Configurable power trading risk monitoring method, device and computer equipment

Abstract

The present application relates to a configurable power trading risk monitoring method, device and computer equipment. The method includes: obtaining power trading business data; the power trading business data includes at least one of power management data, power trading data and metering and settlement data; classifying the power trading business data, determining at least one type of target business data, and generating abnormal monitoring indicators for the target business data; in the abnormal monitoring item, setting the abnormal monitoring indicator to be monitored as an indicator variable, and determining an expression containing the indicator variable; the expression is used to represent the abnormal monitoring logic; parsing the expression, traversing the monitoring subjects in the abnormal monitoring indicator, and obtaining the monitoring results of the abnormal monitoring item; the monitoring results include the target monitoring subject with abnormalities. The use of this method can improve the abnormality detection efficiency of the monitoring subject.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a configurable electric power trading risk monitoring method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the continuous deepening of power reform, the continuous advancement of the construction of power spot markets, and the continuous expansion of the market scope, new demands have been put forward for risk control in the power trading process. With the iteration of trading rules and trading models, the underlying structure and data content of key business data will undergo great changes, and more and more business items will be related. The risk points in the transaction process will also continue to change and increase. Traditional technologies still have the problem of low efficiency in detecting anomalies of the monitoring subject. Summary of the invention

[0003] Based on this, it is necessary to provide a configurable power trading risk monitoring method, device, computer equipment, computer-readable storage medium and computer program product that can improve the abnormality detection efficiency of the monitoring subject in response to the above technical problems.

[0004] In a first aspect, the present application provides a configurable power trading risk monitoring method, the method comprising:

[0005] Acquiring power transaction business data; the power transaction business data includes at least one of power management data, power transaction data and metering and settlement data;

[0006] Classifying the power trading business data, determining at least one type of target business data, and generating an abnormal monitoring indicator for the target business data;

[0007] In the abnormal monitoring item, the abnormal monitoring indicator to be monitored is set as an indicator variable, and an expression containing the indicator variable is determined; the expression is used to represent the abnormal monitoring logic;

[0008] The expression is parsed, the monitoring subjects in the abnormal monitoring indicator are traversed, and the monitoring result of the abnormal monitoring item is obtained; the monitoring result includes the target monitoring subject with abnormality.

[0009] In one embodiment, parsing the expression, traversing the monitoring subjects in the abnormal monitoring indicator, and obtaining the monitoring result of the abnormal monitoring item includes:

[0010] Extracting data from the abnormal monitoring index corresponding to the index variable, assigning values ​​to the variables in the expression, and converting the general expression containing the index variable into a program-readable logical expression;

[0011] Verify the correctness of the expression after assignment to ensure that the expression complies with grammatical rules;

[0012] Calculating the function in the expression to generate a mathematical expression;

[0013] Performing reverse Polish notation on the mathematical expression, and judging whether the monitored subject has an abnormality according to the calculation result;

[0014] The monitoring data of the next monitoring subject is brought into the indicator variable, and the above steps are repeated.

[0015] In one of the embodiments, the power management data includes at least one of enterprise registration data, market status data, margin data, transaction service fee data, retail relationship data, digital certificate information, and registration process data;

[0016] and / or,

[0017] The power transaction data includes at least one of transaction contract data, transaction product data, transaction market data, market transaction data, power generation capacity data, transaction volume and price data, retail relationship data and transaction statistics data;

[0018] and / or,

[0019] The metering settlement data includes at least one of retail user settlement data, wholesale user settlement data, power plant settlement data, power sales company settlement data, revenue settlement data and historical electricity data.

[0020] In one embodiment, the classifying the power trading business data, determining at least one type of target business data, and generating an abnormal monitoring indicator for the target business data includes:

[0021] Obtaining a basis for data classification; the basis for data classification includes at least one of an indicator dimension type, an indicator data type, and an indicator statistical frequency;

[0022] According to the data classification basis, determining at least one type of target business data in the power trading business data;

[0023] Generate an indicator for the target business data to obtain the abnormal monitoring indicator.

[0024] In one embodiment, the method further comprises:

[0025] Sending the monitoring result of the abnormal monitoring item to a user terminal; the user terminal is used to prompt the user that the target monitoring subject has an abnormality; the user terminal is also used to receive the abnormal handling result for the target monitoring subject;

[0026] Receive the exception handling result returned by the user terminal.

[0027] In one embodiment, the method further comprises:

[0028] Performing statistical processing on the abnormal handling results to obtain statistical handling results;

[0029] The processing results after the statistics are displayed.

[0030] In a second aspect, the present application also provides a configurable power trading risk monitoring device, the device comprising:

[0031] An acquisition module, used to acquire power transaction business data; the power transaction business data includes at least one of power management data, power transaction data and metering and settlement data;

[0032] A classification module, used to classify the power trading business data, determine at least one type of target business data, and generate an abnormal monitoring indicator for the target business data;

[0033] A determination module, used to set the abnormal monitoring indicator to be monitored as an indicator variable in the abnormal monitoring item, and determine an expression containing the indicator variable; the expression is used to represent the abnormal monitoring logic;

[0034] The traversal module is used to parse the expression, traverse the monitoring subjects in the abnormal monitoring indicator, and obtain the monitoring results of the abnormal monitoring items; the monitoring results include the target monitoring subjects with abnormalities.

[0035] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0037] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0038] The above-mentioned configurable power trading risk monitoring method, device, computer equipment, storage medium and computer program product, by extracting and organizing abnormal monitoring indicators based on the information summary of each module of the power trading center, and judging and preventing and controlling abnormalities through general analytical expressions, can flexibly modify the judgment logic of existing monitoring items, and quickly capture and monitor newly discovered abnormalities. It is highly targeted and practical, filling the gap in the special business of configurable power trading abnormality monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is an application environment diagram of a configurable power transaction risk monitoring method in an embodiment;

[0040] Figure 2 A schematic diagram of a flow chart of a configurable power transaction risk monitoring method in an embodiment;

[0041] Figure 3 is a flow chart of a configurable power transaction risk monitoring method in another embodiment;

[0042] Figure 4 is a structural block diagram of a configurable power transaction risk monitoring device in one embodiment;

[0043] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] The configurable power transaction risk monitoring method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 obtains power trading business data from the server 104; the power trading business data includes at least one of power management data, power trading data and metering and settlement data; the terminal 102 classifies the power trading business data, determines at least one type of target business data, and generates an abnormal monitoring indicator for the target business data; the terminal 102 sets the abnormal monitoring indicator to be monitored as an indicator variable in the abnormal monitoring item, and determines an expression containing the indicator variable; the expression is used to represent the abnormal monitoring logic; the terminal 102 parses the expression, traverses the monitoring subject in the abnormal monitoring indicator, and obtains the monitoring result of the abnormal monitoring item; the monitoring result includes the target monitoring subject with abnormality. Among them, the terminal 102 can be but not limited to various personal computers, laptops, smart phones, and tablet computers. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0046] In one embodiment, Figure 2 As shown in FIG, a configurable power transaction risk monitoring method is provided, which is applied to Figure 1 The computer device in the example is used to illustrate, including the following steps:

[0047] Step S210, obtaining power trading business data.

[0048] In a specific implementation, the terminal obtains power trading business data from the server where the power trading center is located.

[0049] Among them, the power trading business data may include at least one of power management data, power trading data and metering and settlement data.

[0050] Among them, the power management data may include at least one of enterprise registration data, market status data, deposit data, transaction service fee data, retail relationship data, digital certificate information and registration process data.

[0051] Among them, electricity trading data may include at least one of transaction contract data, transaction product data, transaction market data, market transaction data, power generation capacity data, transaction volume and price data, retail relationship data and transaction statistical data.

[0052] Among them, the metering settlement data may include at least one of retail user settlement data, wholesale user settlement data, power plant settlement data, power sales company settlement data, revenue settlement data and historical electricity data.

[0053] Step S220, classify the power trading business data, determine at least one type of target business data, and generate abnormal monitoring indicators for the target business data.

[0054] In a specific implementation, after the terminal obtains the power trading business data, the terminal can classify the power trading business data, determine at least one type of target business data, and generate abnormal monitoring indicators for the target business data.

[0055] Step S230: In the abnormal monitoring item, the abnormal monitoring indicator to be monitored is set as an indicator variable, and an expression including the indicator variable is determined.

[0056] Among them, the expression is used to represent the abnormal monitoring logic.

[0057] In a specific implementation, the terminal sets the abnormal monitoring indicator to be monitored as an indicator variable in the abnormal monitoring item, and determines an expression containing the indicator variable. The terminal sets the abnormal monitoring indicator to be monitored as an indicator variable including:

[0058] Indicator variables are the redefinition of indicator data within a certain time range. Variables are divided into main variables and common variables. You need to select the main variable first. The main variable constrains the indicator dimension and indicator frequency of the common variable.

[0059] The indicator variable is a structured risk monitoring element organization system. The indicator variable definition includes the following elements:

[0060] A. The name of the monitoring variable, used to represent this variable in the logical expression;

[0061] B. Data source of monitoring indicators and variable values;

[0062] C. Time offset: users locate the range of monitoring indicators based on time.

[0063] The time offset is set based on the indicator frequency. For example, if the variable corresponds to daily data, the time offset is represented by "D±x", where "D" represents daily data (Day), "+" represents a future offset to the current time, "-" represents a past offset to the current time, and "x" is a number representing the specific number of days of the offset. For example, if the time offset is set to "D-2", it means that the variable takes the data of the corresponding indicator two days ago.

[0064] The terminal determines that the expression containing the indicator variable specifically includes:

[0065] By mathematically analyzing the abnormal monitoring logic, it is possible to perform arithmetic operations such as addition, subtraction, multiplication, division, and remainder, logical operators such as AND, OR, and NOT, as well as the "?:" ternary operation, and handle the priority of brackets.

[0066] Monitoring expressions can perform addition, subtraction, multiplication, division, remainder and other complex mathematical operations on numerical data, character data processing operations such as character interception, character comparison, and character inclusion on string data, and time judgment operations such as time equality and time difference on time data. Boolean data can also be directly added to supplement the monitoring expression; the results of the monitoring logic expression are "TRUE" and "FALSE", and it is used to judge whether the monitoring subject has an abnormality. In practical applications, the above anomalies can also be named risks.

[0067] Step S240, parse the expression, traverse the monitoring subjects in the abnormal monitoring indicator, and obtain the monitoring results of the abnormal monitoring items; the monitoring results include the target monitoring subjects with abnormalities.

[0068] In a specific implementation, the terminal parses the expression, traverses the monitoring subjects in the abnormal monitoring index, and obtains the monitoring results of the abnormal monitoring items. The monitoring results include the target monitoring subjects with abnormalities.

[0069] In the above-mentioned configurable power trading risk monitoring method, by extracting and organizing abnormal monitoring indicators based on the information summary of each module of the power trading center, and judging and preventing anomalies through general analytical expressions, the judgment logic of existing monitoring items can be flexibly modified, and newly discovered anomalies can be quickly captured and monitored. It is highly targeted and practical, filling the gap in the special business of configurable power trading anomaly monitoring.

[0070] In another embodiment, an expression is parsed, and monitoring subjects in the abnormal monitoring indicator are traversed to obtain monitoring results of the abnormal monitoring items, including: taking numbers from the abnormal monitoring indicators corresponding to the indicator variables, assigning values ​​to the variables in the expression, and converting the general expression containing the indicator variables into a program-readable logical expression; verifying the correctness of the expression after assignment to ensure that the expression complies with grammatical rules; calculating the function in the expression to generate a mathematical expression; performing reverse Polish notation on the mathematical expression, and judging whether there is an abnormality in the monitoring subject based on the calculation result; bringing the monitoring data of the next monitoring subject into the indicator variable, and repeating the above steps.

[0071] In the specific implementation, the terminal can obtain data from the abnormal monitoring indicator corresponding to the indicator variable, and then the terminal can assign values ​​to the variables in the expression, and the terminal can convert the general expression containing the indicator variable into a program-readable logical expression; then, the terminal can verify the correctness of the expression after assignment to ensure that the expression complies with the grammatical rules; then, the terminal can calculate the function in the expression to generate a mathematical expression; then, the terminal can perform reverse Polish notation on the mathematical expression, and determine whether there is an abnormality in the monitored subject based on the calculation result; finally, the terminal can bring the monitoring data of the next monitored subject into the indicator variable and repeat the above steps.

[0072] Specifically, the grammar rules include:

[0073] The string constant in the expression needs to be written in double quotes """", and the time constant needs to be written in brackets "[]";

[0074] The function in the expression must start with a "$" sign, and the type and number of function parameters must be the same as the function definition;

[0075] The expression should ultimately obtain a Boolean operation result through operations such as logical AND ("&&"), logical OR ("||"), logical NOT ("!"), and logical comparison operations (">>=<<===!="), which is used to determine whether there is a risk in the monitored subject.

[0076] The functions in the expression are as follows: the symbol "$" in the expression indicates that a function needs to be referenced; the function type is indicated by English or Chinese keywords; the function parameters are indicated in "()", and if there are multiple parameters, they are separated by "," commas. Function parameters can be specific numbers, characters, time, or variables. For example, "$MoM(curm,lastm)", where "$MoM" represents the month-on-month growth rate calculation function, "curm" and "lastm" are the two variable names of this month's data and last month's data, and this function represents the month-on-month growth rate of this month's and last month's data. Some functions are shown in Table 2;

[0077] Table 2

[0078]

[0079]

[0080] In another embodiment, power trading business data is classified, at least one category of target business data is determined, and abnormal monitoring indicators for the target business data are generated, including: obtaining data classification basis; determining at least one category of target business data in the power trading business data according to the data classification basis; generating indicators for the target business data to obtain abnormal monitoring indicators.

[0081] The data classification basis includes at least one of the indicator dimension type, indicator data type and indicator statistical frequency.

[0082] The indicator dimension types may include at least one of: market management, capital management, power trading, settlement management, information management and planning management.

[0083] The indicator data type may include at least one of a numeric type, a string type, a date type, and an enumeration type.

[0084] The statistical frequency of indicators may include at least one of daily data, monthly data, quarterly data, annual data and regular data.

[0085] The information of sub-monitoring indicators can be found in Table 1;

[0086] Table 1

[0087] Metric dimension type Indicator name Metric Data Type Frequency of indicator statistics Market Management Authorized Contact STRING Daily data Market Management Username STRING Daily data Market Management Electricity usage category STRING Daily data Market Management Unified social credit code for industry and commerce STRING Daily data Market Management Legal representative of industry and commerce STRING Daily data Market Management Industrial and commercial registered capital NUMBER Daily data Power Trading Number of electricity sales agent users NUMBER Monthly data Power Trading Number of electricity sales agent users NUMBER Monthly data Power Trading Electricity sales agent quantity NUMBER Monthly data Power Trading Transaction behavior credit evaluation results STRING Daily data Power Trading Digital certificate validity period DATE Daily data Power Trading Transaction service fee NUMBER Daily data Power Trading Unpaid transaction service fees NUMBER Daily data Power Trading Service satisfaction STRING Daily data

[0088] In the specific implementation, the terminal can reorganize the power trading business data from at least three dimensions, including indicator dimension type, indicator data type and indicator statistical frequency, according to the characteristics of the power trading business data, and determine at least one type of target business data in the power trading business data; finally, the terminal generates indicators for the target business data to obtain abnormal monitoring indicators.

[0089] The technical solution of this embodiment,

[0090] In another embodiment, the method also includes: sending the monitoring results of the abnormal monitoring items to the user terminal; the user terminal is used to prompt the user that there is an abnormality in the target monitoring subject; the user terminal is also used to receive the abnormal handling results for the target monitoring subject; and receiving the abnormal handling results returned by the user terminal.

[0091] The terminal can also perform statistical processing on the abnormal handling results to obtain the statistical handling results; and display the statistical handling results.

[0092] In the specific implementation, after the terminal determines that there is an abnormality in the target monitoring subject, the terminal can send the monitoring results of the abnormal monitoring items to the user terminal to prompt the user that there is an abnormality in the target monitoring subject; the user terminal is also used to receive the abnormal handling results for the target monitoring subject; and receive the abnormal handling results returned by the user terminal.

[0093] For example, after the terminal finds that there is an abnormality in the target monitoring subject, the terminal automatically initiates the risk disposal process through the process engine and sends the specific monitoring result details to the person in charge of the monitoring item; then, after the person in charge of the monitoring item manually disposes, he enters the disposal results of each risk monitoring subject in the process and returns the process to the risk monitoring system. The disposal results include "disposed", "to be disposed", and "excluded". The risk monitoring system counts and displays the results of this risk disposal, and skips the monitoring subject that has been set to "excluded" during the next monitoring.

[0094] The present disclosure provides a configurable method for monitoring the risk of power trading. Based on the information summary of each module of the power trading center, risk monitoring indicators are extracted and sorted out, and market risks are judged and controlled through general analytical expressions. The method is highly targeted and practical, filling the gap in the special business of configurable risk monitoring of power trading. Through a customized configurable method, it is suitable for different businesses and different module requirements in power trading. It can be used alone or in combination through an integrated process. It has the advantages of flexibility and efficiency, can monitor and analyze the operation of the power market, minimize the operation risks of power trading, and improve the level of risk management.

[0095] In another embodiment, Figure 3 As shown in the figure, a configurable power trading risk monitoring method is provided, which is applied to Figure 1 The computer device in the example is used to illustrate, including the following steps:

[0096] Step S310, acquiring power trading business data; the power trading business data includes at least one of power management data, power trading data and metering and settlement data.

[0097] Step S320, obtaining data classification basis; the data classification basis includes at least one of indicator dimension type, indicator data type and indicator statistical frequency.

[0098] Step S330, according to the data classification basis, at least one type of target business data is determined in the power trading business data.

[0099] Step S340, generating indicators for target business data to obtain abnormal monitoring indicators.

[0100] Step S350, in the abnormal monitoring item, the abnormal monitoring indicator to be monitored is set as an indicator variable, and an expression containing the indicator variable is determined; the expression is used to represent the abnormal monitoring logic.

[0101] Step S360, parse the expression, traverse the monitoring subjects in the abnormal monitoring indicator, and obtain the monitoring results of the abnormal monitoring items; the monitoring results include the target monitoring subjects with abnormalities.

[0102] Step S370, sending the monitoring result of the abnormal monitoring item to the user terminal; the user terminal is used to prompt the user that there is an abnormality in the target monitoring subject; the user terminal is also used to receive the abnormal handling result for the target monitoring subject.

[0103] Step S380: receiving the exception handling result returned by the user terminal.

[0104] It should be noted that the specific limitations of the above steps can refer to the specific limitations of a configurable power trading risk monitoring method mentioned above.

[0105] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0106] Based on the same inventive concept, the embodiment of the present application also provides a configurable power trading risk monitoring device for implementing the configurable power trading risk monitoring method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more configurable power trading risk monitoring device embodiments provided below can refer to the limitations of the configurable power trading risk monitoring method above, and will not be repeated here.

[0107] In one embodiment, Figure 4 As shown, a configurable power transaction risk monitoring device is provided, comprising:

[0108] The acquisition module 410 is used to acquire power transaction business data; the power transaction business data includes at least one of power management data, power transaction data and metering and settlement data;

[0109] The classification module 420 is used to classify the power trading business data, determine at least one type of target business data, and generate an abnormal monitoring indicator for the target business data;

[0110] The determination module 430 is used to set the abnormal monitoring indicator to be monitored as an indicator variable in the abnormal monitoring item, and determine an expression containing the indicator variable; the expression is used to represent the abnormal monitoring logic;

[0111] The traversal module 440 is used to parse the expression, traverse the monitoring subjects in the abnormal monitoring indicator, and obtain the monitoring results of the abnormal monitoring items; the monitoring results include the target monitoring subjects with abnormalities.

[0112] In another embodiment, the traversal module 440 is specifically used to extract numbers from the abnormal monitoring indicators corresponding to the indicator variables, assign values ​​to the variables in the expression, and convert the general expression containing the indicator variables into a program-readable logical expression; verify the correctness of the expression after assignment to ensure that the expression complies with grammatical rules; calculate the function in the expression to generate a mathematical expression; perform reverse Polish notation on the mathematical expression, and determine whether there is an abnormality in the monitoring subject based on the calculation result; bring the monitoring data of the next monitoring subject into the indicator variable, and repeat the above steps.

[0113] In another embodiment, the power management data includes at least one of enterprise registration data, market status data, deposit data, transaction service fee data, retail relationship data, digital certificate information and registration process data; and / or, the power transaction data includes at least one of transaction contract data, transaction product data, transaction market data, market transaction data, power generation capacity data, transaction volume and price data, retail relationship data and transaction statistics data; and / or, the metering settlement data includes at least one of retail user settlement data, wholesale user settlement data, power plant settlement data, power sales company settlement data, revenue settlement data and historical electricity data.

[0114] In another embodiment, the classification module 420 is specifically used to obtain data classification basis; the data classification basis includes at least one of indicator dimension type, indicator data type and indicator statistical frequency; according to the data classification basis, at least one type of target business data is determined in the power trading business data; indicators are generated for the target business data to obtain the abnormal monitoring indicators.

[0115] In another embodiment, the device also includes: a sending module for sending the monitoring results of the abnormal monitoring items to a user terminal; the user terminal is used to prompt the user that there is an abnormality in the target monitoring subject; the user terminal is also used to receive the abnormal handling results for the target monitoring subject; and a receiving module is used to receive the abnormal handling results returned by the user terminal.

[0116] In another embodiment, the device further includes: a statistical module for performing statistical processing on the abnormal handling results to obtain statistical handling results; and a display module for displaying the statistical handling results.

[0117] Each module in the above-mentioned configurable power trading risk monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0118] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a configurable power trading risk monitoring method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0119] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0120] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the above-mentioned steps of a configurable power trading risk monitoring. Here, the steps of a configurable power trading risk monitoring can be the steps of a configurable power trading risk monitoring in each of the above-mentioned embodiments.

[0121] In one embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the processor executes the above-mentioned steps of a configurable power trading risk monitoring. Here, the steps of a configurable power trading risk monitoring can be the steps of a configurable power trading risk monitoring in each of the above-mentioned embodiments.

[0122] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, causes the processor to perform the above-mentioned steps of a configurable power trading risk monitoring. Here, the steps of a configurable power trading risk monitoring may be the steps of a configurable power trading risk monitoring in each of the above-mentioned embodiments.

[0123] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0124] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0125] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A configurable power trading risk monitoring method, characterized in that: The method comprises: Acquiring power transaction business data; the power transaction business data includes at least one of power management data, power transaction data and metering and settlement data; Classifying the power trading business data, determining at least one type of target business data, and generating an abnormal monitoring indicator for the target business data; In the abnormal monitoring item, the abnormal monitoring indicator to be monitored is set as an indicator variable, and an expression containing the indicator variable is determined; the expression is used to represent the abnormal monitoring logic; the indicator variable is divided into a main variable and a common variable, and the method further includes: firstly selecting the main variable, the main variable constraining the indicator dimension and indicator frequency of the common variable; Parsing the expression, traversing the monitoring subjects in the abnormal monitoring indicator, and obtaining the monitoring result of the abnormal monitoring item; the monitoring result includes the target monitoring subject with abnormality; The parsing of the expression, traversing the monitoring subjects in the abnormal monitoring indicator, and obtaining the monitoring result of the abnormal monitoring item include: Extracting data from the abnormal monitoring index corresponding to the index variable, assigning values ​​to the variables in the expression, and converting the general expression containing the index variable into a program-readable logical expression; Verify the correctness of the expression after assignment to ensure that the expression complies with grammatical rules; Calculating the function in the expression to generate a mathematical expression; Performing reverse Polish notation on the mathematical expression, and judging whether the monitored subject has an abnormality according to the calculation result; The monitoring data of the next monitoring subject is brought into the indicator variable, and the above steps are repeated.

2. The method according to claim 1, characterized in that The power management data includes at least one of enterprise registration data, market status data, margin data, transaction service fee data, retail relationship data, digital certificate information, and registration process data; and / or, The power transaction data includes at least one of transaction contract data, transaction product data, transaction market data, market transaction data, power generation capacity data, transaction volume and price data, retail relationship data and transaction statistics data; and / or, The metering settlement data includes at least one of retail user settlement data, wholesale user settlement data, power plant settlement data, power sales company settlement data, revenue settlement data and historical electricity data.

3. The method according to claim 1, characterized in that The classifying the power trading business data, determining at least one type of target business data, and generating an abnormal monitoring indicator for the target business data includes: Obtaining a basis for data classification; the basis for data classification includes at least one of an indicator dimension type, an indicator data type, and an indicator statistical frequency; According to the data classification basis, determining at least one type of target business data in the power trading business data; Generate an indicator for the target business data to obtain the abnormal monitoring indicator.

4. The method according to claim 1, characterized in that: The method further comprises: Sending the monitoring result of the abnormal monitoring item to a user terminal; the user terminal is used to prompt the user that the target monitoring subject has an abnormality; the user terminal is also used to receive the abnormal handling result for the target monitoring subject; Receive the exception handling result returned by the user terminal.

5. The method according to claim 4, characterized in that The method further comprises: Performing statistical processing on the abnormal handling results to obtain statistical handling results; The processing results after the statistics are displayed.

6. A configurable power trading risk monitoring device, characterized in that: The device comprises: An acquisition module, used to acquire power transaction business data; the power transaction business data includes at least one of power management data, power transaction data and metering and settlement data; A classification module, used to classify the power trading business data, determine at least one type of target business data, and generate an abnormal monitoring indicator for the target business data; A determination module is used to set the abnormal monitoring indicator to be monitored as an indicator variable in the abnormal monitoring item, and determine an expression containing the indicator variable; the expression is used to represent the abnormal monitoring logic; the indicator variable is divided into a main variable and a common variable, and the main variable is first selected, and the main variable constrains the indicator dimension and indicator frequency of the common variable; A traversal module, used to parse the expression, traverse the monitoring subjects in the abnormal monitoring indicator, and obtain the monitoring results of the abnormal monitoring items; the monitoring results include the target monitoring subjects with abnormalities; The traversal module is used to extract data from the abnormal monitoring indicators corresponding to the indicator variables, assign values ​​to the variables in the expression, and convert the general expression containing the indicator variables into a program-readable logical expression; verify the correctness of the expression after assignment to ensure that the expression complies with grammatical rules; calculate the function in the expression to generate a mathematical expression; perform reverse Polish notation on the mathematical expression, and determine whether there is an abnormality in the monitoring subject based on the calculation result; bring the monitoring data of the next monitoring subject into the indicator variable, and repeat the above steps.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. 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 5 are implemented.

9. A computer program product, comprising a computer program, 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 5 are implemented.

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