Distribution network outage risk assessment method, device and electronic equipment

Abstract

The present invention provides a method, device and electronic equipment for assessing the outage risk of a distribution network. The method, device and electronic equipment for assessing the outage risk of a distribution network provided by the present invention determine whether the original network diagram of the distribution network is a cyclic network diagram, and perform tree decomposition on the original network diagram that is a cyclic network diagram to obtain a tree network diagram under each decomposition scenario. The scene existence probability of each decomposition scenario and the power-on probability of each node in the tree network diagram under the scenario are used to assess the outage risk of each node in the original network diagram, thereby achieving outage risk assessment of the target distribution network, thereby utilizing the tree decomposition principle and the node power-on probability solution principle to achieve accurate and reliable distribution network outage risk assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power grids, and in particular to a method, device, and electronic equipment for evaluating the risk of outage in a distribution network. Background Art

[0002] The distribution network, which distributes electricity from the main grid to the user end, is widely distributed within the power system. Reliable operation of the distribution network is essential for the safe and stable operation of the power system. Therefore, assessing the risk of distribution network outages can effectively determine whether the distribution network is operating reliably.

[0003] However, with the surge in users' demand for electricity, the scale of distribution networks has shown a trend of rapid expansion, the number of system nodes has increased rapidly, and the structure has become increasingly complex. As a result, the existing distribution network outage risk assessment method cannot accurately infer the outage probability of each node in the distribution network, and the reliability of the outage risk assessment results is low.

[0004] Therefore, there is an urgent need for a more accurate and reliable distribution network outage risk assessment method to solve the above technical problems. Summary of the Invention

[0005] The present invention provides a distribution network outage risk assessment method, device and electronic equipment to address the defects of the existing distribution network outage risk assessment method in the art, namely, the inability to accurately infer the outage probability of each node in the distribution network and the low reliability of the outage risk assessment results, thereby achieving accurate and reliable assessment of the distribution network outage risk.

[0006] In a first aspect, the present invention provides a method for assessing the risk of a power distribution network outage, the method comprising:

[0007] Obtain the original network diagram of the target distribution network;

[0008] Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, perform tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario.

[0009] Obtain the scenario existence probability corresponding to each decomposition scenario, and calculate the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario;

[0010] Based on the scenario existence probability and the power-on probability of each node in the tree network diagram, the outage risk of each node in the original network diagram is evaluated to obtain an outage risk assessment result of the target distribution network.

[0011] According to a method for assessing the outage risk of a distribution network provided by the present invention, it is determined whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is subjected to tree decomposition based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario, including:

[0012] Determine whether the original network graph is a cyclic network graph, and if the original network graph is a cyclic network graph, construct a spanning tree and a branch set corresponding to the original network graph;

[0013] Enumerating the on-off combinations of each branch in the branch set, and merging some nodes in the spanning tree according to a preset merging condition to generate a transition network diagram;

[0014] Determine whether the transition network graph is a cyclic network graph, and if the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph;

[0015] Enumerate the on-off combinations of each branch in the branch set corresponding to the transition network diagram, and merge some nodes in the spanning tree corresponding to the transition network diagram according to the preset merging conditions until the decomposition termination conditions are met, so as to obtain the tree network diagram corresponding to each decomposition scenario.

[0016] The above tree decomposition process is mainly aimed at scenarios where the original network diagram structure is relatively simple. By determining whether the original network diagram is a cyclic network diagram and performing tree decomposition on the original network diagram that is a cyclic network diagram, a tree network diagram under each decomposition scenario is obtained, which facilitates the subsequent solution of the probability of each node being powered.

[0017] According to a method for assessing the outage risk of a distribution network provided by the present invention, it is determined whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is subjected to tree decomposition based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario, including:

[0018] Determine whether the original network diagram is a cyclic network diagram, and if so, divide the original network diagram into multiple local network diagrams;

[0019] Performing structure completion processing on each of the local network graphs to obtain a completed local network graph;

[0020] Determine whether the completed local network graph is a cyclic network graph, and if the completed local network graph is a cyclic network graph, construct a spanning tree and a branch set corresponding to the completed local network graph;

[0021] Enumerating the on-off combinations of each branch in the branch set, and merging some nodes in the spanning tree according to a preset merging condition to generate a transition network diagram;

[0022] Determine whether the transition network graph is a cyclic network graph, and if the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph;

[0023] Enumerate the on-off combinations of each branch in the branch set corresponding to the transition network diagram, and merge some nodes in the spanning tree corresponding to the transition network diagram according to the preset merging conditions until the decomposition termination conditions are met, so as to obtain the tree network diagram corresponding to each decomposition scenario.

[0024] The above tree decomposition process is targeted at scenarios where the original network diagram has a complex structure. Because complex distribution networks contain multiple transfer lines, direct tree decomposition would result in a large number of decomposition scenarios and a lengthy decomposition process. Therefore, the present invention first divides the original network diagram into blocks and then performs tree decomposition on each of the resulting local network diagrams. This reduces the number of topology enumerations and significantly improves decomposition efficiency.

[0025] According to a method for assessing the risk of a distribution network outage provided by the present invention, the original network diagram is divided into blocks and divided into multiple local network diagrams, including:

[0026] The main power supply node in the original network diagram is removed, and multiple local network diagrams are obtained by dividing the original network diagram.

[0027] The present invention can divide the original network diagram into multiple connected components by removing the main power supply node in the original network diagram, thereby obtaining multiple local network diagrams. The block division process is simple and easy to implement.

[0028] According to a method for assessing the risk of a distribution network outage provided by the present invention, a structure completion process is performed on each of the local network diagrams to obtain a completed local network diagram, including:

[0029] A main power supply node and lines related to the main power supply node are added to each of the local network diagrams to obtain a completed local network diagram.

[0030] In order to ensure the smooth progress of the tree decomposition process with the local network diagram as the decomposition object, it is necessary to complete the local network diagrams and complete the main power nodes and related lines removed during the block division to ensure the accuracy and reliability of the tree decomposition process.

[0031] According to a method for assessing the outage risk of a distribution network provided by the present invention, the decomposition termination condition is that the newly generated transition network diagram is a non-cyclic network diagram or the scenario existence probability of the current decomposition scenario is less than a preset probability threshold.

[0032] When determining whether the tree decomposition process has ended, the transition network diagram can be judged by whether it is a non-cyclic network diagram. When the transition network diagram is a non-cyclic network diagram, it means that the probability of each node being powered can be calculated based on the current decomposition scenario, and a tree network diagram can be output. To shorten the decomposition time of the tree decomposition, a probability threshold can also be set to determine whether the probability of the scene existing in the current decomposition scenario is too low. If the probability of the scene existing in the current decomposition scenario is too low, the decomposition can be terminated, which can improve the decomposition efficiency.

[0033] According to a method for assessing the outage risk of a distribution network provided by the present invention, obtaining the scenario existence probability corresponding to each decomposed scenario includes:

[0034] Obtain the disconnected line set, closed line set, and semi-disconnected line set in the tree network diagram under each decomposition scenario respectively;

[0035] Based on the disconnection probability of each line in the disconnected line set, the closing probability of each line in the closed line set, and the closing probability of each line in the semi-disconnected line set, a scenario existence probability corresponding to each decomposed scenario is obtained.

[0036] According to a method for assessing the outage risk of a distribution network provided by the present invention, based on the probability of the scenario existing and the probability of power being supplied to each node in the tree network diagram, the outage risk of each node in the original network diagram is assessed to obtain an outage risk assessment result of the target distribution network, including:

[0037] Based on the scenario existence probability and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, the power-on probability of each node in the original network diagram is calculated;

[0038] Based on the power-on probability of each node in the original network diagram, the outage probability of each node in the original network diagram is calculated to obtain an outage risk assessment result of the target distribution network.

[0039] The present invention evaluates the outage risk of the distribution network by calculating the outage probability of each node in the original network diagram of the distribution network, and can obtain accurate and reliable evaluation results.

[0040] In a second aspect, the present invention further provides a device for assessing the risk of a power distribution network outage, the device comprising:

[0041] An acquisition module is used to obtain the original network diagram of the target distribution network;

[0042] A first processing module is configured to determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is decomposed into trees based on different decomposition scenarios to obtain tree network diagrams corresponding to the decomposition scenarios.

[0043] The second processing module is used to obtain the scene existence probability corresponding to each decomposition scene, and to obtain the power-on probability of each node in the tree network diagram corresponding to each decomposition scene;

[0044] The third processing module is used to evaluate the outage risk of each node in the original network diagram based on the existence probability of the scenario and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, and obtain the outage risk assessment result of the target distribution network.

[0045] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for assessing the risk of distribution network outage as described above are implemented.

[0046] The method, device and electronic equipment for assessing the outage risk of a distribution network provided by the present invention determine whether the original network diagram of the distribution network is a cyclic network diagram, and perform tree decomposition on the original network diagram that is a cyclic network diagram to obtain a tree network diagram under each decomposition scenario. The scene existence probability of each decomposition scenario and the power-on probability of each node in the tree network diagram under the scenario are used to assess the outage risk of each node in the original network diagram, thereby achieving outage risk assessment of the target distribution network, thereby utilizing the tree decomposition principle and the node power-on probability solution principle to achieve accurate and reliable distribution network outage risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 1 is a flow chart of a method for assessing the risk of a distribution network outage provided by the present invention;

[0049] Figure 2 It is a schematic diagram of the tree decomposition principle of a distribution network containing three nodes;

[0050] Figure 3 It is a schematic diagram of the principle of block partitioning of a distribution network with m connected components;

[0051] Figure 4 This is a schematic diagram of the principle of merging node clusters in a scenario where there are adjacent node clusters;

[0052] Figure 5 This is a schematic diagram of the principle of renumbering the lines;

[0053] Figure 6 It is a schematic diagram of the topological structure of each line collection in the distribution system;

[0054] Figure 7 This is a schematic diagram of the principle of solving the probability of nodes being charged in a local directed area;

[0055] Figure 8 This is a schematic diagram of the tree decomposition results of a single-source power distribution system;

[0056] Figure 9 This is a schematic diagram of the tree decomposition results of the multi-power distribution system;

[0057] Figure 10 Schematic diagram of the structure of the device for assessing the risk of power distribution network outage provided by the present invention;

[0058] Figure 11 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0060] The following combination Figures 1-11 The present invention describes a method, device, and electronic device for evaluating the risk of power distribution network outage.

[0061] Figure 1 The present invention provides a method for assessing the risk of a power distribution network outage, which includes:

[0062] Step 110: Obtain an original network diagram of the target distribution network.

[0063] This embodiment uses the known topology data of the target distribution network and the reliability data of the lines to obtain the original network diagram of the target distribution network. The network diagram represents power sources and loads in the form of nodes, and represents lines through connections between nodes. The reliability data of the lines is the probability that each line has power.

[0064] Step 120: Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, perform tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario.

[0065] In order to improve the calculation efficiency and accuracy of the distribution network outage probability, this embodiment uses an extended probability graph model to calculate the node outage probability. The model can solve the target node's power probability based on the power probability of the surrounding nodes and connected lines, and then the target node's outage probability can be obtained. The extended probability graph model mainly draws on the local dependency relationship of the probability graph model, takes the node power probability as the unknown quantity, and writes the node power probability equation based on the power supply status of the node's adjacent nodes. Since the distribution network is generally a highly sparse network, the Newton iteration method based on sparse matrices is used to solve the equation group, which can greatly improve the calculation efficiency. This equation is applicable to radial distribution networks and can solve the network outage probability containing multiple distributed power sources. The accuracy of this method depends only on the convergence criterion of the Newton iteration method. By setting a reasonable convergence criterion, accurate reasoning within the allowable error range can be achieved.

[0066] Considering that the solution of the node outage probability mentioned above is only applicable to radial distribution networks (which are represented as a tree in topology), it is necessary to determine whether the distribution network to be solved is a ring network before solving it. When facing a distribution network with a loop, it needs to be converted into multiple independent tree networks before further solution can be performed.

[0067] When the target distribution network structure is relatively simple, the above process of determining whether the original network diagram is a cyclic network diagram and, if the original network diagram is a cyclic network diagram, performing tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario may include:

[0068] First, determine whether the original network graph is a cyclic network graph. If the original network graph is a cyclic network graph, construct the spanning tree and branch set corresponding to the original network graph;

[0069] Then, the on-off combinations of each branch in the branch set are enumerated, and some nodes in the spanning tree are merged according to the preset merging conditions to generate a transition network diagram;

[0070] Afterwards, it is determined whether the transition network graph is a cyclic network graph. If the transition network graph is a cyclic network graph, the spanning tree and the connected branch set corresponding to the transition network graph are constructed again.

[0071] Finally, the on-off combinations of each branch in the branch set corresponding to the transition network diagram are enumerated, and some nodes in the spanning tree corresponding to the transition network diagram are merged according to the preset merging conditions until the decomposition termination conditions are met, and the tree network diagram corresponding to each decomposition scenario is obtained.

[0072] For an undirected cyclic connected graph G = (V, E), we can always find a spanning tree T = (V, E T ) and the connected branch set E L =EE TFor nodes u and v at both ends of a branch (u, v), if the branch (u, v) has been proven to be reliable, then the power states of u and v should be the same and they can be considered as one node; otherwise, (u, v) can be deleted from the connectivity graph.

[0073] For the graph generated according to the above rules, we continue to determine whether it contains cycles (i.e., whether it is a cyclic network graph). If it does not, we enter the tree stack and output a tree network graph. If it does, we enter the cyclic network stack and continue decomposition. Since the spanning tree of a connected graph always exists, and the decomposition process includes node merging, the number of nodes in the graph continues to decrease. Therefore, any cyclic network graph can always be decomposed into a certain number of tree network graphs using the above rules.

[0074] See attached Figure 2 This embodiment takes a three-node distribution network as an example to explain the tree decomposition process in detail:

[0075] Figure 2 The leftmost part is the original network diagram of the distribution network, which contains a power node, load node 1, and load node 2. Obtain the spanning tree of the original network diagram and obtain the connected branch set E r = {(1,2)}. Since the network diagram specifies the power supply nodes, the directionality of the power supply allows the undirected loop network to be decomposed into two directed tree-like network diagrams. Specifically, assuming line 1-2 is faulty, a corresponding tree-like network diagram can be obtained. Assuming line 1-2 is intact, a corresponding tree-like network diagram can also be obtained, thus decomposing the original network diagram into two tree-like network diagrams. Since the direction is known, the outage probability of each node can be calculated using traditional Bayesian network inference methods.

[0076] Considering that tree decomposition can accurately solve general loop networks, for a distribution network with N transfer lines, at least 2 N In a decomposition scenario, the amount of calculation increases dramatically with the expansion of the distribution network scale.

[0077] In actual power distribution systems, transfer lines often form power supply loops within one area without affecting other areas. The overall system presents a tree-like structure with local loops. Therefore, each decomposition can be performed within a single area, which greatly reduces the number of topology enumerations.

[0078] Based on this, when facing a large-scale and complex distribution network, the above-mentioned process of determining whether the original network diagram is a cyclic network diagram and, if the original network diagram is a cyclic network diagram, performing tree decomposition on the original network diagram based on different decomposition scenarios to obtain the tree network diagram corresponding to each decomposition scenario may include:

[0079] The first step is to determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is divided into blocks and divided into multiple local network diagrams.

[0080] The second step is to perform structural completion processing on each local network graph to obtain a completed local network graph;

[0081] The third step is to determine whether the completed local network graph is a cyclic network graph. If the completed local network graph is a cyclic network graph, construct the spanning tree and branch set corresponding to the completed local network graph.

[0082] The fourth step is to enumerate the on-off combinations of each branch in the branch set, and merge some nodes in the spanning tree according to the preset merging conditions to generate a transition network diagram;

[0083] The fifth step is to determine whether the transition network graph is a cyclic network graph. If the transition network graph is a cyclic network graph, the spanning tree and branch set corresponding to the transition network graph are constructed again.

[0084] The sixth step is to enumerate the on-off combinations of each branch in the branch set corresponding to the transition network diagram, and merge some nodes in the spanning tree corresponding to the transition network diagram according to the preset merging conditions until the decomposition termination conditions are met, and obtain the tree network diagram corresponding to each decomposition scenario.

[0085] Specifically, the process of dividing the original network graph into multiple local network graphs may include:

[0086] The main power supply node in the original network graph is removed and divided into multiple local network graphs.

[0087] Specifically, the process of performing structure completion processing on each local network graph to obtain a completed local network graph may include:

[0088] The main power supply node and the lines related to the main power supply node are added to each local network diagram respectively to obtain a completed local network diagram.

[0089] See attached Figure 3 , the principle of distribution network partitioning is explained by taking a distribution network with m connected components (i.e., local networks) as an example.

[0090] like Figure 3 As shown in the figure, the squares represent the local network areas that form loops, and the dots represent the main power nodes. When solving, the source nodes of the tree are first deleted from the graph. The source nodes generally correspond to the main power nodes in the distribution network, not the distributed power nodes, so that the graph is divided into m connected components. Then, for each connected component, the source nodes and the corresponding connecting lines are added and the tree decomposition is performed separately. This block solution method reduces the solution complexity from 2 N Reduced to where n i is the number of transfer lines included in block i, and satisfies n1+n2+…+n m =N.

[0091] It should be noted that the preset merging conditions mentioned in the above process mainly include topology merging rules and common adjacent node merging rules.

[0092] During the tree decomposition process, since the network may have loops of different forms, this embodiment defines a topology merging rule to describe special cases of network decomposition and saves merging records to facilitate subsequent calculations.

[0093] Define a vertex cluster as a merged record of nodes, which is a mapping from node number to node set. In the tree decomposition step, if the current graph G k The node i in the original graph G is merged with the nodes j, k, ..., then the node cluster V i ={i,j,k,…}; when no node is merged, the node cluster V i ={i}.

[0094] The definition of a node cluster combines multiple nodes into one node. By treating multiple edges as parallel and merging them into one line, the unilateral nature of the graph is maintained, thereby reducing the computational complexity of solving the outage probability. The reliability of multiple lines in parallel can be calculated as follows:

[0095]

[0096] Among them, R′ u-v Represents the node cluster V u 、V v The parallel equivalent reliability of the lines between x-y Indicates the probability that the line between node x and node y is intact.

[0097] For two node clusters to be merged, if they have a common adjacent node cluster, then after the merger, the merged cluster and the common adjacent cluster will be connected through multiple paths. These connection lines are in a parallel relationship. The disconnection of any line will not affect the connectivity of the two node clusters. Similarly, the parallel information of the lines in this scenario also needs to be recorded.

[0098] Figure 4 The principle of merging node clusters in the presence of adjacent node clusters is shown. Figure 4 Mid-node cluster V u 、V v are two node clusters to be merged, V o is a cluster of common adjacent nodes, and the merged cluster V u +Vv With the common adjacent node cluster V o They are connected by two paths.

[0099] After merging, the lines need to be renumbered. For details, see the attached Figure 5 , for two node clusters to be merged (V u ,V v ), if there is a node cluster V w It is V v adjacent clusters and non-public adjacent clusters, assuming that V v Merged into V u Then the line (v,w) needs to be renumbered as (u,w) after merging, and the reliability of the new line uw is R u-w =R v-w .

[0100] After the merger, the nodes need to be renumbered. Specifically, according to the node numbers at both ends, the two node clusters V are merged. u and V v , the union V u ∪V v Map to node number u and delete the merged node cluster V v .

[0101] It should be noted that when performing tree decomposition, the decomposition termination condition can be that the newly generated transition network diagram is a non-cyclic network diagram, that is, the newly generated transition network diagram is a tree, or the scene existence probability of the current decomposition scene is less than a preset probability threshold.

[0102] For a larger distribution system or a distribution system with complex loops, its scenario decomposition may require several topology enumerations and merging, which takes a long time. To this end, this embodiment can add a pruning link during the decomposition process. When the probability of a decomposition scenario with a loop network occurring (i.e., the probability of the current decomposition scenario existing) is lower than a preset probability threshold, the decomposition will not continue. Instead, the logarithm of the reliability of the edge (i.e., the probability of the branch being intact) is used as the weight to find a maximum spanning tree (i.e., the most reliable tree), and use this maximum spanning tree as the tree network diagram of the current decomposition scenario.

[0103] It is not difficult to see that the introduction of the above pruning link can effectively improve the decomposition efficiency of tree decomposition.

[0104] Step 130: Obtain the scenario existence probability corresponding to each decomposition scenario, and calculate the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario.

[0105] In this embodiment, the process of obtaining the scene existence probability corresponding to each decomposed scene may include:

[0106] First, the disconnected line set, closed line set, and half-open line set in the tree network diagram under each decomposition scenario are obtained respectively;

[0107] Then, based on the disconnection probability of each line in the disconnected line set, the closing probability of each line in the closed line set, and the closing probability of each line in the semi-disconnected line set, the scenario existence probability corresponding to each decomposed scenario is obtained.

[0108] Since each decomposition scenario corresponds to a tree network diagram during the decomposition process according to the tree decomposition rules, each resulting tree network diagram can be understood as a decomposition scenario. Since the decomposition scenario incorporates the assumption that some lines are disconnected while others are operating normally, each decomposition scenario is associated with a probability value—the scenario existence probability—to indicate the likelihood that this assumption holds true. The scenario existence probabilities of different decomposition scenarios are related to the reliability of each line in the actual power grid. Therefore, for an actual distribution network, once the grid structure is determined, only one topological decomposition is required, and the decomposition results saved. When the disaster scenario to be analyzed changes, the scenario existence probabilities corresponding to each decomposition scenario are recalculated.

[0109] Assuming that there is no correlation between line faults, then for any connecting edge (u,v)∈E L , let its survival probability be R u-v , the probability of line opening and closing is 1-R u-v and R u-v Obviously, the opening and closing of a line are mutually exclusive events.

[0110] For graph G, the evidence set L k Represents the decomposition scene G k Determine the circuit combination of open and closed states, its subset Indicates a disconnected line set. Represents a closed circuit set. However, for some scenarios where there are common adjacent nodes to merge, such as Figure 4 In the scenario shown, the lines between the two node clusters are in parallel. To disconnect the line between the two node clusters, all the connection lines between the two node clusters need to be disconnected, while to ensure survival, only at least one connection line needs to survive. Therefore, the semi-disconnected line set is defined. At least one of the lines is alive. Figure 6 The topological structure of each line collection in the power distribution system is shown.

[0111] Therefore, in the current evidence set L k Next, decompose scene G k The formula for calculating the probability of the scene existence is as follows:

[0112]

[0113] Among them, (i,j) represents the closed circuit set One of the lines, R i-j represents the probability that the line between node i and node j is intact, and (m,n) represents the set of disconnected lines One of the lines, R m-n represents the probability that the line between node m and node n is intact, Represents a set of half-open circuits In the i-th group of semi-disconnected lines, (x, y) represents a line in the semi-disconnected lines, R x-y Indicates the probability that the line between node x and node y is intact.

[0114] In this embodiment, the process of obtaining the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario can be obtained through connectivity reliability, which describes the connectivity probability from the source node to the load node in the tree network diagram (i.e., the probability of the existence of a connectivity path). Assuming that all power nodes in the distribution network are reliable (i.e., the power-on probability is 1), the outage probability calculation for each node is to solve the value of a joint distribution, that is:

[0115] P(e i ,e s1 ,e s2 ,…) (3)

[0116] Among them, e i is the power event at node i, e s1 ,e s2 ,… indicates that there is an electrical event at each power node. Based on the above assumptions, P(e s1 )=P(e s2 )=…=1, the power supply is always on. Therefore, solving the value of this joint distribution is the same as solving the marginal distribution, that is:

[0117] P(e i ,e s1 ,e s2 ,…)=P(e i ) (4)

[0118] In the actual calculation process, first, define P(e i ) is the probability of node i being powered, and R is defined i-j =R j-i is the probability of the line between nodes i and j being intact, and P(e i |e j ) is the probability that node i depends on node j for power supply, when node j is not powered by node i, P(e i |e j ) is calculated as follows:

[0119]

[0120] Among them, Ω j represents the set of adjacent nodes of node j, that is, the set of nodes directly connected to node j, Ω j / i represents the remaining nodes in the set of adjacent nodes of node j excluding node i. Node i is out of service if and only if all nodes around node i are out of service. Therefore, P(e i ) is calculated as:

[0121]

[0122] If i is a power node, then the following formula exists:

[0123] P(e i )=1 (7)

[0124] P(e i |e j )=0 (8)

[0125] P(e j |e i )=R j-i (9)

[0126] Afterwards, P(e i |e j ) is the variable to be solved, there are 2b variables in total (b is the number of branches), and the variable to be solved P(e i |e j ) are all denoted as x ij . Let f(x ij )=0 is x ij The equation that satisfies this is that other relevant variables x can be used jk Calculate x ij The value of . Depending on the node type, the equation can be expressed as:

[0127] If i is a power node, then the corresponding equation is:

[0128] f(x ij )=-x ij (10)

[0129] f(x ji )=-x ji +R j-i (11)

[0130] If i and j are both load nodes, the corresponding equation is:

[0131]

[0132] Since the Newton iteration method requires the calculation of the Jacobian matrix, the partial derivatives of each equation with respect to each variable are obtained to obtain the following Jacobian matrix elements:

[0133] For all nodes, there are:

[0134]

[0135]

[0136] Among them, m and n are two nodes in the network that are different from i and j.

[0137] If i is a power node, then:

[0138]

[0139]

[0140] If i and j are both load nodes, then:

[0141]

[0142] Where k is the neighboring node of node j, and k is different from i. According to the above calculation method, we can get x ij Then, we can solve P(e i |e j ), and then the above formula (6) can be used to solve P(e i ), and thus the probability of the node being powered is obtained.

[0143] Based on this, the probability of each node being powered on in the tree network diagram corresponding to each decomposition scenario can be obtained based on the above solution.

[0144] In the actual application process, for a node i to be analyzed, when calculating its power probability P(e i ), there is an electrical event e i It depends on the power supply status of adjacent nodes, but does not affect the power supply status of adjacent nodes. Therefore, in the process of calculating the power supply probability of the node, the influence of the adjacent nodes of node i on the power supply status of i can be represented by directed edges, which are local.

[0145] Figure 7 The principle of solving the probability of nodes being charged in a local directed area of a tree network diagram is shown. Figure 7 The dotted lines in the figure represent the connection between the node and other nodes. These connections are ignored in this calculation scenario. Only when analyzing the probability of node 1 being powered, Figure 7If we analyze the probability of node 2 being charged, the direction of edge 1-2 should be 1→2.

[0146] Since the marginal probability distribution P(e i ) is as above (6), and the condition for this formula to be valid is that there is an electrical event e at node j. j With j∈Ω i The conditions are independent.

[0147] according to Figure 7 The local directed structure in the network is called a "head-to-head" structure in the Bayesian network. When the state of node 1 is not given, the local conditional independence of nodes 0, 2, and 3 can be guaranteed. At this time, node 1 is called a blocking node. However, accurate probability solution requires global conditional independence, that is, in the current graph, it is guaranteed that e0, e2, and e3 are conditionally independent. For radial networks, it is necessary to ensure that the network is an acyclic network graph. The conditional independence of any two points can be determined by the D separation method of the Bayesian network. Since there is only one path between any two points in the tree network, for all adjacent nodes of node 1, according to Figure 7 As shown, the path between any two points must pass through the blocked node 1, so all adjacent nodes of node 1 are conditionally independent of each other.

[0148] D-Separation is a graphical method for determining conditional independence of variables. Compared to non-graphical methods, D-Separation is more intuitive and computationally simple. For a directed acyclic graph, D-Separation can quickly determine whether two nodes are conditionally independent.

[0149] Therefore, the method for calculating the probability of a node being powered provided by this embodiment can be used in radial networks containing multiple power sources, and the accuracy of the probability inference results is proved based on the D separation method.

[0150] Step 140: Based on the scenario existence probability and the energized probability of each node in the tree network diagram, the outage risk of each node in the original network diagram is evaluated to obtain an outage risk assessment result of the target distribution network.

[0151] In this embodiment, based on the scenario existence probability and the energized probability of each node in the tree network diagram, the process of evaluating the outage risk of each node in the original network diagram and obtaining the outage risk assessment result of the target distribution network may include:

[0152] First, based on the scenario existence probability and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, the power-on probability of each node in the original network diagram is calculated.

[0153] In this embodiment, the set of all evidence sets is denoted as Ω L , since each evidence set is independent, the probability of each node i being powered in the original network graph can be expressed as:

[0154]

[0155] Among them, P(e i |L k ) represents the decomposition scene G k The probability of node i being charged is P(e i ), if node i has been incorporated into node cluster V u Then P(e i |L k )=P(e u |L k ); P(L k ) represents the decomposition scene G k The probability of the scenario existing.

[0156] Then, based on the energized probability of each node in the original network diagram, the outage probability of each node in the original network diagram is calculated to obtain the outage risk assessment result of the target distribution network.

[0157] When the power probability of each node in the original network graph is obtained, the 1-P′(e i ) can be used to solve the outage probability of each node, thereby evaluating the outage risk of the distribution network.

[0158] The specific outage risk assessment method can be reasonably set according to actual application needs. For example, several risk levels can be set and the assessment conditions corresponding to different levels can be set. For example, primary outage risk, intermediate outage risk and high outage risk can be set. When the number of nodes in the original network diagram that meet the preset primary outage probability threshold exceeds the preset primary number threshold, it is determined that the distribution network has a primary outage risk.

[0159] Taking a complex distribution network as an example, the following describes the implementation process of the above-mentioned distribution network outage risk assessment method from the perspective of software program execution during the application process.

[0160] The first step is to delete the main power node from the original network graph and find the connected components.

[0161] The second step is to decompose each connected component. First, add the main power node and the corresponding edge to each connected component to determine whether the connected component is a tree. If it is a tree (that is, not a ring network graph), it enters the tree stack; otherwise, it enters the ring network stack.

[0162] The third step is to take out the top element of the cyclic network stack in a loop when the cyclic network stack is not empty, generate a spanning tree and branch of this element, enumerate the open and close combinations of the branch, and form a new network diagram (i.e., transition network diagram) according to the merging rules.

[0163] The fourth step is to continue to determine whether the new network graph is a tree. If it is a tree, it enters the tree stack. If it is a cyclic network graph, it enters the cyclic network stack. The loop ends when the cyclic network stack is empty.

[0164] In the fifth step, after the loop ends, each tree network diagram in the tree stack is output, the probability of each node in each tree network diagram being electrified is solved, and the probability of the scene existence corresponding to each decomposition scene is calculated.

[0165] In the sixth step, the power-on probability of each node corresponding to each decomposed scenario and the scenario existence probability are used to obtain the power-on probability of each node in the original network graph.

[0166] In the seventh step, the power-on probability of each node in the original network diagram is calculated, and the outage probability of each node is calculated to realize the outage risk assessment of the distribution network.

[0167] In order to verify the accuracy and reliability of the distribution network outage risk assessment method provided in this embodiment, a number of specific embodiments are used to compare and analyze the outage probability of each node in the original network diagram obtained by solving the distribution network outage risk assessment method provided by the present invention in various application scenarios with the solution results obtained by using the Monte Carlo method.

[0168] The Monte Carlo method calculates the probability of a network node outage by generating a binary random number (0-1) based on the reliability of each line, representing the two states of disconnection and connection. The connectivity of the power supply to all nodes is then checked. If the node cannot connect to any power source, it is out of service and is recorded as 0. Otherwise, it indicates that there is power and is recorded as 1.

[0169] Example 1

[0170] The test code in this embodiment is written in Python 3.8, the test platform is a laptop with an Intel i7 CPU, and the Monte Carlo times for all systems is 3200000. The application scenario of this embodiment is a single power distribution system with 7 nodes.

[0171] Figure 8 The original network diagram of a single-power distribution system containing 7 nodes, the tree network diagram under each decomposition scenario, and the scenario existence probability corresponding to each decomposition scenario are shown. Among them, node 0 is the power node, which contains ten decomposition scenarios: a, b, c, d, e, f, g, k, l, and i.

[0172] The error vector 2-norm between the solution vector obtained after decomposition and the Monte Carlo result is 0.00027. The calculation results of the outage probability of each node are shown in Table 1 below:

[0173] Table 1 Statistics of outage probability of each node

[0174] method Node 0 Node 1 Node 2 Node 3 Node 4 Node 5 Node 6 Monte Carlo 1.00000 0.96446 0.96437 0.94604 0.95262 0.94446 0.95970 Tree decomposition method 1.00000 0.96436 0.96436 0.94588 0.95258 0.94434 0.95973

[0175] It can be seen from Table 1 that the method for assessing the outage risk of a distribution network provided in this embodiment can accurately obtain the outage probability of each node when applied to a distribution system with a single power source.

[0176] Example 2

[0177] The test code in this embodiment is written in Python 3.8, and the test platform is a notebook with Intel i7 CPU. The Monte Carlo times of all systems are 3200000 times. The application environment of this embodiment is to add a reliable distributed power supply under the application environment of the embodiment. It can be assumed that node 6 in Example 1 is a distributed power supply. If it is assumed that node 6 is a distributed power supply, the tree network diagrams of each scenario are the same as Figure 8 It is also possible to add a power node 7 based on Example 1. The original network diagram of the multi-power distribution system containing 8 nodes and the tree network diagram under each decomposition scenario and the scenario existence probability corresponding to each decomposition scenario are as follows: Figure 9 As shown in the figure, there are ten decomposition scenes including m, n, o, p, q, r, s, t, u, and v.

[0178] The results obtained by the Monte Carlo method, the results obtained by using node 6 as a distributed power source, and the results obtained by adding power node 7 are shown in Table 2 below. The error 2-norm is 0.000265.

[0179] Table 2 Statistics of outage probability of each node

[0180]

[0181] It can be seen from Table 2 above that the method for assessing the outage risk of a distribution network provided in this embodiment can also accurately obtain the outage probability of each node when applied to a distribution system with multiple power sources.

[0182] Example 3

[0183] This example tests the pruning process and uses an IEEE 33-node power distribution system for comparative analysis. The IEEE 33-node power distribution system contains five transfer lines and has a relatively complex loop. Using exact decomposition, 32,509 trees were formed, and the decomposition and solution took a total of 252.41 seconds. Using approximate decomposition with a threshold of 0.001, 3,767 trees were formed, and the decomposition and solution took a total of 26.81 seconds. Using approximate decomposition with a threshold of 0.0001, 13,658 trees were formed, and the decomposition and solution took a total of 108.09 seconds. The statistical results are shown in Table 3 below:

[0184] Table 3. Exact decomposition and corresponding results under different thresholds

[0185] method Number of decomposition trees Decomposition and solution time (s) Error 2 norm Precise decomposition 32509 252.41 - The threshold is 0.001 3767 26.81 0.3159 The threshold is 0.0001 13658 108.09 0.0729

[0186] It can be seen that after setting the pruning link, the speed of tree decomposition is effectively improved.

[0187] Example 4

[0188] This example tests the block decomposition process using a real-world power grid. This grid has 483 nodes and 495 lines. After the original network graph is divided into blocks, four ring networks and nine radial networks are formed. The ring networks are decomposed into 44, 58, 16, and 21 trees, respectively.

[0189] Without block decomposition, the overall algorithm failed to complete the decomposition after 10 minutes. However, with block decomposition, the decomposition and solution were completed within 21 seconds. This fully demonstrates the importance of block decomposition for improving tree decomposition efficiency.

[0190] The following describes the distribution network outage risk assessment device provided by the present invention. The distribution network outage risk assessment device described below and the distribution network outage risk assessment method described above can refer to each other.

[0191] Figure 10 The present invention provides an embodiment of a device for assessing the risk of a power distribution network outage, the device comprising:

[0192] An acquisition module 101 is used to acquire an original network diagram of a target distribution network;

[0193] The first processing module 102 is used to determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is decomposed into trees based on different decomposition scenarios to obtain tree network diagrams corresponding to the decomposition scenarios.

[0194] The second processing module 103 is used to obtain the scene existence probability corresponding to each decomposition scene, and to obtain the power-on probability of each node in the tree network diagram corresponding to each decomposition scene;

[0195] The third processing module 104 is used to evaluate the outage risk of each node in the original network diagram based on the scenario existence probability and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, and obtain the outage risk assessment result of the target distribution network.

[0196] In an exemplary embodiment, the first processing module 102 is specifically configured to:

[0197] Determine whether the original network graph is a cyclic network graph. If the original network graph is a cyclic network graph, construct the spanning tree and branch set corresponding to the original network graph;

[0198] Enumerate the on-off combinations of each branch in the branch set, and merge some nodes in the spanning tree according to the preset merging conditions to generate a transition network diagram;

[0199] Determine whether the transition network graph is a cyclic network graph. If the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph;

[0200] The on-off combinations of each branch in the branch set corresponding to the transition network diagram are enumerated, and some nodes in the spanning tree corresponding to the transition network diagram are merged according to the preset merging conditions until the decomposition termination conditions are met, thereby obtaining the tree network diagram corresponding to each decomposition scenario.

[0201] In another exemplary embodiment, the first processing module 102 is specifically configured to:

[0202] Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, divide the original network diagram into blocks and divide it into multiple local network diagrams.

[0203] Performing structural completion processing on each local network graph respectively to obtain a completed local network graph;

[0204] Determine whether the completed local network graph is a cyclic network graph. If the completed local network graph is a cyclic network graph, construct a spanning tree and a connected branch set corresponding to the completed local network graph.

[0205] Enumerate the on-off combinations of each branch in the branch set, and merge some nodes in the spanning tree according to the preset merging conditions to generate a transition network diagram;

[0206] Determine whether the transition network graph is a cyclic network graph. If the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph;

[0207] The on-off combinations of each branch in the branch set corresponding to the transition network diagram are enumerated, and some nodes in the spanning tree corresponding to the transition network diagram are merged according to the preset merging conditions until the decomposition termination conditions are met, thereby obtaining the tree network diagram corresponding to each decomposition scenario.

[0208] In an exemplary embodiment, the first processing module 102 implements the function of dividing the original network graph into multiple local network graphs by the following methods, including:

[0209] The main power supply node in the original network graph is removed and divided into multiple local network graphs.

[0210] In an exemplary embodiment, the first processing module 102 implements the function of performing structure completion processing on each local network graph to obtain a completed local network graph in the following manner, including:

[0211] The main power supply node and the lines related to the main power supply node are added to each local network diagram respectively to obtain a completed local network diagram.

[0212] In an exemplary embodiment, the decomposition termination condition may be that the newly generated transition network graph is a non-cyclic network graph or the scenario existence probability of the current decomposition scenario is less than a preset probability threshold.

[0213] In an exemplary embodiment, the second processing module 103 is specifically configured to:

[0214] Obtain the disconnected line set, closed line set, and semi-disconnected line set in the tree network diagram under each decomposition scenario respectively;

[0215] Based on the disconnection probability of each line in the disconnected line set, the closing probability of each line in the closed line set, and the closing probability of each line in the semi-disconnected line set, the scenario existence probability corresponding to each decomposed scenario is obtained.

[0216] In an exemplary embodiment, the third processing module 104 is specifically configured to:

[0217] Based on the scenario existence probability and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, the power-on probability of each node in the original network diagram is calculated;

[0218] Based on the energized probability of each node in the original network diagram, the outage probability of each node in the original network diagram is calculated to obtain the outage risk assessment result of the target distribution network.

[0219] Figure 11 An example of a physical structure diagram of an electronic device is shown below. Figure 11As shown, the electronic device may include: a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other via the communication bus 114. The processor 111 may call the logic instructions in the memory 113 to execute a method for assessing the outage risk of a distribution network, the method comprising: obtaining an original network diagram of a target distribution network; determining whether the original network diagram is a ring network diagram; if the original network diagram is a ring network diagram, performing tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario; obtaining a scenario existence probability corresponding to each decomposition scenario, and calculating the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario; and assessing the outage risk of each node in the original network diagram based on the scenario existence probability and the power-on probability of each node in the tree network diagram to obtain an outage risk assessment result of the target distribution network.

[0220] In addition, the logic instructions in the above-mentioned memory 113 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0221] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the distribution network outage risk assessment method provided by the above methods, the method including: obtaining the original network diagram of the target distribution network; judging whether the original network diagram is a ring network diagram; if the original network diagram is a ring network diagram, performing tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario; obtaining the scenario existence probability corresponding to each decomposition scenario, and calculating the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario; based on the scenario existence probability and the power-on probability of each node in the tree network diagram, evaluating the outage risk of each node in the original network diagram to obtain the outage risk assessment result of the target distribution network.

[0222] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a distribution network outage risk assessment method provided by the above-mentioned methods, the method comprising: obtaining an original network diagram of the target distribution network; determining whether the original network diagram is a cyclic network diagram; if the original network diagram is a cyclic network diagram, performing tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario; obtaining a scenario existence probability corresponding to each decomposition scenario, and calculating the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario; evaluating the outage risk of each node in the original network diagram based on the scenario existence probability and the power-on probability of each node in the tree network diagram to obtain an outage risk assessment result of the target distribution network.

[0223] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0224] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0225] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for assessing the risk of a distribution network outage, characterized in that: include: Obtain the original network diagram of the target distribution network; Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, perform tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario. Obtain the scenario existence probability corresponding to each decomposition scenario, and calculate the power-on probability of each node in the tree network diagram corresponding to each decomposition scenario; Based on the scenario existence probability and the power-on probability of each node in the tree network diagram, the outage risk of each node in the original network diagram is evaluated to obtain an outage risk assessment result of the target distribution network.

2. A method for assessing the risk of a power distribution network outage according to claim 1, characterized in that: Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, perform tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario, including: Determine whether the original network graph is a cyclic network graph, and if the original network graph is a cyclic network graph, construct a spanning tree and a branch set corresponding to the original network graph; Enumerating the on-off combinations of each branch in the branch set, and merging some nodes in the spanning tree according to a preset merging condition to generate a transition network diagram; Determine whether the transition network graph is a cyclic network graph, and if the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph; Enumerate the on-off combinations of each branch in the branch set corresponding to the transition network diagram, and merge some nodes in the spanning tree corresponding to the transition network diagram according to the preset merging conditions until the decomposition termination conditions are met, so as to obtain the tree network diagram corresponding to each decomposition scenario.

3. The method for assessing the risk of a power distribution network outage according to claim 1, wherein: Determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, perform tree decomposition on the original network diagram based on different decomposition scenarios to obtain a tree network diagram corresponding to each decomposition scenario, including: Determine whether the original network diagram is a cyclic network diagram, and if so, divide the original network diagram into multiple local network diagrams; Performing structure completion processing on each of the local network graphs to obtain a completed local network graph; Determine whether the completed local network graph is a cyclic network graph, and if the completed local network graph is a cyclic network graph, construct a spanning tree and a branch set corresponding to the completed local network graph; Enumerating the on-off combinations of each branch in the branch set, and merging some nodes in the spanning tree according to a preset merging condition to generate a transition network diagram; Determine whether the transition network graph is a cyclic network graph, and if the transition network graph is a cyclic network graph, reconstruct the spanning tree and branch set corresponding to the transition network graph; Enumerate the on-off combinations of each branch in the branch set corresponding to the transition network diagram, and merge some nodes in the spanning tree corresponding to the transition network diagram according to the preset merging conditions until the decomposition termination conditions are met, so as to obtain the tree network diagram corresponding to each decomposition scenario.

4. A method for assessing the risk of a power distribution network outage according to claim 3, characterized in that: The original network diagram is divided into multiple local network diagrams, including: The main power supply node in the original network diagram is removed, and multiple local network diagrams are obtained by dividing the original network diagram.

5. The method for assessing the risk of a power distribution network outage according to claim 3, wherein: Performing structure completion processing on each of the local network graphs to obtain a completed local network graph includes: A main power supply node and lines related to the main power supply node are added to each of the local network diagrams to obtain a completed local network diagram.

6. A method for assessing the risk of a power distribution network outage according to claim 2 or 3, characterized in that: The decomposition termination condition is that the newly generated transition network diagram is a non-cyclic network diagram or the scene existence probability of the current decomposition scene is less than a preset probability threshold.

7. The method for assessing the risk of a power distribution network outage according to claim 1, wherein: Obtain the scenario existence probability corresponding to each decomposition scenario, including: Obtain the disconnected line set, closed line set, and semi-disconnected line set in the tree network diagram under each decomposition scenario respectively; Based on the disconnection probability of each line in the disconnected line set, the closing probability of each line in the closed line set, and the closing probability of each line in the semi-disconnected line set, a scenario existence probability corresponding to each decomposed scenario is obtained.

8. The method for assessing the risk of a power distribution network outage according to claim 1, wherein: Based on the scenario existence probability and the energized probability of each node in the tree network diagram, the outage risk of each node in the original network diagram is evaluated to obtain an outage risk assessment result of the target distribution network, including: Based on the scenario existence probability and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, the power-on probability of each node in the original network diagram is calculated; Based on the power-on probability of each node in the original network diagram, the outage probability of each node in the original network diagram is calculated to obtain an outage risk assessment result of the target distribution network.

9. A device for assessing the risk of a power distribution network outage, characterized in that: include: An acquisition module is used to obtain the original network diagram of the target distribution network; A first processing module is configured to determine whether the original network diagram is a cyclic network diagram. If the original network diagram is a cyclic network diagram, the original network diagram is decomposed into trees based on different decomposition scenarios to obtain tree network diagrams corresponding to the decomposition scenarios. The second processing module is used to obtain the scene existence probability corresponding to each decomposition scene, and to obtain the power-on probability of each node in the tree network diagram corresponding to each decomposition scene; The third processing module is used to evaluate the outage risk of each node in the original network diagram based on the existence probability of the scenario and the power-on probability of each node in the tree network diagram corresponding to the decomposed scenario, and obtain the outage risk assessment result of the target distribution network.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for evaluating the risk of power distribution network outage as claimed in any one of claims 1 to 8 are implemented.

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