A power distribution network fault recovery capability dynamic evaluation method and system

Abstract

This invention relates to the field of distribution network fault recovery technology, and provides a method and system for dynamic evaluation of distribution network fault recovery capability. The method includes processing fault isolation state data of the target distribution network to obtain an initial effective power supply topology description; constructing a feeder network connectivity subgraph for power supply control path analysis to obtain an initial docking point set; obtaining the topological distance between each initial docking point and the load center and filtering it to obtain a candidate docking point set; performing steady-state power flow simulation of energy storage access operation based on the candidate docking point set and the feeder network connectivity subgraph, and filtering by segmented voltage drop rate and voltage compliance to obtain a feasible location set; and obtaining a target location combination scheme based on the feasible location set, with maximizing downstream critical load coverage as the optimization objective, and performing distribution network operation simulation to obtain the recovery capability evaluation result. This invention can accurately identify feasible energy storage docking locations with connected power supply paths and meeting voltage quality requirements, achieving maximum coverage of the feasible domain for critical load recovery.

Description

Technical Field

[0001] This invention relates to the field of power distribution network fault recovery technology, and in particular to a method and system for dynamic evaluation of power distribution network fault recovery capability. Background Technology

[0002] Distribution network fault recovery capability is a key indicator for assessing whether a distribution network can quickly restore power supply to users and ensure normal social operation after extreme events such as equipment failure and natural disasters. Mobile energy storage is often used as a flexible emergency power source to temporarily connect to a faulty distribution network, providing power restoration support for critical loads or end users, and the choice of its deployment location has a decisive impact on the recovery effect.

[0003] Currently, when using mobile energy storage to support distribution network fault recovery, the selection of mobile energy storage docking points is mainly based on the distance from the load center and the static network structure. It is assumed that the closer the docking point is to the load center, the smaller the line voltage drop and the easier it is to guarantee the voltage quality at the end. However, this mobile energy storage deployment scheme is only reasonable in scenarios where the network topology remains unchanged. It ignores the fact that the actual operating state of the feeder sectionalizing switches (the opening and closing combinations of the sectionalizing switches) directly changes the connectivity of the power supply path during the distribution network fault recovery process. For example, if a feeder fails and the load center is located downstream of the fault point, and the upstream sectionalizing switch is open to isolate the fault area, even if the physical location of the mobile energy storage docking point is very close to the downstream load center, the lack of a continuous path from the power source to the docking point means that the energy storage is essentially operating as an island after being connected, and still cannot supply power to the upstream target load. As a result, what seemed to be the optimal docking location cannot form an effective power supply channel under the real topology, making it impossible to restore a large number of critical loads in the actual fault recovery scenario in a timely manner. Therefore, assessing the fault recovery capability of a distribution network based on the real-time topology conditions after a distribution network fault, while also considering the dynamic coupling relationship between the docking location of mobile energy storage and the accessibility of the actual power supply path, has significant engineering implications. Summary of the Invention

[0004] To address the aforementioned technical issues, this invention provides a method and system for dynamically evaluating the fault recovery capability of distribution networks. By performing coupled correlation analysis on real-time topology changes in distribution network faults and the selection of mobile energy storage locations, it accurately identifies feasible docking locations for mobile energy storage that have connected power supply paths and meet voltage quality requirements. This maximizes the coverage of the feasible domain for critical load recovery, providing effective technical support for the formulation of accurate, reliable, and efficient power supply recovery strategies in distribution network fault scenarios.

[0005] In a first aspect, embodiments of the present invention provide a method for dynamically evaluating the fault recovery capability of a distribution network, the method comprising: The fault isolation status data of the target distribution network is processed to obtain the corresponding initial effective power supply topology description; the initial effective power supply topology description includes a switch and node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers; Based on the initial effective power supply topology description, a feeder network connectivity subgraph is constructed, and power supply control path analysis is performed based on the feeder network connectivity subgraph to obtain the initial docking point set; Obtain the topological distance between each initial stop in the initial stop set and the load center, and filter the stops based on the topological distance to obtain a candidate stop set; Based on the candidate docking point set and the feeder network connectivity subgraph, a steady-state power flow simulation of energy storage access operation is performed. Based on the simulation results, the candidate docking point set is sequentially screened by segmented voltage drop rate and voltage compliance to obtain a feasible location set. Based on the set of feasible locations, a target location combination scheme is obtained with the optimization objective of maximizing the downstream critical load coverage rate. Then, a power distribution network operation simulation is performed based on the target location combination scheme to obtain the recovery capability assessment result.

[0006] Furthermore, the fault isolation status data includes sectional switch opening / closing data, feeder node operation data, and sectional line operation data; The step of processing the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description includes: Each segment switch is sequentially numbered according to its direction from the power source to the end of the feeder. Based on the obtained switch numbers and the switching data of each segment switch, a mapping relationship is established between the switch status value and the corresponding downstream control node set, thus obtaining the switch-node mapping table. Based on the state values ​​of each segment switch in the switch-node mapping table, the connectivity relationship between nodes and the energized state information of the corresponding control line segment are obtained. Based on the connectivity relationships between nodes of all the control line segments, the node connectivity matrix is ​​generated, and based on the energized state information of all the nodes, the energized state identifier set is obtained. The operating data of the feeder nodes and the operating data of the segmented lines are associated and stored based on the node number and the switch-node mapping table to generate the electrical parameter set of the distribution network.

[0007] Furthermore, the step of constructing a connected subgraph of the feeder network based on the initial effective power supply topology description includes: Set the physical installation location of each segment switch in the switch-node mapping table as a control node, and set the opening / closing status attribute for each control node according to the energized status identifier set. The load access points in the target distribution network are identified according to the node connectivity matrix, each load access point is set as a demand node, and the node power consumption attributes are set for each demand node according to the distribution network electrical parameter set. According to the set of energized status identifiers, obtain the line segments with energized status identifiers, set each of the line segments with energized status identifiers as a connection edge, and set the connection attributes for each connection edge according to the set of electrical parameters of the distribution network to generate an initial feeder network subgraph. The validity of the initial feeder network subgraph is verified to obtain the connected subgraph of the feeder network.

[0008] Furthermore, the step of performing power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial docking point set includes: Based on the depth-first search algorithm, starting from the power supply point, all reachable paths between any control node and each demand node in the connected subgraph of the feeder network are traversed to obtain the path redundancy of each control and demand node pair. The path redundancy of each of the control node pairs is compared with a preset redundancy threshold to obtain the control nodes whose path redundancy is greater than the preset redundancy threshold, and a candidate control node set is generated. Based on preset docking point setting conditions, the candidate control points in the candidate control node set are filtered to obtain a potential docking point set; the preset docking point setting conditions include direct connection to the demand node and having mobile energy storage docking space. A switch link closure continuity tracing analysis was performed on each potential stop in the potential stop set to obtain a complete stop set of the link; Calculate the cumulative line impedance between each complete link stop in the complete link stop set and the load center, and sort all the cumulative line impedance values ​​in ascending order to obtain the initial stop set.

[0009] Further, the step of obtaining the topological distance between each initial stop in the initial stop set and the load center, and filtering the stops based on the topological distance to obtain a candidate stop set includes: The feeder network connectivity subgraph is traversed using the search direction from each initial stop point to the load center to obtain the number of segment switches between each initial stop point and the load center. The number of segmented switches between each initial docking point and the load center is used as the corresponding topology distance, and the initial docking points with topology distances less than a preset near-end threshold are obtained to form the candidate docking point set.

[0010] Furthermore, the simulation results include the line operation information from each candidate stop point in the candidate stop point set to the corresponding immediate upstream node, as well as the voltage information at the end of the candidate stop point; the line operation information includes the line impedance and the current flowing through the line; The step of performing segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the obtained simulation results to obtain the feasible location set includes: Based on the operating information of each line, the corresponding voltage drop value is obtained, and based on the voltage drop value and the corresponding segment line length, the segment voltage drop rate of the corresponding candidate stop point is obtained. Based on the segmented pressure drop rate corresponding to each candidate stop and the preset upper limit of the segmented pressure drop rate, the candidate stop set is filtered by segmented pressure drop rate to obtain a pressure drop smooth set. Based on the voltage information at the end of the candidate docking points, the voltage of each docking point with a gradual voltage drop in the voltage drop gradient set is screened to meet the voltage requirements, thereby obtaining a set of feasible locations.

[0011] Further, the step of filtering for voltage compliance among various voltage-gradient docking points in the voltage-gradient set based on the terminal voltage information of the candidate docking points to obtain a feasible location set includes: Based on the terminal voltage information of the candidate docking points, obtain the terminal voltage value of each of the docking points with a gradual voltage drop; Based on the terminal voltage value of each of the voltage drop smoothing docking points and the preset allowable lower voltage limit, voltage compliance screening is performed to obtain a set of voltage compliant docking points; Calculate the voltage margin of each voltage-compliant stop in the voltage-compliant stop set, and sort all the voltage-compliant stops in the voltage-compliant stop set in descending order according to the voltage margin to obtain the feasible location set.

[0012] Furthermore, the downstream critical load coverage rate is the ratio of the weighted sum of the downstream critical loads corresponding to the selected feasible location to the mobile energy storage capacity. The step of obtaining a target location combination scheme based on the feasible location set, with the optimization objective of maximizing the downstream critical load coverage rate, includes: A chromosome population is constructed based on the set of feasible locations, and a fitness function is set based on the downstream critical load coverage. Based on the chromosome population and the fitness function, a genetic algorithm is used for iterative optimization to obtain the target position combination scheme.

[0013] Furthermore, the target location combination scheme includes multiple target docking point locations; The step of performing distribution network operation simulation based on the target location combination scheme to obtain the recovery capability assessment result includes: Based on the target location combination scheme, various typical operating scenarios are simulated for the target distribution network to obtain the location feasible domain extension distribution; the location feasible domain extension distribution includes feasible domain node distribution information corresponding to each target docking point; the feasible domain node distribution information includes the power value and load type of each downstream load under different typical operating scenarios; Based on the location feasible region expansion distribution, calculate the weighted load recovery amount for each of the target docking points; The target docking point whose weighted load recovery amount exceeds the preset recovery amount threshold is obtained as the effective docking point, and the load coverage of all the effective docking points is merged to obtain the load recovery maximum coverage. The power supply path connectivity analysis is performed based on the load restoration maximization coverage and the location feasible domain expansion distribution to obtain the recovery capability assessment result.

[0014] Secondly, embodiments of the present invention provide a dynamic evaluation system for the fault recovery capability of a distribution network, the system comprising: The power grid topology analysis module is used to process the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description; the initial effective power supply topology description includes a switch and node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers; The initial docking point acquisition module is used to construct a feeder network connectivity subgraph based on the initial effective power supply topology description, and perform power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial docking point set. The candidate docking point acquisition module is used to acquire the topological distance between each initial docking point in the initial docking point set and the load center, and to filter the docking points according to the topological distance to obtain a candidate docking point set; The feasible location analysis module is used to perform steady-state power flow simulation of energy storage access operation based on the candidate docking point set and the feeder network connectivity subgraph, and to perform segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the simulation results to obtain the feasible location set. The resilience assessment module is used to obtain target location combination schemes based on the feasible location set, with the optimization objective of maximizing the downstream critical load coverage rate, and to perform distribution network operation simulation based on the target location combination schemes to obtain resilience assessment results.

[0015] This invention provides a method and system for dynamically evaluating the fault recovery capability of a distribution network. The method processes fault isolation state data of a target distribution network, including a switch-node mapping table, a node connectivity matrix, a set of distribution network electrical parameters, and a set of energized status identifiers, to obtain a corresponding initial effective power supply topology description. Based on this description, a feeder network connectivity subgraph is constructed. After analyzing the power supply control path from the feeder network connectivity subgraph to obtain an initial docking point set, the topological distance between each initial docking point and the load center is acquired. Based on this distance, docking points are screened to obtain a candidate docking point set. A steady-state power flow simulation of energy storage access operation is performed based on the candidate docking point set and the feeder network connectivity subgraph. Based on the simulation results, the candidate docking point set is sequentially screened by segmented voltage drop rate and voltage compliance to obtain a feasible location set. Finally, based on the feasible location set, a target location combination scheme is obtained with maximizing downstream critical load coverage as the optimization objective. The method then performs distribution network operation simulation based on the target location combination scheme to obtain the recovery capability evaluation result. Compared with existing technologies, this dynamic evaluation method for distribution network fault recovery capability can perform coupled correlation analysis on real-time topology changes in the distribution network and the selection of mobile energy storage locations. It realizes a closed-loop logic for dynamic evaluation of distribution network recovery capability from topology description, path analysis, simulation verification to combined optimization. It can accurately identify feasible docking locations for mobile energy storage that have connected power supply paths and meet voltage quality requirements under real fault scenarios, and maximize the coverage of the feasible domain for critical load recovery. It is more in line with the needs of actual engineering applications and can improve the power supply recovery effect. It provides effective technical support for dispatchers to quickly formulate accurate, reliable and efficient power supply recovery strategies suitable for distribution network fault scenarios. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the dynamic evaluation method for power distribution network fault recovery capability in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the dynamic evaluation system for power distribution network fault recovery capability in an embodiment of the present invention; The attached figures are labeled as follows: 1. Power grid topology analysis module; 2. Initial docking point acquisition module; 3. Candidate docking point acquisition module; 4. Feasible location analysis module; 5. Recovery capability assessment module. Detailed Implementation

[0017] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Obviously, the embodiments described below are only part of the embodiments of this invention and are used to illustrate the invention, but are not intended to limit the scope of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0018] The dynamic assessment method for distribution network fault recovery capability provided by this invention can be understood as addressing the current application situation where the deployment location of mobile energy storage is determined solely based on physical distance and static network structure in existing distribution network fault recovery capability assessment technologies, ignoring the power supply path failure caused by changes in switch states after a fault, leading to inconsistencies between the assessment results and the actual application effects in fault scenarios. This method proposes an effective power supply topology change analysis based on fault isolation state data of the target distribution network during a fault. It dynamically adjusts the selectable range boundary of docking points according to the effective power supply topology, and combines this with maximizing the coverage requirement of the critical load recovery feasible domain to obtain feasible docking locations that satisfy path connectivity and voltage quality standards. Finally, it obtains the recovery capability assessment result based on distribution network operation simulation. This method is applicable to distribution network fault recovery capability assessment scenarios where fault isolation is achieved through sectionalized switches and mobile power supply access provides external power supply recovery operation modes. The following embodiments will provide a detailed description of the dynamic assessment method for distribution network fault recovery capability of this invention.

[0019] In one embodiment, such as Figure 1 As shown, a dynamic evaluation method for the fault recovery capability of a distribution network is provided, including: S11. Process the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description; where the target distribution network can be understood as the distribution network that needs to be assessed for fault recovery capability in actual applications, and the corresponding fault isolation status data can be understood as the real-time operating status data collected under the fault scenario of the target distribution network, which can be used to accurately reflect the real-time topology changes of the distribution network fault.

[0020] In this preferred embodiment, the fault isolation status data includes sectional switch closing / opening data, feeder node operation data, and sectional line operation data. The sectional switch closing / opening data includes the IDs of all sectional switches within the target distribution network and their corresponding remote signaling status values, which can be obtained through the distribution network SCADA (Supervisory Control and Data Acquisition). A remote signaling status value of 1 indicates that the sectional switch auxiliary contact is closed (corresponding line segment is energized), and a remote signaling status value of 0 indicates that the sectional switch auxiliary contact is open (corresponding line segment is de-energized). The feeder node operation data may include the node ID, three-phase voltage amplitude, power information (active and reactive power), and power supply priority of all feeder nodes obtained from the distribution automation master station. If the node is a load access node, it may also include the corresponding load density value. The corresponding load density value can be calculated by first calculating the total power of the node within a preset power supply radius (e.g., 500 meters) and dividing by... The initial load density value is obtained by calculating the area of ​​the power supply area (based on the preset power supply radius). The initial load density value is then corrected based on the electricity consumption type of the power supply area. For example, if the electricity consumption type is residential electricity, the initial load density value is multiplied by the corresponding residential electricity load factor to obtain the required load density value. The segmented line operation data may include the impedance value and current value of each segmented line in the target distribution network. The impedance value may include the positive sequence impedance parameter and zero sequence impedance parameter obtained through the line ledger database. The current value (effective value of three-phase current) can be obtained through measuring devices such as three-phase current transformers, which will not be described in detail here.

[0021] In this embodiment, the initial effective power supply topology description can be understood as real-time distribution network fault topology information obtained by processing the fault isolation status data of the target distribution network, including segment switch status information. Preferably, it includes a switch-to-node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers. The switch-to-node mapping table represents the mapping relationship between each segment switch in the target distribution network and all downstream nodes it controls. The node connectivity matrix represents the connectivity relationship between all nodes in the target distribution network. The distribution network electrical parameter set represents the set of electrical parameters for all nodes and all segment lines in the target distribution network. Specifically, the step of processing the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description includes: Each section switch is sequentially numbered according to its path from the power source to the feeder end. Based on the obtained switch numbers and the switching status data of each section switch, a mapping relationship is established between the switch status values ​​and the corresponding downstream control node sets, resulting in the switch-node mapping table. This table can be understood as a relational table constructed based on the switching status data of the section switches and the original topology of the target distribution network, containing information such as switch number, switch ID, switch status value, and corresponding downstream control node sets. In practical applications, based on the original topology of the target distribution network, a depth-first or breadth-first traversal is performed along the feeder main line and branches towards the end, starting from the power source (e.g., substation busbar). During the traversal, each section switch is assigned a unique, incremental sequential number according to the order of flow, implicitly indicating the electrical distance. Each switch number is matched with its corresponding switch status value based on its switch ID, and a traversal search is performed based on the original topology to obtain all downstream control nodes corresponding to each section switch. The nodes (all nodes that cannot be reached from the power source via other paths after the sectionalizing switch is disconnected) are used to obtain the corresponding downstream control node set. Based on the obtained switch number, switch ID, switch status value, and downstream control node set, a mapping table can be constructed with the switch number as the primary key, the switch ID as the foreign key, and the switch status value and the downstream control node set as the values. It should be noted that since the target distribution network is usually in a radial operation mode, the disconnection of a sectionalizing switch will only isolate its downstream network and will not form a ring network. That is, the downstream control node set corresponding to each sectionalizing switch is usually unique and definite.

[0022] Based on the state values ​​of each segmented switch in the switch-node mapping table, the connectivity between nodes and the energized state information of the corresponding control line segment are obtained. In the radial operation network, the connectivity between nodes usually depends on whether all switches on the connection path between two nodes are closed. That is, for a closed segmented switch, it means that its upstream and downstream nodes are electrically connected. Based on this, the connectivity between nodes of the control line segment can be obtained by traversing the switch-node mapping table and based on the state values ​​of the segmented switches: if the switch state value is 1 (closed), the upstream and downstream nodes of the switch are merged into the same connected component; if the switch state is 0 (open), they are not merged. Finally, nodes belonging to the same connected component are considered to have a connectivity relationship.

[0023] The energized state information of a node can be understood as follows: The node is energized only if all switches along the path from the power source are closed after fault isolation. In practical applications, the switch-node mapping table is traversed, propagating downstream from the power source. For a given sectionalizing switch, if its upstream node (or power source) is energized and the switch state is 1 (closed), then all nodes in the downstream node set controlled by that sectionalizing switch can be marked as "energized." Conversely, if the sectionalizing switch is open, then all nodes in the downstream node set controlled by that sectionalizing switch can be marked as "de-energized." Similarly, if a segmented line between two nodes is considered as a single node, its energized state can be obtained by referring to the above node energized state information. Alternatively, the energized state of the corresponding line segment can be determined based on the energized states of adjacent nodes for subsequent analysis.

[0024] Based on the connectivity relationships between nodes of all the control line segments, a node connectivity matrix is ​​generated, and based on the energized state information of all the nodes, an energized state identifier set is obtained. Each element of the node connectivity matrix can be directly determined based on the connectivity relationships between nodes of the corresponding control line segment. For example, if two nodes are connected, their corresponding matrix element is 1; otherwise, it is 0. Further details are omitted here. Simultaneously, by summarizing the energized states of each node and their corresponding node IDs obtained above, the required energized state identifier set can be obtained.

[0025] The operating data of the feeder nodes and the operating data of the segmented lines are associated and stored based on the node number and the switch-node mapping table to generate the electrical parameter set of the distribution network. The electrical parameter set includes node electrical parameters and line electrical parameters. In practical applications, since the operating data of the feeder nodes includes node IDs and corresponding voltage amplitudes, power information, power supply priority, and load density values, the node ID can be directly used as the key, and the remaining information can be filled into the corresponding node record. Simultaneously, since each segmented line in the operating data corresponds to two nodes, the first node ID and the last node ID corresponding to each segmented line can be found through the line ledger database. Then, the segmented line ID is used as the primary key, and the corresponding first node ID and last node ID are used as foreign keys, with impedance and current values ​​as values. Alternatively, the operating data of the segmented line can be directly stored by attaching it to the power supply side node of that segmented line; no specific limitation is made here. The electrical parameter set of the distribution network obtained here can provide reliable electrical data support for subsequent feeder network connectivity subgraphs and distribution network operation simulation.

[0026] This embodiment is based on a structured processing mechanism for fault isolation state data of the target distribution network. It effectively captures the topology state changes under distribution network fault scenarios and generates a comprehensive and effective power supply topology description including network topology skeleton and electrical information. This provides an accurate and reliable data analysis foundation for subsequent power supply control path analysis, steady-state power flow simulation and distribution network operation simulation.

[0027] S12. Based on the initial effective power supply topology description, construct a feeder network connectivity subgraph, and perform power supply control path analysis based on the feeder network connectivity subgraph to obtain an initial docking point set. The feeder network connectivity subgraph can be understood as a standardized and structured abstract mapping of the actual target distribution network topology based on the initial effective power supply topology description. That is, while replicating the core topological features and operating status of the actual target distribution network, it simplifies redundant physical structures and strengthens the electrical attributes required for analysis to adapt to the needs of subsequent power supply control path analysis. It is a simplified topology with sectional switch positions as control nodes, load access points as demand nodes, and line segments with switch status indicators as connecting edges. It is not a completely new topology independent of the actual target distribution network topology.

[0028] Specifically, the step of constructing a feeder network connectivity subgraph based on the initial effective power supply topology description includes: The physical installation location of each segment switch in the switch-node mapping table is set as a control node, and the on / off state attribute is set for each control node according to the energized state identifier set; that is, each segment switch in the switch-node mapping table is mapped as a controllable unit in the feeder network connectivity subgraph, and the corresponding switch number in the switch-node mapping table is used as the unique identifier of the control node, and the node attribute of the control node is set based on its corresponding switch state value. If the switch state value is closed, the control node is set to the conducting state (allowing power flow to pass through), otherwise it is set to the open state.

[0029] The load access points in the target distribution network are identified based on the node connectivity matrix. Each load access point is designated as a demand node, and its power consumption attributes are set according to the distribution network electrical parameter set. A load access point can be understood as a node in the physical power grid that consumes electrical energy. In practical applications, all connected components in the current distribution network can be identified based on the node connectivity matrix, and all node IDs within each connected component can be obtained. Then, based on each node ID, the corresponding node type is obtained by searching the line ledger database to determine all load access points in the target distribution network. After mapping the load access points in the physical network to demand nodes in the feeder network connectivity subgraph, the relevant node electrical parameters in the distribution network electrical parameter set can be searched to set the corresponding node power consumption attributes, such as load power demand values ​​and power supply priority, etc., which are not specifically limited here.

[0030] Based on the set of energized status identifiers, obtain the line segments with energized status identifiers, set each of the energized status identifier line segments as a connection edge, and set the connection attributes for each connection edge according to the set of distribution network electrical parameters to generate an initial feeder network subgraph. The energized status identifier line segments can be obtained based on the node energized status information in the set of energized status identifiers, combined with the correspondence between line segments and nodes: if both the first and last nodes of a line segment have an "energized" or "non-energized" identifier, then the line segment is mapped as a connection edge of the feeder network connected subgraph. In this way, connection edges between different node pairs obtained by combining power supply points, control nodes, and demand nodes can be obtained. Based on the status identifier of the energized status identifier line segment (if both the first and last nodes have an "energized" identifier, the corresponding status identifier is 1; otherwise, the corresponding status identifier is 0) and the electrical parameters corresponding to the energized status identifier line segment in the set of distribution network electrical parameters, set the connection attributes for each connection edge. For example, the connection attributes may include the status identifier of the energized status identifier line segment, line impedance, and line flow rate, etc., which are not specifically limited here.

[0031] The initial feeder network subgraph is validated to obtain the connected subgraph of the feeder network. The validation can be understood as a step to verify whether the initial feeder network subgraph can ensure the accuracy and reliability of subsequent power supply control path analysis, steady-state power flow simulation of energy storage access operation, and distribution network operation simulation. It may include connectivity and attribute integrity verification. Connectivity is used to ensure that the topology meets the requirements of radial operation, there are no electrical loops, and there are no isolated points or islands that cannot be powered by the power source. Attribute integrity verification is used to ensure that each node and connection edge has the necessary electrical parameters. In practical applications, connectivity verification can start from the power source point and use a depth-first search (DFS) or breadth-first search (BFS) algorithm to traverse the initial feeder network subgraph, recording all visited nodes to generate a reachable node set. This reachable node set is then compared with the total node set of the initial feeder network subgraph. If isolated points or islands exist, they are removed from the initial feeder network subgraph to preserve the largest connected component. Next, each connected component is checked for a radial structure. This can be done directly based on the number of nodes and edges within the connected component; if the number of edges is greater than or equal to the number of nodes, a loop is considered possible. Alternatively, the initial feeder network subgraph can be traversed, and if a visited node is encountered during the traversal, a loop is considered to exist. For detected loops, the permission is determined according to the distribution network operation rules. If not permitted, the loop can be broken by disconnecting an edge, depending on the application requirements. Attribute integrity verification can be understood as checking the comprehensiveness and validity of node attributes. Missing values ​​are filled in and outliers are corrected according to the application requirements; this will not be detailed here.

[0032] By using the above methods and steps to model based on graph theory, the static switching and load equipment is decoupled and recombined with the dynamic electrical state. The physical topology of the target distribution network is mapped into a feeder network connected subgraph containing complete electrical attributes and satisfying connectivity constraints, providing a data foundation with a clear structure and direct traversal for subsequent analysis and applications.

[0033] In this embodiment, the power supply control path analysis can be understood as a process of determining the initial stop point selection range based on the path redundancy analysis of the power supply path corresponding to each control node pair (control node and demand node) in the feeder network connectivity subgraph, combined with the stop point setting conditions and power supply path continuity analysis; specifically, the step of performing power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial stop point set includes: Based on the depth-first search algorithm, starting from the power supply point, all reachable paths between any control node and each demand node in the feeder network connectivity subgraph are traversed to obtain the path redundancy of each control-demand node pair. Path redundancy can be understood as the number of independent paths (without common intermediate nodes except for the start and end points) between control-demand node pairs. In practical applications, the depth-first search algorithm can be used to traverse the feeder network connectivity subgraph to obtain all reachable paths between control-demand node pairs. Then, the independence of the reachable paths can be determined by performing an intersection operation on the path node set of each reachable path, thus obtaining the required path redundancy.

[0034] The path redundancy of each control node pair is compared with a preset redundancy threshold to obtain control nodes whose path redundancy is greater than the preset redundancy threshold, thus generating a candidate control node set. The preset redundancy threshold can be set based on the power supply reliability requirements of the actual application and is not specifically limited here. In actual applications, if the path redundancy of the control node pair is higher, the power supply reliability of the control node is considered to be higher, and it is more suitable as an access point for mobile energy storage.

[0035] Based on preset docking point setting conditions, candidate control points in the candidate control node set are screened to obtain a potential docking point set. These preset docking point setting conditions can be understood as the hard physical conditions required for connecting mobile energy storage in practical applications. These conditions may include direct connection to the demand node and availability of mobile energy storage docking space. Direct connection to the demand node can be verified by checking whether the control node has a standard grid connection interface. Adequate availability of mobile energy storage docking space may include a road width not less than a preset width to ensure vehicle passage, a distance of the docking point from the power distribution equipment not exceeding a preset distance to reduce temporary cable length, ground bearing capacity meeting the parking requirements of mobile energy storage vehicles of corresponding weight, and no high-voltage lines crossing the area to avoid safety hazards. Based on these preset docking point setting conditions, the candidate control points in the candidate control node set are screened to obtain a set of docking points that simultaneously meet path redundancy requirements and physical access point conditions.

[0036] A switch link closure continuity tracing analysis is performed on each potential stop in the potential stop set to obtain a complete set of stop points. This analysis can be understood as tracing upstream segment switches along the feeder towards the power source for each potential stop in the set, reading the switch status values ​​of each segment switch along the tracing path, and identifying all potential stops with complete power supply links. During the actual tracing process, if a switch status of 0 is encountered, the tracing is terminated and the potential stop is removed. If all switch statuses are 1 during the tracing to the power source, the potential stop is considered to have a complete power supply link and is retained. Finally, all retained potential stops are summarized to obtain the required complete set of stop points.

[0037] The cumulative line impedance between each complete link stop in the complete link stop set and the load center is calculated, and all the cumulative line impedance values ​​are sorted in ascending order to obtain the initial stop set. The load center can be understood as the concentrated area of ​​electricity load in the target distribution network area. In practical applications, it can be determined based on existing technologies such as the equivalent load moment method, cluster analysis method, and impedance-based electrical distance method, which will not be detailed here. In this embodiment, the cumulative line impedance between each complete link stop and the load center can be obtained by traversing the connected subgraph of the feeder network and superimposing the line impedances of all segmented lines on the path between the complete link stop and the load center. This is equal to the vector sum of the line impedances of each segmented line on the path from the complete link stop to the load center. The smaller the cumulative line impedance value, the closer the electrical distance, the smaller the line voltage drop, and the higher the power transmission efficiency. By sorting the complete link stop points in the complete link stop set in ascending order according to their corresponding cumulative line impedance values, an initial stop set with clear priorities can be formed, providing reliable basic data support for subsequent optimization selection.

[0038] This embodiment not only uses depth-first search to traverse the connected subgraph of the feeder network and filters out control nodes with multi-path power supply capabilities based on power path redundancy analysis, thus ensuring high power supply reliability after the mobile energy storage is connected, but also further filters potential docking points by combining physical access conditions and switch link closure continuity tracing analysis, ensuring the actual deployability of mobile energy storage and avoiding power supply failure due to link interruption. It also prioritizes electrical distance based on the cumulative line impedance values ​​between docking points and load centers, providing a guarantee for reducing line losses and improving power quality when using docking points. It should be noted that the determination of the initial docking point set can also consider actual operational constraints such as the matching degree between the rated capacity of the mobile energy storage and the downstream load demand of the docking point, the coordination relationship between the maximum output power of the energy storage and the line current carrying capacity, and the switching time cost between different docking points, further providing a quantitative basis for rapid recovery decisions after target distribution network failures.

[0039] S13. Obtain the topological distance between each initial stop point in the initial stop point set and the load center, and filter the stops based on the topological distance to obtain a candidate stop point set; wherein, the candidate stop point set can be understood as a near-end stop point subset formed by filtering the initial stops based on the consideration that the closer the stop point is to the load center, the smaller the line voltage drop and the easier it is to ensure the voltage quality at the end.

[0040] Specifically, the step of obtaining the topological distance between each initial stop in the initial stop set and the load center, and filtering the stops based on the topological distance to obtain a candidate stop set includes: The feeder network connected subgraph is traversed in the search direction from each initial stop point to the load center to obtain the number of segment switches between each initial stop point and the load center. The traversal of the number of segment switches between each initial stop point and the load center can still be implemented using the aforementioned depth-first search algorithm or breadth-first search algorithm, which will not be described in detail here.

[0041] The number of sectional switches between each initial docking point and the load center is used as the corresponding topology distance, and the initial docking points with topology distances less than a preset proximity threshold are obtained to form the candidate docking point set. The topology distance is used to quantify the electrical proximity between the initial docking point and the load center. The corresponding preset proximity threshold can be set based on actual application requirements to retain docking points that are closer to the load center. No specific limitation is made here.

[0042] This embodiment not only uses the number of segmented switches to replace complex line impedance calculations, intuitively reflecting the topological connection relationship and reducing computational complexity, but also effectively shortens the power supply path length by prioritizing the selection of docking points closer to the load center, reducing voltage drop and power loss caused by line impedance, reducing the risk of power outages, ensuring the power supply efficiency, power quality, and emergency power supply stability of mobile energy storage, and forming a smaller set of candidate docking points, providing a simplified search space for subsequent refined evaluation or optimization decisions, and improving overall decision-making efficiency.

[0043] S14. Perform steady-state power flow simulation for energy storage access operation based on the candidate docking point set and the feeder network connectivity subgraph. Based on the simulation results, sequentially perform segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set to obtain a feasible location set. The steady-state power flow simulation process for energy storage access operation may include: constructing a simulation model (including power source points, lines, control nodes, and demand nodes) using power system simulation software based on the candidate docking point set and the feeder network connectivity subgraph; adding a mobile energy storage unit as a distributed power source for each candidate docking point to simulate mobile energy storage access at that point; then performing steady-state power flow calculations to obtain simulation results such as current and node voltage on each line. It should be noted that line impedance can be obtained from network parameters, while the current flowing through the line needs to be obtained through power flow calculations. In actual simulations, parameters such as the rated capacity and power factor of the accessed energy storage can be set based on actual application requirements. Furthermore, the detailed implementation process of the above steady-state power flow simulation can be referenced from relevant existing power flow simulation technologies, and will not be detailed here.

[0044] To facilitate segmented voltage drop and voltage compliance screening of each candidate docking point, and further improve the reliability and effectiveness of docking point determination, this embodiment preferably sets the simulation results to include line operation information from each candidate docking point in the candidate docking point set to its corresponding immediate upstream node, and voltage information at the end of the candidate docking point; the line operation information includes line impedance and line current; specifically, the step of performing segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the obtained simulation results to obtain a feasible location set includes: Based on the operational information of each line, the corresponding voltage drop value is obtained, and based on the voltage drop value and the corresponding segmented line length, the segmented voltage drop rate of the corresponding candidate docking point is obtained. The voltage drop value (the voltage difference between the candidate docking point and the adjacent upstream node) can be directly obtained based on the corresponding line impedance and the current flowing through the line, using existing voltage drop calculation formulas, which will not be detailed here. The segmented voltage drop rate is used to characterize the degree of voltage loss per unit length of line. Its calculation involves Ohm's law and the principle of power transmission, and can be expressed as the voltage drop value divided by the corresponding segmented line length. In practical applications, if the segmented voltage drop rate is too large, the voltage quality at the end after the mobile energy storage is connected will be difficult to guarantee.

[0045] Based on the segmented voltage drop rate and the preset upper limit of the segmented voltage drop rate corresponding to each candidate docking point, the candidate docking point set is screened by segmented voltage drop rate to obtain a voltage drop smoothing set; wherein, the preset upper limit of the segmented voltage drop rate can be determined based on the distribution network operation procedures; the corresponding segmented voltage drop rate screening can be understood as obtaining candidate docking points with segmented voltage drop rates lower than the preset upper limit of the segmented voltage drop rate, generating a set of docking points that can ensure the voltage quality at the end after the mobile energy storage is connected, that is, obtaining the required voltage drop smoothing set.

[0046] Based on the terminal voltage information of the candidate docking points, voltage compliance screening is performed on each docking point in the voltage drop smoothing set to obtain a feasible location set. The feasible location set can be understood as a collection of candidate docking points that simultaneously meet both the segmented voltage drop rate and voltage quality standards, providing a smaller and higher-quality range of docking points for subsequent analysis. Specifically, the step of performing voltage compliance screening on each docking point in the voltage drop smoothing set based on the terminal voltage information of the candidate docking points to obtain a feasible location set includes: Based on the terminal voltage information of the candidate docking points, the terminal voltage value of each of the docking points with a gradual voltage drop is obtained; that is, the terminal voltage value of each docking point with a gradual voltage drop is extracted from the terminal voltage information of the candidate docking points.

[0047] Voltage compliance screening is performed based on the terminal voltage value of each voltage drop smoothing stop point and the preset allowable lower voltage limit to obtain a set of voltage-compliant stops. The preset allowable lower voltage limit can also be determined based on the distribution network operation regulations. In practical applications, the terminal voltage value of each voltage drop smoothing stop point is compared with the preset allowable lower voltage limit. If the terminal voltage value is lower than the preset allowable lower voltage limit, it is considered unqualified and cannot guarantee power supply quality, and needs to be removed. Finally, the required set of voltage-compliant stops is obtained by summing all voltage drop smoothing stops that meet the voltage quality requirements.

[0048] Calculate the voltage margin of each voltage-compliant docking point in the voltage compliance docking point set, and sort all the voltage-compliant docking points in the voltage compliance docking point set in descending order according to the voltage margin to obtain the feasible location set; wherein, the voltage margin of each voltage-compliant docking point can be understood as the difference between the corresponding end voltage value and the preset allowable lower voltage limit value. The larger the value, the more guaranteed the end voltage value is after the energy storage is connected; sort the voltage-compliant docking points in the voltage compliance docking point set from largest to smallest according to the corresponding voltage margin to form a feasible location set in which both segmented voltage drop rate and voltage meet the standards.

[0049] This embodiment generates a feasible location set by using line operation information and terminal voltage data obtained from steady-state power flow simulation of energy storage access to perform segmented screening of candidate docking points based on both voltage drop rate and voltage quality. This not only filters out docking points with gentle voltage drops, which helps reduce line losses and improve terminal voltage levels after energy storage access, thus avoiding terminal voltage collapse due to excessive line impedance, but also ensures that the docking points have good line electrical characteristics and meet steady-state voltage qualification requirements. This enhances the adaptability and robustness of mobile energy storage access and ensures the engineering feasibility of distribution network recovery capability assessment.

[0050] S15. Based on the set of feasible locations, a target location combination scheme is obtained with the optimization objective of maximizing the downstream critical load coverage rate. A distribution network operation simulation is then performed based on the target location combination scheme to obtain the recovery capability assessment result. The downstream critical load coverage rate is the ratio of the weighted power of the downstream critical loads corresponding to the selected feasible locations to the capacity of the mobile energy storage. The weighted power of the downstream critical loads corresponding to the selected feasible locations can be understood as the sum of the weighted power values ​​of all downstream critical loads corresponding to all feasible locations selected during the iterative optimization process. The mobile energy storage capacity can be understood as the sum of the capacities of mobile energy storage with the same number of selected feasible locations. It should be noted that, for the sake of simplifying the analysis, this embodiment preferably uses mobile energy storage with the same capacity for recovery capability assessment.

[0051] In this embodiment, the target location combination scheme can be understood as selecting which feasible locations in the feasible location set to deploy mobile energy storage; specifically, the step of obtaining the target location combination scheme based on the feasible location set and maximizing the downstream critical load coverage rate as the optimization objective includes: A chromosome population is constructed based on the feasible location set, and a fitness function is set based on the downstream critical load coverage rate. The construction process of the chromosome population includes: chromosomes are encoded in binary, and the length of each chromosome is equal to the total number of feasible locations in the feasible location set; each gene bit of each chromosome is set to a value of 1 to indicate that mobile energy storage is deployed at the feasible location, and 0 indicates that it is not deployed; the chromosome population is randomly generated according to the preset population size, and the values ​​of each gene bit in the binary string of each chromosome in the chromosome population are generated randomly with equal probability to ensure the diversity of the initial solution.

[0052] The fitness function is used to evaluate the quality of each chromosome. In this embodiment, it is defined as the downstream critical load coverage rate, which is the ratio of the total critical load power that can be restored at the selected location to the total deployed energy storage capacity. The specific calculation steps in practical applications include: extracting the location indices of all gene positions with a value of 1 in each chromosome in the chromosome population to obtain the corresponding deployment point set; based on the topology of the connected subgraph of the feeder network, obtaining the downstream critical load set corresponding to each deployment point in the deployment point set, and, on the premise of avoiding duplicate calculations, weighting and summing the different critical loads in the downstream critical load set according to their corresponding power and the weight determined based on the load type to obtain the corresponding downstream critical load weighted power value; then summing the downstream critical load weighted power values ​​of all deployment points to obtain the total downstream critical load weighted power corresponding to the deployment point set; obtaining the required mobile energy storage capacity based on the total number of deployment points in the deployment point set and the rated power of a single mobile energy storage unit; and comparing the obtained total downstream critical load weighted power with the mobile energy storage capacity to obtain the corresponding fitness value. The larger the value, the more load is restored per unit of energy storage capacity, and the better the scheme. It should be noted that the weights determined based on load type must adhere to the basic principles of safe and stable operation of the power system. For example, primary loads include hospital emergency rooms, important communication hubs, and subway traction power supply, where power outages would cause personal injury or significant economic losses, and their weight can be set to 1.0 to indicate that they must be restored first. Secondary loads include large shopping malls, important office buildings, and residential areas, where short-term power outages would have a significant impact but would not endanger lives, and their weight can be set to 0.6. Tertiary loads are mainly general industrial and commercial users who can withstand a certain period of power outages, and their weight is set to 0.3, so that the weighted total power of downstream critical loads can comprehensively reflect the social benefits of the restoration plan.

[0053] Based on the chromosome population and the fitness function, a genetic algorithm is used for iterative optimization to obtain the target position combination scheme. The iterative optimization process using the genetic algorithm includes: employing a roulette wheel selection method to allocate selection probabilities based on fitness values; calculating the sum of the fitness of all chromosomes in the current population, where the probability of each chromosome being selected is proportional to its fitness, with individuals with higher fitness having a greater chance of entering the next generation; to protect the optimal solution from being destroyed, individuals with the highest fitness in each generation are retained at a predetermined proportion (e.g., 10%) and directly copied to the next generation, without participating in subsequent crossover and mutation; for the remaining individuals not retained in each generation, a roulette wheel is used to select parent pairs, and a single-point crossover operation is performed by randomly generating a crossover point, exchanging the gene segments of the two parent chromosomes after that point, and generating two offspring individuals. If no crossover occurs, the parent generation is directly copied. For each offspring obtained after crossover, each gene locus is flipped (i.e., 0 becomes 1, 1 becomes 0) with a preset probability (e.g., 0.01) to perform mutation operations, thereby increasing population diversity and preventing premature convergence of the algorithm. After each round of iteration optimization, it is determined whether the change in the optimal fitness value meets the convergence condition (e.g., the change in the optimal fitness value is less than 0.001 for 50 consecutive generations) or has reached the preset maximum number of iterations. If either condition is met, the iteration optimization is terminated, and the chromosomes corresponding to the optimal fitness values ​​of each generation are used as the desired target position combination scheme. Otherwise, the optimal fitness value and chromosome in the chromosome population corresponding to each round of iteration are recorded, and a new generation population is generated based on elite retention, selection, crossover, and mutation. The above process is repeated until the termination condition is met to obtain the target position combination scheme.

[0054] In this embodiment, a fitness function is constructed using the downstream critical load coverage rate index, and a genetic algorithm is used to optimize and select mobile energy storage deployment points from feasible locations. This not only ensures that limited mobile energy storage resources are invested in the most efficient control nodes, maximizing the unit capacity of restored load and improving the economy and effectiveness of emergency power supply, but also ensures the efficiency and reliability of the target location combination scheme.

[0055] The target location combination scheme obtained through the above methods and steps may include multiple target docking point locations, that is, to realize multi-point access of mobile energy storage to improve power supply recovery capability and recovery speed; based on the obtained target location combination scheme, the load recovery coverage and power supply path connectivity after the mobile energy storage is accessed are verified to maximize the coverage and obtain the recovery capability assessment result corresponding to the target location combination scheme; specifically, the step of performing distribution network operation simulation according to the target location combination scheme to obtain the recovery capability assessment result includes: Based on the target location combination scheme, various typical operation scenarios are simulated for the target distribution network to obtain the location feasible domain extension distribution. Among them, the simulation of various typical operation scenarios can be understood as the operation simulation of typical fault isolation scenarios that may occur after the target distribution network is connected to mobile energy storage, based on the target location combination scheme. These scenarios include simulating permanent faults in different sections of different feeders in the target distribution network, and automatic tripping of upstream and downstream sectional switches to isolate the fault area. Each scenario corresponds to a state combination of sectional switches, which can be determined based on the historical operation data and fault statistical analysis of the target distribution network. The specific typical fault isolation scenario settings vary depending on the actual topology of the target distribution network and are not specifically limited here. In practical applications, when simulating various typical operating scenarios of a target distribution network based on target location combination schemes, it is necessary to use the original topological connection relationship of the target distribution network corresponding to the initial effective power supply topology description for simulation. Under each scenario simulation, starting from each target stop point in the target location combination scheme, a depth-first search algorithm is used to traverse and search the set of reachable nodes corresponding to each target stop point. Finally, the set of reachable nodes of the same target stop point in all scenarios is merged to form the union of its corresponding location feasible regions. Then, the union of the location feasible regions of all target stops is summarized to obtain the required location feasible region extended distribution. That is, the location feasible region extended distribution includes the feasible region node distribution information corresponding to each target stop point, and the feasible region node distribution information includes the power value and load type of each downstream load under different typical operating scenarios, reflecting the scenario association relationship between each target stop point and each load node. It should be noted that the simulation model construction and operation settings involved in the simulation of various typical operating scenarios in this embodiment can be implemented with reference to existing distribution network simulation operation technology, which will not be detailed here.

[0056] Based on the feasible domain expansion distribution of the location, the weighted load recovery amount of each of the target docking points is calculated respectively. The weighted load recovery amount can be understood as the weighted average of the load recovery amount of the target docking point under different typical operating scenarios, so as to reflect the average efficiency of the target docking point in long-term operation or in response to unknown faults. The calculation of the load recovery amount under each typical operating scenario can be based on the power value and load type of all downstream loads in the corresponding feasible domain node distribution information, referring to the calculation method of the weighted power value of the downstream critical load corresponding to the feasible location, which will not be repeated here. It should be noted that the weight value of the load recovery amount of the same target docking point under different typical operating scenarios can be determined based on the historical fault occurrence probability of the corresponding typical operating scenario (obtained by statistical analysis based on the fault operation and maintenance ledger of the target distribution network), which will not be detailed here.

[0057] The target docking point whose weighted load recovery exceeds a preset recovery threshold is obtained as an effective docking point, and the load coverage of all effective docking points is merged to obtain the maximum load recovery coverage. The preset recovery threshold can be determined based on actual application requirements and is not specifically limited here. The load coverage of the effective docking point is the set of all downstream load nodes corresponding to the location feasible domain extension distribution, and the corresponding maximum load recovery coverage can be understood as the total set of load nodes that can be covered by mobile energy storage throughout the entire network.

[0058] Based on the maximum load recovery coverage and the location feasible domain expansion distribution, a power supply path connectivity analysis is performed to obtain the recovery capability assessment result; wherein, the power supply path connectivity analysis can be understood as the process of analyzing the recovery status of each load node in the maximum load recovery coverage under all typical operating scenarios through access to mobile energy storage at the target docking point.

[0059] In practical applications, for each load node within the maximum load restoration coverage area, the feasible location domain is traversed, and the number of effective docking points and typical operating scenario combinations reachable from effective docking points under different typical operating scenarios is counted. Then, the product of the number of effective docking points and the number of typical operating scenarios is calculated to obtain the maximum total number of load nodes that can be reached. Based on the ratio of the total number of effective docking point and typical operating scenario combinations corresponding to each load node to the maximum total number of load nodes that can be reached, the power supply path reliability of the load node is obtained, i.e., the comprehensive probability of load node restoration. After obtaining the power supply path reliability of each load node within the maximum load restoration coverage area, the recovery capability assessment result can be obtained through the following steps: 1) Normalize the power supply path reliability of each load node to obtain normalized reliability. Based on the reliability requirements of the power system or the reliability level threshold set in advance by engineering experience, classify each load node into different reliability levels. For example, load nodes with normalized reliability greater than or equal to 0.9 are classified as high reliability nodes, load nodes with normalized reliability greater than or equal to 0.6 and less than 0.9 are classified as medium reliability nodes, and load nodes with normalized reliability less than 0.6 are classified as low reliability nodes. After obtaining the reliability level of each load node, the percentage of nodes that meet the reliability standard and the corresponding load percentage can be obtained based on the preset reliability standard. 2) Calculate the number of load nodes for different reliability levels and the percentage of load nodes corresponding to each reliability level; calculate the total load power for different reliability levels and the percentage of total load power corresponding to each reliability level. You can also calculate the power percentage of high-reliability nodes in different reliability levels based on load type. It should be noted that the total load power for different reliability levels can be the sum of the actual power of the load nodes or the weighted sum of the actual power based on the load type. There is no specific limitation here. 3) Calculate the arithmetic mean of reliability based on the normalized reliability of each load node within the maximum coverage area of ​​load recovery, and calculate the standard deviation or coefficient of variation of reliability; use the power of each load node as the weight to calculate the load weighted average reliability by weighting the normalized reliability. 4) Identify the load node with the lowest normalized reliability within the maximum load recovery coverage area, and provide its corresponding location, load type, and reliability value; By summarizing the indicators determined through the above analysis process, the required recovery capability assessment results can be obtained. This not only intuitively reflects the reliability distribution of all load nodes within the maximum coverage of load recovery, the load volume that can be guaranteed under different reliability levels, and the degree of guarantee for critical loads, but also reflects the average level of overall recovery capability, the degree of guarantee for the recovery of important large loads, the degree of satisfaction of basic reliability requirements, and weak nodes in recovery. This provides clear quantitative basis for relevant dispatchers to quickly formulate recovery strategies in emergency situations, and also provides reliable data support for subsequent distribution network planning, energy storage dispatch, and emergency drills.

[0060] This invention provides a method for processing fault isolation state data of a target distribution network, including a switch-node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a live status identifier set, to obtain a corresponding initial effective power supply topology description. Based on this initial effective power supply topology description, a feeder network connectivity subgraph is constructed. After obtaining an initial docking point set through power supply control path analysis based on the feeder network connectivity subgraph, the topological distance between each initial docking point in the initial docking point set and the load center is obtained. Based on the topological distance, docking points are screened to obtain a candidate docking point set. Then, steady-state power flow simulation of energy storage access operation is performed based on the candidate docking point set and the feeder network connectivity subgraph. Based on the simulation results, the candidate docking point set is sequentially screened by segmented voltage drop rate and voltage compliance to obtain a feasible location set. Finally, based on the feasible location set... This technical solution, which aims to maximize downstream critical load coverage, obtains target location combinations and then simulates distribution network operation based on these combinations to assess recovery capabilities. It is a closed-loop logic for dynamic evaluation of distribution network recovery capabilities, established through coupled correlation analysis of real-time topology changes in the distribution network and the selection of mobile energy storage locations. This logic encompasses topology description, path analysis, simulation verification, and combination optimization. It accurately identifies feasible docking locations for mobile energy storage that maintain power supply path connectivity and meet voltage quality requirements in real-world fault scenarios, maximizing coverage of the feasible domain for critical load recovery. This approach better aligns with practical engineering applications and improves power restoration effectiveness, providing effective technical support for dispatchers to quickly develop precise, reliable, and efficient power restoration strategies suitable for distribution network fault scenarios.

[0061] It should be noted that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders.

[0062] In one embodiment, such as Figure 2 As shown, a dynamic evaluation system for the fault recovery capability of a distribution network is provided, the system comprising: The power grid topology analysis module 1 is used to process the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description; the initial effective power supply topology description includes a switch and node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers; The initial docking point acquisition module 2 is used to construct a feeder network connectivity subgraph based on the initial effective power supply topology description, and perform power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial docking point set; The candidate docking point acquisition module 3 is used to acquire the topological distance between each initial docking point in the initial docking point set and the load center, and to filter the docking points according to the topological distance to obtain a candidate docking point set. The feasible location analysis module 4 is used to perform steady-state power flow simulation of energy storage access operation based on the candidate docking point set and the feeder network connectivity subgraph, and to perform segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the simulation results to obtain the feasible location set. The resilience assessment module 5 is used to obtain a target location combination scheme based on the feasible location set, with the optimization objective of maximizing the downstream critical load coverage rate, and to perform distribution network operation simulation based on the target location combination scheme to obtain the resilience assessment result.

[0063] Specific limitations regarding the dynamic assessment system for distribution network fault recovery capability can be found in the limitations of the dynamic assessment method for distribution network fault recovery capability described above; the corresponding technical effects are equivalent and will not be repeated here. Each module in the aforementioned dynamic assessment system for distribution network fault recovery capability can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0064] In summary, the dynamic evaluation method and system for distribution network fault recovery capability provided by this invention, based on the coupled correlation analysis of real-time topology changes in the distribution network fault and the selection of mobile energy storage locations, establishes a closed-loop logic for dynamic evaluation of distribution network recovery capability from topology description, path analysis, simulation verification to combined optimization. This logic can accurately identify feasible docking locations for mobile energy storage that are connected to the power supply path and meet voltage quality requirements under real fault scenarios, maximizing the coverage of the feasible domain for critical load recovery. This approach better meets the needs of actual engineering applications and improves the power supply recovery effect, providing effective technical support for dispatchers to quickly formulate accurate, reliable, and efficient power supply recovery strategies suitable for distribution network fault scenarios.

[0065] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0066] The above-described embodiments are merely preferred embodiments of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. A method for dynamically evaluating power distribution network fault restoration capability, characterized in that, The method includes: The fault isolation status data of the target distribution network is processed to obtain the corresponding initial effective power supply topology description; the initial effective power supply topology description includes a switch and node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers; Based on the initial effective power supply topology description, a feeder network connectivity subgraph is constructed, and power supply control path analysis is performed based on the feeder network connectivity subgraph to obtain the initial docking point set for mobile energy storage. Obtain the topological distance between each initial stop in the initial stop set and the load center, and filter the stops based on the topological distance to obtain a candidate stop set; Based on the candidate docking point set and the feeder network connectivity subgraph, a steady-state power flow simulation of energy storage access operation is performed. Based on the simulation results, the candidate docking point set is sequentially screened by segmented voltage drop rate and voltage compliance to obtain a feasible location set. Based on the set of feasible locations, a target location combination scheme is obtained with the optimization objective of maximizing the downstream critical load coverage rate. The distribution network operation is simulated based on the target location combination scheme to obtain the recovery capacity assessment result. The downstream critical load coverage rate is the ratio of the weighted power of the downstream critical loads corresponding to the selected feasible locations to the mobile energy storage capacity.

2. The method of claim 1, wherein, The fault isolation status data includes sectional switch opening and closing data, feeder node operation data, and sectional line operation data. The step of processing the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description includes: Each segment switch is sequentially numbered according to its direction from the power source to the end of the feeder. Based on the obtained switch numbers and the switching data of each segment switch, a mapping relationship is established between the switch status value and the corresponding downstream control node set, thus obtaining the switch-node mapping table. Based on the state values ​​of each segment switch in the switch-node mapping table, the connectivity relationship between nodes and the energized state information of the corresponding control line segment are obtained. Based on the connectivity relationships between nodes of all the control line segments, the node connectivity matrix is ​​generated, and based on the energized state information of all the nodes, the energized state identifier set is obtained. The operating data of the feeder nodes and the operating data of the segmented lines are associated and stored based on the node number and the switch-node mapping table to generate the electrical parameter set of the distribution network.

3. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The step of constructing a feeder network connectivity subgraph based on the initial effective power supply topology description includes: Set the physical installation location of each segment switch in the switch-node mapping table as a control node, and set the opening / closing status attribute for each control node according to the energized status identifier set. The load access points in the target distribution network are identified according to the node connectivity matrix, each load access point is set as a demand node, and the node power consumption attributes are set for each demand node according to the distribution network electrical parameter set. According to the set of energized status identifiers, obtain the line segments with energized status identifiers, set each of the line segments with energized status identifiers as a connection edge, and set the connection attributes for each connection edge according to the set of electrical parameters of the distribution network to generate an initial feeder network subgraph. The validity of the initial feeder network subgraph is verified to obtain the connected subgraph of the feeder network.

4. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The step of performing power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial docking point set includes: Based on the depth-first search algorithm, starting from the power supply point, all reachable paths between any control node and each demand node in the connected subgraph of the feeder network are traversed to obtain the path redundancy of each control and demand node pair. The path redundancy of each of the control node pairs is compared with a preset redundancy threshold to obtain the control nodes whose path redundancy is greater than the preset redundancy threshold, and a candidate control node set is generated. Based on preset docking point setting conditions, the candidate control points in the candidate control node set are filtered to obtain a potential docking point set; the preset docking point setting conditions include direct connection to the demand node and having mobile energy storage docking space. A switch link closure continuity tracing analysis was performed on each potential stop in the potential stop set to obtain a complete stop set of the link; Calculate the cumulative line impedance between each complete link stop in the complete link stop set and the load center, and sort all the cumulative line impedance values ​​in ascending order to obtain the initial stop set.

5. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The step of obtaining the topological distance between each initial stop in the initial stop set and the load center, and filtering the stops based on the topological distance to obtain a candidate stop set includes: The feeder network connectivity subgraph is traversed using the search direction from each initial stop point to the load center to obtain the number of segment switches between each initial stop point and the load center. The number of segmented switches between each initial docking point and the load center is used as the corresponding topology distance, and the initial docking points with topology distances less than a preset near-end threshold are obtained to form the candidate docking point set.

6. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The simulation results include the line operation information from each candidate stop to the corresponding adjacent upstream node in the candidate stop set, as well as the voltage information at the end of the candidate stop; The line operation information includes the line impedance and the current flowing through the line; The step of performing segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the obtained simulation results to obtain the feasible location set includes: Based on the operating information of each line, the corresponding voltage drop value is obtained, and based on the voltage drop value and the corresponding segment line length, the segment voltage drop rate of the corresponding candidate stop point is obtained. Based on the segmented pressure drop rate corresponding to each candidate stop and the preset upper limit of the segmented pressure drop rate, the candidate stop set is filtered by segmented pressure drop rate to obtain a pressure drop smooth set. Based on the voltage information at the end of the candidate docking points, the voltage of each docking point with a gradual voltage drop in the voltage drop gradient set is screened to meet the voltage requirements, thereby obtaining a set of feasible locations.

7. The dynamic evaluation method for distribution network fault recovery capability as described in claim 6, characterized in that, The step of filtering for voltage compliance among all voltage-gradient docking points in the voltage-gradient set based on the terminal voltage information of the candidate docking points to obtain a feasible location set includes: Based on the terminal voltage information of the candidate docking points, obtain the terminal voltage value of each of the docking points with a gradual voltage drop; Based on the terminal voltage value of each of the voltage drop smoothing docking points and the preset allowable lower voltage limit, voltage compliance screening is performed to obtain a set of voltage compliant docking points; Calculate the voltage margin of each voltage-compliant stop in the voltage-compliant stop set, and sort all the voltage-compliant stops in the voltage-compliant stop set in descending order according to the voltage margin to obtain the feasible location set.

8. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The step of obtaining a target location combination scheme based on the feasible location set, with the optimization objective of maximizing the downstream critical load coverage rate, includes: A chromosome population is constructed based on the set of feasible locations, and a fitness function is set based on the downstream critical load coverage. Based on the chromosome population and the fitness function, a genetic algorithm is used for iterative optimization to obtain the target position combination scheme.

9. The dynamic evaluation method for distribution network fault recovery capability as described in claim 1, characterized in that, The target location combination scheme includes multiple target docking point locations; The step of performing distribution network operation simulation based on the target location combination scheme to obtain the recovery capability assessment result includes: Based on the target location combination scheme, various typical operating scenarios are simulated for the target distribution network to obtain the location feasible domain extension distribution; the location feasible domain extension distribution includes feasible domain node distribution information corresponding to each target docking point; the feasible domain node distribution information includes the power value and load type of each downstream load under different typical operating scenarios; Based on the location feasible region expansion distribution, calculate the weighted load recovery amount for each of the target docking points; The target docking point whose weighted load recovery amount exceeds the preset recovery amount threshold is obtained as the effective docking point, and the load coverage of all the effective docking points is merged to obtain the load recovery maximum coverage. The power supply path connectivity analysis is performed based on the load restoration maximization coverage and the location feasible domain expansion distribution to obtain the recovery capability assessment result.

10. A dynamic evaluation system for the fault recovery capability of a distribution network, characterized in that, The system includes: The power grid topology analysis module is used to process the fault isolation status data of the target distribution network to obtain the corresponding initial effective power supply topology description; the initial effective power supply topology description includes a switch and node mapping table, a node connectivity matrix, a distribution network electrical parameter set, and a set of energized status identifiers; The initial docking point acquisition module is used to construct a feeder network connectivity subgraph based on the initial effective power supply topology description, and perform power supply control path analysis based on the feeder network connectivity subgraph to obtain the initial docking point set. The candidate docking point acquisition module is used to acquire the topological distance between each initial docking point in the initial docking point set and the load center, and to filter the docking points according to the topological distance to obtain a candidate docking point set for mobile energy storage. The feasible location analysis module is used to perform steady-state power flow simulation of energy storage access operation based on the candidate docking point set and the feeder network connectivity subgraph, and to perform segmented voltage drop rate screening and voltage compliance screening on the candidate docking point set according to the simulation results to obtain the feasible location set. The resilience assessment module is used to obtain a target location combination scheme based on the feasible location set, with the optimization objective of maximizing the downstream critical load coverage rate, and to perform distribution network operation simulation based on the target location combination scheme to obtain the resilience assessment result; the downstream critical load coverage rate is the ratio of the weighted total power of the downstream critical loads corresponding to the selected feasible locations to the mobile energy storage capacity.

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