An unmanned aerial vehicle deployment system for cleaning large-scale photovoltaic base stations

Abstract

The present invention relates to the technical field of UAV deployment, and specifically discloses a UAV deployment system for cleaning large-scale photovoltaic base stations, including: a scheduling platform, a plurality of first UAVs with a general cleaning mode, a plurality of second UAVs with a strong cleaning mode, and a plurality of third UAVs with a mixed cleaning mode; wherein, the scheduling platform specifically includes: an interaction module for performing human-machine interaction to obtain the type of the photovoltaic base station; a scheduling mode matching module that communicates with the interaction module for matching different scheduling modules according to different types of photovoltaic benchmarks; a first scheduling module for configuring UAVs based on the first photovoltaic base station to clean the photovoltaic panels; a second scheduling module for configuring UAVs based on the second photovoltaic base station to clean the photovoltaic panels. The present invention obtains the basic situation of the photovoltaic panels in the photovoltaic base station to be cleaned through the interaction module, so as to match the corresponding scheduling module for configuring UAVs for cleaning.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an unmanned aerial vehicle deployment system for cleaning large-scale photovoltaic base stations. Background Art

[0002] A photovoltaic panel is an array of solar panels composed of a series of solar cells connected in series and parallel. Due to the obstruction of dust and other stains, it will affect the power generation efficiency of the photovoltaic panels, and even generate photovoltaic hot spots, damaging the photovoltaic panel components; nowadays, photovoltaic power stations exist in various forms, such as building-integrated photovoltaic ones, large-scale photovoltaic power stations in the northwest desert areas, etc.; the solar panels of these photovoltaic power stations are vulnerable to the influence of stains such as dust accumulation, bird droppings, water scale, and oil stains, resulting in a significant decline in power generation efficiency and causing economic losses. Therefore, the cleaning of photovoltaic panels is essential.

[0003] The prior art Chinese patent application CN202210411513.6 discloses a photovoltaic cleaning method combined with an unmanned aerial vehicle, including the following steps: Step 1, dividing a photovoltaic power station into several areas, and each area is allocated a set of cleaning devices; Step 2, using an unmanned aerial vehicle to collect images of photovoltaic panels, using a cloud platform to identify stains and set cleaning trajectories; Step 3, using an unmanned aerial vehicle to drop a photovoltaic cleaning robot, and the photovoltaic cleaning robot cleans along the planned path; Step 4, the unmanned aerial vehicle finally transports the photovoltaic cleaning robot to an energy storage charging bin.

[0004] The above prior art proposes a specific method for cleaning photovoltaic panels by using an unmanned aerial vehicle. However, its cleaning method is relatively fixed and has certain limitations. Due to the installation angle and environment of solar photovoltaic panels, dust is not evenly distributed. The fixed cleaning method not only requires more cleaning costs but also cannot guarantee the cleaning efficiency of solar photovoltaic panels.

[0005] Another prior art Chinese patent application CN202310330164.X discloses a solar photovoltaic panel cleaning operation monitoring and regulation system, which includes a photovoltaic panel basic information acquisition module, a photovoltaic panel dust monitoring module, a photovoltaic panel pollution monitoring module, a photovoltaic panel cleaning mode analysis module, a photovoltaic panel cleaning rule analysis module, a photovoltaic panel cleaning regulation plan generation module, and a cleaning operation information database;

[0006] The above prior art monitors the dust concentration and pollution information of each solar photovoltaic panel laid in a specified area, and thus analyzes the cleaning requirements, cleaning modes, and cleaning rules, and then conducts cleaning regulation. However, the above prior art does not conduct corresponding research on the cleaning of photovoltaic panels by unmanned aerial vehicles, making this technical field still relatively weak. Summary of the Invention

[0007] The object of the present invention is to provide a drone deployment system for cleaning large-scale photovoltaic base stations, which partially solves or alleviates the above deficiencies in the prior art and can configure corresponding types of drones for cleaning according to the types of dirt in the photovoltaic panel area.

[0008] To solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions:

[0009] A drone deployment system for cleaning large-scale photovoltaic base stations, comprising: a scheduling platform, a plurality of first drones with a normal cleaning mode, a plurality of second drones with a strong cleaning mode, and a plurality of third drones with a mixed cleaning mode, wherein the first drones, the second drones and the third drones are all in wireless data communication with the scheduling platform; wherein, the scheduling platform specifically includes:

[0010] An interaction module for performing human-computer interaction to obtain the type of the photovoltaic base station; the types of the photovoltaic base station include a first photovoltaic base station deployed in a flat area and a second photovoltaic base station deployed in a mountainous area with complex terrain;

[0011] A scheduling mode matching module, which communicates with the interaction module and is used to match different scheduling modules according to different types of photovoltaic reference; wherein, the scheduling module includes a first scheduling mode applicable to the first photovoltaic base station and a second scheduling module applicable to the second photovoltaic base station;

[0012] A first scheduling module for configuring drones to clean the photovoltaic panels based on the first photovoltaic base station;

[0013] A second scheduling module for configuring drones to clean the photovoltaic panels based on the second photovoltaic base station.

[0014] As an improvement, the first scheduling module includes:

[0015] A first area division module for dividing the photovoltaic panels to be cleaned in the first photovoltaic base station into areas;

[0016] A first calculation module for calculating the density Pi of each of the three cleaning modes in each area based on the respective cleaning modes of each photovoltaic panel in each area of the first photovoltaic base station; the three cleaning modes include: normal cleaning mode, strong cleaning mode and mixed cleaning mode; the density is the number of photovoltaic panels corresponding to each cleaning mode in the current area; i = 1, 2, 3;

[0017] A first configuration module, configured to, when the density of the first cleaning mode in any area is greater than a first preset density threshold P0 and the sum of the densities of the other two cleaning modes is less than a second preset density threshold P0', configure a plurality of first unmanned aerial vehicle groups with the first cleaning mode for the any area;

[0018] configured to, when the density of the first cleaning mode in the any area is greater than a third preset density threshold P0'' and the density of the second cleaning mode is greater than a fourth preset density threshold P0''', configure a plurality of first unmanned aerial vehicle groups with the first cleaning mode and a plurality of second unmanned aerial vehicle groups with the second cleaning mode for the any area; the first cleaning mode is any one of the normal cleaning mode, the strong cleaning mode, and the mixed cleaning mode, and the second cleaning mode is any one of the other two cleaning modes other than the first cleaning mode; the third preset density threshold P0'' is less than the first preset density threshold P0, and the fourth preset density threshold P0''' is greater than the second preset density threshold P0';

[0019] configured to, when the first judgment module determines that the difference between the densities of any two of the three cleaning modes in the any area is less than a preset difference threshold △P, respectively configure a plurality of unmanned aerial vehicle groups with the normal cleaning mode, a plurality of unmanned aerial vehicle groups with the strong cleaning mode, and a plurality of unmanned aerial vehicle groups with the mixed cleaning mode for the any area;

[0020] A secondary cleaning scheduling module I, configured to perform area scanning after cleaning is completed to obtain a target for secondary cleaning and perform secondary cleaning.

[0021] As an improvement, when the density of the first cleaning mode in any area is greater than a first preset density threshold P0 and the sum of the densities of the other two cleaning modes is less than a second preset density threshold P0', and when the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the first configuration module configures unmanned aerial vehicles with the corresponding cleaning mode to perform cleaning, and the remaining part is to be cleaned secondarily;

[0022] When the density of the first cleaning mode in any area is greater than a first preset density threshold P0 and the sum of the densities of the other two cleaning modes is less than a second preset density threshold P0', and when the first cleaning mode is the mixed cleaning mode, the first configuration module configures unmanned aerial vehicles with the mixed cleaning mode to clean the entire area.

[0023] As an improvement, when the density of the first cleaning mode in any of the regions is greater than the third preset density threshold P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold P0''', in the case where both the first cleaning mode and the second cleaning mode are one of the normal cleaning mode or the strong cleaning mode, the first configuration module configures the drones with the corresponding cleaning mode to perform cleaning; and the remaining part is cleaned by the drones with the normal cleaning mode and the drones with the strong cleaning mode respectively;

[0024] When the density of the first cleaning mode in any of the regions is greater than the third preset density threshold P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold P0''', in the case where the first cleaning mode or the second cleaning mode is the mixed cleaning mode, the first configuration module configures the drones with the corresponding cleaning mode to perform cleaning; and the remaining part awaits secondary cleaning.

[0025] As an improvement, the second scheduling module includes:

[0026] A second area division module, which takes a specified first photovoltaic panel as the starting point. If the number of first photovoltaic panels adjacent to it and having the same cleaning mode reaches the first preset threshold N1, the first photovoltaic panel and the first photovoltaic panels adjacent to it and having the same cleaning mode are divided into one area, obtaining multiple areas with a single cleaning mode and multiple areas with a mixed cleaning mode; the single cleaning mode is either the normal cleaning mode or the strong cleaning mode; the mixed cleaning mode includes the normal cleaning mode and the strong cleaning mode;

[0027] A second calculation module, which calculates the density Pi of the cleaning mode corresponding to multiple scattered second photovoltaic panels between any specified area and its adjacent areas; the density Pi = the number n of second photovoltaic panels in any cleaning mode / the sum N of the numbers of second photovoltaic panels in the three cleaning modes, where i = 1, 2, 3;

[0028] A second integration module, which, when the second judgment module determines that N is greater than or equal to the second preset threshold N2 and the density Pi of any one of the cleaning modes is greater than or equal to the first preset density threshold p0, divides each of the scattered second photovoltaic panels between the specified area and its adjacent areas into a separate comprehensive area;

[0029] When the second judgment module determines that N is greater than or equal to the second preset threshold N2 and the density Pi of any one of the cleaning modes is less than the first preset density threshold p0, it divides each of the second photovoltaic panels into the area closest to it according to its cleaning mode;

[0030] When the second judgment module determines that N is less than the second preset threshold value N2, all the second photovoltaic panels are divided into the designated area;

[0031] A second configuration module is used to configure a drone group with a corresponding cleaning mode for each area;

[0032] The secondary cleaning scheduling module II is used to scan the area after the cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning.

[0033] As an improvement, the scheduling platform further includes:

[0034] The power judgment module is used to receive and judge whether the remaining power feedback from any drone reaches a preset power threshold;

[0035] The task allocation module is used to obtain a list of pending tasks of any UAV when the remaining power of the UAV reaches a preset power threshold, and determine whether the list of pending tasks is empty;

[0036] If it is not empty, obtain the remaining power and pending task lists of multiple other drones near the any drone, and determine whether the other drones can add new cleaning tasks according to the remaining power of the other drones and the number of pending tasks in the pending task list; if it can be added, select at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than a preset threshold, and evenly distribute the pending tasks in the pending task list of any drone to the selected at least one other drone;

[0037] The return control module is used to control any drone to return to the starting point from the current position.

[0038] As an improvement, the task allocation module further includes:

[0039] The recommendation submodule is used to calculate the recommendation index of each other drone when at least one other drone is screened out: P=K1*D i，j +K2*T i，j ; Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other drones to execute the newly added task; K1 and K2 are empirical constants;

[0040] Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

[0041] As an improvement, the task allocation module further includes:

[0042] A new drone module is added, which is used to re - dispatch a new drone for the area when the number of tasks to be processed in the to - be - processed task list of any drone is greater than or equal to a preset threshold of the number of tasks to be processed.

[0043] As an improvement, the task allocation module further includes:

[0044] A current task allocation module, which is used to judge whether the current task is completed when any drone returns to the starting point from the current position; if not, allocate the current task to the nearest other drone.

[0045] As an improvement, both the secondary cleaning scheduling module I and the secondary cleaning scheduling module II include:

[0046] A target calculation module, which is used to calculate the secondary cleaning target quantity of each area and judge whether the secondary cleaning target quantity is greater than or equal to the addable to - be - processed task quantity of all the drones that can work again in the area;

[0047] A secondary configuration module, which is used to allocate the idle and reusable drones in the adjacent areas when the secondary cleaning target quantity is greater than or equal to the addable to - be - processed task quantity of all the drones that can work again in the area;

[0048] When the secondary cleaning target quantity is less than the addable to - be - processed task quantity of all the drones that can work again in the area, evenly distribute each of the secondary cleaning targets in the area to all the drones that can work again in the area.

[0049] The beneficial effects of the present invention are as follows:

[0050] The present invention obtains the basic situation of the photovoltaic panels in the photovoltaic base station to be cleaned through the interaction module, so as to match the corresponding scheduling module for configuring drones for cleaning. Among them, the scheduling module includes a first scheduling mode applicable to the first photovoltaic base station and a second scheduling module applicable to the second photovoltaic base station.

[0051] The first scheduling module divides the entire area to be cleaned into several preset areas according to the established division rules, and calculates the cleaning density of the three cleaning modes in each area. After obtaining the density ratio of the three cleaning modes, different forms of drone configuration are carried out in three cases.

[0052] When the density of the first cleaning mode is greater than the first preset density threshold P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold P0', only configure multiple drones with the first cleaning mode. If the first cleaning mode is the normal cleaning mode or the strong cleaning mode, configure the corresponding drones for cleaning, and the remaining part awaits secondary cleaning. If the first cleaning mode is the mixed cleaning mode, configure the drones with the mixed cleaning mode to clean the entire area. The drones with the mixed cleaning mode can clean all types of dirt. Since the total amount of normal + strong dirt in this area is small, it is more economical and efficient to directly configure the drones with the mixed cleaning mode for cleaning.

[0053] When the density of the first cleaning mode is greater than the third preset density threshold P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold P0''', configure the drones with the corresponding cleaning modes for cleaning. If both the first cleaning mode and the second cleaning mode are one of the normal cleaning mode or the strong cleaning mode, configure the corresponding drones for cleaning. The remaining part can be completed by separately cleaning with the drones with the normal cleaning mode and the drones with the strong cleaning mode, without the need to separately configure the drones with the mixed cleaning mode for cleaning. If the first cleaning mode or the second cleaning mode is the mixed cleaning mode, configure the corresponding drones for cleaning, and the remaining part awaits secondary cleaning.

[0054] When the difference between the densities of the three cleaning modes taken pairwise is less than the preset difference threshold, it is sufficient to configure the drones with the corresponding cleaning modes for cleaning.

[0055] For the characteristic that the photovoltaic panels in the mountain photovoltaic base station are relatively scattered, the second scheduling module integrates the photovoltaic panels with the same cleaning mode that are adjacent or indirectly adjacent into one area through a method similar to "clustering" and overall configures the drones for cleaning.

[0056] For the scattered photovoltaic panels between regions, the present invention has carried out separate treatments according to three situations:

[0057] Integrate the scattered photovoltaic panels that reach a certain order of magnitude and have a relatively concentrated cleaning mode into a separate area. For the scattered photovoltaic panels that reach a certain order of magnitude but have a relatively scattered cleaning mode, absorb them according to the cleaning mode in the surrounding areas. For the scattered photovoltaic panels with a small number, directly incorporate them into a designated area.

[0058] Through the above drone configuration method, the cleaning efficiency can be greatly improved, and the loss of drones during the journey can be reduced.

[0059] In addition, the present invention can also allocate drones according to the battery power of the drones. When the remaining battery power of a certain drone reaches the battery power threshold, the drone is made to return, avoiding the problem that the drone cannot return due to too low remaining battery power during operation due to the vastness of the photovoltaic base stations.

[0060] At the same time, the present invention also finds a successor for the returning drone to take over its unfinished tasks and ensure the execution of the cleaning tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale. Obviously, the following-described drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0062] Figure 1 It is a schematic structural diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0064] In this article, suffixes such as "module", "component", or "unit" used to represent elements are only for the convenience of the description of the present invention and have no specific meaning in themselves. Therefore, "module", "component", or "unit" can be used interchangeably.

[0065] In this article, terms such as "upper", "lower", "inner", "outer", "front", "rear", "one end", "the other end", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation of the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0066] In this article, unless otherwise clearly defined and limited, terms such as "installation", "equipped with", "connection", etc. shall be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, and can also be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0067] In this article, "and / or" includes any and all combinations of one or more of the listed related items.

[0068] In this article, "a plurality of" means two or more, that is, it includes two, three, four, five, etc.

[0069] Embodiment 1:

[0070] As Figure 1 shown, the present invention provides a drone deployment system for cleaning large-scale photovoltaic base stations, which is applied to the cleaning of photovoltaic panels in photovoltaic base stations. Photovoltaic base stations can be built in open areas such as deserts and plains, or in mountainous areas with relatively rough and complex terrains. It can be understood that the photovoltaic panels of photovoltaic base stations located in open terrains are arranged more concentratedly. Compared with plain areas such as deserts, since the terrain in mountainous areas is more complex, not all terrains are suitable for installing photovoltaic panels, so the installation of photovoltaic panels is relatively scattered.

[0071] The present invention aims to efficiently clean the photovoltaic panels in the above two types of photovoltaic base stations through the deployment of drones. This system specifically includes

[0072] a scheduling platform, a plurality of first drones with a normal cleaning mode, a plurality of second drones with a strong cleaning mode, and a plurality of third drones with a hybrid cleaning mode, wherein the first drones, the second drones, and the third drones are all in wireless data communication with the scheduling platform.

[0073] The photovoltaic panels in the photovoltaic base stations arranged in deserts and plains are mainly soiled with dust, water scale, oil stains, bird droppings, etc. Among them, the cleaning of dust and water scale is relatively simple. Therefore, in the present invention, the cleaning mode of the drone for cleaning dust and water scale is classified as the normal mode (the first drone). The cleaning of oil stains and bird droppings is relatively complex. Therefore, in the present invention, the cleaning mode of the drone for cleaning oil stains and bird droppings is classified as the strong mode (the second drone). The cleaning agents and cleaning tools carried by the drone in the two modes are different, resulting in that both cleaning modes can only target their own types of soiling and cannot cover other types of soiling. In practice, some of the soiling on the photovoltaic panels is not of only one type. Therefore, the cleaning mode of the drone in the present invention also includes a mixed cleaning mode (the third drone), which can perform both normal cleaning and strong cleaning. Of course, it can be foreseen that the types of cleaning agents and cleaning tools carried by the drone in the mixed cleaning mode are more, which will greatly reduce the endurance time of the drone. Therefore, it cannot be used as a conventional mode.

[0074] In the present invention, the cleaning mode of each photovoltaic panel in the entire area to be cleaned can be obtained in advance, that is, the corresponding cleaning mode is matched according to the type of soiling on each photovoltaic panel. For the specific method of obtaining the type of soiling, reference can be made to the prior art CN202310330164.X in the background technology, which will not be elaborated here.

[0075] In this embodiment, the types of soiling include the normal type (dust + water scale), the strong type (oil stain + bird droppings), and the mixed type (dust + water scale + oil stain + bird droppings), which respectively correspond to the cleaning modes of the drone: the normal cleaning mode, the strong cleaning mode, and the mixed cleaning mode.

[0076] In addition, it can be foreseen that the drone realizes wireless communication with the dispatching platform through a wireless network.

[0077] The dispatching platform is responsible for dispatching the drone so that the drone can clean efficiently and avoid consuming too much power on the way.

[0078] Specifically, it includes:

[0079] An interaction module for performing human-machine interaction to obtain the type of the photovoltaic base station; the types of the photovoltaic base station include the first photovoltaic base station arranged in a flat area and the second photovoltaic base station arranged in a mountainous area with complex terrain.

[0080] Through the interaction module, human-machine interaction can be carried out to obtain relevant information about the photovoltaic base station, such as the number, distribution, soiling situation, and layout terrain of the photovoltaic panels.

[0081] The scheduling mode matching module communicates with the interaction module for data, and is used to match different scheduling modules according to different photovoltaic benchmark types. Among them, the scheduling module includes a first scheduling mode applicable to the first photovoltaic base station and a second scheduling module applicable to the second photovoltaic base station.

[0082] After obtaining the basic situation of the photovoltaic base station, the scheduling mode matching module matches the corresponding scheduling module for the photovoltaic base station that needs to be cleaned currently.

[0083] Among them, the first scheduling module is used to configure drones to clean the photovoltaic panels based on the first photovoltaic base station. Specifically, it includes:

[0084] The first area division module is used to divide the photovoltaic panels to be cleaned in the first photovoltaic base station into areas.

[0085] Since the area of the area to be cleaned may be relatively large, which is not conducive to the deployment of drones. Therefore, in this embodiment, the area to be cleaned can be divided into several preset areas by the first area division module first, and then the drones can be arranged for cleaning in a coordinated manner.

[0086] The rule for dividing the preset areas can be to directly divide the area to be cleaned into equal-area averages, or to divide it according to the dirt type. In this embodiment, the second division method is more preferred.

[0087] In this embodiment, the dirt types include ordinary type (dust + water scale), strong type (oil stain + bird droppings), and mixed type (dust + water scale + oil stain + bird droppings), which correspond to the cleaning modes of the drones: ordinary cleaning mode, strong cleaning mode, and mixed cleaning mode respectively.

[0088] Of course, it can be understood that even if the division is made according to the dirt type, for the simplicity of the division, the area division is also a rough division, trying to make there be only one dirt type in one area, while there will still be multiple types of dirt in some actual areas.

[0089] The first calculation module is used to calculate the density Pi of each of the three cleaning modes in each area based on the respective cleaning modes of each photovoltaic panel in each area of the first photovoltaic base station. The three cleaning modes include: ordinary cleaning mode, strong cleaning mode, and mixed cleaning mode. The density is the number of photovoltaic panels corresponding to each cleaning mode in the current area; i = 1, 2, 3.

[0090] After dividing the preset area, the density of each cleaning mode can be calculated according to the density of photovoltaic panels with various types of dirt. Simply put, it is analyzed that in a certain preset area, there is 80% of ordinary dirt, 15% of strong dirt, and 10% of mixed dirt. The corresponding densities of the cleaning modes are P1 = 80%, P2 = 15%, P3 = 5%, and so on.

[0091] The first configuration module is used to configure multiple first unmanned aerial vehicle groups with the first cleaning mode for any area when the density of the first cleaning mode in any area is greater than the first preset density threshold P0 and the sum of the densities of the other two cleaning modes is less than the second preset density threshold P0'.

[0092] The first calculation module calculates the density of each cleaning mode in a certain preset area. However, if the drones are completely matched according to the density, it is unreasonable in some cases. For example, when the density of a certain cleaning mode is as high as more than 90%, and the sum of the densities of other modes does not exceed 5% (the remaining 5% does not need to be cleaned), for the drones with a cleaning mode density of only 5%, the round-trip time and the time for jumping within the area may be longer than the cleaning time, and this situation is considered uneconomical.

[0093] Therefore, in this module, when the density of a certain cleaning mode (such as the ordinary cleaning mode) is greater than the first preset density threshold P0 (such as 90%), and the sum of the densities of the other two cleaning modes is less than the second preset density threshold P0' (5%), then only the drones with the ordinary cleaning mode are configured to go.

[0094] The mode with a density greater than the preset density threshold P0 may be one of the ordinary cleaning mode, the strong cleaning mode, and the mixed cleaning mode.

[0095] When the first cleaning mode is the ordinary cleaning mode or the strong cleaning mode, the first configuration module configures the drones with the ordinary cleaning mode or the strong cleaning mode to clean 90% of the corresponding area, and the remaining 5% will be cleaned by configuring drones in the subsequent secondary cleaning.

[0096] When the first cleaning mode is the mixed cleaning mode, the first configuration module configures the drones with the mixed cleaning mode to clean the entire area. The drones with the mixed cleaning mode can clean all types of dirt. Since the total amount of ordinary + strong dirt in this area is also less than 5%, it is more economical and efficient to directly configure the drones with the mixed cleaning mode for cleaning.

[0097] The first configuration module is further configured to, when the density of the first cleaning mode in any of the regions is greater than a third preset density threshold P0'', and the density of the second cleaning mode is greater than a fourth preset density threshold P0''', configure a plurality of first unmanned aerial vehicle groups with the first cleaning mode and a plurality of second unmanned aerial vehicle groups with the second cleaning mode for any of the regions; the first cleaning mode is any one of the normal cleaning mode, the strong cleaning mode, and the mixed cleaning mode, and the second cleaning mode is any one of the remaining two cleaning modes other than the first cleaning mode; the third preset density threshold P0'' is less than the first preset density threshold P0, and the fourth preset density threshold P0''' is greater than the second preset density threshold P0'.

[0098] When the density of a certain cleaning mode in a preset region is too small, it is uneconomical to configure drones individually. However, when the density of a certain type of dirt reaches a certain threshold, it is necessary to configure corresponding types of drones for cleaning.

[0099] For example, if the density of the first cleaning mode in a certain region is greater than the third preset density threshold P0'' (50%), and the density of the second cleaning mode is greater than the fourth preset density threshold P0''' (e.g., 40%), then drones with the above two cleaning modes should be configured for targeted cleaning.

[0100] When both the first cleaning mode and the second cleaning mode are one of the normal cleaning mode or the strong cleaning mode, the first configuration module configures corresponding drones for cleaning. And the remaining 10% (of course, it may be less than 10% because some photovoltaic panels do not need to be cleaned) can be completed by cleaning with drones with the normal cleaning mode and drones with the strong cleaning mode respectively, without the need to separately configure drones with the mixed cleaning mode for cleaning.

[0101] When the first cleaning mode or the second cleaning mode is the mixed cleaning mode, the first configuration module configures corresponding drones for cleaning. And the remaining 10% (which may be the normal cleaning mode or the strong cleaning mode) can be cleaned by configuring corresponding drones in subsequent secondary cleaning.

[0102] The first configuration module is further configured to, when the first judgment module determines that the difference between any two of the densities of the three cleaning modes in any of the regions is less than a preset difference threshold △P, configure a plurality of unmanned aerial vehicle groups with the normal cleaning mode, a plurality of unmanned aerial vehicle groups with the strong cleaning mode, and a plurality of unmanned aerial vehicle groups with the mixed cleaning mode for any of the regions respectively.

[0103] It can be foreseen that if the densities of the three modes are too close, it is uneconomical to use alternative cleaning methods (i.e., using drones with ordinary cleaning modes and drones with strong cleaning modes to cooperate in cleaning mixed dirt, or using drones with composite cleaning modes to clean ordinary dirt or strong dirt).

[0104] Therefore, when the difference between any two of the densities of the three cleaning modes is less than the preset difference threshold (e.g., 10%), the first configuration module can directly configure the corresponding drones for cleaning.

[0105] The secondary cleaning scheduling module I is used to perform area scanning after cleaning is completed to obtain the targets to be secondarily cleaned and perform secondary cleaning.

[0106] For the sake of economy, it is possible that some areas are not cleaned. After the entire area to be cleaned has undergone one round of cleaning, the uncleaned areas are coordinated and re-divided, and then another round of cleaning is carried out according to the above scheme until all the photovoltaic panels are cleaned.

[0107] In addition, in some other embodiments, the secondary cleaning module I (the same applies to the subsequent secondary cleaning module II) includes:

[0108] The target calculation module is used to calculate the number of secondary cleaning targets for each area and determine whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to all the drones that can work again in the area.

[0109] During secondary cleaning, the remaining uncleaned areas after the first cleaning are integrated and re-divided. The division rule is still based on the dirt type.

[0110] After the area is re-divided, there may be drones in the area still performing the tasks of the previous cleaning. Therefore, it can first be determined whether the drones in the area can meet the requirements of this cleaning.

[0111] The secondary configuration module is used to allocate the idle and reusable drones in the adjacent areas when the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to all the drones that can work again in the area.

[0112] In the case where the drones in the area cannot meet the requirements of the secondary cleaning of the area, drones that can still perform tasks are allocated from the adjacent areas for cleaning. It can be foreseen that if the task lists of the drones in the adjacent areas are all saturated, the drones need to be reconfigured.

[0113] The adjacent areas mentioned above can be the areas adjacent to the target area or the areas whose distance from the target area is less than the distance threshold.

[0114] The secondary configuration module is further configured to evenly distribute each of the secondary cleaning targets in the area to all the drones that can work again in the area when the number of the secondary cleaning targets is less than the amount of addable pending tasks of all the drones that can work again in the area.

[0115] In the case where the drones in the area can already meet the requirements, the secondary cleaning tasks can be evenly distributed.

[0116] The second scheduling module in this embodiment is used to configure drones to clean the photovoltaic panels based on the second photovoltaic base station. Specifically, it includes:

[0117] A second area division module, which is configured to take a specified first photovoltaic panel as an initial point. If the number of the first photovoltaic panels adjacent to it and having the same cleaning mode reaches a first preset threshold N1, the first photovoltaic panel and the first photovoltaic panels adjacent to it and having the same cleaning mode are divided into one area, so as to obtain multiple areas with a single cleaning mode and multiple areas with a mixed cleaning mode; the single cleaning mode is any one of the normal cleaning mode and the strong cleaning mode; the mixed cleaning mode includes the normal cleaning mode and the strong cleaning mode.

[0118] The function of this module is to divide the preset cleaning areas so as to better overall arrange the drones for cleaning. In view of the scattered distribution of the mountain photovoltaic panels (of course, generally speaking, the cleaning modes of the photovoltaic panels in adjacent areas are still roughly the same), it is first necessary to "cluster" the photovoltaic panels with the same cleaning type and close distance. Specifically, taking a certain specified photovoltaic panel as the center, the photovoltaic panels of the same type adjacent to it (including indirectly adjacent) are divided into the same preset cleaning area. Of course, as a cleaning area, the number of its photovoltaic panels should not be too small. Therefore, a first preset threshold N1 is set in this embodiment, that is, the number of the same type of photovoltaic panels needs to reach the first preset threshold N1 to be used as a preset area. The purpose is to prevent the preset cleaning areas from being too scattered.

[0119] A second calculation module, which is configured to calculate the density Pi of the cleaning modes corresponding to multiple scattered second photovoltaic panels between any specified area and its adjacent areas; the density Pi = the number n of the second photovoltaic panels of any cleaning mode / the sum N of the numbers of the second photovoltaic panels of the three cleaning modes, where i = 1, 2, 3.

[0120] This module can calculate the density of various cleaning modes according to the density of the photovoltaic panels of various types of dirt contained. Simply put, it is analyzed that there are 80% of normal dirt, 15% of strong dirt, and 10% of mixed dirt in a certain preset area, and the corresponding density of the cleaning mode P1 = 80%, P2 = 15%, P3 = 5%, and so on.

[0121] The second integration module is used to integrate the scattered photovoltaic panels.

[0122] The second area division module can integrate the relatively concentrated photovoltaic panels of the same type into a preset cleaning area. After the integration of this step, there will still be some scattered photovoltaic panels (the second photovoltaic panels) not included in the preset cleaning area. Therefore, the role of the second integration module is to integrate the above-mentioned scattered photovoltaic panels, which includes three situations:

[0123] One is to form a new independent cleaning area; the second is to be absorbed by the surrounding cleaning areas respectively; the third is to be all absorbed by a certain preset cleaning area.

[0124] First, arbitrarily specify an area in the already divided area, and divide the scattered photovoltaic panels between this area and its adjacent areas.

[0125] Let the number of the above-mentioned scattered photovoltaic panels be N.

[0126] The second integration module is used to divide each of the second photovoltaic panels scattered between the designated area and its adjacent areas into a separate comprehensive area when the second judgment module determines that N is greater than or equal to the second preset threshold N2, and the density Pi of any one of the cleaning modes is greater than or equal to the first preset density threshold p0.

[0127] That is to say, when the number of scattered photovoltaic panels is greater than or equal to N2 (for example, 500), and the density of any one of the cleaning modes is greater than Pd (70%), then these scattered photovoltaic panels can form an independent area. That is to say, try to make the scattered photovoltaic panels relatively concentrated in type under the condition of meeting certain quantity requirements.

[0128] The second integration module is also used to divide each of the second photovoltaic panels into the area closest to it according to its cleaning mode when the second judgment module determines that N is greater than or equal to the second preset threshold N2, and the density Pi of any one of the cleaning modes is less than the first preset density threshold p0.

[0129] That is to say, when the number of scattered photovoltaic panels is greater than or equal to N2 (for example, 500), but the densities of all cleaning types are lower than Pd (70%), it means that the types of scattered photovoltaic panels are relatively messy and not suitable for forming an independent area. At this time, these scattered photovoltaic panels can be integrated into the surrounding areas according to their types.

[0130] The second integration module is further used to divide all the second photovoltaic panels into the designated area when the second judgment module determines that N is less than the second preset threshold N2.

[0131] That is to say, if the number of scattered photovoltaic panels is greater than N2 (for example, 500), it indicates that the level of scattered photovoltaic panels is relatively small, and they can be directly incorporated into the designated area. Of course, a better method is to incorporate them into the corresponding area according to the cleaning mode with the highest density.

[0132] The second configuration module is used to configure the unmanned aerial vehicle groups for each area with corresponding cleaning modes.

[0133] The function of this module is to configure the unmanned aerial vehicles for the areas divided by the second area division module. It can be understood that for areas with a single cleaning mode, directly configure the unmanned aerial vehicles with the corresponding cleaning mode for cleaning. For some composite areas (i.e., areas including multiple cleaning modes), this module also provides corresponding configuration strategies. The composite areas mainly refer to the situation where multiple second photovoltaic panels are divided into a single area. Of course, this method can also be extended to other areas that incorporate photovoltaic panels with other cleaning modes. The specific method for this module to configure the unmanned aerial vehicles can refer to the first configuration module, which will not be elaborated here.

[0134] Different from the first configuration module, when multiple second photovoltaic panels are divided into the designated area, and the cleaning mode of the designated area is a mixed cleaning mode, the second configuration module configures the unmanned aerial vehicles with the mixed cleaning mode to clean the entire designated area.

[0135] After the scattered photovoltaic panels (second photovoltaic panels) are divided into the designated area, it may bring photovoltaic panels with different cleaning modes to the designated area. Since the number of scattered photovoltaic panels is small and the area they are added to is already a mixed cleaning area, then directly use the unmanned aerial vehicles with the mixed cleaning mode to clean all the photovoltaic panels in the entire area.

[0136] The second configuration module also configures the unmanned aerial vehicles with the corresponding cleaning mode for cleaning when the cleaning mode of the designated area is the ordinary cleaning mode or the strong cleaning mode, and the remaining part awaits secondary cleaning.

[0137] If the original area is not a photovoltaic panel with a mixed cleaning mode, then configure the corresponding unmanned aerial vehicles according to the original cleaning mode to clean the photovoltaic panels of that cleaning mode, and the remaining un-cleaned photovoltaic panels await secondary cleaning.

[0138] When the scattered photovoltaic panels are incorporated into the surrounding areas according to their own cleaning modes, just configure them according to the original cleaning mode of the surrounding areas.

[0139] The secondary cleaning scheduling module II is used to perform area scanning after cleaning is completed to obtain the targets to be secondarily cleaned and perform secondary cleaning.

[0140] Similar to the secondary cleaning scheduling module I, after the cleaning in the previous step, there will still be some scattered photovoltaic panels that have not been cleaned. Therefore, area scanning is required to obtain the positions of the uncleaned photovoltaic panels and organize the drones for secondary cleaning.

[0141] In addition, the scheduling platform further includes:

[0142] A power judgment module, configured to receive and judge whether the remaining power fed back by any drone reaches a preset power threshold.

[0143] Generally speaking, photovoltaic base stations are relatively vast, and the cleaning work consumes a large amount of power for the drones. Therefore, it is necessary to always pay attention to the power of the drones to avoid being unable to return.

[0144] This module judges whether the drone has enough power to return by monitoring the remaining power of the drone in real time.

[0145] A task allocation module, configured to, when the remaining power of any drone reaches the preset power threshold, obtain the list of pending tasks of the any drone and judge whether the list of pending tasks is empty;

[0146] If it is not empty, obtain the remaining power and the list of pending tasks of multiple other drones near the any drone, and judge whether the other drones can add new cleaning tasks according to the remaining power of the other drones nearby and the number of pending tasks in the list of pending tasks; if they can add, select at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than the preset threshold, and evenly distribute the pending tasks in the list of pending tasks of the any drone to the selected at least one other drone.

[0147] When the drone reaches the preset power, it may still be executing tasks or there are tasks to be executed. In the above cases, it is necessary to find a successor for the tasks.

[0148] When a drone that is still executing tasks or has tasks to be executed reaches the preset power, it is necessary to find a successor for the tasks. Therefore, search for adjacent drones with the current position of the drone as the center and a preset radius, and obtain the remaining power and the list of pending tasks of the adjacent drones.

[0149] When looking for a successor for the tasks, it is necessary to judge whether the drone has enough power to support the subsequent tasks and the newly added tasks, so as to judge whether the drone is suitable for adding new tasks. It is easy to understand that drones with sufficient power and few tasks are preferred.

[0150] In addition to determining whether a drone can add a new task, the distance between the two and the waiting time must also be considered. Therefore, in this embodiment, the task allocation module also includes a recommendation submodule. When at least one other drone is selected, the recommendation index of each other drone is calculated: P = K1*D i，j +K2*T i，j ; Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other UAVs to execute the newly added task; K1 and K2 are empirical constants.

[0151] Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

[0152] The drone may still be executing the current task when the power threshold is reached, so the task allocation module also includes a current task allocation module, which is used to determine whether the current task is completed when any drone returns to the starting point from the current position; if not completed, the current task is allocated to the nearest other drone.

[0153] And a newly added drone module is used to dispatch a new drone to the area when the number of pending tasks in the pending task list of any drone is greater than or equal to a preset pending task threshold.

[0154] The number of pending tasks in a drone's task list is preset to a pending threshold, indicating that the drone's tasks are saturated and no new tasks can be accepted. When all drones are saturated with tasks, new drones need to be added.

[0155] The return control module is used to control any drone to return to the starting point from its current position.

[0156] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0157] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a computer terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0158] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the present invention and the claims. All of these are within the protection scope of the present invention.

Claims

1. A drone deployment system for cleaning large photovoltaic base stations, characterized in that: include: A scheduling platform, a plurality of first drones with a normal cleaning mode, a plurality of second drones with a strong cleaning mode, and a plurality of third drones with a mixed cleaning mode, wherein the first drones, the second drones, and the third drones all communicate wirelessly with the scheduling platform; wherein the scheduling platform specifically includes: An interaction module, used for performing human-computer interaction to obtain the type of photovoltaic base station; the type of photovoltaic base station includes a first photovoltaic base station deployed in a flat area and a second photovoltaic base station deployed in a mountainous area with complex terrain; A scheduling mode matching module performs data communication with the interaction module and is used to match different scheduling modules according to different photovoltaic base station types; wherein the scheduling module includes a first scheduling module applicable to the first photovoltaic base station and a second scheduling module applicable to the second photovoltaic base station; A first scheduling module is used to configure a drone to clean the photovoltaic panel based on the first photovoltaic base station; A second scheduling module is used to configure the drone to clean the photovoltaic panel based on the second photovoltaic base station; The first scheduling module includes: A first area division module, used for dividing the photovoltaic panels to be cleaned in the first photovoltaic base station into areas; The first calculation module is used to calculate the density Pi of the three cleaning modes in each area based on the cleaning mode of each photovoltaic panel in each area of ​​the first photovoltaic base station; the three cleaning modes include: ordinary cleaning mode, strong cleaning mode and mixed cleaning mode; the density is the percentage of photovoltaic panels corresponding to each cleaning mode in the current area; i=1, 2, 3; The first configuration module is used to configure a plurality of first drone groups with the first cleaning mode for any area when the density of the first cleaning mode in any area is greater than a first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than a second preset density threshold value P0'; and to configure a plurality of first drone groups with the first cleaning mode and a plurality of second drone groups with the second cleaning mode for any area when the density of the first cleaning mode in any area is greater than a third preset density threshold value P0'', and the density of the second cleaning mode is greater than a fourth preset density threshold value P0'''; the first cleaning mode is the ordinary cleaning mode , any one of the strong cleaning mode and the mixed cleaning mode, the second cleaning mode is any one of the other two cleaning modes other than the first cleaning mode; the third preset density threshold P0'' is less than the first preset density threshold P0, and the fourth preset density threshold P0''' is greater than the second preset density threshold P0'; and when the first judgment module determines that the difference between the densities of the three cleaning modes in any area is less than the preset difference threshold △P, a plurality of drone groups with ordinary cleaning mode, a plurality of drone groups with strong cleaning mode and a plurality of drone groups with mixed cleaning mode are respectively configured for any area; The secondary cleaning scheduling module I is used to scan the area after the cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning; When the density of the first cleaning mode in any area is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', and when the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the first configuration module configures the drone with the corresponding cleaning mode to clean, and the remaining part is to be cleaned twice; When the density of the first cleaning mode in any area is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', and the first cleaning mode is a mixed cleaning mode, the first configuration module configures the drone with the mixed cleaning mode to clean the entire area; When the density of the first cleaning mode in any area is greater than the third preset density threshold value P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''', in the case where the first cleaning mode and the second cleaning mode are both one of the ordinary cleaning mode and the strong cleaning mode, the first configuration module configures the drone with the corresponding cleaning mode to clean; and the remaining part is cleaned by the drone with the ordinary cleaning mode and the drone with the strong cleaning mode respectively; When the density of the first cleaning mode in any area is greater than the third preset density threshold value P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''', in the case where the first cleaning mode or the second cleaning mode is a mixed cleaning mode, the first configuration module configures the drone with the corresponding cleaning mode to perform cleaning; and the remaining part is to be cleaned twice; Specifically, the secondary cleaning scheduling module I includes: A target calculation module is used to calculate the number of secondary cleaning targets in each area, and determine whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all drones that can work again in the area; A secondary configuration module, configured to deploy idle and reusable drones in adjacent areas when the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all reusable drones in the area; When the number of the secondary cleaning targets is less than the amount of tasks that can be added to be processed by all the drones that can work again in the area, the secondary cleaning targets in the area are evenly distributed to all the drones that can work again in the area.

2. The drone deployment system for cleaning large photovoltaic base stations according to claim 1 is characterized in that: The second scheduling module includes: A second area division module is used to take the designated first photovoltaic panel as the initial point, and if the number of first photovoltaic panels adjacent to the designated first photovoltaic panel and having the same cleaning mode reaches a first preset threshold value N1, divide the first photovoltaic panel and the first photovoltaic panels adjacent to the designated first photovoltaic panel and having the same cleaning mode into one area, so as to obtain multiple areas of a single cleaning mode and multiple areas of a mixed cleaning mode; the single cleaning mode is any one of a normal cleaning mode and a strong cleaning mode; the mixed cleaning mode includes a normal cleaning mode and a strong cleaning mode; The second calculation module is used to calculate the density Pi of the cleaning modes corresponding to the scattered multiple second photovoltaic panels between any designated area and its adjacent areas; the density Pi=the number n of the second photovoltaic panels in any cleaning mode / the sum of the numbers of the second photovoltaic panels in the three cleaning modes N, wherein i=1, 2, 3; A second integration module, configured to divide the second photovoltaic panels scattered between the designated area and its adjacent areas into a separate integrated area when the second judgment module determines that N is greater than or equal to a second preset threshold value N2, and the density Pi of any cleaning mode is greater than or equal to a first preset density threshold value p0; When the second judgment module determines that N is greater than or equal to the second preset threshold value N2, and the density Pi of any cleaning mode is less than the first preset density threshold value p0, each of the second photovoltaic panels is divided into the area closest to it according to its cleaning mode; When the second judgment module determines that N is less than the second preset threshold value N2, all the second photovoltaic panels are divided into the designated area; A second configuration module is used to configure a drone group with a corresponding cleaning mode for each area; The secondary cleaning scheduling module II is used to scan the area after the cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning.

3. The drone deployment system for cleaning large photovoltaic base stations according to claim 1 is characterized in that: The scheduling platform also includes: The power judgment module is used to receive and judge whether the remaining power feedback from any drone reaches a preset power threshold; The task allocation module is used to obtain a list of pending tasks of any UAV when the remaining power of the UAV reaches a preset power threshold, and determine whether the list of pending tasks is empty; If it is not empty, obtain the remaining power and pending task lists of multiple other drones near the any drone, and determine whether the other drones can add new cleaning tasks according to the remaining power of the other drones and the number of pending tasks in the pending task list; if it can be added, select at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than a preset threshold, and evenly distribute the pending tasks in the pending task list of any drone to the selected at least one other drone; The return control module is used to control any drone to return to the starting point from the current position.

4. The drone deployment system for cleaning large photovoltaic base stations according to claim 3 is characterized in that: The task allocation module also includes: The recommendation submodule is used to calculate the recommendation index of each other drone when at least one other drone is screened out: P=K1*D i，j +K2*T i，j Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other drones to perform the newly added tasks; K1 and K2 are empirical constants; Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

5. The drone deployment system for cleaning large photovoltaic base stations according to claim 3 is characterized in that: The task allocation module also includes: A newly added drone module is used to dispatch a new drone to the area where the drone is working when the number of pending tasks in the pending task list of any drone is greater than or equal to a preset pending task threshold.

6. The drone deployment system for cleaning large photovoltaic base stations according to claim 3 is characterized in that: The task allocation module also includes: The current task allocation module is used to determine whether the current task is completed when any drone returns to the starting point from the current position; if not, the current task is allocated to the nearest other drone.

7. The drone deployment system for cleaning large photovoltaic base stations according to claim 2 is characterized in that: The secondary cleaning scheduling module II includes: A target calculation module is used to calculate the number of secondary cleaning targets in each area, and determine whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all drones that can work again in the area; A secondary configuration module, configured to deploy idle and reusable drones in adjacent areas when the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all reusable drones in the area; When the number of the secondary cleaning targets is less than the amount of tasks that can be added to be processed by all the drones that can work again in the area, the secondary cleaning targets in the area are evenly distributed to all the drones that can work again in the area.

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