Post-disaster load recovery method for distribution system based on communication and navigation fusion power emergency drone

Abstract

The present invention discloses a method for post-disaster load recovery of a distribution system based on a communication-conductance fusion power emergency drone, which specifically includes: based on the information-physical coupling characteristics of a new distribution system, by establishing an information-physical collaborative recovery framework, including a distribution system load recovery framework, an information network recovery framework, and a communication-conductance fusion drone-information network collaborative recovery framework, to achieve rapid recovery of the distribution system after a disaster. In addition, the present invention also proposes a distribution system communication-conductance fusion drone access and post-disaster information-physical collaborative recovery optimization model, which optimizes the drone access and post-disaster information-physical collaborative recovery system model, maximizes the system benefit after the drone access model, and improves the utility of drones in the post-disaster load recovery scenario of the new distribution system.

Description

Technical Field

[0001] The present invention relates to the field of power distribution networks, and in particular to a method for post-disaster load recovery of a power distribution system based on a communication-conductivity-integrated power emergency drone. Background Art

[0002] The stable operation of the new distribution system is an important foundation for the stable development of the modern economy and society. In recent years, extreme natural disasters have occurred frequently, and post-disaster power outages have occurred frequently, which has brought huge challenges to the stable operation of the new distribution system. The existing distribution system information network is easily damaged by natural disasters and has weak response capabilities to extreme situations. At present, the control and monitoring capabilities of the distribution system equipment are insufficient, which can easily cause cascading failures and expand the scope of power outages. In the context of promoting the construction of a new distribution system, the state perception capability of the distribution system needs to be improved, and it is urgent to study post-disaster load recovery technology suitable for the new distribution system, so that when extreme natural disasters cause the power communication terminal to fail to work normally, it can respond quickly and assist the new distribution system in post-disaster recovery and reconstruction.

[0003] Drones have been widely used in power system maintenance due to their simple equipment, flexibility and low cost. However, the communication capabilities of the current power emergency drones are highly dependent on ground base stations. If the ground base stations are damaged, it is difficult to provide reliable communication guarantees in disaster scenarios, and the reliability needs to be improved. At the same time, the navigation and positioning capabilities of drones affect the efficiency of post-disaster recovery of distribution systems. The communication and navigation fusion drones based on low-orbit satellite Internet and Beidou navigation system have the characteristics of "strong damage resistance", "high flexibility" and "easy access", and can be used as temporary base stations and data relay nodes in disaster scenarios, and communication nodes can be quickly deployed over disaster areas. By establishing a temporary communication network to assist the post-disaster recovery of new distribution systems, and relying on navigation and positioning services to quickly access important recovery nodes in the distribution system, the post-disaster recovery efficiency of new distribution systems can be significantly improved. Summary of the invention

[0004] The purpose of the present invention is to provide a post-disaster load recovery method for a power distribution system based on a communication-conductivity-integrated power emergency drone to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for post-disaster load recovery of a power distribution system based on a communication-conductance fusion power emergency drone is characterized by comprising the following steps:

[0007] Step 1: Establish a new post-disaster information-physical communication and navigation fusion drone collaborative recovery framework for power distribution systems, including a distribution system load recovery framework, an information network recovery framework, and a communication and navigation fusion drone-information network collaborative recovery framework. The three types of recovery frameworks are as follows:

[0008] (1) A distribution system load recovery framework is established based on the distribution system. During the post-disaster recovery process, the distribution system topology is constructed in the form of a collection of busbar nodes and transmission lines. At the same time, each node in the distribution system network is connected to a load, and some of the nodes are equipped with black start power supplies, so that these nodes have rapid recovery capabilities;

[0009] (2) Establish an information network recovery framework based on the communication network, regard the wired network part of the communication network as a coupling structure with the distribution system, and construct the communication network topology in the form of a collection of information nodes and communication lines. At the same time, the information node is composed of a data switch and an information control center, and the same switch is coupled with multiple distribution system nodes; each node in the information network corresponds to a switch or control center, in which the normal operation of each switch and its subordinate sensor device depends on the power supply of the corresponding power supply line of the distribution system;

[0010] (3) Based on the communication and navigation fusion power emergency drone, a communication and navigation fusion drone-information network collaborative recovery framework is established. The communication and navigation fusion power emergency drone is connected near the key load area. During the post-disaster recovery process, the communication and navigation fusion power emergency drone acts as a mobile terminal to process and send data, replacing the switch to realize the transmission of sensor information and the issuance of control signals of the corresponding distribution system nodes, and provides navigation and positioning services for repair personnel, so as to realize the rapid recovery of distribution system visibility and rapid reconstruction of island topology before the wired communication network is restored;

[0011] Step 2: Construct a new distribution system communication and guidance integrated power emergency drone access and post-disaster information-physical collaborative recovery optimization model, as follows:

[0012] (1) Constructing the objective function of the optimization problem, which includes two parts: load loss cost and Cost of access to emergency drones for power generation and communication integration , the expression is as follows:

[0013]

[0014] Where: is the time interval for model analysis, is the total number of time periods; is the set of nodes in the power distribution system, A collection of distribution system nodes that are initially equipped with power inspection drones; For distribution system nodes The load weight factor; For distribution system nodes In time The load recovery amount; To access the load-money conversion factor of the integrated power emergency drone, To guide the access cost of integrated power emergency drones, For display node A 0-1 variable indicating whether to access the drone communication service. A value of 1 indicates that the node Connected, 0 means not connected;

[0015] (2) Construct a new type of distribution system recovery constraint, the distribution system recovery constraint is as follows:

[0016] New distribution system restoration path constraints:

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] Where: represents the set of nodes in the power distribution system, represents the collection of lines in the power distribution system, Represents a set of black start power supply nodes in a power distribution system; is the node connection matrix in the power distribution system, =1 means existence and Recoverable paths between

[0024] New distribution system restoration time constraints:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031] Where: Represents a power distribution system node Time to restore power supply; is the node switch action time matrix in the distribution system, whose elements Representation Node , The time required for the switch to operate, Representation Node The black start power supply self-start time at; Represents a power distribution system node Power supply has been restored and the target node of the path has been restored Recovering information takes considerable time, For distribution system nodes It takes considerable time to restore the wired information network. Represents a power distribution system node UAV communication access time, is a sufficiently large constant;

[0032] On this basis, a 0-1 variable matrix Indicates the recovery status of the power distribution system nodes in each period. Its elements =1 means that the power distribution system node resumes power supply in time period t, and it satisfies the following constraints:

[0033]

[0034]

[0035]

[0036] The new power distribution system restores the initial state constraints:

[0037]

[0038]

[0039] Where: and They represent the set of distribution system nodes that cannot be restored and the set of lines that cannot be closed respectively;

[0040] Distribution system power flow state constraints:

[0041]

[0042]

[0043]

[0044] Where: and Indicates that at the node The active and reactive outputs of the black start power supply at time t; and Representation Node The lower and upper limits of the active output of the black start power supply; and Representation Node The lower and upper limits of reactive power output of black start power supply; and Indicates its maximum rate of power reduction / increase;

[0045] (3) Constructing information network recovery constraints

[0046] Information network recovery path constraints:

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053] Where: represents a collection of information network nodes, Represents a collection of information network lines, It represents the node where the central server is located in the information network; is the node connection matrix in the information network;

[0054] Information network recovery time constraints:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062] Where: Indicates the time when the repair team completes the dth step of repair; It represents the repair time function, whose value is the repair time required to repair x information network nodes at the same time, which generally increases with the increase of the number of nodes repaired at the same time; Represents the total number of nodes in the information network with repair order d; Indicates the repair order of node a; Indicates the repair order of the parent nodes of node a in the emergency repair topology; Indicates the recovery completion time of information network node a; For the judgment variable, When , its value is 1, otherwise it is 0;

[0063] Information network traffic constraints:

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070] At the same time, due to the limitation of the flow rate that can be passed through each line in the information network, the completion of the repair of each switch channel in the information network does not mean that the corresponding nodes of the distribution system have recovered significantly. Indicates the situation where the nodes of the power distribution system in each period are restored to a considerable extent in the information network, and constructs the following constraints:

[0071]

[0072]

[0073]

[0074] Where: Represents a power distribution system node Considerable time to restore wired information network; Responsible for forwarding the distribution system node The information network node where the switch that obtains the observation data from the sensors is located;

[0075] In addition, considering the line flow limit, there are the following constraints:

[0076]

[0077]

[0078]

[0079]

[0080]

[0081] Where: represents the set of distribution system nodes connected to the switch at information network node a, Observing power distribution nodes for sensors The data traffic generated; represents the data flow input by information network node a at time t, Indicates the output data flow; is a 0-1 variable representing the recovery status of distribution system line g at time t, =0 means line recovery; Indicates the maximum data flow through line g; is the connection relationship variable between line g and node a. If g = (a,b), that is, line g connects nodes a and b and the connection direction is from a to b, then , , ;

[0082] Information network initial state constraints:

[0083]

[0084]

[0085] Where: and They respectively represent the set of information network nodes and the set of lines that do not need to be restored;

[0086] Information network energy supply constraints:

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] Where: represents a set of power distribution system nodes that supply power to the switch at information network node a, including a main power supply line access node and a backup power supply line access node; To indicate the distribution system node A 0-1 variable indicating whether the switch power supply requirement is met at time t. =1 means that the load recovery ratio at time t is greater than the minimum ratio α required for power supply, and the switch power supply can be restored; Indicates the time point when information network node a resumes power supply;

[0093] (4) Constraints on cooperative communication of integrated UAVs

[0094] Access constraints of communication and navigation fusion drones:

[0095]

[0096]

[0097]

[0098]

[0099] Where: It is an alternative power distribution system node for drone nests with communication and navigation integration; For Node The time to access the communication and navigation fusion drone, For Node If the communication signal of the UAV is lost, , indicating a node No communication and navigation fusion drones were connected during the recovery process; A 0-1 variable indicating the access of the communication and navigation fusion drone. Indicates that at the node Configure the terminal;

[0100] Communication and navigation fusion UAV collaborative restoration path constraints:

[0101]

[0102]

[0103]

[0104] Where: Represents the set of drone nest nodes; Represents the set of drone recovery routes; Recover the path matrix for UAV communications;

[0105] Communication capacity constraints of integrated UAV:

[0106]

[0107]

[0108]

[0109] Where: and Respectively represent the node number limit and maximum flow limit of the communication of the integrated UAV; use a 0-1 variable matrix It represents the communication status of the nodes in the power distribution system and the integrated UAV communication in each period. =1 indicates a power distribution system node In the period There is a communication signal of the UAV that is integrated with the navigation and navigation system;

[0110] Communication duration constraints for integrated UAVs:

[0111]

[0112]

[0113] Where: Represents the forwarding distribution system node The information network node where the switch of the observation data is located; To indicate the node A 0-1 variable that represents the order of the wired communication network's observable recovery time and load recovery time;

[0114] Step 3: Linearization of constraints. The above distribution system communication and guidance fusion drone access and post-disaster information-physical collaborative recovery optimization model is nonlinear, and the constraints of the optimization problem need to be handled. By introducing auxiliary variables, it is equivalent to a mixed integer linear programming MILP problem.

[0115] Step 4: Use the GUROBI solver to solve the MILP problem and obtain the solution to the optimization problem, which is the new post-disaster load loss minimization strategy for the distribution system under the collaboration of the communication and navigation integrated power emergency drone.

[0116] Compared with the prior art, the present invention has the following beneficial effects: BRIEF DESCRIPTION OF THE DRAWINGS

[0117] Figure 1 :Schematic diagram of the operation framework of the information-physical system integrating power emergency drone and distribution system

[0118] Figure 2 :New distribution system post-disaster recovery system variable coupling relationship based on communication and navigation fusion drone

[0119] Figure 3 : Recovery strategy flow chart. DETAILED DESCRIPTION

[0120] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0121] See also Figures 1 to 3 In an embodiment of the present invention, a method for post-disaster load recovery of a power distribution system based on a communication-conductivity-integrated power emergency drone is characterized by comprising the following steps:

[0122] Step 1: Establish a new post-disaster information-physical communication and navigation fusion drone collaborative recovery framework for power distribution systems, including a distribution system load recovery framework, an information network recovery framework, and a communication and navigation fusion drone-information network collaborative recovery framework. The three types of recovery frameworks are as follows:

[0123] (1) A distribution system load recovery framework is established based on the distribution system. During the post-disaster recovery process, the distribution system topology is constructed in the form of a collection of busbar nodes and transmission lines. At the same time, each node in the distribution system network is connected to a load, and some of the nodes are equipped with black start power supplies, so that these nodes have rapid recovery capabilities;

[0124] (2) Establish an information network recovery framework based on the communication network, regard the wired network part of the communication network as a coupling structure with the distribution system, and construct the communication network topology in the form of a collection of information nodes and communication lines. At the same time, the information node is composed of a data switch and an information control center, and the same switch is coupled with multiple distribution system nodes; each node in the information network corresponds to a switch or control center, in which the normal operation of each switch and its subordinate sensor device depends on the power supply of the corresponding power supply line of the distribution system;

[0125] (3) Based on the communication and navigation fusion power emergency drone, a communication and navigation fusion drone-information network collaborative recovery framework is established. The communication and navigation fusion power emergency drone is connected near the key load area. During the post-disaster recovery process, the communication and navigation fusion power emergency drone acts as a mobile terminal to process and send data, replacing the switch to realize the transmission of sensor information and the issuance of control signals of the corresponding distribution system nodes, and provides navigation and positioning services for repair personnel, so as to realize the rapid recovery of distribution system visibility and rapid reconstruction of island topology before the wired communication network is restored;

[0126] Step 2: Construct a new distribution system communication and guidance integrated power emergency drone access and post-disaster information-physical collaborative recovery optimization model, as follows:

[0127] (1) Constructing the objective function of the optimization problem, which includes two parts: load loss cost and Cost of access to emergency drones for power generation and communication integration , the expression is as follows:

[0128]

[0129] Where: is the time interval for model analysis, is the total number of time periods; is the set of nodes in the power distribution system, A collection of distribution system nodes that are initially equipped with power inspection drones; For distribution system nodes The load weight factor; For distribution system nodes In time The load recovery amount; To access the load-money conversion factor of the integrated power emergency drone, To guide the access cost of integrated power emergency drones, For display node A 0-1 variable indicating whether to access the drone communication service. A value of 1 indicates that the node Connected, 0 means not connected;

[0130] (2) Construct a new type of distribution system recovery constraint, the distribution system recovery constraint is as follows:

[0131] New distribution system restoration path constraints:

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] Where: represents the set of nodes in the power distribution system, represents the collection of lines in the power distribution system, Represents a set of black start power supply nodes in a power distribution system; is the node connection matrix in the power distribution system, =1 means existence and Recoverable paths between

[0139] New distribution system restoration time constraints:

[0140]

[0141]

[0142]

[0143]

[0144]

[0145]

[0146] Where: Represents a power distribution system node Time to restore power supply; is the node switch action time matrix in the distribution system, whose elements Representation Node , The time required for the switch to operate, Representation Node The black start power supply self-start time at; Represents a power distribution system node Power supply has been restored and the target node of the path has been restored Recovering information takes considerable time, For distribution system nodes It takes considerable time to restore the wired information network. Represents a power distribution system node UAV communication access time, is a sufficiently large constant;

[0147] On this basis, a 0-1 variable matrix Indicates the recovery status of the power distribution system nodes in each period. Its elements =1 means that the power distribution system node resumes power supply in time period t, and it satisfies the following constraints:

[0148]

[0149]

[0150]

[0151] The new power distribution system restores the initial state constraints:

[0152]

[0153]

[0154] Where: and They represent the set of distribution system nodes that cannot be restored and the set of lines that cannot be closed respectively;

[0155] Distribution system power flow state constraints:

[0156]

[0157]

[0158]

[0159] Where: and Indicates that at the node The active and reactive outputs of the black start power supply at time t; and Representation Node The lower and upper limits of the active output of the black start power supply; and Representation Node The lower and upper limits of reactive power output of black start power supply; and Indicates its maximum rate of power reduction / increase;

[0160] (3) Constructing information network recovery constraints

[0161] Information network recovery path constraints:

[0162]

[0163]

[0164]

[0165]

[0166]

[0167]

[0168] Where: represents a collection of information network nodes, Represents a collection of information network lines, It represents the node where the central server is located in the information network; is the node connection matrix in the information network;

[0169] Information network recovery time constraints:

[0170]

[0171]

[0172]

[0173]

[0174]

[0175]

[0176]

[0177] Where: Indicates the time when the repair team completes the dth step of repair; It represents the repair time function, whose value is the repair time required to repair x information network nodes at the same time, which generally increases with the increase of the number of nodes repaired at the same time; Represents the total number of nodes in the information network with repair order d; Indicates the repair order of node a; Indicates the repair order of the parent nodes of node a in the emergency repair topology; Indicates the recovery completion time of information network node a; For the judgment variable, When , its value is 1, otherwise it is 0;

[0178] Information network traffic constraints:

[0179]

[0180]

[0181]

[0182]

[0183]

[0184]

[0185] At the same time, due to the limitation of the flow rate that can be passed through each line in the information network, the completion of the repair of each switch channel in the information network does not mean that the corresponding nodes of the distribution system have recovered significantly. Indicates the situation where the nodes of the power distribution system in each period are restored to a considerable extent in the information network, and constructs the following constraints:

[0186]

[0187]

[0188]

[0189] Where: Represents a power distribution system node Considerable time to restore wired information network; Responsible for forwarding the distribution system node The information network node where the switch that obtains the observation data from the sensors is located;

[0190] In addition, considering the line flow limit, there are the following constraints:

[0191]

[0192]

[0193]

[0194]

[0195]

[0196] Where: represents the set of distribution system nodes connected to the switch at information network node a, Observing power distribution nodes for sensors The data traffic generated; represents the data flow input by information network node a at time t, Indicates the output data flow; is a 0-1 variable representing the recovery status of distribution system line g at time t, =0 means line recovery; Indicates the maximum data flow through line g; is the connection relationship variable between line g and node a. If g = (a,b), that is, line g connects nodes a and b and the connection direction is from a to b, then , , ;

[0197] Information network initial state constraints:

[0198]

[0199]

[0200] Where: and They respectively represent the set of information network nodes and the set of lines that do not need to be restored;

[0201] Information network energy supply constraints:

[0202]

[0203]

[0204]

[0205]

[0206]

[0207] Where: represents a set of power distribution system nodes that supply power to the switch at information network node a, including a main power supply line access node and a backup power supply line access node; To indicate the distribution system node A 0-1 variable indicating whether the switch power supply requirement is met at time t. =1 means that the load recovery ratio at time t is greater than the minimum ratio α required for power supply, and the switch power supply can be restored; Indicates the time point when information network node a resumes power supply;

[0208] (4) Constraints on cooperative communication of integrated UAVs

[0209] Access constraints of communication and navigation fusion drones:

[0210]

[0211]

[0212]

[0213]

[0214] Where: It is an alternative power distribution system node for drone nests with communication and navigation integration; For Node The time to access the communication and navigation fusion drone, For Node If the communication signal of the UAV is lost, , indicating a node No communication and navigation fusion drones were connected during the recovery process; A 0-1 variable indicating the access of the communication and navigation fusion drone. Indicates that at the node Configure the terminal;

[0215] Communication and navigation fusion UAV collaborative restoration path constraints:

[0216]

[0217]

[0218]

[0219] Where: Represents the set of drone nest nodes; Represents the set of drone recovery routes; Recover the path matrix for UAV communications;

[0220] Communication capacity constraints of integrated UAV:

[0221]

[0222]

[0223]

[0224] Where: and Respectively represent the node number limit and maximum flow limit of the communication of the integrated UAV; use a 0-1 variable matrix It represents the communication status of the nodes in the power distribution system and the integrated UAV communication in each period. =1 indicates a power distribution system node In the period There is a communication signal of the UAV that is integrated with the navigation and navigation system;

[0225] Communication duration constraints for integrated UAVs:

[0226]

[0227]

[0228] Where: Represents the forwarding distribution system node The information network node where the switch of the observation data is located; To indicate the node A 0-1 variable that represents the order of the wired communication network's observable recovery time and load recovery time;

[0229] Step 3: Linearization of constraints. The above distribution system communication and guidance fusion drone access and post-disaster information-physical collaborative recovery optimization model is nonlinear, and the constraints of the optimization problem need to be handled. By introducing auxiliary variables, it is equivalent to a mixed integer linear programming MILP problem.

[0230] Step 4: Use the GUROBI solver to solve the MILP problem and obtain the solution to the optimization problem, which is the new post-disaster load loss minimization strategy for the distribution system under the collaboration of the communication and navigation integrated power emergency drone.

[0231] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0232] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for post-disaster load recovery of a power distribution system based on a communication-conductance fusion power emergency drone, characterized in that: The steps include: Step 1: Establish a post-disaster information-physical communication and navigation fusion drone collaborative recovery framework for the power distribution system, including the power distribution system load recovery framework, the information network recovery framework, and the communication and navigation fusion drone-information network collaborative recovery framework. The three types of recovery frameworks are as follows: (1) A distribution system load recovery framework is established based on the distribution system. During the post-disaster recovery process, the distribution system topology is constructed in the form of a collection of busbar nodes and transmission lines. At the same time, each node in the distribution system network is connected to a load, and some of the nodes are equipped with black start power supplies, so that these nodes have rapid recovery capabilities; (2) Establish an information network recovery framework based on the communication network, regard the wired network part of the communication network as a coupling structure with the distribution system, and construct the communication network topology in the form of a collection of information nodes and communication lines. At the same time, the information node is composed of a data switch and an information control center, and the same switch is coupled with multiple distribution system nodes; each node in the information network corresponds to a switch or control center, in which the normal operation of each switch and its subordinate sensor device depends on the power supply of the corresponding power supply line of the distribution system; (3) Based on the communication and navigation fusion power emergency drone, a communication and navigation fusion drone-information network collaborative recovery framework is established. The communication and navigation fusion power emergency drone is connected near the key load area. During the post-disaster recovery process, the communication and navigation fusion power emergency drone acts as a mobile terminal to process and send data, replacing the switch to realize the transmission of sensor information and the issuance of control signals of the corresponding distribution system nodes, and provides navigation and positioning services for repair personnel, so as to realize the rapid recovery of distribution system visibility and rapid reconstruction of island topology before the wired communication network is restored; Step 2: Construct a power distribution system communication and guidance integrated power emergency drone access and post-disaster information-physical collaborative recovery optimization model, as follows: (1) Constructing the objective function of the optimization problem, which includes two parts: load loss cost and Cost of access to emergency drones for power generation and communication integration , the expression is as follows: Where: is the time interval for model analysis, is the total number of time periods; is the set of nodes in the power distribution system, A collection of distribution system nodes that are initially equipped with power inspection drones; For distribution system nodes The load weight factor; For distribution system nodes In time The load recovery amount; To access the load-money conversion factor of the integrated power emergency drone, To guide the access cost of integrated power emergency drones, For display node A 0-1 variable indicating whether to access the drone communication service. A value of 1 indicates that the node Connected, 0 means not connected; (2) Constructing the power distribution system recovery constraints, the power distribution system recovery constraints are as follows: Distribution system restoration path constraints: Where: represents the set of nodes in the power distribution system, represents the collection of lines in the power distribution system, Represents a set of black start power supply nodes in a power distribution system; is the node connection matrix in the distribution system, =1 means existence and Recoverable paths between Distribution system restoration time constraints: Where: Represents a power distribution system node Time to restore power supply; is the node switch action time matrix in the distribution system, whose elements Representation Node , The time required for the switch to operate, Representation Node The black start power supply self-start time at; Represents a power distribution system node Power supply has been restored and the target node of the restored path Recovering information takes considerable time, For distribution system nodes It takes considerable time to restore the wired information network. Represents a power distribution system node UAV communication access time, is a sufficiently large constant; On this basis, a 0-1 variable matrix Indicates the recovery status of the power distribution system nodes in each period. Its elements =1 indicates that the distribution system node is in the period t When power supply is restored, it satisfies the following constraints: The power distribution system returns to its initial state constraints: Where: and They represent the set of distribution system nodes that cannot be restored and the set of lines that cannot be closed respectively; Distribution system power flow state constraints: Where: and Indicates that at the node Black start power at time t Active and reactive output; and Representation Node The lower and upper limits of the active output of the black start power supply; and Representation Node The lower and upper limits of reactive power output of black start power supply; and Indicates its maximum rate of power reduction / increase; (3) Constructing information network recovery constraints Information network recovery path constraints: Where: represents a collection of information network nodes, Represents a collection of information network lines, It represents the node where the central server is located in the information network; is the node connection matrix in the information network; Information network recovery time constraints: Where: The repair team completed the d Step repair time; Represents the repair time function, whose value is simultaneous repair x The repair time required for each information network node increases as the number of nodes being repaired simultaneously increases; Indicates the repair order is d The total number of information network nodes; Representation Node a The repair order of Indicates that in the emergency repair topology, the node a The repair order of the parent nodes; Represents information network node a The time it takes for the recovery to be completed; For the judgment variable, When , its value is 1, otherwise it is 0; Information network traffic constraints: Another 0-1 variable matrix Indicates the situation where the nodes of the power distribution system in each period are restored to a considerable extent in the information network, and constructs the following constraints: Where: Represents a power distribution system node Considerable time to restore wired information network; Responsible for forwarding the distribution system node An information network node where a switch that obtains observation data from sensors at a certain location is located; In addition, considering the line flow limit, there are the following constraints: Where: Represents information network node a The set of distribution system nodes connected to the switch, Observing power distribution nodes for sensors The data traffic generated; Represents information network node a In time t The input data flow, Indicates the output data flow; To represent the power distribution system line g In time t A 0-1 variable representing the recovery status of =0 means line recovery; Indicates the flow line g Maximum data flow rate; For line g and nodes a If the connection variable g = ( a , b ), that is, line g Connecting Nodes a and b And the connection direction is from a to b ,but , , , ; Information network initial state constraints: Where: and They respectively represent the set of information network nodes and the set of lines that do not need to be restored; Information network energy supply constraints: Where: Represented as an information network node a A set of power distribution system nodes powered by switches at the location, including a main power supply line access node and a backup power supply line access node; To indicate the distribution system node A 0-1 variable indicating whether the switch power supply requirement is met at time t. =1 means that it is at time t The load recovery ratio is greater than the minimum ratio required for power supply α , the switch power supply can be restored; Represents information network node a The time when power supply will be restored; (4) Constraints on cooperative communication of integrated UAVs Access constraints of communication and navigation fusion drones: Where: It is an alternative power distribution system node for drone nests with communication and navigation integration; For Node The time to access the communication and navigation fusion drone, For Node If the communication signal of the UAV is lost, , indicating a node No communication and navigation fusion drones were connected during the recovery process; A 0-1 variable indicating the access of the communication and navigation fusion drone. Indicates that at the node Configure the terminal; Communication and navigation fusion UAV collaborative restoration path constraints: Where: Represents the set of drone nest nodes; Represents the set of drone recovery routes; Recover the path matrix for UAV communications; Communication capacity constraints of integrated UAV: Where: and Respectively represent the node number limit and maximum flow limit of the communication of the integrated UAV; use a 0-1 variable matrix It represents the communication status of the nodes in the power distribution system and the integrated UAV communication in each period. =1 indicates a power distribution system node In the period There is a communication signal of the UAV that is integrated with the navigation and navigation system; Communication duration constraints for integrated UAVs: Where: Represents the forwarding distribution system node The information network node where the switch of the observation data is located; To indicate the node A 0-1 variable that represents the order of the wired communication network's observable recovery time and load recovery time; Step 3: Linearize the constraints. The above distribution system communication and guidance fusion drone access and post-disaster information-physical collaborative recovery optimization model is nonlinear. Auxiliary variables are introduced to make it equivalent to a mixed integer linear programming MILP problem. Step 4: Use the GUROBI solver to solve the MILP problem and obtain the solution to the optimization problem, which is the strategy for minimizing the post-disaster load loss of the distribution system under the collaboration of the communication and navigation integrated power emergency drone.

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