Power grid equipment reliability evaluation method, system and device and computer equipment

Abstract

The invention relates to a power grid equipment reliability evaluation method, system and device and computer equipment. The method comprises the steps of obtaining equipment parameters and operation data of a plurality of power grid equipment in a power grid, taking the equipment parameters and the operation data as input, calling a constructed power grid equipment reliability evaluation model, simulating the operation state of the power grid under the condition that different power grid equipment breaks down under different time dimensions, obtaining stable time, and calculating the reliability of the power grid equipment. The stabilization time is the time when the power grid can maintain a normal operation state under the condition that different power grid devices have faults, determining the influence degree of the faults of the different power grid devices on the power grid based on the stabilization time, and visually displaying the stabilization time and the influence degree of the power grid under the condition that the different power grid devices have the faults. By adopting the method, the reliability evaluation accuracy of the power grid equipment can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power grid planning, and in particular to a method, system, device, computer equipment, computer-readable storage medium, and computer program product for evaluating the reliability of power grid equipment. Background Art

[0002] With the continuous development of the power system and the continuous growth of electricity demand for production and life, the scale of the current power grid is also expanding, and its structure is becoming increasingly complex. In order to improve the efficiency of power utilization, evaluating the reliability of each power grid equipment in the power grid has become a key link in the construction and operation of the power system.

[0003] Traditional solutions usually use visual inspection methods to judge the reliability of power grid equipment. For example, check whether the power grid equipment has obvious damage, deformation, corrosion, etc., and whether the connection parts of the power grid equipment are loose or hot, etc., or use historical failure rate, maintenance times and other data of the power grid equipment to evaluate the reliability of the power grid equipment.

[0004] However, the traditional method of evaluating the reliability of power grid equipment through appearance inspection is highly subjective and can only find surface defects of power grid equipment. It is difficult to evaluate the inherent faults of power grid equipment and it is difficult to specifically quantify the reliability of power grid equipment, resulting in low accuracy in the reliability assessment of power grid equipment. Summary of the invention

[0005] Based on this, it is necessary to provide a power grid equipment reliability assessment method, device, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of power grid equipment reliability assessment in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for evaluating the accuracy of reliability of power grid equipment, comprising:

[0007] Obtain equipment parameters and operating data of multiple power grid equipment in the power grid;

[0008] Taking the equipment parameters and the operation data as input, calling the constructed power grid equipment reliability assessment model, simulating the operation state of the power grid when different power grid equipment fails in different time dimensions, and obtaining the stabilization time, which is the time during which the power grid can maintain a normal operation state when different power grid equipment fails;

[0009] Based on the stabilization time, determining the impact of failures of different power grid devices on the power grid;

[0010] Visually display the stability time of the power grid and the degree of impact when different power grid equipment fails;

[0011] The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

[0012] In one embodiment, the method further comprises:

[0013] receiving a data query request, wherein the data query request carries a query parameter and a query time range;

[0014] Searching for query results matching the query parameters within the query time range from a preset database, the query results including the stability time of the power grid and the degree of impact when different power grid devices fail;

[0015] Integrate the stability time of the power grid and the impact degree to obtain an integration result;

[0016] The integration results are visualized.

[0017] In one embodiment, the visual display of the stability time and the impact degree of the power grid when different power grid equipment fails includes:

[0018] Calling a preset chart tool to display the stability time of the power grid and the degree of impact in the form of a chart when different power grid equipment fails;

[0019] The visual display of the integration result includes:

[0020] The preset chart tool is called to display the integration result in the form of a chart.

[0021] In one embodiment, after determining the degree of influence of failures of different power grid devices on the power grid based on the stabilization time, the method further includes:

[0022] Determining importance levels of different power grid devices according to the stabilization time;

[0023] A power grid maintenance strategy for the power grid is determined according to the importance levels and operation data of different power grid devices.

[0024] In one embodiment, determining the grid maintenance strategy of the grid according to the importance levels and operation data of different grid devices includes:

[0025] According to the importance levels, sorting the different power grid devices to obtain a sorting result;

[0026] Determining maintenance priorities of different power grid devices according to the sorting results;

[0027] A power grid maintenance strategy for the power grid is determined according to the maintenance priorities of the different power grid devices and the operation data.

[0028] In a second aspect, the present application also provides a power grid equipment reliability assessment system, the system comprising a server and a visualization module connected to each other;

[0029] The server is used to obtain equipment parameters and operating data of multiple power grid devices in the power grid, and use the equipment parameters and the operating data as input to call the constructed power grid equipment reliability assessment model to simulate the operating state of the power grid when different power grid devices fail in different time dimensions, and obtain the stable time, which is the time during which the power grid can maintain a normal operating state when different power grid devices fail. Based on the stable time, determine the impact of the failure of different power grid devices on the power grid, and send the stable time and the impact to the visualization module;

[0030] The visualization module is used to receive the stability time and the impact degree, and visualize the stability time of the power grid and the impact degree when different power grid devices fail;

[0031] The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

[0032] In a third aspect, the present application also provides a power grid equipment reliability assessment device, comprising:

[0033] A data acquisition module, used to acquire equipment parameters and operation data of multiple power grid equipment in the power grid;

[0034] A reliability assessment module is used to use the equipment parameters and the operation data as inputs, call the constructed power grid equipment reliability assessment model, simulate the operation state of the power grid when different power grid equipment fails in different time dimensions, and obtain the stability time, which is the time during which the power grid can maintain a normal operation state when different power grid equipment fails;

[0035] An impact degree determination module, used to determine the impact degree of failure of different power grid devices on the power grid based on the stabilization time;

[0036] A visualization display module, used for visually displaying the stability time of the power grid and the degree of impact when different power grid devices fail;

[0037] The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

[0038] In a fourth aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps in any one of the above-mentioned power grid equipment reliability assessment method embodiments when executing the computer program.

[0039] In a fifth 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 steps in any one of the above-mentioned embodiments of the method for evaluating the reliability of power grid equipment are implemented.

[0040] In a sixth aspect, the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the steps in any one of the above-mentioned power grid equipment reliability assessment method embodiments.

[0041] The above-mentioned power grid equipment reliability assessment method, system, device, computer equipment, computer-readable storage medium and computer program product are different from the appearance inspection method in the traditional scheme. In this scheme, the operating state of the power grid when different power grid equipment fails is dynamically simulated to determine the stable time for the power grid to maintain normal operation, and then the impact of the power grid equipment on the power grid is evaluated based on the stable time, thereby realizing the quantification of the reliability of the power grid equipment and significantly improving the accuracy of the reliability assessment of the power grid equipment. Furthermore, this scheme also visualizes the stable time and impact of the power grid under different power grid equipment failure conditions. This intuitive data display can provide users with clear and regular decision-making basis, improve data accessibility and data analysis efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] 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.

[0043] FIG1 is a diagram of an application environment of a method for evaluating reliability of power grid equipment in one embodiment;

[0044] Figure 2A schematic diagram of a process flow of a method for evaluating reliability of power grid equipment in one embodiment;

[0045] Figure 3 is a flow chart of a method for evaluating reliability of power grid equipment in another embodiment;

[0046] Figure 4 A schematic diagram of a flow chart of a method for evaluating reliability of power grid equipment in another embodiment;

[0047] Figure 5 is a flow chart of a method for evaluating reliability of power grid equipment in yet another embodiment;

[0048] Figure 6 A schematic diagram of a flow chart of a method for evaluating reliability of power grid equipment in yet another embodiment;

[0049] Figure 7 A schematic diagram of a flow chart of a method for evaluating reliability of power grid equipment in a detailed embodiment;

[0050] Figure 8 A structural block diagram of a power grid equipment reliability assessment system in one embodiment;

[0051] Fig. 9 is a structural block diagram of a power grid equipment reliability assessment device in one embodiment;

[0052] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] 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.

[0054] The power grid equipment reliability assessment method provided in the embodiment of the present application can be applied in the application environment shown in FIG1. ​​The terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers.

[0055] Specifically, the staff can send the equipment parameters and operation data of multiple power grid devices in the power grid to the server 104 through the terminal 102. The server 104 uses the equipment parameters and operation data as input, calls the constructed power grid equipment reliability assessment model, simulates the operation status of the power grid when different power grid devices fail in different time dimensions, and obtains the stability time, wherein the stability time is the time that the power grid can maintain a normal operation state when different power grid devices fail, and then determines the impact of the failure of different power grid devices on the power grid based on the stability time. Finally, the server 104 visualizes the stability time and impact of the power grid when different power grid devices fail, wherein the power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data, and historical failure records of multiple power grid devices.

[0056] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices may be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server 104 may be an independent physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0057] In an exemplary embodiment, Figure 2 As shown, a method for evaluating the reliability of power grid equipment is provided, which is described by taking the method applied to the server 104 in FIG. 1 as an example, and includes the following steps:

[0058] S100, obtaining equipment parameters and operation data of multiple power grid equipment in the power grid.

[0059] Among them, power grid equipment includes but is not limited to transformers, generators, cables, switches and other equipment in the power grid. Taking the transformer as an example, the equipment parameters include but are not limited to the rated capacity, impedance, rated voltage, etc. of the transformer. Taking the switch as an example, the equipment parameters include but are not limited to the rated voltage and rated current of the switch. Operation data includes but is not limited to the real-time power, real-time voltage, real-time current, operating frequency, operating temperature, etc. of the power grid equipment.

[0060] Specifically, the equipment parameters of the power grid equipment may be pre-stored in the data storage system of the server, and the operation data of the power grid equipment may be collected in real time by sensors deployed near each power grid equipment.

[0061] S200, taking equipment parameters and operation data as input, calling the constructed power grid equipment reliability assessment model, simulating the operation status of the power grid when different power grid equipment fails in different time dimensions, and obtaining the stabilization time.

[0062] Among them, the stability time is the time that the power grid can maintain normal operation when failures occur in different power grid equipment. The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical failure records of multiple power grid equipment.

[0063] It should be noted that, in this embodiment, the stabilization time can also be considered as the N-1 passing time of the power grid, and the power grid equipment reliability assessment model is also constructed based on the N-1 criterion of the power grid. The N-1 criterion is one of the important criteria for evaluating the safety of the power system, which means that in the normal operating state of the power system, after any power grid equipment (such as lines, generators, transformers, etc.) in the power system is disconnected due to a fault (or there is no fault but the disconnection is used to simulate the situation of a fault), the power system should be able to maintain stable operation and normal power supply, and other power grid equipment does not exceed the load, and the voltage and frequency are within the allowable range, and the N-1 passing time refers to the length of time that other power grid equipment in the power system can still maintain normal operation under the N-1 condition, that is, the stability time for the power system to maintain normal operation.

[0064] For example, before reliability assessment is performed, a reliability assessment model for power grid equipment is constructed based on the historical equipment parameters, historical operation data, historical fault records of power grid equipment in the power grid, and the network structure of the power grid, based on the N-1 criterion. Thus, when performing reliability assessment, the reliability assessment model for power grid equipment is called to simulate the operation status of the power grid when different power grid equipment fails in different time dimensions, and obtain the stabilization time.

[0065] Specifically, when it is necessary to simulate the failure of different power grid equipment, it is only necessary to modify the corresponding model parameters in the power grid equipment reliability assessment model, so that the power grid equipment reliability assessment model can simulate the operating state of the power grid when any equipment fails, and because the power grid equipment reliability assessment model has learned the association between historical equipment parameters, historical operating data and historical failure records of multiple power grid equipment during the training phase, it can output the stability time of the power grid when different power grid equipment fails in different time dimensions. It should be noted that the stability time of the power grid in different time dimensions may include, but is not limited to, the stability time of the power grid when a certain power grid equipment fails at the current moment, the stability time of the power grid when a certain power grid equipment fails at any moment in the future, etc.

[0066] S300, based on the stabilization time, determining the impact of failures of different power grid devices on the power grid.

[0067] Following the above steps, based on the stabilization time of the power grid when different power grid devices fail in different time dimensions, the impact of power grid failure on the power grid can be further analyzed. For example, if a certain power grid device A fails, the stabilization time of the power grid is 10 minutes, and if another power grid device B fails, the stabilization time of the power grid is 8 minutes. It can be analyzed that compared with power grid device A, the power grid is more affected when power grid device B fails.

[0068] Among them, the impact of failures of different power grid equipment on the power grid can be expressed by the impact level. For example, when a certain power grid equipment fails, the stabilization time of the power grid is within 0-5 minutes, and the corresponding impact level of the power grid equipment is severe impact. If the power grid stabilization time is within 5-10 minutes, the corresponding impact level of the power grid equipment is moderate impact. If the power grid stabilization time exceeds 10 minutes, the corresponding impact level of the power grid equipment is slight impact. The above specific stabilization time range can be set according to actual conditions.

[0069] S400 will visualize the grid stability time and impact level when different grid equipment fails.

[0070] Furthermore, in order to improve the efficiency of data access, the stability time and impact degree determined by the above steps can also be visualized, for example, in the form of charts and tables, so as to comprehensively present the operating status of the power grid and the reliability evaluation results of each power grid equipment.

[0071] For example, a user-friendly visualization interface is presented through a terminal connected to the server, through which users can query, analyze and make decisions on data. The visualization interface can display the data that users expect to query, such as the stability time and impact degree of the power grid, through a variety of data display methods such as tables and tables.

[0072] The above-mentioned power grid equipment reliability assessment method is different from the appearance inspection method in the traditional scheme. In this scheme, the operating state of the power grid when different power grid equipment fails is dynamically simulated to determine the stable time for the power grid to maintain normal operation, and then the impact of the power grid equipment on the power grid is evaluated based on the stable time, thereby realizing the quantification of the reliability of the power grid equipment and significantly improving the accuracy of the reliability assessment of the power grid equipment. Furthermore, this scheme also visualizes the stable time and impact of the power grid under different power grid equipment failure conditions. This intuitive data display can provide users with a clear and regular decision-making basis, improving data accessibility and data analysis efficiency.

[0073] In an exemplary embodiment, Figure 3 As shown, the method also includes:

[0074] S510: Receive a data query request, where the data query request carries a query parameter and a query time range.

[0075] S520, searching a preset database for query results that match the query parameters within a query time range.

[0076] S530, integrating the stability time and impact degree of the power grid to obtain an integration result.

[0077] S540, visually display the integration result.

[0078] Among them, a data query request refers to a request for querying specific data sent by a user or system to a server through an interface, and a query parameter is a condition used to limit the query content. For example, a query parameter can be the name of a specific power grid device, the type of power grid device, the device number, the device parameters, etc. The query time range is used to limit the time span of the query content. For example, if a user wants to query the stability time of the power grid when a certain power grid device fails one month in the future, the query time range is one month in the future, and the query parameter can be the device number of the power grid device. The query results include the stability time and impact degree of the power grid when different power grid devices fail. The database may include but is not limited to power grid planning data, power grid equipment data, grid data and other data.

[0079] Specifically, a user can initiate a data query request through a front-end device. After the data query request is transmitted to a back-end server through a network, the server parses the query parameters and query time range carried in the data query request through a specific interface, and then retrieves relevant data from a preset database based on the query parameters and query time range, thereby finding a query result that includes the stability time and impact degree of the power grid that matches the query parameters.

[0080] Furthermore, the stability time and impact degree of the found power grid are integrated and summarized for analysis. For example, when the user hopes to inquire about the stability time and impact degree of the power grid when any power grid equipment fails within the next month, after the server finds the stability time and impact degree corresponding to each power grid equipment, it can further integrate the corresponding stability time and impact degree of each power grid equipment, such as classifying the data according to the type of power grid equipment, comparing the impact degree and corresponding stability time of different power grid equipment, analyzing the reliability of each type of equipment, etc., to obtain an integrated result.

[0081] Finally, the integration results are intuitively presented to the user in the form of graphs, charts, tables, etc., such as line graphs, bar graphs, pie charts, etc. For example, a pie chart can be used to represent the proportion of stable time corresponding to different power grid equipment. The larger the proportion, the smaller the impact of the power grid equipment on the power grid. For the same power grid equipment, a line graph can be used to represent the trend of stable time corresponding to the power grid equipment over time.

[0082] In this embodiment, by combining the query parameters and the query time range, the query results that match the user's expectations can be quickly found from the database, and the stability time and impact degree in the query results can be further integrated, and the integrated results of the data can be presented in a visual manner, which can improve the accessibility and analysis efficiency of the data, and also provide an intuitive basis for subsequent users' power grid planning and decision-making.

[0083] In an exemplary embodiment, Figure 4 As shown, S400 includes:

[0084] S410, calling a preset chart tool to display the stability time and impact degree of the power grid in the form of a chart when different power grid equipment fails.

[0085] S540 includes:

[0086] S541, calling a preset chart tool to display the integration result in the form of a chart.

[0087] The preset chart tool refers to a visualization tool built into or integrated in the server, which can display data through various types of charts, such as line charts, bar charts, pie charts, etc.

[0088] Specifically, the server can directly call the preset chart tool through a specific interface, and import the data such as the stability time and impact degree of the power grid, query results, etc. into the chart tool to generate the corresponding chart. For example, a line chart can be used to show the changing trend of the stability time of the power grid when a certain power grid equipment fails in different time dimensions, and a bar chart or pie chart can be used to show the stability time of different power grid equipment.

[0089] In this embodiment, by visualizing the data, a global perspective of the power grid operation can be provided to the user, which not only improves the data processing capability and analysis accuracy of the power grid, but also enhances the decision-making efficiency of the user's subsequent project scheduling and resource optimization, making the power grid planning more intelligent and efficient.

[0090] In an exemplary embodiment, Figure 5 As shown, the method also includes:

[0091] S610, determining importance levels of different power grid devices according to the stabilization time.

[0092] S620, determining a power grid maintenance strategy for the power grid according to the importance levels and operation data of different power grid devices.

[0093] The importance level is determined based on the impact of the power grid equipment on the overall operation of the power grid. The higher the importance level of the power grid equipment, the more important the equipment is to the stability and operational safety of the power grid. The power grid maintenance strategy includes but is not limited to the regular inspection frequency of power grid equipment, maintenance plan, and replacement frequency of power grid equipment.

[0094] Specifically, the server determines the stability time of the power grid when various power grid devices fail through the steps in the above embodiments. Since the stability time reflects how long the power grid can maintain normal operation, if a certain power grid device fails, the stability time of the power grid is very short, which means that when the power grid device fails, the power grid will quickly face operational risks, so the importance level of the power grid device is relatively high.

[0095] Furthermore, the server will formulate a power grid maintenance strategy based on the importance level of the power grid equipment and the operation data of the power grid equipment. The operation data of the power grid equipment includes but is not limited to the real-time voltage, real-time current, real-time power, etc. of the power grid equipment. The server can formulate a corresponding maintenance plan based on the operation data of the power grid equipment, and determine which power grid equipment should be repaired first based on the importance level of the power grid equipment, for example, the power grid data with a high importance level should be repaired first.

[0096] In this embodiment, a power grid maintenance strategy is formulated based on the importance level and operating data of the power grid equipment. The importance level determines the priority of each device, and the operating data reflects the current health status and operating performance of the power grid equipment. By combining these two aspects of information, a targeted power grid maintenance strategy can be formulated quickly and accurately, and important power grid equipment is maintained first, thereby improving the reliability and stability of the power grid.

[0097] In an exemplary embodiment, Figure 6 As shown, S620 includes:

[0098] S621, sorting different power grid devices according to their importance levels to obtain sorting results.

[0099] S622: Determine maintenance priorities of different power grid devices according to the sorting results.

[0100] S623, determining a power grid maintenance strategy for the power grid according to maintenance priorities and operation data of different power grid devices.

[0101] Among them, the sorting results are the basis for formulating power grid maintenance strategies and are used to determine the order of maintenance and inspection of power grid equipment.

[0102] Specifically, the server sorts all power grid equipment according to their importance levels. The sorting is based on the corresponding stabilization time, impact level, and real-time operation data of the power grid equipment. For example, power grid equipment with a high importance level usually has a shorter stabilization time and a greater impact level. Therefore, power grid equipment with a high importance level is sorted higher and has a higher maintenance priority in subsequent maintenance and inspection links.

[0103] Furthermore, after the maintenance priority of the power grid equipment is determined, a maintenance plan can be formulated for each power grid equipment based on the maintenance priority of the power grid equipment and the operation data of the power grid equipment, combined with the overall operation status of the power grid, to form a power grid maintenance strategy. For example, more frequent inspections and fault warnings can be arranged for power grid equipment with a higher maintenance priority.

[0104] In this embodiment, the power grid maintenance strategy formulated according to the operation data and maintenance priority of the power grid equipment can reduce the failure risk of those power grid equipments that have a great impact on the power grid as much as possible, thereby improving the stability and operation efficiency of the power grid.

[0105] In order to make a clearer description of the power grid equipment reliability assessment method provided by the present application, the following is a specific embodiment and the attached Figure 7 To illustrate, this specific embodiment includes the following steps:

[0106] S701, obtaining equipment parameters and operation data of multiple power grid equipment in the power grid.

[0107] S702, using equipment parameters and operation data as input, calling the constructed power grid equipment reliability assessment model, simulating the operation status of the power grid when different power grid equipment fails in different time dimensions, and obtaining the stabilization time.

[0108] S703, based on the stabilization time, determine the impact of the failure of different power grid equipment on the power grid, call a preset chart tool, and display the stabilization time and impact of the power grid in the form of a chart when the failure of different power grid equipment occurs.

[0109] S704: Receive a data query request, where the data query request carries query parameters and a query time range.

[0110] S705, searching a preset database for query results that match the query parameters within a query time range, wherein the query results include the stability time and impact degree of the power grid when different power grid equipment fails.

[0111] S706, integrating the stability time and impact degree of the power grid to obtain an integration result, calling a preset chart tool, and displaying the integration result in the form of a chart.

[0112] S707, determining the importance levels of different power grid devices according to the stabilization time, and sorting the different power grid devices according to the importance levels to obtain a sorting result.

[0113] S708, determining maintenance priorities of different power grid devices according to the sorting results, and determining a power grid maintenance strategy of the power grid according to the maintenance priorities and operation data of the different power grid devices.

[0114] In an exemplary embodiment, a power grid equipment reliability assessment system 800 is provided, including a server 810 and a visualization module 820 connected to each other.

[0115] The server 810 is used to obtain equipment parameters and operation data of multiple power grid devices in the power grid, and use the equipment parameters and operation data as input to call the constructed power grid equipment reliability assessment model, simulate the operation state of the power grid when different power grid devices fail in different time dimensions, and obtain the stabilization time, which is the time during which the power grid can maintain a normal operation state when different power grid devices fail. Based on the stabilization time, determine the impact of the failure of different power grid devices on the power grid, and send the stabilization time and the impact to the visualization module 820;

[0116] A visualization module 820 is used to receive the stability time and the impact degree, and visualize the stability time and the impact degree of the power grid when different power grid equipment fails;

[0117] Among them, the reliability assessment model of power grid equipment is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment. The visualization module 820 in this embodiment can be a front-end display screen, which can not only visualize the stability time and impact degree obtained by the background server analysis, but also realize the data query function in response to the user's touch operation. In addition, the server 810 can also realize real-time processing, storage and analysis of data collected by sensors in the power grid in real time through digital technology (such as the Internet of Things, cloud computing, big data analysis, etc.), thereby improving the system's data processing capability and analysis accuracy, and then present the data processing results through the visualization module 820, providing strong technical support for power grid planning and decision-making.

[0118] In addition, the server 810 can also analyze the operating data of various data sources in the power grid in real time, such as EMS real-time data, state estimation data, PMU data, etc. It can also combine the patrol stations with multiple perceptions in the power grid, integrate the data collected in real time by the intelligent patrol system in the patrol stations, and display the operating data in the above-mentioned power grid and the data integration results of the intelligent patrol system through the visualization module 820 in a dynamic, three-dimensional, and virtual reality manner, thereby realizing panoramic data management, visualization of operating status, intelligent analysis of anomalies, and efficient operation and maintenance inspections, reducing the workload of operation and maintenance, and improving operation and maintenance efficiency.

[0119] It should be noted that the specific data processing steps when the server 810 calls the constructed power grid equipment reliability assessment model have been described in detail in the above-mentioned power grid equipment reliability assessment method embodiment, and will not be repeated here.

[0120] 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.

[0121] Based on the same inventive concept, the embodiment of the present application also provides a power grid equipment reliability assessment device for implementing the power grid equipment reliability assessment 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 power grid equipment reliability assessment device embodiments provided below can refer to the limitations of the power grid equipment reliability assessment method above, and will not be repeated here.

[0122] In an exemplary embodiment, Fig. 9 As shown, a power grid equipment reliability assessment device 900 is provided, comprising: a data acquisition module 910, a reliability assessment module 920, an impact degree determination module 930 and a visualization display module 940, wherein:

[0123] The data acquisition module 910 is used to acquire device parameters and operation data of multiple power grid devices in the power grid.

[0124] The reliability assessment module 920 is used to call the constructed power grid equipment reliability assessment model with the equipment parameters and the operating data as input, simulate the operating state of the power grid when different power grid equipment fails in different time dimensions, and obtain the stabilization time. The stabilization time is the time during which the power grid can maintain a normal operating state when different power grid equipment fails.

[0125] The impact degree determination module 930 is used to determine the impact degree of the failure of different power grid devices on the power grid based on the stabilization time.

[0126] The visualization display module 940 is used to visualize the stability time of the power grid and the impact degree when different power grid equipment fails.

[0127] The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

[0128] In an exemplary embodiment, the power grid equipment reliability assessment device 900 is also used to receive a data query request, which carries a query parameter and a query time range, and searches a preset database for query results that match the query parameters within the query time range. The query results include the stability time and the degree of impact of the power grid in the event of failure of different power grid equipment, integrate the stability time and the degree of impact of the power grid to obtain an integrated result, and visualize the integrated result.

[0129] In an exemplary embodiment, the visualization display module 940 is also used to call a preset chart tool to display the stability time of the power grid and the degree of impact in the form of a chart when different power grid equipment fails, and to call a preset chart tool to display the integration result in the form of a chart.

[0130] In an exemplary embodiment, the power grid equipment reliability assessment device 900 is also used to determine the importance levels of different power grid equipment according to the stabilization time, and determine the power grid maintenance strategy of the power grid according to the importance levels and operation data of different power grid equipment.

[0131] In an exemplary embodiment, the power grid equipment reliability assessment device 900 is also used to sort the different power grid equipment according to the importance levels to obtain sorting results, determine the maintenance priorities of the different power grid equipment according to the sorting results, and determine the power grid maintenance strategy of the power grid according to the maintenance priorities of the different power grid equipment and the operating data.

[0132] Each module in the above-mentioned power grid equipment reliability assessment device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0133] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.10 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as equipment parameters and operating data of multiple power grid devices. 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 through a network connection. When the computer program is executed by the processor, a method for evaluating the reliability of power grid equipment is implemented.

[0134] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0135] 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 steps in any one of the above-mentioned power grid equipment reliability assessment method embodiments are implemented.

[0136] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in any one of the above-mentioned power grid equipment reliability assessment method embodiments are implemented.

[0137] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps in any one of the above-mentioned power grid equipment reliability assessment method embodiments.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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 evaluating the reliability of power grid equipment, characterized in that: The method comprises: Obtain equipment parameters and operating data of multiple power grid equipment in the power grid; Taking the equipment parameters and the operation data as input, calling the constructed power grid equipment reliability assessment model, simulating the operation state of the power grid when different power grid equipment fails in different time dimensions, and obtaining the stabilization time, which is the time during which the power grid can maintain a normal operation state when different power grid equipment fails; Based on the stabilization time, determining the impact of failures of different power grid devices on the power grid; Visually display the stability time of the power grid and the degree of impact when different power grid equipment fails; The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

2. The method according to claim 1, characterized in that The method further comprises: receiving a data query request, wherein the data query request carries a query parameter and a query time range; Searching for query results matching the query parameters within the query time range from a preset database, the query results including the stability time of the power grid and the degree of impact when different power grid devices fail; Integrate the stability time of the power grid and the impact degree to obtain an integration result; The integration results are visualized.

3. The method according to claim 2, characterized in that The visual display of the stability time and the impact degree of the power grid when different power grid equipment fails includes: Calling a preset chart tool to display the stability time of the power grid and the degree of impact in the form of a chart when different power grid equipment fails; The visual display of the integration result includes: The preset chart tool is called to display the integration result in the form of a chart.

4. The method according to any one of claims 1 to 3, characterized in that: After determining the degree of influence of failures of different power grid devices on the power grid based on the stabilization time, the method further includes: Determining importance levels of different power grid devices according to the stabilization time; A power grid maintenance strategy for the power grid is determined according to the importance levels and operation data of different power grid devices.

5. The method according to claim 4, characterized in that Determining the grid maintenance strategy of the grid according to the importance levels and operation data of different grid devices includes: According to the importance levels, sorting the different power grid devices to obtain a sorting result; Determining maintenance priorities of different power grid devices according to the sorting results; A power grid maintenance strategy for the power grid is determined according to the maintenance priorities of the different power grid devices and the operation data.

6. A power grid equipment reliability assessment system, characterized in that: The system includes a server and a visualization module connected to each other; The server is used to obtain equipment parameters and operating data of multiple power grid devices in the power grid, and use the equipment parameters and the operating data as input to call the constructed power grid equipment reliability assessment model to simulate the operating state of the power grid when different power grid devices fail in different time dimensions, and obtain the stable time, which is the time during which the power grid can maintain a normal operating state when different power grid devices fail. Based on the stable time, determine the impact of the failure of different power grid devices on the power grid, and send the stable time and the impact to the visualization module; The visualization module is used to receive the stability time and the impact degree, and visualize the stability time of the power grid and the impact degree when different power grid devices fail; The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

7. A power grid equipment reliability assessment device, characterized in that: The device comprises: A data acquisition module, used to acquire equipment parameters and operation data of multiple power grid equipment in the power grid; A reliability assessment module is used to use the equipment parameters and the operation data as inputs, call the constructed power grid equipment reliability assessment model, simulate the operation state of the power grid when different power grid equipment fails in different time dimensions, and obtain the stability time, which is the time during which the power grid can maintain a normal operation state when different power grid equipment fails; An impact degree determination module, used to determine the impact degree of failure of different power grid devices on the power grid based on the stabilization time; A visualization display module, used for visually displaying the stability time of the power grid and the degree of impact when different power grid devices fail; The power grid equipment reliability assessment model is constructed based on historical equipment parameters, historical operation data and historical fault records of multiple power grid equipment.

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 5 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 5 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 5 are implemented.

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