A power purchase fee settlement process automation intelligent management method and system

Abstract

This invention discloses an automated and intelligent management method for electricity purchase fee settlement. It constructs a data template containing the four elements of an invoice, acquires all invoice information from the invoice pool, obtains the element information of invoices awaiting settlement, forming pending processing information, collects settlement notifications into the financial control system, and marks successful matches between invoice element information and settlement notification information as valid matching data, collects valid matching data, generates settlement statements and pending vouchers, and stores the valid matching data corresponding to the settlement statements to form the first processing data, and filters and extracts the electricity purchase fee amount from the settlement statements and pending vouchers corresponding to the invoice element information and settlement notification information, generates a payment application, and stores the valid matching data corresponding to the payment application to form the second processing data. This invention achieves efficient business processing of electricity fee settlement, reduces low-value repetitive work for financial personnel, and automatically outputs electricity purchase fee invoice information, settlement information, payment information, and ledger information.

Description

Technical Field

[0001] This invention belongs to the field of power grid electricity bill settlement technology, specifically relating to an automated and intelligent management method and system for electricity purchase fee settlement process. Background Technology

[0002] The electricity price management module is a crucial component of the financial control system. Based on generator units, this module manages the entire process of electricity purchase costs, including electricity data collection, grid connection price execution, electricity bill settlement and payment, and report preparation. It enables detailed accounting, settlement, bookkeeping, summarization, and statistical queries of electricity purchase costs based on different time periods and electricity prices for power plants / units. Currently, the main services available on the grid connection side include: input of electricity purchase targets, electricity cost estimation, electricity bill settlement notification, invoice ledger management, electricity bill settlement, electricity bill payment, report preparation, and data querying.

[0003] With the development of information technology, the efficiency of the existing system for electricity purchase fee settlement needs to be improved, and it cannot form a fully automated processing mode. At the same time, due to human involvement, the error of manual review is increased, which affects the settlement results of electricity purchase fees. Therefore, it is necessary to develop automated settlement of electricity purchase fees and dynamic monitoring of process information to promote the standardization and intelligentization of business and financial work.

[0004] To adapt to the requirements of power system reform and internal enterprise management, it is urgent to develop intelligent settlement of electricity purchase fees, realize the automatic output of electricity purchase fee invoice information, settlement information, payment information, and ledger information, improve the service level of grid-connected manufacturers, enhance the level of lean management of electricity purchase fees, and provide strong data support for transmission and distribution price reform and intelligent electricity price analysis.

[0005] In view of the shortcomings of existing technologies, there is an urgent need to design an automated and intelligent management method and system for electricity purchase fee settlement process to solve the above-mentioned technical problems. Summary of the Invention

[0006] To address the shortcomings of the existing technology, the present invention aims to overcome these deficiencies and provide an automated and intelligent management method for electricity purchase fee settlement, the method comprising the following:

[0007] S1, construct a data template containing the four elements of an invoice, match the invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool;

[0008] S2, obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the completed invoice information to form information to be processed;

[0009] S3, collect the settlement notification to the financial control system, match the invoice element information with the settlement notification information, and mark the successful match as valid matching data;

[0010] S4, collect the valid matching data, generate a settlement statement and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement statement to form the first processing data;

[0011] S5, based on the first processing data and the settlement statement, filter and extract the electricity purchase amount from the settlement statement and pending vouchers containing the corresponding invoice element information and settlement notification information, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

[0012] As a further optimization of the above solution, step S2 specifically includes the following:

[0013] Set a data template containing the four elements of an invoice, detect the collected invoice element information, and save the invoice element information that conforms to the invoice four-element template;

[0014] The invoice element information of the data template that meets the four elements of the invoice is matched with the invoice information that has been submitted. The successfully matched invoice element information and the invoice information that has been submitted are saved to form information to be processed.

[0015] The detection of the collected invoice element information includes the following:

[0016] Based on any keyword to be detected from the collected invoice elements, calculate the correlation coefficient sim between the keyword and all comparison selections in the text recognition database, and arrange the correlation coefficients sim1, sim2, ..., sim s, sim t in descending order;

[0017] Based on the calculated correlation coefficient sim, a correlation threshold s is set. 1 <s≤t;

[0018] If at least two inventory data items are recorded in the first s items of inventory data calculated by the character recognition library, then the keyword to be detected exists in a similar unit. The graphics corresponding to multiple similar units are divided into ω×ω square selection areas. The correlation coefficient of all individual square selection areas within each selection area is calculated to obtain candidate options from the character recognition library for correctly describing the keyword as effective description parameters. The square selection areas of the effective description parameters are weighted and calculated, and weights are assigned based on the magnitude of the correlation coefficients to construct a weight matrix for the effective description parameters. The maximum value of the weighted sum of the weights and correlation coefficients is obtained as the keyword detection result.

[0019] If the first s items of inventory data calculated by the character recognition library contain only one record, then the keyword to be detected does not have a similar unit; set a coordination threshold λ. 1 < λ ≤ t; Based on the coordination threshold λ, the coordination units are marked, and the correlation coefficients of all coordination units are assigned weights to construct the weight matrix of the coordination units; the maximum value of the weighted sum of the weights and correlation coefficients is obtained as the collected invoice keyword detection result.

[0020] As a further optimization of the above scheme, the method for obtaining candidate text recognition libraries for correctly describing the keywords as valid description parameters specifically includes the following:

[0021] The threshold for consensus on the association coefficient, which is used as an effective descriptive parameter, is q.

[0022] Traversing ω 2 Record the correlation coefficients corresponding to each square selection area, and record the number of square selection areas with correlation coefficients less than q.

[0023] If the number of square selection areas less than q is related to ω 2 If the ratio is not less than 0.6, then the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is discarded.

[0024] As a further optimization of the above solution, step S2 also includes the following:

[0025] If the collected invoice element information matches the data template of the four elements of the invoice, the corresponding matched invoice element information is moved to the archived data pool, and a movement record is generated.

[0026] If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding unmatched invoice element information is moved to the data pool to be processed, and a movement record is generated.

[0027] As a further optimization of the above solution, step S3 specifically includes the following:

[0028] Collect all invoices issued by electricity purchasing units to the power grid company exported from the tax platform, obtain full invoice information, and generate an invoice pool;

[0029] The system matches all invoice information stored in the invoice pool with the information to be processed. If a match is found, the corresponding information to be processed is marked as valid matching data. The corresponding successfully matched information to be processed is then moved to the archived data pool, and a move record is generated.

[0030] As a further optimization of the above solution, step S4 specifically includes the following:

[0031] Based on the valid matching data that successfully matches the full set of invoice information stored in the invoice pool with the information to be processed, a settlement order is generated accordingly;

[0032] Mark the valid matching data corresponding to the generated settlement order as the first processing data; move the corresponding settlement order and the information to be processed to the archived data pool to generate a movement record;

[0033] Based on the above settlement statement, generate a pending voucher and complete the accounting operation.

[0034] As a further optimization of the above solution, step S5 also includes the following:

[0035] The successfully matched payment application and the first processed data are moved to the archived data pool to generate a movement record.

[0036] A payment request for electricity purchase is generated based on the payment application form.

[0037] This invention also discloses an automated intelligent management system for electricity purchase fee settlement, the system comprising the following:

[0038] The invoice pool management module is used to construct a data template containing the four elements of an invoice, match invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool.

[0039] The data processing module is used to obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the invoice information that has been submitted to form information to be processed;

[0040] The invoice processing module is used to collect settlement notices into the financial control system, match the invoice element information with the settlement notice information, and mark the successful match as valid matching data.

[0041] The electricity purchase settlement module is used to collect the valid matching data, generate a settlement form and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement form to form the first processing data;

[0042] The settlement and payment module is used to filter and extract the electricity purchase amount from the settlement and pending vouchers with the corresponding invoice element information and settlement notification information based on the first processing data and the settlement document, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

[0043] As a further optimization of the above solution, the data processing module includes the following:

[0044] The data acquisition unit is used to collect invoice element information;

[0045] The data detection unit is used to set a data template containing the four elements of an invoice, detect the collected invoice element information, and save the invoice element information that conforms to the invoice four-element template.

[0046] The data verification unit is used to match the invoice element information of the data template that conforms to the four elements of the invoice with the invoice information that has been submitted, and save the successfully matched invoice element information and the submitted invoice information to form information to be processed.

[0047] As a further optimization of the above solution, the data processing module also includes the following:

[0048] If the collected invoice element information matches the data template of the four elements of the invoice, the corresponding matched invoice element information is moved to the archived data pool, and a movement record is generated.

[0049] If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding unmatched invoice element information is moved to the data pool to be processed, and a movement record is generated.

[0050] As a further optimization of the above solution, the invoice processing module includes the following:

[0051] The invoice pool is used to collect all invoices issued by electricity purchasing units to the power grid company exported from the tax platform, and to obtain full invoice information.

[0052] The invoice matching unit is used to match the full amount of invoice information stored in the invoice pool with the information to be processed. If the match is successful, the corresponding information to be processed is marked as valid matching data, and the corresponding successfully matched information to be processed is moved to the archived data pool to generate a movement record.

[0053] The present invention adopts the above-described technical solution, and compared with the prior art, it has the following beneficial effects:

[0054] 1. This invention constructs a data template containing the four elements of an invoice, matches invoices in the invoice pool of the financial control system; obtains the invoice element information of pending electricity purchase fees, forming pending processing information; collects settlement notifications to the financial control system; collects the effective matching data, generates settlement slips and pending vouchers corresponding to the invoice element information and settlement notification information of the effective matching data, and stores the effective matching data corresponding to the settlement slips to form first processing data; based on the first processing data and the settlement slips, the settlement slips and pending vouchers with the corresponding invoice element information and settlement notification information are filtered and the electricity purchase fee amount is extracted to generate a payment application. According to the construction requirements of electricity purchase fee settlement, the financial management electricity price management module of this invention realizes automatic invoice matching, automatic settlement and accounting, and automatic initiation of payment applications and pooling, achieving efficient business processing in all aspects of electricity fee settlement and reducing low-value repetitive work for financial personnel. By optimizing the system process, constructing an invoice pool, a voucher pool, and an electricity purchase fee management ledger, it realizes automatic output of electricity purchase fee invoice information, settlement information, payment information, and ledger information, and real-time online collection of settlement data, improving the lean management level of electricity purchase fees and meeting internal management and external supervision requirements.

[0055] 2. This invention monitors the electricity purchase fee settlement process in real time, intuitively displays the accounting status of electricity purchase fee costs, and provides timely warnings of abnormal events; it automatically integrates information such as payable, actual payment, payment batches, payment methods, and payment status, comprehensively displaying the electricity purchase fee payment results, and avoiding accounting problems in invoice auditing and payment caused by the failure to match abnormal electricity purchase fee data entered by the power grid company. Attached Figure Description

[0056] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0057] Figure 1 This is a schematic diagram of the process of the present invention;

[0058] Figure 2 This is another schematic diagram of the process of the present invention. Detailed Implementation

[0059] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0060] like Figure 1-2 As shown in the figure, this invention discloses an automated intelligent management method for electricity purchase fee settlement, including the following:

[0061] S1, construct a data template containing the four elements of an invoice, match the invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool;

[0062] S2, obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the completed invoice information to form information to be processed;

[0063] S3, collect the settlement notification to the financial control system, match the invoice element information with the settlement notification information, and mark the successful match as valid matching data;

[0064] S4, collect the valid matching data, generate a settlement statement and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement statement to form the first processing data;

[0065] S5, based on the first processing data and the settlement statement, filter and extract the electricity purchase amount from the settlement statement and pending vouchers containing the corresponding invoice element information and settlement notification information, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

[0066] This invention enables efficient business processing at each stage of electricity bill settlement, reducing low-value repetitive work for finance personnel. By optimizing system processes and constructing an invoice pool, a receipt pool, and an electricity purchase fee management ledger, it achieves automatic output of electricity purchase fee invoice information, settlement information, payment information, and ledger information. Settlement data is collected online in real time, improving the level of lean management of electricity purchase fees and meeting internal management and external supervision requirements.

[0067] Specifically, step S2 includes the following:

[0068] Set a data template containing the four elements of an invoice, detect the collected invoice element information, and save the invoice element information that conforms to the invoice four-element template;

[0069] The invoice element information of the data template that meets the four elements of the invoice is matched with the invoice information that has been submitted. The successfully matched invoice element information and the invoice information that has been submitted are saved to form information to be processed.

[0070] The detection of the collected invoice element information includes the following:

[0071] Based on any keyword to be detected from the collected invoice elements, calculate the correlation coefficient sim between the keyword and all comparison selections in the text recognition database, and arrange the correlation coefficients sim1, sim2, ..., sim s, sim t in descending order;

[0072] Based on the calculated correlation coefficient sim, a correlation threshold s is set. 1 < s ≤ t; In particular, the technology of the present invention compares and matches the features of the keyword to be detected with the character recognition library, and provides a four-element detection and judgment standard for subsequent invoices by setting an association threshold. After confirming the number of items that meet the association threshold, it can quickly determine whether there are easily confused interference items in the keyword to be detected. That is, through this setting, the matching accuracy of the keyword to be detected is improved, and the risk of four-element matching failure in collecting invoices can be reduced;

[0073] If among the first s inventory data calculated in the character recognition library, the recorded inventory data is at least 2, then there are similar units in the keyword to be detected; respectively divide the corresponding graphics of the multiple similar units into ω×ω square selection areas, calculate the correlation coefficients of all the individual square selection areas within the selection area, and obtain the alternatives of the character recognition library for correctly describing the keyword as effective description parameters; perform weighted calculation on the square selection areas of the effective description parameters, and based on the numerical size of the correlation coefficient, allocate weights correspondingly to construct a weight matrix of the effective description parameters; obtain the maximum value of the weighted sum of the weight and the correlation coefficient as the keyword detection result;

[0074] In particular, it should be noted that the correlation coefficient of the present invention is based on graphic feature extraction, specifically manifested as constructing an image comparison feature map of the keyword to be detected and the existing data stored in the character recognition library. The calculation method is as follows:

[0075]

[0076] In the above formula, x t is the image feature of the keyword to be detected, is the average value of x t ; y t is the image feature of the existing data stored in the character recognition library, is the average value of y t ;

[0077] For the convenience of calculation, according to the keyword structure, the present invention divides the corresponding graphic into (2n - 1)×(2n - 1) square selection areas to ensure the existence of a central square selection area. Preferably, the present invention divides the corresponding graphic into a 3×3 pattern.

[0078] The extraction and calculation of any image feature belong to conventional technologies, and processing the image of the keyword to be detected into the same image specification as the existing data stored in the character recognition library belongs to the prior art. Therefore, no detailed description is given here, and those skilled in the art can understand and master this means according to the technical solution of the present invention.

[0079] If among the first s inventory data calculated in the character recognition library, the recorded inventory data is 1, then there are no similar units in the keyword to be detected; set a coordination threshold λ, 1 < λ ≤ t; Based on the coordination threshold λ, the coordination units are marked, and the correlation coefficients of all coordination units are assigned weights to construct the weight matrix of the coordination units; the maximum value of the weighted sum of the weights and correlation coefficients is obtained as the collected invoice keyword detection result.

[0080] It should be noted that the effective methods for assigning weights to the correlation coefficients between the parameters, the coordination unit, and the keywords to be detected include the following:

[0081]

[0082] Based on the above formula, let the maximum value of the weighted sum of the weights and correlation coefficients be set as Goal, then:

[0083]

[0084] Where t is the keyword to be detected.

[0085] Specifically, the method for obtaining candidate text recognition libraries for correctly describing the keywords as valid description parameters includes the following:

[0086] The threshold for consensus on the association coefficient, which is used as an effective descriptive parameter, is q.

[0087] Traversing ω 2 Record the correlation coefficients corresponding to each square selection area, and record the number of square selection areas with correlation coefficients less than q.

[0088] If the number of square selection areas less than q is related to ω 2 If the ratio is not less than 0.6, then the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is discarded.

[0089] In determining the effective descriptive parameters, this invention further discloses the correlation coefficient agreement threshold. That is, after dividing the candidate options of any character recognition library into equal areas, the correlation coefficient corresponding to each square selection area is calculated, and the number of units that meet the correlation coefficient agreement threshold is counted. This further determines whether the similar unit can be used as an effective descriptive parameter, eliminates a large number of interference items, and improves the detection accuracy of the four elements of the invoice.

[0090] More specifically, it can set up data templates containing the four elements of an invoice according to the target audience. It can be designed to include basic information such as seller information, buyer information, transaction information, and time information, and further record information such as transaction account, electricity consumption data, and tax payment rate to facilitate the integrity verification of invoice information.

[0091] Specifically, step S2 also includes the following:

[0092] If the collected invoice element information matches the data template of the four elements of the invoice, the corresponding matched invoice element information is moved to the archived data pool, and a movement record is generated.

[0093] If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding unmatched invoice element information is moved to the data pool to be processed, and a movement record is generated.

[0094] More specifically, this invention further verifies invoice information matched using a data template that includes the four elements of an invoice. In daily use, the data actually approved by the enterprise is used as the final reference standard for verifying invoice information. If the invoice successfully matched using the data template includes the four elements of an invoice and the actual approved data are accurate, the corresponding matched invoice element information is moved to the archived data pool; otherwise, it is moved to the pending data pool.

[0095] This invention provides real-time monitoring of the electricity purchase fee settlement process, intuitively displays the accounting status of electricity purchase fee costs, and promptly warns of abnormal events. It automatically integrates information such as payable, actual payment, payment batches, payment methods, and payment status, comprehensively displaying the electricity purchase fee payment results. This avoids accounting problems in invoice auditing and payment caused by the failure to match abnormal electricity purchase fee data entered by the power grid company.

[0096] As another embodiment of the present invention, the present invention also provides the following:

[0097] The billing information is displayed in tabs for estimated and formal settlement, and can be filtered by month and year of electricity billing for easy viewing and export of details;

[0098] Automatically match invoices with pending settlement data according to invoice matching rules, and call the electricity bill settlement data and invoice consistency audit service to audit the rules;

[0099] If automatic matching fails, a manual intervention interface is provided to manually match documents and invoices that cannot be matched.

[0100] Automatically match invoices with pending settlement data according to invoice matching rules, and call the electricity bill settlement data and invoice consistency audit service to audit the rules;

[0101] It supports the export of pending and settled data, facilitating subsequent reconciliation and other business operations.

[0102] Specifically, step S3 includes the following:

[0103] Collect all invoices issued by electricity purchasing units to the power grid company exported from the tax platform, obtain full invoice information, and generate an invoice pool;

[0104] More specifically, the invoices issued by all electricity purchasing units to the power grid company mentioned in this invention mainly include various types such as special invoices, ordinary invoices, and electronic invoices. This invention's technology achieves continuous acquisition of electricity invoice information data from all electricity purchasing units to the power grid company by connecting the enterprise with the tax platform. Furthermore, all invoices used for recording electricity consumption data from electricity purchasing units to the power grid company together constitute an invoice pool.

[0105] Specifically, the full set of invoice information stored in the invoice pool is matched with the information to be processed. If a match is successful, the corresponding information to be processed is marked as valid matching data, and the corresponding successfully matched information to be processed is moved to the archived data pool to generate a move record.

[0106] Specifically, step S4 includes the following:

[0107] Based on the valid matching data that successfully matches the full set of invoice information stored in the invoice pool with the information to be processed, a settlement statement is generated accordingly. This invention, based on the automated process of invoice pool storage, fully realizes the automatic processing and entry of settlement statements. Furthermore, the matching data corresponding to the settlement statement and the pending voucher is saved in the settlement statement and marked as the first processing data. It should be noted that after marking the first processing data, the matching data corresponding to the settlement statement and the pending voucher in the valid matching data needs to be subtracted simultaneously to avoid double counting.

[0108] Mark the valid matching data corresponding to the generated settlement order as the first processing data; move the corresponding settlement order and pending information to the archived data pool to generate a movement record; generate a pending voucher based on the above settlement order to complete the accounting operation.

[0109] More specifically, based on settlement statement information, this invention automatically generates pending vouchers, calls the voucher generation service, constructs a data model, calls the voucher review service, generates settlement vouchers, and saves information such as voucher numbers; it also automatically supplements auxiliary accounting information such as the number of attached documents and account dimensions, and automatically records the transactions.

[0110] More specifically, approval rules can be preset according to the actual situation, and the settlement statement can be approved according to the approval rules to complete the above approval process.

[0111] Specifically, step S5 also includes the following:

[0112] The successfully matched payment application and the first processed data are moved to the archived data pool to generate a movement record.

[0113] A payment request for electricity purchase is generated based on the payment application form.

[0114] More specifically, an automated process for electricity purchase settlement and payment can be set up to replace the generation of electricity purchase order settlement and payment requests, enter the electricity payment application function, query pending payment data, initiate payment applications, and provide feedback on task processing status via email.

[0115] More specifically, this invention automatically triggers a payment request based on the recorded cost voucher information and links it to the cash flow budget, generating a payment request form. The specific implementation is as follows:

[0116] Offers the option to set a payment time for scheduled payments;

[0117] It provides the function of setting payment methods, including bank transfer, bank draft, etc.;

[0118] It provides a function to set the payment ratio, allowing payments to be made proportionally.

[0119] It provides a function to set up payment batches, allowing payments to be made in batches;

[0120] Automatically trigger payment requests and generate payment documents from settled records.

[0121] The present invention also discloses another embodiment, an automated intelligent management system for electricity purchase fee settlement process, the system comprising the following:

[0122] The invoice pool management module is used to construct a data template containing the four elements of an invoice, match invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool.

[0123] The data processing module is used to obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the invoice information that has been submitted to form information to be processed;

[0124] The invoice processing module is used to collect settlement notices into the financial control system, match the invoice element information with the settlement notice information, and mark the successful match as valid matching data.

[0125] The electricity purchase settlement module is used to collect the valid matching data, generate a settlement form and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement form to form the first processing data;

[0126] The settlement and payment module is used to filter and extract the electricity purchase amount from the settlement and pending vouchers with the corresponding invoice element information and settlement notification information based on the first processing data and the settlement document, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

[0127] It should be noted that another embodiment of the present invention, an automated intelligent management system for electricity purchase fee settlement process, uses the same technical means as an automated intelligent management method for electricity purchase fee settlement process, and therefore will not be described in detail here.

[0128] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for automating and intelligently managing the electricity purchase fee settlement process, characterized in that, The method includes the following: S1, construct a data template containing the four elements of an invoice, match the invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool; S2, obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the completed invoice information to form information to be processed; Step S2 specifically includes the following: Set a data template containing the four elements of an invoice, detect the collected invoice element information, and save the invoice element information that conforms to the invoice four-element template; The invoice element information of the data template that meets the four elements of the invoice is matched with the invoice information that has been submitted. The successfully matched invoice element information and the invoice information that has been submitted are saved to form information to be processed. The detection of the collected invoice element information includes the following: Based on any keyword to be detected from the collected invoice elements, calculate the correlation coefficient between the keyword and all comparison selections in the character recognition database. The correlation coefficients are arranged in descending order. ; Based on the calculated correlation coefficient Set the association threshold , , ; If the text recognition database is used for calculation... If at least two inventory records are recorded in the inventory data, then the keyword to be detected has similar units; the graphics corresponding to multiple similar units are divided into equal parts. For a square selection area, the correlation coefficient of all individual square selection areas within the selection area is calculated to obtain candidate options from the text recognition library for correctly describing the keyword as effective description parameters; the square selection areas of the effective description parameters are weighted and calculated, and weights are assigned according to the magnitude of the correlation coefficient to construct a weight matrix of the effective description parameters; the maximum value of the weighted sum of the weights and correlation coefficients is obtained as the keyword detection result; If the text recognition database is used for calculation... If there is only one record of inventory data in the inventory data, then there is no similar unit for the keyword to be detected; set a coordination threshold. , , Based on coordination threshold Label the coordination units, assign weights to the correlation coefficients of all coordination units, and construct a weight matrix for the coordination units; obtain the maximum value of the weighted sum of the weights and correlation coefficients as the collected invoice keyword detection results; Effective methods for assigning weights to the correlation coefficients between parameters, coordination units, and the keywords to be detected include the following: ； Based on the above formula, the maximum value of the weighted sum of the weights and correlation coefficients is set as follows: ,but: ； in, Keywords to be detected; The method for obtaining candidate text recognition libraries for correctly describing the keywords as valid description parameters specifically includes the following: The threshold for agreeing on the association coefficient as a valid descriptive parameter is: ; Traversal The correlation coefficients corresponding to the selected square regions are recorded, and the correlation coefficients are less than [a certain value]. The number of square selection areas; If less than The number of square selection areas and If the ratio is not less than 0.6, then the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is discarded. S3, collect the settlement notification to the financial control system, match the invoice element information with the settlement notification information, and mark the successful match as valid matching data; S4, collect the valid matching data, generate a settlement statement and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement statement to form the first processing data; S5, based on the first processing data and the settlement statement, filter and extract the electricity purchase amount from the settlement statement and pending vouchers containing the corresponding invoice element information and settlement notification information, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

2. The automated intelligent management method for electricity purchase fee settlement process according to claim 1, characterized in that, Step S2 further includes the following: If the collected invoice element information matches the data template of the four elements of the invoice, the corresponding matched invoice element information is moved to the archived data pool, and a movement record is generated. If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding unmatched invoice element information is moved to the data pool to be processed, and a movement record is generated.

3. The automated intelligent management method for electricity purchase fee settlement process according to claim 2, characterized in that, Step S3 specifically includes the following: Collect all invoices issued by electricity purchasing units to the power grid company exported from the tax platform, obtain full invoice information, and generate an invoice pool; The system matches all invoice information stored in the invoice pool with the information to be processed. If a match is found, the corresponding information to be processed is marked as valid matching data. The corresponding successfully matched information to be processed is then moved to the archived data pool, and a move record is generated.

4. The automated intelligent management method for electricity purchase fee settlement process according to claim 3, characterized in that, Step S4 specifically includes the following: Based on the valid matching data that successfully matches the full set of invoice information stored in the invoice pool with the information to be processed, a settlement order is generated accordingly; Mark the valid matching data corresponding to the generated settlement statement as the first processing data; Move the corresponding settlement order and pending information to the archived data pool to generate a move record; Based on the above settlement statement, generate a pending voucher and complete the accounting operation.

5. The automated intelligent management method for electricity purchase fee settlement process according to claim 4, characterized in that, Step S5 also includes the following: The successfully matched payment application and the first processed data are moved to the archived data pool to generate a movement record. A payment request for electricity purchase is generated based on the payment application form.

6. An automated intelligent management system for electricity purchase fee settlement process, wherein the system adopts the automated intelligent management method for electricity purchase fee settlement process as described in claim 1, characterized in that, The system includes the following: The invoice pool management module is used to construct a data template containing the four elements of an invoice, match invoices in the invoice pool of the financial control system, and obtain the full invoice information of the invoice pool. The data processing module is used to obtain the invoice element information of the electricity purchase fee to be settled, and match the invoice element information with the invoice information that has been submitted to form information to be processed; The invoice processing module is used to collect settlement notices into the financial control system, match the invoice element information with the settlement notice information, and mark the successful match as valid matching data. The electricity purchase settlement module is used to collect the valid matching data, generate a settlement form and a pending voucher that correspond to the invoice element information and settlement notification information of the valid matching data, and store the valid matching data corresponding to the settlement form to form the first processing data; The settlement and payment module is used to filter and extract the electricity purchase amount from the settlement and pending vouchers with the corresponding invoice element information and settlement notification information based on the first processing data and the settlement document, generate a payment application form, and store the valid matching data corresponding to the payment application form to form the second processing data.

7. The automated intelligent management system for electricity purchase fee settlement process according to claim 6, characterized in that, The data processing module includes the following: The data acquisition unit is used to collect invoice element information; The data detection unit is used to set a data template containing the four elements of an invoice, detect the collected invoice element information, and save the invoice element information that conforms to the invoice four-element template. The data verification unit is used to match the invoice element information of the data template that conforms to the four elements of the invoice with the invoice information that has been submitted, and save the successfully matched invoice element information and the submitted invoice information to form information to be processed.

8. The automated intelligent management system for electricity purchase fee settlement process according to claim 7, characterized in that, The data processing module also includes the following: If the collected invoice element information matches the data template of the four elements of the invoice, the corresponding matched invoice element information is moved to the archived data pool, and a movement record is generated. If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding unmatched invoice element information is moved to the data pool to be processed, and a movement record is generated.

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