Power distribution network fault recovery method and device considering unmanned aerial vehicle communication recovery

Abstract

The invention provides a power distribution network fault recovery method and device considering unmanned aerial vehicle communication recovery. The method comprises the following steps: constructing a first active power distribution network fault recovery model not involving fault repair and a second active power distribution network fault recovery model involving fault repair; determining a fault information blind area in the power distribution network; according to the first active power distribution network fault recovery model, carrying out first-stage temporary power supply recovery on the information blind area; establishing an unmanned aerial vehicle emergency communication model; obtaining an unmanned aerial vehicle deployment scheme according to the unmanned aerial vehicle emergency communication model, and controlling the unmanned aerial vehicle to establish temporary communication for the corresponding information blind area; after the temporary communication is established, performing second-stage temporary power supply recovery for the information blind area according to the first active power distribution network fault recovery model; after temporary power supply recovery in the second stage, according to a second active power distribution network fault recovery model, determining a line first-aid repair scheme to carry out first-aid repair on the fault line; the method can improve the reliability of power distribution network fault recovery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network, and particularly relates to a power distribution network fault recovery method and device considering unmanned aerial vehicle (UAV) recovery communication. BACKGROUND

[0002] With large-scale access of new types of sources and loads such as distributed power sources and electric vehicles, the physical structure and power flow distribution of the power distribution network have changed significantly, the role of the information layer in grid regulation has become increasingly prominent, and the coupling degree between the power physical system and the information system has been further deepened. In the normal operating state, such close coupling helps to ensure the safety and reliability of the power system. However, in extreme disaster conditions, the deep coupling characteristics will amplify system vulnerability, making the power distribution system face more complex challenges. The traditional power distribution network recovery strategy has been difficult to meet the needs under the new situation, and how to achieve efficient recovery in the communication and physical system compound failure scenario has become an important direction and difficult problem for future research.

[0003] The patent text CN120150124A discloses a power distribution network information-physical coupling recovery method considering unmanned aerial vehicle ad hoc network, comprising the following steps: obtaining the topology structure, system parameters, line fault points, information of communication failure points and initial position of the unmanned aerial vehicle of the power distribution network; in the first stage, based on the communication link of the unmanned aerial vehicle, an unmanned aerial vehicle working point deployment model is established to solve the unmanned aerial vehicle working point position; in the second stage, the unmanned aerial vehicle working point position obtained in the first stage, the topology structure, system parameters, line fault points, information of communication failure points and initial position data of the unmanned aerial vehicle of the power distribution network are combined with the unmanned aerial vehicle communication link networking and transmission flow to establish an information-physical coupling recovery model; the unmanned aerial vehicle working point deployment model takes the number of deployed unmanned aerial vehicle working points and minimization of hovering energy consumption as the target; the information-physical coupling recovery model takes the number of dispatched unmanned aerial vehicles, dispatching path, hovering energy consumption and minimization of power distribution network weighted active load loss as the target; in the information-physical coupling recovery model, the state of the communication node of the power distribution network is associated with the switch state of the power distribution network automation terminal; the communication node and the load access state in the power distribution network are associated with the active load loss of the power distribution network; the dispatching scheme of the unmanned aerial vehicle is associated with the state of the communication node in the power distribution network; the information-physical coupling recovery model is solved to obtain the number of dispatched unmanned aerial vehicles and the optimal dispatching path, so as to recover the active load loss of the power distribution network as soon as possible. However, the constraint model of the unmanned aerial vehicle in this method is too much, the control is complex, and the reliability is not high. SUMMARY

[0004] The present application provides a power distribution network fault recovery method and device considering unmanned aerial vehicle emergency communication, which can improve the reliability of power distribution network fault recovery.

[0005] A power distribution network fault recovery method considering unmanned aerial vehicle recovery communication, comprising: construct a first active power distribution network fault recovery model not involving fault repair and a second active power distribution network fault recovery model involving fault repair; determine an information blind area in which a fault occurs in the power distribution network; perform first-stage temporary power restoration for the information blind area according to the first active power distribution network fault recovery model; establish an unmanned aerial vehicle emergency communication model according to the information blind area and constraint conditions in the unmanned aerial vehicle scheduling process; obtain an unmanned aerial vehicle deployment scheme according to the unmanned aerial vehicle emergency communication model, and control the unmanned aerial vehicle to establish temporary communication for the corresponding information blind area according to the unmanned aerial vehicle deployment scheme; after the temporary communication is established, perform second-stage temporary power restoration for the information blind area according to the first active power distribution network fault recovery model; after the second-stage temporary power restoration, determine a line repair scheme according to the second active power distribution network fault recovery model, and repair the fault line in the information blind area based on the line repair scheme.

[0006] A power distribution network fault recovery device considering unmanned aerial vehicle recovery communication, comprising: a recovery model construction module configured to construct a first active power distribution network fault recovery model not involving fault repair and a second active power distribution network fault recovery model involving fault repair; a fault identification module configured to determine an information blind area in which a fault occurs in the power distribution network; a first-stage control module configured to perform first-stage temporary power restoration for the information blind area according to the first active power distribution network fault recovery model; a communication model construction module configured to establish an unmanned aerial vehicle emergency communication model according to the information blind area and constraint conditions in the unmanned aerial vehicle scheduling process; a communication control module configured to obtain an unmanned aerial vehicle deployment scheme according to the unmanned aerial vehicle emergency communication model, and control the unmanned aerial vehicle to establish temporary communication for the corresponding information blind area according to the unmanned aerial vehicle deployment scheme; a second-stage control module configured to, after the temporary communication is established, perform second-stage temporary power restoration for the information blind area according to the first active power distribution network fault recovery model; a repair control module configured to, after the second-stage temporary power restoration, determine a line repair scheme according to the second active power distribution network fault recovery model, and repair the fault line in the information blind area based on the line repair scheme.

[0007] An electronic device comprising a processor and a memory, the memory storing a plurality of instructions, and the processor being configured to read the instructions and perform the above method.

[0008] The power distribution network fault recovery method and device considering unmanned aerial vehicle recovery communication provided by the application have at least the following beneficial effects: (1) Under the constraint of limited unmanned aerial vehicle resources, an unmanned aerial vehicle emergency communication model is constructed with the priority of blind area load as the optimization target to determine the optimal deployment position of the unmanned aerial vehicle and the configuration scheme of the number of unmanned aerial vehicles required by each information blind area. Then, by coordinating the schedulable resources of the information blind area and the non-information blind area, island division and network topology reconstruction are simultaneously implemented to realize the collaborative optimization of the unmanned aerial vehicle deployment scheme, the temporary recovery scheme and the repair dispatching, thereby maximizing the short-time load recovery amount and improving the reliability of power distribution network fault recovery; (2) The temporary emergency communication network is quickly established by the unmanned aerial vehicle, and combined with the joint optimization strategy of island division and network reconstruction, the temporary power supply of the power failure load in the information blind area is quickly realized, the power failure time is minimized, and the maximization of the short-time load recovery amount is realized; (3) The complete recovery time of the power failure load is effectively shortened, and a higher load recovery rate is realized in the same recovery period. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 The flowchart of one embodiment of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0010] Figure 2 The schematic diagram of one embodiment of the communication coverage range of the unmanned aerial vehicle in the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0011] Figure 3 The schematic diagram of the power distribution network topology in one application scenario of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0012] Figure 4 The schematic diagram of the initial recovery topology of the power distribution network in one application scenario of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0013] Figure 5 The schematic diagram of the emergency recovery situation in one application scenario of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0014] Figures 6(a) to 6(d) The schematic diagram of the repair process in one application scenario of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0015] Figure 7 The schematic diagram of the comparison between the application and the prior art in one application scenario of the power distribution network fault recovery method considering unmanned aerial vehicle recovery communication provided by the application.

[0016] Figure 8 FIG. 1 is a structural schematic diagram of an embodiment of a power distribution network fault recovery device considering unmanned aerial vehicle (UAV) recovery communication provided by the present application. DETAILED DESCRIPTION

[0017] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in combination with the accompanying drawings and specific embodiments.

[0018] Reference Figure 1 In some embodiments, a power distribution network fault recovery method considering unmanned aerial vehicle (UAV) recovery communication is provided, comprising: S1, constructing a first active power distribution network fault recovery model not involving fault repair and a second active power distribution network fault recovery model involving fault repair; S2, determining an information blind area in which a fault occurs in the power distribution network; S3, according to the first active power distribution network fault recovery model, performing first-stage temporary power restoration for the information blind area; S4, according to the information blind area and constraint conditions in the UAV dispatching process, establishing an UAV emergency communication model; S5, according to the UAV emergency communication model, obtaining a UAV deployment scheme, and controlling the UAV to establish temporary communication for the corresponding information blind area according to the UAV deployment scheme; S6, after the temporary communication is established, performing second-stage temporary power restoration for the information blind area according to the first active power distribution network fault recovery model; S7, after the second-stage temporary power restoration, determining a line repair scheme according to the second active power distribution network fault recovery model, and repairing the fault line in the information blind area based on the line repair scheme.

[0019] Specifically, in step S4, according to the information blind area and constraint conditions in the UAV dispatching process, the UAV emergency communication model is established, comprising: S41, according to the height of the UAV and the communication sensing range angle, establishing a UAV communication coverage radius constraint; S42, according to the endurance time of the UAV, establishing a UAV time constraint; S43, according to the flight line planning of the UAV, establishing a UAV space constraint; S44, according to the positions of the feeder terminal units (FTU) in the information blind area and the values and emergency degrees of the loads controlled by the FTUs, establishing a UAV phased coverage model; S45. The UAV communication coverage radius constraint, UAV time constraint, UAV space constraint, and the UAV phased coverage model constitute the UAV emergency communication model.

[0020] Specifically, in step S41, the communication coverage radius of the UAV is the product of the UAV's hovering altitude and the tangent of the angle of the communication sensing range.

[0021] The communication coverage of a single UAV at candidate docking point j is as follows Figure 2 As shown. By Figure 2 It can be seen that the communication coverage of a UAV is related to its hovering altitude h, coverage radius R, and the angle θ of the UAV's maximum sensing range (assuming that each UAV has the same hovering altitude, recovery radius, and maximum sensing angle). Therefore, the formula for calculating the altitude of the UAV is shown in equation (1): (1) Among them, h j R represents the altitude at which the drone hovers at candidate docking point j. j θ represents the communication coverage radius of the UAV at candidate docking point j. j This indicates the maximum sensing range angle of the drone at candidate docking point j.

[0022] Furthermore, in step S42, the drone time constraint includes the drone's mission duration being less than its maximum endurance, and the drone's mission duration being the sum of its flight time, hovering time, and the time it takes to establish temporary communication.

[0023] Specifically, after an extreme disaster occurs, the drone receives instructions to depart from node i and travel to candidate docking point j in the information blind zone. The flight time is... (The optimal path has been planned to achieve the following) (It is the shortest time between two nodes), the time to establish temporary communication is The time spent hovering in the air is The maximum flight time of the drone during the fault recovery period is The UAV departs from the emergency warehouse at time T0 and returns to the emergency warehouse at time T1. The time constraints of the UAV are shown in equations (2) and (3): (2) (3) Where T1-T0 is the duration of the UAV's mission, Equation (2) indicates that the time difference between the UAV's final return to the emergency warehouse and its departure from the emergency warehouse (the duration of the mission) should be less than the maximum endurance of the UAV during the fault recovery period; Equation (3) indicates the flight time of the UAV. , The time for the drone group to establish temporary communication , the air suspension time of the UAV The sum of the three times is equal to the time difference between the final return of the UAV to the emergency warehouse and the departure from the emergency warehouse.

[0024] Further, in step S43, the UAV space constraints include single or double trips of the UAV from the starting emergency warehouse to the candidate stopping point, single trips of the UAV between candidate stopping points, and the UAV flying to the next candidate stopping point after completing the line repair in the current information blind area, as follows: ; (4) ; (5) ; (6) wherein z represents the emergency warehouse point; x i,j,u represents whether the UAV u departs from the candidate stopping point i to the candidate stopping point j, which is a 0-1 variable, x i,j,u =1 represents that the UAV u departs from the candidate stopping point i to the candidate stopping point j, x i,j,u =0 otherwise; represents the set of fault lines in the information blind area; y j,K,u represents that the FTU device of the information blind area is covered by the UAV u at the candidate stopping point j in a temporary communication mode K, which is a 0-1 variable, y j,K,u =1 represents that it is covered, otherwise y j,K,u =0. x j,i,u represents whether the UAV u departs from the candidate stopping point j to the candidate stopping point i, x z,j,u represents whether the UAV u departs from the emergency warehouse point z to the candidate stopping point j, x j,z,u represents whether the UAV u departs from the candidate stopping point j to the emergency warehouse point z, x j,K,u represents whether the UAV u departs from the candidate stopping point j to establish temporary communication K coverage, all of which are 0-1 variables. mn represents the fault line, G mn represents whether the fault line is repaired, 1 represents that the repair is completed, and 0 represents that the repair is not completed.

[0025] Formula (4) represents that the UAV can be double or single from the emergency warehouse to the candidate stopping point. Formula (5) represents that the UAV can only be single from the candidate stopping point (non-emergency warehouse point) to the candidate stopping point. Formula (6) represents that the UAV will only go to the next area for communication recovery when all the fault lines in the coverage area are repaired.

[0026] Further, in step S44, according to the position of the FTU device in the information blind area and the value and emergency degree of the load controlled by the FTU device, a UAV staged coverage model is established, including: According to the position coordinates of the FTU device, the planar position coordinates of the unmanned aerial vehicle at the candidate landing point, the distance between the planar position of the unmanned aerial vehicle and the FTU device is calculated; According to the unmanned aerial vehicle communication coverage radius constraint and the distance between the planar position of the unmanned aerial vehicle and the FTU device, the unmanned aerial vehicle communication range constraint is established; According to the value and emergency degree of the load controlled by the FTU device, the priority weight of the FTU device is generated; According to the unmanned aerial vehicle communication range constraint and the priority weight, a first objective function and its constraint condition considering the priority weight and aiming at completely covering the information blind area are established, and the unmanned aerial vehicle phased coverage model is obtained.

[0027] Specifically, according to the occurrence position of the fault in the power distribution network, a set of information blind areas R is obtained, and each information blind area r∈R; the emergency communication mode is an unmanned aerial vehicle, denoted as K; and a set of candidate landing points is J.

[0028] In the power distribution network physical system, whether the FTU device associated with the physical node (or tie switch) is covered by the unmanned aerial vehicle communication, needs to meet the communication range constraints of formula (7) to formula (8): ; (7) ; (8) Where (x j , y j ) represents the planar position coordinates of the candidate landing point, (x a , x b ) represents the position coordinates of the FTU device in the information blind area; d aj represents the distance between the associated FTU device and the planar position of the unmanned aerial vehicle; y ajK represents whether the FTU device a in the information blind area is covered by the unmanned aerial vehicle communication of the candidate landing point j, which is a 0-1 variable, y ajK =1 indicates that it is covered, otherwise y ajK =0; L jK represents the coverage range of the unmanned aerial vehicle at the candidate landing point j, which is determined by the communication coverage radius R j of the unmanned aerial vehicle; A represents the set of FTU devices.

[0029] Further, the blind area coverage priority is defined, and the priority weight p r is generated according to the value q r and the emergency degree v of the load controlled by the FTU device in the information blind area r, that is, p r =q r ×v.

[0030] The emergency communication model of the UAV cooperation is established. Since the number of UAVs is limited, the target of the emergency communication deployment of the UAV cooperation is to seek the maximum of the total value of the controlled load in the covered information blind area. The target function and the constraint condition are obtained by improving the maximum coverage model, i.e. the UAV phased coverage model, as shown in the following: (9) wherein z r represents whether the information blind area r is completely covered, z r =1 represents that the information blind area r is completely covered, otherwise z r =0; p r represents the priority weight; max f 1 represents the first target function; x jK represents whether the UAV emergency communication K is deployed at the candidate stopping point j, which is a 0-1 variable, x jK =1 represents that the UAV emergency communication K is deployed at the candidate stopping point j, otherwise x jK =0; N UAV is the number of UAVs; a rj represents whether the UAV at the candidate stopping point j can cover the FTU device in the information blind area r, which is a 0-1 variable, a rj =1 represents that the UAV at the candidate stopping point j can cover the FTU device in the information blind area r, otherwise a rj =0; Nr represents the number of UAVs required to completely cover each information blind area r, R represents the set of information blind areas, y rajK represents whether the FTU device a of the information blind area r is covered by the UAV of the candidate stopping point j with the temporary communication K.

[0031] In summary, the obtained UAV emergency communication model includes the constraint condition and the first target function shown in formula (1) to formula (9).

[0032] In step S4, the emergency communication model is solved by an optimization algorithm, such as a particle algorithm or a genetic algorithm, to obtain a UAV deployment scheme according to the priority weight order and the coverage of the information blind area. According to the priority order, the number of UAVs required for each information blind area, and the driving path of each UAV, the UAV establishes a temporary communication for the corresponding information blind area.

[0033] Further, in step S1, a first active power distribution network fault recovery model not involving fault repair is constructed, including: S11, a second target function with the minimum loss of power failure is established according to the importance of each load node in the power distribution network, the power supply situation, the active power, and the cost coefficient of the power failure load; S12, an operation constraint condition satisfying the radial operation of the power distribution network is constructed; S13. Based on the allowable load reduction power and coefficient in the distribution network, establish controllable load constraints. S14. Establish energy storage constraints based on the remaining capacity and charging / discharging power of energy storage devices in the power distribution network that can supply power to the power outage loads. S15. Establish power flow balance constraints and node voltage constraints after the distribution network fault recovery. S16. The second objective function, operating constraints, controllable load constraints, energy storage constraints, power flow balance constraints, and node voltage constraints constitute the first active distribution network fault recovery model.

[0034] Specifically, in step S11, a first active distribution network fault recovery model is established that does not involve fault repair. This mainly includes two stages. In the first stage, after a fault occurs, distributed power sources or energy storage devices that are not in information blind spots and have stable islanding capabilities are prioritized to restore power to some of the lost loads. In the second stage, through a hierarchical and zoned strategy, after temporary restoration of communication in information blind spots, distributed power sources are dynamically managed to achieve full restoration of the lost loads.

[0035] Both phases employ a joint optimization method of islanding and network reconfiguration. Based on the importance of each load node in the distribution network, power supply status, active power, and cost coefficient of the power outage load, a second objective function is established to minimize the power outage loss. (10) Among them, T M Δt represents the total number of time periods during which all drones establish temporary communication networks upon arriving at candidate docking points; Δt represents the length of the time interval t; c1 represents the cost coefficient of the power outage load in the distribution network; w k Indicates the importance of load node k; b k Indicates whether the distribution network supplies power to load node k; it is a 0-1 variable, b. k =1 indicates that the distribution network is not supplying power to load node k; N represents the total number of load nodes in the distribution network; P k,t This represents the active power consumed by load node k during time period t, min. f 2 represents the second objective function.

[0036] Furthermore, in step S12, the operating constraints for radial operation of the distribution network are as follows: (11) Where g represents the topology in the distribution network fault recovery scheme; G is the set of all topologies that satisfy the radial operation of the distribution network.

[0037] Furthermore, in step S13, some load users have agreements with the power supply company allowing them to moderately reduce their load during peak or fault periods, provided that normal power consumption is not affected. The controllable load constraints are as follows: (12) (13) Where, β k This represents the agreement coefficient between load node k and the local power supply company, and is a 0-1 variable; e k,t e represents the load reduction factor of load node k during time period t. k,t ∈[0,1]; , P represents the active power and reactive power reduction at load node k during time period t, respectively. k,t Q represents the active power of the load node. k,t This represents the reactive power of the load node.

[0038] Furthermore, in step S14, the energy storage device can effectively alleviate the problem of fluctuating wind and solar power output. During fault recovery, planned islanded power supply relies on energy storage for regulation, which can both store excess energy and supplement the load when output is insufficient. Its operation must meet capacity and charging / discharging power constraints; that is, energy storage constraints include remaining capacity constraints and charging / discharging power constraints. The remaining capacity constraints are as follows: (14) (15) in, These represent the capacity of the energy storage device at load node k and the remaining energy during time period t, respectively. These represent the initial, minimum, and maximum values ​​of the charge level of the energy storage device at load node k, respectively. These refer to the charging efficiency and discharging efficiency of the energy storage device, respectively. Let represent the charging power and discharging power of load node k during the time interval t-1, respectively, and let ΔT represent the length of the time interval t.

[0039] Furthermore, the charging and discharging power constraints are as follows: (16) (17) (18) in, These represent the charging and discharging states of load node k during time period t, respectively, and are both 0-1 variables; These represent the maximum charging power and maximum discharging power limits of load node k during time period t, respectively. These represent the charging power and discharging power of load node k during time period t, respectively.

[0040] Furthermore, in step S15, the power flow balance constraint includes the power balance constraint. The power balance constraint of each node in the distribution network after fault recovery is as follows: (19) (20) Among them, P L,k and Q L,k These represent the active and reactive power injected at load node k, respectively; a positive value indicates that the power is flowing into load node k. k and U f D represents the voltage at load node k and load node f; kf Let B be the conductance of the branch between load node k and load node f. kf The susceptance is the voltage across the branch between load node k and load node f. P represents the voltage phase angle difference between load node k and load node f. pv,k Let P be the active power generated by the distributed power source at load node k. k Q represents the active power consumed at load node k. pv,k Q represents the reactive power generated by the distributed power source at load node k. k This represents the reactive power consumed at load node k.

[0041] When the power flow of the distribution network system reaches equilibrium, the power flow balance constraints satisfied by each branch also include: ;(twenty one) Among them, P kf P represents the active power flowing along the branch from load node k to load node f. kf,max This represents the maximum active power allowed to flow on the branch from load node k to load node f.

[0042] After fault recovery, the node voltages of the distribution network system need to be limited by a range, i.e., the node voltage constraints are: ;(twenty two) Among them, U k,max and U k,min These represent the upper and lower limits of the voltage amplitude at load node k after fault recovery, respectively. k Let be the voltage at load node k.

[0043] In step S16, the second objective function, operating constraints, controllable load constraints, energy storage constraints, power flow balance constraints, and node voltage constraints constitute the first active distribution network fault recovery model.

[0044] Further, in step S3, based on the first active distribution network fault recovery model, a first-stage temporary power restoration is performed for the information blind spot, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone, solve the first active distribution network fault recovery model, obtain a first temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the first temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone to temporarily restore power supply to the power-loss loads in the information blind zone. In step S6, a second phase of temporary power restoration is performed for the information blind spot based on the first active distribution network fault recovery model, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone, solve the first active distribution network fault recovery model, obtain a second temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the second temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone to temporarily restore power to the power-loss loads in the information blind zone.

[0045] Specifically, before the UAV establishes emergency communication, an optimization algorithm is used to solve the first active power distribution network fault recovery model. This yields a first temporary recovery scheme that satisfies the above constraints and minimizes power loss. Based on this scheme, distributed power sources or energy storage devices with stable islanding capabilities in non-information blind spots are used to restore power to some of the lost loads. After the UAV establishes emergency communication, distributed power sources and / or energy storage devices with stable islanding capabilities within the information blind spots are used to temporarily restore power to the lost loads in those blind spots. Through a hierarchical and zoning strategy, distributed power sources are dynamically managed to achieve full recovery of the lost loads.

[0046] Further, in step S1, a second active distribution network fault recovery model involving fault repair is constructed, including: S17. Based on the restoration cost, repair time, and travel time to the faulty line for each faulty line, construct a third objective function with the goal of minimizing the power loss load in the shortest possible time. S18. Establish a fourth objective function that minimizes the total repair time. S19. Based on the emergency repair resources and the emergency repair time, establish emergency repair resource constraints and fault time constraints; S110, the third objective function, the fourth objective function, emergency repair resource constraints, fault time constraints, operation constraints, controllable load constraints, energy storage constraints, power balance constraints, power flow balance constraints, and node voltage constraints constitute the second active distribution network fault recovery model.

[0047] Specifically, a second active distribution network fault recovery model is established during the fault repair process. Due to the large number of faults and the existence of unknown physical faults in the information blind spots, new faults may occur during the repair period, so a phased strategy is adopted. Under the condition of different fixed repair time and travel time, the focus is on minimizing the economic loss of power load in the shortest time. In order to determine the priority repair lines, it is necessary to use distribution network simulation to quantitatively compare the restoration cost and load restoration amount of different lines, so as to reasonably rank the repair priorities. The established third objective function is shown in equations (23) and (24).

[0048] ;(twenty three) ;(twenty four) Where μ is the weighting coefficient for emergency repair time, which can be 1000; T represents the total number of fault recovery periods; △t s Indicates t s Length of the time interval; This indicates the simulated emergency repair. The recovery cost obtained in time period t+1 after a faulty line; f t+1 n represents the minimum recovery cost obtained in time period t+1. ''' This indicates the number of faulty lines remaining in time period t; To simulate emergency repairs The sum of the travel time and repair time used for each faulty line, where c1 represents the cost coefficient of the power outage load in the distribution network; w k Indicates the importance of load node k; b k Indicates whether the distribution network supplies power to load node i; it is a 0-1 variable, b. k =1 indicates that the distribution network is not supplying power to load node k; N represents the total number of load nodes in the distribution network; P k,t This represents the active power consumed by load node k during time period t, min. f 3 represents the third objective function.

[0049] To guide a drone to the next information blind spot, one of the following two conditions must be met: 1) After all faulty lines in the information blind spot covered by the drone have been repaired, the circuit breakers on both sides of the lines can close normally; 2) The information blind spot is caused by the base station losing power. After communication is temporarily restored, the power source in the guidance area supplies power to restore communication in that area.

[0050] Once all power outage loads in the physical system have been restored, the repair sequence should be arranged to minimize the time required. The established fourth objective function is shown in equation (25): (25) Among them, Ts a Indicates physical repair team s a The time required to complete the remaining emergency repair tasks is the sum of the travel time of the physical repair team on their way to complete the remaining repair tasks and the time spent repairing the faulty line. f 4 represents the fourth objective function.

[0051] The constraints of the second active distribution network fault recovery model include equations (11)-(22), namely, operation constraints, controllable load constraints, energy storage constraints, power balance constraints, power flow balance constraints and node voltage constraints. At the same time, constraints on physical emergency repair arrangements are added as shown in equations (26)-(31).

[0052] Emergency repair resources include physical repair teams; constraints on emergency repair resources: G mn,sa Let s be a matrix representing the physical repair team s a Are they responsible for emergency repairs of the faulty line (mn)? Physical emergency repair team (s) a When G is assigned to the faulty line mn, mn,sa The value is 1 in all cases and 0 in all other cases.

[0053] (26)

[0054] (27) (28) (29) Where S represents the number of physical repair teams; Represents the set of all faulty lines in the distribution network; g mn→pq,sa Indicates physical repair team s a The repair sequence is from faulty line mn to faulty line pq, and is a variable of 0 and 1, g mn→pq,sa =1 represents the physical repair team s a Strictly follow the repair sequence from faulty line mn to faulty line pq, g mn→pq,sa =0 indicates that the physical repair team did not follow the repair sequence from faulty line mn to faulty line pq. z represents the collection of physical repair teams; z represents the emergency warehouse; x sa,z,mn Variables are 0 and 1. x sa,z,mn=1 represents the physical repair team s a Depart from emergency warehouse z and head to the faulty line mn. x sa,z,mn =0 indicates the physical repair team s a The route does not start from emergency warehouse z and proceed to the faulty line mn. x sa,mn,z Variables are 0 and 1. x sa,mn,z =1 represents the physical repair team s a Return from the faulty line mn to the emergency warehouse z. x sa,mn,z =0 indicates the physical repair team s a No team returned to the emergency warehouse z from the faulty line mn. Equation (26) indicates that the faulty line can only be repaired by one repair team. Equation (27) indicates that the repair teams carry out fault repairs in a strict order. Equation (28) ensures that the repair team starts from the emergency warehouse; Equation (29) indicates that the repair team will eventually return to the emergency warehouse.

[0055] Failure time constraints: (30)

[0056] (31) in, They represent the emergency repair team s a The start and end times of repairing the physically faulty line mn; Indicates the emergency repair team s a The time spent repairing the physically faulty line mn; Indicates the emergency repair team s a The time taken from faulty line mn to faulty line pq; T now Indicates the current moment, G mn This indicates whether the line needs emergency repair (mn).

[0057] Furthermore, a line repair plan is determined based on the second active distribution network fault recovery model, and repairs are carried out on the faulty lines in the information blind spot based on the line repair plan, including: Solve the second active distribution network fault recovery model to obtain the repair sequence of all faulted lines, and repair the faulted lines in each information blind zone according to the repair sequence.

[0058] The method proposed in this embodiment will be further explained through specific application scenarios below.

[0059] Taking the communication network and the improved IEEE 33-node distribution network system as an example, the constructed fault recovery model is validated. Fault scenarios of the distribution network's communication and physical networks after extreme natural disasters are as follows: Figure 3As shown. Figure 3 In this example, the emergency warehouse is located at node 12, and the system power outage load cost factor is taken as 15 yuan / (kW·h). The load importance and load type of each node are shown in Tables 1 and 2. In the physical network, distributed power sources are connected to nodes 13, 17, 21, 24, and 30. Among them, photovoltaic energy storage devices are connected to nodes 17, 21, and 24, and wind energy storage devices are connected to nodes 13 and 30. The energy storage device has a capacity of 100 kW·h and a rated power of 20 kW. Two physical repair teams are set up, starting from the emergency warehouse. It is assumed that the processing time for each fault is set to 40 minutes. It is also assumed that the UAV flight speed is 80 km / h, the UAV communication coverage radius is 3 km, the number of main UAVs is 3, and the system's candidate docking points are nodes 5, 6, 17, 20, 21, 24, 25, and 30.

[0060] Assume an extreme natural disaster occurs at 9:30 AM. Six physical network failures occur on lines 4-5 (S1), 8-9 (S2), 15-16 (S3), 20-21 (S4), 23-24 (S5), and 26-27 (S6). The communication network has four failure points: communication nodes 2, 3, 4, and 8, each with sufficient backup power. This physical scenario simulates the most extreme case, assuming no backup power at the physical nodes. To effectively restore power, distributed power sources with black-start capability can form planned islands with some of the lost loads.

[0061] Table 1 Classification of Load Importance for Each Node

[0062] Table 2 Node Load Types

[0063] Fault recovery result analysis: To achieve efficient power restoration, the physical and communication network status information of the distribution network is first collected after a fault occurs. A joint optimization strategy integrating islanding and network reconfiguration is then employed for fault handling. In cases where both communication and physical systems are damaged and repairs have not yet commenced, the initial restored topology is as follows: Figure 4 As shown.

[0064] Considering the rapid recovery of the drone's communication network: First, drones need to be dispatched to the target area to establish a temporary communication network to quickly restore communication capabilities. For example... Figure 5 As shown, this demonstrates the emergency recovery of the communication network with the assistance of drones.

[0065] Table 3 shows the travel time for drones to reach corresponding areas to restore information blind spots, using a tiered and zoned protection system. Drones travel to docking points 5, 21, and 24. The deployment time of the drones (i.e., a deployment time of 5 minutes) can be used to calculate the time required for each drone to establish an emergency communication network.

[0066] Table 3. Corresponding nodes visited by UAV communication equipment and travel time.

[0067] Active power distribution network fault recovery after temporary communication restoration in some blind areas: After temporary communication is restored in some blind spots, a joint optimization of island partitioning and network reconstruction is adopted to form the optimal recovery plan for the current stage.

[0068] As shown in Figure 6(c), the emergency repair work on physical lines 23-24 was completed at 11:08. At this time, all faulty lines within the information blind spot covered by UAV 3 had been repaired. The UAV flew from docking point 24 to docking point 17, a flight time of approximately 13.7 minutes, and deployed for 5 minutes at docking point 17. After the emergency repairs on lines 8-9 were completed, some connecting switches were closed and some sectional switches were opened. To ensure stable system operation, the switch states should be uniformly adjusted after all load nodes and faulty lines have been fully restored. During the physical network power restoration process and subsequent stages, communication maintenance personnel also need to be dispatched to repair communication faults to reduce the operating costs of the UAV.

[0069] Combination Figures 6(a) to 6(d) The fault recovery process of the physical system was analyzed. Since the optimization objective of the model was to restore the lost power load at the lowest cost, and different loads had varying importance, priority was given to restoring critical loads. Nodes 5, 6, 7, and 8 are secondary loads and should have their power restored first after temporary communication was restored. Nodes 6, 7, and 8 were integrated into the islanded system by closing relevant tie switches. Node 5 was not yet connected due to uncontrollable load and limited islanded power. By 11:00, lines 4-5 were repaired, restoring power to the critical load 5. At 11:08, repairs to lines 23-24 were completed, and islanded area 2 was connected to the grid. At 11:30, the UAV established a temporary communication network at docking point 17, restoring the FTUs associated with nodes 15, 16, 17, and 18 to normal operation. The master station issued an instruction to disconnect the sectionalizing switch at point 16 to isolate fault S3, and then sequentially closed tie switches 34, 36, and 37, connecting islanded area 3 to the grid. Ultimately, the process achieved load restoration for nodes 5, 15, 16, 17, 18, and 26.

[0070] Example scheme proposal and result comparison To verify the superiority of the fault recovery strategy proposed in this embodiment, under the premise of a large number of information blind spots, the fault recovery strategy of this embodiment is compared with the fault recovery strategy of manually restoring the communication network. The amount of power loss load restored at different times is as follows: Figure 7 As shown.

[0071] Option 1 is a power distribution network fault recovery strategy based on manual communication repair. Scheme 2 is the power grid fault recovery strategy proposed in this paper that considers emergency communication between UAVs and communication vehicles.

[0072] As shown in the figure, the post-disaster fault recovery time of Scheme 1 is significantly longer than that of Scheme 2. The main reason is that the communication network was not repaired in a timely manner, leading to a further expansion of the line fault area, requiring the physical repair team to invest more time in locating the fault point. Simultaneously, Scheme 1 has a large number of information blind spots in the initial recovery phase, making it impossible to grasp the operating status of the physical systems within these blind spots and to utilize multiple power sources to form stable islands for power restoration, resulting in a larger initial load loss. Even after the physical lines within the blind spots have been repaired, the system status information for that area cannot be obtained in a timely manner, and it is still necessary to wait for communication to be restored before reliably controlling the sectionalizing switches to close and restore power to the load. In contrast, Scheme 2 significantly shortens the time for complete recovery of the lost load and exhibits a higher load recovery rate within the same recovery period.

[0073] refer to Figure 8 In some embodiments, a power grid fault recovery device considering the restoration of communication by unmanned aerial vehicles is provided, comprising: The recovery model construction module 201 is used to construct a first active distribution network fault recovery model that does not involve fault repair and a second active distribution network fault recovery model that involves fault repair. Fault identification module 202 is used to determine the information blind spots where faults occur in the distribution network; The first-stage control module 203 is used to perform a first-stage temporary power restoration for the information blind spot based on the first active power distribution network fault recovery model. The communication model construction module 204 is used to establish an emergency communication model for UAVs based on the information blind spots and the constraints in the UAV scheduling process. The communication control module 205 is used to obtain a drone deployment plan based on the drone emergency communication model, and control the drone to establish temporary communication for the corresponding information blind spots according to the drone deployment plan; The second-stage control module 206 is used to temporarily restore power supply to the information blind spot in the second stage according to the first active power distribution network fault recovery model after establishing temporary communication. The emergency repair control module 207 is used to determine the line emergency repair plan according to the second active distribution network fault recovery model after the second phase of temporary power restoration, and to carry out emergency repair on the faulty lines in the information blind spot based on the line emergency repair plan.

[0074] Furthermore, the communication model construction module 204 establishes an emergency communication model for the UAV based on the information blind spot and the constraints in the UAV scheduling process, including: Establish constraints on the communication coverage radius of the UAV based on its altitude and the angle of its communication sensing range; Establish time constraints for the drone based on its flight time; Based on the flight path planning of the UAV, establish spatial constraints for the UAV; Based on the location of FTU devices in the information blind spot and the value and urgency of the load controlled by the FTU devices, a phased coverage model for UAVs is established. The drone communication coverage radius constraint, drone time constraint, drone space constraint, and drone phased coverage model constitute the drone emergency communication model.

[0075] Furthermore, the communication coverage radius of the UAV is the product of the UAV's hovering altitude and the tangent of the angle of the communication sensing range; The time constraints for the UAV include that the duration of the UAV's mission is less than the UAV's maximum endurance, and the duration of the UAV's mission is the sum of the UAV's flight time, hovering time, and the time for the UAV to establish temporary communication. The spatial constraints of the UAV include that the UAV can travel from the initial emergency warehouse to the candidate docking point in one or two ways, the flight of the UAV between the candidate docking points is one-way, and the UAV flies to the next candidate docking point after completing the line repair in the current information blind spot.

[0076] Furthermore, the communication model construction module 203 establishes a phased coverage model for the UAV based on the location of the FTU device in the information blind spot and the value and urgency of the load controlled by the FTU device, including: Based on the position coordinates of the FTU device and the planar position coordinates of the UAV at the candidate docking point, calculate the distance between the UAV's planar position and the FTU device; Based on the UAV communication coverage radius constraint and the distance between the UAV's planar position and the FTU device, establish the UAV communication range constraint; Priority weights for FTU units are generated based on the value and urgency of the loads controlled by the FTU units. Based on the UAV communication range constraints and priority weights, a first objective function and its constraints, considering the priority weights and aiming to completely cover the information blind spots, are established to obtain the UAV phased coverage model.

[0077] Furthermore, the recovery model construction module 201 constructs a first active distribution network fault recovery model that does not involve fault repair, including: Based on the importance of each load node in the distribution network, the power supply status, the active power, and the cost coefficient of the power outage load, a second objective function is established to minimize the power outage loss. Construct operational constraints that satisfy the radial operation of the distribution network; Establish controllable load constraints based on the allowable load reduction power and coefficient in the distribution network; Based on the remaining capacity and charging / discharging power of the energy storage devices in the power distribution network that can provide power to the power outage loads, energy storage constraints are established; Establish power flow balance constraints and node voltage constraints after distribution network fault recovery; The second objective function, operating constraints, controllable load constraints, energy storage constraints, power flow balance constraints, and node voltage constraints constitute the first active distribution network fault recovery model.

[0078] Furthermore, the first-stage control module 203, based on the first active power distribution network fault recovery model, performs a first-stage temporary power restoration for the information blind spot, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone, solve the first active distribution network fault recovery model, obtain a first temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the first temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone to temporarily restore power supply to the power-loss loads in the information blind zone. The second-stage control module 206 performs a second-stage temporary power restoration for the information blind spot based on the first active power distribution network fault recovery model, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone, solve the first active distribution network fault recovery model, obtain a second temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the second temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone to temporarily restore power to the power-loss loads in the information blind zone.

[0079] Furthermore, the recovery model construction module 201 constructs a second active distribution network fault recovery model involving fault repair, including: Based on the restoration cost, repair time, and travel time to the faulty line for each faulty line, a third objective function is constructed with the goal of minimizing the power loss load in the shortest possible time. Establish a fourth objective function that minimizes the total repair time; Based on the emergency repair resources and the aforementioned emergency repair time, establish emergency repair resource constraints and fault time constraints; The third objective function, the fourth objective function, emergency repair resource constraints, fault time constraints, operational constraints, controllable load constraints, energy storage constraints, power balance constraints, power flow balance constraints, and node voltage constraints constitute the second active distribution network fault recovery model.

[0080] Furthermore, the emergency repair control module 207 determines a line emergency repair plan based on the second active distribution network fault recovery model, and performs emergency repairs on the faulty lines in the information blind spot based on the line emergency repair plan, including: Solve the second active distribution network fault recovery model to obtain the repair sequence of all faulted lines, and carry out repairs on the faulted lines in each information blind zone according to the repair sequence.

[0081] In some embodiments, an electronic device is also provided, including a processor and a memory, the memory storing a plurality of instructions, the processor being configured to read the instructions and execute the methods described above.

[0082] The power distribution network fault recovery method and apparatus considering UAV emergency communication provided in the above embodiments have at least the following beneficial effects: (1) Under the constraint of limited UAV resources, an emergency communication model for UAVs with the priority of load in blind areas as the optimization objective is constructed to determine the optimal deployment location of UAVs and the configuration scheme of the number of UAVs required in each information blind area. Then, by coordinating the schedulable resources in information blind areas and non-information blind areas, island division and network topology reconstruction are implemented simultaneously to achieve coordinated optimization of UAV deployment scheme, temporary recovery scheme and emergency repair scheduling, thereby maximizing the short-term load recovery and improving the reliability of power distribution network fault recovery; (2) By rapidly establishing a temporary emergency communication network through drones and combining the joint optimization strategy of island division and network reconstruction, the power supply of the power-loss load in the information blind zone can be quickly restored, the power outage time can be minimized, and the short-term load restoration can be maximized. (3) It can effectively shorten the complete recovery time of power failure load and achieve a higher load recovery rate within the same recovery period.

[0083] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if these modifications and modifications of the invention fall within the scope of the claims and their equivalents, the invention is also intended to include these modifications and modifications.

Claims

1. A power distribution network fault recovery method considering unmanned aerial vehicle (UAV) communication recovery, characterized in that, include: Construct a first active distribution network fault recovery model that does not involve fault repair and a second active distribution network fault recovery model that involves fault repair; Identify information blind spots in the power distribution network where faults occur; Based on the first active power distribution network fault recovery model, a first-stage temporary power restoration is performed for the information blind spot; Based on the aforementioned information blind spots and constraints in the drone scheduling process, an emergency communication model for drones is established. Based on the aforementioned UAV emergency communication model, a UAV deployment plan is obtained, and the UAV is controlled to establish temporary communication for the corresponding information blind spots according to the UAV deployment plan. After establishing temporary communication, a second phase of temporary power restoration is carried out for the information blind spot based on the first active power distribution network fault recovery model; After the temporary power restoration in the second phase, a line repair plan is determined based on the second active distribution network fault recovery model, and the faulty lines in the information blind spot are repaired based on the line repair plan.

2. The method according to claim 1, characterized in that, Based on the aforementioned information blind spots and constraints in the UAV scheduling process, an emergency communication model for UAVs is established, including: Establish constraints on the communication coverage radius of the UAV based on its altitude and the angle of its communication sensing range; Establish time constraints for the drone based on its flight time; Based on the flight path planning of the UAV, establish spatial constraints for the UAV; Based on the location of FTU devices in the information blind spot and the value and urgency of the load controlled by the FTU devices, a phased coverage model for UAVs is established. The drone communication coverage radius constraint, drone time constraint, drone space constraint, and drone phased coverage model constitute the drone emergency communication model.

3. The method according to claim 2, characterized in that, The communication coverage radius of a drone is the product of the drone's hovering altitude and the tangent of the angle of the communication sensing range; The time constraints for the UAV include that the duration of the UAV's mission is less than the UAV's maximum endurance, and the duration of the UAV's mission is the sum of the UAV's flight time, hovering time, and the time for the UAV to establish temporary communication. The spatial constraints of the UAV include whether the flight of the UAV from the initial emergency warehouse to the candidate docking point is a one-way or two-way journey, whether the flight of the UAV between the candidate docking points is a one-way journey, and whether the UAV flies to the next candidate docking point after completing the line repair in the current information blind spot.

4. The method according to claim 2, characterized in that, Based on the location of FTU devices in the information blind spot and the value and urgency of the payloads controlled by the FTU devices, a phased coverage model for UAVs is established, including: Based on the position coordinates of the FTU device and the planar position coordinates of the UAV at the candidate docking point, calculate the distance between the UAV's planar position and the FTU device; Based on the UAV communication coverage radius constraint and the distance between the UAV's planar position and the FTU device, establish the UAV communication range constraint; Priority weights for FTU units are generated based on the value and urgency of the loads controlled by the FTU units. Based on the UAV communication range constraints and priority weights, a first objective function and its constraints, considering the priority weights and aiming to completely cover the information blind spots, are established to obtain the UAV phased coverage model.

5. The method according to claim 1, characterized in that, Construct a first active distribution network fault recovery model that does not involve fault repair, including: Based on the importance of each load node in the distribution network, the power supply status, the active power, and the cost coefficient of the power outage load, a second objective function is established to minimize the power outage loss. Construct operational constraints that satisfy the radial operation of the distribution network; Establish controllable load constraints based on the allowable load reduction power and coefficient in the distribution network; Energy storage constraints are established based on the remaining capacity and charging / discharging power of energy storage devices in the power distribution network that can supply power to the power outage loads. Establish power flow balance constraints and node voltage constraints after distribution network fault recovery; The second objective function, operating constraints, controllable load constraints, energy storage constraints, power flow balance constraints, and node voltage constraints constitute the first active distribution network fault recovery model.

6. The method according to claim 5, characterized in that, Based on the first active distribution network fault recovery model, a first-stage temporary power restoration is performed for the information blind spot, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone, solve the first active distribution network fault recovery model, obtain a first temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the first temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the non-information blind zone to temporarily restore power supply to the power-loss loads in the information blind zone. Based on the first active distribution network fault recovery model, a second phase of temporary power restoration is performed for the information blind spot, including: Identify distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone, solve the first active distribution network fault recovery model, obtain a second temporary recovery scheme that satisfies the first active distribution network fault recovery model, and, based on the second temporary recovery scheme, use distributed power sources and / or energy storage devices with stable islanding operation capabilities within the information blind zone to temporarily restore power to the power-loss loads in the information blind zone.

7. The method according to claim 5, characterized in that, Construct a second active distribution network fault recovery model involving fault repair, including: Based on the restoration cost, repair time, and travel time to the faulty line for each faulty line, a third objective function is constructed with the goal of minimizing the power loss load in the shortest possible time. Establish a fourth objective function that minimizes the total repair time; Based on the emergency repair resources and the aforementioned emergency repair time, establish emergency repair resource constraints and fault time constraints; The third objective function, the fourth objective function, emergency repair resource constraints, fault time constraints, operational constraints, controllable load constraints, energy storage constraints, power balance constraints, power flow balance constraints, and node voltage constraints constitute the second active distribution network fault recovery model.

8. The method according to claim 7, characterized in that, Based on the second active distribution network fault recovery model, a line repair plan is determined, and based on the line repair plan, repairs are carried out on faulty lines in the information blind spot, including: Solve the second active distribution network fault recovery model to obtain the repair sequence of all faulted lines, and carry out repairs on the faulted lines in each information blind zone according to the repair sequence.

9. A power distribution network fault recovery device considering the restoration of communication by unmanned aerial vehicles (UAVs), characterized in that, include: The recovery model construction module is used to construct a first active distribution network fault recovery model that does not involve fault repair and a second active distribution network fault recovery model that involves fault repair. The fault identification module is used to determine the information blind spots corresponding to the nodes in the distribution network where faults have occurred. The first-stage control module is used to perform a first-stage temporary power restoration for the information blind spot based on the first active power distribution network fault recovery model. The communication model construction module is used to establish an emergency communication model for drones based on the information blind spots and the constraints in the drone scheduling process. The communication control module is used to obtain a drone deployment plan based on the drone emergency communication model, and control the drone to establish temporary communication for the corresponding information blind spots according to the drone deployment plan; The second-stage control module is used to temporarily restore power supply to the information blind spot in the second stage according to the first active power distribution network fault recovery model after establishing temporary communication. The emergency repair control module is used to determine the line emergency repair plan based on the second active distribution network fault recovery model after the second phase of temporary power restoration, and to carry out emergency repairs on the faulty lines in the information blind spot based on the line emergency repair plan.

10. An electronic device, characterized in that, It includes a processor and a memory, the memory storing multiple instructions, and the processor being used to read the instructions and execute the method as described in any one of claims 1-8.

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