Power grid fragile link identification method and device based on network flow betweenness and medium

Abstract

The invention discloses a power grid fragile link identification method and device based on network flow betweenness and a medium, and relates to the technical field of power system safety. According to the technical key points, an actual power transmission path is obtained through a power flow tracking algorithm and a breadth-first search algorithm; calculating a power transmission distribution factor of each power transmission path on the generator load node pair and a power transmission maximum capacity of each power transmission path on the generator load node pair; and calculating the network flow betweenness of each power transmission path according to the power transmission distribution factor and the power transmission maximum capacity, and carrying out vulnerability sorting on the lines and the nodes according to the network flow betweenness. According to the identification method, more comprehensive system state and topological information are considered, and the identification result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of power system safety, and in particular to a method, device and medium for identifying vulnerable links of a power grid based on network flow betweenness. Background Art

[0002] As the most important component of the energy internet, the power grid plays a vital role in its development. my country has the world's largest power grid, with a power supply population of 1.39 billion. The growing demand for electricity has made the interconnection of power grids more obvious, the network form of the system has become more complex, and the corresponding system operation characteristics and parameters have also undergone major changes.

[0003] Large-scale grid interconnection not only brings strong challenges to the stable operation of the power system, but also makes its dynamic characteristics more complicated due to the highly nonlinear dynamic characteristics of the power system. In addition, the extensive use of new materials and new equipment, such as distributed power generation equipment, ultra-high voltage direct current transmission technology, power electronics technology and intelligent information technology, has put forward higher requirements for the safe, stable and reliable operation of the power system.

[0004] Based on the previous experience of power system operation, it is not complete to evaluate the safety status of the power grid simply from the stability and reliability of the power grid operation. The existing power system vulnerable link identification method mainly considers the power flow carrying capacity of the transmission line, and the system status and topology information considered are not comprehensive enough, resulting in low accuracy in identifying the vulnerability of the power system and increasing the risk of power outages in the power system. Therefore, it is of great significance to comprehensively and accurately analyze the weak links and potential dangers of the power system during operation based on the existing topological structure and operating status of the power grid to ensure the safe and stable operation of the power system. Summary of the invention

[0005] The present invention provides a method, device and medium for identifying vulnerable links in a power grid based on network flow betweenness, so as to solve the problem that the system status and topology information considered in the existing method for identifying vulnerable links in a power grid are not comprehensive enough and the identification accuracy is not high.

[0006] The present invention is achieved through the following technical solutions:

[0007] A first aspect of the present invention provides a method for identifying vulnerable links in a power grid based on network flow betweenness, comprising:

[0008] Obtain the power distribution relationship of the power system through the power flow tracking algorithm;

[0009] Based on the power allocation relationship, a breadth-first search algorithm is used to obtain an actual power transmission path;

[0010] Calculate the power transmission distribution factor of each power transmission path on the generator load node pair and the maximum power transmission capacity of each power transmission path on the generator load node pair;

[0011] Calculating the network flow betweenness of each power transmission path according to the power transmission distribution factor and the maximum power transmission capacity, and calculating the network flow betweenness of each node according to the network flow betweenness of the power transmission path;

[0012] The power transmission paths are ranked by vulnerability according to the network flow betweenness of each power transmission path, and the nodes are ranked by vulnerability according to the network flow betweenness of each node. The ranking results of the transmission lines and the ranking results of the nodes are combined to obtain the vulnerable links of the power grid.

[0013] The network flow betweenness (NF) can fully reflect the current operating status and topological structure of the power grid. The larger the network flow betweenness of the line, the higher the overall vulnerability in the network. On this basis, the present invention calculates the network flow betweenness of the actual power transmission path of the power grid, and proposes to identify the vulnerability of the line and the node based on the network flow betweenness of the transmission line and the network flow betweenness of the node. The system status and topological information considered are not comprehensive enough, and the identification result is more accurate.

[0014] In addition, in the network flow problem of the power system, the transmission capacity of the same line at different generator load node pairs is different. If the maximum active transmission capacity allowed by the line is directly used, it cannot fully reflect the load status of the line. The power transmission distribution factor just reflects the power flow carrying capacity of the transmission line and can be used to determine the maximum transmission capacity, making the calculation of the network flow betweenness more scientific and accurate.

[0015] Furthermore, the obtaining of the power distribution relationship of the power system by the power flow tracking algorithm includes:

[0016] S11, performing power flow calculation on the power system, and establishing a directed graph of the power system based on the power grid topology and the power flow calculation results;

[0017] S12, calculate the downstream distribution matrix A and the node injected active power diagonal matrix P TT and the generator output diagonal matrix P GG ;

[0018] S13, calculate the distribution coefficient matrix K:

[0019] K=P GG (P TT ) -1 A -1 ;

[0020] Among them, (P TT )-1 Indicates P TT The inverse matrix, A -1 represents the inverse matrix of A;

[0021] S14, calculating the active power allocated to the generator node on each load node according to the allocation coefficient matrix K, and obtaining the power allocation relationship between the generator node and the load node; and,

[0022] The active power allocated to the generator nodes on each transmission line is calculated according to the allocation coefficient matrix K, and the power allocation relationship between the generator nodes and the transmission lines is obtained.

[0023] Furthermore, based on the power allocation relationship, an optimized breadth-first search algorithm is used to obtain an actual power transmission path, including:

[0024] S21, determine all generator nodes and load nodes;

[0025] S22, obtaining a weighted adjacency matrix of each generator node according to the power allocation relationship between the generator node and the transmission line;

[0026] S23, using the weighted adjacency matrix to search for an adjacent node whose active power of the transmission circuit between the generator node s is not zero;

[0027] S24, based on the power distribution relationship between the generator node and the load, starting from the generator node s and the load node t as the end point, searching from the adjacent nodes of the generator node s from top to bottom layer by layer, to find all the power transmission paths between the generator node s and the load node t;

[0028] S25, performing the search operation of S23-S24 on each generator node to obtain the power transmission path between all generator load node pairs st in the power system.

[0029] Furthermore, the weighted adjacency matrix of the generator node is expressed as:

[0030]

[0031] Among them, Adj ij represents the element in the i-th row and j-th column of the weighted adjacency matrix, P ij Represents the active power on the transmission line ij. When there is power transmission on the transmission line ij, P ij >0, when there is no power transmission on the transmission line ij, P ij =0.

[0032] Furthermore, the power transmission distribution factor is calculated as:

[0033]

[0034] in, represents the power transfer distribution factor of the transmission line ij in the generator load node pair st, P ij represents the active power on the transmission line ij, x ij is the reactance value of the transmission line ij, θ i represents the voltage phase angle at node i, θ j represents the voltage phase angle at node j, x is is the element in the ith row and sth column of the power system reactance matrix, x jt 、x js 、x it They correspond respectively to the j-th row and t-th column element, the j-th row and s-th column element, and the ith row and t-th column element in the reactance matrix.

[0035] Furthermore, the maximum power transmission capacity is calculated as:

[0036]

[0037] Among them, P st represents the maximum power transmission capacity of the transmission line ij between the generator node s and the load node t, L represents the set of all transmission lines in the power transmission path of the generator load node pair st, It is an indicator that defines the power transfer capability of a transmission line. is the maximum active transmission power of the transmission line between the generator load node pair st, is the power transfer distribution factor of transmission line ij.

[0038] Furthermore, the network flow betweenness of the transmission line is calculated as:

[0039]

[0040] Among them, B ij is the network flow betweenness of the transmission line ij, G represents the generator node set, F represents the load node set, P st represents the maximum power transfer capacity of the transmission line ij between the generator node s and the load node t, Represents the power transfer distribution factor of transmission line ij.

[0041] Furthermore, the network flow betweenness of the node is calculated as:

[0042]

[0043] Among them, B i is the network flow betweenness of node i, Ω is the set of adjacent nodes j of node i, D i is the degree of node i, Bij is the network flow betweenness of transmission line ij.

[0044] A second aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method for identifying vulnerable links in a power grid based on network flow betweenness as described in any one of the first aspect of the present invention.

[0045] According to a third aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for identifying vulnerable links in a power grid based on network flow betweenness as described in any one of the first aspect of the present invention is implemented.

[0046] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0047] The network flow betweenness of the actual power transmission path of the power grid is calculated, and the vulnerability of the line and the node is identified based on the network flow betweenness of the transmission line and the network flow betweenness of the node. The system status and topology information considered are not comprehensive enough, and the identification result is more accurate.

[0048] The power transmission distribution factor is used to determine the maximum transmission capacity, and the network flow betweenness is calculated based on the power transmission distribution factor and the maximum transmission capacity. The power transmission distribution factor can reflect the power flow carrying capacity of the transmission line, making the calculation of the network flow betweenness more scientific and accurate.

[0049] When calculating the power distribution factor, the actual power transmission path is obtained based on power flow tracking and an improved breadth-first search algorithm. Compared with previous studies that calculated all generator load node pairs, this reduces the redundancy of the power transmission path. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0051] Figure 1 It is a flow chart of a method for identifying vulnerable links in a power grid based on network flow betweenness according to an embodiment of the present invention;

[0052] Figure 2 It is the IEEE-39 node power system topology diagram;

[0053] Figure 3It is the system load loss rate calculated after a deliberate attack on the IEEE-39 node power system. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0055] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to or inherent to other steps or units of the device.

[0056] The terms used in the various embodiments of the application are only used to describe the purpose of specific embodiments and are not intended to limit the various embodiments of the application. As used herein, the singular form is intended to also include the plural form, unless the context clearly indicates otherwise. Unless otherwise limited, all terms used here (including technical terms and scientific terms) have the same meaning as the meanings commonly understood by ordinary technicians in the field of the various embodiments of the application. The terms (such as the terms defined in the dictionary generally used) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning, unless clearly defined in the various embodiments of the application.

[0057] The embodiments of the present invention provide a method, device and medium for identifying vulnerable links in a power grid based on network flow betweenness, which are applicable to new energy grid-connected systems such as wind grid-connected systems and are conducive to improving the accuracy of identification.

[0058] like Figure 1 The flowchart of the method for identifying vulnerable links in a power grid based on network flow betweenness includes the following steps.

[0059] S1, obtain the power distribution relationship of the power system through the power flow tracking algorithm.

[0060] S2, according to the power allocation relationship, adopt the breadth-first search algorithm to obtain the actual power transmission path.

[0061] S3, according to the actual power transmission path, calculating the power transmission distribution factor of each power transmission path on the generator load node pair and the maximum power transmission capacity of each power transmission path on the generator load node pair.

[0062] S4, calculating the network flow betweenness of each power transmission path and the network flow betweenness of each node according to the power transmission distribution factor and the maximum power transmission capacity.

[0063] S5, identify the vulnerable links of the power system through the network flow betweenness of transmission paths or nodes.

[0064] The power flow tracking algorithm analyzes the source-flow relationship of the power grid, and can solve which power sources or loads cause the power flow on any branch or component, and how much each contributes. The present invention first analyzes the power distribution relationship of the power network based on the power flow tracking algorithm, and obtains the active power distributed by each generator on each load and the active power distributed by each generator on each transmission line. The solution process is as follows.

[0065] S11, performing power flow calculation on the power system, and establishing a directed graph of the power system based on the power grid topology and power flow calculation results.

[0066] S12, calculate the downstream distribution matrix A, the node injected active power diagonal matrix P TT , generator output diagonal matrix P GG .

[0067] S13, calculate the distribution coefficient matrix K:

[0068] K=P GG (P TT ) -1 A -1 (1)

[0069] Among them, (P TT ) -1 Indicates P TT The inverse matrix, A -1 represents the inverse matrix of A.

[0070] S14, calculating the active power allocated to the generator node on each load node according to the allocation coefficient matrix K, thereby obtaining the power allocation relationship between the generator node and the load node.

[0071] S15, calculating the active power allocated to the generator nodes on each transmission line according to the allocation coefficient matrix K, thereby obtaining the power allocation relationship between the generator nodes and the transmission lines.

[0072] And according to the calculation results of S14 and S15, the generator-load power distribution table and the generator-transmission line power distribution table can be prepared.

[0073] In step S2, when searching for power transmission paths in the power network, since the power transmission between the generator and the load node does not pass through all the lines, some of the transmission paths do not have power flowing through, which is seriously inconsistent with the operation of the actual power system. If the breadth-first search algorithm is directly used to search for the path, it will cause redundancy of the power transmission path. Therefore, the present invention proposes an improved breadth-first search algorithm to search for power transmission paths and obtain the actual power transmission path.

[0074] According to the power distribution relationship between the generator and the transmission line, if some lines do not play the role of power transmission, all these transmission lines are considered disconnected to form adjacency matrices under different topological structures. According to the size and direction of the power flow calculation, the line power value is used as the element (weight) of the adjacency matrix to establish the weighted adjacency matrix Adj.

[0075]

[0076] Among them, Adj ij represents the element in the i-th row and j-th column of the weighted adjacency matrix Adj, P ij Represents the active power on the transmission line ij. When there is power transmission on the transmission line ij, P ij is a value greater than 0. When there is no power transmission on the transmission line ij, P ij =0.

[0077] Furthermore, after adjustment, the specific steps of the improved breadth-first search algorithm are as follows.

[0078] S21, determine all the generator nodes s and load nodes t in the current network to form a generator node set G and a load node set F.

[0079] S22, according to the power distribution relationship between the generator node and the transmission line, a weighted adjacency matrix (Formula (2)) of each generator node is obtained.

[0080] S23, using the weighted adjacency matrix to search for the active power P of the transmission circuit between the generator node s ij Non-zero adjacent nodes.

[0081] S24, according to the power distribution relationship between the generator node and the load, with the generator node s as the starting point and the load node t as the end point, the adjacent nodes are searched layer by layer from top to bottom starting from the adjacent nodes of the generator node s until all power transmission paths between the generator node s and the load node t are found.

[0082] S25, repeating the search operations of S23-S24 for each generator node s in the generator node set G, that is, obtaining all power transmission paths between all generator load node pairs in the entire power system.

[0083] When searching for nodes, record the nodes that each power transmission path passes through in sequence and mark them. All power transmission paths from all generator nodes to load nodes form a set L. There are multiple transmission lines between each generator-load node pair st, among which there can be multiple power transmission paths.

[0084] The present invention proposes a network flow betweenness considering the actual power transmission path of the power grid. Firstly, the power transmission distribution factor of each power transmission path on the generator load node pair and the maximum power transmission capacity of each power transmission path on the generator load node pair are calculated.

[0085] Power Transfer Distribution Factors (PTDF) refers to the change in line power caused by injecting power at the generator load node pair, which reflects the power flow carrying capacity of the transmission line and can be used to determine the maximum transmission capacity. When calculating the power distribution factor, previous studies often calculated all the generator load node pairs, but in actual power grid transmission, there is no power flow between some generator load node pairs, so this embodiment uses the actual power transmission path results obtained based on the above-mentioned power flow tracking and improved breadth-first search algorithm for calculation, which is more scientific and accurate.

[0086] PTDF measures the sensitivity of power transmission of each line at the generator load node. In the DC power flow model, the power transfer distribution factor (PTDF) of the transmission line ij is expressed as:

[0087]

[0088] in, represents the power transfer distribution factor of the transmission line ij in the generator load node pair st, P ij represents the active power on the transmission line ij, x ij is the reactance value of the transmission line ij, P t represents the active power absorbed by the load node t, θ i represents the voltage phase angle at node i, θ j represents the voltage phase angle at node j, x is is the element in the ith row and sth column of the power system reactance matrix, x jt 、x js 、x itare respectively the element in the j-th row and t-th column, the element in the j-th row and s-th column, and the element in the ith row and t-th column in the reactance matrix.

[0089] Let the maximum active power transfer between the generator load node pair st be Combined with the power transmission distribution factor, the power transmission capacity index of the transmission line ij is defined as:

[0090]

[0091] For a single generator load node pair, there is the following formula:

[0092]

[0093] Where P st represents the maximum power transmission capacity of the transmission line ij between the generator node s and the load node t, and L represents the set of all transmission lines in the power transmission path of the generator load node pair st.

[0094] From a global perspective, and taking into account the maximum transmission power capacity of the generator load node pair and the power transmission distribution factor, the network flow betweenness B of the transmission line is obtained: ij It is expressed as follows:

[0095]

[0096] Among them, B ij is the network flow betweenness of the transmission line ij, G represents the generator node set, F represents the load node set, P st represents the maximum power transfer capacity of the transmission line ij between the generator node s and the load node t, Represents the power transfer distribution factor of transmission line ij.

[0097] The network flow number (NF) can fully reflect the current operating status and topological structure of the power grid. The larger the network flow number, the stronger its ability to transmit and carry power, and the better the power flow transmission position in the topological structure, the higher the overall vulnerability in the network.

[0098] Analogous to the network flow betweenness of a line, the network flow betweenness of node i is proposed i It is expressed as follows:

[0099]

[0100] In the formula, B i is the network flow betweenness of node i, Ω is the set of adjacent nodes j of node i, D i is the degree of node i, B ij is the network flow betweenness of transmission line ij.

[0101] In step S5, identifying the vulnerable links of the power system through the network flow betweenness of the transmission path or the node specifically includes: sorting the vulnerability of each power transmission path according to the network flow betweenness of the power transmission path, sorting the vulnerability of each node according to the network flow betweenness of the node to obtain vulnerable lines and vulnerable nodes, and finally finding the more vulnerable links in the power grid by combining the sorting results of the lines and the sorting results of the nodes.

[0102] The vulnerability is sorted according to the network flow betweenness, that is, the network flow betweenness is sorted from large to small. A large network flow betweenness means a large vulnerability. Finally, the weak links of the power grid are obtained based on the sorting results of the lines and the sorting results of the nodes.

[0103] Furthermore, the wind grid power system is based on the ICEEMDAN-DOA-GRU model to predict wind power. The model uses ICEEMDAN to perform modal decomposition on wind power, reduce the randomness and volatility of wind power signals, and optimizes the hyperparameters of GRU using the wild dog algorithm. The decomposed wind power data is then input into the optimized GRU model, and the output results are superimposed to output the final prediction results. The wind power prediction results will be used to explore the impact of wind turbines on the vulnerability of the power system after grid connection.

[0104] The present invention adopts Figure 2 The IEEE-39 node power system topology shown in the figure is used as an example for implementation demonstration. Among them, the first six lines with the highest vulnerability are shown in Table 1.

[0105] Table 1 IEEE-39 bus system line identification results

[0106]

[0107]

[0108] It can be seen from Table 1 and the IEEE-39 node power system topology diagram that 5 of the 6 lines with the highest network flow betweenness, namely L14, L20, L33, L37, and L46, are connected to generators G31, G32, G33, G35, and G38, and are the only external power transmission channels of the generators. If they fail, the system will experience large-scale power transfer. Once these lines fail, the system will experience large-scale power shortages, which verifies that the present invention can effectively identify vulnerable lines.

[0109] In order to further verify the accuracy of the power system vulnerability identification method proposed in the present invention, intuitively reflect the impact of important lines on the stability and transmission performance of the power network, and analyze the system load loss situation under deliberate attacks.

[0110] The formula for the load loss rate is as follows:

[0111]

[0112] Where P loss_rate Indicates the load loss rate, P loss It is the amount of load lost in the system after a deliberate attack on the line, and P represents the total load of the power system.

[0113] Firstly, three comparative identification methods were selected to compare with the vulnerable identification method proposed in this invention, namely, the cascade index method (CEI), the maximum flow theory method (MF), and the PageRank algorithm (PR). Experimental operation: A DC cascading failure model was established for the top 6 vulnerable lines in the IEEE-39 node power system and the maximum level of cascading failures was set. The first 6 lines were attacked continuously and intentionally. When a line was attacked, it was determined whether other lines were overloaded. If overloaded, the line was removed until no line was overloaded or the maximum level of cascading failures was reached. Finally, the lost load and the load loss rate of the power system were calculated. When the line was removed, the higher the system load loss rate was, the more important the line was.

[0114] Conduct deliberate attacks on the IEEE-39 node power system and count the system load loss rate, such as Figure 3 As shown. Figure 3 It can be seen that after the deliberate attack on the 6 most vulnerable lines in the power system, the residual load rates of the method (NF) proposed by the present invention, the cascade index method (CEI), the maximum flow theory method (MF), and the PageRank algorithm (PR) are 61.77%, 75.65%, 92.86%, and 65.95%, respectively. The load loss of the method of the present invention is higher than that of the other algorithms. The deliberate attack on the line of the algorithm of the present invention causes the greatest power outage loss. The CEI and MF algorithms only have power outage losses when the number of lines is increased to 4, while the present invention will experience load loss quickly when the number of lines is increased to the second line, and the higher the judgment accuracy. The accuracy of the vulnerable line identified by MF is not high, as it only considers the line capacity, and the factors examined are not comprehensive, and the PR residual load is also low. In summary, from the perspective of load loss index, the network flow betweenness algorithm of the present invention identifies vulnerable lines with higher accuracy and is superior to the other vulnerable line identification algorithms.

[0115] According to the idea of ​​the present invention, vulnerable node identification based on network flow is performed. Among them, the first six nodes with the highest degree of vulnerability are selected and compared with a power system key node identification method based on integrated power flow tracking and link analysis proposed by Wang Jiayu, and Table 2 is generated as shown in the following table:

[0116] Table 2 Results of vulnerable node identification in IEEE-39 node system

[0117]

[0118]

[0119] From Table 2 and the IEEE 39-node power system topology diagram, it can be seen that among the six nodes with the highest network flow betweenness, five nodes 31, 32, 33, 35, and 38 are generator nodes. If they fail, the system will undergo large-scale power flow transfer. These nodes have a great impact on the connectivity of the system. At the same time, by comparing with the literature, five of the first six nodes are the same, which also proves the recognition accuracy of the method of the present invention.

[0120] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory; the number of the processors can be one or more.

[0121] The memory is a computer-readable storage medium that can be used to store software programs, computer executable programs, and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory to implement the power grid vulnerable link identification method based on network flow betweenness according to any of the above embodiments of the present invention.

[0122] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0123] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for identifying vulnerable links in a power grid based on network flow betweenness according to any embodiment of the present invention is implemented. The storage medium may be a ROM / RAM, a magnetic disk, an optical disk, etc.

[0124] An embodiment of the present invention provides a computer program product. When the computer program product is run on a computer, the computer executes the method for identifying vulnerable links of a power grid based on network flow betweenness according to any one of the above embodiments of the present invention.

[0125] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying vulnerable links in power grids based on network flow betweenness, characterized in that: include: Obtain the power distribution relationship of the power system through the power flow tracking algorithm; Based on the power allocation relationship, an optimized breadth-first search algorithm is used to obtain an actual power transmission path; Calculate the power transmission distribution factor of each power transmission path on the generator load node pair and the maximum power transmission capacity of each power transmission path on the generator load node pair; Calculating the network flow betweenness of each power transmission path according to the power transmission distribution factor and the maximum power transmission capacity, and calculating the network flow betweenness of each node according to the network flow betweenness of the power transmission path; The power transmission paths are ranked by vulnerability according to their network flow betweenness, and each node is ranked by vulnerability according to its network flow betweenness. The ranking results of the lines and the ranking results of the nodes are combined to obtain the vulnerable links of the power grid.

2. The method for identifying vulnerable links in a power grid based on network flow betweenness according to claim 1 is characterized in that: The method of obtaining the power distribution relationship of the power system by using the power flow tracking algorithm includes: S11, performing power flow calculation on the power system, and establishing a directed graph of the power system based on the power grid topology and the power flow calculation results; S12, calculate the downstream distribution matrix A and the node injected active power diagonal matrix P TT and the generator output diagonal matrix P GG ; S13, calculate the distribution coefficient matrix K: K=P GG (P TT ) -1 A -1 ; Among them, (P TT ) -1 Indicates P TT The inverse matrix, A -1 represents the inverse matrix of A; S14, calculating the active power allocated to the generator node on each load node according to the allocation coefficient matrix K, and obtaining the power allocation relationship between the generator node and the load node; and, The active power allocated to the generator nodes on each transmission line is calculated according to the allocation coefficient matrix K, and the power allocation relationship between the generator nodes and the transmission lines is obtained.

3. The method for identifying vulnerable links in a power grid based on network flow betweenness according to claim 2 is characterized in that: The step of acquiring the actual power transmission path based on the power allocation relationship by using an optimized breadth-first search algorithm includes: S21, determine all generator nodes and load nodes; S22, obtaining a weighted adjacency matrix of each generator node according to the power allocation relationship between the generator node and the transmission line; S23, using the weighted adjacency matrix to search for an adjacent node whose active power of the transmission circuit between the generator node s is not zero; S24, based on the power distribution relationship between the generator node and the load, starting from the generator node s and the load node t as the end point, searching from the adjacent nodes of the generator node s from top to bottom layer by layer to find out all the power transmission paths between the generator node s and the load node t; S25, performing the search operation of S23-S24 on each generator node to obtain the power transmission path between all generator load node pairs st in the power system.

4. The method for identifying vulnerable links in power grids based on network flow betweenness according to claim 3 is characterized in that: The weighted adjacency matrix of the generator node is expressed as: Among them, Adj ij represents the element in the i-th row and j-th column of the weighted adjacency matrix, P ij Represents the active power on the transmission line ij. When there is power transmission on the transmission line ij, P ij >0, when there is no power transmission on the transmission line ij, P ij =0.

5. The method for identifying vulnerable links in power grids based on network flow betweenness according to claim 1 is characterized in that: The power transfer distribution factor is calculated as: in, represents the power transfer distribution factor of the transmission line ij in the generator load node pair st, P ij represents the active power on the transmission line ij, x ij is the reactance value of the transmission line ij, θ i represents the voltage phase angle at node i, θ j represents the voltage phase angle at node j, x is is the element in the ith row and sth column of the power system reactance matrix, x jt 、x js 、x it They correspond respectively to the j-th row and t-th column element, the j-th row and s-th column element, and the ith row and t-th column element in the reactance matrix.

6. The method for identifying vulnerable links in power grids based on network flow betweenness according to claim 5 is characterized in that: The power transfer maximum capacity is calculated as: Among them, P st represents the maximum power transmission capacity of the transmission line ij between the generator node s and the load node t, L represents the set of all transmission lines in the power transmission path of the generator load node pair st, It is an indicator that defines the power transfer capability of a transmission line. is the maximum active transmission power of the transmission line between the generator load node pair st, is the power transfer distribution factor of transmission line ij.

7. The method for identifying vulnerable links in a power grid based on network flow betweenness according to claim 6 is characterized in that: The network flow betweenness of the transmission line is calculated as: Among them, B ij is the network flow betweenness of the transmission line ij, G represents the generator node set, F represents the load node set, P st represents the maximum power transfer capacity of the transmission line ij between the generator node s and the load node t, Represents the power transfer distribution factor of transmission line ij.

8. The method for identifying vulnerable links in power grids based on network flow betweenness according to claim 7, characterized in that: The network flow betweenness of the node is calculated as: Among them, B i is the network flow betweenness of node i, Ω is the set of adjacent nodes j of node i, D i is the degree of node i, B ij is the network flow betweenness of transmission line ij.

9. 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 computer program, the method for identifying vulnerable links in a power grid based on network flow betweenness according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for identifying vulnerable links in a power grid based on network flow betweenness according to any one of claims 1 to 8 is implemented.

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