Container loading method and device for electric power facility after disaster, electronic equipment and storage medium

Abstract

The invention discloses an electric power facility post-disaster container loading method and device, electronic equipment and a storage medium. The method comprises the steps that the number and size of containers, the size of each type of unmanned aerial vehicles and the size of unit first-aid repair materials are obtained; calculating the remaining loadable volume of the container according to the number and size of the container, the size of each type of unmanned aerial vehicle and the size of the unit emergency repair material; according to the remaining loadable volume, the maximum number of the line patrol type unmanned aerial vehicles and the maximum number of the transportation type unmanned aerial vehicles which are all used for loading unit first-aid repair materials in the remaining loadable volume are calculated; constructing a loading configuration model according to the corresponding maximum number and the corresponding weight coefficient; solving the loading configuration model to obtain target numbers corresponding to unit first-aid repair materials, patrol type unmanned aerial vehicles and transportation type unmanned aerial vehicles; according to the target number, loading the remaining loadable volume; by implementing the method, the problem that the emergency repair requirement of a disaster area cannot be met due to an unreasonable loading plan can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics and transportation management, and in particular to a container loading method, device, electronic equipment and storage medium for post-disaster power facility operations. Background Art

[0002] Drones have shown great potential in transporting emergency supplies to power facilities, especially in complex terrain and adverse weather conditions. Traditional ground transportation is often hindered by road damage, traffic paralysis, or the inability of large transport vehicles to enter the disaster area. Drones, with their strong mobility and ability to quickly adapt to various environments, can effectively transport emergency supplies to disaster areas.

[0003] A successful drone cargo transport not only depends on the performance of the aircraft, but also requires a reasonable transportation plan, which includes comprehensive consideration of transportation route planning, container loading plan, and drone launch and recovery locations to ensure rapid response and meet rescue needs in an emergency.

[0004] In actual scenarios, it is necessary to load drones and emergency repair materials in containers. If the emergency repair materials are loaded too much and the drone is loaded too little, the drone's transportation efficiency will be low, and various materials cannot be transported to the corresponding emergency repair area within the specified time. If the emergency repair materials are loaded too little and the drone is loaded too much, it will lead to insufficient emergency repair materials and cannot meet the material needs of the emergency repair area. Therefore, how to effectively balance the number of emergency repair materials and drones is an urgent problem that needs to be solved. Summary of the invention

[0005] The embodiments of the present invention provide a container loading method, device, electronic device and storage medium for power facilities after disasters. By implementing the present invention, it is possible to load a suitable amount of emergency repair materials and a number of drones in a limited container volume, and to transport emergency repair materials to the affected power facility area through drones after power facilities are damaged, so that emergency repair personnel can obtain emergency repair materials as soon as possible to repair power facilities, thereby ensuring that they can respond quickly and meet rescue needs in emergency situations.

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

[0007] Obtain the number of containers to be configured, the size of the containers to be configured, the size of each type of drone to be loaded, and the size of the unit repair materials to be loaded. Among them, the types of drones include transport drones, patrol drones, and communication drones, and each container must be loaded with a communication drone and at least a preset number of unit repair 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 drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume.

[0009] According to the size of unit repair materials, the first maximum quantity of unit repair materials that can be loaded is calculated when the remaining loadable volume is all used to load unit repair materials; according to the size of patrol drones, the second maximum quantity of patrol drones that can be loaded is calculated when the remaining loadable volume is all used for patrol drones. According to the size of transport drones, the third maximum quantity of transport drones that can be loaded is calculated when the remaining loadable volume is all used for transport drones.

[0010] A loading configuration model is constructed 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 using a hierarchy analysis method.

[0011] Under the constraint of the remaining loadable volume, the loading configuration model is solved to calculate the first target number of unit repair materials that can be loaded, the second target number of line patrol type UAVs that can be loaded, and the third target number of transport type UAVs that can be loaded when the target value corresponding to the loading configuration model is maximum.

[0012] The remaining loadable volume of the container is loaded according to the first target quantity, the second target quantity and the third target quantity.

[0013] Furthermore, loading the remaining loadable volume of the container according to the first target quantity, the second target quantity, and the third target quantity includes:

[0014] A container packing layout plan is generated based on a packing algorithm according to the first target quantity, the second target quantity, and the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed.

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

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

[0017] The performance parameters of each type of drone to be packed, the location of the target location, the location of the distribution network transmission line and the location of the main network transmission line are obtained; wherein the target location includes: the disaster-stricken location and the undamaged high-voltage equipment tower base.

[0018] According to the performance parameters of the various types of drones to be loaded and the location of the target location, the rough deployment location of the container to be configured is generated based on the maximum distance that a transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty 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 location, based on the rough deployment location, the final deployment location of the container to be deployed is calculated and generated.

[0020] Furthermore, according to the performance parameters of the various types of drones to be loaded and the location of the target location, the rough deployment location of the container to be configured is generated based on the maximum distance that the transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state, including:

[0021] According to the performance parameters of the transport UAV, the maximum distance from the nest that the transport UAV can reach in the process of flying out from the nest with full charge in one direction and successfully returning to the nest is calculated, when the transport UAV flies out with full load and returns to the nest with no load.

[0022] For each target location, a concentric circle area corresponding to each target location is generated with the target location as the center and the first limit distance as the radius.

[0023] The overlapping areas between the different concentric circle areas are used as the rough deployment positions of the containers to be deployed.

[0024] Furthermore, before loading the remaining loadable volume of the container according to the first target quantity, the second target quantity, the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed, the method further includes:

[0025] The product of the first target quantity and the preset ratio is calculated to generate a first product result; and the first product result is used as the updated first target quantity.

[0026] The product of the third target quantity and the preset ratio is calculated to generate a second product result; and the second product result is used as the updated third target quantity.

[0027] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0028] An embodiment of the present invention provides a container loading device for power facilities after a disaster, including: 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 used to obtain the number of containers to be configured, the size of the containers to be configured, the size of each type of drone to be packed, and the size of the unit repair materials to be packed.

[0030] 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 calculate the remaining loadable volume of the container according to the communication drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials and the total loadable volume.

[0031] The maximum quantity calculation module is used to calculate, according to the size of the unit emergency repair materials, a first maximum quantity of unit emergency repair materials that can be loaded when the remaining loadable volume is all used to load the unit emergency repair materials; to calculate, according to the size of the line-patrol type UAV, a second maximum quantity of line-patrol type UAVs that can be loaded when the remaining loadable volume is all used for the line-patrol type UAVs; and to calculate, according to the size of the transport type UAV, a third maximum quantity of transport type UAVs that can be loaded when the remaining loadable volume is all used for the transport type UAVs.

[0032] 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 coefficients.

[0033] The model solving module is used to solve the loading configuration model under the constraint of the remaining loading volume, and calculate the first target number of unit repair materials that can be loaded, the second target number of line patrol type drones that can be loaded, and the third target number of transport type drones that can be loaded when the target value corresponding to the loading configuration model is maximum.

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

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

[0036] The deployment position calculation module is used to obtain the performance parameters of each type of drone to be packed, the location of the target location, the location of the distribution network transmission line and the location of the main network transmission line. The target location includes: the disaster site and the high-voltage equipment tower base that is not affected by the disaster; based on the performance parameters of each type of drone to be packed and the location of the target location, the rough deployment position of the container to be configured is generated based on the maximum distance that the transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state; based on the location of the distribution network transmission line, the location of the main network transmission line and the location of the target location, the final deployment position of the container to be configured is calculated and generated based on the rough deployment position.

[0037] Based on the above method embodiment, the present invention provides a corresponding electronic device embodiment.

[0038] An embodiment of the present invention 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 container loading method for post-disaster power facility operations described in any one of the above method embodiments can be implemented.

[0039] Based on the above method item embodiments, the present invention provides a corresponding storage medium item embodiment.

[0040] An embodiment of the present invention provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the container loading method for power facility post-disaster as described in any one of the above method embodiments can be implemented.

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

[0042] The embodiment of the present invention provides a method, device, electronic device and storage medium for loading a container. The method calculates the remaining loadable volume of the container according to the number of containers, the size of the containers and the number of emergency repair materials and drones that must be loaded in each container to meet the basic needs of the disaster area; according to the remaining loadable volume of the container, respectively calculate the maximum number of the remaining loadable volume for loading only unit emergency repair materials, the remaining loadable volume for loading only patrol type drones and the remaining loadable volume for loading only transport type drones; according to the respective maximum numbers and the weight coefficients calculated by the hierarchical analysis method, construct a loading configuration model so that the loading configuration model is solved to generate the loading quantity of each of the three types of unit emergency repair materials, patrol type drones and transport type drones. The remaining loadable volume of the container is loaded according to the loading quantity solved by the model.

[0043] The present invention calculates and generates the weights of unit emergency repair materials, patrol-type UAVs and transport-type UAVs through the hierarchical analysis method, solves the model according to the weights, and effectively weighs the number of emergency repair materials and UAVs, thereby ensuring that a reasonable number of emergency repair materials and UAVs can be stuffed into a limited container space, thereby solving the problem of being unable to meet the emergency repair needs of the disaster area due to an unreasonable container loading plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention is a flowchart of a container loading method for power facility post-disaster situations provided by an embodiment of the present invention.

[0045] Figure 2 It is a flowchart of a container loading method for power facility post-disaster provided by another embodiment of the present invention.

[0046] Figure 3 The present invention is a schematic structural diagram of a container loading device for power facility post-disaster use provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] In order to facilitate the study of technical issues, the following assumptions are made for the technical scenario of the present invention:

[0049] Ignore the impact of environment and weather: When making plans, we assume that the environment and weather have no impact on the flight and observation of the drone. This is because our plans are designed for most situations, and extreme weather conditions are rare.

[0050] Reserves of emergency repair materials: The affected areas have the ability to store additional emergency repair materials within a day to meet the power restoration needs in the next few days. This means that in addition to the materials needed to meet the current emergency repair needs, the affected areas can also reserve more materials for emergency use.

[0051] The special role of communication drones: Communication drones play an important role in the system. They are responsible for providing communication support for other drones and the control center. Therefore, we need to equip each container with at least one communication drone to ensure smooth communication.

[0052] like Figure 1As shown, an embodiment of the present invention provides a container loading method for power facilities after a disaster, which at least includes the following steps:

[0053] Step S1, obtaining the number of containers to be configured, the size of the containers to be configured, the size of each type of drone to be packed, and the size of the unit repair materials to be packed.

[0054] It should be noted here that the unit repair materials of a unit refer to the amount of materials that can meet the repair work of one day. The types of drones include transport drones, patrol drones and communication drones, and each container must be loaded with a communication drone and at least a preset number of unit repair materials.

[0055] Step S2, calculating 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; calculating the remaining loadable volume of the container according to the communication drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials and the total loadable volume.

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

[0057] Calculate the product of the number of containers to be configured and the volume of the containers to be configured to obtain the total loadable volume of the containers;

[0058] According to the size of the communication type UAV and the number of communication type UAVs to be loaded, the volume required for loading the communication type UAVs is calculated;

[0059] According to the size of the unit repair materials and the quantity of the unit repair materials to be loaded, the volume required for loading the unit repair materials is calculated;

[0060] Calculate the difference between the total volume that can be loaded in the container and the volume required to load the communication type UAV to obtain a first difference value;

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

[0062] Among them, the at least preset quantity can be selected according to actual conditions. Here, the at least preset quantity of unit emergency repair materials is set to 7 units of unit emergency repair materials. One unit of unit emergency repair materials represents the quantity of materials that can meet one day's emergency repair work.

[0063] Step S3, according to the size of the unit emergency repair materials, calculate the first maximum number of unit emergency repair materials that can be loaded when the remaining loadable volume is all used to load the unit emergency repair materials; according to the size of the patrol type UAV, calculate the second maximum number of patrol type UAVs that can be loaded when the remaining loadable volume is all used for the patrol type UAV; according to the size of the transport type UAV, calculate the third maximum number of transport type UAVs that can be loaded when the remaining loadable volume is all used for the transport type UAV.

[0064] In actual operation, the volume of a unit of emergency repair materials is calculated based on the size of the unit emergency repair materials;

[0065] Calculate the quotient of the remaining loadable volume and the volume of one unit of emergency repair materials to obtain a first calculation result; round down the first calculation result to obtain a first maximum quantity of the unit emergency repair materials that can be loaded;

[0066] According to the size of the line patrol type UAV, calculate and generate the volume of a line patrol type UAV;

[0067] Calculate the quotient of the remaining loadable volume and the volume of one line patrol type UAV to obtain a second calculation result; round down the second calculation result to obtain a second maximum number of line patrol type UAVs that can be loaded;

[0068] According to the size of the line patrol type UAV, calculate and generate the volume of a line patrol type UAV;

[0069] Calculate the quotient of the remaining loadable volume and the volume of one transport-type drone to obtain a third calculation result; round down the third calculation result to obtain a third maximum number of transport-type drones that can be loaded;

[0070] Step S4: construct a loading configuration model according to the first maximum number, the second maximum number, the third maximum number and corresponding weight coefficients.

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

[0072] CE=ω1·f(n1)=ω2·g(n2)+ω3·h(n3)

[0073] Among them, CE is the target value of the loading configuration model; ω1 is the weight coefficient of the first maximum number; ω2 is the weight coefficient of the second maximum number; ω3 is the weight coefficient of the third maximum number; n1 is the target number of unit repair materials; n2 is the target number of patrol-type drones; n3 is the target number of transport-type drones. f(n1) is the standardized model of unit repair materials; g(n2) is the standardized model of patrol-type drones; h(n3) is the standardized model of transport-type drones;

[0074] Specifically, the standardized model f(n1) of unit emergency repair materials is as follows:

[0075]

[0076] in, is the first maximum number.

[0077] The standardized model g(n2) of the patrol-type UAV is as follows:

[0078]

[0079] in, is the second largest number.

[0080] The standardized model h(n3) of transport drones is as follows:

[0081]

[0082] in, is the second largest number.

[0083] Among them, the weight coefficient is calculated by the hierarchical analysis method; the hierarchical analysis method constructs a judgment matrix, compares the unit repair materials, patrol drones and transport drones in pairs, and calculates the relative importance of the two factors; calculates the weight of each factor according to the relative importance; and performs a consistency check on the weight of each factor to ensure the rationality of the weight.

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

[0085] factor Transport UAV Unit repair supplies Line patrol drone Transport UAV 1 0.25 3 Unit repair supplies 4 1 8 Line patrol drone 0.33 0.13 1

[0086] According to the judgment matrix, calculate the sum of each row as the sum corresponding to the representative factor of the row;

[0087] Add the sums corresponding to all the row-representing factors to get the sum of the judgment matrix;

[0088] The weight of each row of representative factors is calculated based on the ratio of the sum corresponding to each row of representative factors to the sum of the judgment matrix.

[0089] Specifically, according to the above table, it can be calculated that the weight of the transport drone is 0.23; the weight of the unit repair materials is 0.69; and the weight of the patrol drone 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 number of unit repair materials that can be loaded, the second target number of line patrol type drones that can be loaded, and the third target number of transport type drones 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 may be solved by a greedy algorithm.

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

[0093] Calculate the product of the volume of a unit of emergency repair materials and the first target quantity to obtain a first product result;

[0094] Calculate the product of the volume of a patrol-type UAV and the number of second targets to obtain a second product result;

[0095] Calculate the product of the volume of a transport drone and the third target quantity to obtain a third product result;

[0096] Calculate the sum of the first product result and the second product result 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] Determine whether the fifth calculation result is less than the remaining loadable volume. If so, the solution of this model is valid; if not, the solution of this model is invalid, and the loading configuration model is solved again.

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

[0100] In a preferred embodiment, loading 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 order of the unit's emergency repair materials, line patrol drones and transport drones, these items are loaded into containers in sequence according to the first target quantity, the second target quantity and the third target quantity. When one container is full, it will be transferred to the next container to ensure the effective use of each container.

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

[0103] Generate a container packing layout plan based on a packing algorithm according to the first target quantity, the second target quantity, the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed;

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

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

[0106] Input the size of the object to be loaded, and the 3DBP system will perform intelligent planning with the goal of minimizing the number of containers used, generating the specific placement location and orientation of each item. The algorithm for generating the specific placement location can use the best fit decreasing strategy or the first fit decreasing strategy.

[0107] The best adaptation decreasing strategy specifically includes: sorting the items in descending order according to their volume or weight, and trying to put each item into the container with the largest remaining space. If the current container cannot accommodate the item, try the next container until a container that can accommodate the item is found or all containers cannot accommodate the item.

[0108] The first adaptation decreasing strategy specifically includes: sorting the items in descending order according to their volume or weight, and trying to put each item into the first container that can be loaded.

[0109] like Figure 2 As shown, another embodiment of the present invention provides a tie line power distribution method, which, in addition to steps S1-S6 of the above embodiment, also includes the following steps before step S6:

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

[0111] It should be noted here that when planning the packing of the number of transport drones and the number of repair materials per unit, we adopted a reduction strategy based on a preset ratio. This is because in the actual packing process, if the theoretical value calculated by the model is directly used for packing, it is often encountered that the materials cannot be fully loaded due to insufficient volume estimation. Given that the volume of transport drones and the volume of repair materials per unit are significantly larger than that of patrol drones in most cases, it is an effective way to prevent loading failures to moderately reduce the volume of the two. The preset ratio can be flexibly adjusted, and 75% is taken here.

[0112] In actual operation, if we find that there is still significant remaining space in the container after the items are packed according to the preset ratio, we should make strategic adjustments, that is, gradually increase the preset ratio to ensure that the volume of the container is maximized, thereby optimizing loading efficiency.

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

[0114] Obtaining the performance parameters of each type of drone to be packed, the location of the target location, the location of the distribution network transmission line, and the location of the main network transmission line; wherein the target location includes: the disaster-stricken location and the undamaged high-voltage equipment tower base;

[0115] According to the performance parameters of the various types of drones to be loaded and the location of the target location, a rough deployment location of the container to be configured is generated based on the maximum distance that a transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state;

[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 location, based on the rough deployment location, the final deployment location of the container to be deployed is calculated and generated.

[0117] In a specific implementation, the rough deployment position of the container to be configured is generated based on the performance parameters of each type of drone to be loaded and the location of the target location, and based on the maximum distance that the transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state, including:

[0118] According to the performance parameters of the transport UAV, calculate the maximum distance from the nest that the transport UAV can reach when it flies out with full load and returns to the nest without load, in the process of flying out with full power in one direction and successfully returning to the nest;

[0119] For each target location, a concentric circle area corresponding to each target location is generated with the target location as the center and the first limit distance as the radius;

[0120] The overlapping areas between the different concentric circle areas are used as the rough deployment positions of the containers to be deployed.

[0121] In an optional embodiment, the calculating and generating the final deployment position of the container to be configured 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 location includes:

[0122] A deployment model is constructed according to the location of the distribution network transmission line, the location of the main network transmission line, the location of the target location and the corresponding weight coefficients, wherein the weight coefficients are calculated by the hierarchical analysis method.

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

[0124] F=ω4·d(x)+ω5·d(y)+ω6·d(z)

[0125] Among them, F is the target value of the deployment model; ω4 is the weight coefficient of the distribution network transmission line; ω5 is the weight coefficient of the main network transmission line; ω6 is the weight coefficient of the target location; x is the location of the distribution network transmission line; y is the location of the main network transmission line; z is the location of the target location; d(x) is the distance between the target deployment location and the location of the distribution network transmission line; d(y) is the distance between the target deployment location and the location of the main network transmission line; d(z) is the distance between the target deployment location and the location of the target location.

[0126] The deployment model is solved for the purpose of maximizing 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] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0128] like Figure 3 As shown, an embodiment of the present invention provides a container loading device for power facilities after a disaster, including: a data acquisition module 101, a remaining loadable volume calculation module 102, a maximum quantity 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 used to acquire the number of containers to be configured, the size of the containers to be configured, the size of each type of drone to be packed, and the size of the unit repair materials to be packed;

[0130] The remaining loadable volume calculation module 102 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 calculate the remaining loadable volume of the container according to the communication drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume;

[0131] The maximum quantity calculation module 103 is used to calculate, according to the size of the unit repair materials, a first maximum quantity of the unit repair materials that can be loaded when the remaining loadable volume is all used to load the unit repair materials; according to the size of the line patrol type drone, calculate the second maximum quantity of the line patrol type drone that can be loaded when the remaining loadable volume is all used for the line patrol type drone; according to the size of the transport type drone, calculate the third maximum quantity of the transport type drone that can be loaded when the remaining loadable volume is all used for the transport type drone;

[0132] The loading configuration model building module 104 is used to build a loading configuration model according to the first maximum number, the second maximum number, the third maximum number and the corresponding weight coefficients;

[0133] The model solving module 105 is used to solve the loading configuration model under the constraint of the remaining loading volume, and calculate the first target number of unit repair materials that can be loaded, the second target number of patrol-type UAVs that can be loaded, and the third target number of transport-type UAVs that can be loaded when the target value corresponding to the loading configuration model is the maximum;

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

[0135] Specifically, the container loading module 106 includes: a packaging layout plan generating unit 1061 and a packaging loading unit 1062;

[0136] The packing layout plan generating unit 1061 is used to generate a container packing layout plan based on a packing algorithm according to the first target quantity, the second target quantity, the third target quantity, the sizes of various types of drones to be packed, and the sizes of unit repair materials to be packed.

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

[0138] Another embodiment of the present invention provides a container loading device for post-disaster power facilities, which, in addition to the above-mentioned data acquisition module 101, remaining loadable volume calculation module 102, maximum quantity calculation module 103, loading configuration model construction module 104, model solving module 105 and container loading module 106, also includes: a deployment position calculation module 107.

[0139] The deployment position calculation module 107 is used to obtain the performance parameters of various types of drones to be packed, the location of the target location, the location of the distribution network transmission line and the location of the main network transmission line; wherein the target location includes: the disaster-stricken location and the undamaged high-voltage equipment tower base; based on the performance parameters of the various types of drones to be packed and the location of the target location, the rough deployment position of the container to be configured is generated based on the maximum distance that a transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state; according to the location of the distribution network transmission line, the location of the main network transmission line and the location of the target location, the final deployment position of the container to be configured is calculated and generated based on the rough deployment position.

[0140] It should be noted that the embodiments of the device described above correspond to the above embodiments of the present invention, and can implement any of the methods described above in the present invention. In addition, the embodiments of the above-mentioned device are merely schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0141] Based on the above method embodiment of the present invention, a corresponding electronic device embodiment is provided.

[0142] An embodiment of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the container loading method for post-disaster power facility disasters described in any one of the present invention is implemented, or, when the processor executes the computer program, the functions of the modules in the above-mentioned device embodiments are implemented.

[0143] Exemplarily, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the terminal device.

[0144] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0145] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0146] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device by running or executing the computer program and / or module stored in the memory, and calling the 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 for a function, etc.; 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 memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0147] Based on the above method embodiment, the present invention provides a storage medium embodiment;

[0148] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute any one of the above-mentioned container loading methods for power facility post-disaster of the present invention.

[0149] The storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0150] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0151] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A container loading method for power facilities after a disaster, characterized in that: include: Obtain the number of containers to be configured, the size of the containers to be configured, the size of each type of drone to be loaded, and the size of the unit repair materials to be loaded; the types of drones include transport drones, patrol drones, and communication drones, and each container needs to be loaded with a communication drone and at least a preset number of unit repair materials; 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 drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials and the total loadable volume; According to the size of the unit repair materials, the first maximum number of unit repair materials that can be loaded is calculated when the remaining loadable volume is all used to load the unit repair materials; according to the size of the patrol type drone, the second maximum number of patrol type drones that can be loaded is calculated when the remaining loadable volume is all used for patrol type drones; according to the size of the transport type drone, the third maximum number of transport type drones that can be loaded is calculated when the remaining loadable volume is all used for transport type drones; 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 using a hierarchy analysis method; Under the constraint of the remaining loadable volume, the loading configuration model is solved to calculate the first target quantity of unit repair materials that can be loaded, the second target quantity of patrol-type UAVs that can be loaded, and the third target quantity of transport-type UAVs that can be loaded when the target value corresponding to the loading configuration model is the maximum; The remaining loadable volume of the container is loaded according to the first target quantity, the second target quantity and the third target quantity.

2. The container loading method for power facilities after a disaster as claimed in claim 1, characterized in that: The step of loading the remaining loadable volume of the container according to the first target quantity, the second target quantity, and the third target quantity includes: Generate a container packing layout plan based on a packing algorithm according to the first target quantity, the second target quantity, the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed; The remaining loadable volume of the container is loaded according to the container packing layout plan.

3. The container loading method for power facilities after a disaster as claimed in claim 1, characterized in that: The deployment position of the container to be configured is determined by: Obtaining the performance parameters of each type of drone to be packed, the location of the target location, the location of the distribution network transmission line, and the location of the main network transmission line; wherein the target location includes: the disaster-stricken location and the undamaged high-voltage equipment tower base; According to the performance parameters of the various types of drones to be loaded and the location of the target location, a rough deployment location of the container to be configured is generated based on the maximum distance that the transport drone can reach when it flies out in a fully loaded state and returns to the nest in an empty state; According to the location of the distribution network transmission line, the location of the main network transmission line and the location of the target location, based on the rough deployment location, the final deployment location of the container to be deployed is calculated and generated.

4. The container loading method for power facilities after a disaster as claimed in claim 3, characterized in that: According to the performance parameters of the various types of drones to be loaded and the location of the target location, the rough deployment location of the container to be configured is generated based on the maximum distance that the transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state, including: According to the performance parameters of the transport UAV, calculate the maximum distance from the nest that the transport UAV can reach when it flies out with full load and returns to the nest without load, in the process of flying out with full power in one direction and successfully returning to the nest; For each target location, a concentric circle area corresponding to each target location is generated with the target location as the center and the first limit distance as the radius; The overlapping areas between the different concentric circle areas are used as the rough deployment positions of the containers to be deployed.

5. The container loading method for power facilities after a disaster as claimed in claim 1, characterized in that: Before loading the remaining loadable volume of the container according to the first target quantity, the second target quantity, the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed, the method further includes: Calculate the product of the first target quantity and the preset ratio to generate a first product result; use the first product result as the updated first target quantity; The product of the third target quantity and the preset ratio is calculated to generate a second product result; and the second product result is used as the updated third target quantity.

6. A container loading device for power facilities after a disaster, characterized in that: include: Data acquisition module, remaining loadable volume calculation module, maximum quantity calculation module, loading configuration model building module, model solving module and 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 drone to be packed, and the size of the unit repair materials 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 calculate the remaining loadable volume of the container according to the communication drones to be loaded in each container, the size of the communication drones, at least a preset number of unit repair materials, the size of the unit repair materials, and the total loadable volume; The maximum quantity calculation module is used to calculate, according to the size of the unit repair materials, the first maximum quantity of the unit repair materials that can be loaded when the remaining loadable volume is all used to load the unit repair materials; according to the size of the line patrol type drone, calculate the second maximum quantity of the line patrol type drone that can be loaded when the remaining loadable volume is all used for the line patrol type drone; according to the size of the transport type drone, calculate the third maximum quantity of the transport type drone that can be loaded when the remaining loadable volume is all used for the transport type drone; The loading configuration model building module is used to build a loading configuration model according to the first maximum number, the second maximum number, the third maximum number and the corresponding weight coefficients; The model solving module is used to solve the loading configuration model under the constraint of the remaining loading volume, and calculate the first target number of unit repair materials that can be loaded, the second target number of line patrol type drones that can be loaded, and the third target number of transport type drones that can be loaded when the target value corresponding to the loading configuration model is the maximum; The container loading module is used to load the remaining loadable volume of the container according to the first target quantity, the second target quantity and the third target quantity.

7. The container loading device for power facilities after a disaster as claimed in claim 6, characterized in that: Also includes: Deployment location calculation module; The deployment position calculation module is used to obtain the performance parameters of various types of drones to be packed, the location of the target location, the location of the distribution network transmission line and the location of the main network transmission line; wherein the target location includes: the disaster-stricken location and the undamaged high-voltage equipment tower base; according to the performance parameters of the various types of drones to be packed and the location of the target location, based on the farthest distance that a transport drone can reach when it flies out in a fully loaded state and returns to the machine nest in an empty state, a rough deployment position of the container to be configured is generated; according to the location of the distribution network transmission line, the location of the main network transmission line and the location of the target location, based on the rough deployment position, the final deployment position of the container to be configured is calculated and generated.

8. The container loading device for power facilities after a disaster as claimed in claim 6, characterized in that: The container loading module comprises: a packaging layout plan generating unit and a packaging loading unit; The packing layout plan generating unit is used to generate a container packing layout plan based on a packing algorithm according to the first target quantity, the second target quantity, the third target quantity, the sizes of the various types of drones to be packed, and the sizes of the unit repair materials to be packed; The packing and loading unit is used 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 in the memory and executable on the processor, wherein: When the processor executes the computer program, the container loading method for power facility post-disaster according to any one of claims 1 to 5 can be implemented.

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

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