification result; in response to the verification result indicating that the photovoltaic application form is incomplete, obtain an empty field; based on the empty field, use the form filling model to extract features of the photovoltaic application data to obtain a supplementary field, wherein the supplementary field is used to fill in the empty field.

[0097] An embodiment of the present invention further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein when the program is running, the photovoltaic installation data processing method described in any of the above embodiments is executed.

[0098] Optionally, in this embodiment, the processor in the electronic device may be configured to run an executable program to perform the following steps:

[0099] Step S101, obtaining photovoltaic installation data.

[0100] Step S102: Use the pre-trained form filling model to extract features from the photovoltaic installation data to obtain field data.

[0101] Step S103, fill the field data into the target form to obtain a photovoltaic application form.

[0102] Optionally, the photovoltaic application data acquired by the processor in the above-mentioned electronic device when running the executable program includes at least: the application project name, installation address, project parameters and electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0103] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: obtain historical data, wherein the historical data includes reporting data and forms corresponding to the reporting data; construct a training set and a verification set based on the historical data; use the training set to train a pre-built natural language processing model to obtain an initial model; use the verification set to optimize the initial model to obtain a form filling model.

[0104] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: preprocessing the photovoltaic installation data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization; inputting the standard data into the form filling model for feature extraction to obtain multiple categories of features, wherein the multiple categories of features are used to correspond to multiple field types in the form; and determining the field data based on the multiple categories of features.

[0105] Optionally, the processor in the above electronic device can be configured to run an executable program to perform the following steps: determine a target form from multiple preset forms based on the field data using a preset matching model; fill the field data into the target form to obtain a photovoltaic application form.

[0106] Optionally, the processor in the above-mentioned electronic device can be configured to run an executable program to perform the following steps: using a preset verification strategy to verify the integrity of the photovoltaic application form to obtain a verification result; in response to the verification result indicating that the photovoltaic application form is incomplete, obtaining an empty field; based on the empty field, using the form filling model to extract features of the photovoltaic application data to obtain a supplementary field, wherein the supplementary field is used to fill in the empty field.

[0107] An embodiment of the present invention further provides a computer-readable storage medium, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the photovoltaic installation data processing method described in any of the above embodiments.

[0108] Optionally, in this embodiment, the above executable program may be configured to store an executable program for performing the following steps:

[0109] Step S101, obtaining photovoltaic installation data.

[0110] Step S102: Use the pre-trained form filling model to extract features from the photovoltaic installation data to obtain field data.

[0111] Step S103, fill the field data into the target form to obtain a photovoltaic application form.

[0112] Optionally, the photovoltaic application data acquired when the above executable program is executed includes at least: application project name, installation address, project parameters and electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0113] Optionally, the above-mentioned executable program can be configured to store an executable program for executing the following steps: obtaining historical data, wherein the historical data includes reporting data and forms corresponding to the reporting data; constructing a training set and a validation set based on the historical data; using the training set to train a pre-built natural language processing model to obtain an initial model; and using the validation set to optimize the initial model to obtain a form filling model.

[0114] Optionally, the above-mentioned executable program can be configured to store an executable program for executing the following steps: preprocessing the photovoltaic installation data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization; inputting the standard data into the form filling model for feature extraction to obtain multiple categories of features, wherein the multiple categories of features are used to correspond to multiple field types in the form; and determining the field data based on the multiple categories of features.

[0115] Optionally, the above-mentioned executable program can be configured to store an executable program for executing the following steps: according to the field data, using a preset matching model, determining a target form from multiple preset forms; filling the field data into the target form to obtain a photovoltaic application form.

[0116] Optionally, the above-mentioned executable program can be configured to store an executable program for executing the following steps: using a preset verification strategy to verify the integrity of the photovoltaic application form to obtain a verification result; in response to the verification result indicating that the photovoltaic application form is incomplete, obtaining an empty field; based on the empty field, using the form filling model to extract features of the photovoltaic application data to obtain a supplementary field, wherein the supplementary field is used to fill in the empty field.

[0117] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the photovoltaic installation data processing method described in any of the above embodiments.

[0118] Optionally, in this embodiment, the above computer program implements the following steps when executed by a processor:

[0119] Step S101, obtaining photovoltaic installation data.

[0120] Step S102: Use the pre-trained form filling model to extract features from the photovoltaic installation data to obtain field data.

[0121] Step S103, fill the field data into the target form to obtain a photovoltaic application form.

[0122] Optionally, the photovoltaic application data acquired when the above-mentioned computer program is executed by the processor includes at least: the application project name, installation address, project parameters and electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

[0123] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: obtaining historical data, wherein the historical data includes reporting data and forms corresponding to the reporting data; constructing a training set and a verification set based on the historical data; using the training set to train a pre-built natural language processing model to obtain an initial model; and using the verification set to optimize the initial model to obtain a form filling model.

[0124] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: preprocessing the photovoltaic installation data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization; inputting the standard data into the form filling model for feature extraction to obtain multiple categories of features, wherein the multiple categories of features are used to correspond to multiple field types in the form; and determining the field data based on the multiple categories of features.

[0125] Optionally, the computer program implements the following steps when executed by a processor: determine a target form from a plurality of preset forms based on the field data using a preset matching model; fill the field data into the target form to obtain a photovoltaic application form.

[0126] Optionally, the above-mentioned computer program implements the following steps when executed by the processor: using a preset verification strategy to verify the integrity of the photovoltaic application form and obtain a verification result; in response to the verification result indicating that the photovoltaic application form is incomplete, obtaining an empty field; based on the empty field, using the form filling model to extract features of the photovoltaic application data to obtain a supplementary field, wherein the supplementary field is used to fill the empty field.

[0127] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0128] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0130] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0131] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0132] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0133] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A photovoltaic installation data processing method, characterized in that: include: Obtain photovoltaic installation data; Using a pre-trained form filling model to extract features from the photovoltaic installation data to obtain field data; Fill the field data into the target form to obtain a photovoltaic application form.

2. The photovoltaic installation data processing method according to claim 1, characterized in that: The photovoltaic installation data at least includes: the name of the project, the installation address, the project parameters and the electrical parameters, wherein the project parameters include: installed capacity, inverter model, battery type and bracket material, and the electrical parameters include: expected power generation and cable specifications.

3. The photovoltaic installation data processing method according to claim 1, characterized in that: The training of the form filling model includes: Acquire historical data, wherein the historical data includes application data and a form corresponding to the application data; Constructing a training set and a validation set based on the historical data; Using the training set to train a pre-built natural language processing model to obtain an initial model; The initial model is optimized using the validation set to obtain the form filling model.

4. The photovoltaic installation data processing method according to claim 1, characterized in that: The pre-trained form filling model is used to extract features from the photovoltaic installation data to obtain field data, including: Preprocessing the photovoltaic installation data to obtain standard data, wherein the preprocessing includes text cleaning and text standardization; Inputting the standard data into the form filling model for feature extraction to obtain multiple types of features, wherein the multiple types of features are used to correspond to multiple field types in the form; The field data is determined according to the multiple types of features.

5. The photovoltaic installation data processing method according to claim 1, characterized in that: The step of filling the field data into the target form to obtain a photovoltaic application form includes: According to the field data, a target form is determined from a plurality of preset forms using a preset matching model; The field data is filled into the target form to obtain the photovoltaic application form.

6. The photovoltaic installation data processing method according to claim 1, characterized in that: Also includes: Using a preset verification strategy, the photovoltaic installation form is verified for integrity to obtain a verification result; In response to the verification result indicating that the photovoltaic application form is incompletely filled out, obtaining an empty field; According to the empty fields, the form filling model is used to perform feature extraction on the photovoltaic installation data to obtain supplementary fields, wherein the supplementary fields are used to fill the empty fields.

7. A photovoltaic installation data processing system, characterized in that: include: Acquisition module, used to obtain photovoltaic installation data; An extraction module, used to extract features from the photovoltaic application data using a pre-trained form filling model to obtain field data; The filling module is used to fill the field data into the target form to obtain a photovoltaic application form.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 6 when running.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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