Distribution area topology identification method and device based on transparent monitoring

Abstract

The invention provides a power distribution area topology identification method and device based on transparent monitoring, and relates to the technical field of power grids. According to the invention, state analysis is carried out on the node data of each node in the power distribution area, the working state and the fault condition of each node are determined, and then the topological relation between the nodes is determined, so that the real-time power supply interface of the power distribution area is updated in real time; the influence of the working state and the fault of each node on the topological relation of each node in the transformer area is comprehensively considered, so that the working state of each node in the real-time power supply interface and the topological relation among the nodes are more accurate, transparent monitoring of the topological relation of the power distribution transformer area is realized, and the management efficiency and the operation and maintenance quality of the power distribution transformer area are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power grid, and in particular to a method and device for identifying topology of distribution station areas based on transparent monitoring. Background Art

[0002] In the current management of distribution substations, due to the relatively backward technology and management level, low-voltage distribution networks face great challenges in construction and maintenance. In particular, there are many assets in the distribution substation, the connection relationships are complex, and the equipment topology diagram changes frequently. The traditional method of manual input and management can no longer meet the requirements. This method is not only inefficient and time-consuming, but also difficult to ensure the quality of work, and it is impossible to discover and reveal specific problems in a timely and comprehensive manner.

[0003] Moreover, with the increase of equipment and the complexity of connection relationships, the working status of each node in the distribution area is changeable, which makes it easy for the equipment control in the distribution area to have shutdown errors or power supply failures. In addition, failures often occur in the distribution area, which further increases the error rate of equipment control in the distribution area, affects the management efficiency and operation and maintenance quality of the distribution area, and even poses a safety hazard. Summary of the invention

[0004] The present invention provides a method and device for topological identification of a distribution substation area based on transparent monitoring, which can realize transparent monitoring of topological relations of distribution substation areas and improve management efficiency and operation and maintenance quality of distribution substation areas.

[0005] In a first aspect, the present invention provides a method for topological identification of a distribution substation based on transparent monitoring, the method comprising: acquiring node data of each node in the distribution substation; the node data comprising status data and connection relationships of the nodes; based on the node data of each node, performing status analysis on each node to determine the working status and fault conditions of each node; based on the working status and fault conditions of each node, determining the topological relationship between each node, the topological relationship comprising line-transformer relationship, transformer-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship; based on the working status and fault conditions of each node, and the topological relationship between each node, updating the real-time power supply interface of the distribution substation to achieve transparent monitoring of the distribution substation.

[0006] In one possible implementation, a status analysis is performed on each node based on the node data of each node to determine the working status and fault condition of each node, including: extracting features based on the node data of each node to obtain the feature vector of each node; obtaining the fault condition of each node based on the feature vector of each node and a preset fault analysis model; screening nodes based on the fault condition of each node to obtain fault-free nodes; and determining the working status of fault-free nodes based on the node data of fault-free nodes.

[0007] In a possible implementation, before performing status analysis on each node based on the node data of each node and determining the working status and fault condition of each node, it also includes: obtaining the operating data of each node in the distribution station area in the historical period, the topological data between each node, and the fault time and fault node in the historical period; dividing the operating data of each node in the historical period based on the fault time and fault node in the historical period, and the topological data, to obtain fault operation data and normal operation data; the fault operation data is the power grid operation data of the fault node and the adjacent nodes of the fault node in a set time period before the fault time; the normal operation data includes the power grid operation data of each node and the adjacent nodes of each node that operate normally; based on the fault operation data, generating a fault feature vector; based on the normal operation data, generating a normal feature vector; using the fault feature vector as input and the fault suspicion as output to generate a positive training sample; using the normal feature vector as input and the normal operation as output to generate a negative training sample; training based on the positive training samples and the negative training samples to obtain a fault analysis model.

[0008] In a possible implementation, training is performed based on positive training samples and negative training samples to obtain a fault analysis model, including: step 1: setting initial values ​​of model parameters of a random forest model; the model parameters include the number of trees, the depth of the tree, the maximum depth of the tree, the minimum number of samples required for node classification, the minimum number of samples required for leaf nodes, the maximum number of features during splitting, and whether to use guided sampling; step 2: training is performed based on positive training samples and negative training samples, as well as the initial values ​​of the model parameters, to obtain a first model, and the first model is set as an optimal model; step 3: based on the positive training samples and negative training samples, a test sample is selected, the optimal model is evaluated, and an evaluation value of the optimal model is obtained. Evaluation results; the evaluation results include accuracy; step 4: adjust model parameters, and train based on the training set in the training sample and the adjusted model parameters to obtain a second model; step 5: evaluate the second model based on the test set in the training sample to obtain an evaluation result of the second model; step 6: if the evaluation result of the second model is better than the evaluation result of the optimal model, the second model is determined as the optimal model; if the evaluation result of the optimal model is better than the evaluation result of the second model, the optimal model remains unchanged; step 7, repeat steps 4 to 7 until the number of iterations is greater than the maximum number of iterations; step 8, train based on the model parameters corresponding to the optimal model to determine the fault analysis model.

[0009] In one possible implementation, training is performed based on the model parameters corresponding to the optimal model to determine the fault analysis model, including: training based on the model parameters corresponding to the optimal model, as well as positive training samples and negative training samples to obtain an initial model; taking the initial model as a teacher model, and constructing a student model with the same model parameters as the teacher model; testing the teacher model based on a test set, and calculating a first test accuracy of the teacher model; determining a test accuracy threshold based on the first test accuracy; pruning the student model to obtain an adjusted student model; testing the adjusted student model based on the test set to obtain a second test accuracy; if the second test accuracy is greater than or equal to the test accuracy threshold, repeatedly pruning the student model until the second test accuracy is less than the test accuracy threshold; when the second test accuracy is less than the test accuracy threshold, the student model before adjustment is used as the fault analysis model.

[0010] In a possible implementation, the topological relationship between each node is determined based on the working status and fault condition of each node, including: determining the normally operating nodes based on the working status and fault condition of each node; determining the user phase information and user meter box information based on the node data of the normally operating nodes; determining the line-transformer relationship and the transformer-user relationship based on the working status of the normally operating nodes; determining the trunk-branch connection relationship and the multi-branch connection relationship based on the line-transformer relationship and the change relationship, as well as the fault condition of each node.

[0011] In one possible implementation, the real-time power supply interface of the distribution station area is updated based on the working status and fault conditions of each node and the topological relationship between each node, including: determining the normal operating nodes and the faulty nodes based on the working status and fault conditions of each node; updating the node status of each node in the real-time power supply interface of the distribution station area based on the normal operating nodes, the working status of the normal operating nodes and the fault status of the faulty nodes to obtain a first power supply interface; updating the connection links between each node in the first power supply interface based on the topological relationship between each node to obtain a second power supply interface; and reviewing the node status and the links between nodes based on the second power supply interface to determine the real-time power supply interface.

[0012] In a possible implementation, after updating the real-time power supply interface of the distribution substation based on the working status and fault conditions of each node and the topological relationship between the nodes, it also includes: monitoring the fault conditions in the distribution substation, the fault conditions include the fault location and the fault type; based on the fault conditions in the distribution substation, performing fault deduction to determine the scope of fault impact; the fault impact scope includes multiple normal operating nodes affected by the fault; based on the fault impact scope, determining a fault solution, the fault solution includes a power-off branch and a power-off time; based on the fault solution, generating a control instruction; the control instruction is used to instruct the power-off branch to disconnect at the power-off time; and sending a control instruction to the control node of the power-off branch.

[0013] In a possible implementation, the method further includes: dividing the nodes based on the node data of each node in the distribution station area and the topological relationship between each node to obtain multiple node groups with each node as the central node and the adjacent nodes connected to each node as the edge nodes; generating a node group vector based on the node data of each node group; performing fault analysis based on the node group vector to determine the fault probability of each node; generating a fault probability table based on the working status, fault probability and topological relationship of each node; and displaying the fault probability table for the user to observe the working status of each node.

[0014] In the second aspect, an embodiment of the present invention provides a distribution substation topology identification device based on transparent monitoring, the device comprising: a communication module, used to obtain node data of each node in the distribution substation; the node data includes node status data and connection relationships; a processing module, used to perform status analysis on each node based on the node data of each node, and determine the working status and fault conditions of each node; based on the working status and fault conditions of each node, determine the topological relationship between each node, the topological relationship includes line-transformer relationship, transformer-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship; based on the working status and fault conditions of each node, and the topological relationship between each node, update the real-time power supply interface of the distribution substation to realize transparent monitoring of the distribution substation.

[0015] The present invention provides a method and device for topological identification of a distribution station area based on transparent monitoring. The present invention determines the working status and fault condition of each node by performing status analysis on the node data of each node in the distribution station area, and then determines the topological relationship between each node, so that the real-time power supply interface of the distribution station area is updated in real time, and the influence of the working status and fault of each node on the topological relationship of each node in the area is comprehensively considered, so that the working status of each node in the real-time power supply interface and the topological relationship between each node are more accurate, thereby realizing transparent monitoring of the topological relationship of the distribution station area and improving the management efficiency and operation and maintenance quality of the distribution station area. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 It is a flow chart of a method for identifying topology of a distribution station area based on transparent monitoring provided by an embodiment of the present invention;

[0018] Figure 2 It is a structural schematic diagram of a distribution station area topology identification device based on transparent monitoring provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may 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 prevent unnecessary details from obstructing the description of the present invention.

[0020] In the description of the present invention, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" and "plurality" refer to two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0021] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0022] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include other steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0023] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be described through specific embodiments in conjunction with the accompanying drawings of the present invention.

[0024] As described in the background technology, the current equipment control in the distribution substation area has problems of low management efficiency and low operation and maintenance quality, which poses a safety hazard to the substation area.

[0025] To solve the above technical problems, Figure 1 As shown, an embodiment of the present invention provides a method for identifying a distribution station area topology based on transparent monitoring, including steps S101-S104.

[0026] S101. Obtain node data of each node in a distribution station area.

[0027] In the embodiment of the present application, the node data includes the status data and connection relationship of the node.

[0028] S102: Based on the node data of each node, perform status analysis on each node to determine the working status and fault condition of each node.

[0029] As a possible implementation manner, step S102 may be specifically implemented as steps S1021 - S1024 .

[0030] S1021. Perform feature extraction based on the node data of each node to obtain a feature vector of each node.

[0031] S1022. Obtain the fault condition of each node based on the characteristic vector of each node and a preset fault analysis model.

[0032] S1023. Based on the fault conditions of each node, perform node screening to obtain fault-free nodes.

[0033] S1024. Determine the working status of the non-faulty node based on the node data of the non-faulty node.

[0034] S103: Determine the topological relationship between the nodes based on the working status and fault condition of each node.

[0035] In the embodiment of the present application, the topological relationship includes line-transformer relationship, transformer-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship.

[0036] As a possible implementation manner, step S103 may be specifically implemented as steps S1031 - S1034 .

[0037] S1031. Determine a normally operating node based on the working status and fault condition of each node.

[0038] S1032. Determine user phase information and user meter box information based on node data of the normally operating node.

[0039] S1033. Based on the working status of the normally operating node, determine the line-to-line relationship and the user-to-user relationship.

[0040] S1034. Based on the line-change relationship and the change relationship, as well as the fault conditions of each node, determine the trunk-branch connection relationship and the multi-branch connection relationship.

[0041] S104: Based on the working status and fault conditions of each node and the topological relationship between each node, the real-time power supply interface of the distribution substation is updated to achieve transparent monitoring of the distribution substation.

[0042] As a possible implementation manner, step S104 may be specifically implemented as steps S1041 - S1044 .

[0043] S1041. Determine the normal operating nodes and faulty nodes based on the working status and fault conditions of each node.

[0044] S1042: Based on the normally operating nodes, the working status of the normally operating nodes and the fault status of the faulty nodes, the node status of each node in the real-time power supply interface of the distribution station area is updated to obtain a first power supply interface.

[0045] S1043. Based on the topological relationship between the nodes, update the connection links between the nodes in the first power supply interface to obtain the second power supply interface.

[0046] S1044. Based on the second power supply interface, review the node status and the link between nodes to determine the real-time power supply interface.

[0047] The present invention provides a distribution station area topology identification method based on transparent monitoring. By performing status analysis on node data of each node in the distribution station area, the working status and fault condition of each node are determined, and then the topological relationship between each node is determined, so that the real-time power supply interface of the distribution station area is updated in real time. The influence of the working status and fault of each node on the topological relationship of each node in the station area is comprehensively considered, so that the working status of each node in the real-time power supply interface and the topological relationship between each node are more accurate, and transparent monitoring of the topological relationship of the distribution station area is realized, thereby improving the management efficiency and operation and maintenance quality of the distribution station area.

[0048] Optionally, the method for identifying distribution station area topology based on transparent monitoring provided in an embodiment of the present invention further includes steps S201 to S206 before step S102.

[0049] S201. Obtain the operation data of each node in the distribution substation area in the historical period, the topological data between each node, and the fault time and fault node in the historical period.

[0050] S202: Based on the fault time and fault node in the historical period, and the topology data, the operation data of each node in the historical period is divided to obtain fault operation data and normal operation data.

[0051] In some embodiments, the fault operation data is the grid operation data of the faulty node and its neighboring nodes in a set period before the fault moment; the normal operation data includes the grid operation data of each node and its neighboring nodes operating normally.

[0052] S203: Generate a fault feature vector based on the fault operation data; and generate a normal feature vector based on the normal operation data.

[0053] S204: Taking the fault feature vector as input and the fault suspicion as output, a positive training sample is generated.

[0054] S205: Generate negative training samples by taking the normal feature vector as input and the normal operation as output.

[0055] S206: Perform training based on the positive training samples and the negative training samples to obtain a fault analysis model.

[0056] Exemplarily, the embodiment of the present invention may determine a fault analysis model based on step 1 to step 8.

[0057] Step 1: Set the initial values ​​of the model parameters of the random forest model; the model parameters include the number of trees, the depth of the tree, the maximum depth of the tree, the minimum number of samples required for node classification, the minimum number of samples required for leaf nodes, the maximum number of features when splitting, and whether to use guided sampling.

[0058] Step 2: Based on the positive training samples and the negative training samples, and the initial values ​​of the model parameters, training is performed to obtain a first model, and the first model is set as the optimal model.

[0059] Step 3: Based on the positive training samples and negative training samples, select test samples, evaluate the optimal model, and obtain the evaluation result of the optimal model; the evaluation result includes accuracy.

[0060] Step 4: Adjust the model parameters, and perform training based on the training set in the training sample and the adjusted model parameters to obtain a second model.

[0061] Step 5: Based on the test set in the training sample, the second model is evaluated to obtain the evaluation result of the second model.

[0062] Step 6: If the evaluation result of the second model is better than the evaluation result of the optimal model, the second model is determined as the optimal model; if the evaluation result of the optimal model is better than the evaluation result of the second model, the optimal model remains unchanged.

[0063] Step 7: Repeat steps 4 to 7 until the number of iterations is greater than the maximum number of iterations.

[0064] Step 8: Based on the model parameters corresponding to the optimal model, training is performed to determine the fault analysis model.

[0065] Exemplarily, the embodiment of the present invention may determine a fault analysis model based on steps A1-A7.

[0066] A1. Based on the model parameters corresponding to the optimal model, as well as the positive training samples and the negative training samples, training is performed to obtain an initial model.

[0067] A2. Take the initial model as the teacher model and construct a student model with the same model parameters as the teacher model.

[0068] A3. Test the teacher model based on the test set and calculate the first test accuracy of the teacher model.

[0069] A4. Based on the first test accuracy, determine the test accuracy threshold; prune the student model to obtain an adjusted student model.

[0070] A5. Test the adjusted student model based on the test set to obtain the second test accuracy.

[0071] A6. If the second test accuracy is greater than or equal to the test accuracy threshold, repeatedly prune the student model until the second test accuracy is less than the test accuracy threshold.

[0072] A7. When the second test accuracy is less than the test accuracy threshold, the student model before adjustment is used as the fault analysis model.

[0073] In this way, the embodiment of the present invention can build a fault analysis model before performing status analysis on each node, and reduce the complexity of the fault analysis model, so that the fault analysis model can predict the node working status and fault conditions faster and more accurately, ensuring the accuracy and real-time performance of distribution station area topology identification.

[0074] Optionally, the method for identifying distribution station area topology based on transparent monitoring provided in an embodiment of the present invention further includes steps S301 - S305 after step S104 .

[0075] S301. Monitor the fault conditions in the distribution station area, where the fault conditions include the fault location and the fault type.

[0076] S302: Based on the fault situation in the distribution station area, perform fault deduction to determine the impact scope of the fault.

[0077] In some embodiments, the fault impact range includes multiple normally operating nodes affected by the fault.

[0078] S303: Determine a fault solution based on the fault impact range.

[0079] In some embodiments, the fault solution includes a de-energized branch and a de-energized time;

[0080] S304: Generate a control instruction based on the fault solution.

[0081] In some embodiments, the control instruction is used to instruct the power-off branch to be disconnected at the power-off time.

[0082] S305: Send a control instruction to the control node of the power-off branch.

[0083] In this way, the embodiment of the present invention can isolate and disconnect the fault in the distribution station area more accurately and quickly, reduce the impact range of the fault in the station area, and ensure the safe operation of the distribution station area as a whole.

[0084] Optionally, the method for identifying power distribution area topology based on transparent monitoring provided in the embodiment of the present invention further includes steps S401 to S405 after step S104.

[0085] S401. Based on the node data of each node in the distribution station area and the topological relationship between the nodes, the nodes are divided to obtain a plurality of node groups with each node as a central node and adjacent nodes connected to each node as edge nodes.

[0086] S402 : Generate a node group vector based on the node data of each node group.

[0087] S403: Perform fault analysis based on the node group vector to determine the fault probability of each node.

[0088] S404: Generate a fault probability table based on the working status, fault probability and topological relationship of each node.

[0089] S405: Display a fault probability table to allow the user to observe the working status of each node.

[0090] In this way, the embodiment of the present invention can achieve early prediction of node failures in a distribution station area, transparently display the probability of possible failures to users, and enable users to prepare measures.

[0091] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0092] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0093] Figure 2 The topology identification device 500 for power distribution area based on transparent monitoring provided by an embodiment of the present invention is shown. The topology identification device 500 includes a communication module 501 and a processing module 502 .

[0094] The communication module 501 is used to obtain the node data of each node in the distribution station area; the node data includes the status data and connection relationship of the node.

[0095] Processing module 502 is used to perform status analysis on each node based on the node data of each node to determine the working status and fault condition of each node; determine the topological relationship between each node based on the working status and fault condition of each node, and the topological relationship includes line-transformer relationship, transformer-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship; based on the working status and fault condition of each node, and the topological relationship between each node, update the real-time power supply interface of the distribution substation to realize transparent monitoring of the distribution substation.

[0096] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for identifying distribution area topology based on transparent monitoring, characterized in that: include: Obtaining node data of each node in the distribution station area; the node data includes node status data and connection relationship; Based on the node data of each node, the status of each node is analyzed to determine the working status and fault conditions of each node; Based on the working status and fault conditions of each node, determine the topological relationship between each node, the topological relationship includes line-to-transformer relationship, transformer-to-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship; Based on the working status and fault conditions of each node, as well as the topological relationship between the nodes, the real-time power supply interface of the distribution area is updated to achieve transparent monitoring of the distribution area.

2. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 1 is characterized in that: The state analysis of each node is performed based on the node data of each node to determine the working state and fault condition of each node, including: Based on the node data of each node, feature extraction is performed to obtain a feature vector of each node; Based on the characteristic vector of each node and the preset fault analysis model, the fault condition of each node is obtained; Based on the fault conditions of each node, node screening is performed to obtain fault-free nodes; Based on the node data of the non-faulty node, the working status of the non-faulty node is determined.

3. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 2 is characterized in that: Before performing status analysis on each node based on the node data of each node to determine the working status and fault condition of each node, the method further includes: Obtain the operation data of each node in the distribution area during the historical period, the topological data between the nodes, and the fault time and fault node during the historical period; Based on the fault time and fault node in the historical period, and the topological data, the operation data of each node in the historical period is divided to obtain fault operation data and normal operation data; the fault operation data is the power grid operation data of the fault node and the adjacent nodes of the fault node in a set period before the fault time; the normal operation data includes the power grid operation data of each node and the adjacent nodes of each node in normal operation; Based on the fault operation data, a fault feature vector is generated; based on the normal operation data, a normal feature vector is generated; Taking the fault feature vector as input and the fault suspicion as output, generating positive training samples; Taking the normal feature vector as input and normal operation as output, a negative training sample is generated; Training is performed based on the positive training samples and the negative training samples to obtain the fault analysis model.

4. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 3 is characterized in that: The performing training based on the positive training samples and the negative training samples to obtain the fault analysis model includes: Step 1: Set the initial values ​​of the model parameters of the random forest model; the model parameters include the number of trees, the depth of the tree, the maximum depth of the tree, the minimum number of samples required for node classification, the minimum number of samples required for leaf nodes, the maximum number of features when splitting, and whether to use guided sampling; Step 2: Based on the positive training samples and the negative training samples, and the initial values ​​of the model parameters, training is performed to obtain a first model, and the first model is set as an optimal model; Step 3: Based on the positive training samples and the negative training samples, a test sample is selected to evaluate the optimal model to obtain an evaluation result of the optimal model; the evaluation result includes an accuracy rate; Step 4: adjusting the model parameters, and performing training based on the training set in the training sample and the adjusted model parameters to obtain a second model; Step 5: Based on the test set in the training sample, the second model is evaluated to obtain an evaluation result of the second model; Step 6: If the evaluation result of the second model is better than the evaluation result of the optimal model, the second model is determined as the optimal model; if the evaluation result of the optimal model is better than the evaluation result of the second model, the optimal model remains unchanged; Step 7, repeat steps 4 to 7 until the number of iterations is greater than the maximum number of iterations; Step eight: training based on the model parameters corresponding to the optimal model to determine the fault analysis model.

5. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 4 is characterized in that: The step of training based on the model parameters corresponding to the optimal model to determine the fault analysis model includes: Based on the model parameters corresponding to the optimal model, as well as the positive training samples and the negative training samples, training is performed to obtain an initial model; Taking the initial model as a teacher model, constructing a student model having the same model parameters as the teacher model; Testing the teacher model based on the test set, and calculating a first test accuracy of the teacher model; Based on the first test accuracy, determining a test accuracy threshold; Performing branch pruning on the student model to obtain an adjusted student model; The adjusted student model is tested based on the test set to obtain the second test accuracy; If the second test accuracy is greater than or equal to the test accuracy threshold, repeatedly pruning the student model until the second test accuracy is less than the test accuracy threshold; When the second test accuracy is less than the test accuracy threshold, the student model before adjustment is used as the fault analysis model.

6. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 1, characterized in that: The determining the topological relationship between the nodes based on the working status and fault condition of the nodes includes: Based on the working status and fault conditions of each node, determine the normal operating node; Determine user phase information and user meter box information based on the node data of the normally operating node; Based on the working status of the normal operating nodes, determine the line-to-line relationship and the transformer-to-user relationship; Based on the line-change relationship and the change relationship, as well as the fault conditions of each node, a trunk-branch connection relationship and a multi-branch connection relationship are determined.

7. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 1 is characterized in that: The updating of the real-time power supply interface of the distribution area based on the working status and fault condition of each node and the topological relationship between the nodes includes: Based on the working status and fault conditions of each node, determine the normal operating nodes and faulty nodes; Based on the normal operating node, the working state of the normal operating node and the fault state of the faulty node, the node state of each node in the real-time power supply interface of the distribution station area is updated to obtain a first power supply interface; Based on the topological relationship between the nodes, the connection links between the nodes in the first power supply interface are updated to obtain a second power supply interface; Based on the second power supply interface, the node status and the inter-node link are reviewed to determine the real-time power supply interface.

8. The method for identifying distribution area topology based on transparent monitoring according to claim 1, characterized in that: After updating the real-time power supply interface of the distribution area based on the working status and fault condition of each node and the topological relationship between each node, the method further includes: Monitoring fault conditions in the distribution substation area, the fault conditions including fault location and fault type; Based on the fault situation in the distribution station area, a fault simulation is performed to determine the fault impact range; the fault impact range includes multiple normally operating nodes affected by the fault; Determine a fault solution based on the fault impact range, wherein the fault solution includes a power-off branch and a power-off time; Based on the fault solution, a control instruction is generated; the control instruction is used to instruct the power-off branch to be disconnected at the power-off time; The control instruction is sent to a control node of the power-off branch.

9. The method for identifying the topology of a distribution station area based on transparent monitoring according to claim 1, characterized in that: The method further comprises: Based on the node data of each node in the distribution station area and the topological relationship between the nodes, the nodes are divided to obtain a plurality of node groups with each node as a central node and adjacent nodes connected to each node as edge nodes; Generate a node group vector based on the node data of each node group; Based on the node group vector, a fault analysis is performed to determine the fault probability of each node failing; Generate a fault probability table based on the working status, fault probability and topological relationship of each node; The fault probability table is displayed so that the user can observe the working status of each node.

10. A distribution substation area topology identification device based on transparent monitoring, characterized in that: include: The communication module is used to obtain the node data of each node in the distribution station area; the node data includes the status data and connection relationship of the node; The processing module is used to perform status analysis on each node based on the node data of each node to determine the working status and fault conditions of each node; determine the topological relationship between each node based on the working status and fault conditions of each node, and the topological relationship includes line-transformer relationship, transformer-user relationship, user phase information, user meter box information, trunk-branch connection relationship and multi-branch connection relationship; based on the working status and fault conditions of each node, and the topological relationship between each node, update the real-time power supply interface of the distribution substation to realize transparent monitoring of the distribution substation.

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