Automatic intelligent management method and system for electricity purchase charge settlement process

Abstract

The invention discloses an automatic intelligent management method for an electricity purchase charge settlement process, and the method comprises the steps: constructing a data template containing four elements of an invoice, and obtaining the full-amount invoice information of an invoice pool; obtaining invoice element information to be settled of the electricity purchase charge, and forming to-be-processed information; collecting a settlement notice to a financial management and control system, and marking the successful matching of the invoice element information and the settlement notice information as effective matching data; collecting effective matching data, generating a settlement bill and a voucher to be handled, and storing the effective matching data corresponding to the settlement bill to form first processing data; and screening and extracting an electricity purchase fee amount from a settlement bill and a to-be-handled voucher corresponding to the invoice element information and the settlement notification bill information, generating a payment application form, and storing effective matching data corresponding to the payment application form to form second processing data. According to the invention, efficient service processing of electricity fee settlement is realized, low-value repetitive work of financial staff is reduced, and automatic output of electricity fee purchase invoice information, settlement information, payment information and machine account information is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of power grid electricity fee settlement, and specifically relates to an automated intelligent management method and system for electricity purchase fee settlement process. Background Art

[0002] The electricity price management module is an important part of the financial control system. This module is based on the generator set and realizes the whole process of electricity purchase fee management, including electricity quantity collection, on-grid electricity price execution, electricity fee settlement and payment, and report preparation. It realizes detailed accounting, settlement, account processing, summary and statistical query of electricity purchase costs according to different time periods and different electricity prices of power plants / units. At present, the services that can be realized on the online side mainly include: input of electricity purchase objects, electricity fee estimation, electricity fee settlement notification, invoice ledger management, electricity fee settlement, electricity fee payment, report preparation, data query, etc.

[0003] With the construction of informatization, the efficiency of electricity purchase fee settlement processing in the existing system needs to be improved, and it is impossible to form a fully automatic processing mode. At the same time, due to manual participation, the error of manual review is increased, which affects the settlement results of electricity purchase fees. Therefore, it is necessary to develop automatic settlement of electricity purchase fees and dynamic monitoring of process information to promote the standardization and intelligence of business and financial work.

[0004] In order to adapt to the requirements of power system reform and internal management requirements of enterprises, it is urgently necessary to carry out the construction of 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 to grid-connected manufacturers, improve 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 the existing technology, it is urgent to design an automated intelligent management method and system for the electricity purchase fee settlement process to solve the above technical problems. Summary of the invention

[0006] In order to solve the above-mentioned deficiencies in the prior art, the purpose of the present invention is to overcome the existing deficiencies and provide an automated intelligent management method for the electricity purchase fee settlement process, the method comprising the following steps:

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

[0008] S2, obtaining the invoice element information of the electricity purchase fee to be settled, matching the invoice element information with the completed invoice information, and forming the information to be processed;

[0009] S3, collecting the settlement notice to the financial control system, matching the invoice element information with the settlement notice information, and marking the successful matching of the invoice element information with the settlement notice information as valid matching data;

[0010] S4, collecting the valid matching data, generating a settlement sheet and a pending voucher with invoice element information and settlement notice information corresponding to the valid matching data, and storing the valid matching data corresponding to the settlement sheet to form first processed data;

[0011] S5, based on the first processed data and the settlement sheet, the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information are screened and the electricity purchase fee amount is extracted to generate a payment application form, and the valid matching data corresponding to the payment application form is stored to form the second processed data.

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

[0013] Setting a data template containing the four elements of an invoice, testing the collected invoice element information, and saving the invoice element information that conforms to the invoice four-element template;

[0014] Match the saved invoice element information of the data template that meets the four elements of the invoice with the completed invoice information, and save the successfully matched invoice element information and the completed invoice information 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 of the collected invoice elements, calculate the correlation coefficient sim between the keyword and all the comparison selections of the text recognition library, and arrange the correlation coefficients sim1, sim2, ... sim s, sim t in descending order;

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

[0018] If there are at least 2 recorded inventory data in the first s items of inventory data calculated by the text recognition library, then there are similar units in the keyword to be detected; the corresponding graphics of the multiple similar units are equally divided into ω×ω square selection areas, and the correlation coefficients of all single square selection areas in the selection area are calculated to obtain the candidate items of the text recognition library for correctly describing the keyword as effective description parameters; weighted calculation is performed on the square selection areas of the effective description parameters, and weights are correspondingly assigned based on the numerical values ​​of the correlation coefficients to construct a weight matrix of the effective description parameters; and the maximum value of the weighted sum of the weights and the correlation coefficients is obtained as the keyword detection result;

[0019] If there is 1 recorded inventory data in the first s inventory data calculated by the text recognition library, then there is no similar unit for the keyword to be detected; set the coordination threshold λ, 1<λ≤t; based on the coordination threshold λ, the coordination units are marked, weights are assigned to the correlation coefficients of all coordination units, and a weight matrix of the coordination units is constructed; the maximum value of the weighted sum of the weight and the correlation coefficient is obtained as the collected invoice keyword detection result.

[0020] As a further optimization of the above solution, the method of obtaining the candidate items of the text recognition library for correctly describing the keyword as the effective description parameter specifically includes the following:

[0021] The threshold value of the correlation coefficient agreement of the marker judgment as an effective description parameter is q;

[0022] Traversalω 2 The correlation coefficient corresponding to the square constituencies, record the number of square constituencies with correlation coefficients less than q;

[0023] If the number of square constituencies is less than q and ω 2 If the ratio is not less than 0.6, the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is eliminated.

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

[0025] If the collected invoice element information successfully matches the data template of the four elements of the invoice, the corresponding successfully matched invoice element information is moved to the archived data pool to generate a move record;

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

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

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

[0029] The full amount of invoice information stored in the invoice pool is matched 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 move record.

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

[0031] Generate a corresponding settlement order based on the valid matching data of the full amount of invoice information stored in the invoice pool and the information to be processed;

[0032] Marking the generated valid matching data corresponding to the settlement form as the first processing data; moving the corresponding settlement form and the information to be processed to the archived data pool, and generating a moving record;

[0033] Generate pending vouchers based on the above settlement documents and complete the accounting operation.

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

[0035] Move the successfully matched payment application form and the first processed data to the archived data pool to generate a movement record;

[0036] Generate a power purchase bill settlement payment request based on the payment application form.

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

[0038] The invoice pool management module is used to 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 amount of invoice information in the invoice pool;

[0039] A data processing module is used to obtain 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;

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

[0041] A power purchase settlement module, used to collect the valid matching data, generate a settlement sheet and pending vouchers with invoice element information and settlement notice information corresponding to the valid matching data, and store the valid matching data corresponding to the settlement sheet to form first processed data;

[0042] The settlement and payment module is used to screen and extract the amount of electricity purchase fee from the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information based on the first processed data and the settlement sheet, generate a payment application sheet, and store the valid matching data corresponding to the payment application sheet to form the second processed data.

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

[0044] A data collection unit, used to collect invoice element information;

[0045] A data detection unit, used to set a data template containing 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 saved invoice element information of the data template that meets the four elements of the invoice with the completed invoice information, and save the successfully matched invoice element information and the completed invoice information to form information to be processed.

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

[0048] If the collected invoice element information successfully matches the data template of the four elements of the invoice, the corresponding successfully matched invoice element information is moved to the archived data pool to generate a move record;

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

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

[0051] Invoice pool, which is used to collect all invoices issued by power purchasing units to power grid companies and export them from the tax platform, and 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 pending information. If the match is successful, the corresponding pending information is marked as valid matching data, and the corresponding successfully matched pending information is moved to the archived data pool to generate a move record.

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

[0054] 1. The present invention constructs a data template containing four elements of invoices, matches the invoices in the invoice pool of the financial control system; obtains the invoice element information of the electricity purchase fee to be settled, and forms the information to be processed; collects the settlement notice to the financial control system; collects the effective matching data, generates the settlement slip and pending voucher corresponding to the invoice element information and the settlement notice information of the effective matching data, and stores the effective matching data corresponding to the settlement slip to form the first processing data; based on the first processing data and the settlement slip, the settlement slip and pending voucher corresponding to the invoice element information and the settlement notice information are screened and extracted to generate the payment application slip. According to the construction requirements of the electricity purchase fee settlement, the financial management electricity price management module realizes the automatic matching of invoices, automatic settlement and accounting, and automatic initiation of payment applications into the pool, realizes efficient business processing in all links of electricity fee settlement, and reduces the low-value repetitive work of financial personnel. By optimizing the system process, constructing the invoice pool, bill pool and electricity purchase fee management ledger, realizing the 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. The present invention monitors the electricity purchase fee settlement process in real time, intuitively displays the accounting status of electricity purchase fee costs, and promptly warns of abnormal matters; it automatically integrates information such as payables, actual payments, payment batches, payment methods, and payment status, and comprehensively displays the payment results of electricity purchase fees, thereby avoiding invoice audit and payment account problems caused by the failure to match the abnormal electricity purchase fee data information entered by the power grid company. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0058] Figure 2 Another schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0059] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0060] like Figure 1-2 As shown, the embodiment of the present invention discloses an automated intelligent management method for electricity purchase fee settlement process, including the following:

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

[0062] S2, obtaining the invoice element information of the electricity purchase fee to be settled, matching the invoice element information with the completed invoice information, and forming the information to be processed;

[0063] S3, collecting the settlement notice to the financial control system, matching the invoice element information with the settlement notice information, and marking the successful matching of the invoice element information with the settlement notice information as valid matching data;

[0064] S4, collecting the valid matching data, generating a settlement sheet and a pending voucher with invoice element information and settlement notice information corresponding to the valid matching data, and storing the valid matching data corresponding to the settlement sheet to form first processed data;

[0065] S5, based on the first processed data and the settlement sheet, the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information are screened and the electricity purchase fee amount is extracted to generate a payment application form, and the valid matching data corresponding to the payment application form is stored to form the second processed data.

[0066] The present invention realizes efficient business processing in all aspects of electricity bill settlement and reduces the low-value repetitive work of financial personnel. By optimizing the system process, building an invoice pool, a bill pool and an electricity purchase fee management ledger, the electricity purchase fee invoice information, settlement information, payment information, and ledger information are automatically output, and the settlement data is collected online in real time, which improves the lean management level of electricity purchase fees and meets internal management and external supervision requirements.

[0067] Specifically, the step S2 includes the following steps:

[0068] Setting a data template containing the four elements of an invoice, testing the collected invoice element information, and saving the invoice element information that conforms to the invoice four-element template;

[0069] Match the saved invoice element information of the data template that meets the four elements of the invoice with the completed invoice information, and save the successfully matched invoice element information and the completed invoice information 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 of the collected invoice elements, calculate the correlation coefficient sim between the keyword and all the comparison selections of the text recognition library, and arrange the correlation coefficients sim1, sim2, ... sim s, sim t in descending order;

[0072] Based on the calculated correlation coefficient sim, set the correlation threshold s, 1 < s ≤ t; In particular, the technology of the present invention performs feature comparison and matching on the keyword to be detected and the character recognition library, and provides a four-element detection and judgment standard for subsequent invoices by setting an association threshold. When the number of items that meet the association threshold is confirmed, 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 for the keyword to be detected; respectively divide the corresponding graphics of multiple said similar units into ω×ω square selection areas, calculate the correlation coefficients of all single 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] It should be particularly 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 of x t ; y t is the image feature of the existing data stored in the character recognition library, is the average of y t ;

[0077] For the convenience of calculation, the present invention divides the corresponding graphic into (2n - 1)×(2n - 1) square selection areas according to the keyword structure 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 for the keyword to be detected; set a coordination threshold λ, 1<λ≤t; based on the coordination threshold λ, the coordination units are marked, weights are assigned to the correlation coefficients of all coordination units, and a weight matrix of the coordination units is constructed; the maximum value of the weighted sum of the weight and the correlation coefficient is obtained as the collected invoice keyword detection result.

[0080] It should be noted that the method of assigning weights to the correlation coefficients of the effective description parameters, the coordination units and the keywords to be detected includes the following:

[0081]

[0082] Based on the above formula, the maximum value of the weighted sum of the weight and the correlation coefficient is set as Goal, then:

[0083]

[0084] Among them, t is the keyword to be detected.

[0085] Specifically, the method of obtaining the candidate items of the text recognition library for correctly describing the keyword as the effective description parameter specifically includes the following:

[0086] The threshold value of the correlation coefficient agreement of the marker judgment as an effective description parameter is q;

[0087] Traversalω 2 The correlation coefficient corresponding to the square constituencies, record the number of square constituencies with correlation coefficients less than q;

[0088] If the number of square constituencies is less than q and ω 2 If the ratio is not less than 0.6, the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is eliminated.

[0089] In the process of determining effective description parameters, the present invention further discloses a correlation coefficient agreement threshold, that is, after completing the equal-area segmentation of the candidate items in any text recognition library, the correlation coefficients corresponding to the square selection areas are calculated one by one, and the number of items that meet the correlation coefficient agreement threshold is counted, so as to further determine whether the similar unit can be used as an effective description parameter, eliminate a large number of interference items, and improve the detection accuracy of the characters to be detected in the four elements of the invoice.

[0090] More specifically, a data template containing the four elements of an invoice can be set up according to the target object. It can be designed to include basic information such as seller information, buyer information, transaction information, time information, etc., and further record information including transaction accounts, electricity consumption data, tax rates, etc., to facilitate the integrity verification of the invoice information.

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

[0092] If the collected invoice element information successfully matches the data template of the four elements of the invoice, the corresponding successfully matched invoice element information is moved to the archived data pool to generate a move record;

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

[0094] More specifically, the present invention further verifies the invoice information that matches the data template of the four elements of the invoice. In daily use, the data actually approved by the enterprise shall prevail as the final reference standard for verifying the invoice information data. If the invoice that successfully matches the data template of the four elements of the invoice is verified to be accurate with the actual approved data, the corresponding successfully matched invoice element information will be saved in the archived data pool; otherwise, it will be moved to the pending data pool.

[0095] The present invention monitors the electricity purchase fee settlement process in real time, intuitively displays the accounting status of electricity purchase fee costs, and promptly warns of abnormal matters; it automatically integrates information such as payables, actual payments, payment batches, payment methods, and payment status, and comprehensively displays the electricity purchase fee payment results, thereby avoiding invoice audit and payment account problems caused by the failure of the power grid company to match the input abnormal electricity purchase fee data information.

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

[0097] The settlement bill information is displayed according to the estimated and formal settlement tabs, and can be filtered and distinguished by electricity bill year and month for detailed viewing and export;

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

[0099] If automatic matching fails, a manual intervention interface is provided to manually match the 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 review service to conduct rule review;

[0101] It supports exporting pending settlement data and settled data, facilitating subsequent business operations such as reconciliation.

[0102] Specifically, step S3 includes the following:

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

[0104] More specifically, all the invoices mentioned in the present invention that are issued by power purchasing units to the power grid company mainly include special invoices, ordinary invoices, electronic invoices and other types. The technology of the present invention completes the connection between the enterprise and the tax platform, thereby continuously obtaining the electricity invoice information data of all power purchasing units issued to the power grid company, and all invoices used for power purchasing units to issue electricity consumption data records to the power grid company together constitute an invoice pool.

[0105] Specifically, the full amount of invoice information stored in the invoice pool is matched 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 move record.

[0106] Specifically, step S4 includes the following:

[0107] A settlement statement is generated according to valid matching data that successfully matches the full invoice information stored in the invoice pool with the information to be processed; the present invention fully realizes the automatic processing and entry of the settlement statement based on the automated process stored in the invoice pool, and saves the matching data corresponding to the settlement statement and the pending voucher in the settlement statement and marks it as the first processing data. It is particularly important to note 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 synchronously to avoid duplicate counting.

[0108] The valid matching data corresponding to the generated settlement sheet is marked as the first processing data; the corresponding settlement sheet and the pending information are moved to the archived data pool to generate a movement record; based on the above settlement sheet, a pending voucher is generated to complete the accounting operation.

[0109] More specifically, the present invention automatically generates pending vouchers based on settlement order information, calls voucher generation services, builds data models, calls voucher review services, generates settlement vouchers, and saves information such as voucher numbers; automatically supplements auxiliary accounting information such as the number of attached documents and subject dimensions, and automatically enters the information into the accounts.

[0110] More specifically, approval rules may be preset according to actual conditions, and the settlement form may be approved according to the approval rules, and the above approval process may be completed according to the preset approval rules.

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

[0112] Move the successfully matched payment application form and the first processed data to the archived data pool to generate a movement record;

[0113] Generate a power purchase bill settlement payment request based on the payment application form.

[0114] More specifically, an automatic electricity bill settlement and payment process can also be set up to replace the generation of an electricity bill settlement and payment request, enter the electricity bill payment application function; query the data to be paid, initiate a payment application; and provide feedback on the task processing status by email.

[0115] More specifically, the present invention automatically triggers a payment application based on the recorded cost voucher information and associates it with the cash flow budget to form a payment application form, which is specifically implemented as follows:

[0116] Provide the function of setting payment time and making payment on time;

[0117] Provides the function of setting payment methods, including transfer, bill of exchange, etc.;

[0118] Provides the function of setting payment ratio, and payment can be made in proportion;

[0119] Provides the function of setting payment batches, and can make payments in batches;

[0120] The payment application is automatically triggered and the settled records are pushed to generate payment documents.

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

[0122] The invoice pool management module is used to 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 amount of invoice information in the invoice pool;

[0123] A data processing module is used to obtain 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;

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

[0125] A power purchase settlement module, used to collect the valid matching data, generate a settlement sheet and pending vouchers with invoice element information and settlement notice information corresponding to the valid matching data, and store the valid matching data corresponding to the settlement sheet to form first processed data;

[0126] The settlement and payment module is used to screen and extract the amount of electricity purchase fee from the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information based on the first processed data and the settlement sheet, generate a payment application sheet, and store the valid matching data corresponding to the payment application sheet to form the second processed data.

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

[0128] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

Claims

1. An automated intelligent management method for electricity purchase fee settlement process, characterized in that: The method comprises the following: S1, construct a data template containing four elements of an invoice, match the invoices in the invoice pool of the financial control system, and obtain the full amount of invoice information in the invoice pool; S2, obtaining the invoice element information of the electricity purchase fee to be settled, matching the invoice element information with the completed invoice information, and forming the information to be processed; S3, collecting the settlement notice to the financial control system, matching the invoice element information with the settlement notice information, and marking the successful matching of the invoice element information with the settlement notice information as valid matching data; S4, collecting the valid matching data, generating a settlement sheet and pending voucher with invoice element information and settlement notice information corresponding to the valid matching data, and storing the valid matching data corresponding to the settlement sheet to form first processed data; S5, based on the first processed data and the settlement sheet, the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information are screened and the electricity purchase fee amount is extracted to generate a payment application form, and the valid matching data corresponding to the payment application form is stored to form the second processed data.

2. The method for automated intelligent management of electricity purchase fee settlement process according to claim 1, characterized in that: The step S2 specifically includes the following: Setting a data template containing the four elements of an invoice, testing the collected invoice element information, and saving the invoice element information that conforms to the invoice four-element template; Match the saved invoice element information of the data template that meets the four elements of the invoice with the completed invoice information, and save the successfully matched invoice element information and the completed invoice information to form information to be processed; The detection of the collected invoice element information includes the following: Based on any keyword to be detected of the collected invoice elements, calculate the correlation coefficient sim between the keyword and all the comparison selections of the text recognition library, and arrange the correlation coefficients sim1, sim2, ..., sims, simt in descending order; Based on the calculated correlation coefficient sim, set the correlation threshold s, 1 <s≤t; If there are at least 2 recorded inventory data in the first s items of inventory data calculated by the text recognition library, then there are similar units for the keyword to be detected; the corresponding graphics of the multiple similar units are equally divided into ω×ω square selection areas, and the correlation coefficients of all the single square selection areas in the selection areas are calculated to obtain the candidate items of the text recognition library for correctly describing the keyword as effective description parameters; weighted calculation is performed on the square selection areas of the effective description parameters, and weights are correspondingly assigned based on the numerical values ​​of the correlation coefficients 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; If the recorded inventory data is 1 in the first s items of inventory data calculated by the text recognition library, then there is no similar unit for the keyword to be detected; Set the coordination threshold λ, 1<λ≤t; based on the coordination threshold λ, the coordination units are marked, weights are assigned to the correlation coefficients of all coordination units, and a weight matrix of the coordination units is constructed; the maximum value of the weighted sum of the weight and the correlation coefficient is obtained as the collected invoice keyword detection result.

3. The method for automated intelligent management of electricity purchase fee settlement process according to claim 2, characterized in that: The method of obtaining the candidate items of the text recognition library for correctly describing the keyword as the effective description parameter specifically includes the following steps: The threshold value of the correlation coefficient agreement of the marker judgment as an effective description parameter is q; Traversalω 2 The correlation coefficient corresponding to the square constituencies, record the number of square constituencies with correlation coefficients less than q; If the number of square constituencies is less than q and ω 2 If the ratio is not less than 0.6, the corresponding similar unit is marked as a valid description parameter; otherwise, the corresponding similar unit is eliminated.

4. The method for automated intelligent management of electricity purchase fee settlement process according to claim 3, characterized in that: The step S2 also includes the following: If the collected invoice element information successfully matches the data template of the four elements of the invoice, the corresponding successfully matched invoice element information is moved to the archived data pool to generate a move record; If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding invoice element information that failed to match is moved to the data pool to be processed, and a move record is generated.

5. The method for automated intelligent management of electricity purchase fee settlement process according to claim 4, characterized in that: The step S3 specifically includes the following: Collect all invoices issued by power purchasing units to power grid companies exported by the tax platform, obtain full invoice information, and generate an invoice pool; The full amount of invoice information stored in the invoice pool is matched 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 move record.

6. The method for automated intelligent management of electricity purchase fee settlement process according to claim 5, characterized in that: The step S4 specifically includes the following: Generate a corresponding settlement order based on the valid matching data of the full amount of invoice information stored in the invoice pool and the information to be processed that successfully matches; Marking the generated valid matching data corresponding to the settlement form as first processed data; Move the corresponding settlement documents and pending information to the archived data pool and generate movement records; Generate pending vouchers based on the above settlement documents and complete the accounting operation.

7. The method for automated intelligent management of electricity purchase fee settlement process according to claim 6, characterized in that: The step S5 also includes the following: Move the successfully matched payment application form and the first processed data to the archived data pool to generate a movement record; Generate a power purchase order settlement payment request based on the payment application form.

8. An automated intelligent management system for electricity purchase fee settlement process, characterized in that: The system comprises the following: The invoice pool management module is used to 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 amount of invoice information in the invoice pool; A data processing module is used to obtain 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; An invoice processing module is used to collect settlement notices to the financial control system, match the invoice element information with the settlement notice information, and mark the successful match between the invoice element information and the settlement notice information as valid matching data; A power purchase settlement module, used to collect the valid matching data, generate a settlement sheet and pending vouchers with invoice element information and settlement notice information corresponding to the valid matching data, and store the valid matching data corresponding to the settlement sheet to form first processed data; The settlement and payment module is used to screen and extract the amount of electricity purchase fee from the settlement sheet and pending vouchers corresponding to the invoice element information and the settlement notice information based on the first processed data and the settlement sheet, generate a payment application sheet, and store the valid matching data corresponding to the payment application sheet to form the second processed data.

9. The automated intelligent management system for electricity purchase fee settlement process according to claim 8, characterized in that: The data processing module includes the following: A data collection unit, used to collect invoice element information; A data detection unit, used to set a data template containing 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 saved invoice element information of the data template that meets the four elements of the invoice with the completed invoice information, and save the successfully matched invoice element information and the completed invoice information to form information to be processed.

10. The automated intelligent management system for electricity purchase fee settlement process according to claim 9, characterized in that: The data processing module also includes the following: If the collected invoice element information successfully matches the data template of the four elements of the invoice, the corresponding successfully matched invoice element information is moved to the archived data pool to generate a move record; If the collected invoice element information fails to match the data template of the four elements of the invoice, the corresponding invoice element information that failed to match is moved to the data pool to be processed, and a move record is generated.

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