Distribution control platform based on transmission and transformation risk prediction

Abstract

The present application provides a power distribution control platform based on power transmission and transformation risk prediction, which relates to the field of power distribution control technology, including: obtaining the power transmission and transformation topology network through a topology network acquisition module, partitioning according to the control source by a network partitioning module, monitoring the operation data by an operation monitoring module, locating the fault source by a fault tracing module, constructing a fault network by a fault network construction module, analyzing the key lines by a key control line acquisition module, and controlling by a power distribution control module. The present application can solve the technical problems of low power grid control efficiency and difficulty in quickly locating the fault source caused by the use of single-channel control in the prior art, realize power distribution control of the power transmission and transformation electronic network, ensure that the power grid operates in the best state, reduce the risk of faults, and improve the efficiency and safety of power grid operation.

Description

Technical Field

[0001] The present application relates to the technical field of power distribution control, and in particular to a power distribution control platform based on power transmission and transformation risk prediction. Background Art

[0002] With the expansion of the scale of power systems and the continuous growth of electricity demand, the complexity of power transmission and transformation systems is also increasing. The reliability and stability of the system are crucial to ensuring power supply. Due to the complex topology of the transmission and transformation network, the operating conditions of each node and line directly affect the overall reliability of the system. Once certain nodes or lines in the system fail, it may cause a chain reaction, resulting in large-scale power outages. It is difficult to effectively deal with large-scale power outages.

[0003] At present, the existing technology uses single-path control when regulating lines, resulting in low efficiency in grid regulation and difficulty in quickly locating the source of the fault, which further affects the reliability and safety of grid operation. Summary of the invention

[0004] The purpose of this application is to provide a distribution control platform based on transmission and transformation risk prediction, in order to solve the technical problems of low power grid control efficiency and difficulty in quickly locating the source of faults caused by the use of single-path control in the prior art.

[0005] In view of the above problems, the present application provides a distribution control platform based on power transmission and transformation risk prediction, and the distribution control platform based on power transmission and transformation risk prediction includes: a topology network acquisition module, which is used to obtain the power transmission and transformation topology network; a network partitioning module, which is used to partition the power transmission and transformation topology network according to the control source, and output multiple power transmission and transformation electronic networks, wherein each power transmission and transformation electronic network is controlled by the same control source; an operation monitoring module, which is used to monitor the operation data of each of the multiple power transmission and transformation electronic networks to obtain a multi-block operation data set; a fault tracing module, which is used to trace the fault according to the multi-block operation data set and detect the first fault source corresponding to each power transmission and transformation electronic network; a fault network construction module, which is used to construct a corresponding fault network according to the first fault source corresponding to each power transmission and transformation electronic network; a key control line acquisition module, which is used to perform network center analysis on the fault network through a network center analysis model, and obtain the first key control line corresponding to each power transmission and transformation electronic network; a distribution control module, which is used to control the control source of the corresponding power transmission and transformation electronic network to perform distribution control according to the first key control line.

[0006] Furthermore, the fault network construction module is also used to: obtain the connection relationship in each transmission and transformation electronic network; perform fault propagation analysis on the first fault source according to the connection relationship, obtain the nodes affected by the fault propagation in the transmission and transformation electronic network, and calculate the failure probability of each node; and generate the fault network according to the nodes with a failure probability greater than a preset value of each node.

[0007] Furthermore, the fault network construction module is also used to: define a conditional probability table for each transmission and transformation electronic network, wherein the fault probability of each node in each transmission and transformation electronic network depends on the state of its parent node, wherein each node is set with an initial prior probability; set the initial state of the conditional probability table according to the first fault source; based on the initial state of the conditional probability table, use the Bayesian formula to calculate the posterior probability of the conditional probability table, and output the fault probability of each node.

[0008] Furthermore, the key control line acquisition module is also used to: perform network center analysis on the fault network through a network center analysis model, calculate the degree centrality, betweenness centrality and closeness centrality of each node; fuse the degree centrality, betweenness centrality and closeness centrality of each node, and output the network center index of each node; connect nodes according to the size of the network center index of each node to obtain the first key control line.

[0009] Furthermore, the key control line acquisition module is also used to: obtain the first line node number and the second line node number of the fault network, wherein the first line node number is the maximum number of nodes continuously connected in the fault network, and the second line node number is the minimum number of nodes continuously connected in the fault network; determine the k value according to the first line node number and the second line node number, and then connect k nodes.

[0010] Furthermore, the key control line acquisition module is also used to obtain a first key control line that meets key constraints, wherein the key constraints are that the network center index of k consecutive nodes is greater than a preset network center index, and the k consecutive nodes do not include edge nodes.

[0011] Furthermore, the fault tracing module is also used to: perform fault tracing according to the multi-block operation data set to determine whether the fault occurring in each transmission and transformation electronic network is a mixed fault source, wherein a mixed fault source is two or more fault sources; identify the transmission and transformation electronic network with mixed fault sources and output the identified transmission and transformation electronic network; construct a mixed fault network corresponding to the identified transmission and transformation electronic network; and input the mixed fault network into the network center analysis model for network center analysis.

[0012] Furthermore, the fault tracing module is also used to: obtain N fault sources that identify the transmission and transformation electronic network, where N is a positive integer greater than or equal to 2; obtain N fault networks corresponding to the N fault sources; and fuse the N fault networks by resetting redundant nodes to output a mixed fault network.

[0013] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0014] By partitioning the current power transmission and transformation topology network, and then analyzing the faults of each partition based on fault tracing, when a partition fails, timely regulation is carried out by identifying the key control lines of the current partition, and the line risks caused by the failure are alleviated step by step. This effectively solves the technical problems of low power grid control efficiency and difficulty in quickly locating the source of the fault caused by the use of single-line control in the existing technology, and realizes the distribution control of the power transmission and transformation electronic network, ensuring that the power grid operates in the best state, while reducing the risk of failure and improving the efficiency and safety of power grid operation.

[0015] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0017] Figure 1 This is a schematic diagram of the structure of the power distribution control platform based on power transmission and transformation risk prediction in this application;

[0018] Figure 2 This is a flow chart of generating a fault network in a distribution control platform based on transmission and transformation risk prediction in this application.

[0019] Description of reference numerals:

[0020] Topology network acquisition module 11, network partitioning module 12, operation monitoring module 13, fault tracing module 14, fault network construction module 15, key control line acquisition module 16, power distribution control module 17. DETAILED DESCRIPTION

[0021] This application provides a distribution control platform based on transmission and transformation risk prediction, which solves the problem that the existing technology uses single-path control when controlling the line, resulting in low efficiency of power grid control and difficulty in quickly locating the source of the fault, further affecting the reliability and safety of power grid operation. It realizes distribution control of the transmission and transformation electronic network, ensures that the power grid operates in the best state, reduces the risk of faults, and improves the efficiency and safety of power grid operation.

[0022] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0023] This application provides a distribution control platform based on transmission and transformation risk prediction, please refer to Figure 1 The power distribution control platform based on power transmission and transformation risk prediction includes:

[0024] The topology network acquisition module 11 is used to acquire the power transmission and transformation topology network.

[0025] Specifically, the transmission and transformation topology network refers to the connection relationship network between various transmission lines, substations, switches, transformers and other equipment in the power grid. This network describes the path of energy flow in the power system. Extract real-time data and grid structure information from the monitoring and data acquisition system. Use the grid facility layer in the GIS system to obtain topological information. Remove duplicate, erroneous or irrelevant data to ensure data accuracy. Convert the collected data into a unified format; define substations and buses as nodes, and define transmission lines and transformers as branches; create an adjacency matrix to represent the connection relationship between nodes and branches.

[0026] The network partitioning module 12 is used to partition the power transmission and transformation topology network according to the control source, and output multiple power transmission and transformation electronic networks, wherein each power transmission and transformation electronic network is regulated by the same control source.

[0027] Specifically, determine the control source in the power grid. The control source can be a specific substation, control center, or entity responsible for power supply and control in a certain area. Next, mark each device in the power grid, such as substations, transmission lines, switches, etc., list all control sources, and assign a unique identifier to each control source, and correspond each control source to the power grid device it controls. According to the mapping relationship, the entire power grid is divided into multiple subnetworks. Traverse the list of power grid devices, and add each device to the subnetwork of the corresponding control source according to the control source identifier of each device. For the transmission line connecting the device, also add it to the corresponding subnetwork according to the control source identifier. Each subnetwork contains those power grid devices that belong to the same control source. Finally, output the topology of each subnetwork to ensure that the devices in each subnetwork are only controlled by their corresponding control sources.

[0028] The operation monitoring module 13 is used to monitor the operation data of each of the plurality of transmission and transformation electronic networks to obtain a multi-block operation data set.

[0029] Specifically, determine the key operating parameters that need to be monitored, such as voltage, current, active power, reactive power, frequency, etc. Select appropriate monitoring points in each transmission and transformation electronic network, which can be key substations, lines or buses, and collect operating data from the monitoring points in real time. Integrate the collected data and classify them according to the transmission and transformation electronic network to form a block-based operating data set. List all key operating parameters that need to be monitored, such as voltage, current, active power, reactive power, frequency, etc. Determine the key monitoring points in each transmission and transformation electronic network, such as the incoming and outgoing lines of the substation, busbar connection points, etc. Collect the operating data of the monitoring points at certain time intervals, such as every second or every minute, through devices such as SCADA systems or RTUs. Classify the collected data according to the transmission and transformation electronic network, and each network forms a data block. Check the validity of the data and remove invalid or erroneous data. Normalize the data. Store the preprocessed data in a database, such as a SQL database or a NoSQL database.

[0030] The fault tracing module 14 is used to perform fault tracing according to the multi-block operation data set and detect the first fault source corresponding to each transmission and transformation electronic network.

[0031] Specifically, analyze the multi-block operation data set of each transmission and transformation electronic network to find abnormalities or signs of failure. Determine the source of abnormal data and locate specific equipment or components that may be the source of the failure. Read the multi-block operation data set of each transmission and transformation electronic network. Apply threshold detection to set the upper and lower limits of normal operating parameters, and those exceeding the threshold are considered abnormal. Use clustering algorithms to identify outliers in the data. Apply time series analysis, such as autocorrelation function ACF and partial autocorrelation function PACF, to detect periodic or trend anomalies in the data. Trace back to specific monitoring points based on the time and location information of the abnormal data. Analyze the equipment and lines upstream and downstream of the monitoring point to determine the possible source of the fault. Combined with historical fault data, use decision trees, support vector machines or other classification algorithms to assist in the identification of fault types. Organize the results of fault tracing, including the location of the fault source, fault type, possible causes, etc.

[0032] The fault network construction module 15 is used to construct a corresponding fault network according to the first fault source corresponding to each transmission and transformation electronic network.

[0033] Specifically, identify the first fault source of each transmission and transformation electronic network, that is, the device or location where the abnormality or fault first occurs. Analyze the fault propagation path, that is, the possible path for the fault to propagate outward from the fault source, including directly connected devices and lines. Based on the fault propagation path, build a fault network model containing the fault source, propagation path and related devices. Mark the areas that may be affected by the fault in the fault network, including the affected devices and system parts. Obtain the first fault source information of each transmission and transformation electronic network from the fault tracing analysis. According to the topological structure diagram of the power grid, identify the devices and lines directly connected to the fault source. Analyze the operating principle of the power grid and determine which paths the fault may propagate along. Use graph theory to create a new network diagram in which nodes represent power grid devices and edges represent connections between devices. In the network diagram, take the fault source as the starting node and the devices and lines directly connected to the fault source as the first layer of nodes and edges. Recursively add the next layer of devices and lines affected by the fault until all possible fault propagation paths are covered. In the fault network diagram, use different colors or marks to distinguish the fault source, propagation path and affected devices. Based on the type and severity of the fault, assess the extent to which each device or area is affected by the fault.

[0034] The key control line acquisition module 16 is used to perform a network center analysis on the fault network through a network center analysis model to obtain the first key control line corresponding to each transmission and transformation electronic network.

[0035] Specifically, select network centrality indicators to evaluate the importance of control lines, such as degree centrality, betweenness centrality, closeness centrality, etc. Calculate the selected network centrality indicator for each line in the fault network. Sort all control lines according to the calculation results of the network centrality indicators. Select the highest control line in the sorting as the first key control line for each transmission and transformation electronic network. Use analysis tools such as NetworkX to calculate the betweenness centrality for each line in the fault network. Sort the calculated betweenness centrality values. Based on the sorting results, select the line with the highest betweenness centrality as the first key control line.

[0036] The power distribution control module 17 is used to control the control source of the corresponding transmission and transformation electronic network to perform power distribution control according to the first key control circuit.

[0037] Specifically, formulate corresponding control strategies according to the role and influence of the first key control line in the power grid. According to the control strategy, prepare specific control instructions, including adjusting the switch status of the line, changing the generator output, adjusting the load distribution, etc. Send the control instructions to the corresponding control source, and the control source will perform the control operation. Analyze the impact of the first key control line on the stability of the power grid and determine the priority and target of the control. Determine the equipment parameters that need to be adjusted, such as the switch status, transformer tap position, line flow, etc., write the control instructions, clarify the operation steps and target status, and send the control instructions to the control source. Monitor the power grid operation data after control in real time, including voltage, current, power, etc. Evaluate whether the control operation has achieved the expected effect. If the control effect is not ideal, analyze the cause and adjust the control strategy. Optimize the control plan according to the control effect and power grid operation.

[0038] Further, if Figure 2 As shown, the fault network construction module 15 is also used for:

[0039] Acquire the connection relationship in each transmission and transformation electronic network; perform fault propagation analysis on the first fault source according to the connection relationship, acquire the nodes affected by the fault propagation in the transmission and transformation electronic network, and calculate the failure probability of each node; generate the fault network according to the nodes with a failure probability greater than a preset value of each node according to the failure probability value of each node.

[0040] Specifically, the connection relationship of each transmission and transformation electronic network is extracted from the topological structure of the power grid. Using methods in graph theory, such as creating a directed or undirected graph in NetworkX, the devices in the power grid, such as substations, lines, switches, etc., are used as nodes, and the connections between the devices are used as edges. In the network model, node attributes are used to represent the type of device, and edge attributes are used to represent the type of connection, such as DC, AC, etc. and transmission capacity. According to the results of the fault tracing analysis, the first fault source of each transmission and transformation electronic network is determined. Using a fault propagation model, such as a model based on circuit theory, a state space-based method, etc., the propagation of the fault in the network from the fault source is simulated. According to the fault propagation model, the impact of the fault on each node in the network is evaluated, including voltage drop, current increase, equipment overload, etc. Based on the results of the fault propagation simulation, the probability of each node being affected by the fault is calculated. According to the calculated fault probability value, the nodes with a greater than preset fault probability are screened out. A fault network model is constructed using the screened nodes and the connection relationship between them. In the fault network model, different colors, shapes, or marks can be used to represent the nodes affected by the fault and the connections between them.

[0041] For example, if the nodes of the power transmission and transformation network are A, B, C, D, and E, and the connection relationship is as follows: A is connected to B and C; B is connected to A and D; C is connected to A and E; D is connected to B and E; E is connected to C and D, this network can be represented as a graph, with nodes representing substations or equipment and edges representing power transmission lines. If a fault is detected at node A, A is the first fault source. The fault of A directly affects B and C; through B, the fault may propagate to D; through C, the fault may propagate to E. Assuming that the probability of fault propagation is as follows: AB: 0.8; AC: 0.6; BD: 0.5; CE: 0.7, based on these propagation probabilities, the failure probability of each node can be calculated. The failure probability of node A is 1. The failure probability of node B is 0.8. The failure probability of node C is 0.6. The failure probability of node D is the propagation probability from B to D: 0.8*0.5=0.4. The failure probability of node E is the propagation probability from C to E: 0.6*0.7=0.42. If the preset fault probability threshold is 0.5, select nodes with a fault probability greater than 0.5 to build a fault network. The fault probabilities of nodes A, B, and C are all greater than 0.5, so they form a fault network. The fault probabilities of nodes D and E are less than 0.5, so they are not in the fault network. The final fault network is as follows: nodes: A, B, C; edges: AB, AC.

[0042] Furthermore, the fault network construction module 15 is also used for:

[0043] A conditional probability table for each transmission and transformation electronic network is defined, wherein the failure probability of each node in each transmission and transformation electronic network depends on the state of its parent node, wherein each node is set with an initial prior probability; the initial state of the conditional probability table is set according to the first fault source; based on the initial state of the conditional probability table, the posterior probability of the conditional probability table is calculated using the Bayesian formula, and the failure probability of each node is output.

[0044] Specifically, in the power grid network, each node represents a device or component, and its parent node is the other node directly connected to the node. Set an initial prior probability for each node, based on historical data or system defaults. For each node, determine its parent node and set the conditional probability of each parent node state. These conditional probabilities reflect the impact of the state of the parent node on the failure probability of the child node. According to the results of the fault tracing analysis, determine the first fault source and set its initial state. It is a triggering event, such as line disconnection or equipment damage. According to the initial state of the first fault source, update the state of its parent node, which affects the conditional probability of the child node. Use the Bayesian formula to calculate the posterior probability of each node, that is, the probability of the node failing when the parent node state is known. After the initial state of the first fault source is known, iteratively update the posterior probability of each node according to the Bayesian formula until convergence or the preset number of iterations is reached. Output the posterior probability of each node, which reflects the probability of each node failing after considering the state of other nodes in the network.

[0045] Furthermore, the key control circuit acquisition module 16 is also used for:

[0046] The fault network is subjected to network centrality analysis through a network centrality analysis model, and the degree centrality, betweenness centrality and closeness centrality of each node are calculated; the degree centrality, betweenness centrality and closeness centrality of each node are integrated to output the network centrality index of each node; nodes are connected according to the size of the network centrality index of each node to obtain the first key control line.

[0047] Specifically, degree centrality refers to the number of connections between a node and other nodes in the network. In a fault network, nodes with high degree centrality have higher fault propagation capabilities. Betweenness centrality measures the frequency of a node as a shortest path bridge in a network. In a fault network, nodes with high betweenness centrality are key nodes for fault propagation. Closeness centrality refers to the average shortest path length from a node to all other nodes in the network. In a fault network, nodes with high closeness centrality are usually in a core position in the network. Degree centrality, betweenness centrality, and closeness centrality are integrated to calculate the comprehensive network centrality index of each node. This is achieved through weighted average, hierarchical analysis method, or other comprehensive evaluation methods. According to the specific situation of the power grid and the purpose of analysis, the weights of degree centrality, betweenness centrality, and closeness centrality in the comprehensive index are determined. According to the comprehensive network centrality index of each node, the nodes are sorted. The node with the highest comprehensive index is selected as the first key control line. It is the most important node in the fault network because it has the greatest impact on the stability and security of the power grid. According to the connection relationship of the key nodes, the lines directly connected to them are analyzed, which are the first key control lines.

[0048] Exemplarily, a fault network is constructed, and the fault network nodes are A, B, C, D, and E, and the connection relationship is as follows: AB; AC; BD; CE; the degree centrality, betweenness centrality, and closeness centrality of each node are calculated. The degree centrality represents the number of connections of a node, A: 2 (connecting B and C); B: 2 (connecting A and D); C: 2 (connecting A and E); D: 1 (connecting B); E: 1 (connecting C); betweenness centrality represents the importance of a node on the shortest path, A: 0.5; B: 0.5; C: 0.5; D: 0; E: 0; closeness centrality represents the average distance between a node and other nodes, A: 1 / 2=0.5; B: 1 / 2.5=0.4; C: 1 / 2.5=0.4; D: 1 / 3=0.33; E: 1 / 3=0.33; the centrality index is standardized and then summed to obtain the network centrality index of each node. Assign equal weight to each centrality index, and the network centrality index of each node is as follows: A: (0.5+0.5+0.5) / 3=0.5; B: (0.5+0.5+0.4) / 3=0.4667; C: (0.5+0.5+0.4) / 3=0.4667; D: (0+0.33+0.33) / 3=0.22; E: (0+0.33+0.33) / 3=0.22, connect nodes according to network centrality index, and obtain key control lines. According to the size of network centrality index, determine the most important nodes and their connection relationships. If the two key control lines with the highest centrality are selected, AB (A and B have higher network centrality index); AC (A and C have higher network centrality index) Therefore, AB and AC are key control lines.

[0049] Furthermore, the key control circuit acquisition module 16 is also used for:

[0050] Obtain a first line node number and a second line node number of the fault network, wherein the first line node number is the maximum number of nodes continuously connected in the fault network, and the second line node number is the minimum number of nodes continuously connected in the fault network; determine the k value according to the first line node number and the second line node number, and then perform k node connections.

[0051] Specifically, in a fault network, continuous connection refers to the number of farthest nodes that can be reached from a node through direct or indirect connection. Find the maximum number of nodes connected continuously in the fault network. This is achieved by traversing the network, recording the length of continuous connections from each node, and comparing these lengths. Find the minimum number of nodes connected continuously in the fault network. This is achieved by traversing the network in the same way, recording the length of continuous connections from each node, and comparing these lengths. The k value is set by a technician in this field according to the specific situation of the power grid and the purpose of analysis. The k value is an integer representing the number of nodes to be connected. The selection of the k value should take into account the impact of the fault on the stability of the power grid. The larger the k value, the more nodes are connected, and the wider the impact range of the fault may be. According to the number of nodes in the first line and the number of nodes in the second line, k continuously connected nodes are selected for connection. According to the selected nodes, a connection operation is performed, including changing the connection state of the line, adjusting the parameters of the equipment, etc. After the connection operation is completed, the operating state of the power grid is monitored and the effect of the connection operation is evaluated.

[0052] Furthermore, the key control line acquisition module 16 is also used to obtain a first key control line that meets the key constraint condition, wherein the key constraint condition is that the network center index of k consecutive nodes is greater than a preset network center index, and the k consecutive nodes do not include edge nodes.

[0053] Specifically, the key constraint is that the sum of the network center index of k consecutive nodes must be greater than the preset network center index. Traverse the fault network and find k consecutive nodes that meet the key constraint. This is achieved by traversing the network, recording the length of the continuous connection from each node, and comparing these lengths. Make sure that the selected k consecutive nodes do not include edge nodes, that is, those nodes with only one connection. For each combination of k consecutive nodes that meets the key constraint, calculate its network center index and. Among all the k consecutive node combinations that meet the key constraint, select the node combination with the largest network center index and as the first key control line.

[0054] Furthermore, the fault tracing module 14 is also used for:

[0055] Perform fault tracing based on the multi-block operation data set to determine whether the fault occurring in each transmission and transformation electronic network is a mixed fault source, wherein a mixed fault source is two or more fault sources; identify the transmission and transformation electronic network with mixed fault sources, and output the identified transmission and transformation electronic network; construct a mixed fault network corresponding to the identified transmission and transformation electronic network; and input the mixed fault network into the network center analysis model for network center analysis.

[0056] Specifically, a multi-block running data set is used to determine the location and type of fault by analyzing the changes in parameters such as voltage, current, and power. According to the fault tracing analysis, the fault source in each transmission and transformation electronic network is determined. If a fault source affects multiple transmission and transformation electronic networks at the same time, it is considered that the fault source is a mixed fault source. In the fault tracing analysis, the transmission and transformation electronic networks affected by the mixed fault source are marked. These transmission and transformation electronic networks affected by the mixed fault source are output. According to the results of the fault tracing analysis, the impact range of the mixed fault source, that is, the affected transmission and transformation electronic network, is determined. Using the graph theory method, a mixed fault network model containing mixed fault sources and affected transmission and transformation electronic networks is constructed. The constructed mixed fault network is input into the network center analysis model. The network center indicators such as degree centrality, betweenness centrality, and closeness centrality are calculated for the nodes in the mixed fault network. According to the results of the network center analysis, the key nodes and key lines in the mixed fault network are determined, which are the key paths for fault propagation.

[0057] Exemplarily, obtaining a multi-block operation data set If the power transmission and transformation network includes two blocks, its multi-block operation data set is as follows: Operation data of block one (nodes A, B, C): A: normal; B: fault; C: fault; Operation data of block two (nodes D, E, F): D: normal; E: normal; F: fault; Determine whether there is a mixed fault source (two or more fault sources) in each block, block one: nodes B and C are faulty, so there is a mixed fault source in block one. Block two: only node F is faulty, so there is no mixed fault source in block two. Block one is identified as a power transmission and transformation electronic network with mixed fault sources. For the identified power transmission and transformation electronic network (block one), construct its corresponding mixed fault network. Assuming that its connection relationship is as follows: AB; AC; BC, input the mixed fault network into the network center analysis model for network center analysis. Perform network center analysis on the constructed mixed fault network, including calculating the degree centrality, betweenness centrality and closeness centrality of each node. Degree centrality: A: 2 (connects B and C); B: 2 (connects A and C); C: 2 (connects A and B); Betweenness centrality: A: 0; B: 1; C: 1; Closeness centrality: A: 1; B: 1; C: 1; The centrality index is standardized and fused to obtain the network centrality index of each node. Assuming that each centrality index is given equal weight: A: (2+0+1) / 3=1; B: (2+1+1) / 3=1.33; C: (2+1+1) / 3=1.33; According to the size of the centrality index, B and C have higher centrality indexes, and A is relatively low.

[0058] Furthermore, the fault tracing module 14 is also used for:

[0059] Obtain N fault sources that identify the transmission and transformation electronic network, where N is a positive integer greater than or equal to 2; obtain N fault networks corresponding to the N fault sources; and fuse the N fault networks by resetting redundant nodes to output a mixed fault network.

[0060] Specifically, according to the multi-block operation data set, fault source tracing analysis is performed to determine the fault source of each transmission and transformation electronic network. If a fault source affects multiple transmission and transformation electronic networks at the same time, it is regarded as a mixed fault source. According to the analysis results, N fault sources that identify the transmission and transformation electronic network are obtained, where N is a positive integer greater than or equal to 2. For each fault source, a fault network is constructed, which includes the affected transmission and transformation electronic networks and their connection relationships. According to the number of fault sources, the corresponding N fault networks are constructed. In the N fault networks, redundant nodes are identified, that is, nodes that exist in multiple networks. For each redundant node, its connection relationship in multiple fault networks is reset to a unique connection relationship. The reset N fault networks are fused to form a mixed fault network. Using graph theory methods, a mixed fault network model containing all fault sources and affected transmission and transformation electronic networks is constructed. The constructed mixed fault network is output for subsequent analysis and processing. Through the above steps, N fault sources that identify the transmission and transformation electronic network can be obtained, and the corresponding N fault networks can be constructed and fused to output a mixed fault network, so as to better understand and deal with complex power grid fault conditions.

[0061] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0062] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A power distribution control platform based on power transmission and transformation risk prediction, characterized by: include: A topology network acquisition module is used to acquire the power transmission and transformation topology network; A network partitioning module is used to partition the power transmission and transformation topology network according to the control source, and output multiple power transmission and transformation electronic networks, wherein each power transmission and transformation electronic network is regulated by the same control source; An operation monitoring module, used for monitoring the operation data of each of the plurality of transmission and transformation electronic networks to obtain a multi-block operation data set; A fault tracing module, used to perform fault tracing according to the multi-block operation data set, and detect the first fault source corresponding to each transmission and transformation electronic network; A fault network construction module, used to construct a corresponding fault network according to the first fault source corresponding to each transmission and transformation electronic network; A key control line acquisition module is used to perform a network center analysis on the fault network through a network center analysis model to obtain a first key control line corresponding to each transmission and transformation electronic network; The power distribution control module is used to control the control source of the corresponding transmission and transformation electronic network to perform power distribution control according to the first key control circuit.

2. The power distribution control platform based on power transmission and transformation risk prediction according to claim 1, characterized in that: The Fault Network Building Blocks are also used to: Obtain the connection relationship in each transmission and transformation electronic network; Performing fault propagation analysis on the first fault source according to the connection relationship, obtaining nodes in the transmission and transformation electronic network affected by the fault propagation, and calculating the fault probability of each node; According to the fault probability value of each node, the fault network is generated according to the nodes with a fault probability greater than a preset value.

3. The power distribution control platform based on power transmission and transformation risk prediction according to claim 2 is characterized in that: The Fault Network Building Blocks are also used to: Defining a conditional probability table for each transmission and transformation electronic network, wherein the conditional probability table indicates that the failure probability of each node in each transmission and transformation electronic network depends on the state of its parent node, wherein each node is set with an initial prior probability; Setting an initial state of the conditional probability table according to the first fault source; Based on the initial state of the conditional probability table, the posterior probability of the conditional probability table is calculated using the Bayesian formula, and the failure probability of each node is output.

4. The power distribution control platform based on power transmission and transformation risk prediction according to claim 1, characterized in that: The key control line acquisition module is also used to: Performing network center analysis on the fault network through a network center analysis model, and calculating the degree centrality, betweenness centrality and closeness centrality of each node; According to the degree centrality, betweenness centrality and closeness centrality of each node, the network centrality index of each node is output; Nodes are connected according to the size of the network center index of each node to obtain the first key control line.

5. The power distribution control platform based on power transmission and transformation risk prediction according to claim 4, characterized in that: The key control line acquisition module is also used to: Acquire a first line node number and a second line node number of the faulty network, wherein the first line node number is a maximum number of nodes continuously connected to nodes in the faulty network, and the second line node number is a minimum number of nodes continuously connected to nodes in the faulty network; The k value is determined according to the number of the first line nodes and the number of the second line nodes, and then k nodes are connected.

6. The power distribution control platform based on power transmission and transformation risk prediction according to claim 5, characterized in that: The key control line acquisition module is also used to obtain a first key control line that meets key constraints, wherein the key constraints are that the network center index of k consecutive nodes is greater than a preset network center index, and the k consecutive nodes do not include edge nodes.

7. The power distribution control platform based on power transmission and transformation risk prediction according to claim 1, characterized in that: The fault tracing module is also used to: Perform fault tracing according to the multi-block operation data set to determine whether the fault occurring in each transmission and transformation electronic network is a mixed fault source, wherein a mixed fault source is two or more fault sources; Identify the transmission and transformation electronic network with mixed fault sources, and output the identified transmission and transformation electronic network; Constructing a mixed fault network corresponding to the identified transmission and transformation electronic network; The mixed fault network is input into the network-centric analysis model for network-centric analysis.

8. The power distribution control platform based on power transmission and transformation risk prediction according to claim 7, characterized in that: The fault tracing module is also used to: Obtain and identify N fault sources of the transmission and transformation electronic network, where N is a positive integer greater than or equal to 2; Obtaining N fault networks corresponding to the N fault sources; The N fault networks are merged by resetting redundant nodes to output a mixed fault network.

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