Power grid risk identification method and system based on topological analysis

Abstract

The present invention discloses a power grid risk identification method and system based on topology analysis, including hierarchically dividing a power grid, dividing the power grid into three layers according to the composition relationship of the power grid; obtaining a physical connection model between the second-layer structures of the power grid, and converting the physical connection model into a topology model based on the electrical connection relationship between the second-layer structures of the power grid; obtaining various parameters of the second-layer structures of the power grid, and converting the topology model into a weighted topology model based on the various parameters of the second-layer structures of the power grid; based on the weighted topology model and combining the various parameters of the second-layer structures of the power grid, obtaining the influence factors between the second-layer structures of the power grid; identifying and predicting the power grid risk according to the influence factors between the second-layer structures of the power grid. This method realizes the analysis of equipment operation risks from the level of the power grid, can predict the failure risks of other equipment through the failed equipment, comprehensively reflects the overall risk state of the power grid, and reduces the overall operation risk of the power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of power grid security, and particularly relates to a power grid risk identification method and system based on topological analysis. Background Art

[0002] In the power industry, the safe operation of the power grid is an extremely important issue. The operation risks or faults of power transmission stations will bring great harm to power transmission. Failure to timely identify faulty power transmission stations may further lead to the escalation of power grid accidents, and may even cause large-scale power outages and paralysis of local power grids. Moreover, the harm caused by the faults of power transmission stations to other power supply stations in the power grid needs to be considered, that is, it is necessary to analyze the equipment operation risks from the perspective of the power grid.

[0003] In addition, the urban power grid is large in scale and there are numerous power transmission stations. Generally, the operation risks of individual equipment are analyzed in the power grid, which is difficult to comprehensively reflect the overall risk state of the power grid and is not conducive to reducing the overall operation risk of the power grid. Summary of the Invention

[0004] In view of the problems existing in the above-mentioned prior art, the present invention provides a power grid risk identification method and system based on topological analysis, which takes power transmission stations as objects to identify and predict power grid risks through a topological model, thereby reducing the operation risk of the power grid.

[0005] The first aspect of the embodiment of the present invention provides a power grid risk identification method based on topological analysis, and the method includes:

[0006] Dividing the power grid into layers, and dividing the power grid into three layers according to the composition relationship of the power grid;

[0007] Obtaining a physical connection model between the second-layer structures of the power grid, and converting the physical connection model into a topological model based on the electrical connection relationship between the second-layer structures of the power grid;

[0008] Obtaining various parameters of the second-layer structure of the power grid, and converting the topological model into a weighted topological model based on the various parameters of the second-layer structure of the power grid;

[0009] Based on the weighted topological model and combined with the various parameters of the second-layer structure of the power grid, obtaining the influence factors between the second-layer structures of the power grid;

[0010] Identifying and predicting power grid risks according to the influence factors between the second-layer structures of the power grid.

[0011] As a further optimization of the above solution, the specific process of dividing the power grid into three layers includes: dividing the power grid into three-layer structures of power grid, power supply stations, and power grid equipment, where the power supply nodes are the second-layer structures of the power grid.

[0012] As a further optimization of the above solution, the specific steps for converting the physical connection model into a topological model based on the electrical connection relationship between the second-layer structures of the power grid are as follows:

[0013] S1. Select two second-layer structures of the power grid in the physical connection model in sequence.

[0014] S2. Determine whether the two selected second-layer structures of the power grid are physically connected. If not, reselect.

[0015] S3. If so, further determine whether the two selected second-layer structures of the power grid are electrically connected. If so, retain the physical connection relationship between the two selected second-layer structures of the power grid.

[0016] S4. If not, delete the physical connection relationship between the two selected second-layer structures of the power grid.

[0017] S5. Repeat the above steps S1 - S4 until all the second-layer structures of the power grid in the physical connection model are judged, and the obtained model is the topological model.

[0018] As a further optimization of the above solution, the parameters of the second-layer structure of the power grid include: the maximum load of the second-layer structure, the rated output voltage of the second-layer structure, the rated input voltage of the second-layer structure, and the weight of the weighted topological model is the power supply voltage between the second-layer structures of the power grid.

[0019] As a further optimization of the above solution, the specific process for obtaining the influence factor between the second-layer structures of the power grid is as follows:

[0020] Randomly select a second-layer structure of the power grid, and obtain all the topological paths in the weighted topological model that contain the selected second-layer structure of the power grid.

[0021] Traverse from the selected second-layer structure of the power grid to both ends of its topological path in sequence, and detect whether all the second-layer structures on the topological path output voltage to the selected second-layer structure of the power grid.

[0022] If so, retain the topological path. If not, screen out the first second-layer structure that does not output voltage and the topological path before or after it.

[0023] Based on the screened topological paths, calculate the influence factor of the second-layer structures of the power grid on the selected second-layer structure of the power grid in the topological path in sequence.

[0024] As a further optimization of the above solution, the influence factor between the second-layer structures of the power grid is determined by the power supply voltage between the second-layer structures of the power grid. Among them, the closer the two second-layer structures on the same topological path are, the greater the influence factor.

[0025] As a further optimization of the above solution, the identification and prediction of power grid risks according to the influencing factors between the second-layer structures of the power grid specifically include:

[0026] Obtain the real-time weighted topology model of the power grid, and match the obtained real-time weighted model with the standard weighted topology model of the power grid;

[0027] If the matching results are different, it indicates that there is a fault in the power grid;

[0028] Judge whether the number of nodes in the real-time weighted model is the same as that in the standard weighted topology model of the power grid. If the number of nodes is different, it indicates that a power failure fault has occurred in the second-layer structure of the power grid;

[0029] If they are the same, then compare the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topology model of the power grid;

[0030] If the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topology model of the power grid are different, it indicates that there is a fault in this second-layer structure;

[0031] Based on the faulty second-layer structure, the fault risks of the remaining second-layer structures can be predicted.

[0032] The second aspect of the embodiment of the present invention provides a power grid risk identification system based on topological analysis, and the system includes:

[0033] A layering module for hierarchically dividing the power grid and dividing the power grid into three layers according to the composition relationship of the power grid;

[0034] A model construction module for obtaining the physical connection model between the second-layer structures of the power grid;

[0035] A topology construction module for converting the physical connection model into a topology model based on the electrical connection relationship between the second-layer structures of the power grid;

[0036] Obtain the parameters of the second-layer structure of the power grid, and convert the topology model into a weighted topology model based on the parameters of the second-layer structure of the power grid;

[0037] Based on the weighted topology model and in combination with the parameters of the second-layer structure of the power grid, obtain the influencing factors between the second-layer structures of the power grid;

[0038] A risk analysis module for identifying and predicting power grid risks according to the influencing factors between the second-layer structures of the power grid.

[0039] The third aspect of the embodiment of the present invention provides a readable storage medium, on which an executable program is stored, and when the program is executed by a processor, it implements the above-mentioned power grid risk identification method based on topological analysis.

[0040] In a third aspect of the embodiments of the present invention, a device is provided, including a memory, a processor, and an executable program stored on the memory and running on the processor. When the processor executes the program, the above-mentioned power grid risk identification method based on topological analysis is implemented.

[0041] The power grid risk identification method and system based on topological analysis of the present invention have the following beneficial effects:

[0042] In the present invention, the power grid is divided into three layers, and taking the power transmission stations in the power grid as objects, a topological model between each power transmission station in the power grid is constructed. Then, according to the various parameters of the power transmission stations, the topological model is transformed into a weighted topological model. Based on the weighted topological model, the risks in the operation of the power grid are identified and predicted, realizing the analysis of equipment operation risks from the level of the power grid. At the same time, in the present invention, the influence factors between each power transmission station in the power grid are obtained through the weighted topological model and the various parameters of the power transmission stations. When a fault occurs at a power transmission station in the power grid, based on this influence factor, the probability of a fault occurring at other power transmission stations in the power grid can be predicted, realizing a comprehensive reflection of the overall risk state of the power grid and reducing the overall operation risk of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0044] Figure 1 is the overall flowchart of the power grid risk identification method based on topological analysis of the present invention;

[0045] Figure 2 is a schematic diagram of the physical connection model of the power grid;

[0046] Figure 3 is a schematic diagram of the topological model of the power grid

[0047] Figure 4 is a schematic diagram of the weighted topological model of the power grid. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented in order to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0049] The embodiment of the present invention provides a power grid risk identification method based on topology analysis. The above method includes:

[0050] Divide the power grid into hierarchical levels, and divide the power grid into three layers according to the composition relationship of the power grid;

[0051] Obtain the physical connection model between the second-layer structures of the power grid, and convert the physical connection model into a topology model based on the electrical connection relationship between the second-layer structures of the power grid;

[0052] Obtain the parameters of the second-layer structure of the power grid, and convert the topology model into a weighted topology model based on the parameters of the second-layer structure of the power grid;

[0053] Based on the weighted topology model and combined with the parameters of the second-layer structure of the power grid, obtain the influence factors between the second-layer structures of the power grid;

[0054] Identify and predict the power grid risk according to the influence factors between the second-layer structures of the power grid.

[0055] In this embodiment, the power grid is divided into three-layer structures of power grid, power supply station, and power grid equipment according to the composition relationship of the power grid. Taking the power supply station of the second-layer structure of the power grid as the object, obtain the physical connection model between each power supply station in the power grid, and then convert the physical connection model into a topology model according to the electrical connection relationship between each power supply station. In the topology model, two connected points indicate that the two points are electrically connected, that is, there is a power supply relationship between the two stations. When obtaining the parameters of the power supply station, specifically including the maximum load, rated voltage, etc. of the power supply station, according to the parameters of the power supply station and the electrical connection relationship of the power supply station, obtain the power supply voltage of the connection line between each power supply station, and use the value of the power supply voltage as the weight to convert the topology model to obtain a weighted topology model. According to the weighted topology model between the power supply stations, the influence factors between the power supply stations can be obtained. When a fault occurs in the power grid, the faulty power supply station can be identified according to the change of the weighted topology diagram of the power supply equipment. When a fault occurs or maintenance is carried out on a certain power supply station in the power grid, the risk of other power supply stations being affected can be predicted according to the influence factors between the power supply stations. Through this method, the risk of the power grid can be identified and predicted.

[0056] Based on the above method, the above division of the power grid into three layers specifically includes: dividing the power grid into three-layer structures of power grid, power supply station, and power grid equipment, where the power supply node is the second-layer structure of the power grid.

[0057] Specifically, the power grid is divided into three-layer structure according to the composition relationship of the power grid. The first layer structure is the power grid, the second layer structure is the power supply station, such as power plants, substations, etc., and the third layer structure is the power grid equipment, such as generators, transformers, etc. The power grid is composed of several power supply stations, and each power supply station contains several power supply devices. In the application of this invention, a topology is constructed with the power supply station as the object for power grid fault analysis, realizing the overall safety detection of the power grid and reducing the calculation amount at the same time.

[0058] Based on the above method, the specific steps for converting the physical connection model into a topology model based on the electrical connection relationship between the second-layer structures of the power grid are as follows:

[0059] S1. Select two second-layer structures of the power grid in the physical connection model in sequence.

[0060] S2. Judge whether the two selected second-layer structures of the power grid are physically connected. If not, reselect.

[0061] S3. If so, further judge whether the two selected second-layer structures of the power grid are electrically connected. If so, retain the physical connection relationship between the two selected second-layer structures.

[0062] S4. If not, delete the physical connection relationship between the two selected second-layer structures of the power grid.

[0063] S5. Repeat the above steps S1 - S4 until all the second-layer structures of the power grid in the physical connection model are judged, and the obtained model is the topology model.

[0064] It should be noted that only the power supply connections between power supply stations are considered in the topology model. Therefore, it is necessary to convert the physical connection model of the power supply station, retain the physical connection relationships with electrical connection relationships in the physical connection model. Specifically, select a power supply station in the physical connection model, and judge in sequence whether this power supply station is physically connected to other power supply stations in the physical connection model. If two power supply stations are physically connected, then further judge whether these two power supply stations are electrically connected. If they are electrically connected, retain the physical connection relationship between these two power supply stations, otherwise delete the physical connection relationship between these two power supply stations. Repeat in sequence until all power supply stations are judged, and the topology model can be obtained.

[0065] For example, referring to Figure 2 , where 1, 2, 3, 4, 5, 6, 7 are power supply stations, and a, b, c, d, e, f, g, h are physical connection relationships in the physical connection model. If there is no electrical connection relationship between power supply stations 1 and 4 and between 6 and 7, then the physical connection relationships b and h between power supply stations 1 and 4 and between 6 and 7 need to be deleted, and the remaining physical connection relationships are retained, obtaining Figure 3The topological model shown

[0066] Based on the above method, the parameters of the second-layer structure of the above power grid include: the maximum load of the second-layer structure, the rated output voltage of the second-layer structure, and the rated input voltage of the second-layer structure. The weight of the weighted topological model is the power supply voltage between the second-layer structures of the power grid.

[0067] Specifically, parameters such as the maximum load, rated output voltage, and rated input voltage of the power supply stations in the second-layer structure of the power grid are obtained. According to the parameters of the power supply stations and combined with the power flow algorithm, the power supply voltage between each power supply station in the power grid can be calculated. The value of the power supply voltage between the power supply stations is used as the weight value and added to the topological model to obtain the weighted topological model of the power grid. Refer to Figure 4 , it should be noted that the voltage between the power supply stations includes the input voltage and the output voltage, where the input voltage is represented by a negative number and the output voltage is represented by a positive number.

[0068] Based on the above method, the specific process of obtaining the influence factors between the second-layer structures of the above power grid is as follows:

[0069] Randomly select a second-layer structure of the power grid, and obtain all topological paths in the weighted topological model that contain the selected second-layer structure of the power grid;

[0070] Traverse from the selected second-layer structure of the power grid to both ends of its topological path in turn, and detect whether all the second-layer structures on the topological path output voltage to the selected second-layer structure of the power grid;

[0071] If so, retain the topological path; if not, screen out the first second-layer structure of the power grid that does not output voltage and the topological path before or after it;

[0072] Based on the screened topological paths, calculate the influence factors of the second-layer structures of the power grid on the selected second-layer structure of the power grid in the topological path in turn.

[0073] In this embodiment, the influence factors between each power supply station can be obtained according to the weighted topological model. First, randomly select a power supply station from the weighted topological model, obtain all topological paths in the weighted topological model that contain the power supply station, traverse the obtained topological paths from the selected power supply station to both ends in turn, and detect whether all the power supply stations on the topological path output voltage to the selected power supply station, that is, the weight values between each power supply station before the selected power supply station on the topological path are all positive numbers, and those after are all negative numbers. If so, retain the station; if not, screen out the first power supply station that does not output voltage and the topological path before or after it. The power supply stations on the remaining paths all have an impact on the selected power supply station. According to the voltage relationship between the power supply stations on the topological path, the influence factors of the power supply stations on the topological path on the selected power supply station can be obtained.

[0074] For example, referring to Figure 4 , if the selected power supply station is 3, there are 3 topological paths where 3 is located, namely 1-2-3-4, 1-2-3-5-6, and 1-2-3-5-7. Using the above conditions for screening, among them, 5 does not output voltage to 3. Therefore, the paths after deleting 5 are removed, and then the remaining topological path is only 1-2-3-4. Based on this topological path, the influence factors of the other power supply stations on power supply station 3 can be solved.

[0075] Based on the above method, the influence factors between the second-layer structures of the above power grid are determined by the power supply voltages between the second-layer structures of the power grid. Among them, the closer the two second-layer structures of the power grid are on the same topological path, the greater the influence factor.

[0076] It should be noted that referring to Figure 4 , after screening, for power supply station 3, the topological path only remains 1-2-3-4. According to the topological path 1-2-3-4, the output voltage of power supply station 2 to power supply station 3 is 1, and the output voltage of power supply station 4 to power supply station 3 is -1. Then the input voltage of power supply station 3 is 2. Based on this, the influence factors of power supply stations 2 and 4 on power supply station 3 can be calculated as both 0.5. Further, the influence factor of power supply station 1 on power supply station 2 can also be obtained as 0.5. Then the influence factor of power supply station 1 on power supply station 3 is 0.5 * 0.5 = 0.25. From this, it can be seen that the closer the two power supply stations are on the same topological path, the greater the influence factor between them.

[0077] Based on the above method, the identification and prediction of the power grid risk according to the influence factors between the second-layer structures of the power grid specifically include:

[0078] Obtain the real-time weighted topological model of the power grid, and match the obtained real-time weighted model with the standard weighted topological model of the power grid;

[0079] If the matching results are different, it means that there is a fault in the power grid;

[0080] Judge whether the number of nodes in the real-time weighted model is the same as that in the standard weighted topological model of the power grid. If the number of nodes is different, it means that a power failure fault has occurred in the second-layer structure of the power grid;

[0081] If they are the same, then compare the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topological model of the power grid;

[0082] If the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topological model of the power grid are different, it means that there is a fault in this second-layer structure;

[0083] Based on the second-layer structure with faults, the fault risks of the remaining second-layer structures can be predicted.

[0084] In this embodiment, the risk identification and prediction of the power grid are carried out by obtaining the weighted topological model of the power grid in real time. The obtained real-time weighted topological model of the power grid is compared with the standard weighted topological model in the safe state of the power grid. If the two are the same, it means that there are no faults or risks in the power grid. If they are different, it is necessary to further compare whether the number of nodes in the real-time weighted topological model of the power grid is the same as that in the standard weighted topological model in the safe state of the power grid. If they are different, it means that there is a power supply station power outage in the power grid. According to the position of the missing power supply station in the topological model, the position of the power supply station in reality can be identified. According to the position of the identified power supply station in the topological model, the influence factors between the remaining power supply stations and the faulty power supply station in the power grid can be obtained, so that the possibility of the remaining power supply stations failing in the case of the disconnection of the power supply station can be calculated, and the fault risk prediction can be carried out. If the number of nodes in the real-time weighted topological model of the power grid is the same as that in the standard weighted topological model in the safe state of the power grid, the weights between the corresponding power supply stations in the real-time weighted model and the standard weighted topological model of the power grid are further compared. If the weights between the corresponding power supply stations are different, it means that one or more of the two stations have obstacles, so as to identify the position of the faulty power supply station. Similarly, the possibility of the remaining power supply stations failing can be calculated according to the position of the faulty power supply station, and the fault risk prediction can be carried out. Through this method, the risk identification at the power grid level can be realized, and at the same time, the risks of the remaining stations can be predicted according to the faulty stations, realizing a comprehensive reflection of the overall risk state of the power grid and reducing the overall operation risk of the power grid.

[0085] The embodiment of the present invention provides a power grid risk identification system based on topological analysis. The above system includes:

[0086] A layering module for hierarchically dividing the power grid and dividing the power grid into three layers according to the composition relationship of the power grid;

[0087] A model construction module for obtaining the physical connection model between the second-layer structures of the power grid;

[0088] A topology construction module for converting the physical connection model into a topology model based on the electrical connection relationship between the second-layer structures of the power grid;

[0089] Obtain various parameters of the second-layer structure of the power grid, and convert the topology model into a weighted topology model based on the various parameters of the second-layer structure of the power grid;

[0090] Based on the weighted topology model and combined with the various parameters of the second-layer structure of the power grid, obtain the influence factors between the second-layer structures of the power grid;

[0091] A risk analysis module for identifying and predicting power grid risks based on the influencing factors between the second-layer structures of the power grid.

[0092] The power grid risk identification system based on topology analysis in the embodiments of the present invention corresponds to the power grid risk identification method based on topology analysis in the embodiments of the present invention. The technical features and beneficial effects described in the embodiments of the above-mentioned power grid risk identification method based on topology analysis are applicable to the embodiments of the power grid risk identification system based on topology analysis.

[0093] The embodiments of the present invention provide a readable storage medium with an executable program stored thereon. When the program is executed by a processor, the above-mentioned power grid risk identification method based on topology analysis is implemented.

[0094] It can be understood that the memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. The memory in the embodiments of the present invention can store data to support the operation of the terminal. Examples of these data include: any computer programs for operating on the terminal, such as operating systems and application programs. Among them, the operating system contains various system programs, such as the framework layer, the core library layer, the driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application programs can include various application programs.

[0095] The embodiments of the present invention provide a device including a memory, a processor, and an executable program stored on the memory and running on the processor. When the processor executes the program, the above-mentioned power grid risk identification method based on topology analysis is implemented.

[0096] The device includes: at least one processor, a memory, a user interface, and at least one network interface. Each component in the device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components.

[0097] The present invention is not limited to the above specific embodiments. Those of ordinary skill in the art starting from the above concepts and making various transformations without creative labor fall within the protection scope of the present invention.

Claims

1. A method for identifying power grid risks based on topological analysis, characterized in that, The method includes: Dividing the power grid into levels, dividing the power grid into three layers according to the composition relationship of the power grid, including: dividing the power grid into a three-layer structure of power grid, power supply stations, and power grid equipment, where the power supply stations are the second-layer structure of the power grid; Obtaining the physical connection model between the second-layer structures of the power grid, and converting the physical connection model into a topological model based on the electrical connection relationship between the second-layer structures of the power grid; Obtaining the parameters of the second-layer structure of the power grid, and converting the topological model into a weighted topological model based on the parameters of the second-layer structure of the power grid; Based on the weighted topological model and combined with the parameters of the second-layer structure of the power grid, obtaining the influence factors between the second-layer structures of the power grid; The specific process of obtaining the influence factors between the second-layer structures of the power grid is as follows: Randomly select a second-layer structure of the power grid, and obtain all topological paths in the weighted topological model that contain the selected second-layer structure of the power grid; Traverse from the selected second-layer structure of the power grid to both ends of its topological path in turn, and detect whether all the second-layer structures on the topological path output voltage to the selected second-layer structure of the power grid; If so, retain the topological path, if not, screen out the first second-layer structure that does not output voltage and the topological path before or after it; Based on the screened topological paths, calculate the influence factors of the second-layer structures in the topological paths on the selected second-layer structure of the power grid in turn; Identify and predict the power grid risk based on the influence factors between the second-layer structures of the power grid, including: Obtaining the real-time weighted topological model of the power grid, and matching the obtained real-time weighted model with the standard weighted topological model of the power grid; If the matching results are different, it means that there is a fault in the power grid; Judge whether the number of nodes in the real-time weighted model is the same as that in the standard weighted topological model of the power grid. If the number of nodes is different, it means that a power failure fault has occurred in the second-layer structure of the power grid; If they are the same, then compare the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topological model of the power grid; If the weights between the corresponding second-layer structures in the real-time weighted model and the standard weighted topological model of the power grid are different, it means that there is a fault in this second-layer structure; Based on the faulty second-layer structure, predict the fault risks of the remaining second-layer structures.

2. The method according to claim 1, characterized in that, The specific steps of converting the physical connection model into a topological model based on the electrical connection relationship between the second-layer structures of the power grid are as follows: S1. Select two second-layer structures of the power grid in the physical connection model in turn; S2. Judge whether the two selected second-layer structures of the power grid are physically connected. If not, reselect; S3. If so, further judge whether the two selected second-layer structures of the power grid are electrically connected. If so, retain the physical connection relationship between the two selected second-layer structures; S4. If not, delete the physical connection relationship between the two selected second-layer structures; S5. Repeat the above steps S1-S4 until all the second-layer structures in the physical connection model are judged, and the obtained model is the topological model.

3. The method according to claim 2, characterized in that, The parameters of the second - layer structure of the power grid include: the maximum load of the second - layer structure, the rated output voltage of the second - layer structure, and the rated input voltage of the second - layer structure. The weight of the weighted topology model is the power supply voltage between the second - layer structures of the power grid.

4. The method according to claim 1, characterized in that, The influence factor between the second - layer structures of the power grid is determined by the power supply voltage between the second - layer structures of the power grid. Among them, the closer two second - layer structures of the power grid are on the same topological path, the greater the influence factor.

5. A power grid risk identification system based on topological analysis, characterized in that, The system includes: A hierarchical module for hierarchically dividing the power grid. According to the composition relationship of the power grid, the power grid is divided into three layers, including: dividing the power grid into three - layer structures of power grid, power supply station, and power grid equipment, where the power supply station is the second - layer structure of the power grid; A model construction module for obtaining the physical connection model between the second - layer structures of the power grid; A topology construction module for converting the physical connection model into a topology model based on the electrical connection relationship between the second - layer structures of the power grid; Obtain the parameters of the second - layer structure of the power grid, and convert the topology model into a weighted topology model based on the parameters of the second - layer structure of the power grid; Based on the weighted topology model and combined with the parameters of the second - layer structure of the power grid, obtain the influence factor between the second - layer structures of the power grid; The specific process of obtaining the influence factor between the second - layer structures of the power grid is as follows: Randomly select a second - layer structure of the power grid, and obtain all topological paths in the weighted topology model that contain the selected second - layer structure of the power grid; Traverse from the selected second - layer structure to both ends of its topological path in turn, and detect whether all the second - layer structures on the topological path output voltage to the selected second - layer structure; If so, retain the topological path. If not, screen out the first second - layer structure that does not output voltage and the topological path before or after it; Based on the screened topological paths, calculate the influence factor of the second - layer structures in the topological path on the selected second - layer structure of the power grid in turn; A risk analysis module for identifying and predicting power grid risks according to the influence factor between the second - layer structures of the power grid, including: Obtain the real - time weighted topology model of the power grid, and match the obtained real - time weighted model with the standard weighted topology model of the power grid; If the matching results are different, it indicates that there is a fault in the power grid; Judge whether the number of nodes in the real - time weighted model is the same as that in the standard weighted topology model of the power grid. If the number of nodes is different, it indicates that a power - off fault of the second - layer structure of the power grid has occurred; If they are the same, compare the weights between the corresponding second - layer structures in the real - time weighted model and the standard weighted topology model of the power grid; If the weights between the corresponding second - layer structures in the real - time weighted model and the standard weighted topology model of the power grid are different, it indicates that there is a fault in this second - layer structure; Based on the faulty second - layer structure, predict the fault risks of the remaining second - layer structures.

6. A readable storage medium, characterized in that , on which an executable program is stored. When the program is executed by a processor, it implements the power grid risk identification method based on topological analysis described in any one of claims 1 to 4.

7. A device, characterized in that It includes a memory, a processor, and an executable program stored in the memory and running on the processor. When the processor executes the program, it implements the method for identifying power grid risks based on topological analysis described in any one of claims 1 to 4.

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