Error correction method and system for heliostat in tower-type photo-thermal power generation system

Abstract

The invention discloses a heliostat error correction method and system in a tower-type photo-thermal power generation system, and relates to the technical field of solar heat utilization, and the method comprises the steps: obtaining a preset angle; controlling the heliostat to be corrected to rotate to a preset angle; a target image of the heat collection tower in the position and direction of the heliostat is collected by the unmanned aerial vehicle; identifying a heat collection area of the heat collection tower in the target image, judging whether the center of the heat collection area coincides with the center of the target image, if not, controlling the heliostat to rotate and collecting the target image again, and if the center of the heat collection area in the target image coincides with the center of the target image, recording the rotation angle of the heliostat to obtain a first rotation angle; and correcting the preset angle according to the first rotation angle. The method does not need to depend on light reflected by the heliostat, so that illumination is not required, the application range is wide, the unmanned aerial vehicle can fly autonomously, multiple cameras do not need to be installed in advance, and the operation complexity is greatly reduced.

Description

Technical Field

[0001] The present application relates to the technical field of solar thermal utilization, and in particular to a heliostat error correction method and system in a tower-type solar thermal power generation system. Background Art

[0002] In the tower solar thermal power generation system, heliostats are an important component. Heliostats are usually set around the collector tower. By reflecting sunlight to the collector tower, they can absorb and store the light and heat, and then use it to generate electricity. Since the direction of sunlight will change constantly, the heliostats also need to rotate continuously to accurately reflect sunlight on the collector tower. In this process, the angle control accuracy of the heliostats is relatively high.

[0003] Although the angle of each heliostat is estimated during the design of the solar thermal power plant, the installation of the heliostat involves foundation excavation, bracket installation, and mirror installation. Each process will cause certain errors. The accumulation of these errors may cause a large deviation between the actual posture of the heliostat and the designed posture. If it is put into use directly without correction, a considerable part of the solar thermal energy cannot be used. Therefore, the error correction will be carried out after the installation of the heliostat is completed.

[0004] However, the current technologies for heliostat error correction are all based on the light reflected by the heliostat. For example, CN102116604A and CN108413987A collect the spot image of sunlight reflected by the heliostat, and CN108958229A collects the light reflected by the heliostat to form an image. This technology requires the pre-installation of cameras, and since the number of heliostats is relatively large, multiple cameras need to be pre-installed or the position of the camera needs to be moved, which is very inconvenient to operate. Moreover, the use of light reflected by the heliostat has relatively high requirements for the weather. Not only does it require light, but the light intensity must also reach a certain value, which greatly limits the application of this technology. Summary of the invention

[0005] The embodiments of the present application provide a method and system for heliostat error correction in a tower solar thermal power generation system, so as to solve the problems of inconvenient operation and limited application of the prior art technology for error correction based on reflected light from heliostats.

[0006] On the one hand, an embodiment of the present application provides a method for correcting heliostat errors in a tower-type solar thermal power generation system, comprising: Acquiring design data, the design data including a preset angle of the heliostat; Controlling the heliostat to be corrected to rotate to a preset angle; The target image of the thermal collector tower at the location and direction of the heliostat is collected by a drone, wherein the drone is parked on the mirror surface of the heliostat, and the direction of the camera of the drone is the same as that of the heliostat; Identify the heat collection area of ​​the heat collection tower in the target image, and determine whether the center of the heat collection area in the target image coincides with the center of the target image. If not, determine the direction and distance of the center of the heat collection area in the target image relative to the center of the target image. Control the heliostat to rotate according to the direction and distance, and collect the target image again. If the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, record the angle at which the heliostat starts to rotate from the preset angle to obtain a first rotation angle. The preset angle is corrected according to the first rotation angle.

[0007] On the other hand, the embodiment of the present application further provides a heliostat error correction system in a tower-type solar thermal power generation system, comprising: A computer, used to obtain design data, the design data including a preset angle of the heliostat; A control mechanism, used for controlling the heliostat to be calibrated to rotate to a preset angle; A drone is used to collect a target image of the thermal collector tower at the location and direction of the heliostat, wherein the drone is parked on the mirror surface of the heliostat, and the direction of the drone's camera is the same as that of the heliostat; The computer identifies the heat collection area of ​​the heat collection tower in the target image, and determines whether the center of the heat collection area in the target image coincides with the center of the target image. If not, the computer determines the direction and distance of the center of the heat collection area in the target image relative to the center of the target image. The control mechanism controls the heliostat to rotate according to the direction and distance, and the UAV collects the target image again. If the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, the computer records the rotation angle of the heliostat from the preset angle to obtain a first rotation angle; and the preset angle is corrected according to the first rotation angle.

[0008] A heliostat error correction method and system in a tower-type solar thermal power generation system in the present application has the following advantages: The drone is stopped on the mirror surface of the heliostat to determine whether the mirror surface of the heliostat is facing the heat collection area of ​​the heat collection tower. If it is facing, it means that there is no error in the heliostat. Otherwise, the angle of the heliostat is adjusted, and the angle estimated in the design process is corrected according to the rotation angle. The method of the present application does not need to rely on the light reflected by the heliostat, so there is no requirement for lighting, and the scope of application is wide. In addition, the drone can fly autonomously, and there is no need to pre-install multiple cameras, which greatly reduces the complexity of operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0010] Figure 1 A flowchart of a heliostat error correction method in a tower-type solar thermal power generation system provided in an embodiment of the present application.

[0011] Figure 2 A schematic diagram of a portion of the flight route planned for a drone provided in an embodiment of the present application.

[0012] Figure 3 A schematic diagram of the analysis process of reference images taken by a drone provided in an embodiment of the present application.

[0013] Figure 4 A schematic diagram of an application scenario of a heliostat error correction system in a tower-type solar thermal power generation system provided in an embodiment of the present application.

[0014] Explanation of the accompanying drawings: 100, heliostat; 200, solar tower; 300, drone; 400, computer. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0016] Figure 1 A flowchart of a heliostat error correction method in a tower-type solar thermal power generation system provided in an embodiment of the present application. The present application embodiment provides a heliostat error correction method in a tower-type solar thermal power generation system, comprising the following steps: S100 , obtaining design data, where the design data includes a preset angle of the heliostat 100 .

[0017] For example, during the design of the solar thermal power plant, the angles of each heliostat 100 have been estimated in advance, including the horizontal angle and the pitch angle, and at the horizontal angle and the pitch angle, the heliostat 100 will face the heat collection area on the heat collection tower 200, that is, the normal of the center of the heliostat 100 passes through the center of the heat collection area. Therefore, during the calibration process after the heliostat 100 is installed, the preset angle including the horizontal angle and the pitch angle can be extracted from the design data.

[0018] S110, controlling the heliostat 100 to be calibrated to rotate to a preset angle.

[0019] Exemplarily, the heliostat 100 includes a bracket supporting the mirror surface in addition to the mirror surface, and a control mechanism for driving the mirror surface to rotate in the horizontal and vertical directions is arranged on the bracket, and these control mechanisms usually adopt a combination of a stepper motor and a gear. After the installation is completed, the mirror surface of the heliostat 100 is at an initial angle, and the initial angle may be the same as the preset angle or may be different. However, regardless of whether they are the same, the initial angle and the preset angle will be compared first. If the two are the same, the current state of the heliostat 100 will be maintained, otherwise the stepper motor will be driven to rotate, and the mirror surface of the heliostat 100 will be driven to rotate to the preset angle through the gear.

[0020] S120 , the drone 300 collects a target image of the thermal tower 200 at the location and direction of the heliostat 100 , wherein the drone 300 stops on the mirror surface of the heliostat 100 , and the direction of the camera of the drone 300 is the same as that of the heliostat 100 .

[0021] Exemplarily, the drone 300 is preferably a multi-rotor drone, a main body of which is provided with a rotatable camera, which rotates to a required angle under the control of the main body and captures images.

[0022] Furthermore, the drone 300 is provided with an attitude sensor, which can detect the real-time attitude angle of the drone, which also includes the horizontal angle and the pitch angle. When the drone 300 stops at the mirror surface of the heliostat 100, the drone 300 can collect the current real-time attitude angle, and control the camera to rotate to an angle perpendicular to the plane where the main body of the drone 300 is located according to the real-time attitude angle. At this time, since the main body of the drone 300 is parallel to the mirror surface of the heliostat 100, the camera will also be perpendicular to the mirror surface. If the mirror surface of the heliostat 100 is facing the heat collection area, the position of the heat collection area in the target image will be located at the center of the target image. By analyzing the target image, it can be determined whether there is an error in the heliostat 100.

[0023] Furthermore, before the drone 300 stops on the mirror surface of the heliostat 100, it collects a global image of the solar thermal power plant above the collector tower 200, and plans a correction sequence for each heliostat 100 after analyzing the global image. After determining the correction sequence, the drone 300 stops on the mirror surface of each heliostat 100 in turn according to the correction sequence.

[0024] Specifically, Figure 2As shown, a solar thermal power plant is arranged with a heat collecting tower 200 and a large number of heliostats 100, the heat collecting area is located at the top of the heat collecting tower 200, and the heliostats 100 are arranged with the heat collecting tower 200 as the center. Before collecting the target image of the location of each heliostat 100, the drone 300 will first collect a global image containing all heliostats 100 above the heat collecting tower 200, identify the heat collecting tower 200 and each heliostat 100 in the global image through the recognition model, and then formulate a flight route.

[0025] In an embodiment of the present application, the above-mentioned recognition model can be established based on a convolutional neural network. Before actual use, the recognition model needs to be trained and tested so that the recognition model can more accurately identify the solar tower 200 and the heliostat 100 in the target image.

[0026] After each heliostat 100 is identified, each subsequent heliostat 100 will be connected in series starting from a certain heliostat 100 according to a preset rule, forming a flight route formed by connecting the positions of multiple heliostats 100. Specifically, since the longitude and latitude coordinates of each heliostat 100 have been determined during the design, and there is almost no error in the longitude and latitude coordinates, the drone 300 can directly obtain the longitude and latitude coordinates of each heliostat 100 determined during the design stage, and then determine the longitude and latitude coordinates of each point on the flight route that needs to stop in combination with all flight routes. At this time, the flight route is converted into a broken line formed by connecting the points of multiple longitude and latitude coordinates in sequence. After determining the flight route, the drone 300 will use the positioning module to collect the real-time position during the flight, and determine whether the real-time position is the same as the longitude and latitude coordinates of the point to be reached. If they are the same, it means that the drone 300 has arrived above the heliostat 100, and then the target image can be collected.

[0027] Furthermore, when the drone 300 stops on the mirror surface of the heliostat 100, the camera of the drone 300 collects an edge image of the heliostat 100, and determines whether the drone 300 is located at the center of the mirror surface of the heliostat 100 according to the edge image. If not, the drone 300 adjusts its position until it is located at the center of the mirror surface of the heliostat 100.

[0028] Specifically, although the longitude and latitude coordinates of each point on the flight route have been determined in the above process, there is still a certain error in controlling the flight of the drone 300 based solely on the longitude and latitude coordinates. When the drone 300 flies and lands on a mirror, the camera of the drone 300 will capture the image of the edge of the mirror at a set angle and analyze the length of the mirror edge in the edge image. If the length is the same as or not much different from the preset length data, it means that the drone 300 has landed in the center of the mirror, and then the target image can be captured.

[0029] If the analysis of the edge image shows that the drone 300 is not in the center of the mirror surface, the drone 300 needs to take off and land again. In this process, when the drone 300 is close to the heliostat 100, the camera faces directly downward to collect the landing image, and the landing image is analyzed to determine whether the center of the landing image coincides with the center of the heliostat 100 in the landing image. If not, the position of the drone 300 is adjusted until the center of the landing image coincides with the center of the heliostat 100 in the landing image, and then the drone 300 descends and stops on the mirror surface of the heliostat 100.

[0030] Specifically, after acquiring the landing image, the recognition model is used to identify the mirror surface in the landing image, and then the geometric center of the mirror surface in the landing image is determined, and it is determined whether the geometric center coincides with the center of the landing image. If they coincide, it means that the drone 300 is directly above the mirror surface of the heliostat 100 at this time, and the drone 300 can land vertically downward and stop at the center of the mirror surface.

[0031] Furthermore, a suction cup is provided at the bottom of the drone 300 , and the suction cup is connected to a vacuum pump. When the drone 300 stops on the mirror surface of the heliostat 100 , the vacuum pump extracts the air in the suction cup, so that the drone 300 stops stably on the mirror surface of the heliostat 100 .

[0032] Specifically, since the heliostat 100 is in a tilted state when facing the thermal tower 200 , a suction cup is required to stably stop the drone 300 on the mirror surface.

[0033] S130, identifying the heat collection area of ​​the heat collection tower 200 in the target image, and determining whether the center of the heat collection area in the target image coincides with the center of the target image. If not, determining the direction and distance of the center of the heat collection area in the target image relative to the center of the target image.

[0034] Exemplarily, a recognition model may also be used for identifying the solar collection area. It should be understood that the recognition models appearing in the above multiple places do not represent the same model. These models may be established based on the same neural network, but are trained and tested separately using their own pre-prepared training samples and test samples.

[0035] After the heat collection area is identified, the edge of the heat collection area can be determined in the target image, and the geometric center of the closed area surrounded by the edge is the center of the heat collection area in the target image. If the center coincides with the center of the target image or the distance is very small, it is considered that the mirror surface of the current heliostat 100 is facing the heat collection area, that is, there is no error in the angle of the heliostat 100. If the pixel distance between the two centers exceeds the set threshold, it means that there is a large error in the heliostat 100. At this time, it is necessary to adjust the angle of the heliostat 100. Before adjusting the angle, it is necessary to first determine the direction and angle of adjustment. The direction is the direction of the center of the heat collection area in the target image relative to the center of the target image, and the angle can be determined according to the distance between the two centers in the target image.

[0036] S140, controlling the heliostat 100 to rotate according to the direction and distance, and collecting the target image again, if the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, recording the angle at which the heliostat 100 rotates from the preset angle to obtain a first rotation angle.

[0037] For example, if the heliostat 100 is still not facing the heat collection area after adjusting its angle, its angle may be adjusted again until the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image.

[0038] S150, correcting a preset angle according to the first rotation angle.

[0039] Exemplarily, the corrected preset angle may be obtained by calculating the sum of the first rotation angle and the preset angle.

[0040] Further, in order to ensure that the corrected preset angle can enable the sunlight reflected by the heliostat 100 to accurately illuminate the heat collection area, after determining the first rotation angle, the heliostat 100 rotates to the tracking angle in the automatic tracking mode, and the drone 300 collects a reference image at the position and direction of the heliostat 100, identifies the sun and the heat collection area in the reference image, and determines whether the centers of the sun and the heat collection area in the reference image are symmetrical about the center of the reference image. If not, adjust the angle of the heliostat 100 until the centers of the sun and the heat collection area in the reference image are symmetrical about the center of the reference image, record the angle at which the heliostat 100 rotates from the tracking angle, obtain the second rotation angle, and correct the preset angle according to the first rotation angle and the second rotation angle.

[0041] Specifically, Figure 3As shown in the figure, the outer rectangle represents the edge of the reference image, the inner rectangle represents the heat collection area, the circle represents the sun, and the central cross represents the center of the reference image. In theory, if the heliostat 100 reflects sunlight to the heat collection area, then in the reference image, the center of the sun and the center of the heat collection area will be located on opposite sides of the center of the reference image, and the distances between the two and the reference image will be the same. According to this principle, by analyzing the reference image, it can be determined whether the tracking angle can accurately reflect sunlight after the heliostat 100 enters the tracking mode according to the calibrated preset angle.

[0042] If it is found through analysis of the reference image that the heliostat 100 still cannot accurately reflect sunlight, the angle of the heliostat 100 can be adjusted again until the sunlight is accurately reflected, that is, the centers of the sun and the heat collecting area in the reference image are symmetrical about the center of the reference image. The second rotation angle obtained at this time can be summed with the first rotation angle, and the sum of the sum and the preset angle is the preset angle after secondary correction.

[0043] It should be understood that the presence of the sun is required during the secondary calibration process, so the light intensity data can be collected in advance by a light sensor to determine whether there is currently the sun. If there is no sun, there is no need for secondary calibration.

[0044] The embodiment of the present application also provides a heliostat error correction system in a tower-type solar thermal power generation system, such as Figure 4 As shown, the system includes: The computer 400 is used to obtain design data, wherein the design data includes a preset angle of the heliostat 100; A control mechanism, used for controlling the heliostat 100 to be calibrated to rotate to a preset angle; The drone 300 is used to collect a target image of the thermal tower 200 at the location and direction of the heliostat 100, wherein the drone 300 stops on the mirror surface of the heliostat 100, and the direction of the camera of the drone 300 is the same as that of the heliostat 100; The computer 400 identifies the heat collection area of ​​the heat collection tower 200 in the target image, determines whether the center of the heat collection area in the target image coincides with the center of the target image, and if not, determines the direction and distance of the center of the heat collection area in the target image relative to the center of the target image; The control mechanism controls the heliostat 100 to rotate according to the direction and distance, and the drone 300 collects the target image again. If the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, the computer 400 records the angle at which the heliostat 100 rotates from the preset angle to obtain a first rotation angle; and the preset angle is corrected according to the first rotation angle.

[0045] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0046] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for correcting heliostat errors in a tower-type solar thermal power generation system, characterized in that: include: Acquiring design data, the design data comprising a preset angle of the heliostat (100); Controlling the heliostat (100) to be calibrated to rotate to the preset angle; A target image of the heat collecting tower (200) at the location and direction of the heliostat (100) is collected by a drone (300), wherein the drone (300) is parked on the mirror surface of the heliostat (100), and the orientation of the camera of the drone (300) is the same as that of the heliostat (100); Identifying a heat collection area of ​​a heat collection tower (200) in the target image, determining whether the center of the heat collection area in the target image coincides with the center of the target image, and if not, determining the direction and distance of the center of the heat collection area in the target image relative to the center of the target image; Controlling the heliostat (100) to rotate according to the direction and distance, and collecting the target image again, if the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, recording the angle at which the heliostat (100) rotates from the preset angle to obtain a first rotation angle; The preset angle is corrected according to the first rotation angle.

2. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 1, characterized in that: Before the drone (300) stops on the mirror surface of the heliostat (100), a global image of the solar thermal power generation field is collected above the heat collecting tower (200), and a correction sequence for each heliostat (100) is planned after analyzing the global image. After determining the correction sequence, the drone (300) stops on the mirror surface of each heliostat (100) in sequence according to the correction sequence.

3. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 1, characterized in that: When the drone (300) stops on the mirror surface of the heliostat (100), the camera of the drone (300) collects an edge image of the heliostat (100), and determines whether the drone (300) is located at the center of the mirror surface of the heliostat (100) based on the edge image; if not, the drone (300) adjusts its position until it is located at the center of the mirror surface of the heliostat (100).

4. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 3, characterized in that: When the drone (300) is close to the heliostat (100), the camera faces directly downward to collect a landing image, and the landing image is analyzed to determine whether the center of the landing image coincides with the center of the heliostat (100) in the landing image; if they do not coincide, the position of the drone (300) is adjusted until the center of the landing image coincides with the center of the heliostat (100) in the landing image, at which time the drone (300) descends and stops on the mirror surface of the heliostat (100).

5. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 1, characterized in that: A suction cup is provided at the bottom of the drone (300), and the suction cup is connected to a vacuum pump. When the drone (300) stops on the mirror surface of the heliostat (100), the vacuum pump extracts air from the suction cup, so that the drone (300) stops stably on the mirror surface of the heliostat (100).

6. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 1, characterized in that: After determining the first rotation angle, the heliostat (100) rotates to the tracking angle in the automatic tracking mode, the drone (300) collects a reference image at the position and direction of the heliostat (100), identifies the sun and the heat collection area in the reference image, determines whether the centers of the sun and the heat collection area in the reference image are symmetrical about the center of the reference image, and if not, adjusts the angle of the heliostat (100) until the centers of the sun and the heat collection area in the reference image are symmetrical about the center of the reference image, records the angle at which the heliostat (100) rotates from the tracking angle, obtains a second rotation angle, and corrects the preset angle according to the first rotation angle and the second rotation angle.

7. The method for correcting heliostat errors in a tower-type solar thermal power generation system according to claim 6, characterized in that: The sum of the first rotation angle and the second rotation angle is taken, and the sum of the sum and the preset angle is used as the corrected preset angle.

8. A system using the heliostat error correction method in a tower-type solar thermal power generation system according to any one of claims 1 to 7, characterized in that: include: A computer (400) is used to obtain design data, wherein the design data includes a preset angle of the heliostat (100); A control mechanism, used for controlling the heliostat (100) to be calibrated to rotate to the preset angle; A drone (300) for collecting a target image of a heat collecting tower (200) at a location and direction of a heliostat (100), wherein the drone (300) is parked on a mirror surface of the heliostat (100), and a camera of the drone (300) is oriented in the same direction as that of the heliostat (100); The computer (400) identifies a heat collection area of ​​a heat collection tower (200) in the target image, determines whether a center of the heat collection area in the target image coincides with a center of the target image, and if not, determines a direction and distance of the center of the heat collection area in the target image relative to the center of the target image; The control mechanism controls the heliostat (100) to rotate according to the direction and distance, the drone (300) collects the target image again, and if the center of the heat collection area in the re-collected target image coincides with the center of the re-collected target image, the computer (400) records the angle at which the heliostat (100) rotates from the preset angle to obtain a first rotation angle; and the preset angle is corrected according to the first rotation angle.

Images