Power grid fault detection method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a power grid fault detection method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: constructing a power grid fault scene, and generating fault influence parameter information of a plurality of power grid fault points; generating a first fault influence weight based on the fault influence parameter information, detecting target fault influence parameter information, and generating a second fault influence weight based on the target fault influence parameter information and the first fault influence weight; generating a target fault influence weight of each power grid fault point according to the first fault influence weight and the second fault influence weight corresponding to each power grid fault point; based on target fault influence weights and fault influence parameter information of all power grid fault points in each power grid fault set, screening out a target power grid fault set from the plurality of power grid fault sets to update a power grid fault scene; and performing fault detection on the updated power grid fault scene. By adopting the method, the power grid fault can be accurately detected.

Description

Technical Field

[0001] The present application relates to the field of power electronics technology, and in particular to a power grid fault detection method, device, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] In the power system, ensuring the stability and reliability of the power system is crucial. To achieve this goal, grid operators usually use a series of security analysis tools and technologies to detect potential faults in the power system.

[0003] Among them, the static safety analysis method is a commonly used means of power grid fault detection. It first collects and organizes historical fault data of the power grid, including topology, equipment parameters, power generation and load forecasting information, and defines at least two groups of fault scenarios that need to be considered through expert experience and historical fault data. It then performs DC / AC power flow calculation and transient stability analysis on the network status under each fault scenario, thereby helping to identify factors that may lead to unstable or unsafe operating conditions.

[0004] However, the current power grid fault detection method has the technical problem of being inaccurate. Summary of the invention

[0005] Based on this, it is necessary to provide an accurate power grid fault detection method, device, computer equipment, computer readable storage medium and computer program product to address the above technical problems.

[0006] In a first aspect, the present application provides a power grid fault detection method, comprising:

[0007] Acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0008] For each power grid fault point, a first fault impact weight is generated based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold;

[0009] Generate a target fault impact weight for each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0010] Based on the target fault impact weights and fault impact parameter information of all grid fault points in each grid fault set, a target grid fault set is screened out from multiple grid fault sets, and based on the target grid fault set, a grid fault scenario is updated;

[0011] Perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0012] In one embodiment, the fault impact parameter information includes fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index; and the fault impact parameter information of multiple power grid fault points is generated based on the historical power grid fault data, including:

[0013] Based on the historical fault data of the power grid, the total operation time of the nodes where the faults are located at multiple power grid fault points within a preset time period, the number of faults within the total operation time of the nodes where the faults are located, the number of users affected by the faults, the power outage time affected by the faults, the amount of resources lost due to the faults, the fault redundancy, the fault repair time and the fault dispatch response time are obtained;

[0014] For each grid fault point, the fault occurrence frequency is generated based on the total operating time and number of faults of the node where the fault is located;

[0015] Generate a fault consequence severity index based on the number of users affected by the fault, the power outage time affected by the fault, and the amount of resources lost due to the fault;

[0016] Generate a fault vulnerability index based on fault frequency and fault redundancy;

[0017] A fault recovery time index is generated based on the fault repair time and the fault scheduling response time.

[0018] In one embodiment, the target fault impact parameter information includes the fault occurrence frequency and the fault consequence severity index, and the second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, including:

[0019] Generate an intermediate fault detection value based on the fault occurrence frequency and the fault consequence severity index;

[0020] A second fault impact weight is generated based on the fault intermediate detection value and the first fault impact weight.

[0021] In one embodiment, based on the target fault impact weights and fault impact parameter information of all power grid fault points in each fault set, a target fault set is screened out from multiple power grid fault sets, including:

[0022] Generate a comprehensive scoring result for each power grid fault set based on the target fault impact weights and fault impact parameter information corresponding to all power grid fault points in each power grid fault set;

[0023] The power grid fault set whose comprehensive score result is greater than the preset score threshold is taken as the target fault set.

[0024] In one embodiment, constructing a power grid fault scenario based on historical power grid fault data includes:

[0025] According to the historical fault data of the power grid, a target fault event that meets the fault event selection condition is detected from all fault events of the power grid, wherein the fault event selection condition includes at least one of the fault occurrence frequency being higher than a preset frequency threshold and the fault consequence severity index being higher than a preset consequence severity index threshold;

[0026] The target fault event is taken as the power grid fault point, and the correlation between all power grid fault points is obtained;

[0027] The power grid fault points whose correlation degree is higher than a preset correlation degree threshold value among all power grid fault points are combined respectively to obtain multiple power grid fault sets;

[0028] Gather multiple power grid fault sets and construct power grid fault scenarios.

[0029] In one embodiment, there is more than one fault impact parameter information, and generating a first fault impact weight based on the fault impact parameter information includes:

[0030] For each piece of fault influencing parameter information, obtain a fault weight coefficient of the fault influencing parameter information, and update the fault influencing parameter information based on the fault weight coefficient;

[0031] A first fault impact weight is generated according to all updated fault impact parameter information.

[0032] In a second aspect, the present application also provides a power grid fault detection device, comprising:

[0033] An acquisition module is used to acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0034] a first weight processing module, configured to generate a first fault impact weight for each power grid fault point based on the fault impact parameter information, and generate a second fault impact weight based on the target fault impact parameter information and the first fault impact weight when target fault impact parameter information in the fault impact parameter information is detected, wherein the target fault impact parameter information is fault impact parameter information having an importance higher than a preset importance threshold;

[0035] A second weight processing module, used for generating a target fault impact weight of each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0036] A power grid fault scenario updating module, used to screen out a target power grid fault set from multiple power grid fault sets based on target fault impact weights and fault impact parameter information of all power grid fault points in each power grid fault set, and update the power grid fault scenario based on the target power grid fault set;

[0037] The fault detection module is used to perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0038] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] Acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0040] For each power grid fault point, a first fault impact weight is generated based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold;

[0041] Generate a target fault impact weight for each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0042] Based on the target fault impact weights and fault impact parameter information of all grid fault points in each grid fault set, a target grid fault set is screened out from multiple grid fault sets, and based on the target grid fault set, a grid fault scenario is updated;

[0043] Perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0044] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0045] Acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0046] For each power grid fault point, a first fault impact weight is generated based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold;

[0047] Generate a target fault impact weight for each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0048] Based on the target fault impact weights and fault impact parameter information of all grid fault points in each grid fault set, a target grid fault set is screened out from multiple grid fault sets, and based on the target grid fault set, a grid fault scenario is updated;

[0049] Perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0050] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0051] Acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0052] For each power grid fault point, a first fault impact weight is generated based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold;

[0053] Generate a target fault impact weight for each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0054] Based on the target fault impact weights and fault impact parameter information of all grid fault points in each grid fault set, a target grid fault set is screened out from multiple grid fault sets, and based on the target grid fault set, a grid fault scenario is updated;

[0055] Perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0056] In the above-mentioned power grid fault detection method, device, computer equipment, computer-readable storage medium and computer program product, during the whole process, for each power grid fault point in the power grid fault scenario, the target fault impact weight obtained by combining the first fault impact weight and the second fault impact weight effectively reflects the importance of each power grid fault point in the overall fault detection, and based on the target fault impact weights and fault impact parameter information of all fault points in each fault set, more accurately identifies the target fault set that really needs to be focused on, so as to retain the power grid fault scenarios updated based on the target fault set and exclude other fault scenarios that do not need to be paid attention to, thereby effectively reducing the shortcomings of relying on expert experience and subjective judgment in traditional methods, improving the objectivity, accuracy and scientificity of fault scenario selection, and thus achieving accurate fault detection of updated power grid fault scenarios and generating power grid fault detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments of the present application or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 A diagram showing an application environment of a power grid fault detection method in an embodiment;

[0059] Figure 2 is a schematic flow chart of a power grid fault detection method in one embodiment;

[0060] Figure 3 is a flow chart of a power grid fault detection method in another embodiment;

[0061] Figure 4 is a structural block diagram of a power grid fault detection device in one embodiment;

[0062] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0063] 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 used to explain the present application and are not used to limit the present application.

[0064] The power grid fault detection method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 through a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers.

[0065] The user operates on the terminal 102 to trigger the power grid fault detection control on the interface of the terminal 102 to generate a power grid fault detection request to the server 104. The server 104 receives the power grid fault detection request, obtains the power grid historical fault data from the database, and constructs a power grid fault scenario based on the power grid historical fault data, and generates fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each fault set includes multiple power grid fault points; for each power grid fault point, based on the fault impact parameter information, a first fault impact weight is generated, and when the target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information with an importance higher than a preset importance threshold; based on the first fault impact weight and the second fault impact weight corresponding to each power grid fault point, a target fault impact weight of each fault point is generated; based on the target fault impact weight and the fault impact parameter information of all fault points in each fault set, a target fault set is screened out from multiple power grid fault sets, and based on the target fault set, the power grid fault scenario is updated; fault detection is performed on the updated power grid fault scenario to generate a power grid fault detection result. Furthermore, the power grid fault detection result may be sent to the terminal 102 and displayed to the user by the terminal 102 .

[0066] 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.

[0067] In an exemplary embodiment, Figure 2 As shown, a power grid fault detection method is provided, which is applied to Figure 1 The server 104 in FIG. 1 is used as an example for explanation. Among them:

[0068] S100, acquiring historical power grid fault data, constructing a power grid fault scenario based on the historical power grid fault data, and generating fault impact parameter information of multiple power grid fault points.

[0069] The power grid fault scenario includes multiple power grid fault sets, and each fault set includes multiple power grid fault points.

[0070] Specifically, the user operates on the terminal to trigger the power grid fault detection control on the terminal interface to generate a power grid fault detection request to the server. The server receives the power grid fault detection request, obtains the historical power grid fault data, and constructs the power grid fault scenario and the historical power grid fault data according to the historical power grid fault data, and generates the fault impact parameter information of multiple power grid fault points. Among them, the historical power grid fault data can be the data pre-acquired in the database, that is, the power grid fault data within the historical time period are all stored in the database for subsequent use, or it can be the historical power grid fault data collected in real time. The fault impact parameter information includes the fault impact parameter and the fault impact parameter data value corresponding to the fault impact parameter.

[0071] In an exemplary embodiment, collecting historical power grid fault data first requires determining data requirements, including clarifying the type of data that needs to be collected and the time range for data collection. The data type includes but is not limited to fault time, fault location, number of affected users, power outage time, direct economic loss, repair time, and dispatch response time; the time range may be data within the past three or five years.

[0072] The methods for collecting historical fault data of the power grid include but are not limited to: 1. Exporting historical alarm records and event logs from the data acquisition and monitoring control system, which usually records various abnormal conditions and fault information in the operation of the power grid; 2. Extracting historical fault records from the energy management system, which not only records the operation status of the power grid, but also contains detailed information on the fault handling and recovery process; 3. Accessing paper or electronic records of the power grid operation and maintenance department, including but not limited to fault reports, maintenance records and inspection records; 4. Accessing the internal database of the power company to extract historical fault data of the power grid, which may contain detailed fault records and related technical documents; 5. Using a third-party data service provider and requesting the third-party data service provider to provide historical fault data.

[0073] S200, for each power grid fault point, generate a first fault impact weight based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, generate a second fault impact weight based on the target fault impact parameter information and the first fault impact weight.

[0074] The target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold.

[0075] Specifically, for each power grid fault point, all fault impact parameter information is weighted to generate a first fault impact weight, which is a weight obtained after processing all fault impact parameter information and includes relevant information of all fault impact parameter information.

[0076] Furthermore, if there is more than one fault influencing parameter information, an importance evaluation value of each fault influencing parameter information is obtained, and based on the importance evaluation value of each fault influencing parameter information, target fault influencing parameter information with an importance higher than a preset importance threshold is screened out from multiple fault influencing parameter information.

[0077] When target fault impact parameter information is detected in the fault impact parameter information, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight. The second fault impact weight is a weight obtained after processing all target fault impact parameter information, and includes relevant information of all target fault impact parameter information.

[0078] In an exemplary embodiment, before obtaining the first fault impact weight, the second fault impact weight and the target fault impact weight, in order to ensure data consistency and unit uniformity, it is also necessary to uniformly perform standardization and normalization on the fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index of each grid fault point contained in each grid fault set in each grid fault scenario.

[0079] S300 , generating a target fault impact weight for each power grid fault point according to a first fault impact weight and a second fault impact weight corresponding to each power grid fault point.

[0080] Specifically, for each power grid fault point, the first fault impact weight is the relevant weight of all fault impact parameter information of the power grid fault point, and the second fault impact weight is the relevant weight of the target fault impact parameter information with higher importance of the power grid fault point, further emphasizing the key privacy in all fault impact parameter information. Combining the first fault impact weight and the second fault impact weight, all important factors can be comprehensively considered to generate the target fault impact weight of the fault point. The target fault impact weight includes both the relevant weights of all fault impact parameter information and the relevant weights of the more important target fault impact parameter information. The target fault impact weight obtained is not only more comprehensive, without missing fault impact parameter information, but also can pay more attention to the target fault impact parameter information with high importance. By combining the two fault impact weights, they can complement each other, making the power grid fault detection process based on the target fault impact weight more reliable and accurate. Further, if the first fault impact weight or the second fault impact weight is used alone, some factors may be overemphasized or ignored.

[0081] In an exemplary embodiment, generating a target fault impact weight of each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point also includes:

[0082] For each power grid fault point, obtain a first proportional coefficient of a first fault impact weight and a second proportional coefficient of a second fault impact weight, update the first fault impact weight according to the first proportional coefficient, and update the second fault impact weight according to the second proportional coefficient, and generate a target fault impact weight according to the updated first fault impact weight and the updated first fault impact weight.

[0083] Furthermore, the calculation formula of the target fault impact weight of each power grid fault point is:

[0084] w final ijk =K6w 1 ijk +K7w 2ijk

[0085] Among them, w final ijk represents the target fault impact weight of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; w 1 ijk represents the first fault impact weight of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; w 2 ijk Represents the second fault impact weight of the kth grid fault point included in the jth grid fault set in the ith grid fault scenario; K6 and K7 represent preset proportional coefficients.

[0086] S400, based on the target fault impact weights and fault impact parameter information of all grid fault points in each grid fault set, a target grid fault set is screened out from multiple grid fault sets, and a grid fault scenario is updated based on the target grid fault set.

[0087] Specifically, each power grid fault set includes multiple power grid fault points, and the target fault impact weights and fault impact parameter information of all power grid fault points in each power grid fault set are summarized to obtain the fault detection information of the power grid fault set, and then based on the fault detection information of all power grid fault sets, the target power grid fault set is screened out from the multiple power grid fault sets, and the target power grid fault set in the power grid fault scenario is retained, and the power grid fault set that has not been screened out in the power grid fault scenario is filtered out to update the power grid fault scenario.

[0088] S500, performing fault detection on the updated power grid fault scenario to generate a power grid fault detection result.

[0089] Specifically, a power flow calculation is performed on the updated power grid fault scenario, and a transient stability analysis is performed on the updated power grid fault scenario. Based on the power flow calculation results and the transient stability analysis results, a comprehensive fault detection scoring data is allocated to the updated power grid fault scenario. The comprehensive fault detection scoring data can be regarded as the power grid fault detection result of the updated power grid fault scenario.

[0090] Furthermore, if there is more than one updated power grid fault scenario, the comprehensive fault detection score data of each updated power grid fault scenario is sorted, and a power grid fault scenario sorting result is generated based on the sorting result. The power grid fault scenario sorting result can also be regarded as the power grid fault detection result of the updated power grid fault scenario.

[0091] Finally, the power grid fault detection results are presented in the form of a report, and specific improvement measures are proposed based on the power grid fault detection results, such as strengthening the transmission capacity of specific areas, adjusting the generator output plan, etc., to improve the overall safety of the system.

[0092] In an exemplary embodiment, a power flow calculation is performed on an updated power grid fault scenario, and a transient stability analysis is performed on the updated power grid fault scenario, including: performing AC / DC power flow calculation to determine the power flow after the power grid fault, checking whether the voltage level exceeds the allowable range, branch overload conditions, and generator power limitations, etc. In addition to the immediate power flow conditions, a transient stability analysis is also required to determine whether the system can recover to a normal working state after a large disturbance. According to the above calculation and analysis results, a comprehensive fault detection score data is assigned to each updated power grid fault scenario. In addition, the comprehensive fault detection level of each updated power grid fault scenario can also be determined based on the comprehensive detection score data.

[0093] In the above-mentioned power grid fault detection method, during the whole process, for each power grid fault point in the power grid fault scenario, the target fault impact weight obtained by combining the first fault impact weight and the second fault impact weight effectively reflects the importance of each power grid fault point in the overall fault detection, and based on the target fault impact weights and fault impact parameter information of all fault points in each fault set, the target fault set that really needs to be focused on is more accurately identified, so as to retain the power grid fault scenarios updated based on the target fault set, and exclude other fault scenarios that do not need to be paid attention to, thereby effectively reducing the shortcomings of relying on expert experience and subjective judgment in traditional methods, and improving the objectivity, accuracy and scientificity of fault scenario selection, thereby achieving accurate fault detection of updated power grid fault scenarios and generating power grid fault detection results.

[0094] In an exemplary embodiment, Figure 3 As shown, the fault impact parameter information includes fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index; S100 includes:

[0095] S110, acquiring historical power grid fault data, and constructing a power grid fault scenario according to the historical power grid fault data.

[0096] S120, based on the historical fault data of the power grid, obtain the total operating time of the nodes where the faults are located at multiple power grid fault points within a preset time period, the number of failures within the total operating time of the nodes where the faults are located, the number of users affected by the failures, the power outage time affected by the failures, the amount of resources lost due to the failures, the failure redundancy, the failure repair time, and the failure scheduling response time.

[0097] S130, for each power grid fault point, generating a fault occurrence frequency based on the total operating time of the node where the fault is located and the number of faults.

[0098] S140, generating a fault consequence severity index based on the number of users affected by the fault, the power outage time affected by the fault, and the amount of resources lost due to the fault.

[0099] S150: Generate a fault vulnerability index based on the fault occurrence frequency and the fault redundancy.

[0100] S160: Generate a fault recovery time index based on the fault repair time and the fault scheduling response time.

[0101] Specifically, according to the historical power grid fault data, analysis is performed on each power grid fault point included in each power grid fault set in each power grid fault scenario, and according to the analysis results, the fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index and other fault influencing parameter information of each power grid fault point included in each power grid fault set in each fault scenario are obtained respectively.

[0102] The method for obtaining parameter information affected by each fault includes:

[0103] Regarding the frequency of failure:

[0104] Based on the historical fault data of the power grid, the number of faults m within the total operating time T of the node where the fault is located within a preset time period at each power grid fault point is counted, and the fault occurrence frequency f of each power grid fault point is obtained according to the total operating time T of the node where the fault is located within the preset time period and the number of faults m. More specifically, the fault occurrence frequency f of each power grid fault point is obtained according to the ratio of the total operating time T of the node where the fault is located within the preset time period to the number of faults m.

[0105] For the severity index of failure consequences:

[0106] Based on the historical fault data of the power grid, determine the number of users N affected by the fault, the power outage time t affected by the fault, and the amount of resources lost E caused by the fault, such as direct economic losses, etc. at each power grid fault point; and based on the number of users N affected by the fault, the power outage time t affected by the fault, and the amount of resources lost E, generate the fault consequence severity index of each power grid fault point;

[0107] Among them, the generation expression of the fault consequence severity index of each power grid fault point is:

[0108] S ijk =K1N ijk +K2t ijk +K3E ijk

[0109] Among them, S ijk represents the fault consequence severity index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; N ijk represents the number of users N affected by the kth grid fault point in the jth grid fault set in the ith grid fault scenario; t ijk represents the power outage time t caused by the kth grid fault point fault included in the jth grid fault set in the ith grid fault scenario; E ijk represents the amount of fault loss resources E caused by the kth grid fault point fault included in the jth grid fault set in the i-th grid fault scenario; K1, K2, and K3 represent preset proportional coefficients.

[0110] For the Fault Vulnerability Index:

[0111] Based on the historical fault data of the power grid, determine the fault redundancy R of each power grid fault point d , based on the fault frequency f and fault redundancy R of each power grid fault point d , get the fault vulnerability index of each power grid fault point;

[0112] Among them, the calculation formula for the fault vulnerability index of each power grid fault point is:

[0113] V ijk =K4(1-R d ijk )+K5f ijk

[0114] Among them, V ijk represents the fault vulnerability index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; R d ijk represents the fault redundancy R of the kth grid fault point contained in the jth grid fault set in the i-th grid fault scenario d ;f ijk represents the fault occurrence frequency f of the kth grid fault point included in the jth grid fault set in the i-th grid fault scenario; K4 and K5 represent preset proportional coefficients.

[0115] For the fault recovery time index:

[0116] Determine the fault repair time T of each power grid fault point based on the historical power grid fault data r And the fault dispatch response time T S ; According to the fault repair time T of each power grid fault point S And fault dispatch response time T S , get the fault recovery time index of each power grid fault point;

[0117] The calculation formula of the restoration time index of each power grid fault point is:

[0118] R ijk =T r ijk +T S ijk

[0119] Among them, R ijk represents the fault recovery time index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; T r ijk represents the fault repair time T of the kth grid fault point included in the jth grid fault set in the i-th grid fault scenario r ; T S ijk represents the fault dispatch response time T of the kth grid fault point included in the jth grid fault set in the i-th grid fault scenario S .

[0120] In the above embodiment, the fault impact parameters are comprehensively generated from multiple aspects such as fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index, and accurate power grid fault detection can be performed based on the comprehensive fault impact parameters.

[0121] In an exemplary embodiment, the target fault impact parameter information includes a fault occurrence frequency and a fault consequence severity index, and generating a second fault impact weight based on the target fault impact parameter information and the first fault impact weight includes:

[0122] Based on the fault occurrence frequency and the fault consequence severity index, a fault intermediate detection value is generated, and based on the fault intermediate detection value and the first fault impact weight, a second fault impact weight is generated.

[0123] Specifically, the parameter information with higher importance in the fault impact parameter information is the fault frequency and the fault consequence severity index. Therefore, based on the fault frequency and the fault consequence severity index, the fault intermediate detection value is generated, that is, based on the ratio of the fault frequency and the fault consequence severity index, the fault intermediate detection value is generated, and based on the product of the fault intermediate detection value and the first fault impact weight, the second fault impact weight is generated. Its specific expressions include:

[0124] w 2 ijk =(w 1 ijk f ijk ) / S ijk

[0125] Among them, w 2 ijk represents the second fault impact weight of the kth grid fault point included in the jth grid fault set in the ith grid fault scenario; f ijk represents the fault occurrence frequency f of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; S ijk represents the fault consequence severity index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario, w 1 ijk Represents the first fault impact weight of the kth grid fault point included in the jth grid fault set in the i-th grid fault scenario.

[0126] Because by combining the first fault impact weight with the two key factors of fault frequency and fault consequence severity index, this design makes those grid fault points that occur frequently and have serious consequences get higher weights, and the fault frequency and fault consequence severity index are the main factors for evaluating grid fault points. They directly reflect the possibility and impact of the fault, and are the core indicators that determine the importance of the fault point. In the form of a ratio, the relationship between the fault frequency and the fault consequence severity index can be balanced. For example, if a grid fault point has a high frequency but not serious consequences, then its second fault impact weight will be relatively low; conversely, if a grid fault point has a low frequency but very serious consequences once it occurs, then its second fault impact weight will be relatively high.

[0127] It should be explained that the reason for selecting the fault frequency and fault consequence severity index as the target fault impact parameter information is that the fault frequency and fault consequence severity index are the main factors for assessing the risk of the fault point. They directly reflect the possibility and impact of the fault and are the core indicators for determining the importance of the fault point. However, although the fault vulnerability index and the fault recovery time index are also important parameters, they more reflect the characteristics and recovery capabilities of the fault point. These factors are more suitable for consideration in the comprehensive weight, that is, the target fault impact weight, rather than in the second fault impact weight. At the same time, the first fault impact weight includes all important factors, while the second fault impact weight focuses on the fault frequency and fault consequence severity index, which can ensure the hierarchy and rationality of the weight distribution. In addition, if the fault vulnerability index and the fault recovery time index are introduced again in the second fault impact weight, some factors may be over-emphasized or repeatedly calculated, thereby affecting the accuracy of the weight.

[0128] When the target fault impact weight of each power grid fault point is subsequently generated according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point, because the first fault impact weight includes multiple factors such as fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index, the second fault impact weight further emphasizes the key factors of high importance through the ratio of fault frequency and fault consequence severity index. By combining the first fault impact weight and the second fault impact weight, all important factors can be comprehensively considered to ensure that the fault impact weight of each power grid fault point is more comprehensive and accurate. It is worth noting that using the first fault impact weight or the second fault impact weight alone may cause some factors to be over-emphasized or ignored. By combining the two fault impact weights, they can complement each other and improve the reliability and accuracy of the target fault impact weight.

[0129] In this embodiment, by combining the first fault impact weight with the fault frequency and fault consequence severity index of greater importance in the fault impact parameter information, a second fault impact weight is generated, which can pay more attention to the fault impact parameter information of greater importance, making the subsequent screening of power grid fault scenarios more accurate.

[0130] In an exemplary embodiment, based on the target fault impact weights and fault impact parameter information of all power grid fault points in each power grid fault set, a target power grid fault set is screened out from multiple power grid fault sets, including:

[0131] Based on the target fault impact weights and fault impact parameter information corresponding to all grid fault points in each grid fault set, a comprehensive scoring result for each grid fault set is generated; the grid fault set whose comprehensive scoring result is greater than a preset scoring threshold is taken as the target fault set.

[0132] Specifically, based on the product sum of the target fault impact weight corresponding to each power grid fault point and the fault impact parameter information, a scoring result for each power grid fault point is generated, and based on the scoring results of all power grid fault points in each power grid fault set, a comprehensive scoring result for each power grid fault set is generated. Furthermore, power grid fault points whose comprehensive scoring results are greater than a preset scoring threshold are taken as target fault sets, and power grid fault points whose comprehensive scoring results are less than or equal to the preset scoring threshold are taken as non-target fault sets, the target fault sets in the power grid fault scenarios are retained, and the non-target fault sets in the power grid fault scenarios are filtered.

[0133] Furthermore, when the fault impact parameter information includes the fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index, a scoring result of each power grid fault point is generated based on the product sum of the target fault impact weight corresponding to each power grid fault point and the fault impact parameter information, including:

[0134] For each power grid fault point, the target fault impact weight is multiplied by the fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index respectively to obtain the weighted results of the fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index. The weighted results of the fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index are summed to obtain the scoring result.

[0135] Furthermore, based on the scoring results of all grid fault points in each grid fault set, a comprehensive scoring result of each grid fault set is generated, including: for each grid fault set, the scoring results of all grid fault points are added together to generate a comprehensive scoring result of each grid fault set.

[0136] The comprehensive score result S of each power grid fault set set ij The expression is as follows:

[0137]

[0138] Among them, S set ij represents the comprehensive scoring result of the jth grid fault set in the i-th grid fault scenario; w final ijk represents the target fault impact weight of the kth grid fault point contained in the jth grid fault set in the i-th grid fault scenario; f ijk represents the fault occurrence frequency f of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; S ijk represents the fault consequence severity index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; V ijk represents the fault vulnerability index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; R ijk represents the fault recovery time index of the kth grid fault point contained in the jth grid fault set in the ith grid fault scenario; n ij Represents the number of grid fault points included in the jth grid fault set in the i-th grid fault scenario.

[0139] In addition, it is necessary to set a preset scoring threshold for the comprehensive scoring result, and use the preset scoring threshold to screen the comprehensive scoring result of each power grid fault set in each power grid fault scenario. If the comprehensive scoring result of the current power grid fault set in the current power grid fault scenario is greater than or equal to the threshold, the current power grid fault set is retained; if the comprehensive scoring result of the current power grid fault set in the current power grid fault scenario is less than the threshold, the current power grid fault set is eliminated; the retained current power grid fault set is reassembled to form a new power grid fault scenario.

[0140] In the above embodiment, by generating a comprehensive scoring result for each power grid fault set based on the target fault impact weights and fault impact parameter information corresponding to all power grid fault points in each power grid fault set, it is possible to efficiently screen out power grid fault sets with high importance from power grid fault scenarios, and then retain those power grid fault scenarios that really need to be focused on, such as high-risk power grid fault scenarios, and exclude low-risk or unimportant power grid fault scenarios.

[0141] In an exemplary embodiment, constructing a power grid fault scenario based on historical power grid fault data includes:

[0142] According to the historical fault data of the power grid, the target fault events that meet the fault event selection conditions are detected among all the fault events of the power grid, and the target fault events are used as the power grid fault points. The correlation between all the power grid fault points is obtained, and the power grid fault points with correlation higher than the preset correlation threshold among all the power grid fault points are combined respectively to obtain multiple power grid fault sets. Multiple power grid fault sets are aggregated to construct a power grid fault scenario.

[0143] The fault event selection condition includes at least one of the following: the fault occurrence frequency is higher than a preset frequency threshold, and the fault consequence severity index exceeds a preset consequence severity index threshold.

[0144] Specifically, based on the historical fault data of the power grid, the process of constructing the power grid fault scenario is as follows:

[0145] First, typical faults among all fault events are selected: based on historical fault data, target fault events that meet the fault event selection conditions are detected among all fault events of the power grid. These events should have a high frequency of occurrence or serious consequences, and the target fault events are used as power grid fault points.

[0146] Secondly, combining grid fault points: combining the selected grid fault points into a fault set, specifically, obtaining the correlation between all grid fault points; combining the grid fault points with a correlation higher than a preset correlation threshold among all grid fault points respectively to obtain multiple grid fault sets, that is, the correlation between the grid fault points in each grid fault set is relatively high. For example, if historical fault data shows that line A often has disconnection faults and short circuit faults at positions X and Y, these two grid fault points can be combined into one grid fault set.

[0147] Finally, construct a power grid fault scenario: combine multiple power grid fault sets into one power grid fault scenario. For example, a single line fault scenario can include multiple power grid fault sets in different locations, while a multi-line simultaneous fault scenario can include multiple power grid fault sets in different lines.

[0148] In addition, when constructing a power grid fault scenario, it is also necessary to verify the rationality of the power grid fault scenario. Specific rationality verification methods include: verifying whether the defined power grid fault scenario is reasonable through expert review, ensuring that the power grid fault scenario can cover the main risk factors during fault detection, and is feasible in actual operation.

[0149] In this embodiment, by accurately and efficiently constructing power grid fault scenarios layer by layer from power grid fault points to power grid fault sets, the constructed power grid fault scenarios can cover the main risk factors during fault detection and are feasible in actual operations.

[0150] In an exemplary embodiment, there is more than one fault impact parameter information, and generating a first fault impact weight based on the fault impact parameter information includes:

[0151] For each piece of fault impact parameter information, a fault weight coefficient of the fault impact parameter information is obtained, and the fault impact parameter information is updated based on the fault weight coefficient; and a first fault impact weight is generated according to all updated fault impact parameter information.

[0152] The fault impact parameter information includes but is not limited to the fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index.

[0153] Specifically, for each fault impact parameter information, a fault weight coefficient of the fault impact parameter information is obtained, that is, the fault weight coefficient of the fault occurrence frequency, the fault weight coefficient of the fault consequence severity index, the fault weight coefficient of the fault vulnerability index and the fault recovery time index are obtained, and according to the fault weight coefficient of each fault impact parameter information, all fault impact parameter information are weighted and summed to generate a first fault impact weight, that is, based on the fault weight coefficient of each fault impact parameter information, the fault impact parameter information is updated, and then, all updated fault impact parameter information is summed to generate the first fault impact weight.

[0154] More specifically, based on the fault weight coefficient of each fault impact parameter information, the fault impact parameter information is updated, and then all updated fault impact parameter information is summed to generate a first fault impact weight, including: according to the fault occurrence frequency f ijk Fault weight coefficient , get the updated fault frequency f ijk , according to the failure consequence severity index S ijk Fault weight coefficient , get the updated failure consequence severity index S ijk , according to the fault vulnerability index V ijk Fault weight coefficient , and obtain the updated fault vulnerability index V ijk , according to the fault recovery time index R ijk Fault weight coefficient , get the updated fault recovery time index R ijk Then, the updated fault frequency f ijk , Updated Failure Consequence Severity Index S ijk , Updated Fault Vulnerability Index V ijk And the updated failure recovery time index R ijk Sum and generate the first fault impact weight w 1 ijk . Its expression is as follows:

[0155] w 1 ijk = f ijk + S ijk + Vijk + R ijk

[0156] Among them, i, j, and k respectively represent the kth grid fault point contained in the jth grid fault set in the i-th grid fault scenario.

[0157] In the above embodiment, the first fault impact weight related to all fault impact parameter information is accurately generated by acquiring the fault weight coefficient of the fault impact parameter information and performing weighted summation on the fault weight coefficient of the fault impact parameter information.

[0158] In an exemplary embodiment, the power grid fault detection method further includes:

[0159] S1: Obtain historical fault data of the power grid, and detect target fault events that meet the fault event selection conditions among all fault events of the power grid based on the historical fault data of the power grid, wherein the fault event selection conditions include at least one of the fault occurrence frequency being higher than a preset frequency threshold and the fault consequence severity index exceeding a preset consequence severity index threshold; take the target fault event as the power grid fault point, and obtain the correlation between all power grid fault points; combine the power grid fault points whose correlation is higher than the preset correlation threshold among all power grid fault points, respectively, to obtain multiple power grid fault sets; gather multiple power grid fault sets to construct a power grid fault scenario. In other words, the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points.

[0160] S2: Based on the historical fault data of the power grid, multiple fault impact parameter information is obtained, and the fault impact parameter information includes fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index.

[0161] Specifically, based on the historical fault data of the power grid, the total operating time of the nodes where the faults are located at multiple power grid fault points within a preset time period, the number of faults within the total operating time of the nodes where the faults are located, the number of users affected by the faults, the power outage time affected by the faults, the amount of resources lost due to the faults, the fault redundancy, the fault repair time, and the fault dispatch response time are obtained;

[0162] For each grid fault point, the fault occurrence frequency is generated based on the total operating time and number of faults of the node where the fault is located;

[0163] Generate a fault consequence severity index based on the number of users affected by the fault, the power outage time affected by the fault, and the amount of resources lost due to the fault;

[0164] Generate a fault vulnerability index based on fault frequency and fault redundancy;

[0165] A fault recovery time index is generated based on the fault repair time and the fault scheduling response time.

[0166] S3: For each power grid fault point, obtain the fault weight coefficient of all fault impact parameter information, and update the fault impact parameter information based on the fault weight coefficient of each fault impact parameter information; generate a first fault impact weight according to all updated fault impact parameter information.

[0167] When target fault impact parameter information in the fault impact parameter information is detected, the ratio of the fault occurrence frequency to the fault consequence severity index is multiplied by the first fault impact weight to generate a second fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold.

[0168] Finally, a target fault impact weight of each power grid fault point is generated according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point.

[0169] S4: Generate a comprehensive scoring result for each power grid fault set based on the target fault impact weights and fault impact parameter information corresponding to all power grid fault points in each power grid fault set; and take the power grid fault set whose comprehensive scoring result is greater than a preset scoring threshold as the target fault set.

[0170] S5: Perform power flow calculation on the updated power grid fault scenario, perform transient stability analysis on the updated power grid fault scenario, and assign comprehensive fault detection score data to the updated power grid fault scenario based on the power flow calculation results and the transient stability analysis results.

[0171] S6: This application can generate comprehensive fault detection scoring data for multiple power grid fault scenarios according to steps S1-S5, and sort the power grid fault scenarios based on the comprehensive fault detection scoring data of all power grid fault scenarios to obtain power grid fault detection results, and based on the power grid fault detection results.

[0172] The present application discloses a power grid fault detection method, which quantitatively analyzes the fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index of a power grid fault point, and screens the power grid fault scenarios in combination with the target fault impact weight, wherein the target fault impact weight obtained by combining the first fault impact weight and the second fault impact weight can effectively reflect the importance of each power grid fault point in the overall fault detection, and the comprehensive scoring result calculated in combination with the target fault impact weight can more accurately identify high-risk or unimportant power grid fault sets, thereby retaining those power grid fault sets that really need to be focused on, excluding low-risk or unimportant power grid fault sets, and updating the power grid fault scenarios, thereby effectively reducing the shortcomings of relying on expert experience and subjective judgment in traditional methods, and improving the objectivity, accuracy and scientificity of power grid fault scenario selection.

[0173] It should be understood that, although the steps in the flowcharts involved in the above 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 is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may 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 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.

[0174] Based on the same inventive concept, the embodiment of the present application also provides a power grid fault detection device for implementing the power grid fault detection 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 fault detection device embodiments provided below can refer to the limitations of the power grid fault detection method above, and will not be repeated here.

[0175] In an exemplary embodiment, Figure 4 As shown, a power grid fault detection device is provided, comprising: an acquisition module 100, a first weight processing module 200, a second weight processing module 300, a power grid fault scenario update module 400 and a fault detection module 500, wherein:

[0176] The acquisition module 100 is used to acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each power grid fault set includes multiple power grid fault points;

[0177] The first weight processing module 200 is used to generate a first fault impact weight for each power grid fault point based on the fault impact parameter information, and generate a second fault impact weight based on the target fault impact parameter information and the first fault impact weight when target fault impact parameter information in the fault impact parameter information is detected, wherein the target fault impact parameter information is fault impact parameter information having an importance higher than a preset importance threshold;

[0178] The second weight processing module 300 is used to generate a target fault impact weight of each power grid fault point according to the first fault impact weight and the second fault impact weight corresponding to each power grid fault point;

[0179] A power grid fault scenario updating module 400 is used to screen out a target power grid fault set from multiple power grid fault sets based on the target fault impact weights and fault impact parameter information of all power grid fault points in each power grid fault set, and update the power grid fault scenario based on the target power grid fault set;

[0180] The fault detection module 500 is used to perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

[0181] In one embodiment, the fault impact parameter information includes fault frequency, fault consequence severity index, fault vulnerability index and fault recovery time index; the acquisition module 100 is also used to obtain the total operating time of the node where the fault is located, the number of failures within the total operating time of the node where the fault is located, the number of users affected by the fault, the power outage time affected by the fault, the amount of resources lost by the fault, the fault redundancy, the fault repair time and the fault scheduling response time of multiple power grid fault points within a preset time period based on the historical power grid fault data; for each power grid fault point, the fault frequency is generated based on the total operating time of the node where the fault is located and the number of failures; the fault consequence severity index is generated based on the number of users affected by the fault, the power outage time affected by the fault and the amount of resources lost by the fault; the fault vulnerability index is generated based on the fault frequency and the fault redundancy; the fault recovery time index is generated based on the fault repair time and the fault scheduling response time.

[0182] In one embodiment, the first weight processing module 200 is further used to generate a fault intermediate detection value based on the fault occurrence frequency and the fault consequence severity index; and to generate a second fault impact weight based on the fault intermediate detection value and the first fault impact weight.

[0183] In one embodiment, the power grid fault scenario update module 400 is also used to generate a comprehensive scoring result for each power grid fault set based on the target fault impact weights and fault impact parameter information corresponding to all power grid fault points in each power grid fault set; and the power grid fault set whose comprehensive scoring result is greater than a preset scoring threshold is used as the target fault set.

[0184] In one embodiment, the acquisition module 100 is also used to detect target fault events that meet the fault event selection conditions among all fault events of the power grid based on historical fault data of the power grid, wherein the fault event selection conditions include at least one of a fault frequency higher than a preset frequency threshold and a fault consequence severity index exceeding a preset consequence severity index threshold; taking the target fault event as a power grid fault point, and obtaining the correlation between all power grid fault points; combining all power grid fault points whose correlation is higher than a preset correlation threshold respectively to obtain multiple power grid fault sets; and aggregating multiple power grid fault sets to construct a power grid fault scenario.

[0185] In one embodiment, there is more than one fault impact parameter information, and the first weight processing module 200 is further used to obtain the fault weight coefficient of the fault impact parameter information for each fault impact parameter information, and update the fault impact parameter information based on the fault weight coefficient; generate the first fault impact weight according to all updated fault impact parameter information.

[0186] Each module in the above-mentioned power grid fault detection 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.

[0187] 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. Figure 5As 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 historical fault data of the power grid. 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 power grid fault detection method is implemented.

[0188] Those skilled in the art will understand that Figure 5 The structure shown in the figure is a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0189] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0190] 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 the above-mentioned method embodiments are implemented.

[0191] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0192] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments 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 this 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.

[0193] 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.

[0194] The above 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 power grid fault detection method, characterized in that: The method comprises: Acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each of the power grid fault sets includes multiple power grid fault points; For each of the power grid fault points, a first fault impact weight is generated based on the fault impact parameter information, and when target fault impact parameter information in the fault impact parameter information is detected, a second fault impact weight is generated based on the target fault impact parameter information and the first fault impact weight, wherein the target fault impact parameter information is fault impact parameter information whose importance is higher than a preset importance threshold; Generating a target fault impact weight for each of the power grid fault points according to the first fault impact weight and the second fault impact weight corresponding to each of the power grid fault points; Based on the target fault impact weights and fault impact parameter information of all the grid fault points in each of the grid fault sets, a target grid fault set is screened out from the multiple grid fault sets, and based on the target grid fault set, the grid fault scenario is updated; Perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

2. The method according to claim 1, characterized in that The fault impact parameter information includes fault occurrence frequency, fault consequence severity index, fault vulnerability index and fault recovery time index; Based on the historical fault data of the power grid, the fault impact parameter information of multiple power grid fault points is generated, including: Based on the historical fault data of the power grid, the total operation time of the nodes where the faults are located at the multiple power grid fault points within a preset time period, the number of faults within the total operation time of the nodes where the faults are located, the number of users affected by the faults, the power outage time affected by the faults, the amount of resources lost due to the faults, the fault redundancy, the fault repair time, and the fault dispatch response time are obtained; For each of the power grid fault points, generating a fault occurrence frequency based on the total operating time of the node where the fault is located and the number of faults; Generate a fault consequence severity index based on the number of users affected by the fault, the power outage time affected by the fault, and the amount of resources lost by the fault; generating a fault vulnerability index based on the fault occurrence frequency and the fault redundancy; A fault recovery time index is generated based on the fault repair time and the fault scheduling response time.

3. The method according to claim 2, characterized in that The target fault impact parameter information includes a fault occurrence frequency and a fault consequence severity index, and generating a second fault impact weight based on the target fault impact parameter information and the first fault impact weight includes: Based on the fault occurrence frequency and the fault consequence severity index, generating a fault intermediate detection value; A second fault impact weight is generated based on the fault intermediate detection value and the first fault impact weight.

4. The method according to claim 1, characterized in that: The step of selecting a target fault set from the plurality of power grid fault sets based on the target fault impact weights and fault impact parameter information of all power grid fault points in each of the fault sets comprises: Generate a comprehensive scoring result for each of the power grid fault sets based on the target fault impact weights and the fault impact parameter information respectively corresponding to all of the power grid fault points in each of the power grid fault sets; The power grid fault set whose comprehensive scoring result is greater than a preset scoring threshold is taken as a target fault set.

5. The method according to claim 1, characterized in that The constructing of a power grid fault scenario according to the historical power grid fault data includes: According to the historical fault data of the power grid, a target fault event that meets the fault event selection condition is detected from all fault events of the power grid, wherein the fault event selection condition includes at least one of a fault occurrence frequency higher than a preset frequency threshold and a fault consequence severity index exceeding a preset consequence severity index threshold; Taking the target fault event as a power grid fault point, and obtaining the correlation between all the power grid fault points; The power grid fault points whose correlation is higher than a preset correlation threshold value among all the power grid fault points are combined respectively to obtain a plurality of power grid fault sets; The multiple power grid fault sets are collected to construct a power grid fault scenario.

6. The method according to claim 1, characterized in that The fault impact parameter information is more than one, and generating a first fault impact weight based on the fault impact parameter information includes: For each of the fault impact parameter information, obtaining a fault weight coefficient of the fault impact parameter information, and updating the fault impact parameter information based on the fault weight coefficient; A first fault impact weight is generated according to all updated fault impact parameter information.

7. A power grid fault detection device, characterized in that: The device comprises: An acquisition module is used to acquire historical power grid fault data, and construct a power grid fault scenario based on the historical power grid fault data, and generate fault impact parameter information of multiple power grid fault points, wherein the power grid fault scenario includes multiple power grid fault sets, and each of the power grid fault sets includes multiple power grid fault points; a first weight processing module, configured to generate a first fault impact weight for each of the power grid fault points based on the fault impact parameter information, and to generate a second fault impact weight based on the target fault impact parameter information and the first fault impact weight when target fault impact parameter information in the fault impact parameter information is detected, wherein the target fault impact parameter information is fault impact parameter information having an importance higher than a preset importance threshold; A second weight processing module, configured to generate a target fault impact weight for each of the power grid fault points according to the first fault impact weight and the second fault impact weight corresponding to each of the power grid fault points; A power grid fault scenario updating module, configured to screen out a target power grid fault set from the plurality of power grid fault sets based on target fault impact weights and fault impact parameter information of all power grid fault points in each of the power grid fault sets, and update the power grid fault scenario based on the target power grid fault set; The fault detection module is used to perform fault detection on the updated power grid fault scenario and generate a power grid fault detection result.

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

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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