A container loading method and device for power facility post-disaster, an electronic device and a storage medium

Abstract

The application discloses a container loading method and device for power facility post-disaster, electronic equipment and storage medium, and the method comprises the following steps: acquiring the number and size of the container, the size of each type of unmanned aerial vehicle and the size of unit repair materials; according to the number and size of the container, the size of each type of unmanned aerial vehicle and the size of unit repair materials, the remaining loadable volume of the container is calculated; according to the remaining loadable volume, the maximum number corresponding to the situation that the remaining loadable volume is all used to load unit repair materials, line patrol type unmanned aerial vehicles and transport type unmanned aerial vehicles is respectively calculated; according to the corresponding maximum number and the corresponding weight coefficient, a loading configuration model is constructed; the loading configuration model is solved to obtain the target number corresponding to unit repair materials, line patrol type unmanned aerial vehicles and transport type unmanned aerial vehicles; and the remaining loadable volume is loaded according to the target number. Through the implementation of the application, the problem that the repair demand of the disaster area cannot be met due to unreasonable loading plan can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of logistics and transportation management, and particularly relates to a container loading method and device for post-disaster power facilities, an electronic device and a storage medium. BACKGROUND

[0002] In the aspect of transporting rescue materials for power facilities in disaster areas, unmanned aerial vehicles (UAVs) show great potential, especially in the face of complex terrain and harsh weather conditions. Traditional ground transportation methods are often hindered, such as damaged roads, traffic paralysis, or large transportation tools unable to enter disaster areas. Unmanned aerial vehicles, with their strong maneuverability and ability to quickly adapt to various environments, can effectively transport emergency materials to disaster areas.

[0003] A successful UAV material transportation not only depends on the performance of the aircraft, but also requires a reasonable transportation plan. This includes comprehensive consideration of transportation routes, container loading plans, and UAV launch and recovery locations to ensure that rescue needs can be met quickly in emergency situations.

[0004] In actual scenarios, it is necessary to load UAVs and rescue materials in containers. If too many rescue materials are loaded and too few UAVs are loaded, the transportation efficiency of the UAVs will be low, and various materials cannot be transported to the corresponding rescue areas within the specified time. If too few rescue materials are loaded and too many UAVs are loaded, the rescue materials will be insufficient to meet the needs of the rescue area. Therefore, how to effectively balance the number of rescue materials and UAVs is a problem that needs to be solved. SUMMARY

[0005] The present application provides a container loading method and device for post-disaster power facilities, an electronic device and a storage medium. By implementing the present application, the appropriate number of rescue materials and UAVs can be loaded in a limited container volume, which is used to transport rescue materials to disaster areas by UAVs for post-disaster power facilities, so that rescue personnel can obtain rescue materials as soon as possible to implement the rescue of power facilities, thereby ensuring that rescue needs can be met quickly in emergency situations.

[0006] An embodiment of the present application provides a container loading method for post-disaster power facilities, comprising:

[0007] The number of containers to be configured, the size of the containers to be configured, the size of each type of UAV to be loaded into the containers, and the size of the unit rescue materials to be loaded into the containers are obtained. The UAV types include transportation UAVs, line patrol UAVs, and communication UAVs, and each container needs to load a communication UAV and at least a preset number of unit rescue materials.

[0008] The total loadable volume of the container is calculated according to the number of containers to be configured and the size of the containers to be configured. The remaining loadable volume of the container is calculated according to the communication type unmanned aerial vehicle to be loaded in each container, the size of the communication type unmanned aerial vehicle, at least a preset number of unit repair materials, the size of the unit repair material, and the total loadable volume.

[0009] According to the size of the unit repair material, the first maximum number of loadable unit repair materials is calculated when the remaining loadable volume is used for loading unit repair materials; according to the size of the line inspection type unmanned aerial vehicle, the second maximum number of loadable line inspection type unmanned aerial vehicles is calculated when the remaining loadable volume is used for line inspection type unmanned aerial vehicles. According to the size of the transport type unmanned aerial vehicle, the third maximum number of loadable transport type unmanned aerial vehicles is calculated when the remaining loadable volume is used for transport type unmanned aerial vehicles.

[0010] According to the first maximum number, the second maximum number, the third maximum number, and the corresponding weight coefficient, a loading configuration model is constructed. The weight coefficient is calculated by the analytic hierarchy process.

[0011] Under the constraint of the remaining loadable volume, the loading configuration model is solved, and the first target number of loadable unit repair materials, the second target number of loadable line inspection type unmanned aerial vehicles, and the third target number of loadable transport type unmanned aerial vehicles are calculated when the target value of the loading configuration model is maximum.

[0012] According to the first target number, the second target number, and the third target number, the remaining loadable volume of the container is loaded.

[0013] Further, according to the first target number, the second target number, and the third target number, the remaining loadable volume of the container is loaded, including:

[0014] According to the first target number, the second target number, and the third target number, the size of each type of unmanned aerial vehicle to be loaded, and the size of the unit repair material to be loaded, a container packing layout plan is generated based on a container packing algorithm.

[0015] According to the container packing layout plan, the remaining loadable volume of the container is loaded.

[0016] Further, the deployment position of the container to be configured is determined by:

[0017] The performance parameters of each type of unmanned aerial vehicle to be loaded, the position of the target site, the position of the distribution network transmission line, and the position of the main network transmission line are obtained. The target site includes a disaster site and a non-disaster high-voltage equipment tower foundation.

[0018] According to the performance parameters of the various types of unmanned aerial vehicles to be loaded into the container and the location of the target site, a rough deployment position of the container to be configured is generated based on the farthest distance that can be reached by the transport unmanned aerial vehicle in a full load state flying out and returning to the nest in an empty load state.

[0019] According to the location of the distribution network transmission line, the location of the main network transmission line and the location of the target site, a final deployment position of the container to be configured is calculated and generated based on the rough deployment position.

[0020] Further, the rough deployment position of the container to be configured is generated according to the performance parameters of the various types of unmanned aerial vehicles to be loaded into the container and the location of the target site, based on the farthest distance that can be reached by the transport unmanned aerial vehicle in a full load state flying out and returning to the nest in an empty load state.

[0021] According to the performance parameters of the transport unmanned aerial vehicle, the farthest limit distance from the nest that can be reached by the transport unmanned aerial vehicle in a full load state flying out and returning to the nest in an empty load state is calculated in the process of flying out in one direction from the nest with full power and successfully returning to the nest.

[0022] For each target site, a concentric circular region corresponding to each target site is generated with the target site as the center and the first limit distance as the radius.

[0023] The overlapping region between different concentric circular regions is taken as the rough deployment position of the container to be configured.

[0024] Further, before the remaining loadable volume of the container is loaded according to the first target quantity, the second target quantity, the third target quantity, the size of the various types of unmanned aerial vehicles to be loaded into the container and the size of the unit repair materials to be loaded into the container, the method further comprises:

[0025] A first product result is generated by calculating the product of the first target quantity and a preset ratio, and the first product result is taken as the updated first target quantity.

[0026] A second product result is generated by calculating the product of the third target quantity and a preset ratio, and the second product result is taken as the updated third target quantity.

[0027] On the basis of the above-mentioned method embodiment, the application correspondingly provides a device embodiment.

[0028] An embodiment of the application provides a container loading device for power facility post-disaster, which comprises a data acquisition module, a remaining loadable volume calculation module, a maximum quantity calculation module, a loading configuration model construction module, a model solving module and a container loading module.

[0029] The data acquisition module is configured to acquire the number of containers to be configured, the size of the containers to be configured, the size of each type of unmanned aerial vehicle to be loaded into the containers, and the size of the unit repair materials to be loaded into the containers.

[0030] The remaining loadable volume calculation module is configured to calculate a total loadable volume of the containers according to the number of containers to be configured and the size of the containers to be configured, and calculate a remaining loadable volume of the containers according to the communication-type unmanned aerial vehicles to be loaded into each container, the size of the communication-type unmanned aerial vehicles, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume.

[0031] The maximum number calculation module is configured to calculate a first maximum number of unit repair materials that can be loaded into the containers according to the size of the unit repair materials when the remaining loadable volume is used to load the unit repair materials, calculate a second maximum number of line-patrolling unmanned aerial vehicles that can be loaded into the containers according to the size of the line-patrolling unmanned aerial vehicles when the remaining loadable volume is used to load the line-patrolling unmanned aerial vehicles, and calculate a third maximum number of transport unmanned aerial vehicles that can be loaded into the containers according to the size of the transport unmanned aerial vehicles when the remaining loadable volume is used to load the transport unmanned aerial vehicles.

[0032] The load configuration model construction module is configured to construct a load configuration model according to the first maximum number, the second maximum number, the third maximum number, and corresponding weight coefficients.

[0033] The model solving module is configured to solve the load configuration model under the constraint of the remaining loadable volume, and calculate a first target number of unit repair materials that can be loaded into the containers, a second target number of line-patrolling unmanned aerial vehicles that can be loaded into the containers, and a third target number of transport unmanned aerial vehicles that can be loaded into the containers when a target value corresponding to the load configuration model is maximum.

[0034] The container loading module is configured to load the remaining loadable volume of the containers according to the first target number, the second target number, and the third target number.

[0035] Further, the container loading device for power facility post-disaster relief also includes a deployment position calculation module.

[0036] The deployment position calculation module is configured to acquire performance parameters of each type of unmanned aerial vehicle to be loaded into the container, positions of target sites, positions of distribution network power transmission lines, and positions of main network power transmission lines, wherein the target sites include disaster-stricken sites and non-disaster-stricken high-voltage equipment tower bases; a rough deployment position of the container to be configured is generated according to the performance parameters of each type of unmanned aerial vehicle to be loaded into the container and the positions of the target sites, in a case that a transport unmanned aerial vehicle flies out in a full load state and returns to a nest in an empty load state, and a farthest distance that can be reached is used as a basis; and a final deployment position of the container to be configured is calculated and generated according to the rough deployment position, the positions of the distribution network power transmission lines, the positions of the main network power transmission lines, and the positions of the target sites.

[0037] On the basis of the above-mentioned method embodiment, the present application correspondingly provides an electronic device embodiment.

[0038] An embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor can implement the container loading method for power facility post-disaster facing in any of the above-mentioned method embodiments when executing the computer program.

[0039] On the basis of the above-mentioned method embodiment, the present application correspondingly provides a storage medium embodiment.

[0040] An embodiment of the present application provides a storage medium, and the storage medium has a computer program stored thereon, and the computer program can implement the container loading method for power facility post-disaster facing in any of the above-mentioned method embodiments when executed by a processor.

[0041] Compared with the prior art, the present application has the following beneficial effects:

[0042] Embodiments of the present application provide a container loading method, device, electronic device, and storage medium. The method calculates the remaining loadable volume of the container according to the number of containers, the size of the container, and the number of repair materials that meet the basic needs of the disaster area and the number of unmanned aerial vehicles that each container must load. The maximum number of each of three cases, i.e., the remaining loadable volume is used only for loading unit repair materials, the remaining loadable volume is used only for loading line patrol unmanned aerial vehicles, and the remaining loadable volume is used only for loading transport unmanned aerial vehicles, is calculated according to the remaining loadable volume of the container. A loading configuration model is constructed according to the maximum number of each and a weight coefficient calculated by an analytic hierarchy process, so that the loading configuration model is solved to generate the loading number of unit repair materials, line patrol unmanned aerial vehicles, and transport unmanned aerial vehicles. The loading number solved by the model is used to load the remaining loadable volume of the container.

[0043] The application calculates the weight of each of the unit repair materials, the line patrol unmanned aerial vehicle and the transportation unmanned aerial vehicle by the analytic hierarchy process, solves the model according to the weight, effectively balances the quantity of the repair materials and the unmanned aerial vehicle, thereby ensuring that a reasonable quantity of the repair materials and the unmanned aerial vehicle are put into the limited container space, and thereby solving the problem that the repair demand of the disaster area cannot be met due to the unreasonable loading plan of the container. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 is a flowchart of a container loading method for a power facility disaster according to an embodiment of the application.

[0045] Figure 2 is a flowchart of a container loading method for a power facility disaster according to another embodiment of the application.

[0046] Figure 3 is a structural diagram of a container loading device for a power facility disaster according to an embodiment of the application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the application.

[0048] For the convenience of technical problem research, the technical scenarios of the application are assumed as follows.

[0049] Ignoring the influence of environment and weather: when making plans, we assume that the environment and weather have no influence on the flight and observation of the unmanned aerial vehicle. This is because our plan is designed for most cases, and extreme weather conditions are relatively rare.

[0050] Stockpile of repair materials: the disaster area has the ability to store additional repair materials within a day to meet the power recovery needs of the next few days. This means that in addition to the materials needed for the current emergency repair, the disaster area can also stockpile more materials for future use.

[0051] Special role of communication unmanned aerial vehicle: the communication unmanned aerial vehicle plays an important role in the system, which is responsible for providing communication support for other unmanned aerial vehicles and the control center. Therefore, we need to equip at least one communication unmanned aerial vehicle in each container to ensure smooth communication.

[0052] For example, if the container has a capacity of 1000 kg, we can allocate 800 kg of repair materials, 100 kg of line patrol unmanned aerial vehicles and 100 kg of transportation unmanned aerial vehicles. Figure 1As shown, an embodiment of the present application provides a container loading method for power facility post-disaster, which comprises at least the following steps:

[0053] In step S1, the number of containers to be configured, the size of the containers to be configured, the size of each type of unmanned aerial vehicle to be loaded into the containers, and the size of the unit repair materials to be loaded into the containers are obtained.

[0054] It should be noted that one unit of unit repair materials means the amount of materials that can meet one day of repair work. The types of unmanned aerial vehicles include transport unmanned aerial vehicles, line patrol unmanned aerial vehicles, and communication unmanned aerial vehicles, and each container needs to load one communication unmanned aerial vehicle and at least a preset number of unit repair materials.

[0055] In step S2, the total loadable volume of the containers is calculated according to the number of containers to be configured and the size of the containers to be configured; and the remaining loadable volume of the containers is calculated according to the communication unmanned aerial vehicle to be loaded into each container, the size of the communication unmanned aerial vehicle, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume.

[0056] Specifically, the volume of a container to be configured is calculated according to the size of the container to be configured.

[0057] The product of the number of containers to be configured and the volume of the container to be configured is calculated to obtain the total loadable volume of the containers;

[0058] The volume required for loading the communication unmanned aerial vehicle is calculated according to the size of the communication unmanned aerial vehicle and the number of communication unmanned aerial vehicles to be loaded;

[0059] The volume required for loading the unit repair materials is calculated according to the size of the unit repair materials and the number of unit repair materials to be loaded;

[0060] The difference between the total loadable volume of the containers and the volume required for loading the communication unmanned aerial vehicle is calculated to obtain a first difference value;

[0061] The difference between the first difference value and the volume required for loading the unit repair materials is calculated to obtain the remaining loadable volume of the containers.

[0062] The at least preset number can be selected according to actual conditions, and the at least preset number of unit repair materials is set to 7 units of unit repair materials, and one unit of unit repair materials means the amount of materials that can meet one day of repair work.

[0063] Step S3, according to the size of the unit repair material, the first maximum number of the unit repair material that can be loaded is calculated when the remaining loadable volume is used for loading the unit repair material; according to the size of the line patrol unmanned aerial vehicle, the second maximum number of the line patrol unmanned aerial vehicle that can be loaded is calculated when the remaining loadable volume is used for loading the line patrol unmanned aerial vehicle; according to the size of the transport unmanned aerial vehicle, the third maximum number of the transport unmanned aerial vehicle that can be loaded is calculated when the remaining loadable volume is used for loading the transport unmanned aerial vehicle.

[0064] In actual operation, according to the size of the unit repair material, the volume of one unit of the unit repair material is calculated and generated;

[0065] The quotient of the remaining loadable volume and the volume of one unit of the unit repair material is calculated to obtain a first calculation result; the first calculation result is rounded down to obtain the first maximum number of the unit repair material that can be loaded;

[0066] According to the size of the line patrol unmanned aerial vehicle, the volume of one line patrol unmanned aerial vehicle is calculated and generated;

[0067] The quotient of the remaining loadable volume and the volume of one line patrol unmanned aerial vehicle is calculated to obtain a second calculation result; the second calculation result is rounded down to obtain the second maximum number of the line patrol unmanned aerial vehicle that can be loaded;

[0068] According to the size of the line patrol unmanned aerial vehicle, the volume of one line patrol unmanned aerial vehicle is calculated and generated;

[0069] The quotient of the remaining loadable volume and the volume of one line patrol unmanned aerial vehicle is calculated to obtain a second calculation result; the second calculation result is rounded down to obtain the second maximum number of the line patrol unmanned aerial vehicle that can be loaded;

[0070] Step S4, according to the first maximum number, the second maximum number, the third maximum number and the corresponding weight coefficient, a loading configuration model is constructed.

[0071] In a preferred embodiment, the loading configuration model is specifically:

[0072]

[0073] wherein, is a target value of the loading configuration model; is a weight coefficient of the first maximum number; is a weight coefficient of the second maximum number; is a weight coefficient of the third maximum number; is a target number of the unit repair material; is a target number of the line patrol unmanned aerial vehicle; is a target number of the transport unmanned aerial vehicle. A standardized model of unit repair materials; A standardized model of a line patrol unmanned aerial vehicle; A standardized model of a transport unmanned aerial vehicle;

[0074] The standardized model of unit repair materials , specifically:

[0075]

[0076] Among them, is the first maximum number.

[0077] The standardized model of a line patrol unmanned aerial vehicle , specifically:

[0078]

[0079] Among them, is the second maximum number.

[0080] The standardized model of a transport unmanned aerial vehicle , specifically:

[0081]

[0082] Among them, is the second maximum number.

[0083] The weight coefficient is calculated by the analytic hierarchy process; the analytic hierarchy process calculates the relative importance between two factors by constructing a judgment matrix and comparing unit repair materials, line patrol unmanned aerial vehicles and transport unmanned aerial vehicles; the weight of each factor is calculated according to the relative importance; and the weight of each factor is tested for consistency to ensure the rationality of the weight.

[0084] In a preferred embodiment, the judgment matrix can be represented as:

[0085]

[0086] According to the judgment matrix, the sum of each row is calculated as the sum corresponding to the factor represented by the row;

[0087] The sums corresponding to all the factors represented by the rows are added to obtain the sum of the judgment matrix;

[0088] According to the proportion of the sum corresponding to each factor represented by the row in the sum of the judgment matrix, the weight of each factor represented by the row is calculated.

[0089] Specifically, according to the above table, the weight of the transport unmanned aerial vehicle is 0.23; the weight of the unit repair material is 0.69; and the weight of the line patrol unmanned aerial vehicle is 0.08.

[0090] Step S5: under the constraint of the remaining loadable volume, the loading configuration model is solved to calculate the first target quantity of the unit repair material, the second target quantity of the line patrol unmanned aerial vehicle, and the third target quantity of the transport unmanned aerial vehicle that can be loaded when the target value corresponding to the loading configuration model is maximum.

[0091] In a preferred embodiment, the loading configuration model can be solved by a greedy algorithm.

[0092] The first target quantity, the second target quantity, and the third target quantity obtained by solving the model also need to be constrained by the remaining loadable volume to ensure that the target quantities obtained are feasible. Specifically, it includes:

[0093] The volume of a unit of unit repair material is multiplied by the first target quantity to obtain a first product result;

[0094] The volume of a line patrol unmanned aerial vehicle is multiplied by the second target quantity to obtain a second product result;

[0095] The volume of a transport unmanned aerial vehicle is multiplied by the third target quantity to obtain a third product result;

[0096] The sum of the first product result and the second product result is calculated to obtain a fourth calculation result;

[0097] The sum of the fourth calculation result and the third product result is calculated to obtain a fifth calculation result.

[0098] It is judged whether the fifth calculation result is less than the remaining loadable volume. If yes, the model solving result is valid; if not, the model solving result is invalid, and the loading configuration model is solved again.

[0099] Step S6: according to the first target quantity, the second target quantity, and the third target quantity, the remaining loadable volume of the container is loaded.

[0100] In a preferred embodiment, the loading of the remaining loadable volume of the container according to the first target quantity, the second target quantity, and the third target quantity includes:

[0101] According to the first target quantity, the second target quantity and the third target quantity, the unit repair materials, the line patrol type unmanned aerial vehicle and the transportation type unmanned aerial vehicle are sequentially loaded into the container, and after one container is filled, the next container is transferred, so as to ensure the effective utilization of each container.

[0102] In another preferred embodiment, the loading of the remaining loadable volume of the container according to the first target quantity, the second target quantity and the third target quantity comprises:

[0103] According to the first target quantity, the second target quantity and the third target quantity, the size of each type of unmanned aerial vehicle to be loaded and the size of the unit repair material to be loaded, a container packing layout plan is generated based on a container packing algorithm.

[0104] According to the container packing layout plan, the remaining loadable volume of the container is loaded.

[0105] It should be noted that the container packing algorithm can be a 3DBP algorithm. The 3DBP algorithm is developed by 3Dbinpacking company established in 2012, and aims to solve the three-dimensional packing problem. By using the available API supported by 3DBP, the best packing condition can be obtained. The main operation steps specifically include:

[0106] The size of the object to be loaded is input, and the 3DBP system will intelligently plan to minimize the number of containers used, and generate the specific placement position and orientation of each object. The algorithm for generating the specific placement position can use the best fit decreasing strategy or the first fit decreasing strategy.

[0107] The best fit decreasing strategy specifically includes: sorting the objects in descending order of volume or weight, and sequentially trying to place each object in the container with the largest remaining space. If the current container cannot accommodate the object, the next container is tried until a container that can accommodate the object is found or all containers are unable to accommodate.

[0108] The first fit decreasing strategy specifically includes: sorting the objects in descending order of volume or weight, and sequentially trying to place each object in the first container that can be loaded.

[0109] As shown in Figure 2 Another embodiment of the present application provides a tie line power distribution method. In addition to the steps S1-S6 of the above embodiment, the method further comprises the following steps before step S6:

[0110] Step S5.5, calculating the product of the first target quantity and the preset ratio to generate a first product result; taking the first product result as the updated first target quantity; calculating the product of the third target quantity and the preset ratio to generate a second product result; and taking the second product result as the updated third target quantity.

[0111] It should be noted that, when the number of transport unmanned aerial vehicles and the number of unit repair materials are planned for containerization, a preset ratio reduction strategy is adopted. This is because, in actual containerization, direct containerization according to the theoretical value calculated by the model often encounters the situation that the materials cannot be completely loaded due to insufficient volume estimation. In view of the volume of transport unmanned aerial vehicles and the volume of unit repair materials, in most cases, the volume is significantly larger than that of the line patrol unmanned aerial vehicle. Therefore, the volume of the two is moderately reduced for estimation, which is an effective method to prevent loading failure. The preset ratio can be flexibly adjusted, and here it is taken as 75%.

[0112] In actual operation, if it is found that there is still a significant remaining space in the container after the goods are containerized according to the preset ratio adjustment, strategic adjustment should be taken, that is, gradually increasing the preset ratio to ensure that the volume of the container is maximized to optimize the loading efficiency.

[0113] In a preferred embodiment, the deployment position of the container to be configured is determined by:

[0114] The performance parameters of each type of unmanned aerial vehicle to be containerized, the location of the target site, the location of the distribution network transmission line, and the location of the main network transmission line are obtained. The target site includes a disaster-stricken site and an undamaged high-voltage equipment tower base.

[0115] According to the performance parameters of each type of unmanned aerial vehicle to be containerized and the location of the target site, the farthest distance that can be reached by the transport unmanned aerial vehicle in the full load state and returned to the nest in the empty load state is taken as the basis to generate a rough deployment position of the container to be configured.

[0116] According to the location of the distribution network transmission line, the location of the main network transmission line, and the location of the target site, based on the rough deployment position, the final deployment position of the container to be configured is calculated and generated.

[0117] In a specific implementation, the rough deployment position of the container to be configured is generated according to the performance parameters of each type of unmanned aerial vehicle to be containerized and the location of the target site, taking the farthest distance that can be reached by the transport unmanned aerial vehicle in the full load state and returned to the nest in the empty load state as the basis, including:

[0118] According to the performance parameters of the transport unmanned aerial vehicle, a farthest distance from the nest is calculated, which is reached by the transport unmanned aerial vehicle in a process of flying out from the nest in a full load state, returning to the nest in an empty load state, flying out from the nest in a full load state in a direction, and successfully returning to the nest.

[0119] For each target site, a concentric circular region corresponding to each target site is generated with the target site as the center and the first limit distance as the radius.

[0120] An area overlapping between different concentric circular regions is taken as a rough deployment position of the container to be configured.

[0121] In an optional embodiment, the final deployment position of the container to be configured is calculated and generated based on the rough deployment position according to the positions of the distribution network power transmission line, the main network power transmission line and the target site, and includes:

[0122] A deployment model is constructed according to the positions of the distribution network power transmission line, the main network power transmission line and the target site and corresponding weight coefficients. The weight coefficients are calculated by an analytic hierarchy process.

[0123] In a preferred embodiment, the deployment model specifically includes:

[0124]

[0125] Wherein, is a target value of the deployment model; is a weight coefficient of the distribution network power transmission line; is a weight coefficient of the main network power transmission line; is a weight coefficient of the target site; is the position of the distribution network power transmission line; is the position of the main network power transmission line; is the position of the target site; is a distance between the target deployment position and the position of the distribution network power transmission line; is a distance between the target deployment position and the position of the main network power transmission line; is a distance between the target deployment position and the position of the target site.

[0126] The deployment model is solved to maximize the target value of the deployment model, and the final deployment position of the container to be configured is calculated and generated under the constraint of the rough deployment position.

[0127] On the basis of the above-mentioned method embodiment, the application correspondingly provides a device embodiment.

[0128] As Figure 3As shown, an embodiment of the present application provides a container loading device for power facility post-disaster, comprising: a data acquisition module 101, a remaining loadable volume calculation module 102, a maximum number calculation module 103, a loading configuration model construction module 104, a model solving module 105 and a container loading module 106;

[0129] The data acquisition module 101 is configured to acquire the number of containers to be configured, the size of the containers to be configured, the size of each type of unmanned aerial vehicle to be loaded into the containers, and the size of the unit repair materials to be loaded into the containers.

[0130] The remaining loadable volume calculation module 102 is configured to calculate the total loadable volume of the containers according to the number of containers to be configured and the size of the containers to be configured; and calculate the remaining loadable volume of each container according to the communication type unmanned aerial vehicle to be loaded into the container, the size of the communication type unmanned aerial vehicle, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume.

[0131] The maximum number calculation module 103 is configured to calculate a first maximum number of unit repair materials that can be loaded when the remaining loadable volume is used to load the unit repair materials according to the size of the unit repair materials; calculate a second maximum number of line patrol type unmanned aerial vehicles that can be loaded when the remaining loadable volume is used to load the line patrol type unmanned aerial vehicles according to the size of the line patrol type unmanned aerial vehicles; and calculate a third maximum number of transportation type unmanned aerial vehicles that can be loaded when the remaining loadable volume is used to load the transportation type unmanned aerial vehicles according to the size of the transportation type unmanned aerial vehicles.

[0132] The loading configuration model construction module 104 is configured to construct a loading configuration model according to the first maximum number, the second maximum number, the third maximum number, and corresponding weight coefficients.

[0133] The model solving module 105 is configured to solve the loading configuration model under the constraint of the remaining loadable volume, and calculate a first target number of unit repair materials that can be loaded, a second target number of line patrol type unmanned aerial vehicles that can be loaded, and a third target number of transportation type unmanned aerial vehicles that can be loaded when the target value of the loading configuration model is maximum.

[0134] The container loading module 106 is configured to load the remaining loadable volume of the containers according to the first target number, the second target number, and the third target number.

[0135] Specifically, the container loading module 106 comprises a packing layout plan generation unit 1061 and a packing loading unit 1062.

[0136] The packing layout plan generation unit 1061 is configured to generate a container packing layout plan based on a container packing algorithm according to the first target quantity, the second target quantity, the third target quantity, the size of each type of unmanned aerial vehicle to be packed, and the size of the unit repair material to be packed.

[0137] The packing loading unit 1062 is configured to load the remaining loadable volume of the container according to the container packing layout plan.

[0138] Another embodiment of the present application provides a container loading device for power facility post-disaster, in addition to the data acquisition module 101, the remaining loadable volume calculation module 102, the maximum quantity calculation module 103, the loading configuration model construction module 104, the model solving module 105 and the container loading module 106, further comprising a deployment position calculation module 107.

[0139] The deployment position calculation module 107 is configured to acquire the performance parameters of each type of unmanned aerial vehicle to be packed, the position of the target site, the position of the distribution network transmission line and the position of the main network transmission line; wherein the target site comprises a disaster-stricken site and a non-disaster-stricken high-voltage equipment tower base; according to the performance parameters of each type of unmanned aerial vehicle to be packed and the position of the target site, a rough deployment position of the container to be configured is generated according to the farthest distance that can be reached in the case that the transport unmanned aerial vehicle flies out in a full load state and returns to the nest in an empty load state; and the final deployment position of the container to be configured is calculated and generated based on the rough deployment position according to the position of the distribution network transmission line, the position of the main network transmission line and the position of the target site.

[0140] It should be noted that the above-described device embodiments correspond to the above-described embodiments of the present application, and can implement any of the above-described methods of the present application. In addition, the above-described device embodiments are only illustrative, wherein the modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the device embodiment provided by the present application, the connection relationship between the modules indicates that they have a communication connection therebetween, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0141] On the basis of the above-described method embodiments of the present application, an electronic device embodiment is correspondingly provided.

[0142] An embodiment of the present application provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, when the computer program is executed by the processor, a container loading method for a power facility disaster according to any one of the present application is implemented, or when the computer program is executed by the processor, the functions of each module in each device embodiment are implemented.

[0143] For example, the computer program can be divided into one or more modules, the one or more modules are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.

[0144] The terminal device can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing devices. The terminal device can include, but is not limited to, a processor and a memory.

[0145] The processor can be a central processing unit (CPU), and can also be 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. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and is connected with all parts of the terminal device through various interfaces and lines.

[0146] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the terminal device by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, etc.; and the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0147] On the basis of the above-mentioned method embodiment, the application provides a storage medium embodiment;

[0148] Another embodiment of the application provides a storage medium, which comprises a stored computer program, wherein when the computer program runs, the device where the storage medium is located performs the container loading method for power facility post-disaster facing of any of the above-mentioned embodiments of the application.

[0149] In the above-mentioned storage medium, the storage medium is a computer readable storage medium, the computer program comprises computer program code, and the computer program code can be in the form of source code, object code, an executable file, or some intermediate form, etc. The computer readable medium can include any entity or device, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. that can carry the computer program code. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in a jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include an electrical carrier signal and a telecommunication signal.

[0150] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Also, the specific features, structures, materials or characteristics described can be combined in any appropriate way in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0151] The above is the preferred embodiment of the present application, it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, can also make a number of improvements and refinements, these improvements and refinements are also considered to be within the scope of the present application.

Claims

1. A container loading method for power facility disaster, characterized by, The method comprises the following steps: acquiring the number of containers to be configured, the size of the containers to be configured, the size of each type of unmanned aerial vehicle to be loaded into the containers, and the size of the unit repair materials to be loaded into the containers; wherein the types of unmanned aerial vehicles include transport unmanned aerial vehicles, line-patrolling unmanned aerial vehicles, and communication unmanned aerial vehicles, and each container needs to load a communication unmanned aerial vehicle and at least a preset number of unit repair materials; calculating the total loadable volume of the containers according to the number of containers to be configured and the size of the containers to be configured; and calculating the remaining loadable volume of the containers according to the communication unmanned aerial vehicle to be loaded into each container, the size of the communication unmanned aerial vehicle, at least the preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume; calculating the first maximum number of unit repair materials that can be loaded according to the size of the unit repair materials when the remaining loadable volume is used for loading the unit repair materials; calculating the second maximum number of line-patrolling unmanned aerial vehicles that can be loaded according to the size of the line-patrolling unmanned aerial vehicles when the remaining loadable volume is used for loading the line-patrolling unmanned aerial vehicles; and calculating the third maximum number of transport unmanned aerial vehicles that can be loaded according to the size of the transport unmanned aerial vehicles when the remaining loadable volume is used for loading the transport unmanned aerial vehicles; constructing a loading configuration model according to the first maximum number, the second maximum number, the third maximum number, and corresponding weight coefficients; wherein the weight coefficients are calculated by an analytic hierarchy process; solving the loading configuration model under the constraint of the remaining loadable volume to obtain the first target number of unit repair materials that can be loaded, the second target number of line-patrolling unmanned aerial vehicles that can be loaded, and the third target number of transport unmanned aerial vehicles that can be loaded when the target value of the loading configuration model is maximum; loading the remaining loadable volume of the containers according to the first target number, the second target number, and the third target number; wherein the loading configuration model is specifically: wherein, is a target value for a loading configuration model; is a first maximum number of weight coefficients; is a second maximum number of weight coefficients; is a third maximum number of weight coefficients; is a target number of unit repair materials; is a target number of line-patrolling drones; is a target number of transport drones; is a standardization model for unit repair materials; is a standardization model for line-patrolling drones; is a standardization model for transport drones; Specifically, the standardized model of unit repair materials Specifically, the standardized model of unit repair materials wherein is a first maximum number; Standardized model of line patrol unmanned aerial vehicle , in particular: wherein is a second maximum number; Standardized model of transport drone In particular: wherein is a second maximum number.

2. The container loading method for power facility disaster, according to claim 1, wherein, the loading of the remaining loadable volume of the containers according to the first target number, the second target number, and the third target number comprises: generating a container packing layout plan based on a container packing algorithm according to the first target number, the second target number, the third target number, the size of each type of unmanned aerial vehicle to be loaded into the containers, and the size of the unit repair materials to be loaded into the containers; loading the remaining loadable volume of the containers according to the container packing layout plan.

3. The container loading method for power facility disaster, according to claim 1, wherein, The deployment position of the container to be configured is determined in the following manner: acquiring the performance parameters of each type of unmanned aerial vehicle to be loaded, the positions of target sites, the positions of distribution network transmission lines, and the positions of main network transmission lines; wherein the target sites include disaster-stricken sites and non-disaster-stricken high-voltage equipment tower bases; generating a rough deployment position of the container to be configured according to the performance parameters of each type of unmanned aerial vehicle to be loaded and the positions of target sites, with the farthest distance that a transport unmanned aerial vehicle can reach under the condition that the transport unmanned aerial vehicle flies out in a full load state and returns to a nest in an empty load state as the basis. According to the location of the distribution network transmission line, the location of the main network transmission line and the location of the target site, a final deployment location of the container to be configured is calculated based on the rough deployment location.

4. The container loading method for power facility disaster, according to claim 3, wherein, The rough deployment location of the container to be configured is generated according to the performance parameters of each type of unmanned aerial vehicle to be packed and the location of the target site, and the furthest distance that can be reached by the transport unmanned aerial vehicle flying out in a full load state and returning to the nest in an empty load state. According to the performance parameters of the transport unmanned aerial vehicle, the furthest distance from the nest that the transport unmanned aerial vehicle can reach in the process of flying out in a full load state and returning to the nest in an empty load state along one direction and successfully returning to the nest is calculated. For each target site, a concentric circular region corresponding to each target site is generated with the target site as the center and the first limit distance as the radius. The overlapping region between different concentric circular regions is taken as the rough deployment location of the container to be configured.

5. The container loading method for power facility disaster, according to claim 1, wherein, Before the remaining loadable volume of the container is loaded according to the first target quantity, the second target quantity, the third target quantity, the size of each type of unmanned aerial vehicle to be packed and the size of the unit repair material to be packed, it further includes: A first product result is generated by calculating the product of the first target quantity and a preset proportion; and the first product result is taken as the updated first target quantity. A second product result is generated by calculating the product of the third target quantity and a preset proportion; and the second product result is taken as the updated third target quantity.

6. A container loading device for power utility disaster, characterized by, It includes: A data acquisition module, a remaining loadable volume calculation module, a maximum quantity calculation module, a loading configuration model construction module, a model solving module and a container loading module. The data acquisition module is used to acquire the number of containers to be configured, the size of the containers to be configured, the size of each type of unmanned aerial vehicle to be packed and the size of the unit repair material to be packed. The remaining loadable volume calculation module is used to calculate the total loadable volume of the container according to the number of containers to be configured and the size of the containers to be configured; and the remaining loadable volume of the container is calculated according to the communication unmanned aerial vehicle to be loaded by each container, the size of the communication unmanned aerial vehicle, at least a preset number of unit repair materials, the size of the unit repair material and the total loadable volume. The maximum quantity calculation module is used to calculate the first maximum number of unit repair materials that can be loaded when the remaining loadable volume is used to load unit repair materials according to the size of the unit repair material; to calculate the second maximum number of line patrol unmanned aerial vehicles that can be loaded when the remaining loadable volume is used to load line patrol unmanned aerial vehicles according to the size of the line patrol unmanned aerial vehicle; and to calculate the third maximum number of transport unmanned aerial vehicles that can be loaded when the remaining loadable volume is used to load transport unmanned aerial vehicles according to the size of the transport unmanned aerial vehicle. The loading configuration model construction module is used to construct a loading configuration model according to the first maximum number, the second maximum number, the third maximum number and the corresponding weight coefficient. The model solving module is configured to solve the loading configuration model under the constraint of the remaining loadable volume, and calculate a first target quantity of the unit repair materials that can be loaded, a second target quantity of the line-patrolling unmanned aerial vehicles that can be loaded, and a third target quantity of the transport unmanned aerial vehicles that can be loaded when a target value of the loading configuration model is maximum. The container loading module is configured to load the remaining loadable volume of the container according to the first target quantity, the second target quantity, and the third target quantity. The loading configuration model is specifically: wherein, is a target value for a loading configuration model; is a first maximum number of weight coefficients; is a second maximum number of weight coefficients; is a third maximum number of weight coefficients; is a target number of unit repair materials; is a target number of line-patrolling UAVs; is a target number of transport UAVs; is a standardization model for unit repair materials; is a standardization model for line-patrolling UAVs; is a standardization model for transport UAVs; In particular, the standardized model of unit repair materials , in particular: wherein is a first maximum number; Standardized model of line patrol unmanned aerial vehicle , in particular: wherein is a second maximum number; Standardized model of transport drone , in particular: wherein is a second maximum number.

7. The container loading device for power utility disaster as claimed in claim 6, wherein Further comprising: A deployment position calculation module; The deployment position calculation module is configured to obtain performance parameters of each type of unmanned aerial vehicle to be packed, positions of target sites, positions of distribution network transmission lines, and positions of main network transmission lines; the target sites include disaster-stricken sites and non-disaster-stricken high-voltage equipment towers; a rough deployment position of a container to be configured is generated according to the performance parameters of each type of unmanned aerial vehicle to be packed and the positions of target sites, and the farthest distance that can be reached by a transport unmanned aerial vehicle in a full-load state flying out and returning to a nest in an empty-load state; and a final deployment position of the container to be configured is calculated and generated based on the rough deployment position according to the positions of distribution network transmission lines, the positions of main network transmission lines, and the positions of target sites.

8. The container loading device for power utility disaster as claimed in claim 6, wherein, The container loading module includes a packing layout plan generation unit and a packing loading unit. The packing layout plan generation unit is configured to generate a container packing layout plan based on a packing algorithm according to the first target quantity, the second target quantity, and the third target quantity, sizes of each type of unmanned aerial vehicle to be packed, and a size of unit repair materials to be packed. The packing loading unit is configured to load the remaining loadable volume of the container according to the container packing layout plan.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: The processor executes the computer program to implement the container loading method for a power facility post-disaster situation according to any one of claims 1 to 5.

10. A storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to implement the container loading method for a power facility post-disaster situation according to any one of claims 1 to 5.

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