Power distribution system post-disaster load recovery method and system based on space-air-ground communication resource cooperation

Abstract

The application discloses a kind of space-time-ground communication resource coordination's power distribution system post-disaster load recovery method and system, obtain power distribution system topological data, failure information and the available information of satellite, unmanned aerial vehicle emergency base station and ground base station, establish including multiple recovery stages post-disaster load recovery model;Unmanned aerial vehicle deployment position optimization model and unmanned aerial vehicle dispatch path model are solved in turn, determine unmanned aerial vehicle deployment position, communication link, line split state, dispatch path and load recovery time;Satellite communication participation and recovery scheme of not participating are generated respectively, and scheme is selected according to weighted load loss and iteratively updated system state;According to the selected scheme, the communication link of main station to communication interruption node is established and power distribution system topological reconstruction is implemented.The application can coordinate emergency communication resources and power distribution network recovery process, improve the executability of post-disaster recovery scheme.

Description

Technical Field

[0001] This invention belongs to the field of power distribution system post-disaster recovery and emergency communication technology, specifically relating to a power distribution system post-disaster load recovery method and system that coordinates air-space-ground communication resources. Background Technology

[0002] In recent years, extreme disasters such as typhoons, floods, and earthquakes have occurred frequently, easily causing damage to power distribution lines, towers, switchgear, and distributed power sources, leading to widespread power outages. Power distribution systems directly face user loads and are characterized by wide coverage, dispersed equipment, and complex operating environments; therefore, their post-disaster recovery speed directly affects the power supply to critical loads and emergency response capabilities.

[0003] The operation and control of power distribution systems rely on communication networks to transmit measurement information and control commands. Under extreme disasters, while power equipment is damaged, ground base stations, communication lines, and communication facilities at distribution terminals may also fail, leading to the interruption of communication links between the power distribution system's master station and terminal equipment such as remote switches and load switches. Even if some lines and distributed power sources still have the conditions to restore power supply, network reconstruction may not be possible because the corresponding switches cannot receive control commands, resulting in communication failures that limit power restoration.

[0004] Existing technologies have employed drones or satellites to provide emergency communications for disaster-stricken power distribution systems. While drone-based emergency base stations can quickly reach the affected area and provide temporary access to power distribution terminals, current solutions typically focus on the access link between the drone and the power distribution terminal, failing to adequately address long-distance backhaul between the power distribution system's main station and the drone, as well as relay networking issues among multiple drones. When normal ground base station coverage is insufficient, the power distribution terminals covered by the drone may still be unable to establish a complete communication link to the power distribution system's main station.

[0005] While satellite communication offers advantages such as wide coverage and independence from terrestrial communication facilities, existing satellite-assisted recovery solutions typically require the deployment of satellite communication terminals at the power distribution terminal. The recovery range is limited by the number and installation location of these terminals, making it difficult to provide flexible access to a large number of dispersed communication outage nodes. Furthermore, satellite links are characterized by dynamic changes in availability windows and communication conditions, making it difficult to balance coverage, access flexibility, and recovery timeliness relying solely on satellite communication.

[0006] Furthermore, existing post-disaster recovery methods for power distribution systems typically make separate decisions regarding emergency communication restoration and power distribution network topology reconfiguration. They fail to adequately consider the constraints of communication node recovery status on line switching and connection control, and also fail to uniformly consider the time-series dependencies between factors such as satellite link availability, drone communication coverage and interference, drone endurance and dispatch routes, and the load recovery process. Therefore, problems such as mismatches between communication resource deployment plans and power distribution network reconfiguration needs, long drone dispatch times, and limited communication resources not prioritizing services for critical loads can easily arise, affecting the amount and speed of post-disaster load recovery. Summary of the Invention

[0007] The technical problem to be solved by this invention is to address the shortcomings of the prior art by providing a method and system for post-disaster load recovery of power distribution systems that coordinates air-space-ground communication resources. This method addresses the technical problems that arise when extreme disasters cause simultaneous damage to the power distribution network and communication network, existing UAV or satellite emergency communication methods struggle to form a complete communication link from the power distribution system master station to the communication interruption node. Furthermore, the independent nature of communication resource deployment, UAV dispatch, and power distribution network topology reconfiguration leads to insufficient utilization of limited communication resources, slow load recovery speed, and limited recovery of critical loads.

[0008] The present invention adopts the following technical solution: A method for post-disaster load restoration of power distribution systems using space-air-ground communication resources includes the following steps: S1. Obtain topology data, fault information, and communication resource availability information of the power distribution system, wherein the communication resources include satellites, UAV emergency base stations, and ground base stations; S2. Based on the topology data, fault information, and communication resource availability information, establish a power distribution system post-disaster load recovery model that includes multiple recovery phases executed sequentially. The power distribution system post-disaster load recovery model includes a UAV deployment location optimization model and a UAV dispatch path model. S3. In each recovery phase, based on the current operating status of the power distribution system and the availability of communication resources, solve the UAV deployment location optimization model. Under the constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, determine the UAV target deployment location, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status. S4. Based on the current location of the UAV, the target deployment location of the UAV, and the availability of communication resources, solve the UAV dispatch path model, and determine the UAV dispatch path and load recovery time under the constraints of UAV dispatch path, endurance time, working time, and satellite link availability time. S5. Determine the recovery plans for satellite communication participation and satellite communication non-participation respectively. Select the recovery plan for the current recovery stage according to the weighted load loss corresponding to each recovery plan. Update the power distribution system operation status, communication resource availability status and UAV status according to the selected recovery plan, and enter the next recovery stage until there is no new recovery load. S6. Dispatch drones according to the recovery plan for each recovery stage, establish a communication link from the main station of the power distribution system to the communication interruption node through at least one of satellite link, ground base station link and relay link between drones, and control the power distribution system to perform topology reconstruction according to the line connection and disconnection status.

[0009] Furthermore, before step S2, the method includes obtaining the geographical location information of each node in the power distribution system; step S2 also includes: The geographical distance between nodes is determined based on the geographical location information of each node, and the fault-free electrical connection relationship between nodes is determined based on the topology data and fault information. The similarity between nodes is determined based on the geographical distance and fault-free electrical connection relationships, and a node similarity matrix is ​​constructed. Based on the node similarity matrix, spectral clustering is used to divide the power distribution system into multiple recovery areas, and the deployment locations of UAV targets in each recovery area are determined.

[0010] Furthermore, the drone communication coverage constraints include: Only drone emergency base stations are allowed to establish communication links with communication interrupted nodes located within their communication coverage area; The number of communication interruption nodes connected to each drone emergency base station shall not exceed the first preset number; The number of communication interrupted nodes restored in each recovery phase shall not exceed the second preset number; Each communication interruption node can establish a communication link with at most one drone emergency base station.

[0011] Furthermore, the UAV deployment location optimization model also includes communication quality constraints; The communication quality constraints include: determining the signal-to-interference-plus-noise ratio (SIR) between the UAV emergency base station and the communication interruption node based on the channel gain, signal transmission power, noise power, and interference signals between the UAV emergency base station, the ground base station, and the communication interruption node, and limiting the SIR to not be lower than a preset SIR threshold.

[0012] Furthermore, the communication link connectivity constraints include: Emergency base stations for unmanned aerial vehicles (UAVs) equipped with satellite communication terminals are connected to the main power distribution system station via satellite links; and / or, The drone emergency base station is connected to the power distribution system master station through a normally functioning ground base station; and / or, The UAV emergency base station connects to a satellite or a normally functioning ground base station through a multi-hop relay link formed by one or more other UAV emergency base stations, thus forming a complete communication link from the power distribution system master station to the communication interruption node.

[0013] Furthermore, the line switching control constraints include: Keep the faulty line disconnected; Only remote switches corresponding to power distribution system nodes that have a complete communication link with the power distribution system master station are allowed to change their open / closed status; For power distribution system nodes whose communication links are interrupted, after the power distribution system node connects to the power distribution system master station through the UAV emergency base station, the corresponding remote switch is allowed to change its open / closed state.

[0014] Furthermore, the power distribution system topology constraints are used to limit the power distribution system to form at least one radial microgrid powered by a power source node through line switching control; The operating constraints of the power distribution system include node active power balance constraints, node reactive power balance constraints, node voltage constraints, power output constraints, and line transmission capacity constraints. The drone deployment location optimization model aims to maximize the sum of the products of the recovery load power and the corresponding load weight of each load node, while minimizing the number of drones called up.

[0015] Furthermore, the drone dispatch path constraints include: For each drone to be dispatched, a dispatch path is determined from its current location to the corresponding drone target deployment location, and each drone target deployment location corresponds to one drone. Determine whether the drone is capable of completing the current recovery phase based on its flight time, hovering time, and remaining flight time. If the remaining flight time of the drone is insufficient to complete the work of the current recovery phase, the corresponding drone shall return to the drone warehouse to replace the battery and then fly to the target deployment location of the drone.

[0016] Furthermore, for drones that access the power distribution system master station via satellite links, the satellite link availability time constraint is used to limit the overlap between the drone's working time and at least one satellite availability time window to be no less than the preset time required to complete the line control operation. The load recovery time for each load node is determined based on the time required for the upstream communication interruption node in the power supply path of each load node to access the communication network. The weighted load loss includes the load loss corresponding to the unrecovered load during the current recovery phase and the load loss corresponding to the recovered load before recovery. The UAV dispatch path model takes the minimization of the weighted load loss as its optimization objective.

[0017] Secondly, embodiments of the present invention provide a post-disaster load recovery system for a power distribution system that coordinates air-space-ground communication resources, including a processor, a memory, and a communication interface. The memory stores a program executed by the processor, and the communication interface is used for data interaction with the power distribution system master station, UAV emergency base station, and ground base station. When the processor executes the program, it implements the following: Acquire topology data, fault information, and communication resource availability information of the power distribution system, including satellites, UAV emergency base stations, and ground base stations; Based on the topology data, fault information, and communication resource availability information, a power distribution system post-disaster load recovery model is established, which includes multiple recovery phases executed sequentially. The power distribution system post-disaster load recovery model includes a UAV deployment location optimization model and a UAV dispatch path model. In each recovery phase, the UAV deployment location optimization model is solved based on the current power distribution system operation status and communication resource availability. Under the constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, the target deployment location of the UAV, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status are determined. The drone dispatch path model is solved based on the current location of the drone, the target deployment location of the drone, and the availability of communication resources. Under the constraints of drone dispatch path, endurance time, working time, and satellite link availability time, the drone dispatch path and load recovery time are determined. The recovery plans for satellite communication participation and satellite communication non-participation are determined separately. The recovery plan for the current recovery stage is selected based on the weighted load loss corresponding to each recovery plan. The operation status of the power distribution system, the availability status of communication resources, and the status of the UAV are updated according to the selected recovery plan. The process continues until there is no new recovery load. The recovery scheme for each recovery stage is output through the communication interface, so that the UAV can establish a communication link from the power distribution system master station to the communication interruption node through at least one of the satellite link, the ground base station link and the relay link between the UAVs, and the power distribution system master station controls the power distribution system to perform topology reconstruction according to the line opening and closing status.

[0018] Thirdly, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for post-disaster load recovery of a power distribution system with coordinated air-space-ground communication resources.

[0019] Fourthly, embodiments of the present invention provide a computer-readable storage medium including a computer program, which, when executed by a processor, implements the steps of the above-described method for post-disaster load recovery of a power distribution system with coordinated air-space-ground communication resources.

[0020] Fifthly, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for post-disaster load recovery of a power distribution system with coordinated air-space-ground communication resources.

[0021] In a sixth aspect, embodiments of the present invention provide an electronic device, including a computer program, wherein when the computer program is executed by the electronic device, it implements the steps of the above-described method for post-disaster load recovery of a power distribution system with coordinated air-space-ground communication resources.

[0022] Compared with the prior art, the present invention has at least the following beneficial effects: A post-disaster load restoration method for power distribution systems that coordinates air-space-ground communication resources is proposed. This method acquires the fault status of the power distribution system and the availability of satellite, UAV emergency base stations, and ground base stations. It then solves the UAV deployment location optimization model and UAV dispatch path model in stages, integrating emergency communication link establishment, UAV scheduling, line switching control, and power distribution network topology reconfiguration into a single restoration process. The method addresses the information-physical coupling relationship when both the communication and power networks are simultaneously damaged, ensuring that line control schemes have practically executable communication conditions. By comparing schemes with and without satellite communication participation, it selects the restoration path with the smaller weighted load loss, thereby coordinating limited communication and power restoration resources and reducing load outage time.

[0023] Furthermore, spectral clustering is performed by combining the geographical distance of nodes and the fault-free electrical connections, grouping nodes that are geographically close and electrically interconnected into the same recovery region. This decomposes the large-scale joint optimization problem into multiple regional sub-problems, reducing the number of candidate deployment locations and combined variables, and improving the solution efficiency of the post-disaster recovery model.

[0024] Furthermore, by limiting the drone's communication coverage radius, the number of nodes a single drone can access, the total number of nodes to be restored in a single phase, and the unique access relationship of each node, the drone deployment plan is made to conform to the actual coverage area and communication capacity. This avoids establishing links beyond the coverage area, overloading communication resources, and duplicate access, thereby improving the feasibility of the deployment plan.

[0025] Furthermore, the signal-to-interference-plus-noise ratio (SIR / NDR) is determined based on transmit power, channel gain, noise, and co-channel interference, and a minimum threshold is set. Connections within coverage area but with insufficient communication quality are excluded to ensure that control commands can be transmitted through links with sufficient reliability.

[0026] Furthermore, a complete link from the master station to the communication interruption node is constructed through satellite links, ground base station links, and UAV multi-hop relay links. This leverages the complementary roles of wide-area satellite backhaul, low-latency ground base station access, and flexible UAV relay to expand emergency communication coverage and reduce reliance on satellite communication equipment in power distribution terminals.

[0027] Furthermore, the complete communication link is set as a prerequisite for the remote switch to change its open / closed state, and the closure of the faulty line is prohibited. This ensures that network reconfiguration commands are matched with the communication reachability state, avoiding the generation of unexecutable schemes that cannot be issued or may re-engage the faulty line.

[0028] Furthermore, through radial microgrid constraints and power balance, voltage, power output and line capacity constraints, the reconfigured power distribution system can be guaranteed to meet safe operation conditions; with the goal of maximizing the weighted recovery load and minimizing the number of drones, important loads can be restored first, while reducing communication resource consumption and the number of drones called up.

[0029] Furthermore, the dispatch route is determined based on the drone's current location, target location, flight time, hovering time, and remaining battery life, and a return to the depot for battery swapping is arranged when the battery is low. This enables the drone to continuously complete flight, communication link establishment, and control operations, avoiding dispatch mission interruptions or the inability to establish effective communication support at the target location due to insufficient battery life.

[0030] Furthermore, by constraining the satellite availability time window, the effective duration of the satellite link is ensured to meet the control operation requirements; the load restoration time is calculated based on the communication restoration time of the upstream nodes in the power supply path, with the goal of minimizing weighted load loss. The dynamic availability of satellites, the arrival time of drones, and the sequence of line control are coordinated to prioritize reducing power outage losses caused by critical loads and loads that have not been restored for extended periods.

[0031] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0032] In summary, this invention establishes a cyber-physical collaborative recovery model for power distribution systems. By solving for the optimal deployment location and scheduling path of UAVs, it provides communication support for the post-disaster recovery of power distribution systems. Furthermore, by coordinating with the microgrid reconstruction of the power distribution system, it provides an effective solution for rapid post-disaster recovery. This method fully considers the flexible resource association between communication networks and power grids under the cyber-physical coupling characteristics, enabling rapid and efficient recovery of power distribution systems and reducing power outage losses.

[0033] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0034] Figure 1 Flowchart for solving the load recovery problem in a power distribution system after a disaster; Figure 2 A schematic diagram of the improved IEEE-123 node; Figure 3 Diagram showing the drone's operational plan and power distribution system recovery process; Figure 4 A comparison chart of power distribution system load recovery under different schemes; Figure 5 A schematic diagram of a computer device provided in an embodiment of the present invention; Figure 6 This is a block diagram of a chip according to an embodiment of the present invention; Figure 7 This is a flowchart of the method of the present invention.

[0035] Among them, 60. Computer equipment; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0038] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0039] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0040] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0041] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0042] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0043] This invention provides a post-disaster load restoration method for power distribution systems that coordinates air-space-ground communication resources. Addressing post-disaster scenarios where both communication and power networks are simultaneously damaged, it constructs a cyber-physical coordinated restoration mechanism. This mechanism jointly decides on the scheduling of communication resources from satellite, UAV emergency base stations, and ground base stations, along with UAV deployment locations, dispatch paths, line connection / disconnection status, and load restoration status. Simultaneously, it solves restoration schemes under both satellite communication participation and non-participation conditions, and iteratively selects solutions in stages based on weighted load loss. This ensures that remote switch control relies on a complete communication link from the master station to the communication interruption node, avoiding unenforceable network reconstruction schemes. It expands emergency communication coverage by leveraging the complementary capabilities of satellite wide-area backhaul, stable ground base station access, and UAV multi-hop relay. Furthermore, it arranges the restoration order based on UAV endurance, satellite time windows, and load importance, reducing power outage time for critical loads and ineffective UAV dispatch, thereby improving the feasibility, timeliness, and communication resource utilization efficiency of the post-disaster load restoration plan.

[0044] Please see Figure 7 This invention discloses a method for post-disaster load restoration of a power distribution system based on coordinated air-space-ground communication resources, comprising the following steps: S1. Obtain power distribution system topology data, fault information, and communication resource availability information within the region; S2. Divide the power distribution system into regions based on the geographical information data of the power distribution system obtained in step S1; The basis for dividing the power distribution system into regions includes the geographical proximity of nodes and their electrical connections. Spectral clustering is used to divide the power distribution system into regions.

[0045] The similarity of data points is mainly related to two factors: 1) Nodes that are electrically connected should preferably be assigned to the same area; 2) Nodes that are geographically close should be assigned to the same region.

[0046] Define nodes according to this rule. With nodes Spectral clustering similarity between : (1) (2) (3) in: and Representing nodes respectively With nodes Geographical distance and electrical connections between them; and The weights for geographical distance and electrical connection are represented respectively. It is a node Position coordinates; It is a connection node To the node The number of fault-free shortest paths.

[0047] S3. Based on the power distribution system fault information obtained in step S1 and the regional division results obtained in step S2, establish a power distribution system post-disaster load recovery model. The model divides the power distribution system recovery process into multiple steps. In each recovery step, solve the UAV deployment location optimization model and the UAV dispatch path model independently and sequentially. Calculate the UAV deployment schemes under satellite communication support and non-support scenarios respectively, evaluate and compare the feasibility and load recovery effect of the schemes, and iteratively construct the final implementation scheme. S301. Based on the current operating status of the power distribution system, solve the optimization model for the deployment location of the UAV; The constraints of the drone deployment location optimization model include: (1) Unmanned aerial vehicle (UAV) communication coverage constraints: Considering the limited communication coverage of drone base stations, they can only establish communication links with communication nodes within their coverage area; furthermore, due to bandwidth limitations, the number of communication nodes a base station is allowed to access is also limited. This can be represented as: (4) (5) (6) (7) (8) (9) (10) (11) in, and These represent the candidate deployment locations for drones. and communication interruption node Position coordinates; Indicates deployment location and communication interruption node The distance between them; and These are the set of candidate deployment locations and the set of nodes where communication was interrupted, respectively. It is the maximum communication coverage radius of the drone; This indicates a node where communication is interrupted. Is it in the candidate deployment location? 0-1 variables within the coverage area; It indicates position. Whether the communication interruption node is communicated via drone Establish 0-1 variables for the actual communication link; This indicates the deployment location. A 0-1 variable indicating whether a particular drone has accessed the data. and These represent the maximum number of nodes a drone can connect to and the maximum number of nodes whose communication is restored in a single step, respectively. This indicates a node where communication is interrupted. A 0-1 variable indicating whether an actual communication link is established between a drone and the main station; It refers to drones Is it in the candidate location? The 0-1 variables of the work; This refers to a drone warehouse.

[0048] (2) Communication interference constraints: Interference signals from other drones and ground base stations can affect the communication quality between drones and nodes experiencing communication outages. Therefore, a communication channel model is established between the drone base station and ground power equipment, and signal-to-interference-plus-noise ratio (SIR) constraints are set between the drone base station and communication nodes to ensure communication link quality. This is represented as: (12) (13) (14) (15) (16) (17) (18) in, and These represent the losses of line-of-sight links and non-line-of-sight links, respectively. It is the carrier frequency; and These represent the additional path loss for line-of-sight links and non-line-of-sight links, respectively. Indicates position Height; It is a set of base stations; and These represent the probabilities of line-of-sight links and non-line-of-sight links, respectively. and It is an environmental constant; Indicates a node where communication is interrupted. With drone base stations or ground base stations The angle of elevation between them; Indicates a node where communication is interrupted. With drone base stations or ground base stations The average link loss between them. Indicates a node where communication is interrupted. With drone base stations or ground base stations Average channel gain between; Indicates a node where communication is interrupted. With drone candidate locations The signal-to-interference-plus-noise ratio between them; and These represent the signal transmission power of the drone emergency base station and the ground base station, respectively. It is additive white Gaussian noise; It is a maximum value.

[0049] (3) Unmanned Aerial Vehicle (UAV) communication link constraints: In each step, the UAV base station receives control commands from the power distribution system master station and proceeds to the corresponding deployment location to build an emergency communication network. The UAV base station possesses multi-hop link networking capabilities with normally functioning ground base stations and other airborne base stations. UAV base stations equipped with satellite communication modules can establish satellite-to-ground communication links, thereby providing communication relay services to other UAV base stations. The connectivity of the UAV network is described using a single-goods flow method, expressed as: (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) (25) (26) (27) (28) (29) in, It refers to drones and drones Can a 0-1 variable be linked? This is the maximum distance for drone relay; A collection of drones; and These represent drones The 0-1 variables of whether or not satellite access is possible and whether or not base station access is possible; It refers to drones Can the 0-1 variables of a satellite or base station be directly accessed? It refers to the number of drones equipped with satellite communication terminals in a drone swarm; Indicates injection into drones Goods flow in the middle; Indicates from drones flow to drones The flow of goods; It represents a node Whether to connect drones 0-1 variables.

[0050] (4) Line switching control constraints Nodes with a complete communication link to the master station can receive control commands from the power distribution system master station, thereby controlling the closing or opening of remote switches on the corresponding lines. Nodes whose communication links are interrupted due to communication facility failures need to be covered by a drone base station and have a complete communication link established before they can receive commands from the power distribution system master station. This is represented as: (30) (31) (32) in, It represents a node A 0-1 variable representing the communication status with the master station; Represents the set of nodes in a power distribution system; It indicates the line The initial 0-1 variables of the split and merge states; It is a collection of power distribution system lines; It indicates the line 0-1 variables representing possible states; It indicates the line 0-1 variables in the state of separation and combination; Indicates the line The fault condition is that the faulty circuit cannot be closed, that is, when hour, .

[0051] (5) Power distribution system topology constraints During the recovery process, the power distribution system undergoes topology reconfiguration to form multiple radial microgrids powered by distributed generation sources to restore power supply to the loads. A single-goods flow method is used to construct the microgrid topology constraint model during the recovery process, represented as: (30) (31) (32) (33) (34) (35) (36) in, Indicates from node Flow to Node The flow of goods; It represents a node A 0-1 variable indicating whether it is charged; It is a collection of power nodes; Represents a node The volume of goods injected into the system; Represents a node Is there a load switch? It represents a node A 0-1 variable indicating whether the load has been restored.

[0052] (6) Operational constraints of the power distribution system To ensure the safe and stable operation of the power distribution system, power flow and voltage constraints must be met. This is represented as: (37) (38) (39) (40) (41) (42) (43) (44) in, and Representing nodes respectively The active and reactive power injected by the power source; and Representing nodes respectively The active and reactive power demands of the load; and They represent the lines respectively. The positive and negative currents on the surface; and The lines are respectively Resistance and reactance; Represents a node The voltage; and Representing nodes respectively The lower and upper limits of the active power injected by the power source; and They are nodes The lower and upper limits of reactive power injected by the power source; and These are the upper and lower limits of the allowable voltage fluctuations in the power distribution system, respectively. It is a line Power limitations.

[0053] Furthermore, the objective function of the drone deployment location optimization model is to maximize the weighted power supply in this step while minimizing the number of drones used simultaneously, as expressed below: (45) in, It represents a node A 0-1 variable indicating whether the load has been restored; Represents a node The active power demand of the load; This indicates the deployment location. A 0-1 variable indicating whether a particular drone has accessed the data. It is a node The weight of a load is determined by its importance. It is the weight of the number of drones dispatched.

[0054] S302. Based on the current availability of communication resources, solve the UAV dispatch path model; The constraints of the drone dispatch path model include: (1) UAV path constraints: In a single deployment, one drone should depart from each current work location, and one drone should arrive at each deployment target location. This is represented as: (46) (47) (48) in, This indicates whether a drone is located at [location]. Fly to location 0-1 variables; and These are the initial and destination locations for this movement, respectively. It indicates position. The 0-1 variable indicating whether the drone is equipped with a satellite communication terminal; Indicates the initial position Does the drone carry a satellite communication terminal?

[0055] (2) Drone endurance constraints: Due to battery capacity limitations, in some malfunction scenarios, the drone's battery may be insufficient to complete the next task, requiring it to return to the warehouse for battery replacement. This is indicated as: (49) (50) (51) (52) in, Indicates position The remaining battery power of the drone when it finishes its work; Indicates the drone's location The time it takes to return to the warehouse; The drone's power consumption per unit time; It indicates the destination. Whether the drone at the location started from a fully charged state is a 0-1 variable; It indicates the destination. The 0-1 variable indicating whether the drone should return to the warehouse for battery replacement; Indicates the initial position Is it a warehouse? Indicates the drone's flight time; Indicates the location of the drone The hovering time; Indicates the drone's initial position The remaining power at the location; This indicates that the drone has reached its destination from its initial position. The time required.

[0056] (3) Working time constraints: The drone's flight time depends on whether it returns to the warehouse to replace the battery, as shown below: (53) (54) (55) (56) (57) in, Indicates the destination location The time required to replace the battery of a drone at the location; Indicates starting from the initial position Arrive at the location Direct flight time; and These represent the start and end times of this step, respectively. Indicates the target location Is it a warehouse? It is the shortest time required for a drone to complete control operations, i.e., the lower limit of hovering time; This is the time required to change the drone's battery.

[0057] (4) Satellite link establishment constraints: The coverage characteristics of available satellites and communication signal attenuation caused by weather conditions can prevent UAVs from accessing low-Earth orbit satellites during certain periods. This paper describes the available satellite time periods during the recovery process in the form of time windows. For a UAV to establish a communication link with a satellite and issue control commands, the overlap between the UAV's operating time and the available satellite time window must be greater than the minimum time required for the UAV to complete the control operation. This is expressed as: (58) (59) (60) (61) (62) (63) (64) (65) (66) (67) (68) in, and These represent the available time windows for satellites. The start and end times; It is a set of available time windows for satellites; This indicates the work and time window for this step. Whether 0-1 variables overlap; It indicates position. Can the drones at this location access the 0-1 variables of the satellite? It indicates the destination location. Is it a 0-1 variable in the warehouse? It indicates position. Is the drone a location? The 0-1 variables directly upstream of the information link from the UAV to the main station; when the location The drone at the location can directly connect to satellites, ground base stations, or, if this step is not in operation, ; This refers to the number of available drones; This indicates that the drone starts from its initial position and arrives at its destination. The time required to start work.

[0058] (5) Constraints on power supply path and load recovery time: In a certain step, the node The necessary condition for restoring power is the existence of a fault-free power supply path from the power source to the node, and all lines in the path are closed, as shown below: (69) (70) in, Indicates the nodes in this step Time required to access the communication network; Indicates the nodes in this step The time required for load recovery at the location; It is a bus node The set of upstream communication interruption nodes along the power supply path. Considering the radial path bus nodes for power supply. Power supply can only be restored after the upstream node is energized. and These represent the nodes in this step. The initial and final states of the load at the location are represented by 0-1 variables.

[0059] Furthermore, the objective function of the drone dispatch path model is as follows: (71) S4. Based on the communication resource scheduling and power distribution system control scheme obtained in step S3, the power distribution system is quickly restored after the disaster.

[0060] Please see Figure 1A flowchart of the information-physical collaborative recovery algorithm for power distribution systems is presented. In each recovery step, the working schemes of drones with and without satellite communication support are solved separately. The scheme with higher load recovery efficiency is selected by comparison, and the process is repeated until there is no new load to be restored in the system. In each step of the working scheme with or without satellite communication support, the optimal deployment location of drones is solved for each area and the optimal scheme is selected. The process is repeated until all drones have been dispatched or there is no new load, and then the drone dispatch path planning is solved. To ensure that all drones can access the communication network in a step, drones with already determined locations are treated as fixed base stations that can be accessed during the iteration, and the signal-to-interference-plus-noise ratio is included in the calculation.

[0061] In another embodiment of the present invention, a post-disaster load recovery system for a power distribution system with coordinated air-space-ground communication resources is provided. This system can be used to implement the aforementioned post-disaster load recovery method for a power distribution system with coordinated air-space-ground communication resources. Specifically, the post-disaster load recovery system for a power distribution system with coordinated air-space-ground communication resources includes a processor, a memory, and a communication interface. The memory stores a program executed by the processor, and the communication interface is used for data interaction with the power distribution system master station, UAV emergency base station, and ground base station. When the processor executes the program, it implements the following: Acquire topology data, fault information, and communication resource availability information of the power distribution system, including satellites, UAV emergency base stations, and ground base stations; Based on the topology data, fault information, and communication resource availability information, a power distribution system post-disaster load recovery model is established, which includes multiple recovery phases executed sequentially. The power distribution system post-disaster load recovery model includes a UAV deployment location optimization model and a UAV dispatch path model. In each recovery phase, the UAV deployment location optimization model is solved based on the current power distribution system operation status and communication resource availability. Under the constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, the target deployment location of the UAV, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status are determined. The drone dispatch path model is solved based on the current location of the drone, the target deployment location of the drone, and the availability of communication resources. Under the constraints of drone dispatch path, endurance time, working time, and satellite link availability time, the drone dispatch path and load recovery time are determined. The recovery plans are determined separately for satellite communication participation and satellite communication non-participation. The recovery plan for the current recovery stage is selected based on the weighted load loss corresponding to each recovery plan. The operation status of the power distribution system, the availability status of communication resources, and the status of the UAV are updated according to the selected recovery plan, and the next recovery stage is entered until there is no new recovery load. The recovery scheme for each recovery stage is output through the communication interface, so that the UAV can establish a communication link from the power distribution system master station to the communication interruption node through at least one of the satellite link, ground base station link and relay link between UAVs, and the power distribution system master station controls the power distribution system to perform topology reconstruction according to the line opening and closing status.

[0062] This invention provides a terminal device comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve corresponding method flows or corresponding functions. The processor described in this embodiment can be used in the operation of a post-disaster load recovery method for power distribution systems using space-air-ground communication resource coordination, including: The system acquires topology data, fault information, and communication resource availability information of the power distribution system, including satellite, UAV emergency base station, and ground base station. Based on the topology data, fault information, and communication resource availability information, a post-disaster load recovery model for the power distribution system is established, comprising multiple sequentially executed recovery phases. This model includes a UAV deployment location optimization model and a UAV dispatch path model. In each recovery phase, based on the current operating status of the power distribution system and the availability of communication resources, the UAV deployment location optimization model is solved. Under constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, the target deployment location of the UAV, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status are determined. Based on the current location of the UAV and the availability of communication resources, the system... The model for the deployment location of the drone and the availability of communication resources is solved. Under the constraints of drone deployment path, endurance time, working time, and satellite link availability time, the drone deployment path and load recovery time are determined. Recovery schemes are determined for satellite communication participation and non-participation. The recovery scheme for the current recovery stage is selected based on the weighted load loss corresponding to each recovery scheme. The operating status of the power distribution system, the availability of communication resources, and the drone status are updated according to the selected recovery scheme, and the next recovery stage is entered until there is no new load to be restored. Drones are dispatched according to the recovery schemes of each recovery stage. A communication link is established from the power distribution system master station to the communication interruption node through at least one of the satellite link, ground base station link, and relay link between drones. The power distribution system is controlled to perform topology reconfiguration according to the line connection and disconnection status.

[0063] Please see Figure 5 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the post-disaster load recovery method for power distribution systems using space-air-ground communication resource coordination as described in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the post-disaster load recovery system for power distribution systems using space-air-ground communication resource coordination as described in this embodiment. To avoid repetition, these details are not elaborated here.

[0064] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 5This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0065] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0066] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0067] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0068] Please see Figure 6 The terminal device is an electronic device 600, which is manifested in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0069] The storage unit stores program code, which can be executed by the processing unit 610 to perform the steps described in the method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 1 The steps are shown in the figure.

[0070] Storage unit 620 may include readable media in the form of volatile storage units, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include read-only memory (ROM) 6203.

[0071] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0072] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0073] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem). This communication can be performed via input / output interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network, wide area network, and / or public network, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0074] This invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It is understood that the computer-readable storage medium here can include both built-in storage media in the terminal device and extended storage media supported by the terminal device; it can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). More specific examples of the computer-readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0075] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium can also be any readable medium other than a readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, etc., or any suitable combination thereof.

[0076] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0077] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the post-disaster load recovery method for power distribution systems related to the coordination of air-space-ground communication resources in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps:

[0078] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0079] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0080] With the increasing maturity of autonomous inspection and emergency communication capabilities of drone swarms and the large-scale deployment of low-Earth orbit satellite constellations, the unit communication cost between drones and satellites has been significantly reduced, enabling integrated air-space-ground communication methods to gradually move from technical feasibility to engineering practice. Currently, integrated air-space-ground communication technology has been successfully applied in multiple fields such as communication, navigation, and remote sensing. During the Yajiang forest fire in Sichuan in March 2024, integrated air-space-ground communication technology demonstrated strong emergency communication support capabilities, building a high-quality, full-network, and wide-coverage communication bridge for the firefighting efforts. In June 2025, the State Grid Shaoxing Power Supply Company, in conjunction with Zhejiang Huayun Clean Energy Co., Ltd., constructed an integrated air-space-ground intelligent inspection system at the 500 kV Lanting substation, achieving functions such as precise scanning of partial discharge anomalies and intelligent scanning of the entire station's temperature spectrum.

[0081] In the field of power distribution system post-disaster recovery, existing research has incorporated drones and satellite communication into the recovery framework. Satellite communication, with its wide-area coverage, can provide backhaul channels when ground infrastructure is damaged, overcoming the information silos caused by geographical isolation. Drones, as aerial communication nodes, offer flexible deployment advantages, enabling them to quickly reach target areas and establish temporary access networks after a disaster, with higher communication link reliability. Residual ground communication facilities can provide high-capacity, low-latency access services in localized areas. These three types of resources provide the foundation for constructing a tiered emergency communication architecture, thereby providing emergency communication support for the rapid post-disaster recovery of power distribution systems.

[0082] There is a deep coupling between the information layer and the physical layer of a power distribution system. Under extreme disasters, communication interruptions will cause the physical system to lose considerable controllability, while damage to the physical system will further deteriorate the power supply and transmission conditions of the information layer, resulting in cascading failures. Therefore, from the perspective of cyber-physical coupling, co-optimizing the scheduling of air-space-ground communication resources with the power distribution network recovery process is consistent with the collaborative recovery mechanism of the power distribution system. By establishing an cyber-physical collaborative recovery model, the temporal dependencies between emergency communication resource deployment, power load restoration, and network reconfiguration can be characterized, making the collaborative recovery strategy feasible in practice.

[0083] This invention models the post-disaster load restoration problem of power distribution systems as a mixed-integer linear programming (MILP) problem, which can be solved using commercial solvers. It also employs methods such as discrete deployment location selection and power distribution system regional division to reduce the difficulty and improve efficiency. The resulting restoration plan includes a deployment scheme for air-space-ground communication resources, a power distribution network reconstruction scheme, and a load restoration scheme. Based on the desired hovering position, dispatch path, and satellite link allocation of drones at different time periods, drones can be controlled to fly to the work location, establishing an emergency communication link between the power distribution system master station and the power distribution terminals in the power outage area. This restores the system's power distribution automation functions, and topology adjustments are made according to the network reconstruction scheme to gradually restore power supply to the load.

[0084] The method of this invention fully considers the cyber-physical coupling characteristics during the power distribution system restoration process. It utilizes satellite, UAV, and ground base station resources to establish a temporary communication network for communication interruption nodes in the power distribution system. In coordination with the topology reconstruction of the power distribution system, it maximizes the weighted load restoration of the power distribution system. Based on the communication link and endurance constraints of UAVs, an optimization model for UAV dispatch paths is established. Through coordination with the UAV deployment model, the load restoration efficiency of the power distribution system is improved, and the load loss during the restoration process is effectively reduced.

[0085] Taking the improved IEEE 123-node test system as an example, a verification case was designed to verify the effectiveness of the proposed method.

[0086] Please see Figure 2 The topology of the 123-node power distribution system is as follows: Figure 2 As shown, the total load of the power distribution system is 45.58MW + 24.4Mvar, comprising 7 distributed power sources. There is one normally functioning base station within the area, and the drone warehouse is located at node 1. The disaster caused communication disruptions at 26 nodes, 17 line failures, and the power distribution system was completely dark. The power distribution system is divided into 4 zones.

[0087] Five drones were available during the recovery process, one of which was equipped with a satellite communication terminal. The emergency drone base station had a communication coverage radius of 2km, a relay distance of 3km, a flight speed of 50m / s, a maximum endurance of 25 minutes, and a power consumption of 1 kilowatt-hour. Each drone could establish links with a maximum of five communication interruption nodes. The shortest time for a drone to hover at the work site and complete control operations was 60s, and the time required for a drone to change batteries at the warehouse was 60s. The communication parameters of the drone base station are shown in Table 1. Discrete points spaced 1km apart within the power distribution system area were selected as candidate locations for the drone base station. The recovery process included four satellite availability windows: 300-500s, 600-1200s, 1400-1600s, and 2200-3000s.

[0088] Solve using the following steps: S1. Obtain power distribution system topology data, fault information, and communication resource availability information within the region; S2. Divide the power distribution system into regions based on the geographical information data of the power distribution system obtained in step S1; S3. Based on the power distribution system fault information obtained in step S1 and the regional division results obtained in step S2, establish a power distribution system post-disaster load recovery model. The model divides the power distribution system recovery process into multiple steps. In each recovery step, solve the UAV deployment location optimization model and the UAV dispatch path model independently and sequentially. Calculate the UAV deployment schemes under satellite communication support and non-support scenarios respectively, evaluate and compare the feasibility and load recovery effect of the schemes, and iteratively construct the final implementation scheme. S4. Based on the communication resource scheduling and power distribution system control scheme obtained in step S3, the power distribution system is rapidly restored after the disaster.

[0089] Please see Figure 1A flowchart of the information-physical collaborative recovery algorithm for power distribution systems is presented. In each recovery step, the working schemes of drones with and without satellite communication support are solved separately. The scheme with higher load recovery efficiency is selected by comparison, and the process is repeated until there is no new load to be restored in the system. In each step of the working scheme with or without satellite communication support, the optimal deployment location of drones is solved for each area and the optimal scheme is selected. The process is repeated until all drones have been dispatched or there is no new load, and then the drone dispatch path planning is solved. To ensure that all drones can access the communication network in a step, drones with already determined locations are treated as fixed base stations that can be accessed during the iteration, and the signal-to-interference-plus-noise ratio is included in the calculation.

[0090] To verify the effectiveness of the proposed method, the following schemes were designed for comparison: 1) Option 1: Without taking communication recovery measures, rely solely on nodes in the power distribution system that do not experience communication interruptions to control the reconfiguration and recovery of the power distribution system; 2) Option 2: Deploy drones as emergency base stations to restore the communication capabilities of nodes with communication interruptions. Since there are no satellite resources, drones can only establish links with ground base stations. 3) Option 3: Deploy drones as emergency base stations to restore communication capabilities of nodes with communication outages. Since there are no normally functioning ground base stations, drones rely solely on satellite access to the communication network. 4) Option 4: The strategy proposed in this paper is to dispatch drones as emergency base stations to restore the communication capabilities of nodes with communication interruptions. Drones can access the communication network through satellites and normally functioning ground base stations.

[0091] Please see Figure 3 Of these, drone 3 was equipped with a satellite communication terminal, while the other drones could not establish a direct communication link with the satellite. The power distribution system required three steps to reach maximum load restoration, all of which required satellite communication support. Ultimately, 43.56MW of load in the power distribution system was restored.

[0092] Table 2 compares the working schemes for each step in scenarios where satellite communication is supported and not supported: Please see Figure 4In Scheme 1, the power distribution system master station can only control the opening and closing of some lines through remotely operated switches with normal communication, resulting in a load restoration of only 12.04 MW. In Scheme 2, the UAV can only access the communication network through a normally functioning ground base station, ultimately restoring 23.06 MW of load, a load restoration level far lower than the scheme supported by satellite resources. In Scheme 3, the final restoration level is the same as Scheme 4, but the load restoration speed is slower than Scheme 4. In Scheme 4, the UAV has the ability to access both satellite and ground base station emergency communication networks. On the one hand, it can support the priority restoration of critical loads through distributed deployment; on the other hand, in the scenario of satellite link failure, it can rely on ground base station resources to achieve partial load power restoration control. Through comparison, it can be seen that compared with other methods, the proposed method fully utilizes the emergency communication functions of satellite, UAV, and ground base station, achieving better load restoration results.

[0093] As the number of dispatched drones increases, a comparison of the solution time between the method of this invention and the method that does not employ regional division and drone grouping is shown in Table 3: Table 3 Comparison of solution time for different numbers of UAVs

[0094] Table 4 shows the node information for the IEEE-123 node power distribution system.

[0095] The line information for the IEEE-123 node power distribution system is shown in Table 5:

[0096] The power supply information for the IEEE-123 node power distribution system is shown in Table 6: Table 6 Power Supply Information for IEEE-123 Node Distribution System

[0097] This invention provides communication support for the recovery of power distribution systems by utilizing communication resources such as ground base stations, drones, and satellites, thereby enabling rapid post-disaster recovery of power distribution systems. By considering the establishment of communication links and the availability of communication resources, the optimal deployment scheme under the current conditions is selected. By rationally planning the drone scheduling path, the drone scheduling time is reduced, load loss during the recovery process is reduced, and the resilience of the power distribution system is improved.

[0098] In summary, this invention provides a method and system for post-disaster load restoration of power distribution systems using coordinated air-space-ground communication resources. It fully considers the cyber-physical coupling characteristics during the power distribution system restoration process, utilizing satellite, UAV, and ground base station resources to establish temporary communication networks for communication interruption nodes in the power distribution system. This network coordinates with the topology reconstruction of the power distribution system and works in conjunction with UAV dispatch path planning, enabling rapid and orderly load restoration of the power distribution system after a disaster. This enhances the resilience of the power distribution system and effectively reduces power outage losses. Furthermore, the use of geographic-electrical map feature similarity for fault area segmentation significantly improves solution efficiency.

[0099] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0100] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0101] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0102] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0103] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0104] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0105] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random-access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0106] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0107] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0108] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0109] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for post-disaster load restoration of power distribution systems using space-air-ground communication resource coordination, characterized in that, Includes the following steps: S1. Obtain topology data, fault information, and communication resource availability information of the power distribution system, wherein the communication resources include satellites, UAV emergency base stations, and ground base stations; S2. Based on the topology data, fault information, and communication resource availability information, establish a power distribution system post-disaster load recovery model that includes multiple recovery phases executed sequentially. The power distribution system post-disaster load recovery model includes a UAV deployment location optimization model and a UAV dispatch path model. S3. In each recovery phase, based on the current operating status of the power distribution system and the availability of communication resources, solve the UAV deployment location optimization model. Under the constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, determine the UAV target deployment location, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status. S4. Based on the current location of the UAV, the target deployment location of the UAV, and the availability of communication resources, solve the UAV dispatch path model, and determine the UAV dispatch path and load recovery time under the constraints of UAV dispatch path, endurance time, working time, and satellite link availability time. S5. Determine the recovery plans for satellite communication participation and satellite communication non-participation respectively. Select the recovery plan for the current recovery stage according to the weighted load loss corresponding to each recovery plan. Update the power distribution system operation status, communication resource availability status and UAV status according to the selected recovery plan, and enter the next recovery stage until there is no new recovery load. S6. Dispatch drones according to the recovery plan for each recovery stage, establish a communication link from the main station of the power distribution system to the communication interruption node through at least one of satellite link, ground base station link and relay link between drones, and control the power distribution system to perform topology reconstruction according to the line connection and disconnection status.

2. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources as described in claim 1, characterized in that, Before step S2, the method also includes obtaining the geographical location information of each node in the power distribution system; step S2 also includes: The geographical distance between nodes is determined based on the geographical location information of each node, and the fault-free electrical connection relationship between nodes is determined based on the topology data and fault information. The similarity between nodes is determined based on the geographical distance and fault-free electrical connection relationships, and a node similarity matrix is ​​constructed. Based on the node similarity matrix, spectral clustering is used to divide the power distribution system into multiple recovery areas, and the deployment locations of UAV targets in each recovery area are determined.

3. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources as described in claim 1, characterized in that, The UAV communication coverage constraints include: Only drone emergency base stations are allowed to establish communication links with communication interrupted nodes located within their communication coverage area; The number of communication interruption nodes connected to each drone emergency base station shall not exceed the first preset number; The number of communication interrupted nodes restored in each recovery phase shall not exceed the second preset number; Each communication interruption node can establish a communication link with at most one drone emergency base station.

4. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources as described in claim 1, characterized in that, The drone deployment location optimization model also includes communication quality constraints; The communication quality constraints include: determining the signal-to-interference-plus-noise ratio (SIR) between the UAV emergency base station and the communication interruption node based on the channel gain, signal transmission power, noise power, and interference signals between the UAV emergency base station, the ground base station, and the communication interruption node, and limiting the SIR to not be lower than a preset SIR threshold.

5. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources according to claim 1, characterized in that, The communication link connectivity constraints include: Emergency base stations for unmanned aerial vehicles (UAVs) equipped with satellite communication terminals are connected to the main power distribution system station via satellite links; and / or, The drone emergency base station is connected to the power distribution system master station through a normally functioning ground base station; and / or, The UAV emergency base station connects to a satellite or a normally functioning ground base station via a multi-hop relay link formed by one or more other UAV emergency base stations, thus forming a complete communication link from the power distribution system master station to the communication interruption node.

6. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources according to claim 1, characterized in that, The line switching control constraints include: Keep the faulty line disconnected; Only remote switches corresponding to power distribution system nodes that have a complete communication link with the power distribution system master station are allowed to change their open / closed status; For power distribution system nodes whose communication links are interrupted, after the power distribution system node connects to the power distribution system master station through the UAV emergency base station, the corresponding remote switch is allowed to change its open / closed state.

7. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources according to claim 1, characterized in that, The topology constraints of the power distribution system are used to limit the power distribution system to form at least one radial microgrid powered by a power source node through line switching control. The operating constraints of the power distribution system include node active power balance constraints, node reactive power balance constraints, node voltage constraints, power output constraints, and line transmission capacity constraints. The drone deployment location optimization model aims to maximize the sum of the products of the recovery load power and the corresponding load weight of each load node, while minimizing the number of drones called up.

8. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources according to claim 1, characterized in that, The drone dispatch path constraints include: For each drone to be dispatched, a dispatch path is determined from its current location to the corresponding drone target deployment location, and each drone target deployment location corresponds to one drone. Determine whether the drone is capable of completing the current recovery phase based on its flight time, hovering time, and remaining flight time. If the remaining flight time of the drone is insufficient to complete the work of the current recovery phase, the corresponding drone shall return to the drone warehouse to replace the battery and then fly to the target deployment location of the drone.

9. The method for post-disaster load restoration of a power distribution system based on the collaborative use of space-air-ground communication resources as described in claim 8, characterized in that, For drones that access the power distribution system master station via satellite link, the satellite link availability time constraint is used to limit the overlap between the drone's working time and at least one satellite availability time window to be no less than the preset time required to complete the line control operation. The load recovery time for each load node is determined based on the time required for the upstream communication interruption node in the power supply path of each load node to access the communication network. The weighted load loss includes the load loss corresponding to the unrecovered load during the current recovery phase and the load loss corresponding to the recovered load before recovery. The UAV dispatch path model takes the minimization of the weighted load loss as its optimization objective.

10. A post-disaster load recovery system for a power distribution system that coordinates air-space-ground communication resources, characterized in that, The system includes a processor, a memory, and a communication interface. The memory stores a program executed by the processor, and the communication interface is used for data interaction with the power distribution system master station, the UAV emergency base station, and the ground base station. When the processor executes the program, it implements the following: Acquire topology data, fault information, and communication resource availability information of the power distribution system, including satellites, UAV emergency base stations, and ground base stations; Based on the topology data, fault information, and communication resource availability information, a power distribution system post-disaster load recovery model is established, which includes multiple recovery phases executed sequentially. The power distribution system post-disaster load recovery model includes a UAV deployment location optimization model and a UAV dispatch path model. In each recovery phase, the UAV deployment location optimization model is solved based on the current power distribution system operation status and communication resource availability. Under the constraints of UAV communication coverage, communication link connectivity, line switching control, power distribution system topology, and power distribution system operation, the target deployment location of the UAV, the communication link from the power distribution system master station to the communication interruption node, the line switching status, and the load recovery status are determined. The drone dispatch path model is solved based on the current location of the drone, the target deployment location of the drone, and the availability of communication resources. Under the constraints of drone dispatch path, endurance time, working time, and satellite link availability time, the drone dispatch path and load recovery time are determined. The recovery plans are determined separately for satellite communication participation and satellite communication non-participation. The recovery plan for the current recovery stage is selected based on the weighted load loss corresponding to each recovery plan. The operation status of the power distribution system, the availability status of communication resources, and the status of the UAV are updated according to the selected recovery plan, and the next recovery stage is entered until there is no new recovery load. The recovery scheme for each recovery stage is output through the communication interface, so that the UAV can establish a communication link from the power distribution system master station to the communication interruption node through at least one of the satellite link, ground base station link and relay link between UAVs, and the power distribution system master station controls the power distribution system to perform topology reconstruction according to the line opening and closing status.

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