Wind environment assessment method and system based on unmanned aerial vehicle observation

Abstract

The invention provides a wind environment assessment method and system based on unmanned aerial vehicle observation, and relates to the technical field of wind environment detection, and the method comprises the steps: obtaining the flight parameters of an unmanned aerial vehicle combination at a plurality of moments in a detection period; acquiring unmanned aerial vehicle position information of the unmanned aerial vehicle in a preset coordinate system at a plurality of moments in the detection period; acquiring real-time environment information at a plurality of moments in the detection period; determining absolute wind speed information according to the flight parameters and the real-time environment information; determining a wind energy resource detection score according to the absolute wind speed information and the real-time environment information; determining a wind speed gradient detection score according to the absolute wind speed information and the unmanned aerial vehicle position information; and generating a wind environment assessment report according to the wind energy resource detection score and the wind speed gradient detection score. According to the method and the device, the wind environment can be evaluated according to the wind energy resource condition and the wind speed and air degree distribution state, and the accuracy of a wind environment evaluation result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind environment detection, and particularly to a wind environment assessment method and system based on unmanned aerial vehicle observation. Background Art

[0002] In the related art, CN117540873A relates to the technical field of urban planning, and solves the technical problem that the construction of urban ventilation corridors only considers the influence of a single building scale, resulting in inapplicability to the excavation of ventilation corridors and the optimization of wind environment at the urban scale. In particular, it relates to an optimized method for wind environment assessment to alleviate the heat island effect in the old city. The optimized method identifies morphological parameters based on the distribution of buildings in the existing built environment of the city, is used for the assessment of the regional air circulation capacity, and conducts potential corridor excavation and spatial form optimization of the regional environment according to the assessment. This solution provides a more practical wind environment assessment based on the wind environment evaluation of three-dimensional building morphological characteristics, can be applied to the research and planning and construction of the micro-scale urban wind environment, and provides technical support for wind environment optimization in the process of urban renewal in the old city.

[0003] CN106156516A discloses a method for evaluating the pedestrian wind environment in urban blocks based on wind tunnel tests. It relates to a method for evaluating the pedestrian wind environment in urban blocks, specifically to a method for evaluating the pedestrian wind environment in urban blocks based on wind tunnel tests. This solution aims to solve the problem of insufficient accuracy of existing wind environment assessment methods. The specific steps of this solution are as follows: calibrate the parameters of the improved Irwin wind speed probe; take a typical urban block as the research object; conduct a wind environment test; use formulas (2) and (3) to determine the ratios rM and rG of the hourly average wind speed Ui,site and gust wind speed Ui,gust,site at the pedestrian height in the urban block at each wind direction angle to the hourly average wind speed U10,site at a height of 10 m; based on the wind speed ratios rM and rG, convert the hourly average wind speed threshold Uthr in the wind environment assessment standard into the hourly average wind speed threshold Uthr,M or gust equivalent hourly average wind speed threshold Uthr,GEM at a height of 10 m in the urban block. This solution belongs to the field of building wind environment.

[0004] Based on the above related technologies, the calculation process of wind environment assessment can be simplified. However, the related technologies do not consider the importance of wind energy resource status and wind speed gradient status for wind environment assessment, that is, it is impossible to comprehensively assess the wind environment from the two aspects of wind energy resource status and wind speed gradient status.

[0005] The information disclosed in the background art section of the present application is only intended to deepen the understanding of the general background art of the present application, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0006] The present invention provides a method and system for wind environment assessment based on unmanned aerial vehicle (UAV) observation, which can solve the technical problem that the related art cannot comprehensively evaluate the wind environment from two aspects of wind energy resource status and wind speed gradient status.

[0007] According to a first aspect of the present invention, there is provided a method for wind environment assessment based on UAV observation, including:

[0008] At multiple moments during a detection period, obtain the flight parameters of a UAV combination, where the flight parameters include: flight speed and flight direction. The UAV combination includes multiple UAVs, and the x-axis coordinates and z-axis coordinates of each UAV are the same, while the y-axis coordinates are different from each other. The preset coordinate system is established with a preset origin within the range of the observation area as the origin, the ground of the observation area as the xoz plane of the coordinate system, and the vertically upward direction as the y-axis of the coordinate system;

[0009] At multiple moments during a detection period, obtain the UAV position information of the UAVs in the preset coordinate system;

[0010] At multiple moments during a detection period, through a sensor combination arranged on the UAVs, obtain the real-time environment information of the observation area, where the real-time environment information includes: temperature information, humidity information, pressure information, relative wind speed information, and wind direction information;

[0011] Determine the absolute wind speed information according to the flight parameters and the real-time environment information;

[0012] Determine the wind energy resource detection score according to the absolute wind speed information and the real-time environment information;

[0013] Determine the wind speed gradient detection score according to the absolute wind speed information and the UAV position information;

[0014] Generate a wind environment assessment report according to the wind energy resource detection score and the wind speed gradient detection score.

[0015] According to a second aspect of the present invention, there is provided a system for wind environment assessment based on UAV observation, including:

[0016] A flight parameter module, configured to obtain the flight parameters of a UAV combination at multiple moments during a detection period, where the flight parameters include: flight speed and flight direction. The UAV combination includes multiple UAVs, and the x-axis coordinates and z-axis coordinates of each UAV are the same, while the y-axis coordinates are different from each other. The preset coordinate system is established with a preset origin within the range of the observation area as the origin, the ground of the observation area as the xoz plane of the coordinate system, and the vertically upward direction as the y-axis of the coordinate system;

[0017] A position information module, configured to obtain the UAV position information of the UAV in a preset coordinate system at multiple moments during a detection period;

[0018] An environmental information module, configured to obtain real-time environmental information of an observation area at multiple moments during a detection period through a sensor combination arranged on the UAV, where the real-time environmental information includes: temperature information, humidity information, pressure information, relative wind speed information, and wind direction information;

[0019] An absolute wind speed module, configured to determine absolute wind speed information according to the flight parameters and the real-time environmental information;

[0020] A wind energy resource detection module, configured to determine a wind energy resource detection score according to the absolute wind speed information and the real-time environmental information;

[0021] A wind speed gradient detection module, configured to determine a wind speed gradient detection score according to the absolute wind speed information and the UAV position information;

[0022] An evaluation report module, configured to generate a wind environment evaluation report according to the wind energy resource detection score and the wind speed gradient detection score.

[0023] Technical effects: According to the present invention, the influence of the flight speed and flight direction of the UAV on the wind speed measurement error can be accurately analyzed, thereby improving the accuracy of wind speed measurement. When evaluating the wind environment, based on the wind speed information, environmental information, and UAV position information after correcting the error, the wind energy resource status and wind force gradient distribution status of the observation area are evaluated, improving the comprehensiveness and accuracy of the wind environment evaluation result. When determining the absolute wind speed information, the absolute wind speed information can be determined according to the flight speed, relative wind speed information, and direction angle, improving the scientificity of the absolute wind speed information and providing a data basis for subsequent wind environment evaluation. When determining the wind energy resource detection score, the wind energy resource detection score can be determined according to the absolute wind speed information and air density. During the calculation process, the richness of the wind energy resources in the observation area can be evaluated from two aspects of average wind speed and wind power density respectively, improving the comprehensiveness and accuracy of the wind energy resource detection score. When determining the wind speed gradient detection score, the wind speed gradient detection score can be determined according to the wind speed distribution function. During the calculation process, the overall wind speed gradient reasonable condition of the observation area can be evaluated from two aspects of the reasonable condition of the wind speed gradient in the vertical direction and the reasonable condition of the wind speed gradient in the horizontal direction respectively, improving the objectivity and accuracy of the wind speed gradient detection score.

[0024] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit the present invention. Other features and aspects of the present invention will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Description of the Drawings

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other embodiments can be obtained based on these drawings;

[0026] Figure 1 Exemplarily shown is a schematic flow chart of a wind environment assessment method based on drone observation according to an embodiment of the present invention;

[0027] Figure 2 Exemplarily shown is a schematic diagram of a wind environment assessment system based on drone observation according to an embodiment of the present invention. Detailed Embodiments

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0029] The following will detail the technical solutions of the present invention with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0030] Figure 1 Exemplarily shown is a schematic flow chart of a wind environment assessment method based on drone observation according to an embodiment of the present invention, and the method includes:

[0031] Step S101, at multiple moments in a detection period, obtain the flight parameters of a drone combination, where the flight parameters include: flight speed and flight direction. The drone combination includes multiple drones, and the x-axis coordinates and z-axis coordinates of each drone are the same, and the y-axis coordinates are different from each other. The preset coordinate system is established with the preset origin within the range of the observation area as the origin, the ground of the observation area as the xoz plane of the coordinate system, and the vertically upward direction as the y-axis of the coordinate system;

[0032] Step S102, at multiple moments during the detection period, obtain the drone position information of the drone in the preset coordinate system;

[0033] Step S103, at multiple moments during the detection period, obtain the real-time environmental information of the observation area through the sensor combination set on the drone, where the real-time environmental information includes: temperature information, humidity information, pressure information, relative wind speed information, and wind direction information;

[0034] Step S104, determine the absolute wind speed information according to the flight parameters and the real-time environmental information;

[0035] Step S105, determine the wind energy resource detection score according to the absolute wind speed information and the real-time environmental information;

[0036] Step S106, determine the wind speed gradient detection score according to the absolute wind speed information and the drone position information;

[0037] Step S107, generate a wind environment assessment report according to the wind energy resource detection score and the wind speed gradient detection score.

[0038] According to the wind environment assessment method based on drone observation of the embodiments of the present invention, the influence of the flight speed and flight direction of the drone on the wind speed measurement error can be accurately analyzed, thereby improving the accuracy of wind speed measurement. When evaluating the wind environment, based on the wind speed information, environmental information, and drone position information after correcting the error, the wind energy resource status and wind force gradient distribution status of the observation area are evaluated, improving the comprehensiveness and accuracy of the wind environment assessment results.

[0039] According to an embodiment of the present invention, in step S101, at multiple moments during the detection period, obtain the flight parameters of the drone combination, where the flight parameters include: flight speed and flight direction. The drone combination includes multiple drones, and the x-axis coordinates and z-axis coordinates of each drone are the same, and the y-axis coordinates are different from each other. The preset coordinate system is established with the preset origin within the range where the observation area is located as the origin, the ground of the observation area as the coordinate system xoz plane, and the vertically upward direction as the y-axis of the coordinate system.

[0040] For example, during the detection period, through the drone tracking system, obtain the flight speed and flight direction of multiple drones in the drone combination during the detection period. With the preset origin on the ground where the observation area is located as the origin, the vertically upward direction as the y-axis of the coordinate system, and the ground as the xoz plane, the x-axis coordinates and z-axis coordinates of each drone in the drone combination are the same, and the y-axis coordinates are different from each other.

[0041] According to an embodiment of the present invention, in step S102, at multiple moments during the detection period, the drone position information of the drone in the preset coordinate system is obtained.

[0042] For example, taking the preset origin on the ground where the observation area is located as the origin, taking the vertically upward direction as the y-axis of the coordinate system, and taking the ground as the xoz plane to establish a preset coordinate system, and obtaining the drone position information through the positioning device installed on the drone.

[0043] According to an embodiment of the present invention, in step S103, at multiple moments during the detection period, the real-time environment information of the observation area is obtained through the sensor combination arranged on the drone, wherein the real-time environment information includes: temperature information, humidity information, pressure information, relative wind speed information, and wind direction information.

[0044] For example, before the start of the detection period, considering factors such as terrain and landform, meteorological conditions, and flight restrictions, plan the flight route of the drone to ensure that the drone can safely and effectively cover the observation area, and set a sensor combination on the drone. The sensor combination includes: an anemometer, a wind vane, a temperature sensor, a humidity sensor, and a pressure sensor. During the flight of the drone in the detection period, collect the temperature information, humidity information, pressure information, relative wind speed information, and wind direction information of each position in the observation area through the sensor combination, wherein the relative wind speed information is the wind speed information detected by the wind speed sensor installed on the drone.

[0045] According to an embodiment of the present invention, in step S104, the absolute wind speed information is determined according to the flight parameters and the real-time environment information.

[0046] According to an embodiment of the present invention, step S104 includes:

[0047] Determine the direction angle according to the flight direction and the wind direction information;

[0048] Determine the absolute wind speed information according to the flight speed, the relative wind speed information, and the direction angle.

[0049] For example, determine the direction angle according to the angle between the flight direction of the drone and the wind direction; determine the true wind speed at the position where the drone is located, that is, the absolute wind speed information, according to the flight speed, the relative wind speed information, and the direction angle.

[0050] According to an embodiment of the present invention, determining the absolute wind speed information according to the flight speed, the relative wind speed information, and the direction angle includes: determining the absolute wind speed information Aws at the i-th moment of the detection period according to formula (1) k,i ,

[0051] Awsk,i = ws k,i - fs k,i cosθ k,i (1)

[0052] Wherein, ws k,i is the relative wind speed information of the k-th drone at the i-th moment of the detection period, and fs k,i is the flight speed of the k-th drone at the i-th moment of the detection period, and θ k,i is the direction angle between the flight direction of the k-th drone and the wind direction at the i-th moment of the detection period.

[0053] According to an embodiment of the present invention, when detecting the wind speed by a drone, a wind speed sensor is usually carried. If the drone has a certain speed during flight and the direction of this speed is not completely consistent with the wind speed direction, then the wind speed measured by the wind speed sensor is actually the vector sum of the drone's flight speed and the true wind speed. fs k,i cosθ k,i is the vector value of the flight speed of the k-th drone at the i-th moment of the detection period in the wind speed direction, and ws k,i - fs k,i cosθ k,i is the difference between the relative wind speed information of the k-th drone at the i-th moment of the detection period and the vector value of the flight speed of the k-th drone at the i-th moment of the detection period in the wind speed direction, representing the actual wind speed at the position of the k-th drone at the i-th moment of the detection period, that is, the absolute wind speed information.

[0054] In this way, the absolute wind speed information can be determined according to the flight speed, relative wind speed information and direction angle, improving the scientificity of the absolute wind speed information and providing a data basis for the subsequent evaluation of the wind environment.

[0055] According to an embodiment of the present invention, in step S105, according to the absolute wind speed information and the real-time environment information, a wind energy resource detection score is determined.

[0056] According to an embodiment of the present invention, step S105 includes:

[0057] Determine the air density according to the temperature information, the humidity information and the pressure information;

[0058] Determine the wind energy resource detection score according to the absolute wind speed information and the air density.

[0059] For example, the density of dry air and the density of water vapor are calculated according to the ideal gas state equation, the saturated water vapor pressure is calculated according to the Magnus formula, the actual water vapor pressure, i.e., the partial pressure of water vapor, is calculated based on the saturated water vapor pressure and humidity information, and the partial pressure of dry air is determined by subtracting the partial pressure of water vapor from the pressure information. Finally, the density of humid air is calculated using the density of dry air, the density of water vapor, the partial pressure of water vapor, and the partial pressure of dry air; the wind energy resource status of the observation area is evaluated based on the absolute wind speed information and air density to determine the wind energy resource detection score.

[0060] According to an embodiment of the present invention, determining the wind energy resource detection score based on the absolute wind speed information and the air density includes: determining the wind energy resource detection score Wer of the detection period according to formula (2),

[0061]

[0062] where α 1 and α 2 are preset weight values, Aws T is the preset absolute wind speed information threshold, Aws k,i is the absolute wind speed information at the i-th moment of the detection period at the location of the k-th drone, W T is the preset wind power density threshold, ρ k,i is the air density at the i-th moment of the detection period at the location of the k-th drone, K is the number of drones, k ≤ K, m is the number of moments in the detection period, i ≤ m, and i, m, k, and K are all positive integers.

[0063] According to an embodiment of the present invention, is the average value of the absolute wind speed information of the K drones at the i-th moment of the detection period. The average wind speed is a basic parameter for evaluating wind energy resources, and the magnitude of the average wind speed directly reflects the richness of wind energy resources. is the average value of the average of the absolute wind speed information of the K drones at the i-th moment of the detection period and the preset absolute wind speed information threshold, indicating the wind energy resource status at the location where the drone combination is located at the i-th moment of the detection period. The larger this ratio, the richer the wind energy resource status at the location where the drone combination is located at the i-th moment of the detection period. is the average value obtained according to the number of moments in the detection period, indicating the overall wind energy resource status of the observation area. The larger this ratio, the richer the overall resource status of the observation area. is the wind power density at the location of the k-th drone at the i-th moment of the detection period. is the average wind power density at the position of the K drones at the i-th moment of the detection period, representing the overall wind power density situation at the position of the drone combination at the i-th moment of the detection period. Wind power density is an important indicator for evaluating the potential of wind energy resources. The greater the wind power density, the richer the wind energy resources in the observation area. is the relative difference between the average wind power density at the position of the K drones at the i-th moment of the detection period and the preset wind power density threshold. The larger this ratio, the richer the wind energy resources situation.

[0064] According to an embodiment of the present invention, represents determining the wind energy resource detection score based on two aspects: the average wind speed situation and the wind power density situation.

[0065] In this way, the wind energy resource detection score can be determined according to the absolute wind speed information and air density. During the calculation process, the richness of the wind energy resources in the observation area can be evaluated from two aspects: the average wind speed and the wind power density, improving the comprehensiveness and accuracy of the wind energy resource detection score.

[0066] According to an embodiment of the present invention, in step S106, the wind speed gradient detection score is determined according to the absolute wind speed information and the drone position information.

[0067] According to an embodiment of the present invention, step S106 includes:

[0068] Determine the wind speed distribution function according to the drone position information and the absolute wind speed information;

[0069] Determine the wind speed gradient detection score according to the wind speed distribution function.

[0070] For example, fit the drone position information at any moment in the detection period with the absolute wind speed information at the position of the drone to obtain a wind speed distribution function that describes the relationship between the position information and the absolute wind speed at this moment in the detection period. That is, input any position information into the wind speed distribution function, and the absolute wind speed at this position information can be obtained; evaluate the wind speed gradient situation according to the wind speed distribution functions at multiple moments, and determine the wind speed gradient detection score.

[0071] According to an embodiment of the present invention, determining the wind speed gradient detection score according to the wind speed distribution function includes: determining the wind speed gradient detection score Wg of the detection period according to formula (3),

[0072]

[0073]

[0074] Among them, β 1 and β 2 are preset weight values, if is a conditional function, and Wtd T is the preset wind speed gradient threshold, and Wtd T1 is the first preset wind speed gradient threshold, and Wtd T2 is the second preset wind speed gradient threshold, and Wtd T3 is the third preset wind speed gradient threshold. (x k,i , y k,i , z k,i ) is the drone position information of the k-th drone at the i-th moment of the detection period. A i (x k,i , y k,i , z k,i ) is the function value of the wind speed distribution function at the k-th drone at the i-th moment of the detection period. K is the number of drones, k ≤ K, m is the number of moments in the detection period, i ≤ m, and i, m, k, and K are all positive integers.

[0075] According to an embodiment of the present invention, is to take the partial derivative of the wind speed distribution function with respect to the y-axis direction of the preset coordinate system and substitute the value of the drone position information of the k-th drone at the i-th moment of the detection period, representing the wind speed change rate in the vertical direction at the position of the k-th drone at the i-th moment of the detection period, that is, the wind speed gradient. In formula (3), the following two situations can be represented in the form of a conditional function. When the condition of is satisfied, it means that the wind speed gradient in the vertical direction at the position of the k-th drone at the i-th moment of the detection period is within the interval of the preset wind speed gradient threshold and the first preset wind speed gradient threshold, indicating that the wind speed gradient in the vertical direction at the position of the k-th drone at the i-th moment of the detection period is within a reasonable range, and the value of the conditional function is 1. When the condition of is not satisfied, the wind speed gradient in the vertical direction at the position of the k-th drone at the i-th moment of the detection period is too large or too small. When the wind speed gradient is too large, it may damage the ecosystem and may expand the pollution range of pollutants. When the wind speed gradient is too small, it may cause pollutants to accumulate in a local area, resulting in environmental pollution. The value of the conditional function is is the relative difference between the wind speed gradient in the vertical direction at the position of the k-th drone at the i-th moment of the detection period and the average value of the preset wind speed gradient threshold and the first preset wind speed gradient threshold. The larger this ratio is, the more unreasonable the wind speed gradient in the vertical direction at the position of the k-th drone at the i-th moment of the detection period is. It is to calculate the average according to the number of drones, indicating the reasonable condition of the wind speed gradient in the vertical direction when the drone group is at the i-th moment of the detection period.

[0076]

[0077] It is to calculate the average according to the number of moments in the detection period, indicating the overall reasonable condition of the vertical wind speed gradient in the observation area. The larger this ratio is, the more reasonable the overall vertical wind speed gradient in the observation area is.

[0078] According to an embodiment of the present invention, It is the modulus of the gradient of the wind speed distribution function along the movement direction of the k-th drone in the xoz plane, indicating the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period. In formula (1), the following two situations can be represented in the form of a conditional function. When the condition of is satisfied, the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period is within the interval of the second preset wind speed gradient threshold and the third preset wind speed gradient threshold, indicating that the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period is within a reasonable range, and the value of the conditional function is 1. When the condition of is not satisfied, the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period is too large or too small. When the wind speed gradient is too large, it may damage the ecosystem and may expand the pollution range of pollutants. When the wind speed gradient is too small, it may cause pollutants to accumulate in a local area, resulting in environmental pollution. The value of the conditional function is

[0079] It represents the relative difference between the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period and the average value of the second preset wind speed gradient threshold and the third preset wind speed gradient threshold. The larger this ratio is, the more unreasonable the wind speed gradient in the horizontal direction at the position of the k-th drone at the i-th moment of the detection period is.

[0080]

[0081] It is to calculate the average according to the number of drones, indicating the reasonable condition of the wind speed gradient in the horizontal direction when the drone group is at the i-th moment and the i + 1-th moment of the detection period.

[0082]

[0083] To calculate the average value based on the number of moments in the detection period, representing the reasonable condition of the overall horizontal wind speed gradient in the observation area. The larger this ratio, the more reasonable the overall horizontal wind speed gradient in the observation area.

[0084] According to an embodiment of the present invention,

[0085] To determine the wind speed gradient detection score based on two aspects: the reasonable condition of the overall vertical wind speed gradient and the reasonable condition of the overall horizontal wind speed gradient in the observation area.

[0086] In this way, the wind speed gradient detection score can be determined according to the wind speed distribution function. During the calculation process, the reasonable condition of the overall wind speed gradient in the observation area can be evaluated from two aspects: the reasonable condition of the wind speed gradient in the vertical direction and the reasonable condition of the wind speed gradient in the horizontal direction, improving the objectivity and accuracy of the wind speed gradient detection score.

[0087] According to an embodiment of the present invention, in step S107, a wind environment assessment report is generated based on the wind energy resource detection score and the wind speed gradient detection score.

[0088] For example, if the wind energy resource detection score is less than the preset wind energy resource detection score threshold, it indicates that the wind energy resource in the observation area is not rich. If the wind speed gradient detection score is less than the preset wind speed gradient detection score threshold, it indicates that the wind speed gradient distribution in the observation area is unreasonable.

[0089] The wind environment assessment method based on UAV observation according to an embodiment of the present invention can accurately analyze the influence of the flight speed and flight direction of the UAV on the wind speed measurement error, thereby improving the accuracy of wind speed measurement. When assessing the wind environment, based on the wind speed information, environmental information, and UAV position information after correcting the error, it assesses the wind energy resource status and wind gradient distribution status of the observation area, improving the comprehensiveness and accuracy of the wind environment assessment results. When determining the absolute wind speed information, the absolute wind speed information can be determined according to the flight speed, relative wind speed information, and direction angle, improving the scientific nature of the absolute wind speed information and providing a data basis for subsequent wind environment assessment. When determining the wind energy resource detection score, the wind energy resource detection score can be determined according to the absolute wind speed information and air density. During the calculation process, the richness of the wind energy resources in the observation area can be evaluated from two aspects: average wind speed and wind power density, improving the comprehensiveness and accuracy of the wind energy resource detection score. When determining the wind speed gradient detection score, the wind speed gradient detection score can be determined according to the wind speed distribution function. During the calculation process, the overall wind speed gradient rationality status of the observation area can be evaluated from two aspects: the rationality status of the wind speed gradient in the vertical direction and the rationality status of the wind speed gradient in the horizontal direction, improving the objectivity and accuracy of the wind speed gradient detection score.

[0090] Figure 2 Exemplarily shown is a schematic diagram of a wind environment assessment system based on UAV observation according to an embodiment of the present invention. The system includes:

[0091] A flight parameter module, configured to obtain the flight parameters of the UAV combination at multiple moments during the detection period. Among them, the flight parameters include: flight speed and flight direction. The UAV combination includes multiple UAVs, and the x-axis coordinates and z-axis coordinates of each UAV are the same, while the y-axis coordinates are different from each other. The preset coordinate system is established with the preset origin within the range where the observation area is located as the origin, the ground of the observation area as the xoz plane of the coordinate system, and the vertically upward direction as the y-axis of the coordinate system;

[0092] A position information module, configured to obtain the UAV position information of the UAV in the preset coordinate system at multiple moments during the detection period;

[0093] An environmental information module, configured to obtain the real-time environmental information of the observation area through a sensor combination arranged on the UAV at multiple moments during the detection period. Among them, the real-time environmental information includes: temperature information, humidity information, pressure information, relative wind speed information, and wind direction information;

[0094] An absolute wind speed module, configured to determine the absolute wind speed information according to the flight parameters and the real-time environmental information;

[0095] A resource detection module, configured to determine a wind energy resource detection score according to the absolute wind speed information and the real-time environment information;

[0096] A gradient detection module, configured to determine a wind speed gradient detection score according to the absolute wind speed information and the UAV position information;

[0097] An evaluation report module, configured to generate a wind environment evaluation report according to the wind energy resource detection score and the wind speed gradient detection score.

[0098] The present invention may be a method, an apparatus, a system, and / or a computer program product. The computer program product may include a computer-readable storage medium having thereon computer-readable program instructions for performing various aspects of the present invention.

[0099] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functions and structural principles of the present invention have been shown and described in the embodiments, and the embodiments of the present invention may have any deformation or modification without departing from the principle.

Claims

1. A wind environment assessment method based on drone observation, characterized in that: include: At multiple moments in the detection cycle, the flight parameters of the drone combination are obtained, wherein the flight parameters include: flight speed and flight direction, the drone combination includes multiple drones, and the x-axis coordinates and z-axis coordinates of each drone are the same, and the y-axis coordinates are different from each other, and the preset coordinate system is a coordinate system established based on a preset origin within the range where the observation area is located as the origin, the ground of the observation area as the coordinate system xoz surface, and the vertical upward direction as the coordinate system y axis; At multiple moments in the detection cycle, obtain the drone position information of the drone in a preset coordinate system; At multiple moments in the detection cycle, real-time environmental information of the observation area is obtained through a combination of sensors set on the drone, wherein the real-time environmental information includes: temperature information, humidity information, pressure information, relative wind speed information and wind direction information; Determining absolute wind speed information according to the flight parameters and the real-time environmental information; Determining a wind energy resource detection score according to the absolute wind speed information and the real-time environmental information; Determining a wind speed gradient detection score according to the absolute wind speed information and the drone position information; A wind environment assessment report is generated based on the wind energy resource detection score and the wind speed gradient detection score.

2. The wind environment assessment method based on drone observation according to claim 1 is characterized in that: Determining absolute wind speed information according to the flight parameters and the real-time environmental information includes: Determining a direction angle according to the flight direction and the wind direction information; The absolute wind speed information is determined according to the flight speed, the relative wind speed information and the direction angle.

3. The wind environment assessment method based on drone observation according to claim 2 is characterized in that: Determining absolute wind speed information according to the flight speed, the relative wind speed information and the direction angle includes: According to the formula Aws k,i =ws k,i -fs k,i cosθ k,i Determine the absolute wind speed information Aws of the kth UAV at the i-th moment in the detection cycle k,i , where ws k,i is the relative wind speed information of the kth UAV at the i-th moment in the detection cycle, fs k,i is the flight speed of the kth UAV at the i-th moment of the detection cycle, θ k,i is the angle between the flight direction of the kth UAV and the wind direction at the i-th moment in the detection period.

4. The wind environment assessment method based on drone observation according to claim 1 is characterized in that: Determining a wind energy resource detection score according to the absolute wind speed information and the real-time environmental information includes: determining air density according to the temperature information, the humidity information and the pressure information; A wind energy resource detection score is determined based on the absolute wind speed information and the air density.

5. The wind environment assessment method based on drone observation according to claim 4 is characterized in that: Determining a wind energy resource detection score according to the absolute wind speed information and the air density includes: According to the formula Determine the wind energy resource detection score Wer of the detection period, where α1 and α2 are preset weights, Aws T Aws is the preset absolute wind speed information threshold. k,i is the absolute wind speed information of the kth UAV at the i-th moment in the detection cycle, W T is the preset wind power density threshold, ρ k,i is the air density at the kth UAV's location at the i-th moment in the detection period, K is the number of UAVs, k≤K, m is the number of moments in the detection period, i≤m, i, m, k and K are all positive integers.

6. The wind environment assessment method based on drone observation according to claim 1 is characterized in that: Determining a wind speed gradient detection score according to the absolute wind speed information and the drone position information includes: Determining a wind speed distribution function according to the drone position information and the absolute wind speed information; A wind speed gradient detection score is determined according to the wind speed distribution function.

7. The wind environment assessment method based on drone observation according to claim 1 is characterized in that: Determining a wind speed gradient detection score according to the wind speed distribution function includes: According to the formula Determine the wind speed gradient detection score Wg of the detection period, where β1 and β2 are preset weights, if is a conditional function, and Wtd T is the preset wind speed gradient threshold, Wtd T1 is the first preset wind speed gradient threshold, Wtd T2 is the second preset wind speed gradient threshold, Wtd T3 is the third preset wind speed gradient threshold, (x k,i ,y k,i ,z k,i ) is the position information of the kth UAV at the i-th moment of the detection cycle, A i (x k,i ,y k,i ,z k,i ) is the function value of the wind speed distribution function at the kth UAV at the ith moment of the detection period, K is the number of UAVs, k≤K, m is the number of moments in the detection period, i≤m, i, m, k and K are all positive integers.

8. A wind environment assessment system based on drone observation, characterized in that: include: A flight parameter module, used for obtaining the flight parameters of the drone combination at multiple moments in the detection cycle, wherein the flight parameters include: flight speed and flight direction, the drone combination includes multiple drones, and the x-axis coordinates and z-axis coordinates of each drone are the same, and the y-axis coordinates are different from each other, and the preset coordinate system is a coordinate system established based on a preset origin within the range where the observation area is located as the origin, the ground of the observation area as the coordinate system xoz surface, and the vertical upward direction as the coordinate system y axis; A position information module, used to obtain the position information of the drone in a preset coordinate system at multiple moments in the detection cycle; The environmental information module is used to obtain real-time environmental information of the observation area through a combination of sensors arranged on the drone at multiple times during the detection cycle, wherein the real-time environmental information includes: temperature information, humidity information, pressure information, relative wind speed information and wind direction information; An absolute wind speed module, used to determine absolute wind speed information according to the flight parameters and the real-time environmental information; A resource detection module, used to determine a wind energy resource detection score according to the absolute wind speed information and the real-time environmental information; A gradient detection module, used to determine a wind speed gradient detection score according to the absolute wind speed information and the drone position information; An assessment report module is used to generate a wind environment assessment report based on the wind energy resource detection score and the wind speed gradient detection score.

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