Unmanned aerial vehicle deploying system applied to cleaning of large photovoltaic base station

Abstract

The invention 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 station, which comprises a scheduling platform, a plurality of first unmanned aerial vehicles with a common cleaning mode, a plurality of second unmanned aerial vehicles with a powerful cleaning mode, and a plurality of third unmanned aerial vehicles with a mixed cleaning mode, the scheduling platform specifically comprises an interaction module used for carrying out man-machine interaction so as to obtain the type of the photovoltaic base station; the scheduling mode matching module is in data communication with the interaction module and is used for matching different scheduling modules according to different photovoltaic reference types; the first scheduling module is used for configuring the unmanned aerial vehicle to clean the photovoltaic panel based on the first photovoltaic base station; and the second scheduling module is used for configuring the unmanned aerial vehicle to clean the photovoltaic panel based on the second photovoltaic base station. According to the invention, the basic condition of the photovoltaic panel in the photovoltaic base station to be cleaned is obtained through the interaction module, so that the corresponding scheduling module is matched for the photovoltaic panel to be cleaned for configuring the unmanned aerial vehicle for cleaning.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a unmanned aerial vehicle deployment system used for cleaning large photovoltaic base stations. Background Art

[0002] Photovoltaic panels are composed of a series of solar panels connected in series and parallel. 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 photovoltaic panel components. Nowadays, photovoltaic power stations exist in various forms, such as photovoltaic building integrated type, large photovoltaic power stations in the northwest desert area, etc. The solar panels of these photovoltaic power stations are easily affected by dust, bird droppings, scale, oil stains and other stains, which greatly reduce the power generation efficiency and cause economic losses. Therefore, cleaning of photovoltaic panels is essential.

[0003] Prior art Chinese patent application CN202210411513.6 discloses a photovoltaic cleaning method combined with a drone, comprising the following steps: Step 1, dividing the photovoltaic power station into several areas, each area is assigned a set of cleaning devices; Step 2, using the drone to capture images of the photovoltaic panels, using the cloud platform to identify stains and set the cleaning trajectory; Step 3, using the drone to deploy the photovoltaic cleaning robot, and the photovoltaic cleaning robot cleans along the planned path; Step 4, the drone finally transports the photovoltaic cleaning robot to the energy storage charging warehouse.

[0004] The above-mentioned prior art proposes a specific method of cleaning photovoltaic panels by drones. However, the cleaning method is relatively fixed and has certain limitations. Due to the installation angle and environmental issues of solar photovoltaic panels, dust is not evenly distributed. The fixed cleaning method not only consumes 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 control system, which includes 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 library; The above-mentioned prior art monitors the dust concentration and dirt information of each solar photovoltaic panel laid in a specified area, thereby analyzing the cleaning needs, cleaning mode and cleaning rules, and then performing cleaning control. However, the above-mentioned prior art does not conduct corresponding research on drone photovoltaic panel cleaning, making this technical field still relatively weak. Summary of the invention

[0006] The purpose of the present invention is to provide a drone 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 drones for cleaning according to the type of contamination in the photovoltaic panel area.

[0007] In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions: A drone dispatching system for cleaning a large photovoltaic base station includes: a dispatching 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 drone, the second drone, and the third drone all communicate wirelessly with the dispatching platform; wherein the dispatching 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 benchmark types; 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; A first scheduling module is used to configure a drone to clean the photovoltaic panel based on the first photovoltaic base station; The second scheduling module is used to configure the drone to clean the photovoltaic panels based on the second photovoltaic base station.

[0008] As an improvement, 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 number of photovoltaic panels corresponding to each cleaning mode in the current area; i=1, 2, 3; A first configuration module, configured to configure a plurality of first drone groups having 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'; 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''', a plurality of first unmanned aerial vehicle groups having the first cleaning mode and a plurality of second unmanned aerial vehicle groups having the second cleaning mode are configured for the any area; the first cleaning mode is any one of the ordinary 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 value P0'' is less than the first preset density threshold value P0, and the fourth preset density threshold value P0''' is greater than the second preset density threshold value P0'; When the first judgment module determines that the difference between the densities of the three cleaning modes in any area is less than a preset difference threshold ΔP, a plurality of drone groups with a normal cleaning mode, a plurality of drone groups with a strong cleaning mode, and a plurality of drone groups with a mixed cleaning mode are respectively configured for the 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.

[0009] As an improvement, 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 P0, and the sum of the densities of the other 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 drone with the mixed cleaning mode to clean the entire area.

[0010] As an improvement, 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 P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold P0'', when 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 for cleaning; and the remaining part is to be cleaned a second time.

[0011] As an improvement, 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 scattered second photovoltaic panels 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.

[0012] As an improvement, the scheduling platform further 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.

[0013] As an improvement, the task allocation module further 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 execute the newly added task; 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.

[0014] As an improvement, the task allocation module further includes: A new drone module is added, which 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.

[0015] As an improvement, the task allocation module further 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.

[0016] As an improvement, the secondary cleaning scheduling module I and the secondary cleaning scheduling module II both include: 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.

[0017] The present invention is beneficial in that: The present invention obtains the basic information of the photovoltaic panels in the photovoltaic base station to be cleaned through the interactive module, so as to match the corresponding scheduling module for configuring the drone for cleaning. 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.

[0018] 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 performed in three situations.

[0019] When the density of the first cleaning mode 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', only multiple drones with the first cleaning mode are configured. If the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the corresponding drone is configured for cleaning, and the remaining part is to be cleaned a second time. If the first cleaning mode is a mixed cleaning mode, a drone with a mixed cleaning mode is configured to clean the entire area. A drone with a mixed cleaning mode can clean all types of dirt. Since the total amount of normal + strong dirt in the area is small, it is more economical and efficient to directly configure a drone with a mixed cleaning mode for cleaning.

[0020] When the density of the first cleaning mode 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''', configure the drone of the corresponding cleaning mode for cleaning. If the first cleaning mode and the second cleaning mode are both one of the ordinary cleaning mode and the strong cleaning mode, configure the corresponding drone for cleaning. The remaining part can be cleaned separately by a drone with an ordinary cleaning mode and a drone with a strong cleaning mode, without the need to separately configure a drone with a mixed cleaning mode for cleaning. If the first cleaning mode or the second cleaning mode is a mixed cleaning mode, configure the corresponding drone for cleaning, and the remaining part is subject to secondary cleaning.

[0021] When the difference between the densities of the three cleaning modes is less than the preset difference threshold, the drone of the corresponding cleaning mode can be configured to perform cleaning.

[0022] The second scheduling module takes advantage of the scattered distribution of photovoltaic panels in mountain photovoltaic base stations. It integrates adjacent or indirectly adjacent photovoltaic panels with the same cleaning mode into one area through a method similar to "clustering" and coordinates the deployment of drones for cleaning.

[0023] For scattered photovoltaic panels between regions, the present invention handles them separately according to three situations: Scattered photovoltaic panels that have reached a certain level and have relatively concentrated cleaning patterns will be integrated into a single area. For scattered photovoltaic panels that have reached a certain level but have relatively scattered cleaning patterns, they will be absorbed by the surrounding areas according to the cleaning pattern. For scattered photovoltaic panels with a small number, they will be directly included in a designated area.

[0024] Through the above-mentioned drone configuration method, the cleaning efficiency can be greatly improved and the loss of the drone during the journey can be reduced.

[0025] In addition, the present invention can also adjust the drones according to their power. When the remaining power of a drone reaches a power threshold, the drone is allowed to return, thereby avoiding the problem that the drone cannot return due to low remaining power during work due to the large distance between photovoltaic base stations.

[0026] At the same time, the present invention also searches for a successor for the returning drone to take over its unfinished task and ensure the execution of the cleaning task. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without paying creative labor.

[0028] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Herein, suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings by themselves. Therefore, "module", "component" or "unit" can be used mixedly.

[0031] In this document, the terms "upper", "lower", "inner", "outer", "front", "back", "one end", "the other end" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0032] In this document, unless otherwise clearly specified and limited, the terms "installed", "provided with", "connected", etc. should be understood in a broad sense. For example, "connected" 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, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0033] Herein "and / or" includes any and all combinations of one or more of the associated listed items.

[0034] Herein, "plurality" means two or more than two, ie, it includes two, three, four, five, etc.

[0035] Embodiment 1: like Figure 1 As shown, the present invention provides a drone deployment system for cleaning large photovoltaic base stations, which is used for cleaning photovoltaic panels in photovoltaic base stations. Photovoltaic base stations can be built in open areas such as deserts and plains, or in areas with rugged and complex terrain such as mountains. It can be understood that photovoltaic panels of photovoltaic base stations located in open terrain are arranged more concentratedly, and compared with plain areas such as deserts, mountainous areas have more complex terrain, so not all terrains are suitable for installing photovoltaic panels, making the installation of photovoltaic panels more scattered.

[0036] The present invention aims to efficiently clean the photovoltaic panels in the above two photovoltaic base stations by deploying drones. The system specifically includes 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 perform wireless data communication with the scheduling platform.

[0037] The photovoltaic panels in the photovoltaic base stations arranged in the deserts and plains are mainly contaminated by dust, scale, oil, bird droppings, etc. Among them, the cleaning of dust and scale is relatively simple, so in the present invention, the cleaning mode of the drone for cleaning dust and scale is summarized as the normal mode (first drone). The cleaning of oil and bird droppings is more complicated, so in the present invention, the cleaning mode of the drone for cleaning oil and bird droppings is summarized as the strong mode (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 dirt and cannot cover other dirt. In practice, the dirt on some photovoltaic panels is not only of one type, so the cleaning mode of the drone in the present invention also includes a mixed cleaning mode (third drone), which can perform both ordinary cleaning and strong cleaning. Of course, it is foreseeable that the drone carries more types of cleaning agents and cleaning tools in the mixed cleaning mode, which will greatly reduce the drone's flight time, so it cannot be used as a regular mode.

[0038] 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 by the type of dirt on each photovoltaic panel. The specific method of obtaining the dirt type can refer to the prior art CN202310330164.X in the background technology, which will not be repeated here.

[0039] In this embodiment, the types of dirt include ordinary type (dust + scale), strong type (oil + bird droppings) and mixed type (dust + scale + oil + bird droppings), which correspond to the cleaning modes of the drone: ordinary cleaning mode, strong cleaning mode and mixed cleaning mode.

[0040] In addition, it is foreseeable that the drone can achieve wireless communication with the dispatching platform through a wireless network.

[0041] The dispatching platform is responsible for dispatching the drones so that they can clean efficiently and avoid consuming too much power on the way.

[0042] Specifically include: The interaction module is used for 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.

[0043] The interactive module enables human-computer interaction to obtain relevant information about the photovoltaic base station, such as the number, distribution, contamination and layout of photovoltaic panels.

[0044] The scheduling mode matching module performs data communication with the interaction module and is used to match different scheduling modules according to different photovoltaic benchmark types; wherein the scheduling module includes a first scheduling mode applicable to the first photovoltaic base station and a second scheduling module adapted to the second photovoltaic base station.

[0045] After obtaining the basic information of the photovoltaic base station, the scheduling mode matching module matches the corresponding scheduling module for the photovoltaic base station that currently needs to be cleaned.

[0046] The first scheduling module is used to configure the drone to clean the photovoltaic panel based on the first photovoltaic base station; it specifically includes: The first area division module is used to divide the photovoltaic panels to be cleaned in the first photovoltaic base station into areas.

[0047] Since the area to be cleaned may be relatively large, which is not conducive to the deployment of drones, in this embodiment, the area to be cleaned may be divided into several preset areas by a first area division module and then drones may be arranged for cleaning.

[0048] The rule for dividing the preset areas can be to directly divide the area to be cleaned into equal areas, or to divide it according to the type of dirt. In this embodiment, the second division method is more preferred.

[0049] In this embodiment, the types of dirt include ordinary type (dust + scale), strong type (oil + bird droppings) and mixed type (dust + scale + oil + bird droppings), which correspond to the cleaning modes of the drone: ordinary cleaning mode, strong cleaning mode and mixed cleaning mode.

[0050] Of course, it is understandable that even if the division is based on the type of filth, for the sake of simplicity, the regional division is also a rough division, and try to have only one type of filth in one area, but in reality there will still be multiple types of filth in some areas.

[0051] 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: 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.

[0052] After the preset areas are divided, the density of various cleaning modes can be calculated according to the density of the photovoltaic panels with various types of pollution. Simply put, if it is analyzed that there are 80% ordinary pollution, 15% strong pollution and 10% mixed pollution in a preset area, the density of the corresponding cleaning mode is P1=80%, P2=15%, P3=5%, and so on.

[0053] The first configuration module is used to configure a plurality of first drone groups having 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'.

[0054] The first calculation module calculates the density of each cleaning mode in a preset area. However, it is unreasonable to match drones completely according to density in some cases. For example, when the density of a cleaning mode is as high as 90% or more, and the density of other modes combined does not exceed 5% (the remaining 5% does not need to be cleaned), for drones with a cleaning mode density of only 5%, the round-trip time and the time to jump within the area may be longer than the cleaning time, which is considered uneconomical.

[0055] Therefore, in this module, when the density of a certain cleaning mode (such as the normal 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 drone with the normal cleaning mode is configured to go there.

[0056] The mode with a density greater than the preset density threshold P0 may be one of the normal cleaning mode, the strong cleaning mode and the mixed cleaning mode.

[0057] When the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the first configuration module configures the drone with the normal cleaning mode or the strong cleaning mode to clean 90% of the corresponding area, and the remaining 5% will be cleaned by the drone in the subsequent secondary cleaning.

[0058] When the first cleaning mode is the mixed cleaning mode, the first configuration module configures the drone with the mixed cleaning mode to clean the entire area. The drone with the mixed cleaning mode can clean all types of dirt. Since the total amount of ordinary + strong dirt in the area is also less than 5%, it is more economical and efficient to directly configure the drone with the mixed cleaning mode for cleaning.

[0059] The first configuration module is also used 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 P0'', and the density of the second cleaning mode is greater than a fourth preset density threshold P0''; 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'.

[0060] If the density of a certain cleaning mode in a preset area is too small, it is not economical to deploy a drone alone. However, when the density of a certain type of dirt reaches a certain threshold, it is necessary to deploy a corresponding type of drone for cleaning.

[0061] For example, if the density of the first cleaning mode in a certain area is greater than the third preset density threshold value P0'' (50%), and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''' (for example, 40%), then a drone with the above two cleaning modes should be configured for targeted cleaning.

[0062] In the case where the first cleaning mode and the second cleaning mode are both one of the normal cleaning mode and the strong cleaning mode, the first configuration module configures the corresponding drone to perform cleaning. The remaining 10% (of course, it may be less than 10% because some photovoltaic panels do not need to be cleaned) can be cleaned by drones with normal cleaning mode and drones with strong cleaning mode respectively, without the need to configure a drone with mixed cleaning mode to clean separately.

[0063] When the first cleaning mode or the second cleaning mode is a mixed cleaning mode, the first configuration module configures the corresponding drone for cleaning, and the remaining 10% (which may be a normal cleaning mode or a strong cleaning mode) can be configured with a corresponding drone for cleaning in the subsequent secondary cleaning.

[0064] The first configuration module is also used to configure a plurality of drone groups with a normal cleaning mode, a plurality of drone groups with a strong cleaning mode, and a plurality of drone groups with a mixed cleaning mode for the any area when the first judgment module determines that the difference between the densities of the three cleaning modes in any area is less than a preset difference threshold △P.

[0065] It is foreseeable that if the density difference between the three modes is too small, it will be uneconomical to use alternative cleaning methods (i.e., using a drone with a normal cleaning mode and a drone with a strong cleaning mode to clean mixed dirt, or using a drone with a compound cleaning mode to clean normal dirt or strong dirt).

[0066] 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 for cleaning.

[0067] 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.

[0068] For the sake of economy, some areas may not be cleaned. After the entire area to be cleaned has been cleaned once, the uncleaned areas will be re-divided and cleaned again according to the above plan until all photovoltaic panels are cleaned.

[0069] In addition, in some other embodiments, the secondary cleaning module I (the subsequent secondary cleaning module II is the same) includes: The 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.

[0070] During the second cleaning, the remaining uncleaned areas after the first cleaning are integrated and re-divided. The division rules are still divided according to the type of dirt.

[0071] After the second area division, there may be drones in the area that are still performing the previous cleaning task. Therefore, it is possible to first determine whether the drones in the area can meet the current cleaning requirements.

[0072] The secondary configuration module is used to deploy idle and reusable drones in adjacent areas when the number of the 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.

[0073] If the drones in an area are unable to meet the secondary cleaning needs of the area, drones that can still perform tasks will be deployed from adjacent areas for cleaning. It is foreseeable that if the task lists of drones in adjacent areas are saturated, drones will need to be reconfigured.

[0074] The adjacent area may be an area bordering the target area, or an area whose distance from the target area is less than a distance threshold.

[0075] The secondary configuration module is also used to evenly distribute 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 tasks that can be added to be processed by all the drones that can work again in the area.

[0076] If the drones in the area are already able to meet the demand, the secondary cleaning tasks can be evenly distributed.

[0077] The second scheduling module in this embodiment is used to configure the drone to clean the photovoltaic panels based on the second photovoltaic base station. It specifically includes: The second area division module is used to take the designated first photovoltaic panel as the initial point. If the number of first photovoltaic panels adjacent to the first photovoltaic panel and with the same cleaning mode reaches the first preset threshold value N1, the first photovoltaic panel and the first photovoltaic panels adjacent to the first photovoltaic panel and with the same cleaning mode are divided into one area 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 the ordinary cleaning mode and the strong cleaning mode; the mixed cleaning mode includes the ordinary cleaning mode and the strong cleaning mode.

[0078] The function of this module is to divide the preset cleaning areas so as to better coordinate the arrangement of drones for cleaning. In view of the scattered distribution of photovoltaic panels in mountainous areas (of course, generally speaking, the cleaning modes of photovoltaic panels in adjacent areas are roughly the same), it is first necessary to "cluster" photovoltaic panels with the same cleaning type and close distance. Specifically, a certain photovoltaic panel is taken as the center, and 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 photovoltaic panels should not be too small. Therefore, a first preset threshold value N1 is set in this embodiment, that is, the number of photovoltaic panels of the same type that reaches the first preset threshold value N1 can be used as a preset area. The purpose is to prevent the preset cleaning areas from being too scattered.

[0079] The second calculation module is used to calculate the density Pi of the cleaning modes corresponding to multiple scattered second photovoltaic panels between any designated area and its adjacent areas; the density Pi = the number n of second photovoltaic panels in any cleaning mode / the sum of the numbers of second photovoltaic panels in three cleaning modes N, where i = 1, 2, 3.

[0080] This module can calculate the density of various cleaning modes according to the density of photovoltaic panels with various types of pollution. Simply put, if it is analyzed that there are 80% ordinary pollution, 15% strong pollution and 10% mixed pollution in a preset area, the density of the corresponding cleaning mode is P1=80%, P2=15%, P3=5%, and so on.

[0081] The second integration module is used to integrate scattered photovoltaic panels.

[0082] The second area division module can integrate the concentrated photovoltaic panels of the same type into a preset cleaning area. After the integration in this step, there will still be some scattered photovoltaic panels (second photovoltaic panels) that are not included in the preset cleaning area. Therefore, the role of the second integration module is to integrate the above scattered photovoltaic panels, which includes three situations: 1. Become an independent new cleaning area; 2. Be absorbed by the surrounding cleaning areas respectively; 3. Be completely absorbed by a preset cleaning area.

[0083] First, an area is randomly designated in the divided areas, and the scattered photovoltaic panels between the area and its adjacent areas are divided.

[0084] Assume that the number of the above scattered photovoltaic panels is N.

[0085] The second integration module is used to divide the scattered second photovoltaic panels 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 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.

[0086] That is to say, if the number of 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%), then these scattered photovoltaic panels can be separated into an area. In other words, the types of scattered photovoltaic panels should be relatively concentrated while meeting certain quantity requirements.

[0087] 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 cleaning mode is less than the first preset density threshold p0.

[0088] That is to say, if the number of scattered photovoltaic panels is greater than or equal to N2 (for example, 500), but the density of all clean types is lower than Pd (70%), then the types of scattered photovoltaic panels are relatively messy and are not suitable for forming a separate area. In this case, these scattered photovoltaic panels can be integrated into the surrounding areas according to their types.

[0089] The second integration module is further 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.

[0090] That is to say, if the number of scattered photovoltaic panels is greater than N2 (for example, 500), it means that the scattered photovoltaic panels are small in magnitude and can be directly included in the designated area. Of course, a better method is to include the corresponding area according to the cleaning mode with the highest density.

[0091] The second configuration module is used to configure a drone group with a corresponding cleaning mode for each area.

[0092] The function of this module is to configure the drone in the area divided by the second area division module. It can be understood that for an area with a single cleaning mode, it is sufficient to directly configure a drone 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 area mainly refers to the situation where multiple second photovoltaic panels are divided into a separate 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 the drone in this module can be found in the first configuration module, which will not be repeated here.

[0093] Different from the first configuration module, when a plurality of the 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.

[0094] After scattered photovoltaic panels (second photovoltaic panels) are divided into designated areas, they may bring photovoltaic panels with different cleaning modes to the designated areas. Since the number of scattered photovoltaic panels is small, the area where they are added is a mixed cleaning area. In this case, all photovoltaic panels in the entire area can be cleaned directly by using a drone with a mixed cleaning mode.

[0095] The second configuration module also configures a drone with a corresponding cleaning mode to perform cleaning when the cleaning mode of the designated area is a normal cleaning mode or a strong cleaning mode, and the remaining area is to be cleaned a second time.

[0096] If the original area is not a photovoltaic panel in the mixed cleaning mode, then the corresponding drone can be configured according to the original cleaning mode to clean the photovoltaic panels in the cleaning mode, and the remaining uncleaned photovoltaic panels will wait for secondary cleaning.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] In addition, the scheduling platform also includes: The power judgment module is used to receive and judge whether the remaining power reported by any drone reaches a preset power threshold.

[0101] 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.

[0102] This module monitors the remaining battery power of the drone in real time to determine whether the drone has enough power to return.

[0103] 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 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 list; 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.

[0104] When the drone reaches the preset power level, it may still be performing a mission or have another mission to perform. In the above case, it is necessary to find a successor to the mission.

[0105] When a drone that is still performing a task or has tasks to perform reaches the preset power level, it needs to find a successor. Therefore, it searches for neighboring drones with the current location of the drone as the center and a preset radius, and obtains the remaining power and pending task list of the neighboring drones.

[0106] When looking for a task successor, it is necessary to determine whether the drone has enough power to support subsequent tasks and new tasks, so as to determine whether the drone is suitable for adding new tasks. It is easy to understand that drones with sufficient power and fewer tasks are preferred.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] The return control module is used to control any drone to return to the starting point from the current position.

[0113] 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.

[0114] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. 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, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a computer terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0115] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection 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; The second scheduling module is used to configure the drone to clean the photovoltaic panels based on the second photovoltaic base station.

2. The drone deployment system for cleaning large photovoltaic base stations according to claim 1 is characterized in that: 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 number 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.

3. The drone deployment system for cleaning large photovoltaic base stations according to claim 2 is characterized in that: 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 P0, and the sum of the densities of the other 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 drone with the mixed cleaning mode to clean the entire area.

4. The drone deployment system for cleaning large photovoltaic base stations according to claim 2 is characterized in that: 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 perform cleaning; And the remaining parts are cleaned by drones with normal cleaning mode and drones with strong cleaning mode respectively; When the density of the first cleaning mode in any area 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'', when 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 for cleaning; and the remaining part is to be cleaned a second time.

5. 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.

6. A drone deployment system for cleaning large photovoltaic base stations according to any one of claims 1 to 3, 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 its current position.

7. The drone deployment system for cleaning large photovoltaic base stations according to claim 6 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.

8. The drone deployment system for cleaning large photovoltaic base stations according to claim 6 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.

9. The drone deployment system for cleaning large photovoltaic base stations according to claim 6 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.

10. The drone deployment system for cleaning large photovoltaic base stations according to claim 5, characterized in that: The secondary cleaning scheduling module I and the secondary cleaning scheduling module II both include: 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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