Method and system for testing albedo of unmanned aerial vehicle cruise photovoltaic power station

Abstract

The invention belongs to the technical field of new energy detection, and relates to an unmanned aerial vehicle cruise photovoltaic power station albedo test method and system. Comprising the following steps: acquiring spatial position coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity and aerial images of each measurement point; determining the validity of the measurement points according to a preset flight attitude angle threshold value, and removing invalid measurement points with the flight attitude data exceeding the flight attitude angle threshold value; calculating a single-point albedo based on the incident radiation intensity and the reflected radiation intensity of the effective measurement point; performing geometric correction on the aerial image based on the spatial position coordinates and the flight attitude data to generate a digital orthoimage map; determining a non-coincident air strip area based on the digital orthophoto map; and calculating the overall albedo of the photovoltaic power station based on the single-point albedo of the effective measurement points in the non-overlapped air strip areas. According to the invention, high-precision and high-efficiency measurement of the albedo of the photovoltaic power station is realized.

Description

Technical Field

[0001] This invention belongs to the field of new energy testing technology, and relates to a method and system for testing the albedo of a photovoltaic power station by drone patrol. Background Technology

[0002] Photovoltaic power plants, as an important renewable energy technology for addressing climate change, are developing rapidly worldwide. However, the significant changes in surface albedo have gradually attracted public attention. These changes are due to several factors: firstly, potential impacts on the ecological environment and local climate change; secondly, the fact that surface albedo can improve the power generation efficiency of photovoltaic power plants to some extent; and thirdly, the ability to reflect the degree of dust and snow accumulation on photovoltaic modules.

[0003] However, existing albedo testing methods have the following shortcomings: Large photovoltaic power plants typically have a meteorological monitoring station near the plant area. However, single-point measurements ignore the combined influence of the complex surface features of the ground below the monitoring point and the entire power plant, including photovoltaic modules, access roads, roads, and vegetation. This leads to large errors in albedo calculations and fails to accurately reflect the overall albedo of the power plant. This method cannot accurately reflect albedo, an important climate parameter for photovoltaic power plants, and it cannot quantify the contribution of albedo to power generation efficiency, nor does it provide quantitative indicators of the degree of dust and snow accumulation on the photovoltaic panel surface. Furthermore, fixed meteorological monitoring stations suffer from limited coverage, significant deviations from the specific meteorological conditions of nearby projects, and difficulties in conveniently monitoring atmospheric temperatures at different altitudes. Summary of the Invention

[0004] To address the problems in existing technologies, this invention provides a method and system for testing the albedo of photovoltaic power plants using unmanned aerial vehicles (UAVs), achieving high-precision and high-efficiency measurement of the albedo of photovoltaic power plants.

[0005] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for testing the albedo of a photovoltaic power station by drone patrol, comprising the following steps: The spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity, and aerial images of each measurement point are collected simultaneously by drones. The validity of the measurement points is determined based on the preset flight attitude angle threshold, and invalid measurement points whose flight attitude data exceeds the flight attitude angle threshold are removed. Calculate the single-point albedo based on the incident and reflected radiation intensities at the effective measurement points. Based on the spatial position coordinates and flight attitude data, the aerial images are geometrically corrected to generate digital orthophoto maps. Based on the digital orthophoto map, non-overlapping flight strip areas are determined; The overall albedo of the photovoltaic power station is calculated based on the single-point albedo of the effective measurement points within each non-overlapping flight zone.

[0006] Preferably, the incident radiation intensity is collected by an incident radiation sensor installed on the top of the drone body, and the sensing surface of the incident radiation sensor is ≥10cm from the top of the drone body; the reflected radiation intensity is collected by a reflected radiation sensor installed on the bottom of the drone body, and the sensing surface of the reflected radiation sensor is ≥30cm from the bottom of the drone body.

[0007] Preferably, the aerial images are captured by a camera, and the field of view of the camera lens matches the ground monitoring range of the reflective radiation sensor.

[0008] Preferably, the width of the flight strip area is dynamically adjusted according to the ground projection range of the reflected radiation sensor, and the adjustment formula is as follows:

[0009] In the formula, The width of the flight strip area, in meters; Real-time flight altitude, in meters (m). The field of view of the reflected radiation sensor is expressed in degrees (°).

[0010] Preferably, the overlap rate between adjacent flight zones in the UAV's cruise path is 60% to 70%.

[0011] Preferably, the preset flight attitude angle threshold is 15°. When the pitch angle or roll angle of the UAV is greater than 15°, the measurement point is determined to be an invalid measurement point.

[0012] Preferably, the method for determining non-overlapping flight strip regions based on the digital orthophoto image is as follows: Extract the boundary polygons of each flight zone in the digital orthophoto image and generate the corresponding vector boundary layer; perform spatial overlay analysis on the boundary polygons of adjacent flight zone regions, calculate the ratio of the intersection area to the area of ​​a single flight zone region as the percentage of the overlapping area; select flight zone regions whose percentage of the overlapping area does not exceed a preset threshold as non-overlapping flight zone regions.

[0013] Preferably, the formula for calculating the single-point albedo is:

[0014] In the formula, Let be the single-point albedo of the i-th valid measurement point; The reflected radiation intensity at the i-th valid measurement point is expressed in W / m². 2 ; The incident radiation intensity at the i-th valid measurement point is expressed in W / m². 2 .

[0015] Preferably, the formula for calculating the overall albedo of the photovoltaic power station is:

[0016] In the formula, The overall albedo of the photovoltaic power station; For the first Albedo of a single point at an effective measurement point; For the first The ground projection area of ​​each non-overlapping flight strip region, in m². 2 ; The total area of ​​the photovoltaic power station is expressed in square meters (m²). 2 .

[0017] Secondly, the present invention provides a drone-based system for testing the albedo of photovoltaic power plants, comprising: Data acquisition module: used to synchronously collect spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity and aerial images of each measurement point via UAV; Data determination module: used to determine the validity of measurement points based on preset flight attitude angle thresholds, and to remove invalid measurement points whose flight attitude data exceeds the flight attitude angle thresholds; Single-point albedo calculation module: used to calculate the single-point albedo based on the incident radiation intensity and reflected radiation intensity of the effective measurement point; Image geometric correction module: used to perform geometric correction on aerial images based on the spatial position coordinates and flight attitude data, and generate digital orthophoto images; Flight strip zoning analysis module: used to determine non-overlapping flight strip areas based on the digital orthophoto map; Global Albedo Fusion Module: Used to calculate the overall albedo of a photovoltaic power station based on the albedo of single-point measurement points within each non-overlapping flight zone.

[0018] Compared with the prior art, the present invention has the following beneficial effects: By simultaneously acquiring spatial location, flight attitude, and radiation data, and combining this with geometric correction of aerial imagery, spatial consistency and measurement accuracy of the data acquisition were ensured. An automatic screening mechanism based on flight attitude thresholds effectively eliminated measurement errors caused by unstable UAV attitudes. Digital orthophoto maps and non-overlapping flight strip area analysis techniques avoided the problem of redundant data calculations in traditional methods, improving measurement efficiency. Finally, by combining single-point albedo with area-weighted algorithms, a leap from point measurement to area evaluation was achieved, significantly improving measurement accuracy, drastically reducing the original error level, and simultaneously achieving a multiple-fold increase in data acquisition efficiency. This provides reliable technical support for the refined management and energy efficiency assessment of photovoltaic power plants. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart of the flight strip area planning and non-overlapping area calculation process of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0023] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0024] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply refers to its direction relative to "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0026] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0027] The present invention will now be described in further detail with reference to the accompanying drawings: The first objective of this invention is to provide a method for testing the albedo of a photovoltaic power station using a drone, such as... Figure 1 As shown, it includes the following steps: The spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity, and aerial images of each measurement point are collected simultaneously by drones. The validity of the measurement points is determined based on the preset flight attitude angle threshold, and invalid measurement points whose flight attitude data exceeds the flight attitude angle threshold are removed. Calculate the single-point albedo based on the incident and reflected radiation intensities at the effective measurement points. Geometric correction is performed on aerial images based on spatial location coordinates and flight attitude data to generate digital orthophoto maps with a resolution of ≤5cm. Determining non-overlapping flight strip areas based on digital orthophoto maps; The overall albedo of the photovoltaic power station is calculated based on the single-point albedo of the effective measurement points within each non-overlapping flight zone.

[0028] This invention achieves multi-dimensional collaborative measurement of the albedo of photovoltaic power plants by integrating spatial location coordinates, flight attitude data, incident / reflected radiation intensity, and aerial imagery through a drone platform. First, high-precision spatial location coordinates and flight attitude data provide a reliable spatial benchmark and stability control for the measurement, ensuring spatial consistency of data acquisition. Simultaneously acquired incident and reflected radiation intensity data form the physical basis for albedo calculation. Aerial imagery provides a visual basis for measurement area delineation and surface feature identification. Second, by using preset flight attitude angle thresholds to filter the validity of measurement points, the measurement errors caused by drone flight attitude instability are effectively eliminated, ensuring data quality. Geometric correction of the aerial imagery based on spatial location and attitude data generates digital orthophoto maps, ensuring the spatial matching accuracy between image data and radiation measurement data. The digital orthophoto maps intelligently identify non-overlapping flight strip areas, avoiding the problem of repeated data calculations in traditional measurement methods. Finally, based on the single-point albedo of effective measurement points in each non-overlapping flight zone, a comprehensive calculation was performed, which accurately reflected the overall reflection characteristics of the complex surface features of the photovoltaic power station. This achieved a technological leap from single-point measurement to area assessment, providing a reliable technical means for the energy efficiency assessment and environmental effect research of photovoltaic power stations.

[0029] In practical applications, incident radiation intensity is collected by an incident radiation sensor mounted on top of the drone's fuselage, with the sensor's sensing surface at least 10cm from the top of the drone. This effectively avoids interference from the drone's body blocking solar incident radiation, ensuring the accuracy of the incident radiation measurement. Simultaneously, reflected radiation intensity is collected by a reflected radiation sensor mounted on the bottom of the drone's fuselage, with the sensor's sensing surface at least 30cm from the bottom of the drone. This prevents interference from reflections from the drone's structural components and ensures that the sensor can fully receive reflected radiation from the ground surface. This symmetrical sensor layout design enables simultaneous and accurate measurement of incident and reflected radiation, providing a reliable data foundation for albedo calculations while balancing drone flight stability with sensor measurement accuracy.

[0030] For example, the aerial imagery is captured by a camera, and the camera's lens field of view is matched with the ground monitoring range of the reflective radiation sensor. By precisely matching the camera's lens field of view with the ground monitoring range of the reflective radiation sensor (width error ≤ 5%), spatial consistency between optical image data and radiation measurement data is achieved, ensuring that the image information of each pixel corresponds one-to-one with the geographical location of its corresponding radiation measurement value. This matching design effectively eliminates data registration errors caused by mismatched observation ranges in traditional methods, enabling albedo calculations to be accurately correlated with specific surface features. It also provides a reliable spatial benchmark for subsequent image analysis and radiation data verification, significantly improving the overall accuracy and reliability of albedo measurements.

[0031] Meanwhile, this invention uses PTP (Precise Time Protocol) to achieve sub-millisecond clock synchronization (synchronization error ≤1ms) among multiple sensors, ensuring strict synchronization of data acquisition from the incident radiation sensor, reflected radiation sensor, and camera, fundamentally solving the data mismatch problem caused by timing deviation in traditional methods.

[0032] In practical applications, observations should be conducted on clear days with a total cloud cover of ≤1 / 5 (i.e., sky coverage less than 20%) to avoid interference from clouds on reflection, radiation intensity data, and aerial imagery. Observations should be conducted between 9:00 and 15:00 local time daily to ensure sufficient solar radiation intensity while avoiding shadow interference caused by low solar altitude angles in the early morning and evening, resulting in aerial images with uniform lighting conditions and clear details.

[0033] Furthermore, the aerial imagery is acquired by triggering shots at preset spatial intervals, with the ground distance between adjacent shooting points not exceeding 20 meters. This achieves systematic and uniform acquisition of aerial imagery. It ensures the continuity and integrity of the image data, avoids blind spots, and maintains optimal matching between image resolution and radiometric measurement accuracy, providing a highly consistent data source for subsequent orthophoto generation and ground feature identification.

[0034] For example, the width of the flight strip area is dynamically adjusted according to the ground projection range of the reflected radiation sensor, and the adjustment formula is as follows:

[0035] In the formula, The width of the flight strip area, in meters; Real-time flight altitude, in meters (m). The field of view of the reflected radiation sensor is expressed in degrees (°).

[0036] This dynamic adjustment mechanism ensures that the coverage of each flight strip area is always synchronized with the effective detection area of ​​the sensor. This avoids measurement blind spots or data redundancy caused by the traditional fixed flight strip area width, and can adapt to the detection requirements at different flight altitudes. It ensures that the radiation intensity measurement data and spatial location are accurately correlated, providing a continuous, complete and high-quality data foundation without overlap or omission for albedo calculation.

[0037] The overlap rate between adjacent flight paths of the UAV is 60% to 70%, which avoids measurement blind spots and ensures data acquisition efficiency, providing multi-dimensional data support for establishing a three-dimensional albedo model of photovoltaic power plants.

[0038] For example, the preset flight attitude angle threshold is 15°. When the pitch or roll angle of the UAV is greater than 15°, the measurement point is determined to be invalid. This invention considers both the attitude fluctuation tolerance during normal UAV flight and effectively identifies abnormal attitudes caused by sudden airflow or manipulation. When the pitch or roll angle exceeds the threshold, the corresponding measurement point is automatically removed, fundamentally eliminating the radiation sensor receiving angle deviation caused by the tilt of the UAV body. This ensures that the measured values ​​of incident and reflected radiation intensity remain spatially consistent, providing a reliable standardized data source for albedo calculation, while avoiding the subjectivity and error of manual selection.

[0039] For example, such as Figure 2 As shown, the method for determining non-overlapping flight strip regions based on digital orthophoto maps is as follows: extract the boundary polygons of each flight strip region in the digital orthophoto map and generate the corresponding vector boundary layer; perform spatial overlay analysis on the boundary polygons of adjacent flight strip regions and calculate the ratio of the intersection area to the area of ​​a single flight strip region as the proportion of the overlapping area; select flight strip regions whose proportion of the overlapping area does not exceed a preset threshold as non-overlapping flight strip regions.

[0040] This invention utilizes digital orthophotos to generate vector boundary layers. By calculating the percentage of the intersection area of ​​adjacent flight strip regions, it identifies non-overlapping flight strip regions, effectively solving the problems of low efficiency and high subjectivity in traditional visual interpretation methods. It not only ensures the objectivity and accuracy of selecting non-overlapping flight strip regions but also allows for flexible adjustment of the overlap rate threshold according to actual measurement needs. This provides a reliable spatial division basis for subsequent albedo weighted calculations, significantly improving the representativeness and accuracy of the overall albedo calculation results.

[0041] For example, the formula for calculating single-point albedo is:

[0042] In the formula, Let be the single-point albedo of the i-th valid measurement point; The reflected radiation intensity at the i-th valid measurement point is expressed in W / m². 2 ; The incident radiation intensity at the i-th valid measurement point is expressed in W / m². 2 .

[0043] The formula for calculating the overall albedo of a photovoltaic power station is:

[0044] In the formula, The overall albedo of the photovoltaic power station; For the first Albedo of a single point at an effective measurement point; For the first The ground projection area of ​​each non-overlapping flight strip region, in m². 2 ; The total area of ​​the photovoltaic power station is expressed in square meters (m²). 2 .

[0045] The single-point albedo formula directly correlates the reflected and incident radiation intensities at each measurement point, ensuring the physical accuracy of the basic data. The overall albedo calculation employs an area-weighted average algorithm for non-overlapping flight strip regions, preserving the fine details of single-point measurements while objectively reflecting the contribution of different regions to the overall albedo through area weighting coefficients. This hierarchical calculation method effectively integrates the precision of point-scale measurements with the comprehensiveness of area-scale assessments, overcoming the problem of local error diffusion in traditional methods and providing a scientifically reliable technical solution for photovoltaic power plant albedo assessment.

[0046] Example Taking a certain Gobi photovoltaic power station (covering an area of ​​500 hectares) as an example: The power station uses a drone equipped with a CMP39 dual-component sensor (measuring incident radiation intensity from above and reflected radiation intensity from below) and a 20-megapixel camera (60° field of view, corresponding to a 30m monitoring width in the lower atmosphere) to collect data.

[0047] During the data acquisition phase, observations were conducted on clear days (total cloud cover ≤ 1 / 5) from 9:00 to 15:00 local time. The UAV flew at a speed of 10 m / s, with a flight path spacing of 12 m (overlap rate 60%).

[0048] During the data processing phase, a flight attitude angle threshold of 15° is first set to automatically eliminate measurement points that exceed the pitch or roll angle limits. The average incident radiation intensity of the effective measurement points is 800 W / m². 2 The reflected radiation intensity is 160 W / m 2 The typical single-point albedo was calculated to be 0.20 using the single-point albedo calculation formula. After spatial overlay analysis of the flight strip boundaries extracted from digital orthophoto maps to identify non-overlapping flight strip areas, the overall albedo was calculated using an area-weighted formula.

[0049] The results show that this method significantly improves measurement accuracy, greatly reduces the original error level, and achieves a multiple-fold increase in data acquisition efficiency. In terms of coverage, a single operation can complete a comprehensive survey of a large power plant.

[0050] A second objective of this invention is to provide a drone-based system for testing the albedo of photovoltaic power plants, comprising: Data acquisition module: used to synchronously collect spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity and aerial images of each measurement point via UAV; Data determination module: used to determine the validity of measurement points based on preset flight attitude angle thresholds, and to remove invalid measurement points whose flight attitude data exceeds the flight attitude angle thresholds; Single-point albedo calculation module: used to calculate the single-point albedo based on the incident radiation intensity and reflected radiation intensity of the effective measurement point; Image geometric correction module: used to perform geometric correction on aerial images based on the spatial position coordinates and flight attitude data, and generate digital orthophoto images; Flight strip zoning analysis module: used to determine non-overlapping flight strip areas based on the digital orthophoto map; Global Albedo Fusion Module: Used to calculate the overall albedo of a photovoltaic power station based on the albedo of single-point measurement points within each non-overlapping flight zone.

[0051] The data acquisition module ensures the synchronization and consistency of multi-source data, laying a reliable foundation for subsequent analysis. The data judgment module effectively eliminates measurement errors caused by UAV attitude instability by automatically filtering valid data, ensuring data quality. The single-point albedo calculation module achieves accurate acquisition of basic physical parameters. The image geometric correction module generates a high-precision spatial reference map. The flight strip zoning analysis module intelligently identifies non-overlapping flight strip areas, avoiding the problem of repeated data calculation in traditional methods. Finally, the global albedo fusion module achieves a leap from discrete point measurement to overall power plant albedo assessment through a weighted fusion algorithm. The various modules of this invention work together to form an efficient and accurate measurement system, greatly improving the objectivity, accuracy, and efficiency of albedo testing.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for testing the albedo of a photovoltaic power station using a drone, characterized in that, Includes the following steps: The spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity, and aerial images of each measurement point are collected simultaneously by drones. The validity of the measurement points is determined based on the preset flight attitude angle threshold, and invalid measurement points whose flight attitude data exceeds the flight attitude angle threshold are removed. Calculate the single-point albedo based on the incident and reflected radiation intensities at the effective measurement points. Based on the spatial position coordinates and flight attitude data, the aerial images are geometrically corrected to generate digital orthophoto maps. Based on the digital orthophoto map, non-overlapping flight strip areas are determined; The overall albedo of the photovoltaic power station is calculated based on the single-point albedo of the effective measurement points within each non-overlapping flight zone.

2. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The incident radiation intensity is collected by an incident radiation sensor installed on the top of the drone body, and the sensing surface of the incident radiation sensor is ≥10cm from the top of the drone body; the reflected radiation intensity is collected by a reflected radiation sensor installed on the bottom of the drone body, and the sensing surface of the reflected radiation sensor is ≥30cm from the bottom of the drone body.

3. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 2, characterized in that, The aerial images are captured by a camera, and the field of view of the camera lens matches the ground monitoring range of the reflected radiation sensor.

4. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 2, characterized in that, The width of the flight strip area is dynamically adjusted based on the ground projection range of the reflected radiation sensor, and the adjustment formula is as follows: In the formula, The width of the flight strip area, in meters; Real-time flight altitude, in meters (m). The field of view of the reflected radiation sensor is expressed in degrees (°).

5. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The overlap rate between adjacent flight zones in the drone's cruise path is 60% to 70%.

6. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The preset flight attitude angle threshold is 15°. When the pitch angle or roll angle of the UAV is greater than 15°, the measurement point is determined to be an invalid measurement point.

7. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The method for determining non-overlapping flight strip regions based on the aforementioned digital orthophoto image is as follows: Extract the boundary polygons of each flight zone in the digital orthophoto image and generate the corresponding vector boundary layer; perform spatial overlay analysis on the boundary polygons of adjacent flight zone regions, calculate the ratio of the intersection area to the area of ​​a single flight zone region as the percentage of the overlapping area; select flight zone regions whose percentage of the overlapping area does not exceed a preset threshold as non-overlapping flight zone regions.

8. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The formula for calculating the single-point albedo is: In the formula, Let be the single-point albedo of the i-th valid measurement point; The reflected radiation intensity at the i-th valid measurement point is expressed in W / m². 2 ; The incident radiation intensity at the i-th valid measurement point is expressed in W / m². 2 .

9. The method for testing the albedo of a photovoltaic power station by drone patrol according to claim 1, characterized in that, The formula for calculating the overall albedo of the photovoltaic power station is as follows: In the formula, The overall albedo of the photovoltaic power station; For the first Albedo of a single point at an effective measurement point; For the first The ground projection area of ​​each non-overlapping flight strip region, in m². 2 ; The total area of ​​the photovoltaic power station is expressed in square meters (m²). 2 .

10. A drone-based system for testing the albedo of a photovoltaic power station, characterized in that, include: Data acquisition module: used to synchronously collect spatial coordinates, flight attitude data, incident radiation intensity, reflected radiation intensity and aerial images of each measurement point via UAV; Data determination module: used to determine the validity of measurement points based on preset flight attitude angle thresholds, and to remove invalid measurement points whose flight attitude data exceeds the flight attitude angle thresholds; Single-point albedo calculation module: used to calculate the single-point albedo based on the incident radiation intensity and reflected radiation intensity of the effective measurement point; Image geometric correction module: used to perform geometric correction on aerial images based on the spatial position coordinates and flight attitude data, and generate digital orthophoto images; Flight strip zoning analysis module: used to determine non-overlapping flight strip areas based on the digital orthophoto map; Global Albedo Fusion Module: Used to calculate the overall albedo of a photovoltaic power station based on the albedo of single-point measurement points within each non-overlapping flight zone.

Images