Emergency scheduling method, device and equipment based on unmanned aerial vehicle and storage medium

Abstract

The invention relates to the technical field of emergency and energy scheduling, and discloses an emergency scheduling method, device and equipment based on an unmanned aerial vehicle, and a storage medium, and the method comprises the steps: obtaining each unmanned aerial vehicle path from a starting point coordinate to a terminal point coordinate; according to the risk degree of each grid in each unmanned aerial vehicle path, the flight distance of each section of voyage in each unmanned aerial vehicle path and a preset cost generation model, generating the cost of each unmanned aerial vehicle path, selecting the unmanned aerial vehicle path with the minimum cost as an optimal unmanned aerial vehicle path, and obtaining an unmanned aerial vehicle scheduling scheme corresponding to the optimal unmanned aerial vehicle path; and according to the user loss cost, the load recovery cost and the energy storage battery deployment cost, generating a total loss cost corresponding to the unmanned aerial vehicle scheduling scheme, and when the total loss cost is less than a preset loss cost, selecting the unmanned aerial vehicle scheduling scheme as an emergency scheduling scheme of the power-losing area. According to the invention, the timeliness of emergency response is improved.

Description

Technical Field

[0001] The present application relates to the technical fields of emergency technology and energy dispatch technology, and particularly relates to an emergency dispatch method, device, equipment and storage medium based on an unmanned aerial vehicle (UAV). Background Art

[0003] With the large-scale access of new energy to the power grid, due to the inherent randomness and volatility characteristics of new energy power generation, the operation risk of the power grid becomes higher, and thus power outage areas are likely to occur. A power outage area refers to a geographical area in the power supply system where power supply is interrupted due to specific reasons, resulting in no power available or severely insufficient power supply.

[0004] However, the acquisition process of the existing emergency dispatch scheme for power outage areas is cumbersome, which is not conducive to improving the acquisition efficiency of the emergency dispatch scheme. The reason is that the existing technology mainly adopts the manual acquisition method to obtain the emergency dispatch scheme for power outage areas, and the manual acquisition method will consume a large amount of human and time resources, increasing the acquisition time of the emergency dispatch scheme for power outage areas. Therefore, it is not conducive to improving the acquisition efficiency of the emergency dispatch scheme. Summary of the Invention

[0005] The embodiments of the present application provide an emergency dispatch method, device, equipment and storage medium based on an unmanned aerial vehicle to solve the technical problem that the acquisition process of the existing emergency dispatch scheme for power outage areas is cumbersome and not conducive to improving the acquisition efficiency of the emergency dispatch scheme.

[0006] In a first aspect, the embodiments of the present application provide an emergency dispatch method based on an unmanned aerial vehicle, which is applied to an electronic device. The emergency dispatch method includes: Obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates; Obtain a grid map, traverse each grid of the grid map, and obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path. Generate the risk degree of each grid in each UAV path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk degree generation model; Generate the cost of each UAV path according to the risk degree of each grid in each UAV path, the flight distance of each section of the voyage in each UAV path, and a preset cost generation model. Select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV dispatch scheme corresponding to the preferred UAV path; Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV dispatch scheme; Generate the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model. When the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0007] In a possible implementation manner of the first aspect, the obtaining the coordinates of the power outage area, selecting the coordinates of the power outage area as the end coordinates, and obtaining each UAV path from the start coordinates to the end coordinates includes: Obtain power grid fault information, obtain the coordinates of the power outage area from the power grid fault information, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates.

[0008] In a possible implementation manner of the first aspect, the obtaining the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling plan includes: Generate the user loss cost of the UAV scheduling plan according to the unit power load loss value in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the power outage time in the power outage area, the flight time corresponding to the preferred UAV path, and a preset user loss cost generation model; Generate the load restoration cost of the UAV scheduling plan according to the number of UAV deployments at each node in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the discharge efficiency of the energy storage battery carried by the UAV, and a preset load restoration cost generation model; Generate the deployment cost of the UAV scheduling plan according to the yield rate of the energy storage battery, the operation years of the energy storage battery, the number of UAV deployments at each node in the power outage area, the unit power cost of the energy storage battery, the charging power of the energy storage battery carried by the UAV, the unit capacity cost, the capacity of the energy storage battery carried by the UAV, and a preset deployment cost generation model.

[0009] In a possible implementation manner of the first aspect, after the generating the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, and selecting the UAV scheduling plan as the emergency scheduling plan for the power outage area when the total loss cost is less than the preset loss cost, the emergency scheduling method includes: Create a display window and display the emergency scheduling plan through the display window.

[0010] In a possible implementation manner of the first aspect, the risk degree generation model is: ; Wherein, is the The risk level of the th grid in the th UAV path, is the number of obstacles in the neighborhood range of the th grid in the th UAV path, is the total number of grids in the neighborhood range of the th grid in the

[0011] In a possible implementation of the first aspect, the cost generation model is: ; where represents the cost of the th UAV path, is the first weight coefficient, is the second weight coefficient, is the flight distance of the th flight segment in the th UAV path, is the number of th UAV paths, is the risk level of the th grid in the th UAV path,

[0012] In a possible implementation of the first aspect, the total loss cost generation model is: ; where is the total loss cost; represents the user loss cost; represents the load recovery cost; represents the energy storage battery deployment cost.

[0013] In a second aspect, an embodiment of the present application provides an emergency scheduling device based on a UAV, which is applied to an electronic device and includes: A first acquisition module, configured to acquire the coordinates of a power outage area, select the coordinates of the power outage area as the end coordinates, and acquire each UAV path from the start coordinates to the end coordinates; A second acquisition module, configured to acquire a grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk level of each grid in each UAV path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk level generation model; A generation module, configured to generate the cost of each UAV path according to the risk degree of each grid in each UAV path, the flight distance of each flight segment in each UAV path, and a preset cost generation model, select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV scheduling plan corresponding to the preferred UAV path; A third acquisition module, configured to acquire the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling plan; A scheduling module, configured to generate the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, and when the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, including 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 emergency scheduling method according to any one of the above first aspects is implemented.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the emergency scheduling method according to any one of the above first aspects is implemented.

[0016] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device is enabled to execute the emergency scheduling method according to any one of the above first aspects.

[0017] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: The beneficial effects of the embodiments of the present application are in two aspects. On the one hand, according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, the total loss cost corresponding to the UAV scheduling plan is generated. When the total loss cost is less than the preset loss cost, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. Since it is not necessary to obtain it manually, the acquisition time of the emergency scheduling plan for the power outage area is reduced, which is beneficial to improving the acquisition efficiency of the emergency scheduling plan for the power outage area. On the other hand, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. Compared with the traditional ground transportation method, the emergency scheduling plan of the present application can avoid road traffic obstacles, reduce the emergency response time, and is beneficial to improving the timeliness of emergency response. Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0019] Figure 1 It is an application scenario diagram of the emergency dispatch method provided by the embodiments of the present application; Figure 2 It is a schematic flowchart of the emergency dispatch method provided by the embodiments of the present application; Figure 3 It is a flowchart of obtaining the cost provided by the embodiments of the present application; Figure 4 It is a schematic block diagram of the emergency dispatch device provided by the embodiments of the present application; Figure 5 It is a schematic structural diagram of the electronic device provided by the embodiments of the present application; Figure 6 It is a result diagram of implementing the emergency dispatch method provided by the embodiments of the present application. Detailed implementation manners

[0020] In order to make the purpose, technical solutions and advantages of the present application clearer, the following further details the present application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0021] In addition, in the description of the specification and the appended claims of the present application, the terms "first", "second", "third", etc. are only used for descriptive distinction and cannot be understood as indicating or implying relative importance.

[0022] In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of the technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0023] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all the contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order may be changed according to the actual situation.

[0024] The emergency dispatching method provided by the embodiments of the present application can be applied to electronic devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, personal computers, and personal digital assistants (PDAs). The embodiments of the present application do not impose any restrictions on the specific types of electronic devices.

[0025] Please refer to Figure 1 , Figure 1 which is an application scenario diagram of the emergency dispatching method provided by the embodiments of the present application, and is described in detail as follows: Figure 1 It includes a drone carrying a battery, a power outage area, and a road failure.

[0026] Among them, the drone carrying a battery means that the drone carries an energy storage battery.

[0027] The road traffic obstacles include those caused by road failures and those not caused by road failures.

[0028] The road traffic obstacles not caused by road failures include, but are not limited to, illegal occupation of roads and accident handling.

[0029] Road failures include, but are not limited to, road collapses, road cracks, and road closures due to construction.

[0030] Among them, when a natural disaster or sudden accident causes a power outage and ground traffic paralysis, traditional vehicles may not be able to arrive in time due to road failures on the ground. However, drones, relying on their aerial mobility, can bypass the road failures on the ground and directly fly to the power outage area to deliver the energy storage battery, providing temporary power support for the power outage area.

[0031] In the embodiments of the present application, since drone delivery avoids fuel dependence and long-distance dispatching of ground transportation, the time for power restoration is reduced, and the social and economic losses caused by power outages can be minimized to the greatest extent.

[0032] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of the emergency dispatching method provided by the embodiments of the present application. This method can be applied to an electronic device.

[0033] As Figure 2 shown, the emergency dispatching method provided by the embodiments of the present application includes the following steps, which are described in detail as follows: S201, obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each drone path from the start coordinates to the end coordinates; Among them, obtaining the coordinates of the power outage area, selecting the coordinates of the power outage area as the end coordinates, and obtaining each UAV path from the start coordinates to the end coordinates includes: Obtaining power grid fault information, obtaining the coordinates of the power outage area from the power grid fault information, selecting the coordinates of the power outage area as the end coordinates, and obtaining each UAV path from the start coordinates to the end coordinates.

[0034] Exemplarily, obtaining power grid fault information, obtaining the coordinates of the power outage area from the power grid fault information, selecting the coordinates of the power outage area as the end coordinates, and obtaining each UAV path from the start coordinates to the end coordinates includes: Obtaining power grid fault information, obtaining the coordinates of the power outage area from the power grid fault information, and selecting the coordinates of the power outage area as the end coordinates; According to the constraint conditions of path planning, screening multiple original paths from the start coordinates to the end coordinates to obtain each UAV path from the start coordinates to the end coordinates; Among them, the constraint conditions include the first condition, the second condition, the third condition, the fourth condition, and the fifth condition. The first condition is that each flight distance of the UAV is not less than the minimum path length. The second condition is that the flight range of the UAV is less than the maximum range. The third condition is that the current turning angle of the UAV during flight does not exceed the maximum turning angle. The fourth condition is that the current climbing angle of the UAV during takeoff or flight does not exceed the maximum climbing angle. The fifth condition is that the current load of the UAV during takeoff or flight does not exceed the maximum load.

[0035] Among them, through the first condition, the second condition, the third condition, the fourth condition, and the fifth condition, the rationality of the UAV path and the stability of flight are ensured.

[0036] S202. Obtain a grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk level of each grid in each UAV path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk level generation model. Among them, the risk level generation model is: ; Among them, is the risk level of the th grid in the th UAV path, is the number of obstacles in the neighborhood range of the th grid in the th UAV path, is the th grid in the The total number of grids within the neighborhood range of a grid.

[0037] Among them, the risk generation model is the model for generating the risk.

[0038] Among them, a grid map is obtained. The grid map is used to represent the three-dimensional spatial information of the low-altitude area of the city. In the grid map, the low-altitude area of the city is evenly divided into multiple grids, and each grid represents a specific spatial unit. For example, each grid corresponds to a real area of 10 cubic meters.

[0039] For the convenience of explanation, the following is an example: For example, the first UAV path has 3 grids, which are Grid 1, Grid 2, and Grid 3 respectively; The neighborhood range is a 4-neighborhood. The neighborhood range of Grid 1 is the 4 adjacent grids above, below, left, and right of Grid 1. There is only one obstacle among the 4 adjacent grids above, below, left, and right of Grid 1. The number of obstacles in the neighborhood range of Grid 1 is 1. Since the total number of grids in the neighborhood range of Grid 1 is 4, the number of obstacles in the neighborhood range of Grid 1 is divided by the total number of grids in the neighborhood range of Grid 1. Therefore, the risk of Grid 1 is 0.25.

[0040] The neighborhood range is a 4-neighborhood. The neighborhood range of Grid 2 is the 4 adjacent grids above, below, left, and right of Grid 2. There is only one obstacle among the 4 adjacent grids above, below, left, and right of Grid 2. The number of obstacles in the neighborhood range of Grid 2 is 2. Since the total number of grids in the neighborhood range of Grid 2 is 4, the number of obstacles in the neighborhood range of Grid 2 is divided by the total number of grids in the neighborhood range of Grid 2. Therefore, the risk of Grid 2 is 0.5.

[0041] The neighborhood range is a 4-neighborhood. The neighborhood range of Grid 3 is the 4 adjacent grids above, below, left, and right of Grid 3. There is only one obstacle among the 4 adjacent grids above, below, left, and right of Grid 3. The number of obstacles in the neighborhood range of Grid 3 is 0. Since the total number of grids in the neighborhood range of Grid 3 is 4, the number of obstacles in the neighborhood range of Grid 3 is divided by the total number of grids in the neighborhood range of Grid 3. Therefore, the risk of Grid 3 is 0.

[0042] S203. According to the risk of each grid in each UAV path, the flight distance of each section of the voyage in each UAV path, and a preset cost generation model, generate the cost of each UAV path, select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV scheduling plan corresponding to the preferred UAV path; Among them, the cost generation model is: ; Among them, represents the cost of the th UAV path, is the first weight coefficient, is the second weight coefficient, is the flight distance of the th leg of the Kth UAV path, is the number of legs of the Kth UAV path, and is the risk level of the th grid in the

[0043] where the cost generation model is for generating costs.

[0044] Among them, selecting the UAV path with the minimum cost as the preferred UAV path can reduce the energy loss caused by sudden stops or turns and extend the UAV's endurance.

[0045] S204. Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling plan; S205. Generate the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model. When the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0046] Among them, the total loss cost generation model is: ; where is the total loss cost; represents the user loss cost; represents the load restoration cost; represents the energy storage battery deployment cost.

[0047] Among them, the user loss cost represents the loss cost caused by the power outage.

[0048] Among them, the load restoration cost represents the cost required to restore power supply.

[0049] Among them, the energy storage battery deployment cost is the deployment cost of the energy storage battery.

[0050] Among them, the total loss cost generation model is for generating the total loss cost.

[0051] Among them, when selecting the UAV scheduling plan as the emergency scheduling plan for the power outage area, due to the three-dimensional maneuverability of the UAV, it can avoid surface obstacles during emergency delivery, which can not only reduce the user's power outage waiting time but also reduce the loss cost of the power grid operator, ultimately achieving a win-win situation for both parties.

[0052] Among them, according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, the total loss cost corresponding to the UAV scheduling plan is generated. When the total loss cost is less than the preset loss cost, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. After that, the emergency scheduling method includes: Create a display window and display the emergency scheduling plan through the display window.

[0053] The beneficial effects of the embodiments of the present application are in two aspects. On the one hand, according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, the total loss cost corresponding to the UAV scheduling plan is generated. When the total loss cost is less than the preset loss cost, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. Since it does not require manual acquisition, the acquisition time of the emergency scheduling plan for the power outage area is reduced, which is beneficial to improving the acquisition efficiency of the emergency scheduling plan for the power outage area. On the other hand, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. Compared with the traditional ground transportation method, the emergency scheduling plan of the present application can avoid road traffic obstacles, reduce the emergency response time, and is beneficial to improving the timeliness of the emergency response.

[0054] Please refer to Figure 3 , Figure 3 which is the flowchart of obtaining the cost provided by the embodiments of the present application, and is described in detail as follows: S301, according to the unit power load loss value in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the power outage time of the power outage area, the flight time corresponding to the preferred UAV path, and a preset user loss cost generation model, generate the user loss cost of the UAV scheduling plan; Exemplarily, the user loss cost generation model is: ; Among them, represents the user loss cost; L is the unit power load loss value in the power outage area, is the discharge power of the energy storage battery carried by the UAV at the xth node in the power outage area, is the power outage time of the power outage area, is the flight time corresponding to the preferred UAV path.

[0055] Among them, the user loss cost generation model is the generation model of the user loss cost.

[0056] S302. Generate the load restoration cost of the UAV scheduling plan according to the number of UAVs deployed at each node in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the discharge efficiency of the energy storage battery carried by the UAV, and a preset load restoration cost generation model. Exemplarily, the load restoration cost generation model is: ; Where, represents the load restoration cost; represents the number of UAVs deployed at the x-th node in the power outage area, is the number of nodes, is the discharge power of the energy storage battery carried by the UAV at the x-th node in the power outage area, η is the discharge efficiency of the energy storage battery carried by the UAV, is the power outage time of the power outage area, is the flight time corresponding to the optimal UAV path.

[0057] Where, the load restoration cost generation model is the generation model of the load restoration cost.

[0058] Discharge power: It refers to the energy released by the energy storage battery per unit time, and the unit is watt or kilowatt. The discharge power reflects the speed of the energy storage battery discharging. The larger the power, the more energy the energy storage battery releases in the same time, and the faster the discharge speed.

[0059] Discharge efficiency: It refers to the ratio of the actual output electric energy of the energy storage battery during discharge to the total electric energy stored in the energy storage battery, and is usually expressed as a percentage. The discharge efficiency measures the effective degree of energy conversion during the discharge process of the energy storage battery. The higher the efficiency, the smaller the energy loss of the energy storage battery during discharge, and the more efficiently the stored chemical energy can be converted into electric energy output.

[0060] Exemplarily, the deployment cost generation model is: ; Where, represents the energy storage battery deployment cost; γ is the yield rate of the energy storage battery; T is the operation years of the energy storage battery; represents the number of UAVs deployed at the x-th node in the power outage area; is the number of nodes, is the unit power cost of the energy storage battery, is the rated power of the energy storage battery carried by the UAV, is the unit capacity cost, E is the capacity of the energy storage battery carried by the UAV.

[0061] Among them, the deployment cost generation model is the generation model of the deployment cost of the energy storage battery.

[0062] In the embodiment of the present application, obtaining the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling scheme is beneficial to obtaining the total loss cost corresponding to the UAV scheduling scheme.

[0063] Corresponding to the emergency scheduling method described in the above embodiment, please refer to Figure 4 , Figure 4 which is a schematic block diagram of the emergency scheduling device provided in the embodiment of the present application. Figure 4 The emergency scheduling device 400 shown can be applied to an electronic device in the application scenario diagram as shown in Figure 1 Taking the electronic device as an example, the emergency scheduling device 400 shown in Figure 4 will be elaborated in detail below. The emergency scheduling device 400 may include a first acquisition module 401, a second acquisition module 402, a generation module 403, a third acquisition module 404, and a scheduling module 405.

[0064] The first acquisition module 401 is configured to acquire the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and acquire each UAV path from the start coordinates to the end coordinates. The second acquisition module 402 is configured to acquire a grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk level of each grid in each UAV path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk level generation model. The generation module 403 is configured to generate the cost of each UAV path according to the risk level of each grid in each UAV path, the flight distance of each flight segment in each UAV path, and a preset cost generation model, select the UAV path with the minimum cost as the preferred UAV path, and acquire the UAV scheduling scheme corresponding to the preferred UAV path. The third acquisition module 404 is configured to acquire the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling scheme. The scheduling module 405 is configured to generate the total loss cost corresponding to the UAV scheduling scheme according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, and when the total loss cost is less than the preset loss cost, select the UAV scheduling scheme as the emergency scheduling scheme for the power outage area.

[0065] It should be noted that the various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference can be made to each other.

[0066] The beneficial effects of the embodiments of this application are in two aspects. On the one hand, according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, the total loss cost corresponding to the UAV scheduling plan is generated. When the total loss cost is less than the preset loss cost, the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area. Since it is not necessary to obtain it manually, the acquisition time of the emergency scheduling plan for the power outage area is reduced, which is beneficial to improving the acquisition efficiency of the emergency scheduling plan for the power outage area. On the other hand, when the UAV scheduling plan is selected as the emergency scheduling plan for the power outage area, compared with the traditional ground transportation method, the emergency scheduling plan of this application can avoid road traffic obstacles, reduce the emergency response time, and is beneficial to improving the timeliness of emergency response.

[0067] Please refer to Figure 5 , Figure 5 which is the structural schematic diagram of the electronic device provided by the embodiment of this application.

[0068] As Figure 5 shown, Figure 5 the electronic device 2 includes: at least one processor 20, a memory 21, and a computer program 22 stored in the memory 21 and executable on the at least one processor 20. When the processor 20 executes the computer program 22, the steps in any of the above method embodiments are implemented.

[0069] The electronic device 2 may include, but is not limited to, the processor 20 and the memory 21. Those skilled in the art can understand that Figure 5 this is only an example of the electronic device 2 and does not constitute a limitation on the electronic device 2. It may include more or fewer components than shown in the figure, or combine some components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0070] Among them, the processor 20 is used to run the computer program 22 stored in the memory 21 and implement the following steps when executing the computer program 22: Obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates; Obtain a raster map, traverse each grid of the raster map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk level of each grid in each UAV path according to the number of obstacles, the total number of grids in the neighborhood range of each grid in each UAV path, and a preset risk level generation model. Generate the cost of each UAV path according to the risk level of each grid in each UAV path, the flight distance of each leg of the journey in each UAV path, and a preset cost generation model, select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV scheduling plan corresponding to the preferred UAV path. Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling plan. Generate the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model. When the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0071] In some embodiments, the processor 20 is configured to implement: Obtain power grid fault information, obtain the coordinates of the power outage area from the power grid fault information, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates.

[0072] In some embodiments, the processor 20 is configured to implement: Generate the user loss cost of the UAV scheduling plan according to the value of unit power load loss in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the power outage time of the power outage area, the flight time corresponding to the preferred UAV path, and a preset user loss cost generation model. Generate the load restoration cost of the UAV scheduling plan according to the number of UAV deployments at each node in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the discharge efficiency of the energy storage battery carried by the UAV, and a preset load restoration cost generation model. Generate the deployment cost of the UAV scheduling plan according to the yield rate of the energy storage battery, the operating years of the energy storage battery, the number of UAV deployments at each node in the power outage area, the unit power cost of the energy storage battery, the charging power of the energy storage battery carried by the UAV, the unit capacity cost, the capacity of the energy storage battery carried by the UAV, and a preset deployment cost generation model.

[0073] In some embodiments, the processor 20 is configured to implement: Create a display window and display the emergency scheduling plan through the display window.

[0074] The so-called processor 20 may be a Central Processing Unit (CPU), and the processor 20 may also be other general-purpose processors, digital signal processors, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0075] In some embodiments, the memory 21 may be an internal storage unit of the electronic device 2, such as a hard disk or memory of the electronic device 2. In other embodiments, the memory 21 may also be an external storage device of the electronic device 2, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. equipped on the electronic device 2. Further, the memory 21 may also include both the internal storage unit of the electronic device 2 and the external storage device. The memory 21 is used to store an operating system, application programs, a Boot Loader, data, and other programs, such as the program code of the computer program, etc. The memory 21 may also be used to temporarily store data that has been output or will be output.

[0076] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units, due to being based on the same concept as the method embodiment of the present application, for their specific functions and the technical effects brought, please refer to the method embodiment part specifically, and will not be elaborated here.

[0077] Please refer to Figure 6 , Figure 6 which is the result diagram of the implementation emergency dispatch method provided by the embodiment of the present application.

[0078] As Figure 6 shown, Figure 6 it shows the dispatch quantity of each power outage node and the corresponding load demand, indicating that the energy storage battery carried by the unmanned aerial vehicle can accurately match the power gap of each node; it shows the actual output and state of charge change of the energy storage battery of each node, verifying the stability of the efficiency of the energy storage battery during the discharge process; it compares the loss cost before dispatch and the loss cost after dispatch.

[0079] Among them, Figure 6Including the dispatching quantity, the loss cost before dispatching, the load demand, the energy storage output, the state of charge, and the loss cost after dispatching; There are 6 nodes in the power outage area, namely Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6; the nodes in the power outage area are simply referred to as power outage nodes.

[0080] The value range of the dispatching quantity is from 0 to 12 aircraft; The dispatching quantity of Node 1 is 2 aircraft, indicating that 2 unmanned aerial vehicles are deployed at Node 1; The dispatching quantity of Node 2 is 2 aircraft, indicating that 2 unmanned aerial vehicles are deployed at Node 2; The dispatching quantity of Node 3 is 4 aircraft, indicating that 4 unmanned aerial vehicles are deployed at Node 3; The dispatching quantity of Node 4 is 3 aircraft, indicating that 3 unmanned aerial vehicles are deployed at Node 4; The dispatching quantity of Node 5 is 3 aircraft, indicating that 3 unmanned aerial vehicles are deployed at Node 5; The dispatching quantity of Node 6 is 2 aircraft, indicating that 2 unmanned aerial vehicles are deployed at Node 6; The value ranges of the energy storage output and the load demand are both from 0 KW to 1000 KW; The energy storage outputs of Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6 are 412 KW, 500 KW, 920 KW, 650 KW, 750 KW, and 360 KW respectively.

[0081] The load demands of Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6 are 412 KW, 555 KW, 920 KW, 650 KW, 840 KW, and 360 KW respectively.

[0082] The value range of the state of charge is from 0.2 to 0.5.

[0083] The states of charge of Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6 are 0.38, 0.25, 0.31, 0.35, 0.25, and 0.46 respectively.

[0084] The value ranges of the loss cost before dispatching and the loss cost after dispatching are from 0 ten thousand yuan to 45 ten thousand yuan; The loss costs before dispatching of Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6 are: 18.54 ten thousand yuan, 24.97 ten thousand yuan, 41.4 ten thousand yuan, 29.25 ten thousand yuan, 37.8 ten thousand yuan, and 16.2 ten thousand yuan respectively; The loss costs after dispatching of Node 1, Node 2, Node 3, Node 4, Node 5, and Node 6 are: 5 ten thousand yuan, 6.74 ten thousand yuan, 11.18 ten thousand yuan, 7.9 ten thousand yuan, 10.21 ten thousand yuan, and 4.37 ten thousand yuan respectively; The loss cost after scheduling is the total loss cost. After adopting the method of this application, the total loss costs of nodes 1 to 6 are significantly reduced, reflecting the comprehensive advantages of this method in reducing user loss costs, load restoration costs, and energy storage deployment costs.

[0085] Figure 6 As can be seen, the deployment quantity and discharge power of the drones are highly adaptable to the node requirements, further verifying the effectiveness of the method of this application in the collaborative optimization of path planning and cost.

[0086] Figure 6 The technical effects of the method of this application in optimizing resource allocation and reducing social and economic losses are intuitively demonstrated through multi-dimensional data, providing empirical support for the beneficial effects of the method.

[0087] The embodiment of this application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0088] Program code is stored in the computer-readable storage medium, and the program code can be called by the processor to execute the emergency scheduling method described in the above method embodiments.

[0089] The computer-readable storage medium has a storage space for program code.

[0090] The program code includes the code for any step in the emergency scheduling method described in the above method embodiments.

[0091] For example, when the program code is called by the processor, the following steps can be executed: Obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each drone path from the start coordinates to the end coordinates; Obtain the grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each drone path, and generate the risk level of each grid in each drone path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each drone path and a preset risk level generation model; Generate the cost of each drone path according to the risk level of each grid in each drone path, the flight distance of each section of the voyage in each drone path, and a preset cost generation model, select the drone path with the minimum cost as the preferred drone path, and obtain the drone scheduling plan corresponding to the preferred drone path; Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the drone scheduling plan; Generate the total loss cost corresponding to the UAV scheduling plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model. When the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0092] For the specific implementation of each of the above operations, reference may be made to the previous embodiments, which will not be elaborated herein.

[0093] Among them, the computer-readable storage medium may also be an external storage device of the emergency scheduling device or the electronic device. For example, a plug-in hard disk equipped on the emergency scheduling device or the electronic device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, a non-transitory computer-readable storage medium, etc.

[0094] Since the computer program stored in the computer-readable storage medium can execute any one of the emergency scheduling methods provided by the embodiments of the present application, the computer-readable storage medium can achieve the beneficial effects that any one of the emergency scheduling methods provided by the embodiments of the present application can achieve. For details, reference may be made to the previous embodiments, which will not be elaborated herein.

[0095] The embodiments of the present application provide a computer program product. When the computer program product runs on an electronic device, the electronic device is enabled to execute the above-mentioned emergency scheduling method.

[0096] When the computer program product is loaded by the electronic device, the following steps can be executed: Obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates; Obtain a grid map, traverse each grid of the grid map, and obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path. According to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk degree generation model, generate the risk degree of each grid in each UAV path; According to the risk degree of each grid in each UAV path, the flight distance of each leg of each UAV path, and a preset cost generation model, generate the cost of each UAV path, select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV scheduling plan corresponding to the preferred UAV path; Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV scheduling plan; According to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, generate the total loss cost corresponding to the UAV scheduling plan. When the total loss cost is less than the preset loss cost, select the UAV scheduling plan as the emergency scheduling plan for the power outage area.

[0097] If the integrated 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.

[0098] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiments and will not be elaborated here.

[0099] Based on such an understanding, to implement all or part of the processes in the above method embodiments of this application, it can be completed by instructing 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 a processor, the steps of the above method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electrical carrier signal, a telecommunications signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunications signal.

[0100] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0101] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present application.

Claims

1. An emergency scheduling method based on drones, characterized in that, Applied to an electronic device, the emergency dispatch method includes: Obtain the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates; Obtain a grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk level of each grid in each UAV path according to the number of obstacles, the total number of grids in the neighborhood range of each grid in each UAV path, and a preset risk level generation model; Generate the cost of each UAV path according to the risk level of each grid in each UAV path, the flight distance of each section of the voyage in each UAV path, and a preset cost generation model, select the UAV path with the minimum cost as the preferred UAV path, and obtain the UAV dispatch plan corresponding to the preferred UAV path; Obtain the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV dispatch plan; Generate the total loss cost corresponding to the UAV dispatch plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model. When the total loss cost is less than the preset loss cost, select the UAV dispatch plan as the emergency dispatch plan for the power outage area.

2. The emergency dispatching method according to claim 1, wherein The obtaining the coordinates of the power outage area, selecting the coordinates of the power outage area as the end coordinates, and obtaining each UAV path from the start coordinates to the end coordinates includes: Obtain power grid fault information, obtain the coordinates of the power outage area from the power grid fault information, select the coordinates of the power outage area as the end coordinates, and obtain each UAV path from the start coordinates to the end coordinates.

3. The emergency dispatching method according to claim 1, wherein The obtaining the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV dispatch plan includes: Generate the user loss cost of the UAV dispatch plan according to the unit power load loss value in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the power outage time in the power outage area, the flight time corresponding to the preferred UAV path, and a preset user loss cost generation model; Generate the load restoration cost of the UAV dispatch plan according to the number of UAVs deployed at each node in the power outage area, the discharge power of the energy storage battery carried by the UAV at each node in the power outage area, the discharge efficiency of the energy storage battery carried by the UAV, and a preset load restoration cost generation model; Generate the deployment cost of the UAV dispatch plan according to the yield rate of the energy storage battery, the operating years of the energy storage battery, the number of UAVs deployed at each node in the power outage area, the unit power cost of the energy storage battery, the charging power of the energy storage battery carried by the UAV, the unit capacity cost, the capacity of the energy storage battery carried by the UAV, and a preset deployment cost generation model.

4. The emergency scheduling method according to claim 1, wherein After generating the total loss cost corresponding to the UAV dispatch plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, and when the total loss cost is less than the preset loss cost, selecting the UAV dispatch plan as the emergency dispatch plan for the power outage area, the emergency dispatch method includes: Create a display window and display the emergency dispatch plan through the display window.

5. The emergency dispatching method according to any one of claims 1 to 4, characterized in that The risk degree generation model is: ； Among them, is the hazard level of the th grid in the th UAV path, is the number of obstacles in the neighborhood range of the th grid in the th UAV path, is the total number of grids in the neighborhood range of the th grid in the th UAV path.

6. The emergency dispatching method according to any one of claims 1 to 4, characterized in that The cost generation model is: ； Among them, represents the cost of the th UAV path, is the first weight coefficient, is the second weight coefficient, is the flight distance of the th segment of the Kth UAV path, is the number of segments of the Kth UAV path, is the th grid hazard in the th UAV path, is the th number of grids of the UAV path.

7. The emergency dispatching method according to any one of claims 1 to 4, characterized in that The total loss cost generation model is: ； Among them, is the total loss cost; represents the user loss cost; represents the load restoration cost; represents the energy storage battery deployment cost.

8. An emergency dispatching device based on a drone, characterized in that, Applied to an electronic device, including: A first acquisition module, configured to acquire the coordinates of the power outage area, select the coordinates of the power outage area as the end coordinates, and acquire each UAV path from the start coordinates to the end coordinates; A second acquisition module, configured to acquire a grid map, traverse each grid of the grid map, obtain the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path, and generate the risk degree of each grid in each UAV path according to the number of obstacles and the total number of grids in the neighborhood range of each grid in each UAV path and a preset risk degree generation model; A generation module, configured to generate the cost of each UAV path according to the risk degree of each grid in each UAV path, the flight distance of each leg of each UAV path, and a preset cost generation model, select the UAV path with the minimum cost as the preferred UAV path, and acquire the UAV dispatch plan corresponding to the preferred UAV path; A third acquisition module, configured to acquire the user loss cost, load restoration cost, and energy storage battery deployment cost of the UAV dispatch plan; A dispatch module, configured to generate the total loss cost corresponding to the UAV dispatch plan according to the user loss cost, load restoration cost, energy storage battery deployment cost, and a preset cost generation model, and when the total loss cost is less than a preset loss cost, select the UAV dispatch plan as the emergency dispatch plan for the power outage area.

9. An electronic device, 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, it implements the emergency dispatch method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the emergency dispatch method according to any one of claims 1 to 7.

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