Electric power marketing error beforehand early warning method and system

Abstract

The invention discloses an electric power marketing error beforehand early warning method, which comprises the steps of collecting electric power data, performing consistency verification on the data based on a block chain technology, and verifying the legality of the data through a consensus mechanism; the verified data is integrated through a multi-source data fusion technology, the data from the system is converted into a unified format by using a data fusion algorithm and is integrated, the fused data is analyzed by using an anomaly detection algorithm, and potential power marketing errors are identified; predicting electric charge errors based on user behavior analysis, and establishing a power error prediction model by analyzing historical power consumption behavior data of the user; and applying an intelligent early warning mechanism for the low-power users, and outputting power marketing error early warning information. According to the method, early warning can be carried out on marketing errors and abnormities in advance, advanced pre-control of marketing business risks is realized, and the marketing business risks are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power forecasting, and in particular to a method and system for early warning of power marketing errors. Background Art

[0002] At present, marketing audits are all "post-audits", which are a model of discovering problems after the fact. In recent years, external supervision requirements have become increasingly higher: the country attaches great importance to the comprehensive supervision of power companies and the construction of an optimized business environment. External supervision requirements are becoming increasingly higher, and the pressure on marketing risk prevention and control is gradually increasing. The National Energy Administration and the Yunnan Energy Supervision Office have also conducted inspections on the company to optimize the business environment many times, and the inspection methods and forms are becoming more and more diverse. The construction of the company's internal control system is becoming more and more standardized: the internal control requirements and efforts of inspections, audits, and comprehensive audits of the Southern Power Grid Company are constantly increasing. Many problems in the marketing field are found in each inspection, involving a large number of problems and a large amount of money. Compliance management requirements are becoming increasingly higher: with the official issuance of the power grid company's disciplinary list, which involves a total of 23 clauses in the marketing field, the Southern Power Grid Company and the Yunnan Power Grid Company will further increase the enforcement of disciplinary and assessment measures for marketing errors.

[0003] The above problems have continuously forced the marketing audit work to change from "after-the-fact" problem investigation to "before-the-fact and during-the-fact" risk prevention. The ability to find problems needs to be further improved, which also urges the auditors to transform into "all-round" positions that integrate multiple marketing disciplines. It is necessary to further strengthen the company's marketing business norms, prevent and control marketing risks "before-the-fact and during-the-fact", and reduce marketing "after-the-fact" errors. In order to truly prevent and control marketing business risks, it is necessary to carry out pre- and in-the-fact management and control of marketing business. Audits must intervene in business management and control in advance to discover signs of business problems in advance, so as to achieve the effect of the guarantee system and the supervision system working in the same direction and truly prevent marketing business risks. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for pre-warning of power marketing errors, which improves the ability of auditors to discover problems, solves the current working mode in which auditors basically discover problems after the fact, and can give early warning of marketing errors and anomalies, realize pre-control of marketing business risks, reduce marketing business risks, and realize the comprehensive construction of a marketing business error control system of "inspection, correction, supervision, and prevention" and the realization of a three-in-one marketing business full-process audit and control mode of "before, during, and after".

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions, a method for early warning of power marketing errors, comprising:

[0007] Collect electricity users' electricity bill accounting data, user profile data, equipment status data, and electricity price data, verify the consistency of the data based on blockchain technology, store the electricity marketing data in a distributed ledger, and verify the legitimacy of the data through a consensus mechanism;

[0008] Integrate verified data through multi-source data fusion technology, use data fusion algorithms to convert data from systems into a unified format and integrate them, and use anomaly detection algorithms to analyze the fused data to identify potential power marketing errors;

[0009] Predict electricity bill errors based on user behavior analysis, and establish a power error prediction model by analyzing users' historical electricity consumption behavior data;

[0010] An intelligent early warning mechanism is applied to low-power users to further detect the possibility of electricity bill errors, set early warning thresholds and detect electricity bill errors based on abnormal fluctuations, and output power marketing error early warning information.

[0011] As a preferred solution of the method for pre-warning of power marketing errors described in the present invention, the anomaly detection algorithm includes a detection algorithm based on K-means clustering algorithm, anomaly distribution analysis and rule-based detection algorithm.

[0012] As a preferred solution of the method for advance warning of power marketing errors described in the present invention, the identification of potential power marketing errors includes, when potential errors are detected, correcting abnormal data through an automatic correction mechanism, correcting abnormal table codes, user file data or electricity fee calculation data according to preset correction rules, and generating a correction log.

[0013] As a preferred solution of the method for advance warning of power marketing errors described in the present invention, the intelligent warning mechanism includes automatically identifying and correcting problems such as inconsistent table codes, incorrect file data or abnormal power consumption in electricity fee calculations based on rules in a correction rule base, and generating a log to record the correction operation after correction.

[0014] As a preferred solution of the method for advance warning of power marketing errors described in the present invention, the establishment of a power error prediction model includes using a machine learning algorithm to establish a classification model by training historical power consumption data, identifying pattern deviations in the user's power consumption time series, and predicting potential errors based on the deviations.

[0015] As a preferred scheme of the method for advance warning of power marketing errors described in the present invention, wherein: the intelligent warning mechanism applied to low-power users includes, the intelligent warning mechanism for low-power users includes setting a special anomaly detection threshold based on the power consumption behavior characteristics of low-power users, and judging possible electricity bill errors by analyzing the fluctuations of their power consumption data within the preset threshold range.

[0016] As a preferred solution of the method for advance warning of power marketing errors described in the present invention, the power marketing error warning information includes outputting data after error detection, correction, behavior analysis and intelligent warning to the warning module, marking potential error data and outputting a warning signal, and generating warning information related to the potential error data.

[0017] As a preferred solution of the power marketing error advance warning system of the present invention, it includes: a data collection module, a deep warning analysis module, a message notification module and a data monitoring module;

[0018] The data collection module collects the process data required for various electricity fee analysis and work order analysis, which is used to verify the problems in the electricity fee calculation process and the business expansion work order process in the future;

[0019] The in-depth early warning analysis module is used to formulate early warning analysis rules and verify the data of the electricity fee calculation process;

[0020] The message notification module is used to notify the relevant personnel of the detection and analysis results formed in the deep warning analysis module in a timely manner to handle and close the loop of the problem;

[0021] The data monitoring module is used to monitor the data collection module, deep warning analysis module, message notification module, and problem handling module in real time.

[0022] A computer device includes a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of a method for pre-warning of power marketing errors when executing the computer program.

[0023] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a method for pre-warning of power marketing errors are implemented.

[0024] Beneficial effects of the invention: Through real-time data monitoring and analysis, the early warning system of this patent can quickly identify potential power marketing errors. This timeliness enables managers to take corrective measures before the problem expands, significantly reducing the cost and complexity of subsequent processing.

[0025] The present invention effectively reduces the occurrence of marketing errors through risk prevention and control measures before and during the event. This advantage not only improves the accuracy of marketing activities, but also improves customer satisfaction and enhances the company's market competitiveness.

[0026] As power companies increase their internal control requirements, the system provided by this patent can monitor and assess risks in real time, introduce a pre-warning mechanism, and gradually shift to focusing on risk prevention and control and compliance management, helping the power industry to better meet compliance requirements, enhance the effectiveness of internal control, and reduce financial losses and legal risks caused by errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0028] Figure 1 A schematic flow chart of a method for early warning of power marketing errors provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0030] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0031] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0032] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0033] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0034] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a method for early warning of power marketing errors, comprising:

[0036] S1: Collect electricity users’ electricity bill accounting data, user profile data, equipment status data, and electricity price data, verify the consistency of the data based on blockchain technology, store the electricity marketing data in a distributed ledger, and verify the legitimacy of the data through a consensus mechanism.

[0037] S2: Integrate verified data through multi-source data fusion technology, use data fusion algorithms to convert data from the system into a unified format and integrate them, and use anomaly detection algorithms to analyze the fused data to identify potential power marketing errors.

[0038] S3: Predict electricity bill errors based on user behavior analysis, and establish a power error prediction model by analyzing users' historical electricity consumption behavior data.

[0039] S4: Apply intelligent early warning mechanism for low-power users to further detect the possibility of electricity bill errors, set early warning thresholds and detect electricity bill errors based on abnormal fluctuations, and output power marketing error early warning information.

[0040] The anomaly detection algorithms include those based on K-means clustering algorithm, anomaly distribution analysis and rule-based detection algorithms.

[0041] The identifying of potential power marketing errors includes, when a potential error is detected, correcting abnormal data through an automatic correction mechanism, correcting abnormal table codes, user profile data or electricity fee calculation data according to preset correction rules, and generating a correction log.

[0042] The intelligent early warning mechanism includes automatically identifying and correcting problems such as inconsistent meter codes, incorrect file data or abnormal power consumption in electricity fee calculation based on rules in a correction rule base, and generating a log to record the correction operation after correction.

[0043] The establishment of the power error prediction model includes using a machine learning algorithm to establish a classification model by training historical power consumption data, identifying pattern deviations in the user's power consumption time series, and predicting potential errors based on the deviations.

[0044] The intelligent early warning mechanism for low-power users includes setting a special abnormality detection threshold based on the power consumption behavior characteristics of low-power users, and judging possible electricity bill errors by analyzing the fluctuation of their power consumption data within a preset threshold range.

[0045] The power marketing error warning information includes outputting data after error detection, correction, behavior analysis and intelligent warning to the warning module, marking potential error data and outputting a warning signal, and generating warning information related to the potential error data.

[0046] Embodiment 2 is an embodiment of the present invention, which provides an advance warning system for power marketing errors.

[0047] The system includes a data collection module, a deep warning analysis module, a message notification module and a data monitoring module;

[0048] The data collection module collects the process data required for various electricity fee analysis and work order analysis, which is used to verify the problems in the electricity fee calculation process and the business expansion work order process in the future;

[0049] The in-depth early warning analysis module is used to formulate early warning analysis rules and verify the data of the electricity fee calculation process;

[0050] The message notification module is used to notify the relevant personnel of the detection and analysis results formed in the deep warning analysis module in a timely manner to handle and close the loop of the problem;

[0051] The data monitoring module is used to monitor the data collection module, deep warning analysis module, message notification module, and problem handling module in real time.

[0052] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0053] Example 3

[0054] The third embodiment of the present invention is different from the first two embodiments in that:

[0055] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0056] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0057] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0058] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0059] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0060] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for early warning of power marketing errors, characterized by: include, Collect electricity users' electricity bill accounting data, user profile data, equipment status data, and electricity price data, verify the consistency of the data based on blockchain technology, store the electricity marketing data in a distributed ledger, and verify the legitimacy of the data through a consensus mechanism; Integrate verified data through multi-source data fusion technology, use data fusion algorithms to convert data from systems into a unified format and integrate them, and use anomaly detection algorithms to analyze the fused data to identify potential power marketing errors; Predict electricity bill errors based on user behavior analysis, and establish a power error prediction model by analyzing users' historical electricity consumption behavior data; An intelligent early warning mechanism is applied to low-power users to further detect the possibility of electricity bill errors, set early warning thresholds and detect electricity bill errors based on abnormal fluctuations, and output power marketing error early warning information.

2. The method for early warning of power marketing errors according to claim 1, characterized in that: The anomaly detection algorithms include those based on K-means clustering algorithm, anomaly distribution analysis and rule-based detection algorithms.

3. A method for early warning of power marketing errors according to claim 2, characterized in that: The identifying of potential power marketing errors includes, when a potential error is detected, correcting abnormal data through an automatic correction mechanism, correcting abnormal table codes, user profile data or electricity fee calculation data according to preset correction rules, and generating a correction log.

4. The method for early warning of power marketing errors according to claim 3, characterized in that: The intelligent early warning mechanism includes automatically identifying and correcting problems such as inconsistent meter codes, incorrect file data or abnormal power consumption in electricity fee calculation based on rules in a correction rule base, and generating a log to record the correction operation after correction.

5. The method for early warning of power marketing errors according to claim 4, characterized in that: The establishment of the power error prediction model includes using a machine learning algorithm to establish a classification model by training historical power consumption data, identifying pattern deviations in the user's power consumption time series, and predicting potential errors based on the deviations.

6. A method for early warning of power marketing errors according to claim 5, characterized in that: The intelligent early warning mechanism for low-power users includes setting a special abnormality detection threshold based on the power consumption behavior characteristics of low-power users, and judging possible electricity bill errors by analyzing the fluctuation of their power consumption data within a preset threshold range.

7. A method for early warning of power marketing errors according to claim 6, characterized in that: The power marketing error warning information includes outputting data after error detection, correction, behavior analysis and intelligent warning to the warning module, marking potential error data and outputting a warning signal, and generating warning information related to the potential error data.

8. A system using a power marketing error advance warning method as claimed in any one of claims 1 to 7, characterized in that: Including data collection module, in-depth warning analysis module, message notification module and data monitoring module; The data collection module collects the process data required for various electricity fee analysis and work order analysis, which is used to verify the problems in the electricity fee calculation process and the business expansion work order process in the future; The in-depth early warning analysis module is used to formulate early warning analysis rules and verify the data of the electricity fee calculation process; The message notification module is used to notify the relevant personnel of the detection and analysis results formed in the deep warning analysis module in a timely manner to handle and close the loop of the problem; The data monitoring module is used to monitor the data collection module, deep warning analysis module, message notification module, and problem handling module in real time.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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