CN-120566421-B - Post-disaster power communication network collaborative recovery system and method

CN120566421BCN 120566421 BCN120566421 BCN 120566421BCN-120566421-B

Abstract

The application relates to the technical field of intelligent power grid dispatching and communication network recovery, and provides a post-disaster power communication network collaborative recovery system and a post-disaster power communication network collaborative recovery method, wherein the system comprises a power network model, a power distribution system and a communication network collaborative recovery system, wherein the power network model is used for distributing power supply resources to each node by taking power supply of power network nodes of a shortest time recovery target area as a target; the system comprises a line restoration model, an electric vehicle path planning model, an unmanned aerial vehicle deployment communication network restoration model, an optimal scheme solving unit and a power communication network node, wherein the line restoration model is used for taking an electric vehicle as a load supply and mobile restoration unit, and realizing joint optimization of power network topology reconstruction and power restoration of a target area by coordinating path planning and resource allocation of the electric vehicle, the electric vehicle path planning model is used for taking maximum restoration of power supply of the target area as a target, enabling the electric vehicle to quickly restore the power network within a limited time by optimizing a moving path of the electric vehicle, the unmanned aerial vehicle deployment communication network restoration model is used for taking minimum restoration of the communication network as a target, and combining cooperative work of the electric vehicle and the unmanned aerial vehicle, the unmanned aerial vehicle is deployed as a temporary air base station while power is supplied by a base station node, and the optimal scheme solving unit is provided with a layered multi-target optimization problem for maximizing total power communication coverage time as a target function under the condition of minimizing the restoration time of the power communication network.

Inventors

LIAN JIANYU
Hu Zishan
Xu Qiudian
ZHOU JIAJIE
YANG CHAO
CHEN XIN

Assignees

广东工业大学

Dates

Publication Date: 20260512
Application Date: 20250610

Claims (10)

1. The post-disaster power communication network collaborative recovery system is characterized by comprising a power network model, a line repair model, an electric vehicle path planning model, an unmanned aerial vehicle deployment communication network recovery model and an optimal solution unit; The power network model is used for taking power supply of a power network node of a shortest time recovery target area as a target, and distributing power supply resources to each node, wherein the nodes comprise user nodes and base station nodes, and the power supply resources are directly or indirectly provided by an electric automobile; the line repair model is used for realizing the joint optimization of the power network topology reconstruction and the power recovery of the target area by taking the electric automobile as a mobile repair unit and coordinating the path planning and the resource allocation of the electric automobile; the electric automobile path planning model is used for enabling the electric automobile to quickly repair the electric network within a limited time by optimizing the moving path of the electric automobile with the aim of recovering the electric power supply of the target area to the greatest extent; the unmanned aerial vehicle deployment communication network recovery model is used for taking the communication network recovery in the shortest time as a target, combining the cooperative work of the electric automobile and the unmanned aerial vehicle, and deploying the unmanned aerial vehicle as a temporary air base station while recovering the power supply of the base station node; The optimal solution solving unit is provided with a layered multi-objective optimization problem taking the total maximum power communication coverage duration as an objective function under the condition of minimizing the recovery time of the power communication network, and is used for solving the layered multi-objective optimization problem in real time under the constraint of a power network model, a line repair model, an electric automobile path planning model and an unmanned aerial vehicle deployment communication network recovery model to obtain a real-time optimal solution of power communication network recovery.
2. The post-disaster power communication network collaborative recovery system according to claim 1, wherein an expression of the power network model comprises: In the formula, And Respectively nodes Sum node Is set up in the network of nodes, A set of all nodes in the power network representing the target area; a set of boundary sets for the defined line; Representing the current time; representing a preset time threshold; Representing a set of all electric vehicles; And Respectively represent the first The time of the electric automobile And time of day Is used to determine the current amount of power available, Represent the first The time of the electric automobile Is a node The amount of direct power supplied is provided, Representing a node A set of all child nodes providing power; representing passing nodes To its child node The amount of indirect power supplied; 、、、、 And Are binary variables, if node At the moment of time From the first The electric automobile is directly connected with the power supply Otherwise If the slave node To the point of Is used by power supply Otherwise If node At the moment of time The electric automobile is directly connected with power supply, and the power supply is marked as a root node Otherwise If node At the moment of time Having already supplied electric power Otherwise If the line is At the moment of time Has been repaired, then Otherwise If node Quilt node Selected as the only parent node, then Otherwise 。
3. The post-disaster power communication network collaborative recovery system according to claim 1, wherein an expression of the line repair model comprises: In the formula, Representing the operation time required by line repair; And Are binary variables, if at the moment Circuit arrangement Damaged and the first Electric automobile arrival node Or node Then Otherwise If the line is Damaged, then Otherwise ; 、 Are binary variables, if node At the moment of time From the first The electric automobile is directly connected with the power supply Otherwise If the line is At the moment of time Has been repaired, then Otherwise ; A set of boundary sets for the defined line; indicating a preset time threshold.
4. The post-disaster power communication network collaborative recovery system according to claim 1, wherein an expression of the electric vehicle path planning model comprises: In the formula, Is a binary variable, if The time of the electric automobile Selecting an away node And go to the node Then Otherwise ; Representing slave nodes To the node The number of discrete time steps required; is the energy consumption for running per unit of time, Representing nodes To the node Is used for the road network distance of the road network, Representing the running speed of the electric automobile; is a binary variable, if node At the moment of time From the first The electric automobile is directly connected with the power supply Otherwise ; Representing a preset time threshold; Representing a set of all electric vehicles; A set of all nodes in the power network representing the target area; And Respectively represent the first The time of the electric automobile And time of day Is used for the current available electricity quantity; Is a defined set of line sides.
5. The post-disaster power communication network collaborative recovery system according to claim 1, wherein the expression of the unmanned aerial vehicle deployment communication network recovery model comprises: In the formula, A set of all nodes of the power network representing the target area; representing a base station node; representing a set of all base station nodes in a target area; representing base station nodes And node Is used for the road network distance of the road network, Is a node And node Road network distance of (2); representing a preset constant; The radius of coverage for the base station, A radius is covered for unmanned aerial vehicle communication; Representing unmanned aerial vehicle slave nodes To the node The number of discrete time steps required; the flying speed of the unmanned aerial vehicle is the flying speed of the unmanned aerial vehicle; Represent the first The moment when the electric automobile of the vehicle is connected to the first node; 、、、、 And Is a binary variable, if node At the moment of time Having resumed communication, then Otherwise If the base station node At the moment of time Having already supplied electric power Otherwise And, if you get The unmanned aerial vehicle is arranged at moment Deployed at a node Above, then Otherwise And, if you get The unmanned aerial vehicle is arranged at moment Deployed at a node Above, then Otherwise If base station To the node Is less than the base station coverage radius Then Otherwise And, if you get Node for deployment of unmanned aerial vehicle To the node Is less than the communication coverage radius of the unmanned plane Then Otherwise And, if you get The unmanned aerial vehicle is arranged at moment Leaving node And go to the node Then Otherwise ; Indicating a preset time threshold.
6. The post-disaster power communication network collaborative recovery system according to claim 1, wherein an expression of an objective function of the hierarchical multi-objective optimization problem comprises: In the formula, Representing an objective function that minimizes the power communication network recovery time, An objective function representing a maximum total length of power communication coverage; Indicating the moment at which the last node resumes power, Indicating the time at which the last node resumes communication; indicating a preset power restoration latest time threshold, Representing a preset communication recovery latest time threshold; 、 is a binary variable, if node At the moment of time Having already supplied electric power Otherwise If node At the moment of time Having resumed communication, then Otherwise 。
7. The post-disaster power communication network collaborative recovery system according to any one of claims 1-6, wherein when solving the hierarchical multi-objective optimization problem, a near-end policy optimization algorithm is utilized to solve; The solving step comprises the following steps: The tasks of the near-end strategy optimization algorithm are defined as minimizing the recovery time of the power communication network through electric vehicle path planning, repair line task allocation and unmanned aerial vehicle deployment; defining a state space of a near-end policy optimization algorithm, wherein an expression of the state space comprises: In the formula, Indicating the current time Is used to determine the state space vector of (1), Representing a node power state vector, Representing a state vector of communication of the node, The position of the electric automobile is indicated, Represents the electric quantity of the battery of the electric automobile, Representing the deployment location of the drone, Representing a list of unmanned aerial vehicle overlay nodes, Indicating the total number of unrecovered power nodes, Representing the total number of unrecovered communication nodes; Defining an action space of a near-end policy optimization algorithm, wherein an expression of the action space comprises: In the formula, Indicating the current time Is used for the motion space vector of (a), Representing the selection of an initially deployed node, The movement decision of the electric automobile is represented, The stop decision of the electric automobile is represented, Representing a movement decision of the unmanned aerial vehicle, Representing unmanned aerial vehicle deployment decisions; Defining a reward function of a near-end strategy optimization algorithm by taking the maximization of the total power communication coverage duration as a target under the condition of minimizing the recovery time of the power communication network; After initializing the environment simulator and the network parameters of the intelligent agent of the near-end strategy optimization algorithm, repeatedly interacting the intelligent agent with the environment to collect data, calculating advantages and rewards, carrying out iterative updating on the strategy network and the value network, and stopping iteration when the expected total rewards corresponding to the rewarding function are maximum or the number of iterations reaches a preset value, so as to obtain a real-time optimal scheme for recovering the power communication network.
8. The post-disaster power communication network collaborative recovery system according to claim 7, wherein the expression of the reward function comprises: In the formula, Representing a reward function; Representing a time penalty coefficient; indicating that each unrecovered node produces an additional negative prize coefficient; Represent the first Resume rewards of individual nodes, if The individual nodes are changed from unrecovered to restored, Otherwise ; Representing the coefficients of continuous power and communication contribution, Indicating the current time The total number of nodes that are online and operating properly has been restored, Indicating the current time The total number of nodes that are online or not operating properly is not restored.
9. A recovery method based on a post-disaster power communication network cooperative recovery system comprises the following steps: Acquiring a plurality of electric vehicles and a plurality of unmanned aerial vehicles, and carrying the unmanned aerial vehicles by the electric vehicles; under the constraint of a power network model, a line repair model, an electric automobile path planning model and an unmanned aerial vehicle deployment communication network recovery model, taking the maximized total power communication coverage duration as an objective function under the condition of minimizing the power communication network recovery time, and solving a real-time optimal scheme of power communication network recovery of a target area under the electric automobile and unmanned aerial vehicle resources in real time; Based on the real-time optimal scheme of the power communication network recovery, a path is distributed for each electric automobile, so that the electric automobile starts from a power grid company node and reaches a node position in a target area to provide power load supply and line repair functions; On the basis of power recovery, when an electric automobile carries an unmanned aerial vehicle to reach an initial preset node according to a path allocated by a real-time optimal scheme of power communication network recovery, a communication recovery task is allocated to each unmanned aerial vehicle based on the real-time optimal scheme of power communication network recovery, so that the unmanned aerial vehicle is used as a temporary communication base station, and wireless communication coverage is provided for a target area; In the power communication network recovery process, an optimal solution solving unit is utilized to update a real-time optimal solution for power communication network recovery in real time, so that an electric vehicle dynamically adjusts a path and task priority according to power recovery progress and node requirements, and meanwhile, an unmanned aerial vehicle adjusts a flight task in real time according to communication recovery requirements and power supply conditions until the power communication network is completely recovered.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of claim 9.

Description

Post-disaster power communication network collaborative recovery system and method Technical Field The application relates to the technical field of intelligent power grid dispatching and communication network recovery, in particular to a post-disaster power communication network collaborative recovery system and method. Background The electric power system is used as a core energy supply carrier of the modern society, and the reliable operation of the electric power system is directly related to the normal development of the social production activities and the continuous operation of a public service system. In the context of global climate change exacerbations, compound disasters caused by extreme climate events pose serious challenges to the power infrastructure. In addition, the power system serves as a hub node for the critical infrastructure system, and its failure may trigger cascading failures through the coupling action of the system, such as service interruption of the communication network, ultimately leading to huge economic loss and serious social impact. The recovery of the power network after an extreme event disaster is one of the core problems of the current research, and a great deal of research has been focused on emergency power supply deployment strategies and dynamic topology reconstruction technologies. Along with the rapid increase of the large-scale process of the electric automobile and the permeability of the electric automobile, the automobile-network bidirectional energy interaction model gradually has an engineering application foundation. Electric vehicles (ELECTRIC VEHICLE, EV) are used as rescue vehicles, can supply power to a power distribution network through a V2G (vehicle-to-grid) technology, and have great potential in the aspect of post-disaster emergency recovery. Because the communication network is tightly coupled with the power network, the disaster often further causes service interruption of the communication network while the power failure of the power distribution network is caused. After communication failure, the quick recovery of the communication system can be realized by means of emergency communication technology, communication rush repair and the like. Unmanned aerial vehicle (unmanned AERIAL VEHICLE, UAV) carrying wireless emergency communication module can realize emergency communication through quick maneuver deployment and constructing temporary communication network coverage, provides key support to the quick recovery of post-disaster communication. In the prior art, the EV is directly taken as a power supply source, the EV is not taken as a coupling point of a power distribution network and a traffic network, and the spatial behavior characteristic of the EV in the traffic network is ignored. Furthermore, extreme disasters often accompany damage to the grid lines and traffic roads. In the prior art, considering the influence of traffic road damage on EV scheduling, an electric vehicle energy space-time layered scheduling strategy for assisting important load recovery in road rush-repair is provided, but the influence of power line damage on regional power supply recovery is ignored. In summary, in the prior art, the EV is not used as a coupling point of the power distribution network and the traffic network, and the influence of the damage of the power line on the restoration of the regional power supply is not considered, so that the time required for restoring the power communication network by using the method in the prior art is long, and the communication coverage duration and the power supply duration of the user node are short. Disclosure of Invention In view of the foregoing, it is desirable to provide a post-disaster power communication network collaborative recovery system and method capable of maximizing a communication coverage duration and a power supply duration of a recovery user node on the basis of ensuring a shortest recovery time of a power communication network. The technical scheme of the invention is as follows: The system comprises a power network model, a line repair model, an electric automobile path planning model, an unmanned aerial vehicle deployment communication network recovery model and an optimal solution solving unit; The power network model is used for taking power supply of a power network node of a shortest time recovery target area as a target, and distributing power supply resources to each node, wherein the nodes comprise user nodes and base station nodes, and the power supply resources are directly or indirectly provided by an electric automobile; the line repair model is used for realizing the joint optimization of the power network topology reconstruction and the power recovery of the target area by taking the electric automobile as a mobile repair unit and coordinating the path planning and the resource allocation of the electric automobile; the electric automobile path planning model is used for enablin