Method and device for cleaning photovoltaic modules, storage medium, electronic device, computer program product

Abstract

The application discloses a kind of cleaning method and device of photovoltaic module, storage medium, electronic device, computer program product, it is related to photovoltaic energy cleaning field, the cleaning method of this photovoltaic module includes: determining N photovoltaic modules from photovoltaic power generation field, wherein N photovoltaic modules are the component to be cleaned;Determine the cleaning level and position information of N photovoltaic modules;According to the cleaning level and position information of N photovoltaic modules, determine target cleaning route, wherein target cleaning route is used to indicate the moving route of target equipment, M way points are on moving route, target equipment places cleaning robot on the photovoltaic module corresponding to each way point in M way points, cleaning robot is used to clean photovoltaic module, target equipment allows to supplement cleaning agent for cleaning robot, M is less than or equal to N positive integer;Control target equipment carries cleaning robot to clean N photovoltaic modules based on target cleaning route.

Description

Technical Field

[0001] This application relates to the field of clean photovoltaic energy, and more specifically, to a method and apparatus for cleaning photovoltaic modules, a storage medium, an electronic device, and a computer program product. Background Technology

[0002] Photovoltaic power generation systems are generally installed on rooftops, roads, factories, water surfaces, and other places, mostly in open-air environments. In these environments, dust will accumulate on the photovoltaic module panels. This dust will block sunlight from directly hitting the photovoltaic module panels, thus affecting the power generation efficiency of the photovoltaic panels. Therefore, it is necessary to clean the photovoltaic module panels frequently.

[0003] Traditional photovoltaic panel cleaning methods rely on manual cleaning, which is inefficient, costly, and poses safety risks. While some automated cleaning equipment exists, it often only covers partial areas and is ineffective at cleaning high or hard-to-reach areas of the photovoltaic panels. Deploying a robot in every area would be too costly, making it difficult for the plant to amortize the related procurement and maintenance costs.

[0004] There is currently no effective solution to the problem of low cleaning efficiency of photovoltaic modules in related technologies.

[0005] Therefore, it is necessary to improve the relevant technology to overcome the aforementioned defects. Summary of the Invention

[0006] This application provides a method and apparatus for cleaning photovoltaic modules, 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 the embodiments of this application, a method for cleaning photovoltaic modules is provided, 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 the cleaning level and location information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of deposits on the surface of the photovoltaic modules; determining a target cleaning route based on the cleaning level and location information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the movement route of a target device, the movement route having M waypoints, the target device placing a cleaning robot on the photovoltaic module corresponding to each of the M waypoints, the cleaning robot being used to clean the photovoltaic modules, the target device allowing the cleaning robot to be replenished with cleaning agent, and M being a positive integer less than or equal to N; and 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, determining N photovoltaic modules from a photovoltaic power plant includes: detecting the power generation of the photovoltaic modules in the photovoltaic power plant within a first preset time period; and determining the photovoltaic modules whose power generation within the first preset time period is less than a preset power generation, thereby obtaining the N photovoltaic modules.

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

[0010] In an exemplary embodiment, determining the cleanliness level of the N photovoltaic modules based on their surface texture entropy values ​​includes: determining the cleanliness level of the i-th photovoltaic module to obtain the cleanliness levels of the N photovoltaic modules by: determining the relationship between the surface texture entropy value of the i-th photovoltaic module and a plurality of preset ranges, wherein each preset range corresponds to a cleanliness level; and determining the cleanliness level corresponding to the target preset range as the cleanliness level of the i-th photovoltaic module when the surface texture entropy value of the i-th photovoltaic module is within a target preset range of the plurality of preset ranges.

[0011] In an exemplary embodiment, determining a target cleaning route based on the cleaning level and location information of the N photovoltaic modules includes: sorting the N photovoltaic modules according to their cleaning levels and determining a first weight value for each of the N photovoltaic modules based on the sorting results; determining the distance between the N photovoltaic modules and a preset location based on the location information of the N photovoltaic modules, and determining a second weight value for each of the N photovoltaic modules based on the distance between the N photovoltaic modules and the preset location, wherein the preset location is the starting point of the target cleaning route; determining a target weight value for each photovoltaic module based on the first weight value and the second weight value; determining the cleaning order of each photovoltaic module based on the target weight value of each of the N photovoltaic modules, and determining the target cleaning route based on the cleaning order of each photovoltaic module.

[0012] In an exemplary embodiment, 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 modules based on a target strategy; wherein the target strategy includes: the target device moving to a first waypoint based on the target cleaning route; when the target device moves to the waypoint, placing the cleaning robot on the photovoltaic module corresponding to the waypoint; the cleaning robot cleaning the corresponding photovoltaic module; and when cleaning is completed, sending an instruction to the target device to instruct the target device to carry the cleaning robot to the next waypoint after the first waypoint; wherein, when the cleaning agent in the cleaning robot is less than a first preset threshold, the target device replenishes the cleaning agent for the cleaning robot; and when the cleaning agent in the target device is less than a second preset threshold, the target device returns to a cleaning agent replenishment point to replenish the cleaning agent.

[0013] According to another aspect of the embodiments of this application, a photovoltaic module cleaning device is also provided, comprising: a first determining module, configured to determine 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; a second determining module, configured to determine the cleaning level and location information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of deposits on the surface of the photovoltaic modules; a third determining module, configured to determine a target cleaning route based on the cleaning level and location information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the movement route of a target device, the movement route has M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to 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; and a control module, configured to control the target device to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route.

[0014] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program is configured to execute the above-described cleaning method for photovoltaic modules when running.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described cleaning method for photovoltaic modules through the computer program.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program, which, when executed by a processor, performs the above-described method for cleaning photovoltaic modules.

[0017] This application determines the target cleaning route by identifying the cleanliness level and location information of the photovoltaic modules to be cleaned. Then, it controls a target device carrying a cleaning robot to clean the photovoltaic modules along the target cleaning route. Because the target device can carry a cleaning robot to clean the photovoltaic modules, it can clean high areas that are difficult to reach with traditional cleaning methods, improving the cleaning effect and solving the problem of low cleaning efficiency for photovoltaic modules. Furthermore, since the target device carries the cleaning robot to clean the photovoltaic modules, there is no need to deploy multiple cleaning robots, saving economic costs. Attached Figure Description

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

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a hardware structure block diagram of a mobile terminal for cleaning photovoltaic modules according to an embodiment of this application.

[0021] Figure 2 This is a flowchart of a photovoltaic module cleaning process according to an embodiment of this application;

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

[0023] Figure 4 This is a structural block diagram of a photovoltaic module cleaning device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort 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, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for cleaning photovoltaic modules according to an embodiment of this application. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor (MP) or a programmable gate array (FPGA)) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

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

[0028] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0029] To address the aforementioned issues, this embodiment provides a method for cleaning photovoltaic modules, including but not limited to applications in the aforementioned mobile terminal. Figure 2 This is a flowchart of a photovoltaic module cleaning process according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps S202-S208:

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

[0031] Step S204: Determine the cleanliness level and location information of the N photovoltaic modules, wherein the cleanliness level is used to indicate the content of deposits on the surface of the photovoltaic modules;

[0032] Optionally, the deposits on the surface of the photovoltaic module include, but are not limited to: snow, dust, and fallen leaves.

[0033] It should be noted that classifying the cleanliness level based on the amount of accumulated material helps to develop more reasonable cleaning strategies, such as prioritizing the cleaning of photovoltaic modules with severe dust accumulation.

[0034] Step S206: Determine the target cleaning route based on the cleaning level and location information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the movement route of the target device, the movement route has M waypoints, the target device places the 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;

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

[0036] Optionally, based on the cleanliness 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 fewest number of moves. The target cleaning route contains M waypoints, each waypoint corresponding to one or a group of photovoltaic modules to be cleaned. Among them, all photovoltaic modules in a group of photovoltaic modules corresponding to a waypoint are located in the same photovoltaic array.

[0037] Optionally, taking a mobile robot as the target device, the mobile robot will place the cleaning robot on one or a group of photovoltaic modules corresponding to the path points for cleaning based on the target cleaning route. When the cleaning agent is insufficient, the cleaning agent can be replenished to the cleaning robot 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 travel distance and time of the target equipment and the cleaning robot, thereby improving cleaning efficiency and economy. In addition, by replenishing the cleaning robot with cleaning agent through the target equipment, the cleaning robot can operate continuously without frequent returns to the resupply point, thus 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 move flexibly on the ground according to the planned target cleaning route to reach the designated photovoltaic module location for cleaning. This solves the limitation on the mobility of the cleaning robot caused by complex terrain (such as mountains and uneven ground), enabling the cleaning robot to be used more widely.

[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, to clean and maintain high-altitude photovoltaic modules, reducing reliance 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 enables automated cleaning that integrates ground and air, improving the overall performance and adaptability of the system. In addition, by having the target equipment carry the cleaning robots, the cleaning robots can be shared, which greatly reduces equipment procurement and maintenance costs compared to deploying a separate cleaning robot for each photovoltaic module or string.

[0043] The above steps determine the cleanliness level and location information of the photovoltaic modules to be cleaned, establish a target cleaning route, and then control the target equipment carrying a cleaning robot to clean the photovoltaic modules along the target cleaning route. Because the target equipment can carry a cleaning robot to clean the photovoltaic modules, it can clean high areas that are difficult to reach with traditional cleaning methods, improving the cleaning effect and thus solving the problem of low cleaning efficiency for photovoltaic modules. Furthermore, since the target equipment carries the cleaning robot to clean the photovoltaic modules, 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 can be achieved through the following steps S11-S12:

[0045] Step S11: Detect the power generation of the photovoltaic modules in the photovoltaic power plant during a first preset time period;

[0046] Optionally, after the illumination 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 plant within a first preset time period. During the first time period, the power generation 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 plant.

[0047] Step S12: Identify the photovoltaic modules in the photovoltaic power plant whose power generation is less than the preset power generation during the first preset time period, and obtain the N photovoltaic modules.

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

[0049] Optionally, when the average power generation of the a-th photovoltaic module in the photovoltaic power plant during the first preset time period is less than the first preset power generation, the photovoltaic module is identified as a photovoltaic module to be cleaned, where a is a positive integer; or,

[0050] When the total power generation of the a-th photovoltaic module in the photovoltaic power plant is less than the second preset power generation during the first preset time period, the photovoltaic module is identified as a photovoltaic module to be cleaned.

[0051] It should be noted that by comparing the average power generation of 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, thus avoiding unnecessary cleaning of modules in good condition. Based on the first preset power generation, the system can allocate cleaning resources more rationally, 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 declining power generation efficiency. Timely cleaning can prevent further deterioration of the power generation efficiency of these photovoltaic modules and help maintain the 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. This may be a signal of large-area dust accumulation or other serious faults. This step can more quickly identify photovoltaic modules that need emergency treatment. In addition, based on the judgment of the total power generation of the photovoltaic modules, the system can adjust the cleaning plan, prioritizing the cleaning of those photovoltaic modules that have the greatest impact on the overall power generation, thereby restoring the maximum power generation at 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 clean energy strategy matches the actual power generation demand.

[0054] In an exemplary embodiment, the cleanliness level of the N photovoltaic modules can be determined through the following steps S21-S22:

[0055] Step S21: Obtain infrared and visible light images of the N photovoltaic modules, and determine the surface texture entropy value of the N photovoltaic modules based on the infrared and visible light images of the N photovoltaic modules;

[0056] Optionally, after identifying N photovoltaic modules, a drone (equipped with a high-precision camera) is controlled to acquire infrared and visible light images of the N photovoltaic modules: First, the location information (such as latitude and longitude coordinates) of the N photovoltaic modules is connected in series to form a line to determine the target inspection route of the drone; second, the drone is controlled to perform inspection based on the target inspection route, and infrared and visible light images of the N photovoltaic modules are captured.

[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: Superimpose the infrared image with the first image weight and the visible light image with the second image weight corresponding to the i-th photovoltaic module among the N photovoltaic modules to obtain the target image, wherein the second image weight is usually greater than the first image weight;

[0059] For example, 20% of the infrared image can be overlaid with 80% of the visible light image.

[0060] Step S212: Convert 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 at a certain grayscale level in the grayscale image;

[0061] Step S213: Calculate the probability of occurrence of each gray level in the grayscale image based on the histogram, where the probability of occurrence 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] Where H(i) is the surface texture entropy value of the i-th photovoltaic module, and P(n) is the probability of the n-th gray level.

[0065] It should be noted that surface texture entropy is used to describe the complexity of image texture. In the field of photovoltaic energy cleaning, the surface texture entropy 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 of a photovoltaic module, the greater the amount of accumulated material on the surface of the photovoltaic module, and the more it needs to be cleaned.

[0066] Step S22: Determine the cleanliness level of the N photovoltaic modules based on the surface texture entropy values ​​of the N photovoltaic modules, wherein the cleanliness level of the i-th photovoltaic module among the N photovoltaic modules is determined based on the surface texture entropy value of the i-th photovoltaic module, 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 situation of the accumulated material on the surface of the photovoltaic module is automatically analyzed, and the cleaning level is intelligently determined to determine the cleaning sequence. This enables more efficient allocation of cleaning resources and reduces the impact of cleaning operations on the normal operation of the power station.

[0068] In an exemplary embodiment, the cleanliness level of the N photovoltaic modules is determined based on their surface texture entropy values. This can be achieved through the following steps: determining the cleanliness level of the i-th photovoltaic module through steps S31-S32 to obtain the cleanliness levels of the N photovoltaic modules:

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

[0070] Step S32: If the surface texture entropy value of the i-th photovoltaic module is within the target preset range of the plurality of preset ranges, the cleaning level corresponding to the target preset range is determined as the cleaning level of the i-th photovoltaic module.

[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 slightly high; 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 moderate; and 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 values ​​of photovoltaic modules under different conditions of accumulated material and the cleaning strategy of photovoltaic power plants. In addition, the image resolution, light source conditions, weather conditions, maintenance strategy of photovoltaic power plants, and cost-effectiveness must also be considered.

[0073] In an exemplary embodiment, determining the target cleaning route based on the cleanliness level and location information of the N photovoltaic modules can be achieved through the following steps S41-S44:

[0074] Step S41: Sort the N photovoltaic modules according to their cleanliness levels, and determine the first weight value of each of the N photovoltaic modules according to the sorting results;

[0075] Optionally, the N photovoltaic modules are sorted by their cleanliness level. The higher the cleanliness level of the photovoltaic module (e.g., the cleanliness level is "severe"), the higher it is in the sort. Then, a first weight value is assigned to each of the N photovoltaic modules according to this sorting result. The level of the first weight value reflects the urgency of the photovoltaic module to be cleaned. The photovoltaic module with a higher cleanliness level corresponds to a higher first weight value.

[0076] Step S42: Determine the distance between the N photovoltaic modules and the preset location based on the location information of the N photovoltaic modules, and determine the second weight value of each of the N photovoltaic modules based on the distance between the N photovoltaic modules and the preset location, wherein the preset location is the starting point of the target cleaning route;

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

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

[0079] It should be noted that steps S41 and S42 are not executed in any particular order.

[0080] Step S43: Determine the target weight value of each photovoltaic module based on the first weight value and the second weight value of each of the N photovoltaic modules;

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

[0082] Step S44: Determine the cleaning sequence of each photovoltaic module according to the target weight value of each photovoltaic module among the N photovoltaic modules, and determine the target cleaning route according to the cleaning sequence of each photovoltaic module.

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

[0084] It should be noted that the photovoltaic modules are reordered according to their target weight values, with modules having higher weight values ​​appearing earlier in the cleaning sequence, meaning they will be cleaned first. After determining the cleaning sequence, the system plans an optimal cleaning route, the target cleaning route, which will visit each photovoltaic module sequentially according to the cleaning order, ensuring the efficiency and continuity of the cleaning operation.

[0085] It should be noted that the above steps, by comprehensively considering the cleaning needs and actual locations of the components, achieve intelligent optimization of the cleaning operation. This not only improves the efficiency and effectiveness of cleaning but also reduces operation and maintenance costs, enhances equipment utilization, and improves the scientific nature and accuracy of operation and maintenance decisions. It has significant technical value for promoting the 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 modules 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 modules based on a target strategy; wherein, the target strategy includes: the target device moving to a first waypoint based on the target cleaning route; when the target device moves to the waypoint, placing the cleaning robot on the photovoltaic module corresponding to the waypoint; the cleaning robot cleaning the corresponding photovoltaic module; and upon completion of cleaning, sending an instruction to the target device to instruct the target device to carry the cleaning robot to the next waypoint; wherein, if the cleaning agent in the cleaning robot is less than a first preset threshold, the target device replenishes the cleaning agent for the cleaning robot; and if the cleaning agent in the target device is less than a second preset threshold, the target device returns to a cleaning agent replenishment point to replenish the cleaning agent.

[0087] Optionally, the system sends specific cleaning instructions to the target device, including the cleaning method for each photovoltaic module and the selection of cleaning agent. The target device and the cleaning robot jointly execute the cleaning task according to these instructions and the target cleaning route. Following the target cleaning route, the target device first moves to the location of the first photovoltaic module that needs cleaning, i.e., the first waypoint. A waypoint is a module location that the target device and the cleaning robot need to access during the task execution. Once the target device (such as a mobile robot) reaches the waypoint, it places the cleaning robot on the corresponding photovoltaic module, and the cleaning robot then begins cleaning the module.

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

[0089] Optionally, the cleaning robot consumes cleaning agent during the cleaning process. When the remaining amount of cleaning agent is lower than a set first threshold, the target device will automatically replenish the cleaning agent to ensure that the cleaning robot can continue to operate. The target device (such as a mobile robot) also carries its own cleaning agent. When its cleaning agent is lower than a second preset threshold, the target device returns to the cleaning agent replenishment point to replenish it, so as to avoid the interruption of operation due to the depletion of resources during the cleaning process.

[0090] It should be noted that by implementing the above steps, the cleaning operation of photovoltaic modules can be carried out efficiently in a predetermined order and path. At the same time, through dynamic management and replenishment of resources, the continuous operation capability of the cleaning equipment is guaranteed, avoiding resource waste and interruption of cleaning tasks. This not only improves cleaning efficiency but also reduces operation and maintenance costs, demonstrating 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 the predetermined standards; and simultaneously, performing quality control on the cleaning process to identify and correct potential problems in the cleaning process.

[0092] Obviously, the embodiments described above are merely some embodiments of the present invention, and not all embodiments. To better understand the above method, the following description, in conjunction with embodiments, illustrates the process, but is not intended to limit the technical solutions of the embodiments of the present invention. Figure 3 The diagram illustrates an overall process flow for cleaning a photovoltaic module according to an embodiment of the application. Specifically:

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

[0094] 2. After the power generation of photovoltaic modules stabilizes for one hour after sunrise each day, determine which photovoltaic modules are inefficient based on their power generation efficiency.

[0095] Third, conduct flight path planning, connect all inefficient photovoltaic modules into an inspection and confirmation flight path; automatically import the flight path into the hangar, issue instructions through the hangar to conduct inspections via drones, take visible light and infrared images of all modules in the above-mentioned inefficient string, and identify which photovoltaic modules are inefficient due to dust accumulation.

[0096] 4. Determine the dust accumulation status of each 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 needs to be graded and marked as severe, general, or slight.

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

[0098] 6. The mobile robot identifies the cleaning robot through the camera at the end of the gripper and grabs it with the matching gripper on the gripper. Then, it carries the cleaning robot to the photovoltaic module to be cleaned according to the planned cleaning path. The telescopic gripper places the cleaning robot on the photovoltaic module for cleaning.

[0099] 7. The mobile robot is equipped with a water tank. When the water in the cleaning robot runs out, the mobile robot can directly replenish the water supply to the cleaning robot. After replenishing the water, the mobile robot returns to the water supply pool to pump water to replenish the water tank.

[0100] 8. After the cleaning robot finishes cleaning the nearby photovoltaic modules that can be cleaned, it sends a command to the mobile robot, which then picks up the cleaning robot and takes it to the next planned module to be cleaned.

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

[0102] 10. After cleaning is completed, the cleaning effect is judged again by the power generation. If there are still suspected dust accumulation and inefficient strings, the background will automatically plan the inspection route, then import the route into the hangar, and then send out a drone from the hangar to inspect and 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 where mobile robots cannot pass, drones carrying grippers will be 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, and drone used are all mature products on the market, and the stability of the whole 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 site with only one cleaning robot. Millimeter-wave radar can quickly scan the moving objects in the surrounding environment, unlike visible light and other image inspection modes that require point-by-point collection and judgment; (3) Good adaptability. It can be used to test different terrains such as mountains and plains, as well as the cleaning needs of centralized and distributed photovoltaic sites; (4) Good cleaning continuity. An important problem of photovoltaic automated cleaning is that drones and small cleaning robots have limited water carrying capacity, and mobile robots have poor cleaning effect on high-altitude photovoltaics. This solution effectively realizes the efficient cleaning of photovoltaics by making effective use of the advantages of various intelligent equipment.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0106] This embodiment also provides a photovoltaic module cleaning device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0107] Figure 4 This is a structural block diagram of a photovoltaic module cleaning device according to an embodiment of this application. The device includes:

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

[0109] The second determining module 404 is used to determine the cleanliness level and location information of the N photovoltaic modules, wherein the cleanliness level is used to indicate the content of deposits on the surface of the photovoltaic modules;

[0110] The third determining module 406 is used to determine a target cleaning route based on the cleaning level and location information of the N photovoltaic modules. The target cleaning route is used to indicate the movement route of the target device. The movement route has M waypoints. At each of the M waypoints, the target device places a cleaning robot on the photovoltaic module corresponding to that waypoint. The cleaning robot is used to clean the photovoltaic modules. The target device allows the cleaning robot to be replenished with cleaning agent. 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 modules based on the target cleaning route.

[0112] The aforementioned device determines the target cleaning route by identifying the cleanliness level and location information of the photovoltaic modules to be cleaned. It then controls a target device carrying a cleaning robot to clean the photovoltaic modules along this route. Because the target device can carry the cleaning robot, it can clean high areas that are difficult to reach with traditional cleaning methods, improving the cleaning effect and solving the problem of low cleaning efficiency for photovoltaic modules. Furthermore, since the target device carries the cleaning robot, there is no need to deploy multiple cleaning robots, saving economic costs.

[0113] In an exemplary embodiment, the first determining module 402 is further configured to detect the power generation of photovoltaic modules in the photovoltaic power plant within a first preset time period; and to determine the photovoltaic modules in the photovoltaic power plant whose power generation is less than a preset power generation within the first preset time period, thereby obtaining the N photovoltaic modules.

[0114] In an exemplary embodiment, the second determining module 404 is further configured to acquire infrared images and visible light images of the N photovoltaic modules, and determine the surface texture entropy value of the N photovoltaic modules based on the infrared images and visible light images of the N photovoltaic modules; and determine the cleanliness level of the N photovoltaic modules based on the surface texture entropy value of the N photovoltaic modules, wherein the cleanliness level of the i-th photovoltaic module among the N photovoltaic modules is determined based on the surface texture entropy value of the i-th photovoltaic module, and i is a positive integer less than or equal to N.

[0115] In an exemplary embodiment, the second determining module 404 is further configured to determine the cleanliness level of the i-th photovoltaic module to obtain the cleanliness levels of the N photovoltaic modules by: determining the 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 cleanliness level; and determining the cleanliness level corresponding to the target preset range as the cleanliness level of the i-th photovoltaic module when the surface texture entropy value of the i-th photovoltaic module is located within a target preset range in the plurality of preset ranges.

[0116] In an exemplary embodiment, the third determining module 406 is further configured to: sort the N photovoltaic modules according to their cleaning levels; determine a first weight value for each of the N photovoltaic modules based on the sorting results; determine the distance between the N photovoltaic modules and a preset location based on the location information of the N photovoltaic modules; determine a second weight value for each of the N photovoltaic modules based on the distance between the N photovoltaic modules and the preset location, wherein the preset location is the starting point of the target cleaning route; determine a target weight value for each photovoltaic module based on the first weight value and the second weight value of each of the N photovoltaic modules; determine the cleaning order of each photovoltaic module based on the target weight value of each of the N photovoltaic modules; and determine the target cleaning route based on the cleaning order of each photovoltaic module.

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

[0118] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

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

[0120] S1, determine N photovoltaic modules from the photovoltaic power plant, wherein the N photovoltaic modules are modules to be cleaned, and N is an integer greater than or equal to 1;

[0121] S2, determine the cleanliness level and location information of the N photovoltaic modules, wherein the cleanliness level is used to indicate the content of deposits on the surface of the photovoltaic modules;

[0122] S3, determine the target cleaning route based on the cleaning level and location information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the movement route of the target device, the movement route has M waypoints, the target device places the 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 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, control the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route.

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

[0125] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0126] Embodiments of this application also provide a computer program product, including a computer program, wherein the computer program, when executed by a processor, performs the steps in any of the above method embodiments.

[0127] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

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

[0129] S1, determine N photovoltaic modules from the photovoltaic power plant, wherein the N photovoltaic modules are modules to be cleaned, and N is an integer greater than or equal to 1;

[0130] S2, determine the cleanliness level and location information of the N photovoltaic modules, wherein the cleanliness level is used to indicate the content of deposits on the surface of the photovoltaic modules;

[0131] S3, determine the target cleaning route based on the cleaning level and location information of the N photovoltaic modules, wherein the target cleaning route is used to indicate the movement route of the target device, the movement route has M waypoints, the target device places the 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 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, control the target device to carry the cleaning robot to clean N photovoltaic modules based on the target cleaning route.

[0133] In one 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] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0135] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0136] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of cleaning a photovoltaic module, characterized by, The method comprises the following steps: determining N photovoltaic modules from a photovoltaic power plant, wherein the N photovoltaic modules are to be cleaned, N is an integer greater than or equal to 1; determining the cleaning level and position information of the N photovoltaic modules, wherein the cleaning level is used to indicate the content of the accumulated matter on the surface of the photovoltaic module; determining a target cleaning route according to the cleaning level 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 way points, the target device places a cleaning robot on the photovoltaic module corresponding to each way point in the M way points, the cleaning robot is used to clean the photovoltaic module, the target device allows the cleaning robot to be supplemented with cleaning agent, and M is 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; wherein determining the target cleaning route according to the cleaning level and position information of the N photovoltaic modules comprises: sorting the cleaning level of the N photovoltaic modules, and determining a first weight value of each photovoltaic module in the N photovoltaic modules according to the sorting result; and determining the distance between the N photovoltaic modules and a preset position according to the position information of the N photovoltaic modules, and determining a second weight value of each photovoltaic module in the N photovoltaic modules according to the distance between the N photovoltaic modules and the preset position, wherein the preset position is the starting point of the target cleaning route; determining a target weight value of each photovoltaic module in the N photovoltaic modules according to the first weight value and the second weight value of each photovoltaic module in the N photovoltaic modules; determining the cleaning sequence of each photovoltaic module according to the target weight value of each photovoltaic module in the N photovoltaic modules, and determining the target cleaning route according to the cleaning sequence of each photovoltaic module; wherein determining the cleaning level of the N photovoltaic modules comprises: 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 the visible light images of the N photovoltaic modules; determining the cleaning level of the N photovoltaic modules according to the surface texture entropy values of the N photovoltaic modules, wherein the cleaning level of the i-th photovoltaic module in the N photovoltaic modules is determined according to the surface texture entropy value of the i-th photovoltaic module, i is a positive integer less than or equal to N.

2. The method of claim 1, wherein, Determining N photovoltaic modules from a photovoltaic power plant comprises: detecting the power generation power of the photovoltaic modules in the photovoltaic power plant within a first preset time period; determining the photovoltaic modules with power generation power less than a preset power generation power from the photovoltaic power plant within the first preset time period to obtain the N photovoltaic modules.

3. The method of claim 1, wherein, Determining the cleaning level of the N photovoltaic modules according to the surface texture entropy values of the N photovoltaic modules comprises: determining the cleaning level of the i-th photovoltaic module in the following manner to obtain the cleaning level of the N photovoltaic modules: determine a relationship between the surface texture entropy value of the ith photovoltaic module and a plurality of preset ranges, wherein each preset range in the plurality of preset ranges corresponds to a cleaning level; in a case where the surface texture entropy value of the ith photovoltaic module is located in a target preset range in the plurality of preset ranges, determine the cleaning level corresponding to the target preset range as the cleaning level of the ith photovoltaic module.

4. The method of claim 1, wherein, control the target device to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route, including: sending the target cleaning route to the target device, and instructing the target device and the cleaning robot to clean the N photovoltaic modules based on a target strategy; wherein the target strategy includes: the target device moving to a first way point based on the target cleaning route, in a case where the target device moves to the way point, placing the cleaning robot on the photovoltaic module corresponding to the way point, the cleaning robot cleaning the corresponding photovoltaic module, and in a case where the cleaning is completed, sending an instruction to the target device to instruct the target device to carry the cleaning robot to move to a next way point of the first way point; wherein in a case where the cleaning agent of the cleaning robot is less than a first preset threshold, the target device supplements the cleaning agent for the cleaning robot, and in a case where the cleaning agent in the target device is less than a second preset threshold, the target device returns to a cleaning agent supplement point to supplement the cleaning agent.

5. A cleaning device for photovoltaic modules, characterized in that including: a first determination module configured to determine N photovoltaic modules from a photovoltaic power plant, wherein the N photovoltaic modules are to be cleaned, and N is an integer greater than or equal to 1; a second determination module configured to determine cleaning levels and position information of the N photovoltaic modules, wherein the cleaning levels are used to indicate the content of the surface of the photovoltaic modules; a third determination module configured to determine a target cleaning route according to the cleaning levels and the 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 way points, the target device places a cleaning robot on a photovoltaic module corresponding to each way point in the M way points, the cleaning robot is used to clean the photovoltaic module, and the target device allows the cleaning robot to supplement a cleaning agent, and M is a positive integer less than or equal to N; a control module configured to control the target device to carry the cleaning robot to clean the N photovoltaic modules based on the target cleaning route. The third determining module is further configured to sort the cleaning levels of the N photovoltaic components, determine a first weight value of each of the N photovoltaic components according to a sorting result, determine distances between the N photovoltaic components and a preset position according to position information of the N photovoltaic components, and determine a second weight value of each of the N photovoltaic components according to the distances between the N photovoltaic components and the preset position, wherein the preset position is a starting point of the target cleaning route; determine a 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 a cleaning sequence of each of the N photovoltaic components according to the target weight value of each of the N photovoltaic components, and determine the target cleaning route according to the cleaning sequence of each of the N photovoltaic components. The second determining module is further configured to acquire infrared images and visible light images of the N photovoltaic components, determine surface texture entropy values of the N photovoltaic components according to the infrared images and the visible light images of the N photovoltaic components, and determine the cleaning levels of the N photovoltaic components according to the surface texture entropy values of the N photovoltaic components, wherein a cleaning level of an ith photovoltaic component in the N photovoltaic components is determined according to a surface texture entropy value of the ith photovoltaic component, and i is a positive integer less than or equal to N.

6. A computer readable storage medium, characterized in that, The computer readable storage medium comprises a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 4. 7.An electronic device comprising a memory and a processor, the electronic device characterized by, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 4 by using the computer program.

8. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the method of any one of claims 1 to 4. The computer program, when executed by the processor, implements the method of any one of claims 1 to 4.

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