A method and system for identifying vulnerable parts of a power system under extreme events.

Abstract

This invention provides a method and system for identifying vulnerable parts of a power system under extreme events, comprising: determining an equivalent degree index based on the degree of a node in the power grid and its impact on network connectivity; determining a connectivity impact index based on the impact of channel loss on network connectivity; identifying structurally vulnerable nodes and transmission channels using the equivalent degree and connectivity impact index; determining an equivalent power flow betweenness index for a node based on the load carried by the node and the load supplied to interconnected nodes; determining an equivalent power flow betweenness index for a transmission channel based on the transmission power itself and the proportion of the power deficit caused by its loss in the total load of the receiving-end system; identifying functionally vulnerable nodes and transmission channels using the equivalent power flow betweenness indices of nodes and transmission channels; and identifying nodes and transmission channels that simultaneously exhibit structural and functional vulnerabilities as comprehensively vulnerable nodes or channels, thereby achieving quantitative identification of the vulnerability of power grid nodes and transmission channels under extreme events.

Description

Technical Field

[0001] This invention relates to the field of power system vulnerability assessment and analysis, and specifically to a method and system for identifying vulnerable parts of a power system under extreme events. Background Technology

[0002] Power system vulnerability can be considered as the characteristic of a power system whose overall structure or function is affected when its components or the system itself are disturbed. From the perspective of power system operation, the topology of the power grid provides the basic carrier for the realization of system functions. However, without considering the participation of the system's operating state, structural vulnerability assessment would be meaningless. At the same time, the physical and operational characteristics of the system rely on its own topology. Therefore, structural vulnerability and state vulnerability are interdependent, and both characterize the strength of the system's security performance. The difference lies in that structural vulnerability focuses more on the discovery of vulnerable parts of the system from the perspective of topology, while state vulnerability is a comprehensive consideration of the integrity of the system's topology, the rigor of physical laws, and the rationality of operating parameters, thus possessing a comprehensive characteristic. Among them, structural vulnerability assessment is mainly based on complex network theory, selecting statistical characteristic quantities (such as degree, betweenness number, etc.), and constructing vulnerability assessment indicators by incorporating the system's physical characteristics according to the power grid's topology. State vulnerability assessment mainly starts from the system's operating state, including both steady-state and transient aspects, and captures physical characteristic quantities. Existing related theoretical systems can be divided into deterministic methods and probabilistic methods from a mathematical perspective. Overall, current research mainly focuses on vulnerability assessment under normal operation and routine faults of power systems, with limited research on identifying vulnerable parts of power systems under extreme damage scenarios such as severe natural disasters and deliberate attacks. Therefore, it is urgent to conduct research on identifying vulnerable parts of power systems under extreme damage scenarios, combining the main characteristics that vulnerable parts of power systems may exhibit under extreme events, to lay an important foundation for targeted defense deployments. Summary of the Invention

[0003] To address the aforementioned technical problems, the present invention provides a method for identifying vulnerable parts of a power system under extreme events, comprising:

[0004] Based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of the node is determined; based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is determined; the nodes and transmission channels with structural vulnerabilities in the power system are identified by the node equivalent degree index and the channel connectivity impact index.

[0005] The equivalent power flow betweenness index of a node is determined based on the load it carries and the load it supplies to interconnected nodes. The equivalent power flow betweenness index of a transmission channel is determined based on the proportion of the transmission power of the channel itself and the power deficit caused by the loss of the channel in the total load of the receiving-end system. The nodes and transmission channels with functional vulnerabilities in the power system are identified by the equivalent power flow betweenness index of the node and the equivalent power flow betweenness index of the transmission channel.

[0006] Based on the structural vulnerability of nodes and transmission channels, as well as the functional vulnerability of nodes and transmission channels, nodes and transmission channels that simultaneously exhibit both structural and functional vulnerability are selected and identified as comprehensive vulnerability points or channels.

[0007] Furthermore, based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of the node is determined, including:

[0008] When a node is disconnected from the power grid, and the power grid experiences a disconnection;

[0009] The smaller the degree value of a node and the smaller its impact on network connectivity, the more complete the largest connected subgraph in the remaining network is maintained, and the higher the network connectivity, the smaller the equivalent degree value of the node, which means the lower the importance of the node.

[0010] The higher the degree value of a node and the greater its impact on network connectivity, the smaller the number of nodes in the largest connected subgraph of the remaining network, the higher the equivalent degree value of the node, which represents the higher the importance of the node.

[0011] Based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of the node is specifically as follows:

[0012]

[0013] In the formula, D(node) i Let k be the equivalent degree of node i. i Let N be the degree of node i, and N be the total number of nodes in the initial network. sub Let be the number of nodes in the largest connected subgraph of the remaining network after node i is lost.

[0014] Furthermore, based on the impact of channel loss on network connectivity, connectivity impact indicators for the channels are determined, including:

[0015] When the transmission line is disconnected from the power grid, the interconnectivity of the power grid decreases or even disconnects from the grid.

[0016] When a channel is disconnected from the power grid, the more complete the largest connected subgraph in the remaining network remains, the smaller the impact of the channel disconnection on the network connectivity, and the smaller the connectivity impact index, which represents the lower the importance of the channel.

[0017] Conversely, the greater the impact of a disconnected channel on network connectivity, the higher the connectivity impact index, indicating the greater the importance of the channel.

[0018] Based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is specifically as follows:

[0019]

[0020] In the formula, N is the initial total number of network nodes. sub This represents the maximum number of nodes in the remaining connected subgraph of the network after the channel is lost.

[0021] Furthermore, the nodes and transmission channels that identify structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index include:

[0022] The higher the degree value of a node and the greater its impact on network connectivity, the smaller the number of nodes in the largest connected subgraph of the remaining network, the higher the equivalent degree value of the node, and the higher the importance of the node. In this case, the node is a structurally fragile node.

[0023] The smaller the number of nodes in the largest connected subgraph of the remaining network after a channel is lost, the greater the impact of the channel disconnection on the network connectivity; the larger the connectivity impact index, the higher the importance of the channel, and the channel is a structurally fragile channel.

[0024] Furthermore, based on the load carried by the node itself and the load supplied by the node and the interconnected nodes, the equivalent power flow betweenness index of the node is determined, including:

[0025] The larger the load carried by the node itself, and the larger the load that the node supplies to the interconnected nodes, the larger the value of the node's equivalent power flow betweenness index.

[0026] Based on the load carried by the node itself and the load supplied by the node to interconnected nodes, the equivalent power flow betweenness index of the node is specifically as follows:

[0027]

[0028] In the formula, J(node) i Let P be the equivalent power flow betweenness of node i. ij Let P be the active power flow of the line between node i and node j, where n is the out-degree of node i, and P is the active power flow of the line between node i and node j. i P represents the load carried by node i. j Let J be the load carried by node j.

[0029] Furthermore, based on the proportion of the transmission channel's own transmission power and the power deficit caused by the loss of the channel in the total load of the receiving-end system, the equivalent power flow betweenness index of the transmission channel is determined, including:

[0030] The greater the transmission power of the channel itself, the greater the impact of the channel on the power balance of the sending and receiving end systems;

[0031] The larger the proportion of the power deficit caused by the loss of the channel in the total load of the receiving system, the more severe the impact on the receiving system.

[0032] The equivalent power flow betweenness index of a channel is determined by the proportion of its own transmission power and the power deficit caused by channel loss in the total load of the receiving-end system.

[0033] Internal transmission channels of synchronous power grid: Transmission channels between asynchronous power grids:

[0034] In the formula, RE represents the receiving-end power grid set, and P... i Let n be the active power flow through line i, and n be the number of transmission lines feeding into the receiving-end power grid r (i = 1, 2, ..., n). ΔP j ΔP represents the power transferred through the remaining channels j after the channel feeding into the receiving-end grid r is lost, where m is the number of remaining channels (j = 1, 2, ..., m). jmax P is the power margin for channel j. r Let r be the total load of the receiving-end power grid (r∈RE).

[0035] Furthermore, based on the fact that there is no power transfer after the DC channel between asynchronous interconnected power grids is lost, the transmission channels are divided into transmission channels within synchronous power grids and transmission channels between asynchronous power grids.

[0036] Furthermore, the nodes and transmission channels that identify power system functional vulnerabilities using the equivalent power flow betweenness indices of the nodes and the equivalent power flow betweenness indices of the transmission channels include:

[0037] The larger the load carried by the node itself, the larger the load that the node supplies to the interconnected nodes, the larger the node's equivalent power flow betweenness index value, and the more important the power supply performance of the node, then the node is a functionally vulnerable node.

[0038] The greater the active power transmitted through the internal channels of the synchronous grid, the higher the proportion of the power deficit in the total load at the receiving end, the greater the equivalent power flow betweenness index value of the channel, and the more important the power supply performance of the channel, thus the channel is a functionally vulnerable channel.

[0039] The greater the active power transmitted through the transmission channel between asynchronous power grids, and the greater the proportion of the transmitted power in the total load of the receiving-end system, the greater the equivalent power flow betweenness index of the channel, and the more important the power supply performance of the channel is. In this case, the channel is a functionally vulnerable channel.

[0040] This invention also provides a system for identifying vulnerable parts of a power system under extreme events, comprising:

[0041] The structural vulnerability identification module is used to determine the equivalent degree index of a node based on the node's own degree and its impact on the network connectivity level in the power system network; to determine the connectivity impact index of a channel based on the impact of channel loss on network connectivity; and to identify nodes and transmission channels with structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index.

[0042] The functional vulnerability identification module is used to determine the equivalent power flow betweenness index of a node based on the load it carries and the load it supplies to interconnected nodes; to determine the equivalent power flow betweenness index of a transmission channel based on the proportion of the transmission power of the channel itself and the power deficit caused by the loss of the channel in the total load of the receiving-end system; and to identify nodes and transmission channels with functional vulnerabilities in the power system based on the equivalent power flow betweenness index of the node and the equivalent power flow betweenness index of the transmission channel.

[0043] The comprehensive identification module is used to filter nodes and transmission channels that exhibit both structural and functional vulnerabilities based on the structural vulnerabilities and functional vulnerabilities, and identify them as comprehensive vulnerability points or channels. The remaining nodes or channels that exhibit only a single aspect of vulnerability are identified as vulnerable nodes or channels in that specific aspect.

[0044] The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the method described in any one of the preceding claims.

[0045] This invention provides a method and system for identifying vulnerable parts of a power system under extreme events. Targeting grid nodes and transmission channels, it addresses both structural and functional vulnerability, drawing on concepts such as degree and betweenness in complex network theory. It integrates system topology, physical characteristics, and operational characteristics to construct vulnerability identification indicators, thereby achieving quantitative identification of the vulnerability level of grid nodes and transmission channels under extreme events. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating a method for identifying vulnerable parts of a power system under extreme events, provided by an embodiment of the present invention.

[0047] Figure 2 This is a process diagram illustrating the identification of vulnerable parts of a power system under extreme events, as described in an embodiment of the present invention.

[0048] Figure 3 This is a geographical wiring diagram of the 500kV power grid involved in the embodiments of the present invention;

[0049] Figure 4 These are the system bus voltage curves before and after load shedding under different node total outage faults in the embodiments of the present invention;

[0050] Figure 5 This is a schematic diagram of an inter-provincial power transmission channel according to an embodiment of the present invention;

[0051] Figure 6 This is the system operation curve after the W-S channel is disconnected, as described in the embodiments of the present invention;

[0052] Figure 7 This is the system operation curve after the W-Z channel is disconnected, as described in this embodiment of the invention.

[0053] Figure 8 This is the system bus frequency curve after the AQ-XC channel is disconnected, as described in this embodiment of the invention.

[0054] Figure 9 This is the system bus frequency curve after the XC-GD channel is disconnected, as described in this embodiment of the invention.

[0055] Figure 10 This is an embodiment of the invention relating to the system bus frequency curve after the FFJS channel is disconnected;

[0056] Figure 11 This is a schematic diagram of a system structure for identifying vulnerable parts of a power system under extreme events, provided by an embodiment of the present invention. Detailed Implementation

[0057] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0058] Example 1

[0059] Figure 1 A flowchart illustrating a method for identifying vulnerable parts of a power system under extreme events is shown, the method comprising the following steps:

[0060] Step S101: Determine the equivalent degree index of a node based on its own degree in the power system network and the impact of the node on the network connectivity level; determine the connectivity impact index of a channel based on the impact of the loss of the channel on the network connectivity; identify the nodes and transmission channels with structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index.

[0061] Structural vulnerability identification, firstly, at the node level, involves the potential for grid disconnection when a node is disconnected from the power grid. A smaller node degree value, a smaller impact on network connectivity, a more complete maximum connected subgraph in the remaining network, and a higher degree of network connectivity all indicate a smaller equivalent degree value for the node, representing lower node importance. Conversely, a higher node degree value, a greater impact on network connectivity, a smaller number of nodes in the maximum connected subgraph of the remaining network, and a larger equivalent degree value indicate higher node importance. Based on the node's degree value and its impact on network connectivity in the power system network, the node's equivalent degree index is specifically defined as follows:

[0062]

[0063] In the formula, D(node) i Let k be the equivalent degree of node i. i Let N be the degree of node i, and N be the total number of nodes in the initial network. sub Let be the number of nodes in the largest connected subgraph of the remaining network after node i is lost.

[0064] Secondly, regarding transmission channels, when a channel is disconnected from the power grid, the grid interconnectivity decreases or even disconnects. The more complete the largest connected subgraph remains in the remaining network, the smaller the impact of channel disconnection on network connectivity, resulting in a lower connectivity impact index and a lower structural importance of the channel. Conversely, the greater the impact of channel disconnection on network connectivity, the higher the connectivity impact index and the higher the importance of the channel. Based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is specifically as follows:

[0065]

[0066] In the formula, N is the initial total number of network nodes. sub This represents the maximum number of nodes in the remaining connected subgraph of the network after the channel is lost.

[0067] Step S102: Determine the equivalent power flow betweenness index of the node based on the load it carries and the load it supplies to the interconnected nodes; determine the equivalent power flow betweenness index of the transmission channel based on the proportion of the transmission power of the channel itself and the power deficit caused by the loss of the channel in the total load of the receiving-end system; identify the nodes and transmission channels with functional vulnerabilities in the power system based on the equivalent power flow betweenness index of the node and the equivalent power flow betweenness index of the transmission channel.

[0068] Functional vulnerability identification begins with the following: Firstly, regarding nodes, the larger the load carried by the node itself, and the larger the load supplied by the node to interconnecting nodes, the larger the node's equivalent power flow betweenness index value. Based on the node's own load and the load supplied to interconnecting nodes, the node's equivalent power flow betweenness index is determined as follows:

[0069]

[0070] In the formula, J(node) i Let P be the equivalent power flow betweenness of node i. ij Let P be the active power flow of the line between node i and node j, where n is the out-degree of node i, and P is the active power flow of the line between node i and node j. i P represents the load carried by node i. j Let J be the load carried by node j.

[0071] Secondly, regarding transmission channels, the larger the transmission capacity of the channel itself, the greater its impact on the power balance of the sending and receiving end systems; the larger the proportion of the power deficit caused by the loss of the channel in the total load of the receiving end system, the more severe the impact on the receiving end system. Based on the channel's own transmission capacity and the proportion of the power deficit caused by the loss of the channel in the total load of the receiving end system, the equivalent power flow betweenness indices of the channel are determined. Considering that there is no power transfer after the loss of a DC channel between asynchronous interconnected grids, transmission channels are divided into transmission channels within synchronous grids and transmission channels between asynchronous grids. The specific equivalent power flow betweenness indices of the channels are as follows: Transmission channels within synchronous grids: Transmission channels between asynchronous power grids:

[0072] In the formula, RE represents the receiving-end power grid set, and P... i Let n be the active power flow through line i, and n be the number of transmission lines feeding into the receiving-end power grid r (i = 1, 2, ..., n). ΔP j ΔP represents the power transferred through the remaining channels j after the channel feeding into the receiving-end grid r is lost, where m is the number of remaining channels (j = 1, 2, ..., m). jmax P is the power margin for channel j. r Let r be the total load of the receiving-end power grid (r∈RE).

[0073] The greater the active power transmitted through the internal channels of the synchronous grid, the higher the proportion of the power deficit in the total load at the receiving end, the greater the equivalent power flow betweenness index value of the channel, and the more important the power supply performance of the channel, thus the channel is a functionally vulnerable channel.

[0074] The greater the active power transmitted through the transmission channel between asynchronous power grids, and the greater the proportion of the transmitted power in the total load of the receiving-end system, the greater the equivalent power flow betweenness index of the channel, and the more important the power supply performance of the channel is. In this case, the channel is a functionally vulnerable channel.

[0075] Step S103: Based on the nodes and transmission channels with structural vulnerabilities and the nodes and transmission channels with functional vulnerabilities, select nodes and transmission channels that simultaneously exhibit both structural and functional vulnerabilities, and identify them as comprehensive vulnerability points or channels. The remaining nodes or channels that only exhibit a single aspect of vulnerability are identified as vulnerable nodes or channels in that specific aspect.

[0076] Example 2

[0077] The process for identifying vulnerable parts of the power system under extreme events is as follows: Figure 2 As shown. First, structural vulnerability identification is performed. Starting from structural performance, equivalent degree indices for nodes and connectivity impact indices for transmission channels are defined. The equivalent degree indices for all nodes and the connectivity impact indices for transmission channels across the entire network are calculated. Nodes and channels ranked in descending order are identified as structurally vulnerable. Based on the required number of nodes to be selected, a set of structurally vulnerable nodes and channels is determined, enabling an assessment of the degree of damage to the system network integrity after the loss of nodes and transmission channels. Next, functional vulnerability identification is performed. Considering power supply function, equivalent power flow betweenness indices for nodes and transmission channels are defined, and the equivalent power flow betweenness indices for all nodes and transmission channels across the entire network are calculated. Again, nodes and channels ranked in descending order are identified as functionally vulnerable. Based on the required number of nodes to be selected, a set of functionally vulnerable nodes and channels is determined, enabling an assessment of the power loss impact after the loss of nodes and transmission channels. Finally, comprehensive vulnerability identification is performed. Nodes or channels that appear in both the structurally vulnerable set and the functionally vulnerable set are selected. If a node or channel exhibits strong vulnerability in both aspects, it is identified as a comprehensively vulnerable node or channel. Other nodes or channels that appear only in a single set are identified as vulnerable nodes or channels in the corresponding aspect.

[0078] (1) Structural vulnerability identification

[0079] 1) From the perspective of nodes, considering both local and global characteristics, the structural performance of a node is reflected locally in its own degree, and globally in its impact on the overall network connectivity. Based on this, the degree index in complex networks is improved, and the equivalent degree index for a node is defined as follows:

[0080]

[0081] In the formula, D(node) i Let k be the equivalent degree of node i. i Let N be the degree of node i, and N be the total number of nodes in the initial network. sub Let be the number of nodes in the largest connected subgraph of the remaining network after node i is lost.

[0082] As shown in equation (1), when an attacked node is disconnected from the power grid, it may lead to a grid split. The smaller the degree value of a node, the smaller its impact on network connectivity, the more complete the maximum connected subgraph in the remaining network remains, the higher the network connectivity, and the smaller the node's equivalent degree value, the lower the structural importance of the node. Conversely, the higher the degree value of a node, the greater its impact on network connectivity, the smaller the number of nodes in the maximum connected subgraph of the remaining network, the larger the node's equivalent degree value, and the higher the structural importance of the node.

[0083] 2) Regarding transmission channels, transmission channels interconnect nodes to form a power grid. Damage to these channels leads to a decrease in grid interconnectivity or even grid disconnection. Therefore, considering the impact of channel loss on network connectivity, the following connectivity impact index is defined:

[0084]

[0085] In the formula, N is the initial total number of network nodes. sub This represents the maximum number of nodes in the remaining connected subgraph of the network after the channel is lost.

[0086] As can be seen from equation (2), when the attacked channel is disconnected from the power grid, the more complete the maximum connected subgraph remains in the remaining network, i.e., N sub The larger N is, the smaller the impact of channel disconnection on network connectivity, the smaller the impact on connectivity indicators, and the lower the structural importance of the channel; conversely, the smaller N is. sub The smaller the value, the greater the impact of channel disconnection on network connectivity. The larger the connectivity impact index, the higher the structural importance of the channel, and the more vulnerable it is to the structure.

[0087] (2) Functional vulnerability identification

[0088] 1) From a node perspective, considering power supply functionality, the load impact after a node loss mainly includes two parts: first, the load carried by the node itself, and second, the load supplied to other interconnected nodes (in the worst-case scenario, power transfer is not considered). The traditional power flow betweenness indices are improved, and the equivalent power flow betweenness indices for nodes are defined as follows:

[0089]

[0090] In the formula, J(node) i Let P be the equivalent power flow betweenness of node i. ij Let P be the active power flow of the line between node i and node j, and n be the out-degree of node i, i.e., the line power flow P. ij The number of positive branches (j = 1, 2, ..., n) (defined as outflow direction being positive), P i P represents the load carried by node i. j Let J be the load carried by node j.

[0091] As shown in equation (3), the equivalent power flow betweenness index of a node considers not only the node's own load but also its power supply capacity and importance to connected nodes. The node's out-degree number represents the number of branches supplying power to other nodes; a higher out-degree number indicates a larger power supply range. The proportion of the power flow of connected lines in the load of connected nodes represents the importance of power supply to connected nodes; a higher proportion indicates a larger power flow and a stronger equivalent power supply capacity to connected nodes. The node's own load P... i The larger the value, the greater the equivalent power flow betweenness index of the node, which, when combined with the aforementioned positively correlated indices, indicates that the node's power supply performance is more important.

[0092] 2) Regarding transmission channels, as power transmission links connecting the sending and receiving systems, their functional importance is mainly reflected in two aspects: first, the magnitude of their own transmitted power; the larger the transmitted power, the greater the impact on the power balance of the sending and receiving systems after damage; second, the proportion of the power deficit caused by the loss of the channel in the total load of the receiving system; the larger the proportion of the deficit, the more severe the impact on the receiving system after damage. Considering the power transfer situation of the power grid transmission channels, if the other channels have a strong ability to receive power transfer, the impact of channel loss can be mitigated to some extent. Since the power transfer situations of AC and DC transmission channels differ, there is no power transfer channel after the loss of a DC channel between asynchronous interconnected grids (the impact of parallel DC power increase is not considered for now). Therefore, transmission channels are considered to be divided into two main categories: transmission channels within synchronous grids and transmission channels between asynchronous grids. Based on the above factors, the equivalent power flow betweenness index of transmission channels is defined as follows:

[0093] Internal transmission channels of synchronous power grid: Transmission channels between asynchronous power grids:

[0094] In equation (4), RE is the receiving-end power grid set, and P i Let n be the active power flow through line i, and n be the number of transmission lines feeding into the receiving-end power grid r (i = 1, 2, ..., n). ΔP j ΔP represents the power transferred through the remaining channels j after the channel feeding into the receiving-end grid r is lost, where m is the number of remaining channels (j = 1, 2, ..., m).xjam P represents the power margin of channel j, which is the difference between the transmission power limit of channel j and its current power. r Let r be the total load of the receiving-end power grid (r∈RE).

[0095] In equation (5), RE is the receiving-end power grid set, and P i P represents the active power flow through line i, where n is the number of transmission line cycles (i = 1, 2, ..., n). r Let r be the total load of the receiving-end power grid (r∈RE).

[0096] As shown in equation (4), the equivalent power flow betweenness index of the transmission channel within the synchronous power grid considers both the absolute value of the channel's transmitted power and the proportion of the potential power deficit in the total load of the receiving-end system, thus reflecting both the channel's own characteristics and its impact on the power supply of the receiving-end system. ΔP represents the active power transmitted by the channel. jmax The power margin of the confined channel during the power transfer process, i.e., the power transfer capability, is represented by ΔP. j -ΔP jmax This value can characterize the power deficit caused by the loss of a channel; it should be greater than or equal to 0.

[0097]

[0098] The greater the active power transmitted by the channel, the higher the proportion of the resulting power deficit in the total load at the receiving end. The larger the equivalent power flow betweenness index of the channel, the more important the power supply performance of the channel is, and the greater the impact on the system after damage. It belongs to the functionally vulnerable link.

[0099] As shown in equation (5), the equivalent power flow between asynchronous power grids considers both the absolute value of the transmission power and its relative value to the total load of the receiving system, thus reflecting both the characteristics of the transmission channel itself and its impact on the power supply of the receiving system. Represents the active power transmitted through the channel. The active power transmitted represents the proportion of the channel power in the total load of the receiving system. The larger the active power transmitted and the higher the proportion, the larger the equivalent power flow betweenness index of the channel. This indicates that the power supply performance of the channel is more important, and the impact on the system after damage is greater, making it a functionally vulnerable link.

[0100] (3) Comprehensive vulnerability identification

[0101] Based on the calculation results of the structural and functional vulnerability indices of all network nodes and transmission channels, nodes or channels that appear in both the structurally vulnerable set and the functionally vulnerable set are selected. These nodes or channels exhibit strong vulnerability in both aspects and are identified as comprehensively vulnerable nodes or channels. The remaining nodes or channels that appear only in a single set are identified as vulnerable nodes or channels in the corresponding aspect.

[0102] Example 3

[0103] (1) Node vulnerability assessment

[0104] Taking a provincial power grid as an example, this study identifies vulnerable nodes within the grid. Based on abundant grid data, the grid load is approximately 33,400 MW. Vulnerability screening is performed on nodes at the 500kV level. The geographical wiring diagram of the 500kV power grid is shown below. Figure 3 As shown.

[0105] First, the structural vulnerability was analyzed, and the statistics of the 500kV node degree are shown in Table 1.

[0106] Table 1. Statistics of 500kV node degrees

[0107]

[0108] When counting the number of network nodes, the number of nodes connected to the first-level cross-section of the node is included. After calculation and analysis, the equivalent degree index of the above nodes is arranged in descending order as shown in Table 2.

[0109] Table 2 Calculation Table of 500kV Nodal Equivalence Index

[0110] Serial Number Node Name degree N <![CDATA[N sub ]]> Equivalence 1 FS 11 26 24 11.92 2 SY 10 26 24 10.83 3 AD 9 26 23 10.17 4 CP 9 26 24 9.75 5 MTG 8 26 24 8.67 6 TZ 7 26 25 7.28 7 XHC 7 26 25 7.28 8 TB 6 26 24 6.50 9 KXC 4 26 25 4.16 10 YZN 4 26 25 4.16 11 RZHLZ 2 26 25 2.08 12 HD 2 26 25 2.08 13 CB 2 26 25 2.08 14 GM 2 26 25 2.08 15 CY 2 26 25 2.08 16 XD 2 26 25 2.08 17 LZ 2 26 25 2.08

[0111] Table 2 shows that, considering structural performance, the most vulnerable nodes are FS station, SY station, and AD station, with all of them having an equivalent degree index of 10 or higher. Since the 500kV power grid has a ring network structure, the maximum number of nodes N in the remaining connected subgraph after the loss of different nodes is considered. sub The differences are not significant, meaning the impact on network connectivity is small. Overall, the equivalent degree is positively correlated with the degree.

[0112] Then, the vulnerability of the node power supply function was analyzed, and the node equivalent power flow betweenness indices were arranged in descending order as shown in Table 3.

[0113] Table 3. Calculation Table of Equivalent Power Flow Betweenness Indices for 500kV Nodes

[0114] Serial Number Node Name Equivalent power flow betweenness 1 SY 6353.1 2 FS 5905.9 3 AD 5864.7 4 CP 5229.1 5 XHC 4321.7 6 TZ 4157.6 7 TB 2888.9 8 CB 2424.3 9 HD 2160.6 10 XD 2085.5 11 MTG 2025.1 12 RZHLZ 2015.2 13 GM 1683.2 14 YZN 1598.0 15 LZ 1484.8 16 KXC 1294.6 17 CY 1215.2

[0115] As shown in Table 3, considering power supply function, the most vulnerable nodes are, in order, SY station, FS station, and AD station. These nodes themselves carry a large load and provide strong power support for connected branches. The above node set is the same as the top three structurally vulnerable node sets, with only a slight difference in order. Therefore, these three nodes can be considered as comprehensively vulnerable nodes, exhibiting vulnerability in both structure and function.

[0116] Furthermore, a comparative analysis was conducted on the impact of different node failures on the safe and stable operation of the system. Taking a complete node outage as an example, the load loss of the system after the complete outage of different nodes was compared. The top-ranked vulnerable nodes, SY, FS, and AD, were selected for comparison with randomly selected TB, HD, and LZ stations. Low-voltage load shedding measures were implemented when the node bus voltage dropped below 0.8 pu, and the load shedding ratio was configured according to the constant impedance type. The statistics of the load shedding after a complete outage are shown in Table 4, and the system bus voltage curves before and after load shedding are shown in Table 4. Figure 4 As shown.

[0117] Table 4. Statistics on load shelving after a node complete failure.

[0118] Serial Number Node Name Load shedding (MW) Percentage of resected load 1 SY 14580 43.7％ 2 AD 18000 53.9％ 3 FS 9100 27.2％ 4 TB 80 0.2％ 5 HD 330 1.0％ 6 LZ — —

[0119] Depend on Figure 4 It can be seen that the complete outage of SY, AD, and FS substations caused a local power grid voltage collapse, with the node bus voltage dropping to around 0.6 pu. After taking extensive load shedding measures, the system voltage recovered to the rated value. The lost load accounted for as high as 43.7%, 53.9%, and 27.2% of the total load of the Beijing power grid, respectively. After the complete outage of HD and TB substations, the voltage of some busbars was slightly lower than 0.8 pu, requiring only a small amount of load shedding. After the complete outage of LZ substation, no load shedding was required. Therefore, it is evident that the severity of the impact of faults at vulnerable nodes identified by the proposed method on system operation is significantly higher than that of other nodes, thus proving the effectiveness and accuracy of the proposed method.

[0120] (2) Vulnerability assessment of transmission channels

[0121] Taking a regional power grid as an example, a vulnerability analysis of transmission channels is conducted. Considering the different characteristics of AC and DC transmission channels, and given that this power grid has multiple inter-provincial AC interconnection channels and multiple DC feed-in channels, it is necessary to conduct a comparative vulnerability analysis of AC and DC channels separately.

[0122] (1) Internal transmission channels of synchronous power grid

[0123] Based on current power grid peak load data, the total regional power grid load is 230,000 MW, and the spinning reserve capacity is 18,500 MW. Vulnerability comparisons are conducted using inter-provincial interconnection channels within the power grid, taking the W-S and W-Z transmission channels as examples. The transmission channel structures are as follows: Figure 5 As shown. Since the impact of disconnecting transmission channels on grid connectivity is basically the same, the following analysis mainly focuses on the functional impact.

[0124] Under the W-type power transmission mode, the initial power flow distribution of the channel is shown in Table 5.

[0125] Table 5 Initial Mode Channel Power Flow Statistics

[0126]

[0127] According to statistics, the JS power grid load is 103,910 MW and the ZJ power grid load is 54,090 MW under this method. Considering that the sending and receiving ends are still in a synchronous grid after the transmission channel is lost, the power is transferred through the internal channels of the grid. For example, after the W-S channel is lost, the AH sending end and the JS receiving end are still synchronously interconnected grids. The surplus power at the sending end will be transferred by the W-Z channel and then transmitted through the ZJ, SH and JS interconnection channels. The power transfer after the W-S channel and W-Z channel are disconnected is shown in Table 6. The maximum tolerable power transfer amount is calculated based on the difference between the channel thermal stability limit and the initial power.

[0128] Table 6 Power Transfer and Shortfall Calculation After Channel Disconnection Table 6 Power Transfer and Shortfall Calculation Table

[0129]

[0130] Based on the calculation results in Table 6, the equivalent power flow betweennesses of the W-S channel and the W-Z channel are calculated as follows:

[0131]

[0132] The comparison shows that the equivalent power flow dielectric value of the W-Z channel is higher, indicating that the impact of damage to this channel on the system is greater. Furthermore, to verify the effectiveness of the proposed method, the impact of different transmission channel faults on the safe and stable operation of the system is analyzed using BPA simulation.

[0133] According to the simulation results, after all W-S channels are disconnected, the power flow transfer causes the GD-PY single-circuit line to trip due to overload. The system can maintain stable operation, and the system bus voltage and frequency curves are as follows. Figure 6 As shown.

[0134] After the W-Z channels were completely disconnected, the power flow shift caused the EX-HF and DT-TM double-circuit lines to trip due to overload, and the HN-WH UHV double-circuit line to oscillate and disconnect, ultimately leading to system instability. The system bus voltage and frequency curves are as follows: Figure 7 As shown.

[0135] Simulation results show that the W-Z channel fault has a more severe impact on the system under this method, which is consistent with the index calculation results of the proposed method.

[0136] (2) Transmission channels between asynchronous power grids

[0137] Based on current power grid data during peak and off-peak periods, the total grid load is 140,000 MW, and the spinning reserve capacity is 18,500 MW. High-capacity DC transmission channels fed into the grid are selected, with the AQ-XC, XC-GD, and FFJS channels (HB section) as examples for vulnerability comparison. These channels all contain several DC transmission lines, as shown in Table 7. Due to the short distances between these channels, there is a risk of all transmission channels being disconnected under unconventional conditions.

[0138] Table 7. Statistics of Power Transmission Channels

[0139] Serial Number Channel Name The corridor includes power transmission projects Total channel capacity (MW) 1 AQ-XC Channel LS+JS+FF+GN+LF 21800 2 XC-GD Channel JS+FF+GN+LF 17800 3 FFJS Channel FF+JS 13600

[0140] Based on Table 7, the equivalent power flow betweenness indices for different transmission channels can be calculated as shown in Table 8.

[0141] Table 8. Calculation of Equivalent Power Flow Betweenness Index for Transmission Channels

[0142]

[0143] As shown in Table 8, the AQ-XC channel has the largest equivalent power flow dielectric value, corresponding to the highest vulnerability level; while the FFJS channel has the smallest equivalent power flow dielectric value, corresponding to the lowest vulnerability level.

[0144] Furthermore, a comparative analysis was conducted on the impact of different transmission channel faults on the safe and stable operation of the system. Taking a fault where all transmission channels are disconnected as an example, the load loss of the system after the disconnection of different channels was compared. The low-frequency load shedding schemes of the power grid are shown in Table 9, and the statistics of the load shedding amount after the channel disconnection are shown in Table 10. The system bus frequency curve after the fault is shown in Table 10. Figures 8-10 As shown.

[0145] Table 9 Power Grid Low-Frequency Load Shedding Configuration Scheme

[0146]

[0147] Table 10: Statistics of System Load Shedding After Channel Disconnection

[0148] Serial Number Channel Name Load shedding (MW) Percentage of resected load Lowest frequency (Hz) 1 AQ-XC Channel 22480 16.06％ 48.5 2 XC-GD Channel 12850 9.18％ 48.7 3 FFJS Channel 9828 7.02％ 48.76

[0149] From Table 10, Figures 8-10 It can be seen that after the AQ-XC channel, XC-GD channel, and JS channel were disconnected, the power grid experienced a large power deficit, and the system bus frequency dropped to 48.5Hz, 48.7Hz, and 48.76Hz, respectively, triggering low-frequency load shedding. After the load was cut off, the system frequency returned to near the rated value. The proportion of the load cut off to the total network load was as high as 16.06%, 9.18%, and 7.02%, respectively. The AQ-XC channel was the most vulnerable, and its disconnection had a significantly more serious impact on the safe and stable operation of the system than the other two channels.

[0150] In summary, the proposed method can effectively identify the vulnerability level of power transmission channels, providing a reference for the quantitative comparative analysis of power transmission channel vulnerability.

[0151] Example 4

[0152] Based on the same inventive concept, this invention also provides a system for identifying vulnerable parts of a power system under extreme events, such as... Figure 11 As shown, it includes:

[0153] The structural vulnerability identification module 110 is used to determine the equivalent degree index of a node based on the node's own degree and the node's impact on the network connectivity level in the power system network; to determine the connectivity impact index of a channel based on the impact of the channel being lost on the network connectivity; and to identify the nodes and transmission channels with structural vulnerabilities in the power system based on the node's equivalent degree index and the channel's connectivity impact index.

[0154] The functional vulnerability identification module 120 is used to determine the equivalent power flow betweenness index of a node based on the load it carries and the load it supplies to interconnected nodes; to determine the equivalent power flow betweenness index of a transmission channel based on the transmission power of the channel itself and the proportion of the power deficit caused by the loss of the channel in the total load of the receiving-end system; and to identify nodes and transmission channels with functional vulnerabilities in the power system based on the equivalent power flow betweenness index of the node and the equivalent power flow betweenness index of the transmission channel.

[0155] The comprehensive identification module 130 is used to filter nodes and transmission channels that simultaneously exhibit structural and functional vulnerabilities based on the structural vulnerabilities and functional vulnerabilities, and identify them as comprehensive vulnerability points or channels. The remaining nodes or channels that only exhibit a single aspect of vulnerability are identified as vulnerable nodes or channels in that specific aspect.

[0156] This invention provides a method and system for identifying vulnerable parts of a power system under extreme events. Targeting grid nodes and transmission channels, it addresses both structural and functional vulnerability, drawing on concepts such as degree and betweenness in complex network theory. It integrates system topology, physical characteristics, and operational characteristics to construct vulnerability identification indicators, thereby achieving quantitative identification of the vulnerability level of grid nodes and transmission channels under extreme events.

[0157] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0159] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0160] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A method for identifying vulnerable parts of a power system under extreme events, characterized in that, include: Based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of the node is determined; based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is determined; the nodes and transmission channels with structural vulnerabilities in the power system are identified by the node equivalent degree index and the channel connectivity impact index. The equivalent power flow betweenness index of a node is determined based on the load carried by the node itself and the load supplied by the node to interconnected nodes. The equivalent power flow betweenness index of the transmission channel is determined based on the proportion of the transmission power itself and the power deficit caused by the loss of the channel in the total load of the receiving-end system; the nodes and transmission channels with functional vulnerabilities in the power system are identified by the equivalent power flow betweenness index of the nodes and the equivalent power flow betweenness index of the transmission channels. Based on the structural vulnerability of nodes and transmission channels, and the functional vulnerability of nodes and transmission channels, nodes and transmission channels that simultaneously exhibit structural and functional vulnerability are screened and identified as comprehensive vulnerability points or channels. Based on the impact of channel loss on network connectivity, determine the connectivity impact indicators of the channels, including: When the transmission line is disconnected from the power grid, the interconnectivity of the power grid decreases or even disconnects from the grid. When a channel is disconnected from the power grid, the more complete the largest connected subgraph in the remaining network remains, the smaller the impact of the channel disconnection on the network connectivity, and the smaller the connectivity impact index, which represents the lower the importance of the channel. Conversely, the greater the impact of a disconnected channel on network connectivity, the higher the connectivity impact index, indicating the greater the importance of the channel. Based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is specifically as follows: In the formula, N is the initial total number of network nodes. sub The maximum number of nodes in the remaining connected subgraph of the network after the channel is lost; The nodes and transmission channels that identify structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index include: The higher the degree value of a node and the greater its impact on network connectivity, the smaller the number of nodes in the largest connected subgraph of the remaining network, the higher the equivalent degree value of the node, and the higher the importance of the node. In this case, the node is a structurally fragile node. The smaller the number of nodes in the largest connected subgraph of the remaining network after a channel is lost, the greater the impact of the channel disconnection on the network connectivity; the larger the connectivity impact index, the higher the importance of the channel, and the channel is a structurally fragile channel. Based on the load supplied by the node itself and the load supplied by the node and interconnected nodes, the equivalent power flow betweenness indices of the node are determined, including: The larger the load carried by the node itself, and the larger the load that the node supplies to the interconnected nodes, the larger the value of the node's equivalent power flow betweenness index. Based on the load carried by the node itself and the load supplied by the node to interconnected nodes, the equivalent power flow betweenness index of the node is specifically as follows: In the formula, J(node) i Let P be the equivalent power flow betweenness of node i. ij Let P be the active power flow of the line between node i and node j, where n is the out-degree of node i, and P is the active power flow of the line between node i and node j. i P represents the load carried by node i. j Let J be the load carried by node j. The equivalent power flow betweenness index of the transmission channel is determined based on the proportion of the channel's own transmission power and the power deficit caused by the loss of the channel in the total load of the receiving-end system, including: The greater the transmission power of the channel itself, the greater the impact of the channel on the power balance of the sending and receiving end systems. The larger the proportion of the power deficit caused by the loss of the channel in the total load of the receiving system, the more severe the impact on the receiving system. The equivalent power flow betweenness index of a channel is determined by the proportion of its own transmission power and the power deficit caused by channel loss in the total load of the receiving-end system. Internal transmission channels of synchronous power grid: Transmission channels between asynchronous power grids: In the formula, RE represents the receiving-end power grid set, and P... i Let n be the active power flow through line i, and n be the number of transmission lines feeding into the receiving-end power grid r (i = 1, 2, ..., n). ΔP j ΔP represents the power transferred through the remaining channels j after the channel feeding into the receiving-end grid r is lost, where m is the number of remaining channels (j = 1, 2, ..., m). jmax P is the power margin for channel j. r Let r be the total load of the receiving-end power grid (r∈RE); Based on the fact that there is no power transfer after the DC channel between asynchronous interconnected power grids is lost, transmission channels are divided into transmission channels within synchronous power grids and transmission channels between asynchronous power grids. The nodes and transmission channels whose power system functional vulnerabilities are identified by the equivalent power flow betweenness indices of the nodes and the equivalent power flow betweenness indices of the transmission channels include: The larger the load carried by the node itself, the larger the load that the node supplies to the interconnected nodes, the larger the node's equivalent power flow betweenness index value, and the more important the power supply performance of the node, then the node is a functionally vulnerable node. The greater the active power transmitted through the internal channels of the synchronous grid, the higher the proportion of the power deficit in the total load at the receiving end, the greater the equivalent power flow betweenness index value of the channel, and the more important the power supply performance of the channel, thus the channel is a functionally vulnerable channel. The greater the active power transmitted through the transmission channel between asynchronous power grids, and the greater the proportion of the transmitted power in the total load of the receiving-end system, the greater the equivalent power flow betweenness index of the channel, and the more important the power supply performance of the channel is. In this case, the channel is a functionally vulnerable channel.

2. The method according to claim 1, characterized in that, Based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of a node is determined, including: When a node is disconnected from the power grid, and the power grid experiences a disconnection; The smaller the degree value of a node and the smaller its impact on network connectivity, the more complete the largest connected subgraph in the remaining network is maintained, and the higher the network connectivity, the smaller the equivalent degree value of the node, which means the lower the importance of the node. The higher the degree value of a node and the greater its impact on network connectivity, the smaller the number of nodes in the largest connected subgraph of the remaining network, the higher the equivalent degree value of the node, which represents the higher the importance of the node. Based on the node's own degree and its impact on network connectivity in the power system network, the equivalent degree index of the node is specifically as follows: In the formula, D(node) i Let k be the equivalent degree of node i. i Let N be the degree of node i, and N be the total number of nodes in the initial network. sub Let be the number of nodes in the largest connected subgraph of the remaining network after node i is lost.

3. A system for identifying vulnerable parts of a power system under extreme events, characterized in that, include: The structural vulnerability identification module is used to determine the equivalent degree index of a node based on the node's own degree and its impact on the network connectivity level in the power system network; to determine the connectivity impact index of a channel based on the impact of channel loss on network connectivity; and to identify nodes and transmission channels with structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index. The functional vulnerability identification module is used to determine the equivalent power flow betweenness index of a node based on the load it carries and the load it supplies to interconnected nodes; to determine the equivalent power flow betweenness index of a transmission channel based on the proportion of the transmission power of the channel itself and the power deficit caused by the loss of the channel in the total load of the receiving-end system; and to identify nodes and transmission channels with functional vulnerabilities in the power system based on the equivalent power flow betweenness index of the node and the equivalent power flow betweenness index of the transmission channel. The comprehensive identification module is used to filter nodes and transmission channels that simultaneously exhibit structural and functional vulnerabilities based on the nodes and transmission channels with the structural vulnerabilities and the functional vulnerabilities, and identify them as comprehensive vulnerability points or channels. The remaining nodes or channels that only exhibit vulnerability in a single aspect are the vulnerable nodes or channels in that specific aspect. Based on the impact of channel loss on network connectivity, determine the connectivity impact indicators of the channels, including: When the transmission line is disconnected from the power grid, the interconnectivity of the power grid decreases or even disconnects from the grid. When a channel is disconnected from the power grid, the more complete the largest connected subgraph in the remaining network remains, the smaller the impact of the channel disconnection on the network connectivity, and the smaller the connectivity impact index, which represents the lower the importance of the channel. Conversely, the greater the impact of a disconnected channel on network connectivity, the higher the connectivity impact index, indicating the greater the importance of the channel. Based on the impact of channel loss on network connectivity, the connectivity impact index of the channel is specifically as follows: In the formula, N is the initial total number of network nodes. sub The maximum number of nodes in the remaining connected subgraph of the network after the channel is lost; The nodes and transmission channels that identify structural vulnerabilities in the power system using the node equivalent degree index and the channel connectivity impact index include: The higher the degree value of a node and the greater its impact on network connectivity, the smaller the number of nodes in the largest connected subgraph of the remaining network, the higher the equivalent degree value of the node, and the higher the importance of the node. In this case, the node is a structurally fragile node. The smaller the number of nodes in the largest connected subgraph of the remaining network after a channel is lost, the greater the impact of the channel disconnection on the network connectivity; the larger the connectivity impact index, the higher the importance of the channel, and the channel is a structurally fragile channel. Based on the load supplied by the node itself and the load supplied by the node and interconnected nodes, the equivalent power flow betweenness indices of the node are determined, including: The larger the load carried by the node itself, and the larger the load that the node supplies to the interconnected nodes, the larger the value of the node's equivalent power flow betweenness index. Based on the load carried by the node itself and the load supplied by the node to interconnected nodes, the equivalent power flow betweenness index of the node is specifically as follows: In the formula, J(node) i Let P be the equivalent power flow betweenness of node i. ij Let P be the active power flow of the line between node i and node j, where n is the out-degree of node i, and P is the active power flow of the line between node i and node j. i P represents the load carried by node i. j Let J be the load carried by node j. The equivalent power flow betweenness index of the transmission channel is determined based on the proportion of the channel's own transmission power and the power deficit caused by the loss of the channel in the total load of the receiving-end system, including: The greater the transmission power of the channel itself, the greater the impact of the channel on the power balance of the sending and receiving end systems. The larger the proportion of the power deficit caused by the loss of the channel in the total load of the receiving system, the more severe the impact on the receiving system. The equivalent power flow betweenness index of a channel is determined by the proportion of its own transmission power and the power deficit caused by channel loss in the total load of the receiving-end system. Internal transmission channels of synchronous power grid: Transmission channels between asynchronous power grids: In the formula, RE represents the receiving-end power grid set, and P... i Let n be the active power flow through line i, and n be the number of transmission lines feeding into the receiving-end power grid r (i = 1, 2, ..., n). ΔP j ΔP represents the power transferred through the remaining channels j after the channel feeding into the receiving-end grid r is lost, where m is the number of remaining channels (j = 1, 2, ..., m). jmax P is the power margin for channel j. r Let r be the total load of the receiving-end power grid (r∈RE); Based on the fact that there is no power transfer after the DC channel between asynchronous interconnected power grids is lost, transmission channels are divided into transmission channels within synchronous power grids and transmission channels between asynchronous power grids. The nodes and transmission channels whose power system functional vulnerabilities are identified by the equivalent power flow betweenness indices of the nodes and the equivalent power flow betweenness indices of the transmission channels include: The larger the load carried by the node itself, the larger the load that the node supplies to the interconnected nodes, the larger the node's equivalent power flow betweenness index value, and the more important the power supply performance of the node, then the node is a functionally vulnerable node. The greater the active power transmitted through the internal channels of the synchronous grid, the higher the proportion of the power deficit in the total load at the receiving end, the greater the equivalent power flow betweenness index value of the channel, and the more important the power supply performance of the channel, thus the channel is a functionally vulnerable channel. The greater the active power transmitted through the transmission channel between asynchronous power grids, and the greater the proportion of the transmitted power in the total load of the receiving-end system, the greater the equivalent power flow betweenness index of the channel, and the more important the power supply performance of the channel is. In this case, the channel is a functionally vulnerable channel.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 2.

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