Dynamic scheduling method and system for power disaster relief and repair, and readable storage medium

Abstract

The invention relates to the technical field of electric power disaster relief first-aid repair scheduling, in particular to an electric power disaster relief first-aid repair dynamic scheduling method and system and a readable storage medium. The method comprises the following steps: S1, constructing a dynamic network topology model G of a disaster relief scene; s2, constructing a dynamic power recovery model GP; s3, constructing a first-aid repair dynamic decision-making model: constructing the first-aid repair dynamic decision-making model through the objective function; and S4, optimal first-aid repair strategy calculation: according to the newest dynamic network topology model G and the power recovery model GP and the position of the current power facility node of the rescue team, solving based on a Monte Carlo tree search algorithm to obtain the optimal first-aid repair strategy. According to the method, the situation of a disaster relief site can be dynamically changed, and the first-aid repair strategy is dynamically adjusted according to the change situation of the site.

Description

Technical Field

[0001] The present invention relates to the technical field of power disaster relief repair scheduling, and in particular to a power disaster relief repair dynamic scheduling method, system and readable storage medium. Background Art

[0002] The stable operation of the power grid plays a very important role in people's production and living standards. Once a major natural disaster such as an earthquake or flood causes a large-scale power outage, how to quickly and timely restore power to the grid is of great significance for disaster relief.

[0003] For the post-disaster power grid fault repair and dispatching issues, the main focus is on the analysis of the static power grid environment. In the actual disaster relief and repair scenario, with the secondary and derivative disasters such as aftershocks, mudslides, and landslides, the existing environment will change dynamically. The originally damaged roads may gradually recover, and the originally passable roads may be damaged. The original power-connected network may become a new damaged network, and even the repaired power grid segment may become a damaged segment again. When dealing with the above-mentioned situation where the power grid status further deteriorates, the existing methods can only terminate the solution process and re-solve according to the changed power grid status, resulting in low decision-making efficiency. Summary of the invention

[0004] Based on this, it is necessary for the present invention to provide a method, system and readable storage medium for dynamic scheduling of power disaster relief and repair to solve at least one of the above technical problems.

[0005] To achieve the above purpose, a method for dynamic dispatching of power disaster relief and repair comprises the following steps: Step S1, constructing a dynamic network topology model G for a disaster relief scenario: constructing the dynamic network topology model through an undirected graph G={P,R}, where P is the set of all power facility nodes, , is the set of power facility nodes whose current status is normal, is the set of power facility nodes that are currently damaged, R is the set of all highway sections, , is the set of road sections that are currently in normal and passable state. is the set of highway sections that are currently damaged; the weight value of P is the time required to repair the power facility node, The weight value of is the time required to pass through the highway section; Step S2, constructing a dynamic power restoration model GP: The dynamic power restoration model GP is a collection of power lines of the entire regional power grid, , For a normal collection of power lines, for the collection of damaged power lines; Step S3, constructing a dynamic decision model for emergency repair: through the objective function: , according to the dynamic network topology model G and the dynamic power restoration model GP, a dynamic decision model for emergency repair is constructed; wherein, Indicates the minimum time to repair the entire regional power grid at the current moment, is the time required to repair node i, is the time taken to reach node i from the previous node, Indicates the next time slice The maximum power restored by the entire regional power grid upon arrival, is the jth power line The weight of Step S4, calculation of the best emergency repair strategy: according to the latest dynamic network topology model G and the dynamic power restoration model GP, as well as the location of the power facility node where the rescue team is currently located, the objective function is solved based on the Monte Carlo tree search algorithm to obtain the best emergency repair strategy.

[0006] Furthermore, the The value of is the jth power line The number of all power facility nodes.

[0007] Furthermore, after step S4, the method further includes: step S5, at the beginning of each new time slice T, repeating step S4 to calculate a new optimal emergency repair strategy until all repairs are completed.

[0008] Furthermore, the step S4 specifically includes: Step S41, taking the power facility node where the rescue team is currently located as the root node, and listing all power facility nodes that can be directly reached from the root node as optional child nodes according to the dynamic network topology model G; Step S42: Calculate the weight of each child node according to the UCB formula , select weights The largest value is taken as the optimal child node; Step S43, determining whether there are any unrepaired power facility nodes, if so, proceeding to step S44, if not, proceeding to step S45; Step S44 includes: Step S441, expanding the optimal child node selected in step S42 as a parent node, and listing the power facility nodes reachable from the parent node as optional child nodes; Step S442, randomly select an optional child node as a parent node for expansion, list the power facility nodes that can be reached from the parent node as optional child nodes, and return to step S43; Step S45, update the parameters of each optional child node i by backtracking update formula: , , , Where N represents the number of backtracking times. and They represent the new and old values ​​of the number of backtracking times respectively; Q(i) represents the weight function of the repair capability of child node i, and Respectively represent the new and old values ​​of the weight function of the repair capability of child node i; represents the weight function of the repair time of child node i, and Respectively represent the new value and old value of the weight function of the repair time of child node i; Indicates the change value of Q(i) caused by the expansion of the child node, Indicates the change value of T(i) caused by the expansion of the child node; Step S46, repeat steps S41-S45 iteratively until the preset total number of learning steps is completed, and then output the final optimal solution.

[0009] Furthermore, the UCB formula is: , where i_father represents the parent node of child node i, N represents the number of backtracking of child node i, and is the adjustment factor, which is an empirical constant.

[0010] Furthermore, the calculation formula of Q(i) is: , in, is the preset weight factor of the line corresponding to child node i, is the number of all power facility nodes in the line corresponding to child node i, is the number of unrepaired nodes in the line corresponding to child node i, is the level number of child node i in the tree.

[0011] Furthermore, the calculation formula of T(i) is: ; in, is the total time spent before reaching child node i, The time taken to repair child node i, is the time taken to reach child node i from the previous node.

[0012] Furthermore, the step S5 also includes the step of immediately executing the step S4 when the traffic status of the highway section changes.

[0013] The present invention also provides a dynamic dispatching system for electric power disaster relief and emergency repair, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the dynamic dispatching method for electric power disaster relief and emergency repair as described in any one of the above items are implemented.

[0014] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the dynamic dispatching method for power disaster relief and emergency repair as described in any one of the above items.

[0015] The power disaster relief and emergency repair dynamic scheduling method of the present invention comprises the following steps: step S1, constructing a dynamic network topology model G of the disaster relief scene; step S2, constructing a dynamic power restoration model GP; step S3, constructing an emergency repair dynamic decision model: through the objective function: , according to the dynamic network topology model G and the dynamic power restoration model GP, a dynamic decision-making model for emergency repair is constructed; step S4, calculation of the best emergency repair strategy: according to the latest dynamic network topology model G and the dynamic power restoration model GP, as well as the location of the power facility node where the rescue team is currently located, the Monte Carlo tree search algorithm is used to solve and obtain the best emergency repair strategy. The method of the present invention takes into account the dynamic changes in the situation at the disaster relief site, and the emergency repair strategy will also be dynamically adjusted according to the changes at the site. Furthermore, the Monte Carlo tree search algorithm is used to solve the optimal solution of the multi-objective function to determine the best emergency repair strategy; at the same time, the sub-node weights are improved. The UCB calculation formula avoids the problem of local optimality that is prone to occur in the classic Monte Carlo tree search algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Other features, objectives and advantages of the present invention will become more apparent from a reading of the detailed description of a non-limiting implementation made with reference to the following accompanying drawings.

[0017] Figure 1 The present invention provides a flow chart of a method for dynamic dispatching of power disaster relief and repair.

[0018] Figure 2 It is a schematic diagram of the hardware structure of a system running a dynamic dispatching method for power disaster relief and repair in one embodiment of the present invention.

[0019] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0020] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0021] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0022] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0023] To achieve this, please refer to Figure 1 to Figure 2 The present invention provides a method for dynamic dispatching of power disaster relief and repair, comprising the following steps: Step S1, constructing a dynamic network topology model G of a disaster relief scenario; Step S2, constructing a dynamic power restoration model GP; Step S3, constructing a dynamic decision-making model for emergency repair; Step S4, calculating the best emergency repair strategy.

[0024] Specifically, in the construction of the dynamic network topology model G of the disaster relief scenario in step S1, the dynamic network topology model is constructed through an undirected graph G={P,R}, where P is the set of all power facility nodes, , is the set of power facility nodes whose current status is normal, is the set of power facility nodes that are currently damaged, R is the set of all highway sections, , is the set of road sections that are currently in normal and passable state. is the set of highway sections that are currently damaged, and the weight value of P is the time required to repair the power facility node. The weight value is the time required to pass through the highway section.

[0025] Specifically, in the construction of the dynamic power restoration model GP in step S1, the dynamic power restoration model GP is a collection of power lines of the entire regional power grid. , PL represents a whole line, a power line It is represented as a collection of several power facility nodes on the line , ={ }, For a normal collection of power lines, A collection of damaged power lines.

[0026] In step S3, the objective function is: According to the dynamic network topology model G and the dynamic power restoration model GP, a dynamic decision model for emergency repair is constructed; wherein, Indicates the minimum time to repair the entire regional power grid at the current moment, is the time required to repair node i, is the time taken to reach node i from the previous node, Indicates the next time slice The maximum power restored by the entire regional power grid upon arrival, is the jth power line The weight of .

[0027] The overall goal of emergency repair is to find a strategy to repair the power supply of the entire area in the shortest time under the current conditions, that is, the first objective function In order to ensure that the emergency repair strategy can adapt to the dynamic changes on site in a timely manner, the second goal is set In the current environment, the power in the area can be restored to the maximum extent when the next time slice arrives.

[0028] Furthermore, in this embodiment, the The value of is the jth power line The number of all power facility nodes.

[0029] Furthermore, in this embodiment, step S4, the best emergency repair strategy is calculated: according to the latest dynamic network topology model G and the dynamic power restoration model GP, as well as the location of the power facility node where the rescue team is currently located, the objective function is solved based on the Monte Carlo tree search algorithm to obtain the best emergency repair strategy.

[0030] Specifically, those skilled in the art can know that the Monte Carlo tree algorithm is a search method that applies the upper confidence interval algorithm UCB to the game tree, which is used to solve optimization problems and calculate random numbers, and includes four steps: selection, expansion, simulation, and back propagation. In a specific example of this implementation, further, the step S4 specifically includes: Step S41, taking the power facility node where the rescue team is currently located as the root node, and listing all power facility nodes that can be directly reached from the root node as optional child nodes according to the dynamic network topology model G; Step S42: Calculate the weight of each child node according to the UCB formula , select weights The largest value is taken as the optimal child node; Step S43, determining whether there are any unrepaired power facility nodes, if so, proceeding to step S44, if not, proceeding to step S45; Step S44 includes: Step S441, expanding the optimal child node selected in step S42 as a parent node, and listing the power facility nodes reachable from the parent node as optional child nodes; Step S442, randomly select an optional child node as a parent node for expansion, list the power facility nodes that can be reached from the parent node as optional child nodes, and return to step S43; Step S45, update the parameters of each optional child node i by backtracking update formula: , , , Where N represents the number of backtracking times. and They represent the new and old values ​​of the number of backtracking times respectively; Q(i) represents the weight function of the repair capability of child node i, and Respectively represent the new and old values ​​of the weight function of the repair capability of child node i; represents the weight function of the repair time of child node i, and Respectively represent the new value and old value of the weight function of the repair time of child node i; Indicates the change value of Q(i) caused by the expansion of the child node, Indicates the change value of T(i) caused by the expansion of the child node; Step S46, repeat steps S41-S45 iteratively until the preset total number of learning steps is completed, and then output the final optimal solution.

[0031] Furthermore, in this embodiment, an improved UCB formula is used to avoid the problem of local optimum that is easy to occur in the classic Monte Carlo tree search algorithm. The UCB formula is: , where i_father represents the parent node of child node i, N represents the number of backtracking of child node i, and is the adjustment factor, which is an empirical constant.

[0032] Furthermore, the calculation formula of the weight function Q(i) of the repair capability of the child node i is: , in, is the preset weight factor of the line corresponding to child node i, is the number of all power facility nodes in the line corresponding to child node i, is the number of unrepaired nodes in the line corresponding to child node i, is the level number of child node i in the tree.

[0033] Furthermore, the calculation formula of the weight function T(i) of the repair time of the child node i is: in, is the total time spent before reaching child node i, The time taken to repair child node i, is the time taken to reach child node i from the previous node.

[0034] Furthermore, after step S4, the method further includes: step S5, at the beginning of each new time slice T, repeating step S4 to calculate a new optimal emergency repair strategy until all repairs are completed.

[0035] Preferably, the step S5 also includes the step of immediately executing the step S4 when the traffic status of the highway section changes.

[0036] Since the situation at the disaster relief site changes dynamically, the emergency repair strategy needs to be adjusted dynamically according to the changes at the site. Therefore, a time slice T is set, and every time slice T, the value of the dynamic network topology model G is refreshed and the optimal emergency repair strategy is re-solved.

[0037] The method for dynamic dispatching of power disaster relief and repair of the present invention comprises the following steps: step S1, constructing a dynamic network topology model G of the disaster relief scene; step S2, constructing a dynamic power restoration model GP; step S3, constructing a dynamic decision model for repair: through the objective function: , according to the dynamic network topology model G and the dynamic power restoration model GP, a dynamic decision-making model for emergency repair is constructed; step S4, calculation of the best emergency repair strategy: according to the latest dynamic network topology model G and the dynamic power restoration model GP, as well as the location of the power facility node where the rescue team is currently located, the Monte Carlo tree search algorithm is used to solve and obtain the best emergency repair strategy. The method of the present invention takes into account the dynamic changes in the situation at the disaster relief site, and the emergency repair strategy can be dynamically adjusted according to the changes in the site. Furthermore, the Monte Carlo tree search algorithm is used to solve the optimal solution of the multi-objective function to determine the best emergency repair strategy; at the same time, the sub-node weights are improved. The UCB calculation formula avoids the problem of local optimality that is prone to occur in the classic Monte Carlo tree search algorithm.

[0038] The present invention also provides a dynamic dispatching system for power disaster relief and emergency repair, which is established and operated on the basis of a computer system, and specifically includes a memory 61, a processor 62, and a computer program 63 stored in the memory 61 and executable on the processor 62. When the processor 62 executes the computer program 63, the steps of the dynamic dispatching method for power disaster relief and emergency repair as described in any one of the above items are implemented.

[0039] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the computer.

[0040] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0041] The memory may be an internal storage unit, such as a hard disk or a memory; the memory may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory may include both an internal storage unit and an external storage device. The memory is used to store the computer program and other programs and data required by the terminal device. The memory may also be used to temporarily store data that has been output or is to be output.

[0042] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the dynamic dispatching method for power disaster relief and emergency repair as described in any one of the above items.

[0043] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0044] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0045] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0046] In the embodiments provided by the present invention, it should be understood that the disclosed devices / systems and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0047] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0048] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0049] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0050] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0051] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A dynamic dispatching method for power disaster relief and repair, characterized in that: The following steps are involved: Step S1, constructing a dynamic network topology model G for a disaster relief scenario: constructing the dynamic network topology model through an undirected graph G={P,R}, where P is the set of all power facility nodes, , is the set of power facility nodes whose current status is normal, is the set of power facility nodes that are currently damaged, R is the set of all highway sections, , is the set of road sections that are currently in normal and passable state. is the set of highway sections that are currently damaged; the weight value of P is the time required to repair the power facility node, The weight value of is the time required to pass through the highway section; Step S2, constructing a dynamic power restoration model GP: The dynamic power restoration model GP is a collection of power lines of the entire regional power grid, , For a normal collection of power lines, for the collection of damaged power lines; Step S3, constructing a dynamic decision model for emergency repair: through the objective function: , according to the dynamic network topology model G and the dynamic power restoration model GP, a dynamic decision model for emergency repair is constructed; wherein, Indicates the minimum time to repair the entire regional power grid at the current moment, is the time required to repair node i, is the time taken to reach node i from the previous node, Indicates the next time slice The maximum power restored by the entire regional power grid upon arrival, is the jth power line The weight of Step S4, calculation of the best emergency repair strategy: according to the latest dynamic network topology model G and the dynamic power restoration model GP, as well as the location of the power facility node where the rescue team is currently located, the objective function is solved based on the Monte Carlo tree search algorithm to obtain the best emergency repair strategy.

2. The method for dynamic dispatching of power disaster relief and repair according to claim 1, characterized in that: Said The value of is the jth power line The number of all power facility nodes.

3. The method for dynamic dispatching of power disaster relief and repair according to claim 1, characterized in that: The method further includes the following steps after step S4: at the beginning of each new time slice T, step S4 is repeated to calculate a new optimal emergency repair strategy until all repairs are completed.

4. The method for dynamic dispatching of power disaster relief and repair according to claim 1, characterized in that: The step S4 specifically includes: Step S41, taking the power facility node where the rescue team is currently located as the root node, and listing all power facility nodes that can be directly reached from the root node as optional child nodes according to the dynamic network topology model G; Step S42: Calculate the weight of each child node according to the UCB formula , select weights The largest value is taken as the optimal child node; Step S43, determining whether there are any unrepaired power facility nodes, if so, proceeding to step S44, if not, proceeding to step S45; Step S44 includes: Step S441, expanding the optimal child node selected in step S42 as a parent node, and listing the power facility nodes reachable from the parent node as optional child nodes; Step S442, randomly select an optional child node as a parent node for expansion, list the power facility nodes that can be reached from the parent node as optional child nodes, and return to step S43; Step S45, update the parameters of each optional child node i by backtracking update formula: ， ， ， Where N represents the number of backtracking times. and They represent the new and old values ​​of the number of backtracking times respectively; Q(i) represents the weight function of the repair capability of child node i, and Respectively represent the new and old values ​​of the weight function of the repair capability of child node i; represents the weight function of the repair time of child node i, and Respectively represent the new value and old value of the weight function of the repair time of child node i; Indicates the change value of Q(i) caused by the expansion of the child node, Indicates the change value of T(i) caused by the expansion of the child node; Step S46, repeat steps S41-S45 iteratively until the preset total number of learning steps is completed, and then output the final optimal solution.

5. The method for dynamic dispatching of power disaster relief and repair according to claim 4, characterized in that: The UCB formula is: , where i_father represents the parent node of child node i, N represents the number of backtracking of child node i, and is the adjustment factor, which is an empirical constant.

6. The method for dynamic dispatching of power disaster relief and repair according to claim 5, characterized in that: The calculation formula of Q(i) is: ， in, is the preset weight factor of the line corresponding to child node i, is the number of all power facility nodes in the line corresponding to child node i, is the number of unrepaired nodes in the line corresponding to child node i, is the level number of child node i in the tree.

7. The method for dynamic dispatching of power disaster relief and repair according to claim 6, characterized in that: The calculation formula of T(i) is: ;in, is the total time spent before reaching child node i, The time to repair child node i, is the time taken to reach child node i from the previous node.

8. The method for dynamic dispatching of power disaster relief and repair according to claim 3 is characterized in that: The step S5 also includes the step of immediately executing the step S4 when the traffic status of the highway section changes.

9. A dynamic dispatching system for power disaster relief and repair, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the dynamic dispatching method for power disaster relief and repair as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the dynamic dispatching method for power disaster relief and repair are implemented as described in any one of claims 1 to 8.

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