Photovoltaic station inspection method, device and equipment based on unmanned aerial vehicle and medium

Abstract

The invention discloses a photovoltaic station inspection method, device and equipment based on an unmanned aerial vehicle and a medium. The method comprises the following steps: determining a plurality of alternative operation points according to photovoltaic array distribution information of a target photovoltaic field station; determining a plurality of target operation points based on the operation cost of the alternative operation points and the working radius of the unmanned aerial vehicle; determining a plurality of target operation areas according to the plurality of target operation points and the working radius of the unmanned aerial vehicle, and dividing each target operation area into a plurality of target sub-areas; determining a target task type of each photovoltaic array in each target sub-region, and determining a target inspection route of the target sub-region according to the target task type; and allocating an unmanned aerial vehicle to each target sub-region, and scheduling the unmanned aerial vehicle to inspect the photovoltaic array in the target sub-region according to the target inspection route based on the allocation result. According to the scheme, the unmanned aerial vehicle can be scheduled for photovoltaic inspection based on the optimal operation point and the inspection task type, the inspection accuracy and efficiency are improved, and therefore safe and stable operation of a photovoltaic station is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle control technology, and in particular to a photovoltaic station inspection method, device, equipment and medium based on unmanned aerial vehicle. Background Art

[0002] With the development of photovoltaic technology and the increasing scale of photovoltaic power stations, the significance of photovoltaic inspection has become increasingly prominent. Through regular inspections, problems that arise during the operation of photovoltaic power stations can be discovered and solved in a timely manner to ensure the safety and stability of photovoltaic power station operations. Existing photovoltaic inspection technologies mainly use routes with a certain overlap rate, lack the purpose and planning of inspections, and can only provide an approximate positioning longitude and latitude, resulting in low inspection accuracy and efficiency. Summary of the invention

[0003] The present invention provides a photovoltaic station inspection method, device, equipment and medium based on unmanned aerial vehicle to solve one of the above technical problems.

[0004] According to one aspect of the present invention, a photovoltaic station inspection method based on an unmanned aerial vehicle is provided, the method comprising:

[0005] Acquire photovoltaic array distribution information of a target photovoltaic station, and determine a plurality of candidate operating points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes a plurality of photovoltaic arrays;

[0006] Determine a plurality of target operating points from the plurality of candidate operating points based on the operating costs of the candidate operating points and the operating radius of the drone;

[0007] Determine a plurality of target operation areas according to the plurality of target operation points and the working radius of the UAV, and divide each of the target operation areas into a plurality of target sub-areas;

[0008] Determine a target task type for each photovoltaic array in each of the target sub-areas, and determine a target inspection route for the target sub-area according to the target task type;

[0009] A drone is allocated to each of the target sub-areas, and based on the allocation result, the drone is scheduled to inspect the photovoltaic arrays in the target sub-areas according to the target inspection route.

[0010] According to another aspect of the present invention, a photovoltaic station inspection device based on a drone is provided, the device comprising:

[0011] A candidate operation point determination module is used to obtain photovoltaic array distribution information of a target photovoltaic site, and determine a plurality of candidate operation points according to the photovoltaic array distribution information; wherein the target photovoltaic site includes a plurality of photovoltaic arrays;

[0012] A target operation point determination module, configured to determine a plurality of target operation points from the plurality of candidate operation points based on the operation cost of the candidate operation points and the working radius of the drone;

[0013] A target sub-area determination module, configured to determine a plurality of target operating areas according to the plurality of target operating points and the working radius of the UAV, and divide each of the target operating areas into a plurality of target sub-areas;

[0014] A target inspection route determination module is used to determine the target task type of each photovoltaic array in each target sub-area, and determine the target inspection route of the target sub-area according to the target task type;

[0015] The photovoltaic array inspection module is used to allocate a drone to each of the target sub-areas, and dispatch the drone to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result.

[0016] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0017] at least one processor; and,

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the photovoltaic station inspection method based on a drone as described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the photovoltaic station inspection method based on a drone as described in any embodiment of the present invention when executed.

[0021] The technical solution of the embodiment of the present invention obtains the photovoltaic array distribution information of the target photovoltaic station, and determines multiple candidate operation points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes multiple photovoltaic arrays; based on the operation cost of the candidate operation point and the working radius of the drone, multiple target operation points are determined from the multiple candidate operation points; multiple target operation areas are determined according to the multiple target operation points and the working radius of the drone, and each target operation area is divided into multiple target sub-areas; the target task type of each photovoltaic array in each target sub-area is determined, and the target inspection route of the target sub-area is determined according to the target task type; a drone is allocated to each target sub-area, and the drone is scheduled to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result. This technical solution can schedule drones to perform photovoltaic inspections based on the optimal operation point and the inspection task type, thereby improving the accuracy and efficiency of photovoltaic inspections, thereby ensuring the safe and stable operation of the photovoltaic station.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a flow chart of a photovoltaic station inspection method based on a drone provided according to Embodiment 1 of the present invention;

[0025] Figure 2 is a photovoltaic array distribution diagram of a target photovoltaic station provided according to the first embodiment of the present invention;

[0026] Figure 3 is a schematic diagram of a convex hull of a photovoltaic array in a target photovoltaic station provided according to Embodiment 1 of the present invention;

[0027] Figure 4 is a schematic diagram of a dividing line division provided according to the first embodiment of the present invention;

[0028] Figure 5 is a schematic diagram of an alternative operation point provided according to the first embodiment of the present invention;

[0029] Figure 6 is a schematic diagram of a target operation area provided according to Embodiment 1 of the present invention;

[0030] Figure 7 is a schematic diagram of a target sub-region provided according to Embodiment 1 of the present invention;

[0031] Figure 8 This is a flow chart of a photovoltaic station inspection method based on a drone according to Embodiment 2 of the present invention;

[0032] Fig. 9 is a schematic diagram of a target sub-region provided according to Embodiment 2 of the present invention;

[0033] Fig.10 This is a schematic diagram of the structure of a photovoltaic station inspection device based on a drone according to Embodiment 3 of the present invention;

[0034] Fig.11 It is a structural schematic diagram of an electronic device for implementing a photovoltaic station inspection method based on a drone according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first", "second", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] Embodiment 1

[0038] Figure 1This is a flow chart of a method for inspecting photovoltaic stations based on drones provided in the first embodiment of the present invention. This embodiment can be applied to situations where drones are dispatched to conduct efficient and accurate inspections of photovoltaic stations. The method can be executed by a photovoltaic station inspection device based on drones. The photovoltaic station inspection device based on drones can be implemented in the form of hardware and / or software. The photovoltaic station inspection device based on drones can be configured in an electronic device with data processing capabilities. It should be noted that the drone scheduling and inspection logic provided in this embodiment can also be applied to scenarios other than photovoltaic inspection scenarios. It only needs to adapt the specific implementation details of this embodiment according to the actual application scenario. Figure 1 As shown, the method includes:

[0039] S110, obtaining photovoltaic array distribution information of a target photovoltaic station, and determining a plurality of candidate operating points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes a plurality of photovoltaic arrays.

[0040] The target photovoltaic station may refer to a photovoltaic station with a photovoltaic array inspection demand, and the target photovoltaic station has multiple photovoltaic arrays distributed therein, each photovoltaic array includes multiple photovoltaic panels, and the photovoltaic panels are inspected by drones to detect defects, dirt, etc. in the photovoltaic panels. The photovoltaic array distribution information may be used to describe the location information of the photovoltaic array in the target photovoltaic station, the arrangement form of the photovoltaic panels, etc.

[0041] Exemplarily, the photovoltaic array distribution information can be obtained through a photovoltaic array image or a photovoltaic station design drawing. Figure 2 This is a photovoltaic array distribution diagram of a target photovoltaic station provided in the first embodiment of the present invention, wherein PV-i represents the i-th photovoltaic array. It can be seen that Figure 2 The target photovoltaic station shown in FIG. 1 includes a total of 160 photovoltaic arrays. The candidate operation point may refer to a candidate starting point (ie, a starting point or a take-off point) when the drone performs a photovoltaic inspection task.

[0042] In this embodiment, the photovoltaic array distribution information of the target photovoltaic station is first obtained, and a plurality of candidate operating points are determined based on the photovoltaic array distribution information. Among them, two different methods can be set to determine the candidate operating points, one is an unrestricted method (i.e., unconditional restrictions), and the other is a restricted method (i.e., conditional restrictions), which can be flexibly selected according to actual inspection needs. Optionally, multiple candidate operating points are determined based on the photovoltaic array distribution information, including: determining the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station based on the photovoltaic array distribution information; dividing the enclosing area corresponding to the enclosing contour information into equal intervals to obtain multiple segmentation lines; taking points at equal intervals on each segmentation line to obtain multiple candidate operating points.

[0043] Specifically, first determine the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station according to the photovoltaic array distribution information. The enclosing contour information can be used to describe the enclosing circle contour that can cover all photovoltaic arrays in the target photovoltaic station. Exemplarily, the enclosing contour information can be the convex hull information or contour information formed by the peripheral photovoltaic arrays in the target photovoltaic station. Figure 3 A schematic diagram of the convex hull of a photovoltaic array in a target photovoltaic station provided in the first embodiment of the present invention, wherein the red part represents each photovoltaic array (with Figure 2 The blue line represents the convex hull. Then the enclosing area corresponding to the enclosing contour information is divided into multiple segmentation lines at equal intervals. The enclosing area may refer to a closed area composed of the enclosing contour, and all photovoltaic arrays in the target photovoltaic station are covered in the enclosing area. Figure 4 This is a schematic diagram of a segmentation line division provided in the first embodiment of the present invention, wherein the green lines represent multiple segmentation lines. Finally, points are taken at equal intervals on each segmentation line to obtain multiple candidate operation points. Figure 5 This is a schematic diagram of a candidate operating point provided in the first embodiment of the present invention, wherein the yellow dots on the green line represent multiple candidate operating points.

[0044] Through such a setting, this scheme can quickly determine multiple evenly distributed alternative operating points without any conditional restrictions, so as to subsequently determine the optimal operating point.

[0045] S120, determining a plurality of target operating points from a plurality of candidate operating points based on the operating costs of the candidate operating points and the operating radius of the drone.

[0046] In this embodiment, after determining multiple alternative operation points, it is necessary to determine the operation cost of each alternative operation point separately. Exemplarily, the operation cost may include accessibility cost (related to the flight distance of the drone), battery cost (related to the power of the drone) and remote sensing signal cost (related to the strength of the remote sensing signal of the alternative operation point). Exemplarily, multiple operation cost parameter items can be pre-set according to actual inspection needs, and corresponding weight values ​​can be set for each parameter item according to the importance. For each alternative operation point, the parameter values ​​corresponding to each operation cost parameter item can be determined separately according to preset rules, and the parameter values ​​corresponding to each operation cost parameter item can be weighted and summed to obtain the operation cost of each alternative operation point.

[0047] Among them, the preset rules can be pre-set according to the actual inspection needs. For example, for the reachability cost, a positive mapping relationship between the UAV flight distance and the reachability cost is set, that is, the longer the UAV flight distance, the greater the corresponding reachability cost value; for the battery cost, a positive mapping relationship between the UAV power and the battery cost is set, that is, the more UAV power, the greater the corresponding battery cost value; for the remote sensing signal cost, a positive mapping relationship between the remote sensing signal strength and the remote sensing signal cost is set, that is, the stronger the remote sensing signal of the alternative operation point, the greater the corresponding remote sensing signal cost value.

[0048] After determining the operation cost of each candidate operation point, multiple target operation points can be determined from multiple candidate operation points based on the operation cost of the candidate operation point and the working radius of the drone. The target operation point can be understood as the optimal operation point determined from multiple candidate operation points. Optionally, based on the operation cost of the candidate operation point and the working radius of the drone, multiple target operation points are determined from multiple candidate operation points, including: determining multiple target operation points from multiple candidate operation points according to a target mathematical model, and the target mathematical model is as follows:

[0049]

[0050] Among them, j represents the alternative operation point, c j represents the operation cost of the alternative operation point, i is the task point, and the task point refers to the center point of each photovoltaic array in the target photovoltaic station. And a ij The value of is determined according to the working radius of the UAV, M represents the set of mission points, Ni={j:a ij =1} represents a set of candidate operating points.

[0051] It should be noted that the goal of the target mathematical model is to determine as few target operation points as possible so that all task points i can be successfully executed. ij The value is determined as follows: a circular area is determined with the candidate operation point j as the center and the UAV working radius as the radius. The task point i covered in the circular area is the task point that the candidate operation point j can cover. If the candidate operation point j can cover the task point i, then a ij =1; if the candidate operation point j cannot cover the task point i, then a ij =0.

[0052] Through such a setting, this scheme can quickly determine multiple optimal target operating points based on the target mathematical model, which helps to improve the efficiency of photovoltaic inspection.

[0053] S130, determining multiple target operation areas according to multiple target operation points and the working radius of the UAV, and dividing each target operation area into multiple target sub-areas.

[0054] In this embodiment, after determining multiple target operation points, each target operation point can be used as the center point, and the working radius of the drone can be used as the radius, thereby determining multiple circular areas. Then, the areas where the photovoltaic arrays are located included in the circular areas are determined as target operation areas. For example, Figure 6 A schematic diagram of a target operation area provided in the first embodiment of the present invention, wherein the corresponding UAV working radius is 2 kilometers, including a total of 3 target operation points and corresponding target operation areas, Figure 6 The photovoltaic arrays of the same color in the figure represent a target operation area, and each dot represents a target operation point.

[0055] After determining multiple target operation areas, each target operation area can be further divided into multiple target sub-areas. Optionally, each target operation area is divided into multiple target sub-areas, including: for each target operation area, determining the number of target drones in the target operation area and the number of target photovoltaic arrays included in the target operation area; determining the target distance between each target photovoltaic array in the target operation area according to the photovoltaic array distribution information of the target operation area; dividing the target operation area into multiple target sub-areas according to the number of target drones, the number of target photovoltaic arrays and the target distance.

[0056] The target number of drones may refer to the number of drones expected to be allocated to the target operation area. The target number of photovoltaic arrays may refer to the number of photovoltaic arrays included in the target operation area. The target distance may refer to the distance between every two target photovoltaic arrays in the target operation area.

[0057] For example, the target operation area can be divided into multiple target sub-areas based on the MTSP (Multiple Traveling Salesman Problems) algorithm according to the number of target drones, the number of target photovoltaic arrays and the target distance. Among them, MTSP is one of the classic problems in combinatorial optimization, which refers to dividing the city cluster into M groups, and each group uses TSP to obtain the shortest travel route, so the key to the problem lies in how to determine the grouping of the city cluster; the MTSP algorithm can be understood as an algorithm that can solve MTSP (i.e., multiple traveling salesman problems). Among them, TSP (Traveling Salesman Problem) is a famous problem in operations research, which can be used to describe the following problem: There is a traveling salesman starting from city 1, and needs to go to cities 2, 3, ..., n to sell goods, and finally return to city 1. If the distance between any two cities is known, how should the traveling salesman choose his best walking route?

[0058] It should be noted that MTSP is a multi-objective problem, and evenly distributing the tasks of each traveling salesman is an important part of the multi-traveling salesman algorithm (i.e., MTSP algorithm), and its objectives generally have the following two aspects: 1. Minimize the total journey and evenly distribute the number of nodes visited by multiple traveling salesmen (number of different cities); 2. Minimize the total journey and evenly distribute the visit distance. In this embodiment, the MTSP with evenly distributed number of visited nodes can be used to divide the target operation area into multiple target sub-areas. Among them, the objective function of the MTSP with evenly distributed number of visited nodes can not only minimize the total journey, but also achieve the purpose of evenly distributing the number of visited nodes of M traveling salesmen. Based on this, it can be understood that the target number of drones is the number of traveling salesmen M, the target number of photovoltaic arrays is the total number of visited nodes, and the target distance is the distance between the visited nodes.

[0059] For example, one target operation area is used as an example for description, and it is assumed that the number of target photovoltaic arrays in the target operation area is 50. Figure 7 As shown in the figure, if the number of target drones is 5, the target operation area can be divided into 5 target sub-areas, and the number of photovoltaic arrays allocated to each drone is 10, 10, 10, 10, 10, respectively. Among them, the red dots represent the target operation points corresponding to the target operation area (i.e., the drone take-off point, which is also the landing point), and each color area represents 1 target sub-area. In addition, the number of target drones can also be other values, such as 10, 12, etc.

[0060] Through such a setting, this scheme can divide the target operation area into multiple target sub-areas based on the number of photovoltaic arrays in the target operation area, so as to realize drone scheduling based on the target sub-areas later.

[0061] S140, determining a target task type for each photovoltaic array in each target sub-area, and determining a target inspection route for the target sub-area according to the target task type.

[0062] Among them, the target task type can be used to describe what type of photovoltaic inspection task the drone needs to perform on each photovoltaic array in the target sub-area. For example, the task types may include the following: 1. Ordinary inspection task: refers to the photovoltaic inspection task under the centralized photovoltaic field station; 2. Fragmentation task: used to detect whether the photovoltaic panel in the photovoltaic array is fragmented; 3. Distributed task: refers to the photovoltaic inspection task under the distributed photovoltaic field station. It should be noted that the target task type of each photovoltaic array in the target sub-area can be the same or different, and the specific needs are determined according to the actual inspection needs. In this embodiment, after determining the target task type of each photovoltaic array in each target sub-area, the target sub-area can be planned by the drone path according to the target task type, so as to determine the target inspection route of the target sub-area. Among them, the target inspection route can be understood as the actual flight path of the drone for the photovoltaic array inspection of the target sub-area. It should be noted that different target task types correspond to different drone path planning methods, so different target task types correspond to different target inspection routes.

[0063] In this embodiment, optionally, a target inspection route for a target sub-area is determined according to a target task type, including: if the target task type is a fragmentation task, a first inspection route is generated within a photovoltaic string of a photovoltaic array based on a preset method, and a second inspection route is generated between photovoltaic strings based on a traveling salesman algorithm; wherein, the photovoltaic array includes a plurality of photovoltaic strings, the photovoltaic strings include a plurality of photovoltaic panels, and the fragmentation task is used to detect whether there are fragmentation in the photovoltaic panels in the photovoltaic array; the first inspection route is integrated with the second inspection route to obtain the target inspection route for the target sub-area.

[0064] Among them, the preset method may refer to a method for generating inspection routes within a photovoltaic string that is preset according to actual inspection needs. For example, the preset method may be set to generate inspection routes in an S shape. The first inspection route and the second inspection route may refer to inspection routes generated within a photovoltaic string and between photovoltaic strings, respectively. The traveling salesman algorithm refers to the TSP algorithm, which can be understood as an algorithm that can solve the TSP (i.e., traveling salesman problem).

[0065] Specifically, if the target task type is determined to be a fragmented task, the first inspection route is first generated within the photovoltaic strings of the photovoltaic array based on a preset method (such as S-shape), and then the second inspection route is generated between the photovoltaic strings based on the traveling salesman algorithm. The first inspection route and the second inspection route are then integrated to obtain the target inspection route of the target sub-area.

[0066] Through such a setting, this scheme can generate a corresponding target inspection route for the fragmentation task, so that the UAV can perform efficient inspection of the photovoltaic array in the target sub-area for the fragmentation task according to the target inspection route.

[0067] In this embodiment, optionally, a target inspection route for the target sub-area is determined according to the target task type, including: if the target task type is a common inspection task, an inspection route is generated between photovoltaic strings of the photovoltaic array based on a traveling salesman algorithm as the target inspection route for the target sub-area; wherein the photovoltaic array includes multiple photovoltaic strings, and the common inspection task refers to a photovoltaic inspection task under a centralized photovoltaic station.

[0068] In this embodiment, if the target task type is determined to be a common inspection task, route planning is performed based on photovoltaic strings. Specifically, based on the traveling salesman algorithm, an inspection route is generated between photovoltaic strings of the photovoltaic array as a target inspection route of the target sub-area.

[0069] Through such a setting, this scheme can generate corresponding target inspection routes for ordinary inspection tasks, so that the UAV can perform efficient inspections of photovoltaic arrays in the target sub-area according to the target inspection routes.

[0070] In this embodiment, optionally, a target inspection route for a target sub-area is determined according to the target task type, including: if the target task type is a distributed task, determining the minimum circumscribed rectangle of each distribution area; wherein the distributed task refers to a photovoltaic inspection task under a distributed photovoltaic field station; generating multiple candidate operation lines in the minimum circumscribed rectangle based on a preset spacing, and determining the candidate operation line located inside the distribution area as the target operation line; connecting the target operation lines to obtain the candidate inspection route for the distribution area, and connecting each candidate inspection route to obtain the target inspection route for the target sub-area.

[0071] Among them, the distribution area may refer to the area where the photovoltaic array is located, such as the roof area. It can be understood that a distributed task includes multiple distribution areas. Specifically, if the target task type is determined to be a distributed task, the minimum circumscribed rectangle of each distribution area is first determined, and then multiple candidate operation lines are generated in the minimum circumscribed rectangle based on the preset spacing, and the candidate operation line located inside the distribution area is determined as the target operation line. Among them, the preset spacing may refer to the distance between two adjacent candidate operation lines pre-set according to actual inspection needs. Then, each target operation line is connected in sequence to obtain the candidate inspection route of the distribution area, and finally, each candidate inspection route is connected to obtain the target inspection route of the target sub-area.

[0072] Through such a setting, this scheme can generate corresponding target inspection routes for distributed tasks, so that the drone can perform efficient inspections of the photovoltaic arrays in the target sub-area for distributed tasks according to the target inspection routes.

[0073] S150, allocating a drone to each target sub-area, and scheduling the drone to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result.

[0074] In this embodiment, after each target operation area is divided into multiple target sub-areas, a corresponding drone can be assigned to each target sub-area. For example, if the target operation area is divided into multiple target sub-areas based on the number of photovoltaic arrays in the target operation area, a drone can be assigned to each target sub-area, and then multiple drones are dispatched based on the allocation results to perform parallel inspections on the photovoltaic arrays in the target sub-areas according to the target inspection route, thereby effectively improving the efficiency of photovoltaic inspections.

[0075] The technical solution of the embodiment of the present invention obtains the photovoltaic array distribution information of the target photovoltaic station, and determines multiple candidate operation points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes multiple photovoltaic arrays; based on the operation cost of the candidate operation point and the working radius of the drone, multiple target operation points are determined from the multiple candidate operation points; multiple target operation areas are determined according to the multiple target operation points and the working radius of the drone, and each target operation area is divided into multiple target sub-areas; the target task type of each photovoltaic array in each target sub-area is determined, and the target inspection route of the target sub-area is determined according to the target task type; a drone is allocated to each target sub-area, and the drone is scheduled to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result. This technical solution can schedule drones to perform photovoltaic inspections based on the optimal operation point and the inspection task type, thereby improving the accuracy and efficiency of photovoltaic inspections, thereby ensuring the safe and stable operation of the photovoltaic station.

[0076] In this embodiment, optionally, multiple alternative operation points are determined based on the photovoltaic array distribution information, including: determining the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic site based on the photovoltaic array distribution information; determining the target interference area based on the map information of the target photovoltaic site; wherein the target interference area includes non-road areas and areas with abnormal elevation changes; determining other areas except the target interference area in the enclosing area corresponding to the enclosing contour information as target divided areas; dividing the target divided area into multiple dividing lines at equal intervals, and taking points at equal intervals on each dividing line to obtain multiple alternative operation points.

[0077] It should be noted that, taking into account the differences in topography of different target PV sites, it is sometimes necessary to impose some restrictions on the UAV operation points based on the actual topography. For example, the operation points can only be set on roads or in flat areas. This restriction ensures that the UAV can land and take off safely at the starting point. At this time, non-road areas (such as mud pits) and high terrain areas (such as hillsides) should be excluded to ensure the safety of the UAV.

[0078] In this embodiment, first, the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station is determined according to the photovoltaic array distribution information, wherein the enclosing contour information can be the convex hull information or contour information formed by the peripheral photovoltaic array in the target photovoltaic station. Then, the map information of the target photovoltaic station is obtained, which can be the satellite remote sensing image information of the target photovoltaic station obtained by drone photography or the electronic map information of the target photovoltaic station, and the non-road area and the area with abnormal elevation change are extracted from the map information of the target photovoltaic station as the target interference area. Among them, the area with abnormal elevation change can be understood as an area with a sudden increase in height. Then, the target interference area is eliminated from the enclosing area corresponding to the enclosing contour information to obtain one or more target divided areas. Finally, each target divided area is equally spaced to obtain multiple segmentation lines, and points are taken at equal intervals on each segmentation line to obtain multiple candidate operation points.

[0079] Through such a setting, this solution can quickly determine multiple alternative operation points based on the restrictions under certain conditions, which can better ensure the safety of the drone at the starting point.

[0080] Embodiment 2

[0081] Figure 8 A flowchart of a photovoltaic station inspection method based on drones is provided for the second embodiment of the present invention. This embodiment is optimized based on the above embodiment. The specific optimization is: each target operation area is divided into multiple target sub-areas, including: for each target operation area, the target cost matrix of the target photovoltaic array is determined according to the task type of each target photovoltaic array in the target operation area; the target operation area is divided into multiple target sub-areas according to the drone's cruising range and the target cost matrix.

[0082] like Figure 8 As shown, the method of this embodiment specifically includes the following steps:

[0083] S210, obtaining photovoltaic array distribution information of a target photovoltaic station, and determining a plurality of candidate operating points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes a plurality of photovoltaic arrays.

[0084] S220, determining a plurality of target operating points from a plurality of candidate operating points based on the operating costs of the candidate operating points and the operating radius of the drone.

[0085] S230, determining multiple target operation areas according to the multiple target operation points and the working radius of the UAV.

[0086] S240: For each target operation area, determine a target cost matrix of the target photovoltaic array according to the task type of each target photovoltaic array in the target operation area.

[0087] Among them, the target cost matrix can be used to describe the comprehensive cost required when the UAV performs the corresponding mission type on the target photovoltaic array. It should be noted that the method of determining the target cost matrix is ​​different for different mission types, that is, the target cost matrix corresponding to different mission types is different.

[0088] In this embodiment, optionally, the target cost matrix of the target photovoltaic array is determined according to the task type of each target photovoltaic array in the target operation area, including: if the task type of the target photovoltaic array is an ordinary inspection task, determining the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance; wherein the ordinary inspection task refers to the photovoltaic inspection task under the centralized photovoltaic station; and determining the target cost matrix of the target photovoltaic array according to the reference distance.

[0089] Specifically, if the task type of the target photovoltaic array is determined to be a common inspection task, the distances between the target photovoltaic array and other photovoltaic arrays in the target operation area are calculated as reference distances, and then the reference distances are arranged in order to obtain the target cost matrix of the target photovoltaic array. For common inspection tasks, the target cost matrix can be simply understood as the distance matrix from the current task point to other task points in the target operation area.

[0090] In this embodiment, optionally, a target cost matrix of the target photovoltaic array is determined according to the task type of each target photovoltaic array in the target operation area, including: if the task type of the target photovoltaic array is a fragmentation task or a distributed task, determining the target photovoltaic array's own operation cost according to the task type of the target photovoltaic array; wherein the fragmentation task is used to detect whether there is fragmentation in the photovoltaic panel in the photovoltaic array, and the distributed task refers to the photovoltaic inspection task under the distributed photovoltaic station; determining the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance; and determining the target cost matrix of the target photovoltaic array according to the reference distance and its own operation cost.

[0091] Specifically, if it is determined that the task type of the target photovoltaic array is a fragmented task or a distributed task, it is necessary to first determine the self-operation cost of the target photovoltaic array corresponding to the task type. Among them, the self-operation cost can be preset according to the task type. Then calculate the distance between the target photovoltaic array and other photovoltaic arrays in the target operation area as the reference distance. Then add each reference distance to the self-operation cost to obtain multiple comprehensive costs, and arrange each comprehensive cost in sequence to obtain the target cost matrix of the target photovoltaic array. For fragmented tasks, the target cost matrix can be simply understood as the sum of the distance matrix from the current task point to other task points in the target operation area and the self-cost matrix preset for the fragmented task; for distributed tasks, the target cost matrix can be simply understood as the sum of the distance matrix from the current task point to other task points in the target operation area and the self-cost matrix preset for the distributed task. Among them, the number of rows and columns of the self-cost matrix and the distance matrix are the same, and each element of the self-cost matrix is ​​the self-operation cost corresponding to the task type.

[0092] S250, divides the target operation area into multiple target sub-areas according to the UAV's range and the target cost matrix.

[0093] In this embodiment, after determining the target cost matrix of the target photovoltaic array, the target operation area can be divided into multiple target sub-areas according to the UAV cruising range and the target cost matrix. Specifically, first determine the total time required to complete the photovoltaic array inspection task in the target operation area according to the target cost matrix, then determine the single maximum time that the UAV can fly according to the UAV cruising range, and then determine the specific division of the target operation area into several target sub-areas according to the ratio of the total time to the single maximum time, that is, determine the number of divisions of the target sub-area. Based on this, it can be understood that the cruising range of one UAV can smoothly support the photovoltaic inspection task of a target sub-area. Finally, the target operation area can be divided into target sub-areas according to the number of divisions of the target sub-area based on the CVRP (Capacitated Vehicle Routing Problem, Capacity Constrained Vehicle Routing Problem) algorithm. Among them, the CVRP algorithm can be understood as an algorithm that can solve CVRP (i.e., capacity constrained vehicle routing problem).

[0094] For example, take one target operation area as an example, assuming that the target number of photovoltaic arrays in the target operation area is 50. Fig. 9 As shown in the figure, if the number of target sub-areas is 5, the target operation area can be divided into 5 target sub-areas. The red dots represent the target operation points (i.e., the take-off points and landing points of the drones) corresponding to the target operation areas, and each color area represents one target sub-area.

[0095] S260, determining the target task type of each photovoltaic array in each target sub-area, and determining the target inspection route of the target sub-area according to the target task type.

[0096] S270, assigning a drone to each target sub-area, and scheduling the drone to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the assignment result.

[0097] It should be noted that, since the range of one drone can smoothly support the photovoltaic inspection task of one target sub-area, when assigning drones to each target sub-area, it can be flexibly adjusted according to the actual dispatchable number of drones. When the actual dispatchable number of drones is sufficient, in order to improve the efficiency of photovoltaic inspection, one drone can be assigned to each target sub-area, and one drone is responsible for the photovoltaic inspection of one target sub-area; when the actual dispatchable number of drones is insufficient, multiple target sub-areas can be assigned to one drone, and one drone can fly multiple times, each time performing the photovoltaic inspection task of one target sub-area, so as to realize that one drone is responsible for the photovoltaic inspection of multiple target sub-areas.

[0098] The technical solution of the embodiment of the present invention determines the target cost matrix of the target photovoltaic array according to the task type of each target photovoltaic array in the target operation area for each target operation area; and divides the target operation area into multiple target sub-areas according to the UAV's cruising range and the target cost matrix. This technical solution can divide the target operation area into multiple target sub-areas based on the task type of the target operation area and the UAV's flight capability, so that when the UAV is subsequently scheduled based on the target sub-area, the UAV task volume in each target sub-area can be kept consistent as much as possible.

[0099] Embodiment 3

[0100] Fig.10 This is a schematic diagram of the structure of a photovoltaic station inspection device based on drones provided in the third embodiment of the present invention. The device can execute the photovoltaic station inspection method based on drones provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. Fig.10 As shown, the device comprises:

[0101] The candidate operation point determination module 310 is used to obtain the photovoltaic array distribution information of the target photovoltaic field station, and determine a plurality of candidate operation points according to the photovoltaic array distribution information; wherein the target photovoltaic field station includes a plurality of photovoltaic arrays;

[0102] A target operation point determination module 320 is used to determine a plurality of target operation points from the plurality of candidate operation points based on the operation cost of the candidate operation points and the working radius of the drone;

[0103] A target sub-area determination module 330 is used to determine a plurality of target operating areas according to the plurality of target operating points and the working radius of the UAV, and divide each of the target operating areas into a plurality of target sub-areas;

[0104] A target inspection route determination module 340 is used to determine the target task type of each photovoltaic array in each of the target sub-areas, and determine the target inspection route of the target sub-area according to the target task type;

[0105] The photovoltaic array inspection module 350 is used to allocate a drone to each of the target sub-areas, and dispatch the drone to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result.

[0106] Optionally, the candidate operation point determination module 310 is used to:

[0107] Determine the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station according to the photovoltaic array distribution information;

[0108] Dividing the enclosed area corresponding to the enclosed contour information into equal intervals to obtain a plurality of segmentation lines;

[0109] Points are taken at equal intervals on each of the dividing lines to obtain a plurality of candidate operating points.

[0110] Optionally, the candidate operation point determination module 310 is used to:

[0111] Determine the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station according to the photovoltaic array distribution information;

[0112] Determine a target interference area according to the map information of the target photovoltaic station; wherein the target interference area includes a non-road area and an area with abnormal elevation changes;

[0113] Determine other areas in the enclosed area corresponding to the enclosing contour information except the target interference area as target divided areas;

[0114] The target divided area is divided into multiple dividing lines at equal intervals, and points are taken at equal intervals on each of the dividing lines to obtain multiple candidate operation points.

[0115] Optionally, the target operation point determination module 320 is used to:

[0116] A plurality of target operating points are determined from the plurality of candidate operating points according to a target mathematical model, wherein the target mathematical model is as follows:

[0117]

[0118] Among them, j represents the alternative operation point, c j represents the operation cost of the candidate operation point, i is the task point, and the task point refers to the center point of each photovoltaic array in the target photovoltaic station, And a ij The value of is determined according to the working radius of the UAV, M represents the set of mission points, Ni={j:a ij =1} represents a set of candidate operating points.

[0119] Optionally, the target sub-region determining module 330 is configured to:

[0120] For each of the target operating areas, determining the number of target drones in the target operating area and the number of target photovoltaic arrays included in the target operating area;

[0121] Determine a target distance between target photovoltaic arrays in the target operation area according to the photovoltaic array distribution information of the target operation area;

[0122] The target operation area is divided into a plurality of target sub-areas according to the number of target UAVs, the number of target photovoltaic arrays and the target distance.

[0123] Optionally, the target sub-region determining module 330 includes:

[0124] A target cost matrix determining unit, configured to determine, for each target operating area, a target cost matrix of the target photovoltaic array according to a task type of each target photovoltaic array in the target operating area;

[0125] The target sub-area determination unit is used to divide the target operation area into multiple target sub-areas according to the UAV's cruising range and the target cost matrix.

[0126] Optionally, the target cost matrix determination unit is used to:

[0127] If the task type of the target photovoltaic array is a common inspection task, determine the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance; wherein the common inspection task refers to a photovoltaic inspection task under a centralized photovoltaic station;

[0128] A target cost matrix of the target photovoltaic array is determined according to the reference distance.

[0129] Optionally, the target cost matrix determination unit is used to:

[0130] If the task type of the target photovoltaic array is a fragmentation task or a distributed task, the operation cost of the target photovoltaic array itself is determined according to the task type of the target photovoltaic array; wherein the fragmentation task is used to detect whether there is fragmentation of the photovoltaic panels in the photovoltaic array, and the distributed task refers to the photovoltaic inspection task under the distributed photovoltaic station;

[0131] Determine the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance;

[0132] A target cost matrix of the target photovoltaic array is determined according to the reference distance and the own operation cost.

[0133] Optionally, the target inspection route determination module 340 is used to:

[0134] If the target task type is a fragmentation task, a first inspection route is generated within a photovoltaic string of a photovoltaic array based on a preset method, and a second inspection route is generated between the photovoltaic strings based on a traveling salesman algorithm; wherein the photovoltaic array includes a plurality of photovoltaic strings, the photovoltaic strings include a plurality of photovoltaic panels, and the fragmentation task is used to detect whether a photovoltaic panel in the photovoltaic array is fragmented;

[0135] The first inspection route and the second inspection route are integrated to obtain a target inspection route for the target sub-area.

[0136] Optionally, the target inspection route determination module 340 is used to:

[0137] If the target task type is a common inspection task, generating an inspection route between photovoltaic strings of the photovoltaic array based on a traveling salesman algorithm as a target inspection route for the target sub-area;

[0138] The photovoltaic array includes a plurality of photovoltaic strings, and the common inspection task refers to a photovoltaic inspection task under a centralized photovoltaic station.

[0139] Optionally, the target inspection route determination module 340 is used to:

[0140] If the target task type is a distributed task, determine the minimum circumscribed rectangle of each distribution area; wherein the distributed task refers to a photovoltaic inspection task under a distributed photovoltaic station;

[0141] generating a plurality of candidate operation lines in the minimum circumscribed rectangle based on a preset spacing, and determining the candidate operation line located inside the distribution area as a target operation line;

[0142] The target operation lines are connected to obtain candidate inspection routes of the distribution area, and the candidate inspection routes are connected to obtain the target inspection route of the target sub-area.

[0143] A photovoltaic station inspection device based on a drone provided in an embodiment of the present invention can execute a photovoltaic station inspection method based on a drone provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0144] Embodiment 4

[0145] According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.

[0146] Fig.11 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0147] like Fig.11 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0148] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0149] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a photovoltaic station inspection method based on a drone.

[0150] In some embodiments, the photovoltaic field inspection method based on drones can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the photovoltaic field inspection method based on drones described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the photovoltaic field inspection method based on drones in any other appropriate manner (for example, by means of firmware).

[0151] In some embodiments, the photovoltaic field inspection method based on drones can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the photovoltaic field inspection method based on drones described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the photovoltaic field inspection method based on drones in any other appropriate manner (for example, by means of firmware).

[0152] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0154] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0155] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0156] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0157] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0158] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0159] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A photovoltaic station inspection method based on drones, characterized in that: The method comprises: Acquire photovoltaic array distribution information of a target photovoltaic station, and determine a plurality of candidate operating points according to the photovoltaic array distribution information; wherein the target photovoltaic station includes a plurality of photovoltaic arrays; Determine a plurality of target operating points from the plurality of candidate operating points based on the operating costs of the candidate operating points and the operating radius of the drone; Determine a plurality of target operation areas according to the plurality of target operation points and the working radius of the UAV, and divide each of the target operation areas into a plurality of target sub-areas; Determine a target task type for each photovoltaic array in each of the target sub-areas, and determine a target inspection route for the target sub-area according to the target task type; A drone is allocated to each of the target sub-areas, and based on the allocation result, the drone is scheduled to inspect the photovoltaic arrays in the target sub-areas according to the target inspection route.

2. The method according to claim 1, characterized in that Determining a plurality of candidate operating points according to the photovoltaic array distribution information includes: Determine the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station according to the photovoltaic array distribution information; Dividing the enclosed area corresponding to the enclosed contour information into equal intervals to obtain a plurality of segmentation lines; Points are taken at equal intervals on each of the dividing lines to obtain a plurality of candidate operating points.

3. The method according to claim 1, characterized in that Determining a plurality of candidate operating points according to the photovoltaic array distribution information includes: Determine the enclosing contour information corresponding to the photovoltaic array in the target photovoltaic station according to the photovoltaic array distribution information; Determine a target interference area according to the map information of the target photovoltaic station; wherein the target interference area includes a non-road area and an area with abnormal elevation changes; Determine other areas in the enclosed area corresponding to the enclosing contour information except the target interference area as target divided areas; The target divided area is divided into multiple dividing lines at equal intervals, and points are taken at equal intervals on each of the dividing lines to obtain multiple candidate operation points.

4. The method according to claim 1, characterized in that: Based on the operation cost of the candidate operation points and the working radius of the drone, a plurality of target operation points are determined from the plurality of candidate operation points, including: A plurality of target operating points are determined from the plurality of candidate operating points according to a target mathematical model, wherein the target mathematical model is as follows: Among them, j represents the alternative operation point, c j represents the operation cost of the candidate operation point, i is the task point, and the task point refers to the center point of each photovoltaic array in the target photovoltaic station, And a ij The value of is determined according to the working radius of the UAV, M represents the set of mission points, Ni={j:a ij =1} represents a set of candidate operating points.

5. The method according to claim 1, characterized in that Each of the target operating areas is divided into a plurality of target sub-areas, including: For each of the target operating areas, determining the number of target drones in the target operating area and the number of target photovoltaic arrays included in the target operating area; Determine a target distance between target photovoltaic arrays in the target operation area according to the photovoltaic array distribution information of the target operation area; The target operation area is divided into a plurality of target sub-areas according to the number of target UAVs, the number of target photovoltaic arrays and the target distance.

6. The method according to claim 1, characterized in that Each of the target operating areas is divided into a plurality of target sub-areas, including: For each of the target operating areas, determining a target cost matrix of the target photovoltaic array according to the task type of each target photovoltaic array in the target operating area; According to the UAV's cruising range and the target cost matrix, the target operation area is divided into a plurality of target sub-areas.

7. The method according to claim 6, characterized in that Determining a target cost matrix of the target photovoltaic array according to the task type of each target photovoltaic array in the target operation area includes: If the task type of the target photovoltaic array is a common inspection task, determine the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance; wherein the common inspection task refers to a photovoltaic inspection task under a centralized photovoltaic station; A target cost matrix of the target photovoltaic array is determined according to the reference distance.

8. The method according to claim 6, characterized in that Determining a target cost matrix of the target photovoltaic array according to the task type of each target photovoltaic array in the target operation area includes: If the task type of the target photovoltaic array is a fragmentation task or a distributed task, the operation cost of the target photovoltaic array itself is determined according to the task type of the target photovoltaic array; wherein the fragmentation task is used to detect whether there is fragmentation of the photovoltaic panels in the photovoltaic array, and the distributed task refers to the photovoltaic inspection task under the distributed photovoltaic station; Determine the distance between the target photovoltaic array and other photovoltaic arrays as a reference distance; A target cost matrix of the target photovoltaic array is determined according to the reference distance and the own operation cost.

9. The method according to claim 1, characterized in that: Determining a target inspection route for the target sub-area according to the target task type includes: If the target task type is a fragmentation task, a first inspection route is generated within a photovoltaic string of a photovoltaic array based on a preset method, and a second inspection route is generated between the photovoltaic strings based on a traveling salesman algorithm; wherein the photovoltaic array includes a plurality of photovoltaic strings, the photovoltaic strings include a plurality of photovoltaic panels, and the fragmentation task is used to detect whether a photovoltaic panel in the photovoltaic array is fragmented; The first inspection route and the second inspection route are integrated to obtain a target inspection route for the target sub-area.

10. The method according to claim 1, characterized in that Determining a target inspection route for the target sub-area according to the target task type includes: If the target task type is a common inspection task, generating an inspection route between photovoltaic strings of the photovoltaic array based on a traveling salesman algorithm as a target inspection route for the target sub-area; The photovoltaic array includes a plurality of photovoltaic strings, and the common inspection task refers to a photovoltaic inspection task under a centralized photovoltaic station.

11. The method according to claim 1, characterized in that Determining a target inspection route for the target sub-area according to the target task type includes: If the target task type is a distributed task, determine the minimum circumscribed rectangle of each distribution area; wherein the distributed task refers to a photovoltaic inspection task under a distributed photovoltaic station; generating a plurality of candidate operation lines in the minimum circumscribed rectangle based on a preset spacing, and determining the candidate operation line located inside the distribution area as a target operation line; The target operation lines are connected to obtain candidate inspection routes of the distribution area, and the candidate inspection routes are connected to obtain the target inspection route of the target sub-area.

12. A photovoltaic station inspection device based on drones, characterized in that: The device comprises: A candidate operation point determination module is used to obtain photovoltaic array distribution information of a target photovoltaic site, and determine a plurality of candidate operation points according to the photovoltaic array distribution information; wherein the target photovoltaic site includes a plurality of photovoltaic arrays; A target operation point determination module, configured to determine a plurality of target operation points from the plurality of candidate operation points based on the operation cost of the candidate operation points and the working radius of the drone; A target sub-area determination module, configured to determine a plurality of target operating areas according to the plurality of target operating points and the working radius of the UAV, and divide each of the target operating areas into a plurality of target sub-areas; A target inspection route determination module is used to determine the target task type of each photovoltaic array in each target sub-area, and determine the target inspection route of the target sub-area according to the target task type; The photovoltaic array inspection module is used to allocate a drone to each of the target sub-areas, and dispatch the drone to inspect the photovoltaic array in the target sub-area according to the target inspection route based on the allocation result.

13. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the photovoltaic station inspection method based on a drone as described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the photovoltaic station inspection method based on a drone as described in any one of claims 1-11 when executed.

15. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the unmanned aerial vehicle-based photovoltaic station inspection method according to any one of claims 1 to 11 is implemented.

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