A drone deployment system for cleaning large photovoltaic base stations

Abstract

The application relates to the technical field of unmanned aerial vehicle deployment, and particularly discloses an unmanned aerial vehicle deployment system applied to cleaning of a large photovoltaic base, which comprises a scheduling platform, a plurality of first unmanned aerial vehicles with a normal cleaning mode, a plurality of second unmanned aerial vehicles with a strong cleaning mode, and a plurality of third unmanned aerial vehicles with a mixed cleaning mode; wherein the scheduling platform specifically comprises an interactive module used for man-machine interaction to obtain the type of the photovoltaic base; a scheduling mode matching module in data communication with the interactive module and used for matching different scheduling modules according to different photovoltaic base types; a first scheduling module used for cleaning photovoltaic panels based on the first photovoltaic base configuration unmanned aerial vehicle; and a second scheduling module used for cleaning photovoltaic panels based on the second photovoltaic base configuration unmanned aerial vehicle. The basic conditions of the photovoltaic panels in the photovoltaic base to be cleaned are obtained through the interactive module, so that corresponding scheduling modules are matched to configure the unmanned aerial vehicles for cleaning.

Description

[0001] Divisional application

[0002] The present application is a divisional application of the Chinese invention patent application filed on January 24, 2025, with the application number 202510114554.2, and the title of "A UAV deployment system applied to cleaning of large-scale photovoltaic base station". TECHNICAL FIELD

[0003] The present application belongs to the technical field of unmanned aerial vehicles, and particularly relates to a UAV deployment system applied to cleaning of large-scale photovoltaic base station. BACKGROUND

[0004] Photovoltaic panels are composed of a series of solar panels in series and parallel connection. Due to the obstruction of dust and other stains, the power generation efficiency of photovoltaic panels will be affected, and even photovoltaic hot spots will be generated, damaging the photovoltaic panel assembly. Nowadays, photovoltaic power stations exist in various forms, such as photovoltaic building integrated type, large-scale photovoltaic power stations in northwest desert areas, etc. The solar panels of these photovoltaic power stations are easily affected by dust, bird droppings, limescale, oil stains and other stains, resulting in a significant decrease in power generation efficiency and causing economic losses. Therefore, cleaning of photovoltaic panels is essential.

[0005] The prior art Chinese patent application CN202210411513.6 discloses a photovoltaic cleaning method combined with a UAV, comprising the following steps: step one, dividing the photovoltaic power station into several areas, each area is allocated a set of cleaning devices; step two, using the UAV to collect images of the photovoltaic panels, using the cloud platform to identify stains and set the cleaning track; step three, using the UAV to release the photovoltaic cleaning robot, and the photovoltaic cleaning robot cleans along the planned path; step four, the UAV finally transports the photovoltaic cleaning robot to the energy storage charging bin.

[0006] The above prior art proposes a specific method of cleaning photovoltaic panels by UAV. However, the cleaning method is relatively fixed and has certain limitations. Due to the installation angle and environment of solar photovoltaic panels, dust is not uniformly distributed. The fixed cleaning method not only consumes more cleaning cost, but also cannot guarantee the cleaning efficiency of solar photovoltaic panels.

[0007] Another prior art Chinese patent application CN202310330164.X discloses a solar photovoltaic panel cleaning operation monitoring and control system, which comprises a photovoltaic panel basic information acquisition module, a photovoltaic panel dust monitoring module, a photovoltaic panel contamination monitoring module, a photovoltaic panel cleaning mode analysis module, a photovoltaic panel cleaning rule analysis module, a photovoltaic panel cleaning control scheme generation module and a cleaning operation information database.

[0008] The prior art monitors the dust concentration and dirt information of each solar photovoltaic panel laid in the designated area, analyzes the cleaning demand, cleaning mode and cleaning rule, and then performs cleaning regulation. However, the above-mentioned prior art does not conduct corresponding research on unmanned aerial vehicle photovoltaic panel cleaning, so that the technical field is still weak. SUMMARY

[0009] The purpose of the present application is to provide an unmanned aerial vehicle deployment system for cleaning large photovoltaic base stations, which partially solves or alleviates the above-mentioned deficiencies in the prior art, and can configure corresponding types of unmanned aerial vehicles for cleaning according to the type of dirt on the photovoltaic panel area.

[0010] In order to solve the above-mentioned technical problems, the present application specifically adopts the following technical solutions:

[0011] An unmanned aerial vehicle deployment system for cleaning large photovoltaic base stations, comprising: a dispatch platform, a plurality of first unmanned aerial vehicles with a normal cleaning mode, a plurality of second unmanned aerial vehicles with a strong cleaning mode, and a plurality of third unmanned aerial vehicles with a mixed cleaning mode, wherein the first unmanned aerial vehicles, the second unmanned aerial vehicles and the third unmanned aerial vehicles are in wireless data communication with the dispatch platform; wherein the dispatch platform specifically comprises:

[0012] An interactive module for human-computer interaction to obtain the type of photovoltaic base station; the type of photovoltaic base station includes a first photovoltaic base station laid in a flat terrain area and a second photovoltaic base station laid in a complex terrain area;

[0013] A dispatch mode matching module in data communication with the interactive module for matching different dispatch modules according to different photovoltaic base types; wherein the dispatch module includes a first dispatch mode suitable for the first photovoltaic base station and a second dispatch module suitable for the second photovoltaic base station;

[0014] A first dispatch module for configuring unmanned aerial vehicles to clean photovoltaic panels based on the first photovoltaic base station;

[0015] A second dispatch module for configuring unmanned aerial vehicles to clean photovoltaic panels based on the second photovoltaic base station.

[0016] As an improvement, the first dispatch module comprises:

[0017] A first area division module for dividing the photovoltaic panels to be cleaned in the first photovoltaic base station into areas;

[0018] The first computing module is configured to calculate the density Pi of each of the three cleaning modes in each region based on the respective cleaning mode of each photovoltaic panel in the first photovoltaic base station; the three cleaning modes include: a normal cleaning mode, a strong cleaning mode and a mixed cleaning mode; the density is the number of photovoltaic panels corresponding to each cleaning mode in the current region; i=1, 2, 3;

[0019] The first configuration module is configured to configure a plurality of first drone groups with the first cleaning mode for any region when the density of the first cleaning mode in the region is greater than a first preset density threshold P0, and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0';

[0020] The first configuration module is configured to configure a plurality of first drone groups with the first cleaning mode for any region when the density of the first cleaning mode in the region is greater than a first preset density threshold P0, and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0';

[0021] The first configuration module is configured to configure a plurality of first drone groups with the first cleaning mode for any region when the density of the first cleaning mode in the region is greater than a first preset density threshold P0, and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0';

[0022] The second cleaning scheduling module I is configured to perform region scanning after completing cleaning to obtain a secondary cleaning target and perform secondary cleaning.

[0023] As an improvement, when the density of the first cleaning mode in any region is greater than a first preset density threshold P0, and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0', and in the case that the first cleaning mode is a normal cleaning mode or a strong cleaning mode, the first configuration module configures the drones with the corresponding cleaning mode to clean, and the remaining part is to be cleaned secondarily.

[0024] When the density of the first cleaning mode in any region is greater than the first preset density threshold P0, the sum of the densities of the remaining two cleaning modes is less than the second preset density threshold P0', and the first cleaning mode is a mixed cleaning mode, the first configuration module configures the unmanned aerial vehicle with the mixed cleaning mode to clean the entire region.

[0025] As an improvement, when the density of the first cleaning mode in any region 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"', and the first cleaning mode and the second cleaning mode are one of the ordinary cleaning mode and the strong cleaning mode, the first configuration module configures the unmanned aerial vehicle with the corresponding cleaning mode to clean; and the remaining part is cleaned by the unmanned aerial vehicle with the ordinary cleaning mode and the unmanned aerial vehicle with the strong cleaning mode respectively.

[0026] When the density of the first cleaning mode in any region 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"', and the first cleaning mode or the second cleaning mode is a mixed cleaning mode, the first configuration module configures the unmanned aerial vehicle with the corresponding cleaning mode to clean; and the remaining part is cleaned again.

[0027] As an improvement, the second scheduling module comprises:

[0028] The second region division module is configured to take a designated first photovoltaic panel as an initial point, divide the first photovoltaic panel and the first photovoltaic panels adjacent to the first photovoltaic panel and having the same cleaning mode into a region if the number of the first photovoltaic panels adjacent to the first photovoltaic panel and having the same cleaning mode reaches a first preset threshold N1, and obtain multiple regions with a single cleaning mode and multiple regions with a mixed cleaning mode; the single cleaning mode is any one of the ordinary cleaning mode and the strong cleaning mode; the mixed cleaning mode includes the ordinary cleaning mode and the strong cleaning mode.

[0029] The second calculation module is configured to calculate the density Pi of the cleaning mode corresponding to the scattered second photovoltaic panels between any designated region and adjacent regions; the density Pi = the number n of any cleaning mode second photovoltaic panels / the sum of the number of the three cleaning mode second photovoltaic panels and N, wherein i = 1, 2, 3.

[0030] The second integration module is configured to divide the scattered second photovoltaic panels between the designated region and adjacent regions into a separate comprehensive region when the second judgment module judges that N is greater than or equal to the second preset threshold N2 and the density Pi of any cleaning mode is greater than or equal to the first preset density threshold p0.

[0031] for when the second judging module judges that N is greater than or equal to a second preset threshold N2, and the density Pi of any cleaning mode is less than the first preset density threshold p0, dividing each of the second photovoltaic panels into the region closest to it according to the cleaning mode thereof;

[0032] for when the second judging module judges that N is less than the second preset threshold N2, dividing all of the second photovoltaic panels into the designated region;

[0033] a second configuration module for configuring a group of drones for each region according to a corresponding cleaning mode;

[0034] a secondary cleaning scheduling module II for scanning the region after completing cleaning to obtain a secondary cleaning target and performing secondary cleaning.

[0035] As an improvement, the scheduling platform further comprises:

[0036] a power judging module for receiving and judging whether the remaining power of any drone feedback reaches a preset power threshold;

[0037] a task allocation module for when the remaining power of any drone reaches a preset power threshold, obtaining a to-be-processed task list of the any drone and judging whether the to-be-processed task list is empty;

[0038] if not empty, obtaining the remaining power and to-be-processed task list of a plurality of other drones near the any drone, judging whether the other drones can add new cleaning tasks according to the remaining power and the number of to-be-processed tasks in the to-be-processed task list of the other drones; if can add, selecting at least one other drone from all other drones that can add a cleaning task number greater than a preset threshold, and evenly distributing the to-be-processed tasks in the to-be-processed task list of the any drone to the selected at least one other drone;

[0039] a return control module for controlling any drone to return to the starting point from the current location.

[0040] As an improvement, the task allocation module further comprises:

[0041] a recommendation sub-module for when at least one other drone is selected, calculating a recommendation index P of each other drone: P=K1*D i，j +K2*T i，j ; wherein, D i，j is the distance between the other drone and the any drone, T i，j is the length of time the other drone needs to wait to perform the newly added task; K1 and K2 are empirical constants;

[0042] The top-priority to-be-processed task in the to-be-processed task is preferentially assigned to the other unmanned aerial vehicle with a small recommendation index.

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

[0044] The unmanned aerial vehicle module is added, which is used for re-assigning a new unmanned aerial vehicle to the region when the number of to-be-processed tasks in the to-be-processed task list of any unmanned aerial vehicle is greater than or equal to the preset to-be-processed quantity threshold.

[0045] As an improvement, the task allocation module further comprises:

[0046] The current task allocation module is used for judging whether the current task is completed when any unmanned aerial vehicle returns to the starting point from the current position, and if not, assigning the current task to the nearest other unmanned aerial vehicle.

[0047] As an improvement, the secondary cleaning scheduling module I and the secondary cleaning scheduling module II both comprise:

[0048] The target calculation module is used for calculating the secondary cleaning target quantity of each region and judging whether the secondary cleaning target quantity is greater than or equal to the addable to-be-processed task quantity of all the unmanned aerial vehicles that can work again in the region.

[0049] The secondary configuration module is used for deploying the unmanned aerial vehicles that are idle and can work again in the adjacent region when the secondary cleaning target quantity is greater than or equal to the addable to-be-processed task quantity of all the unmanned aerial vehicles that can work again in the region.

[0050] When the secondary cleaning target quantity is less than the addable to-be-processed task quantity of all the unmanned aerial vehicles that can work again in the region, each secondary cleaning target in the region is evenly assigned to all the unmanned aerial vehicles that can work again in the region.

[0051] The present application has the advantages that:

[0052] The present application obtains the basic situation of the photovoltaic panel in the to-be-cleaned photovoltaic base through the interaction module, so as to match the corresponding scheduling module for configuring the unmanned aerial vehicle for cleaning. The scheduling module comprises a first scheduling mode suitable for a first photovoltaic base and a second scheduling module suitable for a second photovoltaic base.

[0053] The first scheduling module divides the entire to-be-cleaned region into a plurality of preset regions through a predetermined division rule, and calculates the cleaning density of three cleaning modes in each region. After obtaining the density ratio of the three cleaning modes, the unmanned aerial vehicle is configured in different forms in three cases.

[0054] In the case that 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 the multiple unmanned aerial vehicles with the first cleaning mode are configured. If the first cleaning mode is the ordinary cleaning mode or the intensive cleaning mode, the corresponding unmanned aerial vehicle is configured to clean, and the remaining part is cleaned again. If the first cleaning mode is the mixed cleaning mode, the unmanned aerial vehicle with the mixed cleaning mode is configured to clean the entire area. The unmanned aerial vehicle with the mixed cleaning mode can clean all types of dirt, and since the total amount of ordinary + intensive dirt in the area is small, it is more economical and efficient to directly configure the unmanned aerial vehicle with the mixed cleaning mode to clean.

[0055] In the case that 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''', the unmanned aerial vehicle with the corresponding cleaning mode is configured to clean. If the first cleaning mode and the second cleaning mode are one of the ordinary cleaning mode or the intensive cleaning mode, the corresponding unmanned aerial vehicle is configured to clean. The remaining part can be cleaned by the unmanned aerial vehicle with the ordinary cleaning mode and the unmanned aerial vehicle with the intensive cleaning mode respectively, without the need to separately configure the unmanned aerial vehicle with the mixed cleaning mode to clean. If the first cleaning mode or the second cleaning mode is the mixed cleaning mode, the corresponding unmanned aerial vehicle is configured to clean, and the remaining part is cleaned again.

[0056] In the case that the difference between the densities of the three cleaning modes is less than the preset difference threshold, the unmanned aerial vehicle with the corresponding cleaning mode is configured to clean.

[0057] The second scheduling module integrates the photovoltaic panels with the same cleaning mode and adjacent or indirectly adjacent into one area according to the characteristics of the scattered distribution of the photovoltaic panels in the mountain photovoltaic base station, and configures the unmanned aerial vehicle to clean.

[0058] The scattered photovoltaic panels between the areas are processed according to three cases:

[0059] The scattered photovoltaic panels that reach a certain order of magnitude and have relatively concentrated cleaning modes are integrated into a separate area. For the scattered photovoltaic panels that reach a certain order of magnitude but have dispersed cleaning modes, the surrounding areas are absorbed according to the cleaning modes. For the few scattered photovoltaic panels, they are directly included in a designated area.

[0060] Through the above unmanned aerial vehicle configuration mode, the cleaning efficiency can be greatly improved, and the loss of the unmanned aerial vehicle in the journey can be reduced.

[0061] In addition, the unmanned aerial vehicle can be dispatched according to the power of the unmanned aerial vehicle, and the unmanned aerial vehicle returns when the residual power of the unmanned aerial vehicle reaches a power threshold, thereby avoiding the problem that the unmanned aerial vehicle cannot return due to the low residual power during work caused by the large area of the photovoltaic base station.

[0062] Meanwhile, the present application also finds a replacement for the returning unmanned aerial vehicle to take over the unfinished task, thereby ensuring the execution of the cleaning task. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. In all the drawings, similar elements or parts are generally identified by similar reference signs. In the drawings, each element or part is not necessarily drawn according to the actual proportion. Obviously, the drawings described below are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0064] Figure 1 The present application is a structural schematic diagram. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0066] Herein, the suffix such as "module", "part" or "unit" used to represent an element is only for the convenience of the description of the present application, and has no specific meaning. Therefore, "module", "part" or "unit" can be mixedly used.

[0067] Herein, the terms "upper", "lower", "inner", "outer", "front", "back", "one end", "the other end" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance.

[0068] In this article, unless otherwise explicitly specified and limited, the terms "mount", "provided with", "connected" and the like should be broadly understood, for example, "connected" can be fixedly connected, can be detachably connected, or integrally connected; can be mechanically connected, can be directly connected, can be indirectly connected through an intermediate medium, can be internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0069] In this article, "and / or" includes any and all combinations of one or more listed related items.

[0070] In this article, "multiple" means two or more, that is, it includes two, three, four, five, etc.

[0071] Embodiment one:

[0072] As shown in Figure 1 The present application provides a kind of unmanned aerial vehicle deployment system for large photovoltaic base cleaning, it is applied to the cleaning of photovoltaic panel in photovoltaic base.Photovoltaic base can be built in desert, plain and the like relatively open place of topography, it can also be built in mountainous area and the like relatively rugged complex place of topography.It can be understood that, photovoltaic panel of the photovoltaic base in open topography is relatively concentrated, and compared with desert and plain area, high mountain area is relatively complex due to terrain, so not all terrain is suitable for installing photovoltaic panel, so that photovoltaic panel installation is more scattered.

[0073] The present application aims at cleaning photovoltaic panel in the above two photovoltaic bases efficiently by deployment of unmanned aerial vehicle.The system specifically includes

[0074] scheduling platform, multiple first unmanned aerial vehicles with ordinary cleaning mode, multiple second unmanned aerial vehicles with strong cleaning mode, and multiple third unmanned aerial vehicles with mixed cleaning mode, wherein the first unmanned aerial vehicles, the second unmanned aerial vehicles and the third unmanned aerial vehicles are in wireless data communication with the scheduling platform.

[0075] The dirt of the photovoltaic panel arranged in the photovoltaic base station in the desert and the plain mainly includes dust, water scale, oil stain and bird droppings. The cleaning of dust and water scale is relatively simple, and therefore the cleaning mode of the unmanned aerial vehicle for cleaning dust and water scale in the application is summarized as a general mode (first unmanned aerial vehicle). The cleaning of oil stain and bird droppings is relatively complex, and therefore the cleaning mode of the unmanned aerial vehicle for cleaning oil stain and bird droppings in the application is summarized as a strong mode (second unmanned aerial vehicle). The cleaning agent and the cleaning tool carried by the unmanned aerial vehicle in the two modes are different, so that the two cleaning modes can only be used for the dirt of the own type and cannot cover other dirt. In actual application, the dirt on some photovoltaic panels is not of only one type, and therefore the cleaning mode of the unmanned aerial vehicle in the application further includes a mixed cleaning mode (third unmanned aerial vehicle), which can perform general cleaning and strong cleaning. It can be predicted that the types of the cleaning agent and the cleaning tool carried by the unmanned aerial vehicle in the mixed cleaning mode are more, which can greatly reduce the endurance time of the unmanned aerial vehicle, and therefore the mixed cleaning mode cannot be used as a general mode.

[0076] In the application, the cleaning mode of each photovoltaic panel in the entire cleaning area can be obtained in advance, that is, the dirt type on each photovoltaic panel is matched with the corresponding cleaning mode. The specific method for obtaining the dirt type can refer to the prior art CN202310330164.X in the background art, and will not be described here.

[0077] In the embodiment, the dirt type includes a general type (dust + water scale), a strong type (oil stain + bird droppings) and a mixed type (dust + water scale + oil stain + bird droppings), which are respectively corresponding to the cleaning modes of the unmanned aerial vehicle: general cleaning mode, strong cleaning mode and mixed cleaning mode.

[0078] In addition, it can be predicted that the unmanned aerial vehicle realizes wireless communication with the scheduling platform through a wireless network.

[0079] The scheduling platform is responsible for scheduling the unmanned aerial vehicle, so that the unmanned aerial vehicle can efficiently clean and avoid consuming too much power on the way.

[0080] Specifically, it includes:

[0081] The interactive module is used for human-computer interaction to obtain the type of the photovoltaic base station. The type of the photovoltaic base station includes a first photovoltaic base station arranged in a flat area and a second photovoltaic base station arranged in a complex mountainous area.

[0082] Through the interactive module, human-computer interaction can be performed to obtain the related information of the photovoltaic base station, such as the number, distribution, dirt condition and arrangement of the photovoltaic panel and the terrain.

[0083] The scheduling mode matching module is in data communication with the interaction module and is configured to match different scheduling modules according to different photovoltaic benchmark types; wherein the scheduling module includes a first scheduling mode suitable for a first photovoltaic base station and a second scheduling mode suitable for a second photovoltaic base station.

[0084] After obtaining the basic situation of the photovoltaic base station, the scheduling mode matching module matches a corresponding scheduling module for the photovoltaic base station that needs to be cleaned at present.

[0085] The first scheduling module is configured to clean the photovoltaic panel based on the first photovoltaic base station.

[0086] The first region division module is configured to divide the photovoltaic panel to be cleaned in the first photovoltaic base station into regions.

[0087] Since the area of the region to be cleaned can be extensive, which is not conducive to the deployment of the unmanned aerial vehicle, in the embodiment, the region to be cleaned can be divided into a plurality of preset regions by the first region division module before the unmanned aerial vehicle is arranged for cleaning.

[0088] The rule for dividing the preset region can be to divide the region to be cleaned directly in equal area, or to divide according to the dirt type. In the embodiment, the second division method is preferred.

[0089] In the embodiment, the dirt type includes ordinary type (dust + limescale), strong type (oil stain + bird droppings) and mixed type (dust + limescale + oil stain + bird droppings), which correspond to the cleaning modes of the unmanned aerial vehicle: ordinary cleaning mode, strong cleaning mode and mixed cleaning mode, respectively.

[0090] Of course, it can be understood that even if the region is divided according to the dirt type, the division is a rough division for the sake of simplicity, and it is preferred that there is only one type of dirt in one region, and in fact, there can be multiple types of dirt in some regions.

[0091] The first calculation module is configured to calculate the density Pi of each of the three cleaning modes in each region based on the cleaning mode of each photovoltaic panel in each region 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 region; i = 1, 2, 3.

[0092] After the preset area is divided, the density of each cleaning mode can be calculated according to the density of photovoltaic panels of various types of dirt contained. In short, it is analyzed that 80% of the normal type of dirt, 15% of the strong type of dirt, and 10% of the mixed type of dirt are in a certain preset area, and the corresponding cleaning mode density P1=80%, P2=15%, P3=5%, and so on.

[0093] The first configuration module is configured to configure a plurality of first drones with the first cleaning mode for any area when the density of the first cleaning mode in the area is greater than a first preset density threshold P0, and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0'.

[0094] 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 90% or more, and the sum of the densities of the other modes does not exceed 5% (the remaining 5% does not need to be cleaned), for drones with a cleaning mode density of only 5%, the time for round trips and jumping within the area may be longer than the cleaning time, which is considered to be uneconomical.

[0095] Therefore, in this module, when the density of a certain cleaning mode (for example, the normal cleaning mode) is greater than a first preset density threshold P0 (for example, 90%), and the sum of the densities of the remaining two cleaning modes is less than a second preset density threshold P0' (5%), only drones with the normal cleaning mode are configured to go.

[0096] The mode with a density greater than the preset density threshold P0 can be one of the normal cleaning mode, the strong cleaning mode, and the mixed cleaning mode.

[0097] In the case where the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the first configuration module configures drones with the normal cleaning mode or the strong cleaning mode to clean the 90% corresponding area, and the remaining 5% will be cleaned by drones configured in subsequent secondary cleaning.

[0098] In the case where the first cleaning mode is the mixed cleaning mode, the first configuration module configures drones with the mixed cleaning mode to clean the entire area. Drones with the mixed cleaning mode can clean all types of dirt, and since the total amount of normal + strong type dirt in this area is also less than 5%, directly configuring drones with the mixed cleaning mode to clean is more economical and efficient.

[0099] 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 drone groups with the first cleaning mode and a plurality of second drone groups with the second cleaning mode for the any of the regions; the first cleaning mode is any one of the normal cleaning mode, the intensive 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'.

[0100] When the density of a certain cleaning mode in a certain preset region is too low, it is not economical to configure drones alone. But when the density of a certain dirt reaches a certain threshold, drones of the corresponding type need to be configured for cleaning.

[0101] For example, when the density of the first cleaning mode in a 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''' (for example, 40%), drones with the above two cleaning modes should be configured for targeted cleaning.

[0102] When the first cleaning mode and the second cleaning mode are both one of the normal cleaning mode or the intensive cleaning mode, the first configuration module configures the corresponding drones for cleaning. The remaining 10% (of course, it can be less than 10% because some photovoltaic panels do not need to be cleaned) can be cleaned by drones with the normal cleaning mode and drones with the intensive cleaning mode respectively, without the need to separately configure drones with the mixed cleaning mode for cleaning.

[0103] When the first cleaning mode or the second cleaning mode is the mixed cleaning mode, the first configuration module configures the corresponding drones for cleaning. The remaining 10% (which can be the normal cleaning mode or the intensive cleaning mode) can be cleaned by the corresponding drones in subsequent secondary cleaning.

[0104] The first configuration module is further configured to, when the first judgment module determines that the difference between the densities of the three cleaning modes in any of the regions is less than a preset difference threshold AP, configure a plurality of drone groups with the normal cleaning mode, a plurality of drone groups with the intensive cleaning mode and a plurality of drone groups with the mixed cleaning mode for the any of the regions respectively.

[0105] It can be foreseen that if the density of the three types of dirt is too close, it is not economical to clean the mixed dirt by replacing the cleaning mode (i.e. using a drone with a normal cleaning mode and a drone with a strong cleaning mode to clean the mixed dirt, or using a drone with a composite cleaning mode to clean the normal dirt or the strong dirt).

[0106] Therefore, when the difference between the densities of the three cleaning modes is less than a preset difference threshold (for example, 10%), the first configuration module directly configures the corresponding drone to clean.

[0107] The secondary cleaning scheduling module I is used to scan the area after cleaning to obtain a secondary cleaning target and perform secondary cleaning.

[0108] For economy, it is possible that some areas are not cleaned. After the entire area to be cleaned has undergone a cleaning, the areas that are not cleaned are re-divided and cleaned again according to the above scheme until all the photovoltaic panels are cleaned.

[0109] In addition, in some other embodiments, the secondary cleaning module I (the subsequent secondary cleaning module II is the same) includes:

[0110] The target calculation module is used to calculate the number of secondary cleaning targets of each area and determine whether the number of secondary cleaning targets is greater than or equal to the amount of addable to-be-processed tasks of all the drones that can work again in the area.

[0111] In the secondary cleaning, the remaining uncleaned areas after the first cleaning are re-divided. The division rule is still according to the dirt type.

[0112] After the secondary division of the area, there can be drones in the area that are still performing the task of the last cleaning. Therefore, it can be first determined whether the drones in the area can meet the cleaning this time.

[0113] The secondary configuration module is used to deploy the drones that are idle and can work again in the adjacent area when the number of secondary cleaning targets is greater than or equal to the amount of addable to-be-processed tasks of all the drones that can work again in the area.

[0114] In the case that the drones in the area cannot meet the secondary cleaning of the area, the drones that can still perform tasks are deployed from the adjacent area to clean. It can be foreseen that if the task lists of the drones in the adjacent area are all saturated, the drones need to be reconfigured.

[0115] The adjacent area can be an area that borders the target area, or an area that is less than a distance threshold away from the target area.

[0116] The secondary configuration module is further configured to evenly distribute each of the secondary cleaning targets in the region to all the reworkable UAVs in the region when the secondary cleaning target quantity is less than the addable to-be-processed task quantity of all the reworkable UAVs in the region.

[0117] In the case that the UAVs in the region have been able to meet the demand, the secondary cleaning tasks can be evenly distributed.

[0118] The second scheduling module in the embodiment is configured to configure the UAVs to clean the photovoltaic panels based on the second photovoltaic base station. Specifically, the second scheduling module comprises the following steps:

[0119] The second region division module is configured to take a designated first photovoltaic panel as an initial point, divide the first photovoltaic panel and the first photovoltaic panels adjacent to the first photovoltaic panel and having the same cleaning mode into a region if the number of the first photovoltaic panels adjacent to the first photovoltaic panel and having the same cleaning mode reaches a first preset threshold N1, and obtain multiple regions with a single cleaning mode and multiple regions with 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 the normal cleaning mode and the strong cleaning mode.

[0120] The function of the module is to divide the preset cleaning region so as to better arrange the UAVs to clean. In view of the feature that the photovoltaic panels in the mountainous region are relatively scattered (of course, the cleaning modes of the photovoltaic panels in adjacent regions are generally roughly the same), the photovoltaic panels of the same type and close to each other need to be "clustered" first, specifically, taking a designated photovoltaic panel as the center, the photovoltaic panels of the same type adjacent to the photovoltaic panel (including indirectly adjacent) are divided into the same preset cleaning region. Of course, the number of the photovoltaic panels in a cleaning region should not be too small, therefore, the first preset threshold N1 is set in the embodiment, that is, the photovoltaic panels of the same type need to reach the first preset threshold N1 to be a preset region. The purpose is to prevent the preset cleaning region from being too scattered.

[0121] The second calculation module is configured to calculate the density Pi of the cleaning mode of the scattered multiple second photovoltaic panels between any designated region and the adjacent region; the density Pi = the number n of the second photovoltaic panels of any cleaning mode / the sum of the number of the second photovoltaic panels of the three cleaning modes and N, wherein i = 1, 2, 3.

[0122] The module can calculate the density of various cleaning modes according to the density of various types of contaminated photovoltaic panels. Simply speaking, it is analyzed that 80% of the photovoltaic panels in a preset region are of the normal type, 15% of the photovoltaic panels are of the strong type, and 10% of the photovoltaic panels are of the mixed type, and the corresponding cleaning mode densities are P1 = 80%, P2 = 15%, and P3 = 5%, and so on.

[0123] The second integration module is configured to integrate the scattered photovoltaic panels.

[0124] The second region division module is configured to integrate photovoltaic panels of the same type into a preset cleaning region. After the integration in this step, some scattered photovoltaic panels (second photovoltaic panels) are still not included in the preset cleaning region. Therefore, the second integration module is configured to integrate the scattered photovoltaic panels, which includes three cases:

[0125] 1. form a new cleaning region; 2. be included in the surrounding cleaning regions respectively; and 3. be included in a preset cleaning region.

[0126] First, an arbitrary region is specified in the already divided regions, and the scattered photovoltaic panels between the specified region and its adjacent regions are divided.

[0127] Suppose the number of the scattered photovoltaic panels is N.

[0128] The second integration module is configured to divide the scattered second photovoltaic panels between the specified region and its adjacent regions into a single comprehensive region when the second judgment module determines that N is greater than or equal to a second preset threshold N2, and the density Pi of any cleaning mode is greater than or equal to a first preset density threshold p0.

[0129] That is, when the number of the scattered photovoltaic panels is greater than or equal to N2 (for example, 500), and the density of any cleaning mode is greater than Pd (70%), the scattered photovoltaic panels can form a region independently. That is, the types of the scattered photovoltaic panels are relatively concentrated when the number of the scattered photovoltaic panels meets a certain requirement.

[0130] The second integration module is also configured to divide each second photovoltaic panel into the nearest region according to the cleaning mode of the second photovoltaic panel 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 cleaning mode is less than the first preset density threshold p0.

[0131] That is, when the number of the scattered photovoltaic panels is greater than or equal to N2 (for example, 500), but the density of all cleaning types is lower than Pd (70%), it indicates that the types of the scattered photovoltaic panels are relatively mixed, and it is not suitable to form a region independently. At this time, the scattered photovoltaic panels can be integrated into the surrounding regions according to the types.

[0132] The second integration module is also configured to divide all the second photovoltaic panels into the specified region when the second judgment module determines that N is less than the second preset threshold N2.

[0133] In other words, if the number of scattered photovoltaic panels is greater than N2 (e.g., 500), it means that the scattered photovoltaic panels are small in size and can be directly included in the designated area. Of course, a better approach is to include the corresponding area according to the cleaning mode with the highest density.

[0134] The second configuration module is used to configure a drone group with a corresponding cleaning mode for each area.

[0135] The function of this module is to configure drones in the areas divided by the second area division module. It can be understood that for areas with a single cleaning mode, it is sufficient to directly configure drones with the corresponding cleaning mode for cleaning. For some composite areas (i.e., areas that include multiple cleaning modes), this module also provides corresponding configuration strategies. The composite area mainly refers to the situation where multiple second photovoltaic panels are divided into a single area. Of course, this method can also be applied to other areas that incorporate photovoltaic panels with other cleaning modes. The specific method of configuring drones in this module can be found in the first configuration module and will not be repeated here.

[0136] Different from the first configuration module, when multiple second photovoltaic panels are divided into the designated area, the second configuration module configures a drone with a mixed cleaning mode to clean the entire designated area when the cleaning mode of the designated area is a mixed cleaning mode.

[0137] When scattered photovoltaic panels (secondary photovoltaic panels) are assigned to a designated area, they may bring together panels with different cleaning modes. Since the number of scattered photovoltaic panels is small, the area they are added to is already a mixed cleaning area. In this case, a drone with mixed cleaning mode can directly clean all photovoltaic panels in the entire area.

[0138] The second configuration module also configures a drone with a corresponding cleaning mode to clean the designated area when the cleaning mode is a normal cleaning mode or a strong cleaning mode, and the remaining area is to be cleaned a second time.

[0139] If the original area is not a photovoltaic panel in mixed cleaning mode, then the corresponding drone can be configured according to the original cleaning mode to clean the photovoltaic panels in that cleaning mode, and the remaining uncleaned photovoltaic panels will wait for secondary cleaning.

[0140] When scattered photovoltaic panels are incorporated into the surrounding area according to their own cleaning mode, they only need to be configured according to the original surrounding cleaning mode.

[0141] The secondary cleaning scheduling module II is used to scan the area after cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning.

[0142] Similar to the secondary cleaning scheduling module I, after the cleaning in the previous step, there will still be some scattered photovoltaic panels that are not cleaned, so it is necessary to perform regional scanning to obtain the location of the uncleaned photovoltaic panels and organize drones for secondary cleaning.

[0143] In addition, the scheduling platform also includes:

[0144] The battery level determination module is used to receive and determine whether the remaining battery level reported by any drone has reached a preset battery level threshold.

[0145] Generally speaking, photovoltaic base stations are relatively large, and cleaning work consumes a lot of power from drones, so it is necessary to always pay attention to the power of the drone to avoid being unable to return.

[0146] This module monitors the remaining battery power of the drone in real time to determine whether the drone has enough power to return home.

[0147] The task allocation module is used to obtain a pending task list of any UAV when the remaining power of the UAV reaches a preset power threshold, and determine whether the pending task list is empty;

[0148] If it is not empty, obtain the remaining power and pending task lists of multiple other drones near any one of the drones, and determine whether the other drones can add new cleaning tasks based on the remaining power of the other drones nearby and the number of pending tasks in the pending task lists; if they 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 one of the drones to the selected at least one other drone.

[0149] When the drone reaches the preset power level, it may still be performing a mission or have other missions to perform. In this case, it is necessary to find a successor to the mission.

[0150] When a drone that is currently performing a mission or has tasks to complete reaches a preset battery level, it needs to find a replacement. Therefore, a search is performed with the drone's current location as the center and a preset radius to find neighboring drones. The remaining battery level and pending mission list of the neighboring drones are then obtained.

[0151] When looking for a replacement for a task, it is necessary to determine whether the drone has sufficient power to support the subsequent tasks and the newly added tasks, so as to determine whether the drone is suitable for adding the new task. It is easy to understand that drones with sufficient power and fewer tasks are preferred.

[0152] In addition to determining whether the UAV can add a new task, the distance between the two and the waiting time also need to be considered. Therefore, in this embodiment, the task allocation module further comprises a recommendation submodule, when at least one other UAV is screened out, the recommendation index P of each other UAV is calculated: P = K1 * D + K2 * T; wherein, D is the distance between the other UAV and the any UAV, T is the time required for the other UAV to wait to perform the newly added task; K1 and K2 are empirical constants. i，j i，j i，j i，j

[0153] The top-priority to-be-processed task in the to-be-processed task list is preferentially allocated to the other UAV with a small recommendation index.

[0154] When the UAV reaches the power threshold, it can still be performing a current task, therefore, the task allocation module further comprises a current task allocation module, which is configured to determine whether the current task is completed when the any UAV returns to the starting point from the current position, and if not, allocate the current task to the nearest other UAV.

[0155] In addition, the task allocation module further comprises a new UAV module, which is configured to dispatch a new UAV for the region when the number of to-be-processed tasks in the to-be-processed task list of the any UAV is greater than or equal to a preset to-be-processed threshold.

[0156] When the number of to-be-processed tasks in the to-be-processed task list of a UAV is greater than or equal to the preset to-be-processed threshold, it indicates that the task of the UAV is saturated and cannot accept new tasks. When all UAVs are saturated, a new UAV needs to be added.

[0157] The return control module is configured to control the any UAV to return to the starting point from the current position.

[0158] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0159] ​​​​Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, also can be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application essentially or say the part of contribution to the prior art can be embodied in the form of software product, the computer software product is stored in a storage medium (such as ROM / RAM, disk, optical disk), including a plurality of instructions to make a computer terminal (may be a mobile phone, computer, server, or network equipment, etc.) executes the method described in various embodiments of the present application.

[0160] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, the above-mentioned specific embodiments are only illustrative, but not limited, those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which all belong to the protection of the present application.

Claims

1. A drone deployment system for cleaning large photovoltaic base stations, characterized in that: include: A scheduling platform, a plurality of first drones having a normal cleaning mode, a plurality of second drones having a strong cleaning mode, and a plurality of third drones having 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 interactive module, configured to perform human-computer interaction to obtain a type of photovoltaic base station; the type of photovoltaic base station includes a first photovoltaic base station located in a flat area and a second photovoltaic base station located in a mountainous area with complex terrain; A scheduling mode matching module, communicating data with the interaction module, for matching 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 panels based on the first photovoltaic base station; A second scheduling module is used to configure a drone to clean the photovoltaic panels based on the second photovoltaic base station; The first scheduling module includes: A first area division module is used to divide the area to be cleaned in the first photovoltaic base station into equal areas to obtain a plurality of areas to be cleaned; A first calculation module is configured to calculate, based on the cleaning mode of each photovoltaic panel in each area of ​​the first photovoltaic base station, the density Pi of each of the three cleaning modes in each area; the three cleaning modes include: normal 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; a first configuration module, configured to, when the density of the mixed cleaning mode in any area is greater than 90% and the sum of the densities of the other two cleaning modes is less than 5%, configure a plurality of third drone groups with the mixed cleaning mode for the any area; and, when the density of the mixed cleaning mode in any area is greater than 50% and the density of the second cleaning mode is greater than 40%, configure a plurality of first drone groups with the mixed cleaning mode and a plurality of second drone groups with the second cleaning mode for the any area; the second cleaning mode is any one of the normal cleaning mode and the strong cleaning mode; and, when the first judgment module determines that the difference between the densities of the three cleaning modes in any area is less than 10%, configure a plurality of drone groups with the normal cleaning mode, a plurality of drone groups with the strong cleaning mode, and a plurality of drone groups with the mixed cleaning mode, respectively, for the any area; Secondary cleaning scheduling module I is used to scan the area after cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning; When the density of the mixed cleaning mode in any area is greater than 90% and the sum of the densities of the other two cleaning modes is less than 5%, the first configuration module configures the drone with the mixed cleaning mode to clean the entire area; When the density of the mixed cleaning mode in any of the areas is greater than 50% and the density of the second cleaning mode is greater than 40%, and the second cleaning mode is the mixed cleaning mode, the first configuration module configures a third drone with the mixed cleaning mode to perform cleaning; and the remaining area is to be cleaned a second time; Specifically, the secondary cleaning scheduling module 1 includes: A target calculation module is used to re-divide the uncleaned area into regions according to the type of dirt, calculate the number of secondary cleaning targets in each region, and determine whether the number of secondary cleaning targets is greater than or equal to the number of tasks that can be added to the processing of all drones that can work again in the region; A secondary configuration module is configured to deploy idle and reusable drones in adjacent areas when the number of secondary cleaning targets is greater than or equal to the number of tasks that can be added to the task list of all reusable drones in the area; and to reconfigure the corresponding drones when the task list of drones in the adjacent area is saturated; 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 configured to divide the photovoltaic panels in the area to be cleaned in the second photovoltaic base station into areas according to the type of contamination; the contamination types include ordinary, strong, and mixed types; specifically, taking a designated first photovoltaic panel as the starting point, if the number of adjacent first photovoltaic panels with the same cleaning mode reaches a first preset threshold value N1, the first photovoltaic panel and the adjacent first photovoltaic panels with the same cleaning mode are divided into one area, thereby obtaining multiple areas of a single cleaning mode and multiple areas of a mixed cleaning mode; the single cleaning mode is any one of an ordinary cleaning mode and a strong cleaning mode; the mixed cleaning mode includes an ordinary 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 plurality of scattered second photovoltaic panels in any designated 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; a second integration module, configured to divide each of 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 70%; for dividing each second photovoltaic panel into a region closest to it according to its cleaning mode 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 less than 70%; configured 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; A second configuration module is configured to configure a drone group with a corresponding cleaning mode for each area; when a plurality of the second photovoltaic panels are divided into the designated area, if the cleaning mode of the designated area is a mixed cleaning mode, configure a drone with the mixed cleaning mode to clean the designated area; if the cleaning mode of the designated area is a normal cleaning mode or a strong cleaning mode, assign a drone with the corresponding cleaning mode to the designated area, and perform secondary cleaning on the remaining area; Secondary cleaning scheduling module II is used to scan the area after cleaning is completed, obtain the target to be secondary cleaned, and perform secondary cleaning; Wherein, the secondary cleaning scheduling module II includes: A target calculation module is used to re-divide the uncleaned area into regions according to the type of dirt, calculate the number of secondary cleaning targets in each region, and determine whether the number of secondary cleaning targets is greater than or equal to the number of tasks that can be added to the processing of all drones that can work again in the region; The secondary configuration module is used 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; and to reconfigure the corresponding drones when the task list of the drones in the adjacent area is saturated; when the number of secondary cleaning targets is less than the amount of tasks that can be added to be processed by all reusable drones in the area, evenly distribute the various secondary cleaning targets in the area to all reusable drones in the area.

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 battery level determination module is used to receive and determine whether the remaining battery level of any drone has reached a preset battery level threshold; The task allocation module is used to obtain a pending task list of any UAV when the remaining power of the UAV reaches a preset power threshold, and determine whether the pending task list is empty; If it is not empty, obtaining the remaining power and pending task lists of multiple other drones near the said any drone, and judging whether the other drone can add new cleaning tasks based on the remaining power of the other drones and the number of pending tasks in the pending task lists; if it can be added, selecting 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 distributing the pending tasks in the pending task lists of the said any drone to the at least one selected other drone; The return control module is used to control any drone to return to its starting point from its current location.

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 UAVs to execute the newly added task; K1 and K2 are empirical constants; Among the pending tasks, the tasks that are ranked higher in the pending tasks are preferentially assigned to other UAVs 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 new drone module is added, which 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 the 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 assignment module is used to determine whether the current task is completed when any UAV returns to the starting point from the current position; if not, the current task is assigned to the nearest other UAV.

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, configured 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 number of tasks that can be added to be processed by all reusable drones in the area; A secondary configuration module is 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.

Images