Abnormal transaction behavior monitoring method and device, computer equipment, medium and product

Abstract

The invention relates to an abnormal transaction behavior monitoring method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring transaction associated data of electric power resources transacted by transaction participants in different dimensions in a preset monitoring time period; and according to the matching condition between the transaction associated data and the standard reference data, determining whether the transaction participant has an abnormal transaction behavior within the preset monitoring time period. The method can improve the recognition accuracy of the abnormal transaction behaviors of the transaction participants in the regional electric energy transaction market, inhibits the abnormal transaction behaviors of the transaction participants, and guarantees the fairness of the transaction in the regional electric energy market.

Description

Technical Field

[0001] The present application relates to the field of electric power engineering technology, and in particular to a method, device, computer equipment, medium and product for monitoring abnormal transaction behavior. Background Art

[0002] With the emergence of regional electricity spot markets, power generation companies and users can directly trade electricity, breaking the traditional trading model in which power grid companies purchase electricity from power generation companies and sell it to users, and realizing flexible electricity trading.

[0003] However, due to the flexibility of electricity trading in the regional electricity spot market, power generation companies and users may maliciously manipulate the market in order to maximize their own interests, which will seriously affect the fairness of transactions in the regional electricity spot market.

[0004] At present, the behavior monitoring methods of trading participants in the regional electricity spot market cannot accurately monitor the market manipulation behavior of trading participants, and it is difficult to ensure the fairness of transactions in the regional electricity spot market. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment, medium and product for monitoring abnormal trading behavior in response to the above-mentioned technical problems, so as to improve the fairness of transactions in the regional electricity spot market.

[0006] In a first aspect, the present application provides a method for monitoring abnormal transaction behavior, comprising:

[0007] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0008] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0009] In one of the embodiments, if the transaction-related data includes operating parameter data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including at least one of the following: if the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than a first preset frequency threshold, then it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; if the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than a first preset deviation threshold, then it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; and if the frequency at which the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction is greater than the second preset deviation threshold is higher than the second preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0010] In one of the embodiments, if the transaction-related data includes the operating behavior data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including: if the resource provider has interfered with the operation of the unit equipment without reason, then it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; wherein, the behavior of intervening in the operation of the unit equipment without reason includes at least one of the following: the behavior of exiting the automatic power generation control AGV service of the unit equipment without reason, the behavior of applying for unit equipment maintenance without reason, and the behavior of extending the unit equipment maintenance without reason.

[0011] In one of the embodiments, if the transaction-related data includes resource value data of the traded power resources, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have engaged in abnormal trading behavior within a preset monitoring period, including: if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to a preset coefficient threshold, then it is determined that the transaction participants have engaged in abnormal trading behavior within the preset monitoring period; or, if the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, then it is determined that the transaction participants have engaged in abnormal trading behavior within the preset monitoring period.

[0012] In one of the embodiments, if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a transaction deviation between transaction parameters and standard transaction parameters that is greater than a third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction.

[0013] In one of the embodiments, if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that within the preset monitoring period, there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants, then determining that the transaction to be monitored is an abnormal transaction.

[0014] In a second aspect, the present application also provides an abnormal transaction behavior monitoring device, comprising:

[0015] An acquisition module is used to acquire transaction-related data of electric power resources traded by transaction participants in different dimensions within a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant association data between transaction participants;

[0016] The determination module is used to determine whether the transaction participants have any abnormal transaction behavior within a preset monitoring period based on the matching between the transaction-related data and the standard reference data.

[0017] 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 when the processor executes the computer program, the following steps are implemented:

[0018] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0019] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0021] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0022] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0023] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0024] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0025] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0026] The above-mentioned abnormal trading behavior monitoring method, device, computer equipment, medium and product introduce multi-dimensional transaction-related data of transaction participants in electricity trading, and determine whether the transaction participants have abnormal trading behavior based on the matching between a series of transaction-related data and standard reference data, thereby improving the accuracy of identifying abnormal trading behavior of transaction participants in the regional electricity trading market, being able to restrain transaction participants from engaging in abnormal trading behavior, and ensuring the fairness of transactions in the regional electricity market. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0028] FIG1 is a schematic diagram of a flow chart of a method for monitoring abnormal transaction behavior in one embodiment;

[0029] FIG2 is a flow chart of the steps of determining whether there is abnormal transaction behavior in one embodiment;

[0030] FIG3 is a flow chart of the step of determining whether there is abnormal transaction behavior in another embodiment;

[0031] FIG4 is a flow chart of the step of determining whether there is abnormal transaction behavior in another embodiment;

[0032] FIG5 is a flow chart of the step of determining whether there is abnormal transaction behavior in another embodiment;

[0033] FIG6 is a flow chart of the step of determining whether there is abnormal transaction behavior in another embodiment;

[0034] FIG7 is a structural block diagram of an abnormal transaction behavior monitoring device in one embodiment;

[0035] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0036] 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.

[0037] In one embodiment, as shown in FIG1 , a method for monitoring abnormal transaction behavior is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0038] S110, obtaining transaction-related data of electric power resources traded by transaction participants in different dimensions within a preset monitoring period.

[0039] Optionally, the preset monitoring period refers to the period for judging abnormal trading behavior. It should be noted that the preset monitoring period can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any restrictions on this. Among them, the transaction participants can be understood as participants in resource transactions. For example, the transaction participants may include resource providers and resource demanders. Exemplarily, in the regional electric energy futures market, the resource provider can be understood as the party that provides power resources, and the resource demander can be understood as the party that obtains power resources. Furthermore, abnormal trading behavior can be understood as the behavior taken by the transaction participants that affects the fairness of the transaction.

[0040] Furthermore, the transaction-related data of the traded power resources can be understood as the relevant data of the power resources traded between the transaction participants from production to completion of the transaction. Exemplarily, the transaction-related data can include at least one of the operating parameter data of the resource provider, the operating behavior data of the resource provider, the resource value data of the traded power resources, and the participant-related data between the transaction participants.

[0041] Among them, the operating parameter data of the resource provider can be understood as the operating parameter data of the unit equipment used by the resource provider to produce electric power resources. The operating parameter data may include basic operating parameters and key operating parameters. The basic operating parameters may be understood as parameters used to control the actual operation of the unit equipment. Exemplarily, the basic operating parameters may include the actual output power of the unit equipment, etc. The key operating parameters may be understood as parameters that characterize the electric power resource production capacity possessed by the unit equipment. Exemplarily, the key operating parameters may include rated output power, etc. The operating behavior data may be understood as the behavior data of the resource provider intervening in the operation of the unit equipment during the production of electric energy. The resource value data of the traded electric resources may be understood as the price data reflected by the electric resources in the transaction process. Optionally, the resource value data of the traded electric resources may include at least one of the selling price of the electric resources and the adjustment data of the selling price of the electric resources. Further, the adjustment data of the selling price of the electric resources may be understood as data indicating an increase or decrease in the selling price of the electric resources. The participant association data between the transaction participants may be understood as data indicating the degree of association between the transaction participants.

[0042] S120, determining whether the transaction participants have any abnormal transaction behavior within a preset monitoring period based on the matching between the transaction-related data and the standard reference data.

[0043] Optionally, the standard reference data can be understood as data used to limit the transaction-related data corresponding to normal transaction behavior. Further, the matching between the transaction-related data and the standard reference data can be understood as qualitative description data or quantitative description data indicating whether the transaction-related data is within the scope limited by the standard reference data.

[0044] Exemplarily, if both the transaction-related data and the standard reference data are numerical data, then when the transaction-related data exceeds the standard reference data or the corresponding restricted range, it indicates that the transaction-related data does not match the standard reference data, and at this time, it can be determined that the transaction participant corresponding to the transaction-related data has abnormal transaction behavior within the preset monitoring period. On the contrary, when the transaction-related data does not exceed the standard reference data or does not exceed the range restricted by the standard reference data, it indicates that the transaction-related data matches the standard reference data, and at this time, it can be determined that the transaction participant corresponding to the transaction-related data does not have abnormal transaction behavior within the preset monitoring time.

[0045] Exemplarily, if both the transaction-related data and the standard reference data are non-numeric data, then when the transaction-related data and the standard reference data have opposite meanings, it indicates that the transaction-related data do not match the standard reference data, and at this time, it can be determined that the transaction participant corresponding to the transaction-related data has abnormal transaction behavior within the preset monitoring period. On the contrary, when the transaction-related data and the standard reference data have the same meaning, it indicates that the transaction-related data matches the standard reference data, and at this time, it can be determined that the transaction participant corresponding to the transaction-related data does not have abnormal transaction behavior within the preset monitoring period.

[0046] In this embodiment, by introducing multi-dimensional transaction-related data of transaction participants in electricity trading, and determining whether the transaction participants have abnormal trading behavior based on the matching between a series of transaction-related data and standard reference data, the accuracy of identifying abnormal trading behavior of transaction participants in the regional electricity trading market is improved, and the transaction participants can be restrained from engaging in abnormal trading behavior, thereby ensuring the fairness of transactions in the regional electricity market.

[0047] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the step of determining whether there is abnormal transaction behavior is refined.

[0048] Referring to FIG. 2 , the steps for determining whether there is abnormal transaction behavior include:

[0049] S210: If the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period.

[0050] Optionally, the adjustment frequency corresponding to the basic operating parameters of the unit equipment can be understood as the frequency of the resource provider adjusting the basic operating parameters of the unit equipment during the power production process. Among them, the first preset frequency threshold can be understood as the upper limit value of the adjustment frequency corresponding to the basic operating parameters of the unit equipment. It should be noted that the first preset frequency threshold can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any restrictions on this. Exemplarily, if the adjustment frequency corresponding to the basic operating parameters of the unit equipment is greater than the first preset frequency threshold, it means that the resource provider may affect the power generation of the unit equipment by frequently adjusting the basic operating parameters of the unit equipment, so as to achieve the purpose of manipulating electricity prices. Therefore, it is determined that the transaction participants have abnormal trading behavior.

[0051] S220: If the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than the first preset deviation threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period.

[0052] Among them, the registered operating parameters can be understood as the registered parameters of the key operating parameters of the unit equipment. Optionally, the first preset deviation threshold can be understood as the upper limit value of the parameter deviation between the key operating parameters of the unit equipment and the corresponding registered operating parameters. It should be noted that the first preset deviation threshold can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any restrictions on this. Exemplarily, if the parameter deviation between the key operating parameters of the unit equipment and the corresponding registered operating parameters is greater than the first preset deviation threshold, it means that the resource provider may misreport the key operating parameters of the unit equipment to cause a deviation between the actual power production capacity and the expected power production capacity, in order to achieve the purpose of manipulating electricity prices. Therefore, it is determined that the transaction participants have abnormal trading behavior.

[0053] S230, if the frequency of the output power deviation between the actual output power of the unit equipment in the basic operating parameters and the standard output power in the scheduling instruction is greater than the second preset deviation threshold and is higher than the second preset frequency threshold, it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period.

[0054] Optionally, the dispatch instruction can be understood as an instruction for controlling the power generation capacity of the unit equipment. Among them, the standard output power in the dispatch instruction can be understood as the output power carried in the dispatch instruction to control the actual output power of the unit equipment. Further, the output power deviation can be understood as the deviation value between the actual output power of the unit equipment and the standard output power in the dispatch instruction. Optionally, the second preset deviation threshold can be understood as the upper limit value of the output power deviation. Optionally, the second preset frequency threshold can be understood as the upper limit value of the frequency at which the output power is greater than the second preset deviation threshold. It should be noted that the second preset deviation threshold and the second preset frequency threshold can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any restrictions on this. Exemplarily, if the frequency of the output power deviation between the actual output power of the unit equipment and the standard output power in the dispatching instruction being greater than the second preset deviation threshold is higher than the second preset frequency threshold, it means that the resource provider may frequently adjust the actual output power of the unit equipment in private, causing the output power of the unit equipment to frequently deviate greatly from the standard output power in the dispatching instruction, in order to increase the power resources on the market, or reduce the power resources on the market, and then manipulate the power selling price. Therefore, it is determined that the transaction participants have abnormal trading behavior.

[0055] In this embodiment, by comparing the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data with the first preset frequency threshold; comparing the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters, and the first preset deviation threshold; comparing the frequency of the output deviation between the actual output of the unit equipment and the standard output in the dispatching instruction being greater than the second preset deviation threshold, and the second preset frequency threshold, it is determined whether there is abnormal trading behavior among the transaction participants, thereby improving the accuracy of identifying abnormal trading behavior of transaction participants in the regional electric energy trading market, being able to restrain transaction participants from making abnormal trading behaviors, and ensuring the fairness of transactions in the regional electric energy market.

[0056] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the steps of determining whether there is abnormal transaction behavior are described in detail.

[0057] Referring to FIG. 3 , a step of determining whether there is abnormal transaction behavior includes:

[0058] S310: If the resource provider interferes with the operation of the unit equipment without reason, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period.

[0059] Among them, the behavior of interfering with the operation of the unit equipment without reason can be understood as the behavior taken by the resource provider without a legitimate reason to affect the normal operation of the unit equipment. Exemplarily, the behavior of interfering with the operation of the unit equipment without reason can include at least one of the behavior of exiting the AGV (Automatic Generation Control) service of the unit equipment without reason, the behavior of applying for unit equipment maintenance without reason, and the behavior of extending the unit equipment maintenance without reason. Optionally, the AGV service is a service that detects and adjusts the power generation capacity of the unit equipment in real time. It is mainly used by power grid companies to monitor and adjust the electricity in the market in real time. The unit equipment of the trading participants entering the market will join the AGV service in accordance with the agreement to ensure the stable supply of power resources or avoid excess power production capacity.

[0060] For example, if the unit equipment exits the AGV service without reason, it means that the resource provider to which the unit equipment belongs may be unwilling to abide by market rules, but instead privately adjusts the power generation capacity of the unit equipment to affect the power resources on the market, thereby achieving the purpose of manipulating power prices. Therefore, it is judged that the transaction participants have abnormal trading behavior. If the resource provider applies for unit equipment maintenance without reason or extends the unit equipment maintenance without reason, it means that the resource provider may reduce the power generation time of the unit equipment, reduce the power generation of the unit equipment, and affect the power resources on the market, so as to achieve the purpose of manipulating power prices. Therefore, it is judged that the transaction participants have abnormal trading behavior.

[0061] In this embodiment, if the resource provider interferes with the operation of the unit equipment without reason, it is determined that the transaction participant has abnormal trading behavior within the preset monitoring period. The above technical solution can prevent the resource provider from using seemingly legitimate reasons to achieve subjective market manipulation purposes, enhance the monitoring of abnormal trading behaviors of transaction participants, and can inhibit transaction participants from engaging in abnormal trading behaviors, thereby ensuring the fairness of transactions in the regional power market.

[0062] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the steps of determining whether there is abnormal transaction behavior are described in detail.

[0063] Referring to FIG. 4 , a step of determining whether there is abnormal transaction behavior includes:

[0064] S410: If the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to a preset coefficient threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0065] Among them, the reference power line can be understood as other power lines with the same section as the resource provider. The transmission section can be understood as a virtual surface formed by all power lines that transmit power from one area to another area, which can be used to determine the regional electric energy futures market to which the power line belongs. Optionally, the resource value adjustment direction of the reference power line can be understood as the adjustment direction of the power resource sales price of the reference power line. Further, the correlation parameter can be understood as the numerical quantification result of the correlation between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line. Optionally, the preset coefficient threshold can be understood as the upper limit of the correlation coefficient. Exemplarily, if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to the preset coefficient threshold, it means that the resource providers to which different power lines belong may collude privately and take actions to increase or reduce the power price at the same time to manipulate the market power price. Therefore, it is determined that the transaction participants have abnormal trading behavior.

[0066] S420: If the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0067] Optionally, the reference resource value can be understood as the resource value used to evaluate the resource value data of the traded power resources. Exemplarily, the reference resource value may include the historical resource value of the corresponding unit equipment of the resource provider, and the resource value corresponding to the same type of unit equipment as the corresponding unit equipment of the resource provider. Among them, the historical resource value of the corresponding unit equipment of the resource provider can be understood as the historical electricity price of the corresponding unit equipment of the current resource provider; the resource value corresponding to the same type of unit equipment of the corresponding unit equipment of the resource provider can be understood as the current electricity price of the same type of unit equipment as the corresponding unit equipment of the current resource provider. Further, the same type of unit equipment can be understood as unit equipment with the same energy conversion form. The type of unit equipment can include at least one of wind turbine equipment, thermal power unit equipment and hydropower unit equipment. Optionally, the second preset frequency threshold can be understood as the resource value data of the traded power resources, which is lower than the upper limit of the frequency of the reference resource value. It should be noted that the second preset frequency threshold can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any restrictions on this.

[0068] Exemplarily, if the frequency with which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, it indicates that the current resource provider may frequently engage in unfair competition by deliberately lowering the price of electricity. Therefore, it is judged that the transaction participants have abnormal trading behavior.

[0069] In this embodiment, if there is a correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line, which is greater than or equal to the preset coefficient threshold, it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period; if the frequency of the resource value data of the traded power resources is lower than the reference resource value, which is greater than the second preset frequency threshold, it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period. The above technical scheme can determine whether the transaction participants collude privately to control the market power price based on the correlation coefficient between the resource value data of the power resources traded by the current resource provider and the resource value adjustment of the reference power line; based on the comparison result of the resource value data of the power resources traded by the current resource provider and the reference resource value, it can determine whether the current transaction participants have malicious bidding behavior, thereby improving the accuracy of identifying abnormal trading behavior of transaction participants in the regional power trading market, and can inhibit transaction participants from making abnormal trading behaviors, and ensure the fairness of transactions in the regional power market.

[0070] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the steps of determining whether there is abnormal transaction behavior are described in detail.

[0071] Referring to FIG. 5 , a step of determining whether there is abnormal transaction behavior includes:

[0072] S510, if the party association data indicates that the transaction parties belong to the same group, and within the preset monitoring period, in the transactions between the transaction parties, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than a third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction.

[0073] Among them, the transaction parameters can be understood as parameters that represent the actual transaction situation of the transaction participants. Exemplarily, the transaction parameters may include the amount of electricity traded and the price of electricity traded. Optionally, the standard transaction parameters can be understood as parameters that represent the actual transaction situation of the market. Furthermore, the third preset deviation threshold can be understood as the upper limit of the transaction deviation between the transaction parameters and the standard transaction parameters. It should be noted that the third preset deviation threshold can be set or adjusted by technical personnel according to needs or experience, or determined through a large number of experiments, and this application does not impose any limitation on this.

[0074] Exemplarily, if the party association data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than the third preset deviation threshold, then it means that the transaction participants did not conduct transactions in accordance with market conditions, but may have conducted private transactions based on personal interests, which is not in line with the fairness of market transactions. Therefore, it is determined that the transaction participants have engaged in abnormal trading behavior.

[0075] In this embodiment, if the participant association data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a situation where the transaction deviation between the transaction parameters and the standard transaction parameters is greater than the third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction. The above technical solution compares the transaction parameters of the transaction participants with the marked transaction parameters to determine whether the transaction is fairly traded according to market conditions, and then determines whether the transaction participants have abnormal trading behavior of privately trading for personal interests, thereby ensuring the fairness and transparency of transactions in the regional electric energy futures market.

[0076] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment, in which the steps of determining whether there is abnormal transaction behavior are described in detail.

[0077] Referring to FIG. 6 , a step of determining whether there is abnormal transaction behavior includes:

[0078] S610: If the participant association data indicates that there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants within a preset monitoring period, then the transaction to be monitored is determined to be an abnormal transaction.

[0079] Among them, complementary transactions can be understood as transactions in which the supply and demand relationships of the transaction participants are opposite and the transaction parameters are similar. Optionally, similar transaction parameters can include at least one of similar transaction quantities of power resources and similar transaction prices of power resources. Exemplarily, if there are transaction participants A and B, and transaction participants A and B conduct two power energy transactions, in one of the transactions, transaction participant A is the resource provider and transaction participant B is the resource demander; and in the other transaction, transaction participant B is the resource provider and transaction participant A is the resource demander, it means that the supply and demand relationship between the two in these two transactions is opposite.

[0080] For example, if the associated data of the participants indicates that within the preset monitoring period, there are complementary transactions between the resource providers among the transaction participants and the resource demanders among the transaction participants, it means that the transactions conducted by the transaction participants are false transactions, which are actually intended to increase the market transaction volume and reduce the market electricity price to achieve the purpose of manipulating the market electricity price. Therefore, it is determined that the transaction participants have abnormal trading behavior.

[0081] In this embodiment, if the data related to the participants indicates that there is a complementary transaction between the resource provider among the transaction participants and the resource demander among the transaction participants within the preset monitoring period, the transaction to be monitored is determined to be an abnormal transaction. The above technical solution determines whether the transaction between the transaction participants is a false transaction based on whether the transaction participants do not trade with each other, and then determines whether the transaction participants have abnormal trading behavior, which enhances the monitoring of abnormal trading behavior of the transaction participants, can inhibit the transaction participants from making abnormal trading behaviors, and ensure the fairness of transactions in the regional power market.

[0082] 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.

[0083] Based on the same inventive concept, the embodiment of the present application also provides an abnormal transaction behavior monitoring device for implementing the abnormal transaction behavior 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 abnormal transaction behavior monitoring device embodiments provided below can refer to the limitations of the abnormal transaction behavior monitoring method above, and will not be repeated here.

[0084] In an exemplary embodiment, as shown in FIG. 7 , a device for monitoring abnormal transaction behavior is provided, including: an acquisition module 710 and a determination module 720 , wherein:

[0085] Acquisition module 710 is used to obtain transaction-related data in different dimensions of the power resources traded by the transaction participants within a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of the resource provider among the transaction participants, operating behavior data of the resource provider, resource value data of the traded power resources, and participant association data between the transaction participants.

[0086] The determination module 720 is used to determine whether the transaction participants have any abnormal transaction behavior within a preset monitoring period based on the matching between the transaction-related data and the standard reference data.

[0087] In one embodiment, the determination module 720 includes: a first determination unit, which is used to determine that the transaction participants have abnormal trading behavior within the preset monitoring period if the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold; a second determination unit, which is used to determine that the transaction participants have abnormal trading behavior within the preset monitoring period if the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than the first preset deviation threshold; a third determination unit, which is used to determine that the transaction participants have abnormal trading behavior within the preset monitoring period if the frequency at which the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction is greater than the second preset deviation threshold is higher than the second preset frequency threshold.

[0088] In one embodiment, the determination module 720 includes: a fourth determination unit, which is used to determine whether the transaction participant has abnormal transaction behavior within a preset monitoring period if the resource provider has interfered with the operation of the unit equipment without reason.

[0089] In one embodiment, the determination module 720 includes: a fifth determination unit, which is used to determine that the transaction participants have abnormal trading behavior within the preset monitoring period if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to the preset coefficient threshold; a sixth determination unit, which is used to determine that the transaction participants have abnormal trading behavior within the preset monitoring period if the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold.

[0090] In one embodiment, the determination module 720 includes: a seventh determination unit, which is used to determine that the transaction to be monitored is an abnormal transaction if the party association data indicates that the transaction parties belong to the same group, and within the preset monitoring period, there is a transaction deviation between the transaction parameters and the standard transaction parameters in the transactions between the transaction parties that is greater than a third preset deviation threshold.

[0091] In one embodiment, the determination module 720 includes: an eighth determination unit, which is used to determine that the transaction to be monitored is an abnormal transaction if the participant association data indicates that there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants within a preset monitoring period.

[0092] Each module in the abnormal transaction behavior monitoring device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module 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 operations corresponding to each module.

[0093] In an exemplary embodiment, a computer device is provided, and its internal structure diagram can be shown in Figure 8. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. 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 input / output interface of the computer device is used to exchange information between the processor and an external device. 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 implemented through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, a method for monitoring abnormal transaction behavior is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen 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 covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0094] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial 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 shown in the figure, or combine certain components, or have a different arrangement of components.

[0095] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0096] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0097] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0098] In one embodiment, the processor also implements the following steps when executing the computer program: if the transaction-related data includes the operating parameter data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, determine whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including at least one of the following: if the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; if the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than the first preset deviation threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; and if the frequency at which the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction is greater than the second preset deviation threshold is higher than the second preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0099] In one embodiment, the processor also implements the following steps when executing the computer program: if the transaction-related data includes the operating behavior data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, determine whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including: if the resource provider has interfered with the operation of the unit equipment without reason, then determine that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0100] In one embodiment, the processor also implements the following steps when executing the computer program: if the transaction-related data includes resource value data of the traded power resources, then based on the matching between the transaction-related data and the standard reference data, determine whether the transaction participants have abnormal trading behavior within the preset monitoring period, including: if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to a preset coefficient threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period; or, if the frequency of the resource value data of the traded power resources being lower than the reference resource value is greater than a second preset frequency threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period.

[0101] In one embodiment, the processor further implements the following steps when executing the computer program: if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, determine whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than a third preset deviation threshold, then determine that the transaction to be monitored is an abnormal transaction.

[0102] In one embodiment, the processor further implements the following steps when executing the computer program: if the transaction-related data includes party-related data between transaction participants, then determining whether the transaction participants have abnormal transaction behavior within a preset monitoring period based on the matching between the transaction-related data and the standard reference data, including: if the party-related data indicates that within the preset monitoring period, there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants, then determining that the transaction to be monitored is an abnormal transaction; wherein, a complementary transaction is a transaction in which the supply and demand relationship between the transaction participants is opposite and the transaction parameters are similar.

[0103] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0104] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0105] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0106] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes the operating parameter data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including at least one of the following: if the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; if the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than the first preset deviation threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; and if the frequency at which the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction is greater than the second preset deviation threshold is higher than the second preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0107] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes the operating behavior data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including: if the resource provider has interfered with the operation of the unit equipment without reason, then it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0108] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes resource value data of the traded power resources, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal trading behavior within the preset monitoring period, including: if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to a preset coefficient threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period; or, if the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period.

[0109] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than a third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction.

[0110] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that within the preset monitoring period, there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants, then determining that the transaction to be monitored is an abnormal transaction.

[0111] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0112] Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions during a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among transaction participants, operating behavior data of resource providers, resource value data of traded electric power resources, and participant-related data between transaction participants;

[0113] Based on the matching between transaction-related data and standard reference data, determine whether the transaction participants have any abnormal transaction behavior during the preset monitoring period.

[0114] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes the operating parameter data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including at least one of the following: if the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; if the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than the first preset deviation threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period; and if the frequency at which the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction is greater than the second preset deviation threshold is higher than the second preset frequency threshold, it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0115] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes the operating behavior data of the resource provider, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within the preset monitoring period, including: if the resource provider has interfered with the operation of the unit equipment without reason, then it is determined that the transaction participants have abnormal transaction behavior within the preset monitoring period.

[0116] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes resource value data of the traded power resources, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal trading behavior within the preset monitoring period, including: if the correlation coefficient between the resource value data of the traded power resources and the resource value adjustment direction of the reference power line is greater than or equal to a preset coefficient threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period; or, if the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, then it is determined that the transaction participants have abnormal trading behavior within the preset monitoring period.

[0117] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that the transaction participants belong to the same group, and within the preset monitoring period, in the transactions between the transaction participants, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than a third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction.

[0118] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the transaction-related data includes party-related data between transaction participants, then based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have abnormal transaction behavior within a preset monitoring period, including: if the party-related data indicates that within the preset monitoring period, there is a complementary transaction between a resource provider among the transaction participants and a resource demander among the transaction participants, then determining that the transaction to be monitored is an abnormal transaction.

[0119] 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, and the collection, use and processing of relevant data must comply with relevant regulations.

[0120] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method 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 memory 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), magnetic 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, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0121] 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 application.

[0122] 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 method for monitoring abnormal transaction behavior, characterized in that: include: Acquire transaction-related data of electric power resources traded by transaction participants in different dimensions within a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among the transaction participants, operating behavior data of the resource providers, resource value data of the traded electric power resources, and participant-related data between the transaction participants; Based on the matching between the transaction-related data and the standard reference data, it is determined whether the transaction participants have any abnormal transaction behavior within the preset monitoring period.

2. The method according to claim 1, characterized in that: If the transaction-related data includes the operating parameter data of the resource provider, then determining whether the transaction participant has abnormal transaction behavior within the preset monitoring period according to the matching between the transaction-related data and the standard reference data includes at least one of the following: If the adjustment frequency corresponding to the basic operating parameters of the unit equipment in the operating parameter data is greater than the first preset frequency threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period; If the parameter deviation between the key operating parameters of the unit equipment in the operating parameter data and the corresponding registered operating parameters is greater than a first preset deviation threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period; as well as, If the frequency of the output deviation between the actual output of the unit equipment in the basic operating parameters and the standard output in the dispatching instruction being greater than the second preset deviation threshold is higher than the second preset frequency threshold, it is determined that the transaction participant has abnormal trading behavior within the preset monitoring period.

3. The method according to claim 1, characterized in that If the transaction-related data includes the operational behavior data of the resource provider, then determining whether the transaction participant has abnormal transaction behavior within the preset monitoring period according to the matching between the transaction-related data and the standard reference data includes: If the resource provider has interfered with the operation of the unit equipment without reason, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period; Among them, the behavior of interfering with the operation of the unit equipment without reason includes at least one of the following: the behavior of exiting the automatic power generation control AGV service of the unit equipment without reason, the behavior of applying for unit equipment maintenance without reason, and the behavior of extending the unit equipment maintenance without reason.

4. The method according to claim 1, characterized in that: If the transaction-related data includes resource value data of the traded power resources, then determining whether the transaction participant has abnormal transaction behavior within the preset monitoring period according to the matching between the transaction-related data and the standard reference data includes: If there is a correlation coefficient between the resource value data of the traded power resource and the resource value adjustment direction of the reference power line that is greater than or equal to a preset coefficient threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period; or, If the frequency at which the resource value data of the traded power resources is lower than the reference resource value is greater than a second preset frequency threshold, it is determined that the transaction participant has abnormal transaction behavior within the preset monitoring period; Among them, the reference power line is other power lines with the same transmission section as that of the resource provider; the reference resource value is the historical resource value of the corresponding unit equipment of the resource provider, or the resource value corresponding to the same type of unit equipment as that of the corresponding unit equipment of the resource provider.

5. The method according to claim 1, characterized in that If the transaction association data includes participant association data between the transaction participants, determining whether the transaction participants have abnormal transaction behavior within the preset monitoring period according to the matching between the transaction association data and the standard reference data includes: If the party association data indicates that the transaction parties belong to the same group, and within the preset monitoring period, in the transactions between the transaction parties, there is a transaction deviation between the transaction parameters and the standard transaction parameters that is greater than a third preset deviation threshold, then the transaction to be monitored is determined to be an abnormal transaction.

6. The method according to claim 1, characterized in that If the transaction association data includes participant association data between the transaction participants, determining whether the transaction participants have abnormal transaction behavior within the preset monitoring period according to the matching between the transaction association data and the standard reference data includes: If the participant association data indicates that there is a complementary transaction between the resource provider among the transaction participants and the resource demander among the transaction participants within the preset monitoring period, then determining that the transaction to be monitored is an abnormal transaction; The complementary transaction refers to a transaction in which the supply and demand relationships of the transaction participants are opposite and the transaction parameters are similar.

7. An abnormal transaction behavior monitoring device, characterized in that: The device comprises: An acquisition module, used to acquire transaction-related data of electric power resources traded by transaction participants in different dimensions within a preset monitoring period; wherein the transaction-related data includes at least one of the following: operating parameter data of resource providers among the transaction participants, operating behavior data of the resource providers, resource value data of the traded electric power resources, and participant association data between the transaction participants; The determination module is used to determine whether the transaction participants have any abnormal transaction behavior within the preset monitoring period based on the matching between the transaction-related data and the standard reference data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. 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 6 are implemented.

10. 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 6 are implemented.

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