Abnormal data display method and device, equipment, medium and product

Abstract

The invention discloses an abnormal data display method and device, equipment, a medium and a product. The method comprises the following steps: acquiring a plurality of power grid data tables; based on a plurality of splicing rules, splicing part of the power grid data tables in the plurality of power grid data tables to obtain a plurality of target tables; according to the exception detection rule corresponding to each target table, extracting exception data in each target table; generating an abnormal data display interface based on the abnormal data in each target table; the abnormal data display interface is displayed in the first area in the main interface, and the identification information of the abnormal data display interface is added to the menu list of the main interface, through the technical scheme, the abnormal data can be displayed, an inspector can directly check the abnormal data, and the inspection efficiency is improved. The checking time of inspectors is greatly shortened, and the inspection accuracy is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer technology, and in particular, to an abnormal data display method, device, equipment, medium and product. Background Art

[0002] Marketing audit is an important supervisory link and guarantee means for power marketing work. It undertakes the important functions of full-process supervision of the quality of marketing business work, handling complaints and reports, investigating and punishing illegal electricity use, cracking down on electricity theft and rectifying the order of the power market.

[0003] In the existing marketing system, marketing auditors need to manually check samples and extract abnormal data. The existing marketing audit method requires a lot of manpower costs and has problems such as low automation rate, low accuracy, and low efficiency. Summary of the invention

[0004] The embodiments of the present invention provide an abnormal data display method, device, equipment, medium and product, which can display abnormal data, and auditors can directly check the abnormal data, which greatly reduces the auditors' verification time and improves the accuracy of the audit.

[0005] According to one aspect of the present invention, there is provided a method for displaying abnormal data, comprising:

[0006] Get multiple power grid data tables;

[0007] splicing some of the plurality of power grid data tables based on a plurality of splicing rules to obtain a plurality of target tables;

[0008] According to the anomaly detection rules corresponding to each target table, extract the abnormal data in each target table;

[0009] Based on the abnormal data in each target table, generate an abnormal data display interface;

[0010] The abnormal data display interface is displayed in a first area of ​​the main interface, and identification information of the abnormal data display interface is added to a menu list of the main interface.

[0011] According to another aspect of the present invention, there is provided an abnormal data display device, the abnormal data display device comprising:

[0012] A data table acquisition module, used to acquire multiple power grid data tables;

[0013] A target table determination module, configured to splice some of the plurality of power grid data tables based on a plurality of splicing rules to obtain a plurality of target tables;

[0014] An abnormal data extraction module is used to extract abnormal data in each target table according to the abnormal detection rules corresponding to each target table;

[0015] An abnormal data display interface generation module, used for generating an abnormal data display interface based on the abnormal data in each target table;

[0016] The display module is used to display the abnormal data display interface in the first area of ​​the main interface, and add the identification information of the abnormal data display interface to the menu list of the main interface.

[0017] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the abnormal data display method described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the abnormal data display method described in any embodiment of the present invention when executed.

[0022] According to another aspect of the present invention, a computer program product is provided. When the computer program is executed by a processor, the computer program implements the abnormal data display method as described in any one of the embodiments of the present invention.

[0023] The embodiment of the present invention obtains multiple target tables by first splicing some power grid data tables in the multiple power grid data tables based on multiple splicing rules; then extracting abnormal data in each target table according to the abnormal detection rules corresponding to each target table; generating an abnormal data display interface based on the abnormal data in each target table; displaying the abnormal data display interface in the first area of ​​the main interface, and adding the identification information of the abnormal data display interface to the menu list of the main interface, so that the abnormal data can be displayed, and the auditors can directly check the abnormal data, which greatly reduces the verification time of the auditors and improves the accuracy of the audit.

[0024] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 is a flow chart of a method for displaying abnormal data in an embodiment of the present invention;

[0027] Figure 2 is a structural schematic diagram of an abnormal data display device in an embodiment of the present invention;

[0028] Figure 3 It is a structural schematic diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0032] Embodiment 1

[0033] Figure 1A flowchart of an abnormal data display method provided in an embodiment of the present invention. This embodiment is applicable to the case where abnormal data is displayed. The method can be executed by the abnormal data display device in the embodiment of the present invention. The device can be implemented in software and / or hardware. Figure 1 As shown, the method specifically comprises the following steps:

[0034] S110, obtaining multiple power grid data tables.

[0035] In this embodiment, the power grid data table can be a power grid marketing data table, and the multiple power grid data tables may include: metering point table, electricity user table, user-meter field relationship table, system organization table, electric energy meter asset table, operating electric energy meter, operating electric energy meter electricity meter, photovoltaic user related information table, business expansion work order basic information table, electric energy meter installation and disassembly record table, user-meter field relationship table, system organization table, voltage measurement point daily electricity data table, meter reading information table and photovoltaic user profile information table, etc.

[0036] S120, splicing some of the multiple power grid data tables based on multiple splicing rules to obtain multiple target tables.

[0037] In this embodiment, the splicing rules include: splicing the power grid data table whose table name includes any keyword in the first keyword set, splicing the power grid data table whose table name includes any keyword in the second keyword set, and splicing the power grid data table whose table name includes any keyword in the third keyword set.

[0038] In this embodiment, based on multiple splicing rules, some of the power grid data tables in the multiple power grid data tables are spliced ​​to obtain multiple target tables in a manner that: splicing the power grid data tables whose table names include any keyword in the first keyword set to obtain the first target table; splicing the power grid data tables whose table names include any keyword in the second keyword set to obtain the second target table; splicing the power grid data tables whose table names include any keyword in the third keyword set to obtain the third target table. Based on multiple splicing rules, some of the power grid data tables in the multiple power grid data tables are spliced ​​to obtain multiple target tables in a manner that: splicing some of the power grid data tables in the multiple power grid data tables through a connection query statement to obtain multiple target tables.

[0039] Optionally, based on multiple splicing rules, some of the multiple power grid data tables are spliced ​​to obtain multiple target tables, including:

[0040] The power grid data tables whose table names include any keyword in the first keyword set are concatenated to obtain a first target table.

[0041] In this embodiment, the first keyword set includes at least one of: metering point, electricity user, user-meter field relationship, system organization, energy meter asset, operating energy meter, operating energy meter power, and photovoltaic user related information.

[0042] In this embodiment, the grid data tables whose table names include any keyword in the first keyword set are spliced ​​to obtain the first target table in a manner as follows: based on the first splicing rule, the grid data tables whose table names include any keyword in the first keyword set are spliced ​​to obtain the first target table. The first splicing rule includes: the metering point table and the electricity user table are spliced ​​by user number; the user field relationship table is spliced ​​by metering point number; the system organization table is spliced ​​by power supply organization number; the running energy meter power is spliced ​​by energy identification and time condition; the photovoltaic user association information table is spliced ​​by user number and table asset number. It should be noted that the energy meter asset table and the running energy meter use subqueries and window functions to select the latest energy meter asset information. And the selected latest energy meter asset information is spliced ​​with the information in other tables.

[0043] In this embodiment, the metering point table and the electricity user table are spliced ​​by user number, that is, the rows with the same user number in the metering point table and the electricity user table are spliced ​​to obtain the spliced ​​table. Other splicing rules are similar and will not be repeated here.

[0044] The power grid data tables whose table names include any keyword in the second keyword set are concatenated to obtain a second target table.

[0045] In this embodiment, the second keyword set includes at least one of: basic information of business expansion work orders, installation and removal records of electric energy meters, household meter field relationships, system organization, daily electricity data of voltage measurement points, and meter reading information.

[0046] In this embodiment, the power grid data tables whose table names include any keyword in the second keyword set are spliced ​​to obtain the second target table in the following manner: based on the second splicing rule, the power grid data tables whose table names include any keyword in the second keyword set are spliced ​​to obtain the second target table. The second splicing rule includes: the basic information table of the business expansion work order and the electric energy meter installation and disassembly record table are spliced ​​by the work order number, the user field relationship table is spliced ​​by the asset number, the system organization table is spliced ​​by the power supply bureau code, and the voltage measurement point daily electricity data table is spliced ​​by a subquery. It should be noted that in this embodiment, multiple voltage measurement point daily electricity data tables are merged through subqueries, and the earliest data time of each meter is selected using a window function.

[0047] The power grid data tables whose table names include any keyword in the third keyword set are spliced ​​to obtain a third target table, wherein some keywords in the first keyword set, the second keyword set and the third keyword set are the same.

[0048] In this embodiment, the third keyword set includes at least one of photovoltaic user profile information, system organization, photovoltaic user related information, and power plant meter reading information.

[0049] In this embodiment, the grid data tables whose table names include any keyword in the third keyword set are spliced ​​to obtain the third target table in a manner as follows: the grid data tables whose table names include any keyword in the third keyword set are spliced ​​based on a third splicing rule to obtain the third target table. The third splicing rule includes: splicing the photovoltaic user profile information table and the system organization table by the power supply organization number, splicing the photovoltaic user profile information table and the photovoltaic user association information table by the user number, and splicing multiple power plant meter reading information tables by subquery.

[0050] S130, extracting abnormal data in each target table according to the abnormality detection rules corresponding to each target table.

[0051] In this embodiment, the abnormality detection rules corresponding to the first target table include: if the total reverse active power is greater than the first value, the corresponding power purchaser of the power user is empty, and the corresponding power purchaser of the meter identifier is not empty, then the data is determined to be abnormal; if the total reverse active power is greater than the second value, the corresponding power purchaser of the power user is empty, and the total reverse active power is greater than the total forward active power, then the data is determined to be abnormal. The abnormality detection rules corresponding to the second target table include: if the earliest data time of the metering system is earlier than the time of power connection and transmission, and the earliest forward active total meter code is greater than the third value, then the data is determined to be abnormal; if the monthly power generation of the photovoltaic power generation household is less than the online power generation, then the data is determined to be abnormal; if the annual power generation is greater than the annual preset power, then the data is determined to be abnormal.

[0052] In this embodiment, according to the anomaly detection rules corresponding to each target table, the method of extracting abnormal data in each target table can be: extracting data in each target table according to the key field set corresponding to each target table, obtaining a partial table of each target table, and performing anomaly detection on the data in the partial table of each target table according to the anomaly detection rules corresponding to each target table; extracting abnormal data in the partial table of each target table.

[0053] Optionally, according to the anomaly detection rules corresponding to each target table, the abnormal data in each target table is extracted, including:

[0054] The data in each target table is extracted according to the key field set corresponding to each target table to obtain a partial table of each target table.

[0055] In this embodiment, the key field set corresponding to the first target table includes: total forward active power, total reverse active power, electricity users corresponding to electricity buyers, and meter identifiers corresponding to electricity buyers; the key field set corresponding to the second target table includes: earliest data time of the metering system, power supply time, and total forward active power meter code; the key field set corresponding to the third target table includes: monthly power generation of photovoltaic power generators, online power generation, annual power generation, and contract capacity.

[0056] According to the anomaly detection rules corresponding to each target table, anomaly detection is performed on the data in part of each target table.

[0057] In this embodiment, according to the abnormality detection rules corresponding to each target table, the data in some tables of each target table are detected for abnormality, including: if the total reverse active power is greater than the first value, the corresponding power purchaser of the power user is empty, and the corresponding power purchaser of the meter identifier is not empty, then the data is determined to be abnormal; if the total reverse active power is greater than the second value, the corresponding power purchaser of the power user is empty, and the total reverse active power is greater than the total forward active power, then the data is determined to be abnormal. The abnormality detection rules corresponding to the second target table include: if the earliest data time of the metering system is earlier than the time of power connection and transmission, and the earliest forward active total meter code is greater than the third value, then the data is determined to be abnormal; if the monthly power generation of the photovoltaic power generation household is less than the online power, then the data is determined to be abnormal; if the annual power generation is greater than the annual preset power, then the data is determined to be abnormal.

[0058] Extract abnormal data from part of each target table.

[0059] In this embodiment, the method of extracting abnormal data in a part of each target table may be: obtaining data carrying an abnormal mark in each target table, wherein the abnormal mark includes: any one of a first mark, a second mark and a third mark.

[0060] Optionally, performing anomaly detection on data in some tables of the first target table according to anomaly detection rules corresponding to the first target table includes:

[0061] If the total reverse active power is greater than the first value, the electricity user corresponding to the electricity buyer is empty, and the electricity meter identifier corresponding to the electricity buyer is not empty, it is determined that the data is abnormal and a first mark is added.

[0062] In this embodiment, the first mark is: the reverse power quantity is not zero and is not associated with an electricity purchaser.

[0063] In this embodiment, the first value is a preset value, for example, the first value may be 0.

[0064] If the total reverse active power is greater than the second value, the corresponding power purchaser of the power user is empty, and the total reverse active power is greater than the total forward active power, the data is determined to be abnormal and a second mark is added.

[0065] In this embodiment, the second mark is: the reverse power quantity is not zero, the electric energy meter is faulty or the electric energy meter is incorrectly wired.

[0066] In this embodiment, the first value and the second value are different, and both the first value and the second value are preset values, for example, the second value may be 10.

[0067] Optionally, performing anomaly detection on data in a part of the second target table according to anomaly detection rules corresponding to the second target table includes:

[0068] If the earliest data time of the metering system is earlier than the time of power supply, and the earliest total forward active power meter code is greater than the third value, the data is determined to be abnormal and a third mark is added.

[0069] In this embodiment, the third mark is: the actual power consumption time is earlier than the power supply time, the earliest positive active total meter code is greater than 1, and the time logic is abnormal.

[0070] In this embodiment, the time logic abnormality may be extracorporeal circulation.

[0071] In this embodiment, the first value, the second value and the third value are different, and the first value, the second value and the third value are all preset values, for example, the third value may be 1.

[0072] Optionally, performing anomaly detection on data in some tables of the third target table according to anomaly detection rules corresponding to the third target table includes:

[0073] If the monthly power generation of the photovoltaic power generation household is less than the grid-connected power, the data is determined to be abnormal and a fourth mark is added.

[0074] In this embodiment, the fourth mark is: the monthly power generation of the photovoltaic power generation household is less than the grid-connected power, and the capacity is abnormal;

[0075] Determine the annual preset electricity quantity based on the contract capacity.

[0076] In this embodiment, the capacity abnormality may be unauthorized capacity increase.

[0077] In this embodiment, according to the contract capacity, the annual preset power quantity may be determined by: determining the annual preset power quantity based on the following formula:

[0078] Annual preset electricity consumption = contract capacity × 12 × 365.

[0079] If the annual power generation is greater than the annual preset power, the data is determined to be abnormal and a fifth mark is added, wherein the fifth mark is: the annual power generation is greater than the annual preset power and the capacity is abnormal.

[0080] S140: Generate an abnormal data display interface based on the abnormal data in each target table.

[0081] S150, displaying the abnormal data display interface in a first area of ​​the main interface, and adding identification information of the abnormal data display interface to a menu list of the main interface.

[0082] In an embodiment of the present invention, the Alpine Data tool is used to obtain the required power grid data table, and the big data analysis is performed according to the predetermined screening rules to obtain the abnormal data table, and then the cloud report tool is used to convert the abnormal data table into a cloud report, and then the dashboard tool is used to create the rule dashboard, and finally the rule dashboard is added to the main dashboard for display.

[0083] In a specific example, the abnormal data display process includes:

[0084] The first step is to use the dashboard tool to create the main dashboard of the marketing audit and monitoring application, which is the main interface. The main interface includes title text, LIST menu, and menu slide area.

[0085] The second step is to use SQL programming in the Alpine Data tool to obtain the required data table, and perform operations such as query, comparison, aggregation, and grouping according to the predetermined exception rules to obtain the exception data table.

[0086] 1. Rule metering management - the reverse power of public transformer users is not zero. Use the CREATE TABLE...AS SELECT statement to select and combine data from multiple tables to create a new table.

[0087] The following fields are extracted from each table: power supply bureau, power supply station, user number, user name, metering point number, meter identification, electricity consumption time, electricity user corresponding to electricity buyer, meter identification corresponding to electricity buyer, total forward active power, and total reverse active power.

[0088] Use CASE statements to detect anomalies: If the total reverse active power is greater than 0, the corresponding power purchaser of the power user is empty, and the corresponding power purchaser of the meter ID is not empty, then the data is determined to be abnormal and marked as "reverse power is not zero, suspected to be unassociated with the power purchaser";

[0089] If the total reverse active power is greater than 10, the corresponding power purchaser of the electricity user is empty, and the total reverse active power is greater than the total forward active power, the data is determined to be abnormal and marked as "the reverse power is not zero, suspected power meter failure / wrong wiring".

[0090] 2. Rules for business expansion application - the actual electricity consumption time is earlier than the time of connection. Use the CREATE TABLE...ASSELECT statement to select and combine data from multiple tables to create a new table.

[0091] Extract fields from each table, including power supply bureau, power supply station, work order number, acceptance time, user number, power supply time, meter identification, earliest data time of the metering system (from the daily electricity data table of the voltage measurement point), earliest forward active total meter code (from the daily electricity data table of the voltage measurement point) and earliest reverse active total meter code (from the daily electricity data table of the voltage measurement point).

[0092] Use CASE statements for anomaly detection: If the earliest data time of the metering system is earlier than the time of power connection and the earliest total positive active meter code is greater than 1, the data is determined to be abnormal. Add the "actual power consumption time is earlier than the time of power connection, the earliest total positive active meter code is greater than 1, suspected extracorporeal circulation" mark. It should be noted that extracorporeal circulation refers to the behavior of not working according to the business process and installing the meter on site before starting the order in the system. It is an abnormal process. The normal process is to start the order first and then install the meter.

[0093] 3. Regular distributed photovoltaic power generation - photovoltaic users increase capacity privately. Use the CREATE TABLE...AS SELECT statement to select and combine data from multiple tables to create a new table.

[0094] Extract fields such as power supply bureau, power supply station, PV power generation user number, PV project name, project address, contract capacity, installed capacity, intended consumption method, electricity consumption time (from the sub-query power plant meter reading information table), PV power generation user power generation, power generation in the past 12 months, power purchase user number, online power generation, and contract capacity from multiple tables.

[0095] Use CASE statements for anomaly detection: If the monthly power generation of a photovoltaic power generation household is less than the grid-connected power, it is marked as "the monthly power generation of the photovoltaic power generation household is less than the grid-connected power, suspected of unauthorized capacity increase"; if the annual power generation is greater than the maximum theoretical power (contract capacity × 12 × 365), it is marked as "the annual power generation is greater than the annual preset power, suspected of unauthorized capacity increase".

[0096] An abnormal data table is generated based on the abnormal data.

[0097] Step 3: Use the cloud reporting tool to convert the abnormal data table obtained in step 2 into an abnormal data cloud report. The abnormal data cloud report includes: adding field names, field data, filters, and export buttons.

[0098] Step 4: Use the dashboard tool to convert the abnormal data cloud report in step 3 into an abnormal data dashboard (that is, the abnormal data display interface). The abnormal data dashboard includes: report display area and filter display area.

[0099] Step 5. Add the abnormal data dashboard generated in step 4 to the menu slide area in the main dashboard in step 1, add the abnormal rule name in the LIST menu, and associate the abnormal rule name with the abnormal data dashboard.

[0100] The technical solution of this embodiment is to obtain multiple target tables by first splicing some of the power grid data tables in the multiple power grid data tables based on multiple splicing rules; then extracting abnormal data in each target table according to the abnormal detection rules corresponding to each target table; generating an abnormal data display interface based on the abnormal data in each target table; displaying the abnormal data display interface in the first area of ​​the main interface, and adding the identification information of the abnormal data display interface to the menu list of the main interface, so that the abnormal data can be displayed, and the auditors can directly check the abnormal data, which greatly reduces the verification time of the auditors and improves the accuracy of the audit.

[0101] Embodiment 2

[0102] Figure 2 This is a schematic diagram of the structure of an abnormal data display device provided by an embodiment of the present invention. This embodiment is applicable to situations where abnormal data is displayed. The device can be implemented in software and / or hardware. The device can be integrated in any device that provides abnormal data display function, such as Figure 2 As shown, the abnormal data display device specifically includes: a data table acquisition module 210, a target table determination module 220, an abnormal data extraction module 230, an abnormal data display interface generation module 240 and a display module 250.

[0103] Wherein, the data table acquisition module is used to acquire multiple power grid data tables;

[0104] A target table determination module, configured to splice some of the plurality of power grid data tables based on a plurality of splicing rules to obtain a plurality of target tables;

[0105] An abnormal data extraction module is used to extract abnormal data in each target table according to the abnormal detection rules corresponding to each target table;

[0106] An abnormal data display interface generation module, used for generating an abnormal data display interface based on the abnormal data in each target table;

[0107] The display module is used to display the abnormal data display interface in the first area of ​​the main interface, and add the identification information of the abnormal data display interface to the menu list of the main interface.

[0108] The above-mentioned product can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0109] The technical solution of this embodiment is to obtain multiple target tables by first splicing some of the power grid data tables in the multiple power grid data tables based on multiple splicing rules; then extracting abnormal data in each target table according to the abnormal detection rules corresponding to each target table; generating an abnormal data display interface based on the abnormal data in each target table; displaying the abnormal data display interface in the first area of ​​the main interface, and adding the identification information of the abnormal data display interface to the menu list of the main interface, so that the abnormal data can be displayed, and the auditors can directly check the abnormal data, which greatly reduces the verification time of the auditors and improves the accuracy of the audit.

[0110] Embodiment 3

[0111] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0112] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0113] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0114] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 performs the various methods and processes described above, such as the abnormal data display method.

[0115] In some embodiments, the abnormal data display method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the abnormal data display method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the abnormal data display method in any other appropriate manner (e.g., by means of firmware).

[0116] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0118] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0121] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0122] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0123] An embodiment of the present invention further provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the abnormal data display method according to any embodiment of the present invention is implemented.

[0124] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0125] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for displaying abnormal data, characterized in that: include: Get multiple power grid data tables; splicing some of the plurality of power grid data tables based on a plurality of splicing rules to obtain a plurality of target tables; According to the anomaly detection rules corresponding to each target table, extract the abnormal data in each target table; Based on the abnormal data in each target table, generate an abnormal data display interface; The abnormal data display interface is displayed in a first area of ​​the main interface, and identification information of the abnormal data display interface is added to a menu list of the main interface.

2. The method according to claim 1, characterized in that: Based on multiple splicing rules, some of the multiple power grid data tables are spliced ​​to obtain multiple target tables, including: splicing the power grid data tables whose table names include any keyword in the first keyword set to obtain a first target table; splicing the power grid data tables whose table names include any keyword in the second keyword set to obtain a second target table; The power grid data tables whose table names include any keyword in the third keyword set are spliced ​​to obtain a third target table, wherein some keywords in the first keyword set, the second keyword set and the third keyword set are the same.

3. The method according to claim 2, characterized in that According to the anomaly detection rules corresponding to each target table, the abnormal data in each target table is extracted, including: Extract the data in each target table according to the key field set corresponding to each target table, and obtain a partial table of each target table, wherein the key field set corresponding to the first target table includes: total forward active power, total reverse active power, electricity users corresponding to electricity buyers, and meter identifiers corresponding to electricity buyers; the key field set corresponding to the second target table includes: earliest data time of the metering system, time of power connection and power transmission, and total forward active power meter code; the key field set corresponding to the third target table includes: monthly power generation of photovoltaic power generation households, online power generation, annual power generation, and contract capacity; According to the anomaly detection rules corresponding to each target table, anomaly detection is performed on the data in some tables of each target table; Extract abnormal data from part of each target table.

4. The method according to claim 3, characterized in that According to the anomaly detection rule corresponding to the first target table, anomaly detection is performed on the data in some tables of the first target table, including: If the total reverse active power is greater than the first value, the power user corresponding to the power buyer is empty, and the meter identifier corresponding to the power buyer is not empty, then the data is determined to be abnormal, and a first mark is added, wherein the first mark is: the reverse power is not zero, and the power buyer is not associated; If the total reverse active power is greater than the second value, the corresponding power purchaser of the electricity user is empty, and the total reverse active power is greater than the total forward active power, the data is determined to be abnormal and a second mark is added, wherein the second mark is: the reverse power is not zero, the electric energy meter is faulty, or the electric energy meter is miswired.

5. The method according to claim 3, characterized in that: According to the anomaly detection rule corresponding to the second target table, anomaly detection is performed on the data in some tables of the second target table, including: If the earliest data time of the metering system is earlier than the time of power connection and power transmission, and the earliest total positive active power meter code is greater than the third value, the data is determined to be abnormal, and a third mark is added, wherein the third mark is: the actual power consumption time is earlier than the time of power connection and power transmission, the earliest total positive active power meter code is greater than 1, and the time logic is abnormal.

6. The method according to claim 3, characterized in that According to the anomaly detection rule corresponding to the third target table, anomaly detection is performed on the data in some tables of the third target table, including: If the monthly power generation of the photovoltaic power generation household is less than the grid-connected power, the data is determined to be abnormal, and a fourth mark is added, wherein the fourth mark is: the monthly power generation of the photovoltaic power generation household is less than the grid-connected power, and the capacity is abnormal; Determine the annual preset electricity quantity according to the contract capacity; If the annual power generation is greater than the annual preset power, the data is determined to be abnormal and a fifth mark is added, wherein the fifth mark is: the annual power generation is greater than the annual preset power and the capacity is abnormal.

7. An abnormal data display device, characterized in that: include: A data table acquisition module, used to acquire multiple power grid data tables; A target table determination module, configured to splice some of the plurality of power grid data tables based on a plurality of splicing rules to obtain a plurality of target tables; An abnormal data extraction module is used to extract abnormal data in each target table according to the abnormal detection rules corresponding to each target table; An abnormal data display interface generation module, used for generating an abnormal data display interface based on the abnormal data in each target table; The display module is used to display the abnormal data display interface in the first area of ​​the main interface, and add the identification information of the abnormal data display interface to the menu list of the main interface.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the abnormal data display method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the abnormal data display method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the abnormal data display method according to any one of claims 1 to 6 is implemented.

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