Cleaning path planning method and related device
By constructing a two-dimensional photovoltaic module map and cleaning path planning, the problem of photovoltaic cleaning robots missing or repeated cleaning in complex arrays is solved, achieving more efficient cleaning effects and efficiency.
Patent Information
- Application Number
- CN202510525746.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-24
- Publication Date
- 2025-08-01
AI Technical Summary
When planning the cleaning path, existing photovoltaic cleaning robots are prone to leakage or repeated cleaning, resulting in unsatisfactory cleaning results and low efficiency, especially in complex irregular photovoltaic arrays.
By obtaining photovoltaic site data, determining the boundaries and component layout of the photovoltaic array, building a two-dimensional photovoltaic module map, and combining the cleaning path constraints, a target cleaning path is generated to ensure that the cleaning path conforms to the actual environment.
It effectively avoids missed sweeping or repeated sweeping, improves cleaning efficiency and effect, reduces unreasonable sweeping paths, and improves the power generation efficiency of photovoltaic arrays.
Smart Images
Figure CN120406447A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of photovoltaic power generation, and more specifically, to a cleaning path planning method and related devices. Background Art
[0002] With the accelerating promotion of the global clean energy transformation, photovoltaic power generation systems have been widely used in various scenarios such as industrial and commercial rooftops, agricultural-photovoltaic complementary, and large-scale ground power stations. However, foreign matters such as dust on the surface of photovoltaic modules significantly reduce the power generation efficiency of the photovoltaic array. Therefore, the cleaning and maintenance of the photovoltaic array have become a key link to ensure the power generation efficiency.
[0003] To improve the power generation efficiency of the photovoltaic array, existing solutions use photovoltaic cleaning robots to clean foreign matters such as dust on the surface of photovoltaic modules. Existing photovoltaic cleaning robots usually plan the cleaning path according to the boundary of the photovoltaic array. However, the actual layout of photovoltaic modules in the photovoltaic array is relatively complex. Planning the cleaning path only according to the boundary of the photovoltaic array is likely to be out of touch with the actual layout of the photovoltaic array, resulting in unreasonable cleaning path planning. Especially in a complex and irregular photovoltaic array, it is easy to miss cleaning or repeat cleaning, resulting in unsatisfactory cleaning effect and low cleaning efficiency. Summary of the Invention
[0004] In view of this, the present invention discloses a cleaning path planning method and related devices to reasonably plan the cleaning path, avoid missing cleaning or repeat cleaning, ensure the cleaning effect, and improve the cleaning efficiency.
[0005] A cleaning path planning method includes:
[0006] Obtaining photovoltaic site data;
[0007] Determining the boundary of the photovoltaic array based on the photovoltaic site data;
[0008] Determining the layout of the photovoltaic array based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the boundary of the photovoltaic array;
[0009] Creating a basic map of the photovoltaic site based on the photovoltaic site data, and combining the basic map of the photovoltaic site with the layout of the photovoltaic array to construct a two-dimensional photovoltaic module map;
[0010] Obtaining a target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
[0011] Optionally, determining the boundary of the photovoltaic array based on the photovoltaic site data includes:
[0012] Based on the coordinates of the four vertices of the photovoltaic array in the photovoltaic site data, calculate the vectors of two adjacent sides for each vertex.
[0013] Based on the vectors of two adjacent sides for each vertex, calculate the normal vector for each vertex, and normalize the normal vector to obtain the corresponding target normal vector.
[0014] Calculate the average of the four target normal vectors of the photovoltaic array to obtain the average normal vector.
[0015] Based on the average normal vector and the geometric parameters of the photovoltaic array, obtain the vertex offset.
[0016] Offset the original boundary points of the photovoltaic array according to the vertex offset to obtain the latest boundary points.
[0017] Connect the respective latest boundary points to obtain the boundary of the photovoltaic array.
[0018] Optionally, determine the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the boundary of the photovoltaic array, including:
[0019] Create uniformly distributed grid sampling points within each photovoltaic module area.
[0020] Determine the target grid sampling points located within the boundary of the photovoltaic array among all the grid sampling points in each photovoltaic module area.
[0021] Calculate the sampling point ratio of all the target grid sampling points among all the grid sampling points in the corresponding photovoltaic module area.
[0022] In the case where the sampling point ratio reaches the sampling point ratio threshold, if the center point of the photovoltaic module in the photovoltaic module area is located within the boundary of the photovoltaic array, determine that the corresponding target photovoltaic module in the photovoltaic module area is located within the boundary of the photovoltaic array, and determine the photovoltaic module orientation information.
[0023] According to the photovoltaic module positions adapted to all the target photovoltaic modules within the boundary of the photovoltaic array and the corresponding photovoltaic module orientation information, determine the number of photovoltaic modules installed within the boundary of the photovoltaic array and the arrangement mode of the photovoltaic modules to obtain the photovoltaic array layout.
[0024] Optionally, according to the photovoltaic module positions adapted to all the target photovoltaic modules within the boundary of the photovoltaic array and the corresponding photovoltaic module orientation information, determine the number of photovoltaic modules installed within the boundary of the photovoltaic array and the arrangement mode of the photovoltaic modules to obtain the photovoltaic array layout, including:
[0025] Determine the number of photovoltaic modules installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules based on the positions of all the target photovoltaic modules adapted within the photovoltaic array boundary and the corresponding photovoltaic module orientation information, to obtain an initial photovoltaic array layout;
[0026] Output the initial photovoltaic array layout to a visualization interface for display;
[0027] Obtain an array arrangement direction switching instruction input by a user on the visualization interface;
[0028] Based on the array arrangement direction switching instruction, adjust the array arrangement direction of the initial photovoltaic array layout to obtain the photovoltaic array layout.
[0029] Optionally, create a basic photovoltaic site map based on the photovoltaic site data, and combine the basic photovoltaic site map with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, including:
[0030] Create the basic photovoltaic site map based on the photovoltaic site data;
[0031] Locate the key information of each photovoltaic module in the photovoltaic array layout on the basic photovoltaic site map to obtain a photovoltaic site map;
[0032] Add attribute information to each photovoltaic module on the photovoltaic site map and establish a topological relationship between the photovoltaic modules to obtain the two-dimensional photovoltaic module map.
[0033] Optionally, the attribute information includes: a unique position number associated with each photovoltaic module, and the numbering rule of the unique position number is: power station number_array number_row number_column number.
[0034] Optionally, based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions, obtain a target cleaning path, including:
[0035] Obtain a photovoltaic module arrangement matrix based on the unique position numbers of each photovoltaic module in the two-dimensional photovoltaic module map;
[0036] Based on the photovoltaic module arrangement matrix and the cleaning operation area, plan a feasible cleaning path to obtain an initial cleaning path;
[0037] Adjust the initial cleaning path based on the cleaning path constraint conditions to obtain the target cleaning path, where the cleaning path constraint conditions include: photovoltaic module arrangement, cleaning efficiency optimization path, energy consumption of the photovoltaic cleaning robot, and actual photovoltaic module cleaning conditions.
[0038] A cleaning path planning device, comprising:
[0039] A data acquisition unit for acquiring photovoltaic site data;
[0040] An array boundary determination unit for determining a photovoltaic array boundary based on the photovoltaic site data;
[0041] An array layout determination unit for determining a photovoltaic array layout based on grid sampling points within each photovoltaic module area and the positional relationship between the center points of the photovoltaic modules and the photovoltaic array boundary;
[0042] A photovoltaic module map determination unit for creating a basic map of the photovoltaic site based on the photovoltaic site data and combining the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map;
[0043] A cleaning path planning unit for obtaining a target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
[0044] A computer storage medium storing at least one instruction, where when the at least one instruction is executed by a processor, any one of the cleaning path planning methods is implemented.
[0045] A photovoltaic cleaning robot, the photovoltaic cleaning robot comprising: a memory and a processor;
[0046] The memory is used for storing at least one instruction;
[0047] The processor is used for executing the at least one instruction to implement any one of the cleaning path planning methods.
[0048] As can be seen from the above technical solutions, the present invention discloses a cleaning path planning method and related devices, which obtain photovoltaic site data, determine the photovoltaic array boundary based on the photovoltaic site data, determine the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary, create a basic map of the photovoltaic site based on the photovoltaic site data, and combine the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, and obtain the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions. Through the photovoltaic array boundary, the cleaning area range is initially determined. When determining the photovoltaic array layout, the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary are considered. Therefore, the actual position of the photovoltaic module can be more accurately reflected, avoiding the rough division relying only on the photovoltaic array boundary. By combining the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, and generating the final target cleaning path in combination with the cleaning path constraint conditions, the position information of the actual photovoltaic module is converted into map data, enabling the cleaning path planning to be determined based on more detailed information, thereby effectively avoiding the situation of missed cleaning or repeated cleaning. The limitation of the cleaning path constraint conditions makes the generated target cleaning path more in line with the actual environment, effectively reducing unreasonable cleaning paths, ensuring the cleaning effect, and improving the cleaning efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the disclosed drawings without creative efforts.
[0050] Figure 1 It is a flowchart of a cleaning path planning method disclosed in an embodiment of the present invention;
[0051] Figure 2 It is a flowchart of a method for determining the photovoltaic array boundary based on photovoltaic site data disclosed in an embodiment of the present invention;
[0052] Figure 3(1) is a schematic diagram of a single photovoltaic module placed longitudinally disclosed in an embodiment of the present invention;
[0053] Figure 3(2) is a schematic diagram of a single photovoltaic module placed horizontally disclosed in an embodiment of the present invention;
[0054] Figure 4(1) is a schematic diagram of an interactive photovoltaic array arranged longitudinally disclosed in an embodiment of the present invention;
[0055] Figure 4(2) is a schematic diagram of the horizontal arrangement of an interactive photovoltaic array disclosed in an embodiment of the present invention;
[0056] Figure 5 It is a schematic diagram of a two-dimensional photovoltaic module map disclosed in an embodiment of the present invention;
[0057] Figure 6 It is a schematic diagram of the target cleaning path of a photovoltaic cleaning robot disclosed in an embodiment of the present invention;
[0058] Figure 7 It is a schematic diagram of the structure of a cleaning path planning device disclosed in an embodiment of the present invention;
[0059] Figure 8 It is a schematic diagram of the structure of a photovoltaic cleaning robot disclosed in an embodiment of the present invention. Detailed implementation manners
[0060] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0061] An embodiment of the present invention discloses a cleaning path planning method and related devices. The cleaning area range is initially determined through the photovoltaic array boundary. When determining the photovoltaic array layout, the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary are considered. Therefore, the actual positions of the photovoltaic modules can be more accurately reflected, avoiding the rough division relying only on the photovoltaic array boundary. By combining the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map and generating the final target cleaning path in combination with the cleaning path constraint conditions, the position information of the actual photovoltaic modules is converted into map data, enabling the cleaning path planning to be determined based on more detailed information, thereby effectively avoiding the situation of missed cleaning or repeated cleaning. The limitation of the cleaning path constraint conditions makes the generated target cleaning path more in line with the actual environment, effectively reducing unreasonable cleaning paths, ensuring the cleaning effect, and improving the cleaning efficiency.
[0062] Refer to Figure 1 , a flowchart of a cleaning path planning method disclosed in an embodiment of the present application. The method includes:
[0063] Step S101, obtain photovoltaic site data.
[0064] In practical applications, photovoltaic site data can be obtained through RTK (Real-Time Kinematic). The photovoltaic site data may include: photovoltaic array area, apron area for photovoltaic cleaning robots, bridge area, restricted area, etc. The photovoltaic array area contains the coordinates of the four vertices in the photovoltaic array.
[0065] Step S102: Determine the photovoltaic array boundary based on the photovoltaic site data.
[0066] For precise issues such as the frames of photovoltaic modules and the installation gaps between adjacent photovoltaic modules, this application uses an adaptive boundary recognition algorithm for the photovoltaic site data to determine the photovoltaic array boundary, providing accurate spatial constraints for subsequent photovoltaic module layout.
[0067] Step S103: Determine the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary.
[0068] This application creates grid sampling points within each photovoltaic module area, combines the sampling point ratio of the grid sampling points contained within the photovoltaic array boundary and the position of the center point of the photovoltaic module, realizes the adaptability evaluation of the photovoltaic module to the photovoltaic array boundary, ensures the rationality of the photovoltaic array layout within the photovoltaic array boundary, and improves the space utilization rate of the area within the photovoltaic array boundary.
[0069] Step S104: Create a basic photovoltaic site map based on the photovoltaic site data, and combine the basic photovoltaic site map with the photovoltaic array layout to construct a two-dimensional photovoltaic module map.
[0070] In practical applications, this application adopts the technology of digital twin photovoltaic map construction for photovoltaic power plants, combines the created basic photovoltaic site map with the photovoltaic array layout, so that the created two-dimensional photovoltaic module map not only contains the precise position information of the photovoltaic modules, but also integrates multi-dimensional data such as the orientation and size of the photovoltaic modules, forming a complete digital management framework for photovoltaic power plants.
[0071] Step S105: Obtain the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
[0072] Among them, the set cleaning path constraint conditions include but are not limited to: photovoltaic module arrangement, cleaning efficiency optimization path, energy consumption of photovoltaic cleaning robots, and actual cleaning conditions of photovoltaic modules, etc.
[0073] The cleaning efficiency optimization path includes: minimizing the path length and the number of turns, etc.
[0074] Energy consumption of a photovoltaic cleaning robot. For example, the energy consumption of a photovoltaic cleaning robot during cleaning along the target cleaning path does not exceed the set energy value.
[0075] In summary, the present application discloses a cleaning path planning method, which obtains photovoltaic site data, determines the boundary of a photovoltaic array based on the photovoltaic site data, determines the layout of the photovoltaic array based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the boundary of the photovoltaic array, creates a basic map of the photovoltaic site based on the photovoltaic site data, and combines the basic map of the photovoltaic site with the layout of the photovoltaic array to construct a two-dimensional photovoltaic module map, and obtains the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions. In the present application, the cleaning area range is initially determined by the boundary of the photovoltaic array. When determining the layout of the photovoltaic array, the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the boundary of the photovoltaic array are considered. Therefore, the actual position of the photovoltaic module can be more accurately reflected, avoiding the rough division relying only on the boundary of the photovoltaic array. By combining the basic map of the photovoltaic site with the layout of the photovoltaic array to construct a two-dimensional photovoltaic module map, and generating the final target cleaning path in combination with the cleaning path constraint conditions, the position information of the actual photovoltaic module is converted into map data, enabling the cleaning path planning to be determined based on more detailed information, thus effectively avoiding the situation of missed cleaning or repeated cleaning. The limitation of the cleaning path constraint conditions makes the generated target cleaning path more in line with the actual environment, effectively reducing unreasonable cleaning paths, ensuring the cleaning effect, and improving the cleaning efficiency.
[0076] In one embodiment, refer to Figure 2 , the flowchart of a method for determining the boundary of a photovoltaic array based on photovoltaic site data disclosed in an embodiment of the present application. The method includes:
[0077] Step S201: Calculate the vectors of two adjacent sides of each vertex based on the coordinates of the four vertices of the photovoltaic array in the photovoltaic site data.
[0078] For the four vertices of the photovoltaic array, traverse each vertex and calculate the vectors of two adjacent sides of each vertex.
[0079] Assume that the four vertices of the photovoltaic array are arranged in a clockwise or counterclockwise order as P1, P2, P3, and P4, forming a closed quadrilateral. The adjacent vertices of each vertex are determined by the order. The adjacent vertices of P1 are P2 and P4, the adjacent vertices of P2 are P1 and P3, the adjacent vertices of P3 are P2 and P4, and the adjacent vertices of P4 are P3 and P1.
[0080] The process of calculating the vectors of two adjacent sides of each vertex is exemplified as follows:
[0081] Assume that the photovoltaic array is a rectangular array, and the coordinates of the four vertices are:
[0082] P1(0, 0), P2(5, 0), P3(5, 3), P4(0, 3).
[0083] ① The vectors of two adjacent sides of P1(0, 0) are as follows:
[0084] Vector 1 (P1→P2): (5 - 0, 0 - 0) = (5, 0)
[0085] Vector 2 (P1→P4): (0 - 0, 3 - 0) = (0, 3)
[0086] ② The vectors of two adjacent sides of P2(5, 0) are as follows:
[0087] Vector 1 (P2→P1): (0 - 5, 0 - 0) = (-5, 0)
[0088] Vector 2 (P2→P3): (5 - 5, 3 - 0) = (0, 3)
[0089] ③ The vectors of two adjacent sides of P3(5, 3) are as follows:
[0090] Vector 1 (P3→P2): (5 - 5, 0 - 3) = (0, -3)
[0091] Vector 2 (P3→P4): (0 - 5, 3 - 3) = (-5, 0)
[0092] ④ The vectors of two adjacent sides of P4(0, 3) are as follows:
[0093] Vector 1 (P4→P3): (5 - 0, 3 - 3) = (5, 0)
[0094] Vector 2 (P4→P1): (0 - 0, 0 - 3) = (0, -3)
[0095] Step S202: Calculate the normal vector of each vertex based on the vectors and normalize the normal vector to obtain the corresponding target normal vector.
[0096] By taking the cross product of the vectors of two adjacent sides of each vertex, the normal vector of the corresponding vertex is obtained. Normalizing the normal vector ensures that the length of the normal vector is 1, making it a unit vector.
[0097] Step S203: Average the four target normal vectors of the photovoltaic array to obtain the average normal vector.
[0098] By averaging the four target normal vectors of the photovoltaic array, a unit vector representing the overall orientation of the photovoltaic array can be obtained, and this unit vector is also the average normal vector.
[0099] Step S204. Obtain the vertex offset based on the average normal vector and the photovoltaic array geometric parameters.
[0100] Among them, the photovoltaic array geometric parameters include the thickness of the photovoltaic module frame, the horizontal / vertical spacing between adjacent photovoltaic modules, the projection spacing between the front and rear rows of photovoltaic modules, etc.
[0101] Considering that the vertex positions of the photovoltaic array may require a larger offset to maintain the photovoltaic array geometric parameters such as the thickness of the photovoltaic module frame, the horizontal / vertical spacing between adjacent photovoltaic modules, and the projection spacing between the front and rear rows of photovoltaic modules, this application uses the photovoltaic array geometric parameters as the boundary constraints of the photovoltaic module, adjusts the normal vector direction represented by the average normal vector, and obtains the vertex offset that meets the actual installation constraints of the photovoltaic array.
[0102] Step S205. Offset the original boundary points of the photovoltaic array according to the vertex offset to obtain the latest boundary points.
[0103] Step S206. Connect each of the latest boundary points to obtain the photovoltaic array boundary.
[0104] The finally determined photovoltaic array boundary in this application takes into account the photovoltaic array geometric parameters such as the thickness of the photovoltaic module frame, the horizontal / vertical spacing between adjacent photovoltaic modules, and the projection spacing between the front and rear rows of photovoltaic modules. Therefore, it can provide accurate spatial constraints for the subsequent layout of photovoltaic modules.
[0105] In summary, based on the coordinates of the four vertices of the photovoltaic array in the photovoltaic site data, this application calculates the vectors of two adjacent sides of each vertex, then calculates the normal vector of each vertex based on the vectors of two adjacent sides of each vertex, normalizes the normal vector to obtain the corresponding target normal vector, calculates the average of the four target normal vectors of the photovoltaic array to obtain the average normal vector, obtains the vertex offset based on the average normal vector and the photovoltaic array geometric parameters, offsets the original boundary points of the photovoltaic array according to the vertex offset to obtain the latest boundary points, and connects each of the latest boundary points to obtain the photovoltaic array boundary. The calculation process of the adaptive photovoltaic array boundary based on vector analysis provided by this application can achieve accurate modeling of the photovoltaic array by calculating the vectors of two adjacent sides of each vertex of the photovoltaic array, calculating the normal vector of the vertex based on the vector and performing normalization processing, can automatically identify the geometric characteristics of the photovoltaic array boundary, and can dynamically adjust the photovoltaic array geometric parameters such as the thickness of the photovoltaic module frame, the horizontal / vertical spacing between adjacent photovoltaic modules, and the projection spacing between the front and rear rows of photovoltaic modules according to the installation requirements, ensuring a high degree of consistency between the virtual design and the actual installation of the photovoltaic array.
[0106] In one embodiment, step S103 may specifically include:
[0107] (1) Create uniformly distributed grid sampling points within each photovoltaic module area.
[0108] In practical applications, uniformly distributed high-density grid sampling points can be created within each photovoltaic module area.
[0109] Each photovoltaic module area includes: the space occupied by a single photovoltaic module, and a partial gap between this photovoltaic module and adjacent photovoltaic modules, for example, half of the gap between adjacent photovoltaic modules.
[0110] (2) Determine the target grid sampling points located within the boundary of the photovoltaic array among all the grid sampling points in each photovoltaic module area.
[0111] Successively determine whether each grid sampling point in each photovoltaic module area is located within the boundary of the photovoltaic array, and determine the grid sampling points located within the boundary of the photovoltaic array as target grid sampling points.
[0112] (3) Calculate the sampling point ratio of all the target grid sampling points in the corresponding photovoltaic module area among all the grid sampling points in the photovoltaic module area.
[0113] For each photovoltaic module area, calculate the ratio of all the target grid sampling points located within the boundary of the photovoltaic array to all the grid sampling points in this photovoltaic module area to obtain the sampling point ratio.
[0114] (4) When the sampling point ratio reaches the sampling point ratio threshold, if the center point of the photovoltaic module in the photovoltaic module area is located within the boundary of the photovoltaic array, determine that the target photovoltaic module corresponding to the photovoltaic module area is located within the boundary of the photovoltaic array, and determine the photovoltaic module orientation information.
[0115] Among them, the value of the sampling point ratio threshold is determined according to actual needs, for example, 0.85, which is not limited in this application.
[0116] When the sampling point ratio corresponding to the photovoltaic module area reaches the sampling point ratio threshold, continue to determine whether the center point of the photovoltaic module in this photovoltaic module area is located within the boundary of the photovoltaic array. When it is determined that the center point of the photovoltaic module is located within the boundary of the photovoltaic array, determine that the target photovoltaic module corresponding to the photovoltaic module area is located within the photovoltaic array. At this time, the position of the photovoltaic module area within the boundary of the photovoltaic array is the position of the corresponding target photovoltaic module adapted within the boundary of the photovoltaic array. Therefore, this method can accurately evaluate whether any photovoltaic module is suitable for placement at a specific position.
[0117] The photovoltaic module orientation information refers to whether the photovoltaic module is horizontal or vertical.
[0118] (5) Determine the number of photovoltaic modules installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules based on the positions of all the target photovoltaic modules adapted within the photovoltaic array boundary and the corresponding photovoltaic module orientation information, so as to obtain the photovoltaic array layout.
[0119] After determining the positions of the photovoltaic modules adapted for all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information, the number of photovoltaic modules that can finally be installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules can be obtained. The arrangement of the photovoltaic modules includes the number of rows and columns of the photovoltaic modules.
[0120] Among them, the arrangement of the photovoltaic modules supports vertical, horizontal and arrangements at different angles, and can be flexibly adjusted according to actual needs to maximize the number of photovoltaic modules installed within the photovoltaic array boundary.
[0121] For example, for a certain photovoltaic module area, according to the sampling point ratio of the grid sampling points within the photovoltaic module area within the photovoltaic array boundary and whether the center point of the photovoltaic module in the photovoltaic module area is located within the photovoltaic array boundary, the adaptability of the photovoltaic modules within the photovoltaic array can be evaluated to obtain a suitable placement plan for the photovoltaic modules corresponding to the photovoltaic module area. Refer to the longitudinal placement plan of a single photovoltaic module shown in Fig. 3(1) and the horizontal placement plan of a single photovoltaic module shown in Fig. 3(2). The sampling point ratio of the photovoltaic module area corresponding to the photovoltaic array boundary in Fig. 3(1) is: 0.900, and the sampling point ratio of the photovoltaic module area corresponding to the photovoltaic array boundary in Fig. 3(2) is: 0.500. Assuming that the sampling point ratio threshold is 0.85, then 0.9 > 0.85 and 0.5 < 0.85. It can be seen that Fig. 3(1) is a more suitable placement plan for the photovoltaic modules compared to Fig. 3(2). In addition, it can be seen from Fig. 3(1) that the center point of the photovoltaic module in the photovoltaic module area is located within the photovoltaic array boundary. Therefore, the photovoltaic modules corresponding to the photovoltaic module area adopt the longitudinal placement plan shown in Fig. 3(1).
[0122] In summary, the present application creates uniformly distributed grid sampling points within the photovoltaic array area, combines the grid sampling points included in the photovoltaic array boundary and the analysis of the positions of the center points of the photovoltaic modules, and establishes a set of adaptability evaluation systems for the installation positions of the photovoltaic modules. It not only considers the geometric positions of the photovoltaic modules, but also integrates multi-dimensional factors such as the frame thickness of the photovoltaic modules, the horizontal / vertical spacing between adjacent photovoltaic modules, and the projection spacing between the front and rear rows of photovoltaic modules when determining the photovoltaic array boundary. Thus, it realizes the precise quantitative evaluation of the adaptability of the installation positions of the photovoltaic modules, can accurately calculate the layout of the photovoltaic modules in an irregularly shaped photovoltaic array, improves the space utilization rate, significantly increases the number of photovoltaic modules installed in the set area, shortens the design cycle of the installation positions of the photovoltaic modules, and improves the design efficiency.
[0123] In one embodiment, the process of determining the number of photovoltaic modules installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules based on the positions of the target photovoltaic modules adapted within the photovoltaic array boundary and the corresponding photovoltaic module orientation information to obtain the photovoltaic array layout may specifically include:
[0124] (1) Determine the number of photovoltaic modules installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules based on the positions of the target photovoltaic modules adapted within the photovoltaic array boundary and the corresponding photovoltaic module orientation information to obtain an initial photovoltaic array layout.
[0125] In practical applications, when the positions of all the photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information are determined, the photovoltaic modules can be installed within the photovoltaic array boundary, so that the number of photovoltaic modules installed within the photovoltaic array boundary and the arrangement of the photovoltaic modules can be obtained to obtain an initial photovoltaic array layout.
[0126] (2) Output the initial photovoltaic array layout to a visualization interface for display.
[0127] The visualization interface in this application can be a visual interaction interface, and the user can input control instructions on this visual interaction interface.
[0128] By outputting the initial photovoltaic array layout to the visualization interface for display, it is convenient for the user to view key elements such as the photovoltaic array boundary, the photovoltaic module frame, the photovoltaic array layout, the photovoltaic cleaning robot apron area, the bridge area, and the restricted area from the initial photovoltaic array layout, so as to comprehensively understand the photovoltaic site information.
[0129] (3) Obtain the array arrangement direction switching instruction input by the user on the visualization interface.
[0130] The user can, according to actual needs, switch the arrangement direction of any photovoltaic array by inputting an array arrangement direction switching instruction. After the system receives the array arrangement direction switching instruction, it recalculates the photovoltaic module layout of the photovoltaic array and updates the display.
[0131] In practical applications, in addition to switching the array arrangement direction, other operations can also be performed on the photovoltaic array. Taking the instructions that the user can input on the visualization interface as an example, left-click to select / switch the array arrangement direction, right-click to add a photovoltaic module, touch Esc to cancel the selection, C to clear the manually added photovoltaic modules, and the Enter key to switch the editing mode / final layout.
[0132] (4) Adjust the array arrangement direction of the initial photovoltaic array layout based on the array arrangement direction switching instruction to obtain the photovoltaic array layout.
[0133] For example, refer to the schematic diagram of the longitudinal arrangement of the interactive photovoltaic array shown in Figure 4(1). When the photovoltaic array is longitudinally arranged in Figure 4(1), three longitudinally arranged photovoltaic modules can be set in Array 1, and the number of longitudinally arranged photovoltaic modules that can be set in Array 2 is 0. The schematic diagram of the transverse arrangement of the interactive photovoltaic array shown in Figure 4(2), Array 1 can be set with 6 transversely arranged photovoltaic modules, and Array 2 can be set with one transversely arranged photovoltaic module. Comparing Figure 4(1) and Figure 4(2), it can be seen that when the arrangement direction of the photovoltaic modules is different, there are differences in the number of photovoltaic modules that can be placed in the corresponding photovoltaic array. The optimal photovoltaic array layout can be obtained by adopting the solution disclosed in this application.
[0134] After each time the arrangement direction of the photovoltaic array is switched, the visualization interface will display the updated photovoltaic array. The photovoltaic array can include: the number of photovoltaic modules, the number of rows and columns, and key information can be displayed on the visualization interface, so as to quickly evaluate the performance of different solutions based on these key information.
[0135] It should be noted that this application supports the independent optimization of multiple photovoltaic arrays, and each photovoltaic array can have different arrangement directions to meet the design requirements of complex scenarios.
[0136] In summary, the photovoltaic array layout optimization solution based on visualization interface interaction disclosed in this application can switch the arrangement direction of the photovoltaic array (horizontal / vertical / different angles) by operating on the visualization interface, and the relevant information of the photovoltaic array after the arrangement direction is switched can be displayed on the visualization interface. Therefore, the interactive design of the visualization interface can make the comparison and optimization of different solutions intuitive and efficient, thereby greatly reducing the error rate of photovoltaic array design. This application supports photovoltaic modules of different sizes and different arrangement directions, adapts to various actual application scenarios, and improves the flexibility and adaptability of the design.
[0137] In addition, the interactive design of the visualization interface can hide complex algorithms and calculations under a simple and intuitive visualization interface, enabling users to focus on solution optimization rather than technical details, thereby significantly improving the design efficiency and solution quality.
[0138] In one embodiment, step S104 may specifically include:
[0139] (1) Create a basic map of the photovoltaic site based on the photovoltaic site data.
[0140] The photovoltaic site data may include: the photovoltaic array area, the apron area for the photovoltaic cleaning robot, the bridge area, and the restricted area, etc. Therefore, the basic map of the photovoltaic site created based on the photovoltaic site data may include the photovoltaic array boundary determined based on the photovoltaic array area, the apron area for the photovoltaic cleaning robot, the bridge area, and the restricted area, etc.
[0141] (2) Locate the key information of each photovoltaic module in the photovoltaic array layout on the basic map of the photovoltaic site to obtain the photovoltaic site map.
[0142] The key information of each photovoltaic module may include: the coordinates of the center point of the photovoltaic module, the coordinates of the four vertices of the photovoltaic array, the orientation information of the photovoltaic module, etc.
[0143] (3) Add attribute information to each photovoltaic module on the photovoltaic site map and establish the topological relationship between the photovoltaic modules to obtain the two-dimensional photovoltaic module map.
[0144] The attribute information of each photovoltaic module may include: the unique location number associated with each photovoltaic module, the orientation information of the photovoltaic module, the model specifications of the photovoltaic module, etc.
[0145] This application designs a three-level numbering system of power station - array - row - column to achieve the unique identification of photovoltaic modules. The unique location number associated with each photovoltaic module, and the numbering rule of the unique location number is: power station number _ array number _ row number _ column number. For example, A_1_03_05 represents the photovoltaic module in the 3rd row and 5th column of the 1st array in Power Station A. This numbering system has four characteristics: uniqueness (each photovoltaic module has a unique identifier), hierarchy (reflecting the positional relationship of photovoltaic modules in the overall layout), scalability (applicable to photovoltaic power stations of different scales), and intuitiveness (facilitating maintenance personnel to quickly locate), providing a basis for the whole life cycle management of photovoltaic power stations.
[0146] The numbering system is closely integrated with the two-dimensional photovoltaic module map. Any photovoltaic module can be quickly located on the two-dimensional photovoltaic module map through the location number. Conversely, the corresponding numbering information can also be obtained through the location on the two-dimensional photovoltaic module map. This two-way mapping relationship greatly improves the operation and maintenance efficiency, especially during fault location and repair.
[0147] The topological relationship between photovoltaic modules includes: the spatial position relationship and connection relationship between photovoltaic modules. Based on the topological relationship between photovoltaic modules, it is convenient to plan the cleaning path and analyze the fault propagation in the follow-up.
[0148] In practical applications, the two-dimensional photovoltaic module map can be visually displayed on the visualization interface through color coding, layer management, etc. to show the distribution and status information of photovoltaic modules, such as Figure 5 the schematic diagram of the two-dimensional photovoltaic module map shown.
[0149] It should be noted that the two-dimensional photovoltaic module map in this application has the characteristics of high precision (obtaining photovoltaic site data based on RTK, with a positioning accuracy of up to centimeter level), multi-dimensions (integrating multi-dimensional information such as location, number, attributes, etc.), interactivity (supporting interactive operations such as querying, filtering, and statistics), scalability (supporting integration with the monitoring system to display the status of photovoltaic modules in real time), and updatability (supporting dynamic updates to reflect the actual changes in the power station), thus providing a solid foundation for the intelligent operation and maintenance of photovoltaic power stations.
[0150] In summary, this application maps the photovoltaic array into a high-precision digital model and designs a three-level intelligent numbering system based on array-row-column. This system not only realizes the unique identification of photovoltaic modules but also establishes a two-way mapping relationship between the number and the geographical location of photovoltaic modules, forming a complete digital management framework for photovoltaic power stations. Through the unique location number of photovoltaic modules or the two-dimensional photovoltaic module map, any photovoltaic module can be quickly defined, thus reducing the maintenance time of photovoltaic modules. In addition, combined with the monitoring system, faulty photovoltaic modules can be quickly located, improving the maintenance efficiency of photovoltaic modules. The unified location number and the two-dimensional photovoltaic module map also facilitate the establishment of a complete life cycle management database for photovoltaic modules, laying a foundation for the intelligent operation and maintenance of photovoltaic modules.
[0151] In one embodiment, step S105 may specifically include:
[0152] (1) Obtain a photovoltaic module arrangement matrix based on the unique location numbers of each photovoltaic module in the two-dimensional photovoltaic module map.
[0153] Obtaining a photovoltaic module arrangement matrix based on the unique location numbers of each photovoltaic module in the two-dimensional photovoltaic module map, that is, the row-column matrix of photovoltaic modules.
[0154] (2) Based on the photovoltaic module arrangement matrix and the cleaning operation area, plan a feasible cleaning path to obtain an initial cleaning path.
[0155] Based on the photovoltaic module arrangement matrix, combined with cleaning operation areas such as the parking area of the photovoltaic cleaning robot, the bridge area, and the restricted area, plan a feasible cleaning path, thereby obtaining an initial cleaning path.
[0156] (3) Adjust the initial cleaning path based on the cleaning path constraint conditions to obtain a target cleaning path.
[0157] Among them, the cleaning path constraint conditions include: the arrangement of photovoltaic modules, the optimized path for cleaning efficiency, the energy consumption of the photovoltaic cleaning robot, and the actual cleaning conditions of photovoltaic modules.
[0158] In practical applications, considering factors such as the arrangement of photovoltaic modules, the optimization path of cleaning efficiency (including minimizing the path length and the number of turns), the energy consumption of the photovoltaic cleaning robot, and the actual cleaning conditions of the photovoltaic modules, the initial cleaning path is adjusted to obtain a better target cleaning path.
[0159] It should be noted that the cleaning path constraint conditions can also include other conditions, such as obstacle avoidance (automatically avoiding restricted areas), etc., which are specifically adjusted according to actual needs and are not limited in this application.
[0160] For example, the final obtained target cleaning path can be seen in Figure 6 the schematic diagram of the target cleaning path of the photovoltaic cleaning robot shown in Figure 6 and the green line in it is the final target cleaning path.
[0161] In practical applications, the finally planned target cleaning path can be directly visualized on the two-dimensional photovoltaic module map, which is convenient for subsequent monitoring and management by technicians.
[0162] In addition, this application also supports the path simulation function, which can verify the feasibility and cleaning efficiency of the target cleaning path before actual execution to further improve the system reliability.
[0163] In summary, through the photovoltaic module arrangement matrix that characterizes the spatial distribution and connection relationship of photovoltaic modules, combined with the cleaning operation area, this application constructs a target cleaning path under multiple cleaning path constraint conditions, enabling the cleaning path planning to be determined based on more detailed information, thus effectively avoiding the situation of missed cleaning or repeated cleaning. The limitation of the cleaning path constraint conditions makes the generated target cleaning path more in line with the actual environment, effectively reducing unreasonable cleaning paths, significantly reducing the cleaning time and energy consumption, ensuring the cleaning effect, and improving the cleaning efficiency.
[0164] In addition, the target cleaning path planned by this application supports the collaborative cleaning of multiple photovoltaic cleaning robots, thereby further improving the cleaning efficiency, reducing the labor cost and operation and maintenance cost, extending the service life of the photovoltaic system, increasing the return on investment, promoting the sustainable development of the photovoltaic industry, and providing strong support for the clean energy transformation. The cleaning path planning can be dynamically adjusted according to the actual cleaning situation to cope with complex environments.
[0165] Corresponding to the above method embodiment, this application also discloses a cleaning path planning device.
[0166] See Figure 7 , the structural schematic diagram of a cleaning path planning device disclosed in an embodiment of this application. The device includes:
[0167] A data acquisition unit 301, configured to acquire photovoltaic site data.
[0168] In practical applications, photovoltaic site data can be obtained through RTK (Real-Time Kinematic). The photovoltaic site data may include: a photovoltaic array area, a parking area for a photovoltaic cleaning robot, a bridge area, a no-entry area, etc. The photovoltaic array area contains the coordinates of the four vertices in the photovoltaic array.
[0169] An array boundary determination unit 302 is configured to determine a photovoltaic array boundary based on the photovoltaic site data.
[0170] For precise issues such as the frames of photovoltaic modules and the installation gaps between adjacent photovoltaic modules, the present application uses an adaptive boundary recognition algorithm for the photovoltaic site data to determine the photovoltaic array boundary, so as to provide accurate spatial constraints for subsequent photovoltaic module layout.
[0171] An array layout determination unit 303 is configured to determine a photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary.
[0172] The present application creates grid sampling points within each photovoltaic module area, combines the sampling point ratio of the grid sampling points included within the photovoltaic array boundary and the position of the center point of the photovoltaic module, realizes the adaptability evaluation of the photovoltaic module to the photovoltaic array boundary, ensures the rationality of the photovoltaic array layout within the photovoltaic array boundary, and improves the space utilization rate of the area within the photovoltaic array boundary.
[0173] A photovoltaic module map determination unit 304 is configured to create a basic photovoltaic site map based on the photovoltaic site data, and combine the basic photovoltaic site map with the photovoltaic array layout to construct a two-dimensional photovoltaic module map.
[0174] In practical applications, the present application adopts a photovoltaic power station digital twin photovoltaic map construction technology, combines the created basic photovoltaic site map with the photovoltaic array layout, so that the created two-dimensional photovoltaic module map not only contains the precise position information of the photovoltaic modules, but also integrates multi-dimensional data such as the orientation and size of the photovoltaic modules, forming a complete digital management framework for the photovoltaic power station.
[0175] A cleaning path planning unit 305 is configured to obtain a target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
[0176] Among them, the set cleaning path constraint conditions include but are not limited to: the arrangement of photovoltaic modules, the optimized path for cleaning efficiency, the energy consumption of the photovoltaic cleaning robot, and the actual cleaning conditions of the photovoltaic modules.
[0177] The cleaning efficiency optimization paths include: minimizing the path length, the number of turns, etc.
[0178] For example, the energy consumption of the photovoltaic cleaning robot. The energy consumption of the photovoltaic cleaning robot for cleaning along the target cleaning path is not higher than the set energy value.
[0179] In summary, the present application discloses a cleaning path planning device, which acquires photovoltaic site data, determines the photovoltaic array boundary based on the photovoltaic site data, determines the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary, creates a basic map of the photovoltaic site based on the photovoltaic site data, combines the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, and obtains the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions. The present application preliminarily determines the cleaning area range through the photovoltaic array boundary, and considers the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary when determining the photovoltaic array layout. Therefore, it can more accurately reflect the actual position of the photovoltaic modules, avoiding the rough division relying only on the photovoltaic array boundary. By combining the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, and generating the final target cleaning path in combination with the cleaning path constraint conditions, it realizes the conversion of the position information of the actual photovoltaic modules into map data, enabling the cleaning path planning to be determined based on more detailed information, thus effectively avoiding the situation of missed cleaning or repeated cleaning. The limitation of the cleaning path constraint conditions makes the generated target cleaning path more in line with the actual environment, effectively reducing unreasonable cleaning paths, ensuring the cleaning effect, and improving the cleaning efficiency.
[0180] In one embodiment, the array boundary determination unit 302 can specifically be used for:
[0181] Based on the coordinates of the four vertices of the photovoltaic array in the photovoltaic site data, calculate the vectors of two adjacent sides of each vertex;
[0182] Based on the vectors of two adjacent sides of each vertex, calculate the normal vector of each vertex, and normalize the normal vector to obtain the corresponding target normal vector;
[0183] Calculate the average value of the normal vectors of the four target normal vectors of the photovoltaic array to obtain the average value of the normal vectors;
[0184] Based on the average value of the normal vectors and the geometric parameters of the photovoltaic array, obtain the vertex offset;
[0185] Offset the original boundary points of the photovoltaic array according to the vertex offset to obtain the latest boundary points;
[0186] Connect the respective latest boundary points to obtain the photovoltaic array boundary.
[0187] In one embodiment, the array layout determination unit 303 may specifically be configured to:
[0188] Create uniformly distributed grid sampling points within each photovoltaic module area;
[0189] Determine the target grid sampling points located within the photovoltaic array boundary among all the grid sampling points in each photovoltaic module area;
[0190] Calculate the sampling point ratio of all the target grid sampling points in the corresponding photovoltaic module area among all the grid sampling points;
[0191] In the case where the sampling point ratio reaches the sampling point ratio threshold, if the center point of the photovoltaic module in the photovoltaic module area is located within the photovoltaic array boundary, determine that the target photovoltaic module corresponding to the photovoltaic module area is located within the photovoltaic array boundary, and determine the photovoltaic module orientation information;
[0192] According to the photovoltaic module positions adapted to all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information, determine the number of photovoltaic modules installed within the photovoltaic array boundary and the photovoltaic module arrangement mode, so as to obtain the photovoltaic array layout.
[0193] In one embodiment, the array layout determination unit 303 may specifically further be configured to:
[0194] According to the photovoltaic module positions adapted to all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information, determine the number of photovoltaic modules installed within the photovoltaic array boundary and the photovoltaic module arrangement mode, so as to obtain an initial photovoltaic array layout;
[0195] Output the initial photovoltaic array layout to a visualization interface for display;
[0196] Obtain an array arrangement direction switching instruction input by a user on the visualization interface;
[0197] Based on the array arrangement direction switching instruction, adjust the array arrangement direction of the initial photovoltaic array layout to obtain the photovoltaic array layout.
[0198] In one embodiment, the photovoltaic module map determination unit 304 may specifically be configured to:
[0199] Create the photovoltaic site basic map based on the photovoltaic site data;
[0200] Locate the key information of each photovoltaic module in the photovoltaic array layout on the photovoltaic site basic map to obtain the photovoltaic site map;
[0201] Add attribute information to each photovoltaic module on the photovoltaic site map and establish the topological relationship between the photovoltaic modules to obtain the two-dimensional photovoltaic module map.
[0202] In one embodiment, the cleaning path planning unit 305 can specifically be used for:
[0203] Obtain a photovoltaic module arrangement matrix based on the unique position numbers of the photovoltaic modules in the two-dimensional photovoltaic module map;
[0204] Plan a cleaning feasible path based on the photovoltaic module arrangement matrix and the cleaning operation area to obtain an initial cleaning path;
[0205] Adjust the initial cleaning path based on the cleaning path constraint conditions to obtain the target cleaning path, where the cleaning path constraint conditions include: photovoltaic module layout, cleaning efficiency optimization path, energy consumption of the photovoltaic cleaning robot, and actual photovoltaic module cleaning conditions.
[0206] It should be noted that for the specific working principles of the components in the device embodiment, please refer to the corresponding parts of the method embodiment, which will not be elaborated here.
[0207] Corresponding to the above embodiment, the present application also discloses a computer storage medium, and the computer storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the steps shown in the cleaning path planning method embodiment are implemented.
[0208] Corresponding to the above embodiment, as Figure 8 shown, the present invention also provides a structural schematic diagram of a photovoltaic cleaning robot, and the photovoltaic cleaning robot may include: a processor 1 and a memory 2;
[0209] Wherein, the processor 1 and the memory 2 complete mutual communication through a communication bus 3;
[0210] The processor 1 is used to execute at least one instruction;
[0211] The memory 2 is used to store at least one instruction;
[0212] The processor 1 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.
[0213] The memory 2 may include high-speed RAM memory and may also include non-volatile memory, such as at least one disk memory.
[0214] Wherein, the processor executes at least one instruction to implement the steps shown in the embodiment of the cleaning path planning method.
[0215] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.
[0216] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.
[0217] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A cleaning path planning method, characterized in that, Including: Obtain photovoltaic site data; Determine the photovoltaic array boundary based on the photovoltaic site data; Determine the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary; Create a basic map of the photovoltaic site based on the photovoltaic site data, and combine the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map; Obtain the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
2. The cleaning path planning method according to claim 1, wherein Determining the photovoltaic array boundary based on the photovoltaic site data includes: Based on the coordinates of the four vertices of the photovoltaic array in the photovoltaic site data, calculate the vectors of two adjacent sides for each vertex; Calculate the normal vector for each vertex based on the vectors of two adjacent sides for each vertex, and normalize the normal vector to obtain the corresponding target normal vector; Average the four target normal vectors of the photovoltaic array to obtain the average normal vector; Obtain the vertex offset based on the average normal vector and the geometric parameters of the photovoltaic array; Offset the original boundary points of the photovoltaic array according to the vertex offset to obtain the latest boundary points; Connect the respective latest boundary points to obtain the photovoltaic array boundary.
3. The cleaning path planning method according to claim 1, characterized in that Determining the photovoltaic array layout based on the grid sampling points within each photovoltaic module area and the positional relationship between the center point of the photovoltaic module and the photovoltaic array boundary includes: Create evenly distributed grid sampling points within each photovoltaic module area; Determine the target grid sampling points located within the photovoltaic array boundary among all the grid sampling points in each photovoltaic module area; Calculate the sampling point ratio of all the target grid sampling points among all the grid sampling points in the corresponding photovoltaic module area; In the case where the sampling point ratio reaches the sampling point ratio threshold, if the center point of the photovoltaic module in the photovoltaic module area is located within the photovoltaic array boundary, determine that the corresponding target photovoltaic module in the photovoltaic module area is located within the photovoltaic array boundary, and determine the photovoltaic module orientation information; Determine the number of photovoltaic modules installed within the photovoltaic array boundary and the photovoltaic module arrangement method according to the photovoltaic module positions adapted to all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information to obtain the photovoltaic array layout.
4. The cleaning path planning method according to claim 3, wherein Determining the number of photovoltaic modules installed within the photovoltaic array boundary and the photovoltaic module arrangement method according to the photovoltaic module positions adapted to all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information to obtain the photovoltaic array layout includes: Determine the number of photovoltaic modules installed within the photovoltaic array boundary and the photovoltaic module arrangement method according to the photovoltaic module positions adapted to all the target photovoltaic modules within the photovoltaic array boundary and the corresponding photovoltaic module orientation information to obtain the initial photovoltaic array layout; Output the initial photovoltaic array layout to the visualization interface for display; Obtain the array arrangement direction switching instruction input by the user on the visualization interface; Adjust the array arrangement direction of the initial photovoltaic array layout based on the array arrangement direction switching instruction to obtain the photovoltaic array layout.
5. The cleaning path planning method according to any one of claims 1 to 4, characterized in that Create a basic map of the photovoltaic site based on the photovoltaic site data, and combine the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map, including: Create the basic map of the photovoltaic site based on the photovoltaic site data; Locate the key information of each photovoltaic module in the photovoltaic array layout on the basic map of the photovoltaic site to obtain a photovoltaic site map; Add attribute information to each photovoltaic module on the photovoltaic site map and establish the topological relationship between photovoltaic modules to obtain the two-dimensional photovoltaic module map.
6. The cleaning path planning method according to claim 5, wherein, The attribute information includes: a unique position number associated with each photovoltaic module, and the numbering rule of the unique position number is: power station number_array number_row number_column number.
7. The cleaning path planning method according to claim 1, wherein Obtain the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions, including: Obtain a photovoltaic module arrangement matrix based on the unique position numbers of each photovoltaic module in the two-dimensional photovoltaic module map; Plan a feasible cleaning path based on the photovoltaic module arrangement matrix and the cleaning operation area to obtain an initial cleaning path; Adjust the initial cleaning path based on the cleaning path constraint conditions to obtain the target cleaning path, where the cleaning path constraint conditions include: photovoltaic module arrangement, cleaning efficiency optimization path, energy consumption of the photovoltaic cleaning robot, and actual photovoltaic module cleaning conditions.
8. A cleaning path planning device, characterized in that, Including: A data acquisition unit for acquiring photovoltaic site data; An array boundary determination unit for determining the photovoltaic array boundary based on the photovoltaic site data; An array layout determination unit for determining the photovoltaic array layout based on the grid sampling points in each photovoltaic module area and the positional relationship between the photovoltaic module center point and the photovoltaic array boundary; A photovoltaic module map determination unit for creating a basic map of the photovoltaic site based on the photovoltaic site data, and combining the basic map of the photovoltaic site with the photovoltaic array layout to construct a two-dimensional photovoltaic module map; A cleaning path planning unit for obtaining the target cleaning path based on the two-dimensional photovoltaic module map and the set cleaning path constraint conditions.
9. A computer storage medium, characterized in that, The computer storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the cleaning path planning method according to any one of claims 1 to 7 is implemented.
10. A photovoltaic cleaning robot, characterized in that, The photovoltaic cleaning robot includes: a memory and a processor; The memory is used for storing at least one instruction; The processor is used for executing the at least one instruction to implement the cleaning path planning method according to any one of claims 1 to 7.