Cleaning method and device of photovoltaic module, storage medium, electronic device and computer program product

Abstract

The invention discloses a photovoltaic module cleaning method and device, a storage medium, an electronic device and a computer program product, and relates to the field of photovoltaic energy cleaning, and the photovoltaic module cleaning method comprises the steps that N photovoltaic modules are determined from a photovoltaic power generation field, and the N photovoltaic modules are to-be-cleaned modules; determining cleaning levels and position information of the N photovoltaic modules; a target cleaning route is determined according to the cleaning levels and the position information of the N photovoltaic modules, the target cleaning route is used for indicating a moving route of target equipment, M approach points are arranged on the moving route, and the target equipment places a cleaning robot on the photovoltaic module corresponding to the approach point at each approach point in the M approach points, the cleaning robot is used for cleaning the photovoltaic module, the target equipment allows the cleaning robot to be supplemented with a cleaning agent, and M is a positive integer smaller than or equal to N; and controlling the target equipment to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic energy cleaning, and specifically, to a photovoltaic component cleaning method and device, storage medium, electronic device, and computer program product. Background Art

[0002] Photovoltaic power generation systems are generally installed on roofs, roads, factories, water surfaces and other places, most of which are open-air environments. These environments will generate dust on the panels of photovoltaic modules. The dust will block sunlight from directly shining on the panels of photovoltaic modules, thereby affecting the power generation efficiency of the photovoltaic panels. Therefore, it is often necessary to clean the panels of photovoltaic modules.

[0003] The traditional way to clean photovoltaic panels is by manual cleaning, but the traditional manual cleaning method is inefficient, costly and has safety risks. Although there are some automated cleaning equipment, they can only cover some areas and are not very effective in cleaning high and hard-to-reach areas of photovoltaic panels. If a robot is deployed in each area, the economic cost is too high and it is difficult for the site to amortize the related procurement costs and operation and maintenance costs.

[0004] With regard to the problem of low cleaning efficiency of photovoltaic modules in related technologies, no effective solution has been proposed so far.

[0005] Therefore, it is necessary to improve the related technology to overcome the above-mentioned defects in the related technology. Summary of the invention

[0006] The embodiments of the present application provide a photovoltaic module cleaning method and device, a storage medium, an electronic device, and a computer program product to at least solve the problem of low cleaning efficiency of photovoltaic modules in traditional cleaning methods.

[0007] According to one aspect of an embodiment of the present application, there is provided a method for cleaning a photovoltaic module, comprising: determining N photovoltaic modules from a photovoltaic power plant, wherein the N photovoltaic modules are modules to be cleaned, and N is an integer greater than or equal to 1; determining cleaning levels and position information of the N photovoltaic modules, wherein the cleaning levels are used to indicate the content of accumulated materials on the surfaces of the photovoltaic modules; determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route having M waypoints, the target device placing a cleaning robot on the photovoltaic module corresponding to the waypoint at each of the M waypoints, the cleaning robot being used to clean the photovoltaic modules, the target device allowing the cleaning agent to be replenished for the cleaning robot, and M being a positive integer less than or equal to N; controlling the target device to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route.

[0008] In an exemplary embodiment, N photovoltaic components are determined from a photovoltaic power field, including: detecting the power generation power of the photovoltaic components in the photovoltaic power field within a first preset time period; determining from the photovoltaic power field photovoltaic components whose power generation power within the first preset time period is less than a preset power generation power, to obtain the N photovoltaic components.

[0009] In an exemplary embodiment, determining the cleanliness levels of the N photovoltaic components includes: acquiring infrared images and visible light images of the N photovoltaic components, and determining surface texture entropy values ​​of the N photovoltaic components based on the infrared images and visible light images of the N photovoltaic components; determining the cleanliness levels of the N photovoltaic components based on the surface texture entropy values ​​of the N photovoltaic components, wherein the cleanliness level of the i-th photovoltaic component among the N photovoltaic components is determined based on the surface texture entropy value of the i-th photovoltaic component, and i is a positive integer less than or equal to N.

[0010] In an exemplary embodiment, the cleanliness levels of the N photovoltaic components are determined according to the surface texture entropy values ​​of the N photovoltaic components, including: determining the cleanliness level of the ith photovoltaic component in the following manner to obtain the cleanliness levels of the N photovoltaic components: determining a relationship between the surface texture entropy value of the ith photovoltaic component and a plurality of preset ranges, wherein each preset range in the plurality of preset ranges corresponds to a cleanliness level; and when the surface texture entropy value of the ith photovoltaic component is within a target preset range among the plurality of preset ranges, determining the cleanliness level corresponding to the target preset range as the cleanliness level of the ith photovoltaic component.

[0011] In an exemplary embodiment, a target cleaning route is determined based on the cleaning levels and position information of the N photovoltaic components, including: sorting the cleaning levels of the N photovoltaic components, and determining a first weight value of each of the N photovoltaic components based on the sorting result; and determining a distance between the N photovoltaic components and a preset position based on the position information of the N photovoltaic components, and determining a second weight value of each of the N photovoltaic components based on the distance between the N photovoltaic components and the preset position, wherein the preset position is the starting point of the target cleaning route; determining a target weight value of each of the N photovoltaic components based on the first weight value and the second weight value of each of the N photovoltaic components; determining a cleaning order of each of the N photovoltaic components based on the target weight value of each of the N photovoltaic components, and determining the target cleaning route based on the cleaning order of each photovoltaic component.

[0012] In an exemplary embodiment, controlling the target device to carry the cleaning robot to clean N photovoltaic components based on the target cleaning route includes: sending the target cleaning route to the target device, and instructing the target device and the cleaning robot to clean the N photovoltaic components based on a target strategy; wherein the target strategy includes: the target device moves to a first waypoint based on the target cleaning route, and when the target device moves to the waypoint, the cleaning robot is placed on the photovoltaic component corresponding to the waypoint, the cleaning robot cleans the corresponding photovoltaic component, and when the cleaning is completed, sends an instruction to the target device to instruct the target device to carry the cleaning robot to move to the next waypoint of the first waypoint; wherein, when the detergent in the cleaning robot is less than a first preset threshold, the target device replenishes the detergent for the cleaning robot, and when the detergent in the target device is less than a second preset threshold, the target device returns to the detergent replenishment point to replenish the detergent.

[0013] According to another aspect of an embodiment of the present application, a cleaning device for photovoltaic components is also provided, comprising: a first determination module, used to determine N photovoltaic components from a photovoltaic power field, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1; a second determination module, used to determine the cleaning level and position information of the N photovoltaic components, wherein the cleaning level is used to indicate the content of accumulated materials on the surface of the photovoltaic components; a third determination module, used to determine a target cleaning route according to the cleaning level and position information of the N photovoltaic components, wherein the target cleaning route is used to indicate a moving route of a target device, and the moving route has M waypoints, and the target device places a cleaning robot on the photovoltaic component corresponding to the waypoint at each waypoint of the M waypoints, and the cleaning robot is used to clean the photovoltaic components, and the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N; a control module, used to control the target device to carry the cleaning robot to clean the N photovoltaic components based on the target cleaning route.

[0014] According to another aspect of the embodiments of the present application, a computer-readable storage medium is further provided, wherein the computer-readable storage medium includes a stored program, wherein the program is configured to execute the above-mentioned photovoltaic component cleaning method when running.

[0015] According to another aspect of the embodiments of the present application, there is further provided an electronic device, including a memory and a processor, wherein the memory stores a computer program, wherein the processor is configured to execute the above-mentioned photovoltaic component cleaning method through the computer program.

[0016] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and the computer program is the above-mentioned method for cleaning the photovoltaic component when executed by a processor.

[0017] This application determines the target cleaning route by determining the cleaning level and location information of the photovoltaic module to be cleaned, and then controls the target device to carry the cleaning robot to clean the photovoltaic module to be cleaned based on the target cleaning route. Since the target device can carry the cleaning robot to clean the photovoltaic module, it can clean the high areas that are difficult to reach by traditional cleaning methods, improve the cleaning effect of the photovoltaic module, and thus solve the problem of low cleaning efficiency of the photovoltaic module. In addition, since the target device carries the cleaning robot to clean the photovoltaic module, there is no need to deploy multiple cleaning robots, saving economic costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 This is a hardware structure block diagram of a mobile terminal for cleaning photovoltaic components according to an embodiment of the present application;

[0021] Figure 2 is a flow chart of cleaning a photovoltaic module according to an embodiment of the present application;

[0022] Figure 3 is a schematic diagram of an optional process of cleaning a photovoltaic module according to an embodiment of the present application;

[0023] Figure 4 It is a structural block diagram of a photovoltaic module cleaning device according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 1 is a hardware structure block diagram of a mobile terminal for cleaning photovoltaic modules according to an embodiment of the present application. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a microprocessor (MP) or a programmable logic device (FPGA)) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0027] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the cleaning of photovoltaic modules in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0028] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] In order to solve the above problems, a photovoltaic module cleaning method is provided in this embodiment, including but not limited to being applied to the above mobile terminal. Figure 2 is a flow chart of cleaning a photovoltaic module according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps S202-S208:

[0030] Step S202: determining N photovoltaic components from a photovoltaic power plant, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1;

[0031] Step S204: determining the cleaning level and position information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of accumulated matter on the surface of the photovoltaic module;

[0032] Optionally, the accumulated matter on the surface of the photovoltaic module includes, but is not limited to, snow, dust, and fallen leaves.

[0033] It should be noted that grading the cleaning levels according to the content of the accumulated materials can help to formulate more reasonable cleaning strategies, such as giving priority to cleaning photovoltaic modules with serious dust accumulation.

[0034] Step S206: determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each waypoint among the M waypoints, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N;

[0035] Optionally, the target device includes, but is not limited to: a mobile robot (with a mechanical arm) and a drone.

[0036] Optionally, based on the cleaning level and location information, the system plans an optimal cleaning route, namely the target cleaning route, to ensure that the cleaning task of all photovoltaic modules to be cleaned is completed with the least number of moves. The target cleaning route includes M waypoints, each waypoint corresponds to one or a group of photovoltaic modules to be cleaned, wherein all photovoltaic modules in a group of photovoltaic modules corresponding to a waypoint are located in the same photovoltaic array.

[0037] Optionally, taking the target device as a mobile robot as an example, the mobile robot will place the cleaning robot on one or a group of photovoltaic components corresponding to the route point for cleaning based on the target cleaning route, and when the cleaning agent is insufficient, the cleaning robot can be replenished with cleaning agent to ensure the continuity and efficiency of the cleaning process.

[0038] It should be noted that the planning of the target cleaning route can significantly reduce the moving distance and time of the target equipment and the cleaning robot, thereby improving the cleaning efficiency and economy. In addition, by replenishing the cleaning robot with detergent through the target equipment, the cleaning robot can continue to operate without frequently returning to the supply point, thereby improving the continuity and efficiency of the operation.

[0039] Step S208: Control the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route.

[0040] Optionally, when the target device is a mobile robot, the mobile robot can carry the cleaning robot and flexibly move on the ground according to the planned target cleaning route to reach the designated photovoltaic module location for cleaning. This solves the limitation of the cleaning robot's mobility due to complex terrain (such as mountains and undulating ground), allowing the cleaning robot to be more widely used.

[0041] Optionally, when the target device is a drone, the drone can carry a cleaning robot to high altitude locations that are difficult for mobile robots or humans to reach, and clean and maintain photovoltaic panels at high altitudes, reducing dependence on ground equipment, expanding the scope of cleaning operations, and improving overall operational efficiency and adaptability.

[0042] It should be noted that the intelligent collaboration between the target equipment (mobile robots, drones) and the cleaning robots has realized ground-to-air automated cleaning, improving the overall performance and adaptability of the system. In addition, by having the target equipment carry the cleaning robot for cleaning, the cleaning robot can be shared. Compared with deploying a separate cleaning robot on each photovoltaic module or string, the equipment procurement cost and operation and maintenance cost are greatly reduced.

[0043] In the above steps, the target cleaning route is determined by determining the cleaning level and location information of the photovoltaic module to be cleaned, and then the target device is controlled to carry the cleaning robot to clean the photovoltaic module to be cleaned based on the target cleaning route. Since the target device can carry the cleaning robot to clean the photovoltaic module, it can clean the high areas that are difficult to reach by traditional cleaning methods, thereby improving the cleaning effect of the photovoltaic module and solving the problem of low cleaning efficiency of the photovoltaic module. In addition, since the target device carries the cleaning robot to clean the photovoltaic module, there is no need to deploy multiple cleaning robots, saving economic costs.

[0044] In an exemplary embodiment, determining N photovoltaic modules from a photovoltaic power plant may be achieved by following the steps S11-S12:

[0045] Step S11: detecting the power generation of the photovoltaic components in the photovoltaic power plant within a first preset time period;

[0046] Optionally, after the lighting conditions are stable and other factors affecting power generation efficiency (such as temperature changes) are relatively small, the system uses detection equipment to automatically detect the power generation data of all photovoltaic modules in the photovoltaic power field within a first preset time period. During the first time period, the power generation power of the photovoltaic modules is relatively stable, thereby ensuring the accuracy of the data. The detection equipment includes: sensors installed on the photovoltaic modules and a monitoring system for the photovoltaic power field.

[0047] Step S12: determining, from the photovoltaic power generation field, photovoltaic modules whose power generation power is less than a preset power generation power within the first preset time period, to obtain the N photovoltaic modules.

[0048] Optionally, the preset power generation power includes: a first preset power generation power and a second preset power generation power, wherein the first preset power generation power is the average power generation power preset by a photovoltaic component within a first preset time period, and the second preset power generation power is the total power generation power preset by a photovoltaic component within the first preset time period.

[0049] Optionally, when the average power generation power of the a-th photovoltaic component in the photovoltaic power generation field within the first preset time period is less than the first preset power generation power, the photovoltaic component is confirmed as the photovoltaic component to be cleaned, wherein a is a positive integer; or

[0050] When the total power generation power of the a-th photovoltaic component in the photovoltaic power generation field within the first preset time period is less than the second preset power generation power, the photovoltaic component is confirmed as a photovoltaic component to be cleaned.

[0051] It should be noted that by comparing the average power generation of the photovoltaic modules with the first preset power generation, it is possible to more accurately determine whether the photovoltaic modules are affected by environmental factors such as dust accumulation, thereby avoiding unnecessary cleaning of modules in good cleaning condition; based on the first preset power generation, the system can more reasonably allocate cleaning resources, avoiding wasting cleaning agents and manpower on modules with still high power generation efficiency; photovoltaic modules with an average power generation lower than the first preset power generation may be in the initial stage of decreased power generation efficiency. Timely cleaning can prevent further deterioration of the power generation efficiency of the photovoltaic modules, and help maintain stable output of the entire power plant.

[0052] It should be noted that when the total power generation of the photovoltaic modules is lower than the second preset power generation, it usually means that the power generation efficiency of the photovoltaic modules has dropped significantly, which may be a signal of large-scale dust accumulation or other more serious faults. Through this step, photovoltaic modules that need emergency treatment can be identified more quickly. In addition, based on the judgment of the total power generation of the photovoltaic modules, the system can adjust the cleaning plan to give priority to cleaning those photovoltaic modules that have the greatest impact on the overall power generation, thereby restoring the maximum power generation with the lowest cost and time.

[0053] It should be noted that the preset power generation capacity can be adjusted according to dynamic factors such as season, weather, and component aging to ensure that the cleaning strategy matches the actual power generation needs.

[0054] In an exemplary embodiment, determining the cleanliness levels of the N photovoltaic modules may be achieved by following steps S21-S22:

[0055] Step S21: acquiring infrared images and visible light images of the N photovoltaic modules, and determining surface texture entropy values ​​of the N photovoltaic modules according to the infrared images and visible light images of the N photovoltaic modules;

[0056] Optionally, after N photovoltaic modules are confirmed, a drone (the drone is equipped with a high-precision camera) is controlled to obtain infrared images and visible light images of the N photovoltaic modules: first, the location information (such as longitude and latitude coordinates) of the N photovoltaic modules are connected in series into a line to confirm the target inspection route of the drone; secondly, the drone is controlled to perform inspections based on the target inspection route to take infrared images and visible light images of the N photovoltaic modules.

[0057] Optionally, the surface texture entropy value of the i-th photovoltaic module among the N photovoltaic modules is calculated through the following steps S211-S214 to obtain the surface texture entropy values ​​of the N photovoltaic modules:

[0058] Step S211: superimposing an infrared image of a first image weight and a visible light image of a second image weight corresponding to the i-th photovoltaic assembly among the N photovoltaic assemblies to obtain a target image, wherein the second image weight is generally greater than the first image weight;

[0059] For example, a 20% infrared image is superimposed with an 80% visible light image.

[0060] Step S212: converting the target image into a grayscale image to construct a grayscale histogram of the grayscale image, wherein each entry in the grayscale histogram represents the number of pixels of a certain grayscale level in the grayscale image;

[0061] Step S213: Calculate the occurrence probability of each gray level in the gray image according to the histogram, wherein the occurrence probability of the nth gray level is the number of pixels of the nth gray level divided by the total number of pixels, and n is a positive integer;

[0062] Step S214: Calculate the surface texture entropy value of the i-th photovoltaic module using the following formula:

[0063] H(i)=-∑ n P(n)log2[P(n)];

[0064] Among them, H(i) is the surface texture entropy value of the i-th photovoltaic module, and P(n) is the occurrence probability of the n-th gray level.

[0065] It should be noted that the surface texture entropy value is used to describe the complexity of image texture. In the field of photovoltaic energy cleaning, the surface texture entropy value of photovoltaic modules can be used to quantify and evaluate the unevenness and complexity of dust or snow cover on the surface of photovoltaic panels. That is, the higher the surface texture entropy value of the photovoltaic module, the greater the content of accumulated materials on the surface of the photovoltaic module, and the more it needs to be cleaned.

[0066] Step S22: determining the cleanliness levels of the N photovoltaic components according to the surface texture entropy values ​​of the N photovoltaic components, wherein the cleanliness level of the i-th photovoltaic component among the N photovoltaic components is determined according to the surface texture entropy value of the i-th photovoltaic component, and i is a positive integer less than or equal to N.

[0067] It should be noted that, through the above steps S21-S22, the accumulated materials on the surface of the photovoltaic modules are automatically analyzed, and the cleaning level is intelligently determined to determine the cleaning order, which can more effectively allocate cleaning resources and reduce the impact of cleaning operations on the normal operation of the power station.

[0068] In an exemplary embodiment, determining the cleanliness levels of the N photovoltaic modules according to the surface texture entropy values ​​of the N photovoltaic modules can be achieved by the following steps: determining the cleanliness level of the i-th photovoltaic module by the following steps S31-S32 to obtain the cleanliness levels of the N photovoltaic modules:

[0069] Step S31: determining a relationship between the surface texture entropy value of the i-th photovoltaic module and a plurality of preset ranges, wherein each of the plurality of preset ranges corresponds to a cleaning level;

[0070] Step S32: when the surface texture entropy value of the i-th photovoltaic component is within a target preset range among the multiple preset ranges, determining the cleaning level corresponding to the target preset range as the cleaning level of the i-th photovoltaic component.

[0071] Optionally, when the surface texture entropy value of the i-th photovoltaic module is between 2.0 bits / pixel and 3.0 bits / pixel, the cleanliness level of the i-th photovoltaic module is mild; when the surface texture entropy value of the i-th photovoltaic module is between 3.0 bits / pixel and 5.0 bits / pixel, the cleanliness level of the i-th photovoltaic module is general; when the surface texture entropy value of the i-th photovoltaic module is between 5.0 bits / pixel and 7.0 bits / pixel, the cleanliness level of the i-th photovoltaic module is severe.

[0072] It should be noted that the preset range is set based on the typical entropy performance of PV modules under different backlog states and the cleaning strategy of the PV power plant. In addition, the image resolution, light source conditions, weather conditions, maintenance strategy of the PV power plant and cost-effectiveness must also be considered.

[0073] In an exemplary embodiment, determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules can be achieved by the following steps S41-S44:

[0074] Step S41: sorting the cleaning levels of the N photovoltaic assemblies, and determining a first weight value of each of the N photovoltaic assemblies according to the sorting result;

[0075] Optionally, the cleaning levels of the N photovoltaic components are sorted, and the photovoltaic component with a higher cleaning level (for example, the cleaning level is "serious"), the higher it is in the sorting. Subsequently, a first weight value is assigned to each of the N photovoltaic components based on the sorting result. The first weight value reflects the urgency of cleaning the photovoltaic component, and a photovoltaic component with a higher cleaning level corresponds to a higher first weight value.

[0076] Step S42: determining the distance between the N photovoltaic assemblies and a preset position according to the position information of the N photovoltaic assemblies, and determining a second weight value of each of the N photovoltaic assemblies according to the distance between the N photovoltaic assemblies and the preset position, wherein the preset position is the starting point of the target cleaning route;

[0077] Optionally, the location information includes: longitude and latitude coordinates, altitude information and slope information, etc.

[0078] Optionally, the location information of the photovoltaic components is used to calculate the distance between each of the N photovoltaic components and the starting point of the cleaning route. The second weight value of the photovoltaic component that is closer is higher, while the second weight value of the photovoltaic component that is farther away is lower. The second weight value reflects the movement cost of the target device (mobile robot or drone) to reach the component for cleaning.

[0079] It should be noted that there is no specific order in which step S41 and step S42 are to be executed.

[0080] Step S43: determining a target weight value of each photovoltaic component according to the first weight value and the second weight value of each photovoltaic component in the N photovoltaic components;

[0081] Optionally, the target weight value is obtained by comprehensively considering the cleaning level (first weight value) and the distance from the component to the starting point of the cleaning route (second weight value). The first weight value and the second weight value can be combined by weighted average to obtain a target weight value that more comprehensively reflects the cleaning urgency and actual accessibility.

[0082] Step S44: determining a cleaning order of each photovoltaic assembly according to the target weight value of each photovoltaic assembly in the N photovoltaic assemblies, and determining the target cleaning route according to the cleaning order of each photovoltaic assembly.

[0083] Optionally, when the target weight value of the p-th photovoltaic component is greater than the target weight value of the q-th photovoltaic component, the p-th photovoltaic component is cleared first, where p and q are both positive integers.

[0084] It should be noted that the PV modules are reordered according to the target weight value. The PV modules with higher weight values ​​are placed at the front of the cleaning order, which means they will be cleaned first. After determining the cleaning order, the system will plan an optimal cleaning route, namely the target cleaning route. This route will visit each PV module in turn according to the cleaning order to ensure the efficiency and consistency of the cleaning operation.

[0085] It should be noted that the above steps achieve intelligent optimization of cleaning operations by comprehensively considering the cleaning needs and actual locations of the components, which not only improves the efficiency and effectiveness of cleaning, but also reduces operation and maintenance costs, enhances equipment utilization, and improves the scientificity and accuracy of operation and maintenance decisions. It has important technical value for promoting efficient operation and maintenance and sustainable development of photovoltaic power plants.

[0086] In an exemplary embodiment, controlling the target device to carry the cleaning robot to clean N photovoltaic components based on the target cleaning route can be achieved through the following steps: sending the target cleaning route to the target device, and instructing the target device and the cleaning robot to clean the N photovoltaic components based on a target strategy; wherein the target strategy includes: the target device moves to a first waypoint based on the target cleaning route, and when the target device moves to the waypoint, the cleaning robot is placed on the photovoltaic component corresponding to the waypoint, the cleaning robot cleans the corresponding photovoltaic component, and when the cleaning is completed, sends an instruction to the target device to instruct the target device to carry the cleaning robot to the next waypoint of the first waypoint; wherein, when the detergent of the cleaning robot is less than a first preset threshold, the target device replenishes the detergent for the cleaning robot, and when the detergent in the target device is less than a second preset threshold, the target device returns to the detergent replenishment point to replenish the detergent.

[0087] Optionally, the system sends specific cleaning instructions to the target device, including the cleaning method of each photovoltaic module, the selection of cleaning agents, etc. The target device and the cleaning robot jointly perform the cleaning task according to these instructions and the target cleaning route; the target device first moves to the location of the first photovoltaic module to be cleaned according to the target cleaning route, that is, the first waypoint, where the waypoint is the location of the module that the target device and the cleaning robot need to visit during the execution of the task. Once the target device (such as a mobile robot) arrives at the waypoint, the cleaning robot is placed on the corresponding photovoltaic module, and the cleaning robot then starts to clean the module.

[0088] Optionally, for photovoltaic modules at high places, the target device (drone) can grab a cleaning robot and go to the location of the photovoltaic module to clean the photovoltaic module, thereby ensuring that all modules can be effectively cleaned, thereby improving the comprehensiveness and efficiency of the cleaning operation.

[0089] Optionally, the cleaning robot will consume detergent during the cleaning process. When the remaining amount of detergent is lower than a set first threshold, the target device will automatically replenish it with detergent to ensure that the cleaning robot can continue to operate. The target device (such as a mobile robot) also carries detergent. When the detergent is lower than a second preset threshold, the target device returns to the detergent replenishment point for replenishment to avoid interruption of operations due to exhaustion of resources during the cleaning process.

[0090] It should be noted that by implementing the above steps, it is possible to ensure that the cleaning operations of photovoltaic modules are efficiently performed in a predetermined order and path. At the same time, through the dynamic management and replenishment of resources, the continuous operation capability of the cleaning equipment is guaranteed, and the waste of resources and the interruption of cleaning tasks are avoided. This not only improves the cleaning efficiency, but also reduces the operation and maintenance costs, reflecting the advantages of intelligent photovoltaic operation and maintenance management.

[0091] In an exemplary embodiment, the method further includes: verifying the effectiveness of the cleaning operation through image comparison and power generation efficiency monitoring to ensure that the cleaning quality meets predetermined standards, and at the same time, performing quality control on the cleaning process to identify and correct potential problems in the cleaning process.

[0092] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. In order to better understand the above method, the above process is described below in conjunction with the embodiments, but it is not intended to limit the technical solutions of the embodiments of the present invention. Figure 3 The overall flow chart of cleaning a photovoltaic module according to an embodiment of the application is shown, specifically:

[0093] 1. The system consists of a water supply tank, a small cleaning robot, a mobile robot with a gripper (the target equipment mentioned above), and a hangar containing drones;

[0094] 2. After the power generation of the photovoltaic modules is relatively stable one hour after sunrise every day, determine which photovoltaic modules are inefficient based on their power generation efficiency;

[0095] 3. Plan routes and connect all inefficient PV panels in series into an inspection and confirmation route. Automatically import the route into the hangar, issue instructions through the hangar to conduct inspections by drones, and take visible light and infrared images of all the components of the above-mentioned inefficient strings to identify which PV panels are inefficient due to dust accumulation.

[0096] 4. Determine the dust accumulation of each dusty photovoltaic module. If the surface texture entropy value of the photovoltaic module is greater than the empirical threshold, or if snow is found on the surface, the degree of cleaning to be graded and marked is classified into severe, general, slight, etc.;

[0097] 5. Sort the components to be cleaned by severity and distance, and then plan the cleaning path of the mobile robot according to the cleaning sequence;

[0098] 6. The mobile robot identifies the cleaning robot through the camera at the end of the gripper and grabs it with the gripper that matches the cleaning robot. Then, the mobile robot moves to the photovoltaic module to be cleaned according to the planned cleaning path, and uses the telescopic gripper to prevent the cleaning robot from cleaning the photovoltaic module.

[0099] 7. The mobile robot is equipped with a water tank. When the water of the cleaning robot is used up, the mobile robot can directly replenish the water source for the cleaning robot. After replenishment, the mobile robot returns to the replenishment pool to pump water to replenish the water tank;

[0100] 8. After the cleaning robot finishes cleaning the nearby PV panels, it sends a command to the mobile robot, which then grabs the cleaning robot and takes it to the next planned component to be cleaned;

[0101] 9. Repeat the above process until all the photovoltaic modules to be cleaned are cleaned;

[0102] 10. After the cleaning is completed, the cleaning effect is judged again by the power generation. If there are still suspected inefficient strings with dust accumulation, the background will automatically plan the inspection route, and then import the route into the hangar, and then send out a drone through the hangar to inspect again to confirm whether there is dust accumulation. If there is no problem, an alarm will be issued to the on-duty personnel for confirmation;

[0103] 11. For areas with complex terrain that mobile robots cannot pass through, drones carrying grippers are used to grab the cleaning robots and move them.

[0104] It should be noted that this application also has the following advantages: (1) High stability. The photovoltaic cleaning robot, gripper robot, or drone used are all mature products in the market, and the stability of the entire system is high when used; (2) Low cost. Compared with deploying a set of photovoltaic cleaning robots for each photovoltaic string, this solution can basically cover the entire station with only one cleaning robot. Millimeter wave radar can quickly scan moving objects in the surrounding environment, unlike the image inspection mode such as visible light, which requires point-by-point collection and identification; (3) Good adaptability. It can be used in different terrains such as mountains and plains, as well as centralized and distributed photovoltaic stations; (4) Good cleaning continuity. An important problem with photovoltaic automation cleaning is that drones and small cleaning robots have limited water carrying capacity, and mobile robots have poor cleaning effects on high-altitude photovoltaics. This solution effectively realizes efficient cleaning of photovoltaics by effectively utilizing the advantages of various intelligent equipment.

[0105] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment 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 application, 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, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0106] In this embodiment, a photovoltaic module cleaning device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0107] Figure 4 : is a structural block diagram of a photovoltaic module cleaning device according to an embodiment of the present application, the device comprising:

[0108] A first determination module 402 is used to determine N photovoltaic components from a photovoltaic power plant, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1;

[0109] A second determination module 404 is used to determine the cleanliness level and position information of the N photovoltaic components, wherein the cleanliness level is used to indicate the content of accumulated matter on the surface of the photovoltaic component;

[0110] The third determination module 406 is used to determine a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each waypoint of the M waypoints, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N;

[0111] The control module 408 is used to control the target device to carry the cleaning robot to clean N photovoltaic components based on the target cleaning route.

[0112] The above device determines the target cleaning route by determining the cleaning level and location information of the photovoltaic module to be cleaned, and then controls the target device to carry the cleaning robot to clean the photovoltaic module to be cleaned based on the target cleaning route. Since the target device can carry the cleaning robot to clean the photovoltaic module, it can clean the high areas that are difficult to reach by traditional cleaning methods, thereby improving the cleaning effect of the photovoltaic module and solving the problem of low cleaning efficiency of the photovoltaic module. In addition, since the target device carries the cleaning robot to clean the photovoltaic module, there is no need to deploy multiple cleaning robots, saving economic costs.

[0113] In an exemplary embodiment, the first determination module 402 is also used to detect the power generation of the photovoltaic components in the photovoltaic power field within a first preset time period; determine the photovoltaic components in the photovoltaic power field whose power generation power within the first preset time period is less than the preset power generation power, and obtain the N photovoltaic components.

[0114] In an exemplary embodiment, the second determination module 404 is also used to obtain infrared images and visible light images of the N photovoltaic components, and determine surface texture entropy values ​​of the N photovoltaic components based on the infrared images and visible light images of the N photovoltaic components; determine the cleanliness levels of the N photovoltaic components based on the surface texture entropy values ​​of the N photovoltaic components, wherein the cleanliness level of the i-th photovoltaic component among the N photovoltaic components is determined based on the surface texture entropy value of the i-th photovoltaic component, and i is a positive integer less than or equal to N.

[0115] In an exemplary embodiment, the second determination module 404 is also used to determine the cleanliness level of the i-th photovoltaic component to obtain the cleanliness levels of the N photovoltaic components in the following manner: determining the relationship between the surface texture entropy value of the i-th photovoltaic component and multiple preset ranges, wherein each preset range in the multiple preset ranges corresponds to a cleanliness level; when the surface texture entropy value of the i-th photovoltaic component is within a target preset range among the multiple preset ranges, determining the cleanliness level corresponding to the target preset range as the cleanliness level of the i-th photovoltaic component.

[0116] In an exemplary embodiment, the third determination module 406 is also used to sort the cleaning levels of the N photovoltaic components, and determine the first weight value of each of the N photovoltaic components according to the sorting result; and determine the distance between the N photovoltaic components and a preset position according to the position information of the N photovoltaic components, and determine the second weight value of each of the N photovoltaic components according to the distance between the N photovoltaic components and the preset position, wherein the preset position is the starting point of the target cleaning route; determine the target weight value of each of the N photovoltaic components according to the first weight value and the second weight value of each of the N photovoltaic components; determine the cleaning order of each photovoltaic component according to the target weight value of each of the N photovoltaic components, and determine the target cleaning route according to the cleaning order of each photovoltaic component.

[0117] In an exemplary embodiment, the control module 408 is also used to send the target cleaning route to the target device, and instruct the target device and the cleaning robot to clean the N photovoltaic components based on a target strategy; wherein the target strategy includes: the target device moves to a first waypoint based on the target cleaning route, and when the target device moves to the waypoint, the cleaning robot is placed on the photovoltaic component corresponding to the waypoint, the cleaning robot cleans the corresponding photovoltaic component, and when the cleaning is completed, sends an instruction to the target device to instruct the target device to carry the cleaning robot to the next waypoint of the first waypoint; wherein, when the detergent of the cleaning robot is less than a first preset threshold, the target device replenishes the detergent for the cleaning robot, and when the detergent in the target device is less than a second preset threshold, the target device returns to the detergent replenishment point to replenish the detergent.

[0118] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0119] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0120] S1, determining N photovoltaic components from a photovoltaic power generation field, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1;

[0121] S2, determining the cleaning level and position information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of accumulated matter on the surface of the photovoltaic module;

[0122] S3, determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each waypoint among the M waypoints, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N;

[0123] S4, controlling the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route.

[0124] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0125] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0126] An embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps in any one of the above method embodiments are performed.

[0127] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0128] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0129] S1, determining N photovoltaic components from a photovoltaic power generation field, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1;

[0130] S2, determining the cleaning level and position information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of accumulated matter on the surface of the photovoltaic module;

[0131] S3, determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each waypoint among the M waypoints, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N;

[0132] S4, controlling the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route.

[0133] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0134] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0135] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0136] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for cleaning a photovoltaic module, characterized in that: include: Determine N photovoltaic components from the photovoltaic power generation field, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1; Determining the cleanliness level and position information of the N photovoltaic modules, wherein the cleanliness level is used to indicate the content of accumulated matter on the surface of the photovoltaic module; A target cleaning route is determined based on the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each of the M waypoints, the cleaning robot is used to clean the photovoltaic modules, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N; the target device is controlled to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route.

2. The method according to claim 1, characterized in that Determine N photovoltaic panels from the photovoltaic power plant, including: Detecting the power generation of the photovoltaic components in the photovoltaic power generation field within a first preset time period; The photovoltaic components whose power generation power is less than the preset power generation power in the first preset time period are determined from the photovoltaic power generation field to obtain the N photovoltaic components.

3. The method according to claim 1, characterized in that Determining the cleanliness level of the N photovoltaic modules includes: Acquire infrared images and visible light images of the N photovoltaic modules, and determine surface texture entropy values ​​of the N photovoltaic modules according to the infrared images and visible light images of the N photovoltaic modules; The cleanliness levels of the N photovoltaic components are determined according to the surface texture entropy values ​​of the N photovoltaic components, wherein the cleanliness level of the i-th photovoltaic component among the N photovoltaic components is determined according to the surface texture entropy value of the i-th photovoltaic component, and i is a positive integer less than or equal to N.

4. The method according to claim 3, characterized in that Determining the cleanliness levels of the N photovoltaic modules according to the surface texture entropy values ​​of the N photovoltaic modules includes: The cleanliness level of the i-th photovoltaic module is determined in the following manner to obtain the cleanliness levels of the N photovoltaic modules: Determining a relationship between the surface texture entropy value of the i-th photovoltaic module and a plurality of preset ranges, wherein each preset range in the plurality of preset ranges corresponds to a cleaning level; When the surface texture entropy value of the i-th photovoltaic component is within a target preset range among the multiple preset ranges, the cleaning level corresponding to the target preset range is determined as the cleaning level of the i-th photovoltaic component.

5. The method according to claim 1, characterized in that Determining a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules includes: Sorting the cleaning levels of the N photovoltaic assemblies, and determining a first weight value of each of the N photovoltaic assemblies according to the sorting result; and Determine the distance between the N photovoltaic components and a preset position according to the position information of the N photovoltaic components, and determine the second weight value of each of the N photovoltaic components according to the distance between the N photovoltaic components and the preset position, wherein the preset position is the starting point of the target cleaning route; determine the target weight value of each photovoltaic component according to the first weight value and the second weight value of each photovoltaic component in the N photovoltaic components; The cleaning order of each photovoltaic assembly is determined according to the target weight value of each photovoltaic assembly in the N photovoltaic assemblies, and the target cleaning route is determined according to the cleaning order of each photovoltaic assembly.

6. The method according to claim 1, characterized in that Controlling the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route includes: Sending the target cleaning route to the target device, and instructing the target device and the cleaning robot to clean the N photovoltaic components based on the target strategy; The target strategy includes: the target device moves to a first waypoint based on the target cleaning route, and when the target device moves to the waypoint, the cleaning robot is placed on the photovoltaic component corresponding to the waypoint, the cleaning robot cleans the corresponding photovoltaic component, and when the cleaning is completed, sends an instruction to the target device to instruct the target device to carry the cleaning robot to move to the next waypoint of the first waypoint; Wherein, when the detergent in the cleaning robot is less than a first preset threshold, the target device replenishes the detergent for the cleaning robot; when the detergent in the target device is less than a second preset threshold, the target device returns to the detergent replenishing point to replenish the detergent.

7. A photovoltaic module cleaning device, characterized in that: include: A first determination module is used to determine N photovoltaic components from a photovoltaic power generation field, wherein the N photovoltaic components are components to be cleaned, and N is an integer greater than or equal to 1; A second determination module is used to determine the cleanliness level and position information of the N photovoltaic components, wherein the cleanliness level is used to indicate the content of accumulated matter on the surface of the photovoltaic component; A third determination module is used to determine a target cleaning route according to the cleaning levels and position information of the N photovoltaic modules, wherein the target cleaning route is used to indicate a moving route of a target device, the moving route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to the waypoint at each waypoint of the M waypoints, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be replenished with cleaning agent, and M is a positive integer less than or equal to N; A control module is used to control the target device to carry the cleaning robot to clean N photovoltaic components based on the target cleaning route.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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