Power grid enterprise risk evaluation method and device, electronic equipment and storage medium
The electric power enterprise risk evaluation method addresses the challenge of ineffective risk management by dynamically weighting risk and operational indicators, resulting in improved accuracy and control capabilities for electric power enterprises.
Patent Information
- Application Number
- CN202411673542.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-21
- Publication Date
- 2025-03-28
AI Technical Summary
Electric power enterprises face challenges in managing and controlling risks effectively due to their large scale and complex nature, with traditional risk control methods failing to meet the needs for precise, intelligent, and efficient risk management, especially under changing domestic conditions and regulatory policies.
A risk evaluation method for electric power enterprises that involves assigning dynamic weights to risk indicators and operational dimension indicators based on the enterprise's class, allowing for a comprehensive and accurate risk assessment through a multi-dimensional approach.
This method enhances the accuracy and control capabilities of risk evaluation and management within electric power enterprises, enabling them to better navigate risks and improve operational efficiency.
Smart Images
Figure CN119721676A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of risk assessment for power grid enterprises, and in particular to a method, device, electronic equipment and storage medium for risk assessment for power grid enterprises. Background Art
[0002] With the national strategic deployment of preventing and defusing major risks, serving national energy security and "dual carbon" goals, and promoting the construction of a new power system, the requirements for comprehensive risk management, internal control, and compliance management of power grid companies are constantly increasing. Enterprises need to build an integrated, multi-dimensional, practical, and efficient company-level internal control risk assessment index model system to comprehensively improve production and operation levels and risk prevention capabilities. However, power grid companies are large in scale, with a large number of units and many upstream and downstream companies. Affected by changes in the domestic situation and regulatory policies, they face greater risk pressure. However, traditional risk control methods are difficult to meet the needs of efficient, accurate, and intelligent risk internal control compliance. Therefore, promoting the digital transformation of internal control risk management of power grid companies and improving the risk assessment and risk control capabilities of power grid companies are technical issues that need to be solved urgently. Summary of the invention
[0003] In view of this, the purpose of this application is to propose a risk assessment method, device, electronic device and storage medium for power grid enterprises to solve or partially solve the above-mentioned technical problems.
[0004] Based on the above objectives, this application provides a risk assessment method for power grid enterprises, including:
[0005] Obtain the first score of each risk indicator and the second score of each operating dimension indicator corresponding to the target power grid enterprise;
[0006] Obtaining a target category of a target power grid enterprise, and determining a first weight coefficient of each of the risk indicators and a second weight coefficient of each of the business dimension indicators based on the target category;
[0007] Based on the first score, the first weight coefficient, the second score and the second weight coefficient, a risk assessment result of the target power grid enterprise is obtained.
[0008] Based on the same concept, the present application also proposes a risk assessment device for a power grid enterprise, comprising:
[0009] A first acquisition module obtains a first score of each risk indicator and a second score of each operating dimension indicator corresponding to the target power grid enterprise;
[0010] A second acquisition module acquires a target category of a target power grid enterprise, and determines a first weight coefficient of each of the risk indicators and a second weight coefficient of each of the business dimension indicators based on the target category;
[0011] An evaluation module obtains a risk evaluation result of the target power grid enterprise based on the first score, the first weight coefficient, the second score and the second weight coefficient.
[0012] Based on the same concept, the present application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned risk assessment method for power grid enterprises when executing the program.
[0013] Based on the same concept, the present application also proposes a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the power grid enterprise risk assessment method as described above.
[0014] Based on the same concept, the present application also proposes a computer program product, which includes a computer program. The computer program is executed by one or more processors so that the processors execute the above-mentioned grid enterprise risk assessment method.
[0015] From the above, it can be seen that the power grid enterprise risk assessment method, device, electronic device and storage medium provided in the present application obtain the first score of each risk indicator corresponding to the target power grid enterprise and the second score of each operating dimension indicator; obtain the target category of the target power grid enterprise, and determine the first weight coefficient of each risk indicator and the second weight coefficient of each operating dimension indicator based on the target category; based on the first score, the first weight coefficient, the second score and the second weight coefficient, obtain the risk assessment result of the target power grid enterprise, and dynamically assign different weights to each risk indicator and each operating dimension indicator through the target category of the target power grid enterprise, so that the risk assessment method of the present application can be used for different power grid enterprises, and at the same time, the risk assessment results of the target power grid enterprise are determined through the two dimensions of risk indicators and operating dimension indicators, which further ensures the accuracy of the risk assessment of the power grid enterprise and improves the risk assessment and risk management capabilities of the power grid enterprise. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0017] Figure 1 A schematic diagram of an application scenario of an embodiment of the present application;
[0018] Figure 2 A schematic diagram of a process flow of a risk assessment method for a power grid enterprise according to an embodiment of the present application;
[0019] Figure 3 A schematic diagram of the structure of a risk assessment device for a power grid enterprise according to an embodiment of the present application;
[0020] Figure 4 A schematic diagram of a specific electronic device hardware structure of an embodiment of the present application. DETAILED DESCRIPTION
[0021] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.
[0022] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with general skills in the field to which the present application belongs. The "first", "second" and similar words used in the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connecting" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, which can be direct connections, indirect connections, wired connections, and wireless connections. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. In addition, in the description of the present application, unless otherwise specified, the term "multiple" refers to two or more. The term "and / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.
[0023] The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present application, and are not intended to limit the scope of the present application in any way. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.
[0024] It is understandable that before using the technical solutions of each embodiment of the present application, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.
[0025] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to the electronic device, application, server, storage medium or other software or hardware that performs the operation of the technical solution of the present application according to the prompt message.
[0026] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.
[0027] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation method of this application. Other methods that meet relevant laws and regulations may also be applied to the implementation method of this application.
[0028] It should be understood herein that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction rather than having any limiting meaning.
[0029] As described in the background technology section, with the country's strategic deployment to prevent and resolve major risks, serve national energy security and "dual carbon" goals, and promote the construction of a new power system, the requirements for comprehensive risk management, internal control, and compliance management of power grid companies are constantly increasing. Enterprises need to build an integrated, multi-dimensional, practical, and efficient company-level internal control risk assessment index model system to comprehensively improve production and operation levels and risk prevention capabilities. However, power grid companies are large in scale, have a large number of units, and have many upstream and downstream companies. Affected by changes in the domestic situation and regulatory policies, they face greater risk pressure. However, traditional risk management and control methods are difficult to meet the needs of efficient, accurate, and intelligent risk internal control compliance. Therefore, promoting the digital transformation of internal control risk management of power grid companies and improving the risk assessment and risk management capabilities of power grid companies are technical issues that need to be solved urgently.
[0030] In summary, in order to solve the above problems, the present application embodiment proposes a risk assessment method for a power grid enterprise, including:
[0031] Obtain a first score for each risk indicator and a second score for each operating dimension indicator corresponding to the target power grid enterprise; obtain a target category of the target power grid enterprise, and determine a first weight coefficient for each risk indicator and a second weight coefficient for each operating dimension indicator based on the target category; obtain a risk assessment result of the target power grid enterprise based on the first score, the first weight coefficient, the second score and the second weight coefficient, and dynamically assign different weights to each risk indicator and each operating dimension indicator through the target category of the target power grid enterprise, so that the risk assessment method of the present application can be used for different power grid enterprises, and at the same time, the risk assessment result of the target power grid enterprise is determined through the two dimensions of risk indicators and operating dimension indicators, which further ensures the accuracy of the risk assessment of the power grid enterprise and improves the risk assessment and risk management capabilities of the power grid enterprise.
[0032] In some specific application scenarios, the power grid enterprise risk assessment method of the present application can be applied to various platforms or systems involving federated learning. As an example, the application scenario includes at least one server and at least one terminal. Figure 1 , which is a schematic diagram of an application scenario of a fraud intention identification method provided by an exemplary embodiment of the present disclosure. The application scenario includes a terminal device 101, a server 102, and a data storage system 103. Among them, the terminal device 101, the server 102 and the data storage system 103 can be connected through a wired or wireless communication network. The terminal device includes but is not limited to a desktop computer, a mobile phone, a mobile computer, a tablet computer, a media player, a smart wearable device, a personal digital assistant (PDA) or other electronic devices capable of realizing the above functions. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server and the terminal can communicate through the network to realize data transmission. Among them, the network can be a wired network or a wireless network, which is not specifically limited in this application.
[0033] The server may be a server that provides various services. Specifically, the server may be used to provide background services for applications running on the terminal. Optionally, in some implementations, the fraudulent intent identification method provided in the embodiment of the present application may be executed by the server. Optionally, in some implementations, the fraudulent intent identification method provided in the embodiment of the present application may be directly executed by the terminal device.
[0034] Optionally, the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, software or software modules for providing distributed services), or it can be implemented as a single software or software module. This embodiment of the application does not specifically limit this.
[0035] Optionally, the wireless network or wired network uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network). In some embodiments, the data exchanged through the network is represented by technologies and / or formats including hypertext mark-up language (HTML), extensible markup language (XML), etc. In addition, conventional encryption technologies such as secure socket layer (SSL), transport layer security (TLS), virtual private network (VPN), and Internet protocol security (IPsec) can be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.
[0036] The data storage system stores a large amount of data. Optionally, the data storage system can partition the data according to different uses and data types. The source of the data includes but is not limited to an existing database, data crawled from the Internet, or data uploaded by the user when using the client.
[0037] The following describes the risk assessment method for power grid enterprises according to the exemplary implementation of the present application in combination with specific application scenarios. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this regard. On the contrary, the implementation of the present application can be applied to any applicable scenario.
[0038] refer to Figure 2, is a flow chart of a method for risk assessment of a power grid enterprise according to an embodiment of the present application, the method comprising the following steps:
[0039] S101, obtaining a first score for each risk indicator and a second score for each operating dimension indicator corresponding to the target power grid enterprise.
[0040] In the specific implementation, the target power grid enterprise is the enterprise that currently needs to conduct risk assessment. The specific risk indicators and business dimension indicators can be set as needed, and there is no limitation on this. Optionally, the risk indicators may include internal environment indicators, risk assessment indicators, control activity indicators, risk effectiveness indicators, risk information and reporting indicators, etc. Business dimension indicators may include operational effectiveness management indicators, profitability indicators, innovation and growth indicators, etc. After formulating the risk indicators and business dimension indicators, a scoring table can be set for each indicator, and then the first score of each risk indicator and the second score of each business dimension indicator corresponding to the target power grid enterprise can be obtained based on the scoring standard.
[0041] S102, obtaining a target category of a target power grid enterprise, and determining a first weight coefficient of each of the risk indicators and a second weight coefficient of each of the business dimension indicators based on the target category.
[0042] During specific implementation, multiple categories of power grid enterprises can be set in advance, and then the first weight coefficients of the corresponding risk indicators and the second weight coefficients of the operating dimension indicators can be configured for each category of power grid enterprises. In this way, it can be ensured that the present embodiment can be used for multiple categories of power grid enterprises. Optionally, taking a power grid enterprise of a certain target category as an example, in the first weight coefficient of the risk indicator, five aspects are set, namely, internal environment indicators, risk assessment indicators, control activity indicators, risk effectiveness indicators, and risk information and reporting indicators. The weights are 25% for internal environment evaluation, 25% for risk assessment evaluation, 20% for control activity evaluation, 20% for risk control effectiveness, and 10% for risk information reporting. The scoring standards for each detailed index evaluation are divided into 100% for section A, 75% for section B, 50% for section C, 25% for section D, and 0 for section E, with a total score of 100 points. See Table 1 below for details:
[0043]
[0044]
[0045]
[0046]
[0047] Table 1
[0048] Optionally, in some embodiments, taking a power grid enterprise of a certain target category as an example, when setting the second weight coefficient of the operating dimension indicator, the business objectives of the enterprise are fully considered, with the improvement of the company's value creation leadership ability as the main line, and the first-level indicators are set from the three aspects of operation, profitability, and innovation to comprehensively reflect the company's operation management, performance achievement and innovative growth capabilities. The weights are 50% for operational effectiveness management indicators, 30% for profitability level indicators, and 20% for innovative growth indicators. The scoring standards for each detailed index evaluation are divided into 100% for section A, 75% for section B, 50% for section C, 25% for section D, and 0 for section E, with a total score of 100 points. See Table 2 below for details:
[0049]
[0050]
[0051]
[0052] Table 2
[0053] S103: Obtain a risk assessment result of the target power grid enterprise based on the first score, the first weight coefficient, the second score, and the second weight coefficient.
[0054] In specific implementation, after determining the first weight coefficient of each risk indicator and the second weight coefficient of each operating dimension indicator, the risk assessment result of the target power grid enterprise can be directly obtained by weighted summation. Optionally, the risk assessment result of the target power grid enterprise can be a direct assessment score or a set risk level, which is not limited.
[0055] In some embodiments, based on the first score, the first weight coefficient, the second score and the second weight coefficient, obtaining the risk assessment result of the target power grid enterprise specifically includes:
[0056] Obtaining a comprehensive score of the target power grid enterprise by weighted summing the first score, the first weight coefficient, the second score and the second weight coefficient;
[0057] Determining a target preset score range in which the comprehensive score lies from a plurality of preset score ranges; wherein each preset score range corresponds to a preset risk assessment result;
[0058] The preset risk assessment result corresponding to the target preset score range is determined as the risk assessment result of the target power grid enterprise.
[0059] In specific implementation, the preset risk assessment results corresponding to each preset scoring range can be set as needed. For example, the preset risk assessment results can be set to five levels: AAA, AA, A, BBB, and BB, representing the sustainable health level of the enterprise from high to low. The specific correspondence can be referred to in Table 3 below:
[0060]
[0061]
[0062] Table 3
[0063] In order to more accurately determine the risk assessment result of the target power grid enterprise, in some embodiments, based on the first score, the first weight coefficient, the second score and the second weight coefficient, the risk assessment result of the target power grid enterprise is obtained, specifically including:
[0064] The first score, the first weight coefficient, the second score and the second weight coefficient are input into the risk assessment system obtained through training to obtain a risk assessment result of the target power grid enterprise.
[0065] In specific implementation, the training of the risk assessment system can refer to the training of neural network models in related technologies. The risk assessment system can select any model in related technologies as a benchmark model, such as convolutional neural network model (CNN), long short-term memory network (LSTM), Transformer, etc. Then, the benchmark model is trained by a large amount of labeled sample data to obtain the risk assessment system.
[0066] In some embodiments, based on the first score, the first weight coefficient, the second score and the second weight coefficient, obtaining the risk assessment result of the target power grid enterprise specifically includes:
[0067] Determine a comprehensive risk score of the target power grid enterprise based on the first score and the first weight coefficient;
[0068] Determine the comprehensive operating score of the target power grid enterprise based on the second score and the second weight coefficient;
[0069] Multiplying the comprehensive risk score by the comprehensive operation score to obtain a target comprehensive score for the target power grid enterprise;
[0070] A risk assessment result of the target power grid enterprise is obtained based on the target comprehensive score.
[0071] In specific implementation, the target comprehensive score of the target power grid enterprise can be obtained by multiplying the comprehensive risk score with the comprehensive business score. It should be noted that multiplication can not only well integrate the comprehensive risk score with the comprehensive business score, but also highlight the multiplier effect of risk control work to ensure business management. Optionally, before multiplying the comprehensive risk score with the comprehensive business score, the comprehensive risk score can be mapped to a value between 0 and 1, and then the comprehensive business score can be mapped to a value between 0 and 100, so as to ensure that the multiplication of the two can be between 0 and 100.
[0072] In some embodiments, after obtaining the first scores of each risk indicator and the second scores of each business dimension indicator corresponding to the target power grid enterprise, the method further includes:
[0073] Determine a target risk indicator from each of the risk indicators, and determine a target operating dimension indicator associated with the target risk indicator;
[0074] The first score of the target risk indicator is verified based on the second score of the target business dimension indicator.
[0075] During the specific implementation, it is taken into consideration that some risk indicators have a certain correlation with business dimension indicators. For example, when the score of a certain risk indicator is high, under normal circumstances, the corresponding business dimension indicator should also have a high score. Through such a correlation, mutual verification between risk indicators and business dimension indicators can be achieved to further ensure the accuracy of the first score and the second score obtained.
[0076] In some embodiments, verifying the first score of the target risk indicator based on the second score of the target business dimension indicator specifically includes:
[0077] Obtaining a data correlation indicator between the target risk indicator and the target business dimension indicator;
[0078] In response to determining that the second score of the target business dimension indicator and the first score of the target risk indicator meet the data correlation indicator, determining the first score of the target risk indicator as a valid score;
[0079] In response to determining that the second score of the target business dimension indicator and the first score of the target risk indicator do not meet the data correlation indicator, the first score of the target risk indicator is determined to be an invalid score.
[0080] In specific implementation, the data correlation index between the target risk indicator and the target business dimension indicator can be implemented by conducting experiments based on data. For example, the data correlation index between the target risk indicator and the target business dimension indicator can be determined by function fitting or the like, or the relationship between the two can be determined directly through a large amount of data. For example, if a certain target risk indicator is positively correlated with its corresponding target business dimension indicator, then the positive correlation can be used as the data correlation index between the target risk indicator and the target business dimension indicator. That is, when it is determined that the second score of the target business dimension indicator is positively correlated with the first score of the target risk indicator, the first score of the target risk indicator is determined as a valid score; otherwise, the first score of the target risk indicator is determined as an invalid score.
[0081] In some embodiments, after obtaining the risk assessment result of the target power grid enterprise, the method further includes:
[0082] In response to the risk assessment result of the target power grid enterprise belonging to a preset risk level, a risk warning message is issued.
[0083] In specific implementation, in order to help power grid companies discover risks in a timely manner and correct them as soon as possible, when it is determined that the risk assessment result of the target power grid company belongs to the preset risk level, a risk warning information is issued to the target power grid company.
[0084] The power grid enterprise risk assessment method provided in the present application obtains a first score for each risk indicator and a second score for each operating dimension indicator corresponding to the target power grid enterprise; obtains a target category of the target power grid enterprise, and determines a first weight coefficient for each risk indicator and a second weight coefficient for each operating dimension indicator based on the target category; obtains a risk assessment result of the target power grid enterprise based on the first score, the first weight coefficient, the second score and the second weight coefficient, and dynamically assigns different weights to each risk indicator and each operating dimension indicator through the target category of the target power grid enterprise, so that the risk assessment method of the present application can be used for different power grid enterprises, and at the same time, determines the risk assessment result of the target power grid enterprise through the two dimensions of risk indicators and operating dimension indicators, further ensuring the accuracy of the risk assessment of the power grid enterprise and improving the risk assessment and risk management capabilities of the power grid enterprise.
[0085] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a risk assessment device for a power grid enterprise.
[0086] refer to Figure 3 , the grid enterprise risk assessment device comprises:
[0087] A first acquisition module 201 acquires a first score of each risk indicator and a second score of each business dimension indicator corresponding to the target power grid enterprise;
[0088] The second acquisition module 202 acquires the target category of the target power grid enterprise, and determines the first weight coefficient of each of the risk indicators and the second weight coefficient of each of the business dimension indicators based on the target category;
[0089] The evaluation module 203 obtains a risk evaluation result of the target power grid enterprise based on the first score, the first weight coefficient, the second score and the second weight coefficient.
[0090] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.
[0091] The grid enterprise risk assessment device of the above-mentioned embodiment is used to implement the corresponding grid enterprise risk assessment method in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding grid enterprise risk assessment method embodiment, which will not be repeated here.
[0092] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the risk assessment method for a power grid enterprise described in any of the above embodiments is implemented.
[0093] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.
[0094] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0095] Figure 4A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040 and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030 and the communication interface 1040 are connected to each other in communication within the device through the bus 1050.
[0096] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.
[0097] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.
[0098] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.
[0099] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and the power equipment. The communication module can realize communication through a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WIFI, Bluetooth, etc.).
[0100] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).
[0101] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.
[0102] The electronic device of the above embodiment is used to implement the corresponding grid enterprise risk assessment method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.
[0103] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the power grid enterprise risk assessment method described in any of the above embodiments.
[0104] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.
[0105] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the risk assessment method for power grid enterprises as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0106] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a computer program product, which includes a computer program. In some embodiments, the computer program instructions can be executed by one or more processors of a computer so that the computer and / or the processor execute the risk assessment method for power grid enterprises described in the above-mentioned embodiments. Corresponding to the execution subject corresponding to each step in each embodiment of the risk assessment method for power grid enterprises, the processor that executes the corresponding step can belong to the corresponding execution subject.
[0107] To simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the following fact, that is, the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuit) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.
[0108] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.
[0109] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present application as described above, which are not provided in detail for the sake of simplicity.
[0110] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.
Claims
1. A risk assessment method for a power grid enterprise, characterized in that: include: Obtain the first score of each risk indicator and the second score of each operating dimension indicator corresponding to the target power grid enterprise; Obtaining a target category of a target power grid enterprise, and determining a first weight coefficient of each of the risk indicators and a second weight coefficient of each of the business dimension indicators based on the target category; Based on the first score, the first weight coefficient, the second score and the second weight coefficient, a risk assessment result of the target power grid enterprise is obtained.
2. The method according to claim 1, characterized in that Based on the first score, the first weight coefficient, the second score and the second weight coefficient, a risk assessment result of the target power grid enterprise is obtained, specifically including: Obtaining a comprehensive score of the target power grid enterprise by weighted summing the first score, the first weight coefficient, the second score and the second weight coefficient; Determining a target preset score range in which the comprehensive score lies from a plurality of preset score ranges; wherein each preset score range corresponds to a preset risk assessment result; The preset risk assessment result corresponding to the target preset score range is determined as the risk assessment result of the target power grid enterprise.
3. The method according to claim 1, characterized in that: Based on the first score, the first weight coefficient, the second score and the second weight coefficient, a risk assessment result of the target power grid enterprise is obtained, specifically including: The first score, the first weight coefficient, the second score and the second weight coefficient are input into the risk assessment system obtained through training to obtain a risk assessment result of the target power grid enterprise.
4. The method according to claim 1, characterized in that: Based on the first score, the first weight coefficient, the second score and the second weight coefficient, a risk assessment result of the target power grid enterprise is obtained, specifically including: Determine a comprehensive risk score of the target power grid enterprise based on the first score and the first weight coefficient; Determine the comprehensive operating score of the target power grid enterprise based on the second score and the second weight coefficient; Multiplying the comprehensive risk score by the comprehensive operation score to obtain a target comprehensive score for the target power grid enterprise; A risk assessment result of the target power grid enterprise is obtained based on the target comprehensive score.
5. The method according to claim 1, characterized in that After obtaining the first scores of the risk indicators and the second scores of the business dimension indicators corresponding to the target power grid enterprise, the method further includes: Determine a target risk indicator from each of the risk indicators, and determine a target operating dimension indicator associated with the target risk indicator; The first score of the target risk indicator is verified based on the second score of the target business dimension indicator.
6. The method according to claim 5, characterized in that Verifying the first score of the target risk indicator based on the second score of the target business dimension indicator specifically includes: Obtaining a data correlation indicator between the target risk indicator and the target business dimension indicator; In response to determining that the second score of the target business dimension indicator and the first score of the target risk indicator meet the data correlation indicator, determining the first score of the target risk indicator as a valid score; In response to determining that the second score of the target business dimension indicator and the first score of the target risk indicator do not meet the data correlation indicator, the first score of the target risk indicator is determined to be an invalid score.
7. The method according to claim 1, characterized in that After obtaining the risk assessment result of the target power grid enterprise, the method further includes: In response to the risk assessment result of the target power grid enterprise belonging to a preset risk level, a risk warning message is issued.
8. A risk assessment device for a power grid enterprise, characterized in that: include: A first acquisition module obtains a first score of each risk indicator and a second score of each operating dimension indicator corresponding to the target power grid enterprise; A second acquisition module acquires a target category of a target power grid enterprise, and determines a first weight coefficient of each of the risk indicators and a second weight coefficient of each of the business dimension indicators based on the target category; An evaluation module obtains a risk evaluation result of the target power grid enterprise based on the first score, the first weight coefficient, the second score and the second weight coefficient.
9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.
10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.