Calibration of heliostats of a thermo-electric solar energy plant

专利摘要:
The invention relates to a method for calibrating a heliostat of a field of heliostats, comprising the following steps: providing a linear transformation to convert three-dimensional coordinates into two-dimensional coordinates in pixels in an image; obtaining the actual three-dimensional coordinates of the corner points of the reflective surface of each heliostat, for an image captured by a first image-capturing device and an image captured by a second image-capturing device at a determined time; obtaining the two-dimensional coordinates of the corner points of the reflective surface; identifying the contour of the reflective surface of each heliostat in each image; and identifying an ROI in each image. As well as, for each selected heliostat, obtaining a first parameter of the intensity of the pixels of the ROI corresponding to the heliostat in the image captured by the first device; obtaining a second parameter related to the intensity of the pixels of the ROI corresponding to the heliostat in the image captured by the second device; determining adjustments to be applied to the heliostat; and applying the adjustments.
公开号:ES2671847A2
申请号:ES201890022
申请日:2015-10-16
公开日:2018-06-08
发明作者:Pablo CLIMENT SÁNCHEZ；Markus SCHRAMM；Irene OÑA ESCATLLAR
申请人:Abengoa Solar New Technologies SA；
IPC主号:

专利说明:

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Calibration of heliostats of a thermoelectric solar power plant
DESCRIPTION
The present invention relates to the calibration of heliostats of a thermoelectric solar power plant with a central receiver in a tower and more specifically to procedures, systems and software products for the calibration of heliostats of the heliostat field of said power plant solar thermal tower with a central receiver.
BACKGROUND
The tower thermoelectric solar power plants with a central receiver comprising a heliostat field where at least one heliostat (structure formed by a reflective surface to follow the position of the sun on two axes: elevation and azimuth) are known in the state of the art ) that reflects solar radiation at a focus point generally located on a receiver located high on a tower which reaches high temperatures in order to heat a fluid or heat transfer material.
In relation to these plants, some procedures for calibrating heliostat fields are known.
A first procedure is based on the temporary blurring of certain heliostats with respect to a second receiver, target or target, said sensor heliostats or reference surfaces located in the heliostat itself being used to perform the calibration.
Other known procedures are based on the emission of additional light beams to solar radiation to check the proper calibration of the heliostat. In addition, it is also possible to use cameras as calibration equipment, said cameras being placed directly on the reflective surface of each heliostat to be calibrated.
On the other hand, the most common calibration procedure for a current commercial thermoelectric solar power plant with a central receiver in a tower (for example, PS10: 624 heliostats, PS20: 12550 heliostats, PS50: 4120 heliostats) requires the participation of operators . Therefore, man-hours will increase proportionally with the number
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Total heliostats of the plant and, in the same way, the recalibration frequency will be reduced.
In summary, the known procedures are not the most efficient solution for thermoelectric solar power plants with a central receiver in a tower that comprises high-power heliostat fields (higher than current powers) and, therefore, with a very high number of heliostats.
Consequently, there is a need for a system that at least partially solves the problems mentioned above.
SUMMARY OF THE INVENTION
In a first aspect, a calibration procedure is disclosed for at least one heliostat selected from a heliostat field of a thermoelectric solar power plant. Said plant may comprise at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices, each of which is configured to capture an image of the heliostat field at certain times. The imaging devices are arranged to receive circumsolar radiation reflected by the heliostats. The procedure may include:
- Provide, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of that point in a captured image;
- Obtain the actual three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
For at least one image captured by a first imaging device at a given time and an image captured by a second imaging device at a given time:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
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- Identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Identify a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Determine positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Apply the determined positioning settings to the selected heliostat.
Thus, to answer the question about the benefits of the proposed procedure compared to the currently established system, it is necessary to take into account some of the factors involved in a plant size: the size of the recipient, the permissible errors for Each heliostat and the operation strategy. For a commercial heliostat plant, 3 mrad is established as the maximum acceptable error criterion, where heliostat errors in the form of convolution are included.
Basically, the mechanical errors defined for a heliostat in a plant are four: assembly error, deformation error due to its own weight, tracking error and facet manufacturing error. Seeing this from an example, if these errors are allowed to exceed those already established (which could cause a field error greater than 3 mrad), for the same required power, the receiver should necessarily be larger, which results in greater thermoelectric losses, therefore, larger field sizes are required.
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On the contrary, maintaining the overall error of the plant less than or equal to 3 mrad, it is possible to increase / decrease the errors that compose it so that the result is maintained. If a large tracking error is established, there will be little room for deformations by the weight itself, resulting in very rigid structures and higher investment requirements for its foundation.
With the described procedure it is intended to reduce the tracking error so that there is a greater tolerance in deformations by the weight itself, which would mean a reduction in the cost of the heliostat structure, and therefore of the solar field. It would also facilitate the development of new heliostat designs, seeking to optimize other parameters without the main objective of minimizing deformations.
As for achieving a better overall monitoring in the plant, the implementation of pointing strategies will be favored in order to achieve a homogenized flow in the receiver with a minimum flow overflow.
In addition to these mentioned advantages, it should be added, as mentioned above, that the proposed procedure is independent of the size of the field, unlike the case with known systems, whose efforts to calibrate the monitoring increase proportionally with the number of heliostats in field.
The need has therefore been established to find an alternative for the calibration of heliostat monitoring in higher energy plants and larger solar fields. The procedure proposed here only requires investment in hardware and the time required to generate an algorithm capable of correcting the position of each heliostat. As for the maintenance of the same, there must be an operator who periodically verifies the proper functioning of the system, but in no way will it require the resources required by current procedures.
On the other hand, the imaging devices arranged to receive the circumsolar radiation reflected by the heliostats allows to reduce the impact of the high temperature to which they would be subjected (since the circumsolar region has lower intensities), together with a procedure of cooling applied to them (for example, an imaging device such as a camera can be inserted into steel housings
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high temperature resistant stainless, up to 400 ° C, in one of its components - borosilicate window - and can be cooled with water).
If it is difficult or not possible to identify the contour of the reflective surface of a selected heliostat in a captured image (for example, due to the shadows of the tower on a heliostat in the first row which will result in a very dark image on the that it may not be possible to determine the contour of the heliostat with sufficient accuracy), said captured image can be discarded. Alternatively, other procedures can be applied for the processing of the captured images.
On the other hand, depending on the type of imaging device used there may be an optional stage of conversion of each captured image to, for example, digital monochrome or grayscale taking into account the regions of interest identified, so that each pixel in each region of interest it can have an assigned intensity value. Thus, if the imaging devices used capture the images in digital monochrome or grayscale, this stage may not be necessary and if they do it in digital color the previous stage could be convenient but not mandatory.
For some cases, and for at least one selected heliostat, the identification of a region of interest in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, may comprise the identification of the region of interest as the totality of the reflective surface of the selected heliostat, that is, the region of interest identified in the heliostat corresponds to the entire reflective surface of said heliostat.
According to some examples, the method, for at least one selected heliostat, may further comprise determining at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
In this way, the objective of this stage is the extraction of the shaded / blocked area as a result of the stepped configuration of the solar field. Consequently, the part of the heliostat that remains shaded / blocked should be considered if there is
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overlaps between heliostats, in which case only the part not shaded / unlocked in the evaluation should be taken into account.
In some examples, the step of determining at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image may comprise:
- Provide at least one heliostat of the heliostat field that overshadows / blocks the reflective surface of the selected heliostat at the given time;
- Obtain the actual three-dimensional coordinates of the blocked / shaded region of the reflective surface of the selected heliostat taking into account the heliostat provided from the heliostat field that overshadows / blocks the reflective surface of the selected heliostat;
- Obtain the two-dimensional coordinates in pixels of the shaded / blocked region of the reflective surface of the selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the shaded / blocked region and the linear transformation provided.
In some cases, the step of identifying a region of interest in each captured image taking into account the identified contour of the reflective surface of the selected heliostats may comprise:
- Identify the region of interest by removing the shaded / blocked region of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels of the shaded / blocked region of the reflective surface of the selected heliostat.
According to some examples, the first image taking device and the second image taking device can be arranged vertically and in which the step of determining the positioning adjustments to be applied to the selected heliostat can comprise the determination of settings of positioning related to the elevation of the selected heliostat.
In some examples, the first imaging device and the second imaging device may be arranged horizontally and in which the determination of the positioning adjustments to be applied to the selected heliostat may comprise the
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Determination of positioning adjustments related to the azimuth of the selected heliostat.
On the other hand, the image-taking devices may comprise, for example, four image-taking devices, two of which may be arranged vertically and the other two may be arranged horizontally and in which the step of determining the settings of positioning to be applied to the selected heliostat may comprise the determination of positioning adjustments related to the elevation and azimuth, respectively, of the selected heliostat.
In some examples, the step of obtaining the real three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image may comprise:
- Provide the real three-dimensional coordinates of the pivot point of the selected heliostat;
- Provide the real three-dimensional coordinates of the focus point (in English, aiming point);
- Provide the position of the sun in azimuth and elevation at the given time;
- Provide the size of the reflective surface of the selected heliostat;
- Determine the solar vector from the point of rotation of the selected heliostat towards the sun taking into account the real three-dimensional coordinates of the point of rotation of the selected heliostat and the position of the sun in azimuth and elevation;
- Determine the vector from the rotation point of the selected heliostat to the focus point taking into account the actual three-dimensional coordinates of the selected heliostat rotation point and the actual three-dimensional coordinates of the focus point;
- Determine the normal vector of the reflective surface of the selected heliostat taking into account the solar vector, the vector from the rotation point of the selected heliostat to the focus point;
- Obtain the position of the reflective surface of the selected heliostat in azimuth and elevation from the determined normal vector;
- Identify the actual three-dimensional coordinates of the points of the corners of the reflective surface of the selected heliostat taking into account the position obtained from the reflective surface of the selected heliostat in azimuth and elevation, the size of the reflective surface of the selected heliostat and the three-dimensional coordinates Actual rotation point of the selected heliostat.
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In some examples, the position of the sun in azimuth and elevation can be based on the geographical coordinates of the plant, hourly data at the given time and meteorological data at the given time.
According to some examples, the step of determining the normal vector to the reflective surface of the selected heliostat can be performed by a mathematical formula related to the law of reflection:
fi + S 2 cos
in which it represents the vector from the point of rotation of the selected heliostat to the point of focus, S represents the solar vector, H represents the normal vector and 0 is the angle of incidence and reflection of solar radiation.
In some examples, the step of obtaining a first parameter related to the intensity value of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device may comprise:
- Identify the pixels included in the region of interest;
- Obtain the first parameter related to the average intensity of the identified pixels.
Thus, for example, if the captured image is in a digital grayscale format (for example, because the imaging device is a grayscale digital camera or because the captured image has been converted to a scale format digital gray) The average intensity may be the average gray scale of the pixels identified in the region of interest.
In some examples, the step of obtaining a second parameter related to the intensity value of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device may comprise:
- Identify the pixels included in the region of interest;
- Obtain the second parameter related to the average intensity of the identified pixels.
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According to some examples, the step of determining the positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained comprises, for each determined moment:
- Compare the first parameter obtained with the second parameter obtained;
- Determine if the comparison between the first parameter obtained and the second parameter obtained results in the same;
If the first parameter and the second parameter are not equal,
- Apply a default positioning adjustment to the selected heliostat;
For at least one new image captured by the first image capture device of the image capture devices and a new image captured by the second image capture device of the image capture devices:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of the selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the corners of the corners of the reflective surface of the corresponding heliostat selected in each captured image , and the linear transformation provided;
- Identify a contour of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostat in each captured image;
- Identify a region of interest of the selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat;
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Transfer the control of the procedure to the previous stage of comparison of the first parameter obtained with the second parameter obtained;
If the first parameter and the second parameter are equal,
- Set at least one predetermined setting as the determined positioning adjustment applied to the selected heliostat.
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In some examples, the method may further comprise, if the first parameter and the second parameter are the same, store, for example in a repository (more specifically, for example, a database), at least one predetermined positioning adjustment applied to the selected heliostat, associated to the difference value between the first parameter and the second parameter. Thus, when the first and second parameters are not equal, the procedure may comprise a previous step of determining if the repository stores said default settings relative to the difference between the first and second parameters so that, if it exists, it is not necessary perform all the described steps, since it is possible to automatically obtain the default settings to be applied to the heliostat for said difference. Therefore, the default settings associated with the difference may correspond to the settings determined to apply to the selected heliostat.
According to some examples, the determination of the positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained can comprise, for each determined moment:
- Provide a mathematical function f (x) that represents the solar radiation reflected by the selected heliostat on the receiver or alternatively on a target, at the given time considering that the selected heliostat is pointing perfectly at the focus point (aiming point), being solar radiation dependent on distance from the focus point;
- Provide the distance between the first imaging device and the focus point to the receiver;
- Provide the distance between the second imaging device and the focus point to the receiver;
- Determine the distance to be corrected in the heliostat from:
fW + CÚ = G1 f (d - C2) G2
in which G1 is the first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device, G2 is the second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the
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image captured by the second imaging device; C1 is the distance provided between the first imaging device and the focus point, C2 is the distance provided between the second image device and the focus point to the receiver; d is the distance to be determined;
- Obtain the positioning adjustments to be applied to the selected heliostat taking into account the determined distance d.
x of f (x) is the distance from the point of focus (aiming point) to the receiver to any point of the receiver or to an imaging device. The focus point corresponds to x = 0.
In another aspect, a computer program is disclosed. The computer program may comprise program instructions for having a computer system perform a procedure of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant as described above.
The computer program can be included in a storage medium (for example, a CD-ROM, a DVD, a USB drive, in a computer memory or in a read-only memory) or carried on a carrier signal (for example, in an electrical or optical carrier signal).
According to another aspect, a system for calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant is disclosed. Said plant may comprise at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices each of which is configured to capture an image of the heliostat field at certain times, said devices being Taking pictures ready to receive circumsolar radiation reflected by heliostats. The system may include:
- Means for providing, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of said point in a captured image;
- Means for obtaining the real three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
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For at least one image captured by a first imaging device of the imaging devices at a given time and an image captured by a second imaging device of the imaging devices at the given time:
- Means for obtaining the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each heliostat selected in each image captured taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
- Means to identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Means for identifying a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Means for obtaining a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Means for obtaining a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Means for determining positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Means for applying the determined positioning settings to the selected heliostat.
In addition, the system may optionally comprise means for converting each captured image to monochrome or grayscale taking into account the regions of interest identified, so that each pixel in each region of interest can have a monochrome level or gray level value. .
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In some cases, the system may further comprise means for determining at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
According to yet another aspect, a computer system is disclosed. Said computer system may comprise a memory and a processor, containing instructions stored in the memory and executable by the processor, the instructions comprising functionalities for executing a method of calibrating at least one heliostat selected from a heliostat field of a solar power plant thermoelectric as described above.
According to another aspect, a system for calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant is disclosed. Said plant may comprise at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices each of which is configured to capture an image of the heliostat field at certain times. Such imaging devices are arranged to receive circumsolar radiation reflected by heliostats. The system can be configured to:
- Provide, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of that point in a captured image;
- Obtain the actual three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
For at least one image captured by a first imaging device at a given time and an image captured by a second imaging device at a given time:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
- Identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in
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pixel points of the corners of the reflective surface of the selected heliostats in each captured image;
- Identify a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Determine positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Apply the determined positioning settings to the selected heliostat.
In some cases, the system may be configured to determine at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
According to some examples, the system may be configured to convert each image captured to grayscale taking into account the regions of interest identified, so that each pixel in each region of interest has an assigned intensity value corresponding to its level of Gray.
In some examples, in the disclosed systems, the imaging devices may be positioned such that the radiation reflecting the reflective surface of each heliostat towards the receiver may be at an angle greater than 4.65 mrad.
Additional objects, advantages and features of embodiments of the invention will be apparent to those skilled in the art upon examination of the description, or can be learned by the practice of the invention.
BRIEF DESCRIPTION OF THE DRAWINGS
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Non-limiting examples of the present disclosure will be described below, with reference to the attached drawings, in which:
Figure 1 illustrates a schematic diagram of a proposed configuration with an arrangement comprising four cameras according to some examples;
Figure 2 illustrates a graphic diagram of a standard function representing the solar form;
Figure 3 illustrates a schematic diagram of the reflection from a heliostat to a focus point according to some examples;
Figure 4 illustrates an image captured by a camera and processed by a Canny operator according to some examples;
Figure 5 illustrates a schematic diagram of a heliostat block / shadow intersection on a heliostat according to some examples;
Figure 6 illustrates a schematic diagram of a theoretical curve representing the flow map of the heliostat pointing to the focus point and the position of a heliostat without tracking error and a curve representing the actual position of said heliostat.
DETAILED DESCRIPTION OF EMBODIMENTS
Calibration system for a tower thermoelectric solar power plant (the plant may comprise one or more towers), whose plant may comprise a heliostat field with at least one heliostat (structure formed by a reflective surface to follow the sun's position in two axes: elevation and azimuth) and at least one focus point located preferably in the tower and where the solar radiation reflected by the heliostats focuses. Said focus point is preferably placed on a solar receiver that reaches high temperatures. In the present description, the plant comprises a tower and a plurality of heliostats, for example ten heliostats.
In addition, the plant may comprise a plurality of imaging devices (for example, video cameras or cameras or a combination of both) each of which is configured to capture an image of the heliostat field at certain times ( for example, 0.5 seconds <capture <10 minutes), said imaging devices being arranged to receive circumsolar radiation (caused by the attenuation of solar radiation due to the presence of water vapor and particles
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aerosols in the atmosphere) reflected by heliostats in the heliostat field. In general, in the present description, it refers to the placement of a total of four industrial cameras (for example, artificial vision), which capture the entire solar field during a full day of operation from a fixed position (for example, near or around the receiver arranged in the tower), in order to be used until the end of the life of the plant. These four industrial cameras can be of the standard Gigabit-Ethernet camera type. They can also be monochromatic cameras and with a CCD sensor.
As described above, it is important to note that the chambers are arranged to receive circumsolar radiation from the sun and reflected by heliostats in the heliostat field. Figure 1 illustrates a schematic diagram of a proposed configuration of the arrangement of the four cameras near or around the receiver 11 provided in the tower 10 of the plant. It can be seen that there are a pair of horizontal cameras 14, 15 and a pair of vertical 12, 13 (ie, two of the four cameras are arranged vertically and the other two are arranged horizontally). The object is to correct the movement of heliostat 16 in its two axes of movement: azimuth and elevation. In this way, the cameras 14, 15 in the horizontal direction (azimuth) will analyze the intensity of the reflective surface of each heliostat to obtain its average and the value obtained will be compared by each one of them. For a field pointing to the center of the receiver 11, in which the chamber on the right 14 has a greater intensity than the one on the left 15, this will mean that the orientation of the heliostat 16 must be corrected to the left until the intensities The same applies to cameras 12, 13 in a vertical position (elevation): they analyze the intensity of the reflective surface of heliostats, which are compared to determine in which direction they should be directed so that both cameras obtain the same gray value . In this way, the images captured by the cameras must be analyzed taking into account the pairs of cameras, that is, the images captured by the pair of cameras arranged in the horizontal direction must be analyzed together and the same must be applied to the images captured by the pair of cameras arranged in the vertical direction. For this reason, although the examples present comprise four cameras, the description will be based on a pair of cameras (and therefore a pair of images captured by these cameras at certain times), for example, the cameras arranged in the horizontal direction . Obviously, what is disclosed for said pair of cameras can also be applied to the pair of cameras arranged in the vertical direction.
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However, when the plant comprises, for example, a circular heliostat field with a cylindrical outer receiver, the system may comprise more than four cameras and it may not be necessary for the cameras to be paired.
As is known, solar radiation is represented as a cone, which will be seen from a point of origin at a certain angle. The amplitude of said solar angle may vary, since it will depend largely on the condition of the atmosphere at the time the measurement is made.
Figure 2 shows a graphic diagram of a standard function representing the solar form or energy emission profile of the solar disk in which the X axis represents the angular distance from the center of the sun cone while the Y axis represents radiation relative. As can be seen in this figure, the radiation corresponding to the solar disk as an annual average is obtained by an angle of approximately 4.65 mrad (~ 0.27 ° in the diagram), considering circumsolar radiation from this value. It is observed how the solar form varies depending on the circumsolar region considered (10%, 20%, 30%, etc.). However, for a standard day, an aura of 4% is assumed.
Following this approach, the cameras can be placed in such a way that the radiation reflected by each reflective surface towards the receiver is at an angle greater than 4.65 mrad, that is, the angle formed by the straight lines that join the center of the heliostat with the position of the camera and the center of the receiver (the focus point (aiming point)) is not greater than 4.65 mrad, thus ensuring that the flow received by each camera of each heliostat in the field comes from the circumsolar region.
The positioning of the chambers in that region allows, in the first place, to reduce the impact of the high temperature to which they are subjected (since the circumsolar region has lower intensities), together with the cooling procedure applied to them (the chambers will be inside stainless steel housings resistant to high temperatures, up to 400 ° C, in one of its components - borosilicate window - and will be cooled with water).
According to some examples, in the present configuration, the distance between each pair of cameras 12, 13; 14, 15 should be symmetric with respect to the central point of the receiver (the focus point (aiming point)), so that the gray values recorded by each pair correspond to the exact same area of the circumsolar region.
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It should be noted that said disclosed configuration may vary depending on the type of heliostat field analyzed.
On the other hand, it is also important to identify the pivot point of each heliostat or a predetermined set of heliostats selected from the heliostat field. Basically, it consists in automatically finding the turning point of said heliostats, which does not vary with respect to the position of the heliostat, and for a first approximation, it would be sufficient to identify the center point of the reflective surface of the heliostat.
Four heliostats are randomly chosen (which can be, for example, three or more heliostats) in an image captured by one of the cameras and the four corners of each corner of each randomly selected heliostat are selected (more specifically, from the reflective surface of each heliostat) thereby obtaining the pixel coordinates of the four corners of each of said heliostats, the coordinates of the center of the heliostat being calculated in pixels (Xcpixel, Ycpixel, Zcpixel) from said coordinates and by geometry. In this way, the coordinates of the center of each randomly chosen heliostat are obtained from the captured image.
Since the actual three-dimensional coordinates of the pivot point of each randomly selected heliostat are known (i.e., the coordinates of the pivot point of each randomly selected heliostat at a given time, that is, at the time of capturing the image) (Xc , Yc, Zc), the actual three-dimensional coordinates of the center of each randomly selected heliostat can be related to the pixel coordinates of the center of the corresponding randomly selected heliostat of the image (Xcpixel, Ycpixel, Zcpixel). Basically, it is possible to obtain a linear transformation or any other mathematical relationship to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of that point in a captured image.
The result obtained is used as an initial calibration of the system in order to be able to locate the region of interest in the image, so that portions of the image are identified which will be used below for a intended purpose. In this case, the regions of interest of the image are the reflective surfaces of the heliostats, with the pixels that will have a greater intensity than in other areas of the image.
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Consequently, it is necessary to determine the center point of each heliostat (or of each selected heliostat) and the space that said heliostat occupies in the image. In this way, subsequent calculations are simplified and a range can be established in which each heliostat would be located based on the value of the coordinates found at the pivot point.
To do this it is necessary to know in advance the real three-dimensional coordinates of the plant from which a relationship must be established between the pixels that describe the heliostats and their real position in the heliostat field. For example, the methodology used can be based on the principle of least squares optimization, so that from an initial solution and defining an objective function, the optimum that minimizes said function is located. In addition, the ray tracing and reverse ray tracing algorithms converge simultaneously: ray tracing from the camera sensor (usually the analyzed image) to the three-dimensional field and vice versa.
The calculation of said relationship between pixels and real coordinates is based on the operation of the geometric model of an appropriate camera. It is important to note that the image shown on the sensor will appear inverted, following the slope of the line directed from the object to the nodal point (point of the camera lens where all the rays of the photographed space converge to give rise to the inverted image formation in the sensor).
Applying the same reasoning, it is directly interpreted that the three-dimensional field of heliostats are the objects to be detected in the sensor, which are represented in each image as pixels.
As described above, to determine the centers of the reflective surface of each heliostat or each selected heliostat, a number of heliostats (> 3) is chosen randomly. Each of its four corner points is selected, so that these pixels are fixed in the image. From these points of the corners the center is obtained and is related to the three-dimensional coordinates of the field.
Rays are then drawn from the pixels selected as centers of the heliostats in the image to the nodal point of the camera to define, by
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optimization, the rotation and translation matrices (that is, a linear transformation or any other mathematical relationship to convert real three-dimensional coordinates of a point of the plant to two-dimensional coordinates in pixels of said point of the captured image) that allows to pass from a system Three-dimensional to a two-dimensional camera system:
n
min.f = ^ rms (d (Pj, rayi ')'), n = 1: total number of heliostats
¿= I
in which Pi are the coordinates of the pivot point of each heliostat in the solar field and rayi are the rays drawn from the pixels to the nodal point. The search of the matrices is done by minimizing the distance between the rays that go from the pixel "i" (center of the heliostat "i" in the image) through the nodal point, and that contain the real center (pivot point) of the corresponding heliostat "i" (following the established camera model).
The straight line that goes from the nodal point to the heliostat in the field does not initially pass through the real center of said heliostat, so it is necessary to find the angle that this heliostat must be rotated so that the line coincides with the center of rotation . For this, it is necessary to know the minimum distance.
The optimization algorithm will be repeated until each heliostat has been located, with the help of the rotation matrices, in the corresponding ray, that is, until the straight line coming from the node affects the real center of the heliostat. Once these matrices have been obtained, when they are applied on any real point of the field (for example, pivot points of the heliostats), the pixels corresponding to said real point of the image are obtained. In this way, the problem of moving from real three-dimensional coordinates to two-dimensional pixel coordinates in the image is solved. Basically, the matrices to move from one reference system to another are two, a matrix for rotation and a matrix for translation.
Once the disposition of the cameras is defined, the images captured by said cameras (according to the present examples, four images, one for each camera) at each given moment (for example, with a frequency <30 seconds, that is, capture four images every 30 seconds or less) can be processed (by
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for example, simultaneously) by a heliostat calibration system of the thermoelectric solar power plant, which will provide the adjustment of positioning offsets (in English, positioning offsets) for heliostats automatically and sequentially without having to manually act on them .
Said system may be implemented by computer means, electronic means or a combination thereof (i.e., said electronic / computer means can be used interchangeably, that is, one part of the means can be electronic means and the other part can be computer means , or all media can be electronic media or all media can be computer media) and must be able to reproduce a procedure to calibrate at least one heliostat selected from a heliostat field of a thermoelectric solar power plant. On the other hand, the system may be configured to perform or execute said procedure.
An example of a system comprising only computer means may be a computer system, which may comprise a memory and a processor, the memory being adapted to store a series of computer program instructions, and the processor being adapted to execute these instructions stored in the memory in order to generate the various events and actions for which the system has been programmed.
Such computer program instructions (resulting in a computer program) may cause the system to perform the procedure of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant, as described below according to some examples. The instructions of the computer program (i.e. the computer program) may be included in a storage medium (for example, a CD-ROM, a DVD, a USB drive, in a computer memory or in a read-only memory) or carried by a carrier signal (for example, an electrical or optical carrier signal).
The computer program may be in the form of source code, object code, an intermediate source between source code and object code in partially compiled form, or in any other form suitable for use in the implementation of the procedure. The carrier can be any entity or device capable of carrying the computer program.
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For example, the carrier may comprise a storage medium, such as a ROM, for example a CD ROM or a semiconductor ROM, or a magnetic recording medium, for example a hard disk. In addition, the carrier can be a transmissible carrier such as an electrical or optical signal, which can be transmitted through electrical or optical cable or by radio or by other means.
When the computer program is included in a signal that can be carried directly by a cable or other device or medium, the carrier may be constituted by said cable or other device or means.
Alternatively, the carrier may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to perform, or for use in performing the relevant procedure.
Examples of a system comprising only electronic means (i.e., a purely electronic configuration) may be a programmable electronic device such as a CPLD (Complex Programmable Logic Device), an FPGA (Field Programmable Gate Array) or an ASIC (application-specific integrated circuit).
In case the system is a combination of electronic and computer means, the computer means can be a set of computer program instructions and the electronic means can be any electronic circuit capable of implementing the corresponding stage or stages of said procedure.
According to some examples, the method of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant performed or executed by the system described above may comprise the following steps:
- Provide, for each camera (that is, each imaging device), a linear transformation (that is, the translation / rotation matrices obtained above) to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of said point in a captured image;
- Obtain the actual three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
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For at least one image captured by a first image capture device (for example, one of the cameras of the pair of cameras arranged in the horizontal direction) at a given time and an image captured by a second image capture device (the another camera of the pair of cameras arranged in the horizontal direction) at the given time (because the examples present comprise four cameras, the following steps must be repeated for the images captured by the cameras of the pair of cameras arranged in the vertical direction) :
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided (translation / rotation matrices);
- Identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Identify a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Obtain a first parameter related to the intensity (for example, the average gray level) of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity (for example, the average gray level) of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Determine positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Apply the determined positioning settings to the selected heliostat.
At this point it is important to emphasize that the procedure can also comprise an optional stage of conversion of each image captured to grayscale taking into account the regions of interest identified, so that each pixel in each region of
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Interest has an assigned intensity level. In this way, the intensity of the pixels corresponds to the gray level of the pixels.
Figure 3 shows the reflection from a heliostat to a point, which will be used to analyze the stage of obtaining the real three-dimensional coordinates of the points of the corners of the reflective surface of each selected heliostat. In the scheme of Figure 3, the key parameters to determine the position of each heliostat are identified:
- Coordinates of the pivot point of the heliostat (that is, real three-dimensional coordinates of the pivot point / center of the heliostat);
- Coordinates of the receiver in the tower (that is, real three-dimensional coordinates of the receiver), or more precisely the point of focus (aiming point);
- Position of the sun in azimuth and elevation.
At this point it should be taken into account that the real three-dimensional coordinates can be obtained with reference to the center of the tower, that is, the center of coordinates of the reference system can be the center of the tower. In addition, said real three-dimensional coordinates can be obtained from a surveyor (for example, during the construction of the plant) or from a floor plan.
The first two parameters disclosed (that is, the coordinates of the heliostat pivot point and the focus point coordinates) must be known as described above and supplied at the beginning of the system configuration.
As for the third (position of the sun in azimuth and elevation), the position of the sun can be obtained, for example, according to the publication "Solar Position Algorithm for Solar Radiation Applications, Ibrahim Reda and Andreas Afshin, NREL, January 2008" , whose input data is only the geographical coordinates of the plant, hourly data of the instant considered (that is, the determined moment at which the images are captured for each of the four cameras according to some examples) and meteorological data ( for example, pressure and temperature for the NREL procedure). The result will be the zenith / elevation and azimuth angles, which become the solar vector.
Knowing the solar vector S and the vector oriented from the heliostat to the receiver in the tower (that is, the reflection vector affecting the focus point (aiming point)),
It is possible to obtain the normal vector H of the reflective surface of the heliostat:
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fi + S 2 cos
in which it represents the vector from the point of rotation of the selected heliostat to the point of focus, S represents the solar vector, H represents the normal vector and 0 is the angle of incidence and reflection of solar radiation. It should be borne in mind that the normal vector will be different for each day and time of the year and consequently the position of the heliostat and the points of its corners will be different depending on the determined moment (that is, the moment of capture of the images by the cameras ).
The normal vector obtained can be converted to a tilt value of the heliostat at the given time. From the inclination given by the azimuth and elevation angles of the heliostat, the pivot point (which, as mentioned above, is always in the same position during the heliostat tracking) and the size of the heliostat, you can define the corner points of the heliostat as three-dimensional coordinates. Using the matrices calculated above, it would be possible to identify the points of the corners as pixels (two-dimensional coordinates in the captured image) and thus obtain a first approximation of the contour of the heliostat to be evaluated.
It should be noted that the term "heliostat size" may refer to the area and shape of the heliostat.
In summary, the stage of obtaining the real three-dimensional coordinates of the corners of the reflective surface of each selected heliostat may comprise the following sub-stages:
- Provide the real three-dimensional coordinates of the pivot point of the selected heliostat;
- Provide the real three-dimensional coordinates of the focus point (aiming point);
- Provide the position of the sun in azimuth and elevation at the given time (that is, the moment in which the image of the heliostat field is captured by the cameras);
- Provide the size of the reflective surface of the selected heliostat;
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- Determine the solar vector S from the turning point of the selected heliostat towards the sun taking into account the actual three-dimensional coordinates of the turning point of the selected heliostat and the position of the sun in azimuth and elevation;
- Determine the vector from the rotation point of the selected heliostat to the focus point (aiming point) taking into account the actual three-dimensional coordinates of the selected heliostat pivot point and the actual three-dimensional coordinates of the focus point;
- Determine the normal vector H of the reflective surface of the selected heliostat taking into account the solar vector and the vector from the rotation point of the selected heliostat to the focus point (aiming point);
- Obtain the position of the reflective surface of the selected heliostat in azimuth and elevation from the determined normal vector;
- Identify the actual three-dimensional coordinates of the corner points of the reflective surface of the selected heliostat taking into account the position obtained from the reflective surface of the selected heliostat in azimuth and elevation, the size of the reflective surface of the selected heliostat and the three-dimensional coordinates Actual rotation point of the selected heliostat.
On the other hand, the step of obtaining the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each heliostat selected in each captured image requires the actual three-dimensional coordinates previously obtained from the points of the corners of the corresponding reflecting surface. selected heliostat and the linear transformation provided (translation / rotation matrices) as described above.
With reference to the step of identifying a contour of the reflective surface of each selected heliostat in each captured image, segmentation of the captured image is required. This means dividing the captured image into its constituent parts: background and objects of interest. These objects will be the heliostats, which is what needs to be extracted from the image to calculate their intensity value or average gray level.
In this way, once the corner points of each selected heliostat have been identified (i.e., the two-dimensional pixel coordinates of the corners of the reflective surface of each selected heliostat) at the time
image capture, the outline of each heliostat (or selected heliostat) can
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be recognized (that is, it is possible to identify the contour of the reflective surface of the heliostat and identify the regions of interest taking into account these identified contours) in order to proceed to calculate the average intensity of each region of interest identified. There are several algorithms that achieve this goal and the most accepted standard is, for example, the one that was developed by JF Canny, 'Canny's edge detection method' as can be seen in Figure 4. To apply this operator, first, the image must be converted to grayscale and after its application, the result will be a binary image, in which 0 represents the black color and 1 the white color, the latter representing the contour of the detected objects.
Then, the pixels included in this area can be directly extracted (that is, in each region of interest of the captured images), thus obtaining an initial average value of the intensity (average gray level) of that heliostat for each Image captured and allowing verification of the calculated contour (in this case the region of interest corresponds to the entire reflective surface of the heliostat).
However, the initial average value obtained from the intensity (gray level) of that heliostat may not be its definitive value if a blocked or shaded area of the reflective surface of the heliostats can be identified. It is evident that, taking into account the blocked or shaded area of the reflective surface, the result of the process is improved.
In this way, the method can further comprise a step of determining at least one region / shaded / blocked area of the reflective surface of the selected heliostat in the captured images. Because the tower comprises four imaging devices (for example, cameras), this stage must be performed on each of the four captured images.
Consequently, the stage prior to the final calculation of the intensity of the region of interest of the heliostat may be the extraction of the shaded area as a result of the stepped configuration of the solar field. The part of the heliostat that remains blocked should also be considered, because if there are overlaps between heliostats, they should be taken into account in the evaluation of only the unlocked part.
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The procedure applied in this case may be, for example, the one described by G. Sassi in his publication "Some notes on shadow and blockage effects, Instituto di Física, Milan, Italy, 1983".
First of all, it is necessary to know for each heliostat in the field which are the heliostats that shade and block it at each annual moment. Once this is determined, the technique summarized graphically in Figure 5 can be implemented.
The coordinate system is transferred to the center of the heliostat of which it is desired to calculate the blocking / shadow part, and its center is represented by "O". For each heliostat around it, which is known to block / darken, its center is represented by "P" and a straight line from P is projected on the surface of the heliostat O with the inclination of the solar vector S (if shading is calculated ) or with the tilt vector from P to the center of the receiver (if the lock is calculated). The locked / shaded heliostat region will be known as a function of the value taken by the coordinates of point C as a result of the intersection. The area of that region is calculated according to the following formula:
U - | |
v = Ly- ye
in which Lx and Ly are the dimensions of the heliostat in study of center O, (xe, ye) are the coordinates of the point C indicated above and the locked / shaded region in each case will be given by:
A - u.v
Once this is known, this area calculated for the actual three-dimensional position of the heliostat must be related to the pixel image and can be implemented by means of the translation / rotation matrices provided above. Said area is removed from the effective surface of the heliostat in each image, the region of interest for that heliostat being the entire reflective surface minus the calculated area.
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In summary, the step of determining at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image may comprise:
- Provide at least one heliostat of the heliostat field that overshadows / blocks the reflective surface of the selected heliostat at the given time;
- Obtain the actual three-dimensional coordinates of the shaded / blocked region of the reflective surface of the selected heliostat taking into account the heliostat provided from the heliostat field that overshadows / blocks the reflective surface of the selected heliostat;
- Obtain the two-dimensional coordinates in pixels of the shaded / blocked region of the reflective surface of the selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the shaded / blocked region and the linear transformation provided.
In addition, the step of identifying the region of interest may include the removal of the shaded / blocked region of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels of the shaded / blocked region of the reflective surface of the selected heliostat.
Finally, after the completion of the remaining stages mentioned, the final value of the gray level of the heliostat captured by the chambers (arranged vertically or horizontally) must be calculated.
To do this, the step of obtaining a parameter (for example, the average) related to the gray level of the region of interest corresponding to the heliostat selected in the image may comprise:
- Identify the pixels included in the region of interest;
- Obtain the parameter related to the average gray scale of the identified pixels.
On the other hand, different processes can be used to implement the step of determining positioning adjustments to be applied to the selected heliostat.
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According to an iterative process (at least four cameras are required), for each selected heliostat, a first parameter (the first parameter previously disclosed) is generated from the first image (taking into account the region of interest identified), which It is the average intensity G1 of all pixels within the region of interest. In addition, a second parameter (the average intensity G2 of all pixels within the region of interest) is also generated from the second image. Once the first and second parameters have been obtained, a comparison is made between them. Thus, if the first parameter G1 and the second parameter G2 are not equal, an iterative process is initiated, in which the system applies a default setting to the heliostat in azimuth and / or elevation and captures new images until the level of Gray of each image from each camera matches or maintains a relationship defined as acceptable for example G1 = 0.5% G2.
On the other hand, it is possible to store in a repository (for example, a database) the default settings applied to the selected heliostat depending on the difference determined between the first and second parameters. Thus, when the system determines the difference between the first parameter and the second parameter, it searches the database if this difference is stored. If not, the disclosed iterative process begins. On the contrary, if the difference is registered in the database, the system can obtain the default settings (that is, the default settings correspond to the determined settings) to be applied to the selected heliostat to ensure that the heliostat points perfectly to the point of focus (aiming point).
More specifically, the step of determining the positioning adjustments to be applied to the selected heliostat (according to said first process) may comprise:
- Compare the first parameter obtained G1 with the second parameter obtained G2;
- Determine if the comparison between the first parameter obtained and the second parameter obtained results in the same;
If the first parameter and the second parameter are not equal,
- Apply a default positioning adjustment to the selected heliostat;
For at least one new image captured by the first image capture device of the image capture devices and a new image captured by the second image capture device of the image capture devices:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of the selected heliostat in each captured image taking into account
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counts the actual three-dimensional coordinates obtained from the corner points of the reflective surface of the corresponding heliostat selected in each captured image, and the linear transformation provided;
- Identify a contour of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostat in each captured image;
- Identify a region of interest of the selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat;
- Obtain a first parameter related to the intensity of the pixels (for example, the average gray level of the pixels) of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels (for example, the average gray level of the pixels) of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Transfer the control of the procedure to the previous stage of comparison of the first parameter obtained with the second parameter obtained;
If the first parameter and the second parameter are equal,
- Set at least one predetermined setting as the determined positioning adjustment applied to the selected heliostat.
According to an analytical process, theoretical curves can be used. As can be seen in Figure 6, a theoretical curve 70 is obtained from a simulation of the heliostat flow map pointing to the focus point (aiming point) with a tracking error of 0 mrad (ideal focus point). In this way, said theoretical curve can be represented by a mathematical function f (x) that represents the solar radiation reflected by the selected heliostat in the receiver at the given time taking into account that the selected heliostat is pointing perfectly at the point of focus ( aiming point), the solar radiation being related to the distance x with respect to the focus point (aiming point) (x = 0 corresponds to the focus point). From this theoretical curve you can obtain the value of W / m2 (that is, the solar radiation received) that the first chamber and the second chamber would receive if the heliostat pointed perfectly to the focus point (points P1 and P2 in W / m2 of curve 70 in which C1 and C2 represent the position of the cameras with respect to the focus point). Basically, said analytical process
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it comprises the execution of an iterative procedure until curve 71 is obtained which defines the actual position of the selected heliostat. Said curve 71 (equal to theoretical curve 70) is obtained when the following relationship is achieved:
fW + CÚ = G1 f (d - C2) G2
in which G1 is the first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device, G2 is the second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device; C1 is the distance provided between the first imaging device and the focusing point, C2 is the distance provided between the second imaging device and the focus point; d is the distance to be determined.
In addition, as can be seen in Figure 6, the distance between the cut-off point of the two curves with the X-axis in the example will provide (5m) the distance that must be corrected in azimuth or elevation in the heliostat, which can be convert to mrad taking into account the distance from the heliostat to the tower, and from mrad to pulses (that is, the settings determined to apply to the selected heliostat).
Thus, more specifically, according to said analytical process, the step of determining positioning adjustments to be applied to the selected heliostat may comprise:
- Provide a mathematical function f (x) that represents the solar radiation reflected by the selected heliostat in the receiver at the given time considering that the selected heliostat is pointing perfectly at the focus point (aiming point), the solar radiation being related to the distance from the focus point;
- Provide the distance C1 between the first imaging device and the focus point (aiming point);
- Provide the distance C2 between the second imaging device and the focus point (aiming point);
- Determine the distance to be corrected in the heliostat from:
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fW + C1) = G1 f (d - C2) G2
in which G1 is the first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device, G2 is the second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device; C1 is the distance provided between the first imaging device and the focusing point, C2 is the distance provided between the second imaging device and the focus point; d is the distance to be determined;
- Obtain the positioning adjustments to be applied to the selected heliostat taking into account the determined distance d.
It is important to note that in the present examples, the cameras (in the vertical position for elevation or in the horizontal position for azimuth) are at the same distance (C1 = C2) from the focus point (aiming point), but in other examples the Cameras can be provided at different distances from it. In this way, the solar radiation received by the first chamber and the second chamber if the heliostat points perfectly to the focus point could be different and this characteristic must be considered in the execution of the procedure described above.
Although only a number of particular embodiments and examples of the invention have been described herein, those skilled in the art will understand that other alternative embodiments and / or alternative uses of the invention and obvious and equivalent modifications thereof are possible. In addition, the present invention covers all possible combinations of the particular embodiments that have been described. Therefore, the scope of the present invention should not be limited by particular embodiments, but should be determined only by an impartial reading of the claims that follow.
In addition, although the examples described with reference to the drawings comprise computer apparatus / systems and processes performed on computer apparatus / systems, the invention also extends to computer programs, particularly computer programs in a carrier, adapted to implement the system.

权利要求:
Claims (27)
[1]
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1. A method of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant, said plant comprising at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices , each of which is configured to capture an image of the heliostat field at certain times, said imaging devices being arranged to receive circumsolar radiation reflected by the heliostats, characterized in that the method comprises:
- Provide, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of that point in a captured image;
- Obtain the actual three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
For at least one image captured by a first imaging device at a given time and an image captured by a second imaging device at a given time:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
- Identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Identify a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
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- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Determine positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Apply the determined positioning settings to the selected heliostat.
[2]
2. The method according to claim 1, further comprising:
- Convert each image captured to grayscale taking into account the regions of interest identified, so that each pixel in each region of interest has an assigned intensity value corresponding to its gray level.
[3]
3. The method according to any one of claims 1 or 2, wherein, for at least one selected heliostat, the identification of a region of interest in each captured image taking into account the identified contour of the reflective surface of the selected heliostat comprises identifying the region of interest as the entire reflective surface of the selected heliostat.
[4]
4. The method according to any one of claims 1 to 3, for at least one selected heliostat, further comprises:
- Determine at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
[5]
5. The method according to claim 4, wherein the determination of at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image comprises:
- Provide at least one heliostat of the heliostat field that overshadows / blocks the reflective surface of the selected heliostat at the given time;
- Obtain the actual three-dimensional coordinates of the blocked / shaded region of the reflective surface of the selected heliostat taking into account the heliostat provided from the heliostat field that overshadows / blocks the reflective surface of the selected heliostat;
- Obtain the two-dimensional coordinates in pixels of the shaded / blocked region of the reflective surface of the selected heliostat in each captured image having
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take into account the actual three-dimensional coordinates obtained from the shaded / locked region and the linear transformation provided.
[6]
6. The method according to claim 5, wherein the identification of a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat comprises:
- Identify the region of interest by removing the shaded / blocked region of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels of the shaded / blocked region of the reflective surface of the selected heliostat.
[7]
7. The method according to any one of claims 1 to 6, wherein the first imaging device and the second imaging device are arranged vertically and in which the step of determining the positioning adjustments to be applied to the Selected heliostat comprises determining positioning adjustments related to the elevation of the selected heliostat.
[8]
8. The method according to any one of claims 1 to 6, wherein the first imaging device and the second imaging device are arranged horizontally and wherein the determination of the positioning adjustments to be applied to the selected heliostat it comprises determining positioning adjustments related to the azimuth of the selected heliostat.
[9]
9. The method according to any of claims 1 to 6, wherein the imaging devices comprise four imaging devices, two of which are arranged vertically and the other two are arranged horizontally and in which the determination of the positioning adjustments to be applied to the selected heliostat comprises determining positioning adjustments related to the elevation and azimuth respectively of the selected heliostat.
[10]
10. The method according to any one of claims 1 to 9, wherein obtaining the real three-dimensional coordinates of the points of the corners of the reflective surface of each selected heliostat in each captured image comprises:
- Provide the real three-dimensional coordinates of the pivot point of the selected heliostat;
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- Provide the real three-dimensional coordinates of the focus point;
- Provide the position of the sun in azimuth and elevation at the given time;
- Provide the size of the reflective surface of the selected heliostat;
- Determine the solar vector from the point of rotation of the selected heliostat towards the sun taking into account the real three-dimensional coordinates of the point of rotation of the selected heliostat and the position of the sun in azimuth and elevation;
- Determine the vector from the rotation point of the selected heliostat to the focus point taking into account the actual three-dimensional coordinates of the selected heliostat rotation point and the actual three-dimensional coordinates of the focus point;
- Determine the normal vector of the reflective surface of the selected heliostat taking into account the solar vector, the vector from the rotation point of the selected heliostat to the focus point;
- Obtain the position of the reflective surface of the selected heliostat in azimuth and elevation from the determined normal vector;
- Identify the actual three-dimensional coordinates of the corner points of the reflective surface of the selected heliostat taking into account the position obtained from the reflective surface of the selected heliostat in azimuth and elevation, the size of the reflective surface of the selected heliostat and the three-dimensional coordinates Actual rotation point of the selected heliostat.
[11]
11. The method according to claim 10, wherein the position of the sun in azimuth and elevation is based on the geographical coordinates of the plant, hourly data at the given time and meteorological data at the given time.
[12]
12. The method according to any of claims 10 to 11, wherein the determination of the normal vector to the reflective surface of the selected heliostat is performed by a mathematical formula related to the law of reflection:
fi + S 2 cos
in which it represents the vector from the point of rotation of the selected heliostat to the point of focus, S represents the solar vector, H represents the normal vector and 0 is the angle of incidence and reflection of solar radiation.
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[13]
13. The method according to any of claims 1 to 12, wherein the determination of the positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained comprises, for each given moment:
- Compare the first parameter obtained with the second parameter obtained;
- Determine if the comparison between the first parameter obtained and the second parameter obtained results in the same;
If the first parameter and the second parameter are not equal,
- Apply a default positioning adjustment to the selected heliostat;
For at least one new image captured by the first imaging device and a new image captured by the second imaging device:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of the selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the corners of the corners of the reflective surface of the corresponding heliostat selected in each captured image , and the linear transformation provided;
- Identify a contour of the reflective surface of the selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostat in each captured image;
- Identify a region of interest of the selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat;
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Transfer the control of the procedure to the previous stage of comparing the first parameter obtained with the second parameter obtained;
If the first parameter and the second parameter are equal,
- Set as applied position adjustment at least one default setting.
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[14]
14. The method according to claim 13, further comprising, if the first parameter and the second parameter are the same:
- Store at least one default positioning setting applied to the selected heliostat.
[15]
15. The method according to any of claims 1 to 12, wherein the determination of the positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained comprises, for each given moment:
- Provide a mathematical function f (x) that represents the solar radiation reflected by the selected heliostat in the receiver or alternatively on a target, at the determined moment considering that the selected heliostat is pointing perfectly to the focus point, the solar radiation being related with distance from the focus point;
- Provide the distance between the first imaging device and the focus point;
- Provide the distance between the second imaging device and the focus point;
- Determine the distance to be corrected in the heliostat from:
fW + CÚ = G1 f (d - C2) G2
in which G1 is the first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device, G2 is the second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device; C1 is the distance provided between the first imaging device and the focus point, C2 is the distance provided between the second imaging device and the focus point; d is the distance to be determined;
- Obtain the positioning adjustments to be applied to the selected heliostat taking into account the determined distance d.
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The method according to any of claims 1 to 15, wherein obtaining a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device comprises :
- Identify the pixels included in the region of interest;
- Obtain the first parameter related to the average intensity of the identified pixels.
[17]
17. The method according to any one of claims 1 to 16, wherein obtaining a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device understands:
- Identify the pixels included in the region of interest;
- Obtain the second parameter related to the average intensity of the identified pixels.
[18]
18. A computer program comprising program instructions for having a computer system perform a method according to any one of claims 1 to 17 of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant.
[19]
19. The computer program according to claim 18, included in a storage medium.
[20]
20. The computer program according to any of claims 18 or 19, carried on a carrier signal.
[21]
21. A system for calibrating at least one selected heliostat from a heliostat field of a thermoelectric solar power plant, said plant comprising at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices each of which is configured to capture an image of the heliostat field at certain times, said imaging devices being arranged to receive circumsolar radiation reflected by the heliostats, characterized in that the system comprises:
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- Means for providing, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of said point in a captured image;
- Means for obtaining the real three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
For at least one image captured by a first imaging device at a given time and an image captured by a second imaging device at a given time:
- Means for obtaining the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each heliostat selected in each image captured taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
- Means to identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Means for identifying a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Means for obtaining a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Means for obtaining a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Means for determining positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Means for applying the determined positioning settings to the selected heliostat.
[22]
22. The system according to claim 21, further comprising:
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- Means for converting each image captured to grayscale taking into account the regions of interest identified, so that each pixel in each region of interest has an assigned intensity value corresponding to its gray level.
[23]
23. The system according to any of claims 21 or 22, further comprising:
- Means for determining at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
[24]
24. A computer system comprising a memory and a processor, containing instructions stored in the memory and executable by the processor, the instructions comprising functionalities for executing a method according to any one of claims 1 to 17 of calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant.
[25]
25. A system for calibrating at least one heliostat selected from a heliostat field of a thermoelectric solar power plant, said plant comprising at least one focus point that receives solar radiation reflected by the heliostats and a plurality of imaging devices each of which is configured to capture an image of the heliostat field at certain times, said imaging devices being arranged to receive circumsolar radiation reflected by the heliostats, the system being configured to:
- Provide, for each imaging device, a linear transformation to convert real three-dimensional coordinates of a point in the plant to two-dimensional coordinates in pixels of that point in a captured image;
- Obtain the actual three-dimensional coordinates of the corner points of the reflective surface of each selected heliostat in each captured image;
For at least one image captured by a first imaging device at a given time and an image captured by a second imaging device at a given time:
- Obtain the two-dimensional coordinates in pixels of the points of the corners of the reflective surface of each selected heliostat in each captured image taking into account the actual three-dimensional coordinates obtained from the points of the corners of the reflective surface of the corresponding heliostat selected in each image captured, and the linear transformation provided;
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- Identify a contour of the reflective surface of each selected heliostat in each captured image taking into account the two-dimensional coordinates obtained in pixels from the corners of the corners of the reflective surface of the selected heliostats in each captured image;
- Identify a region of interest of each selected heliostat in each captured image taking into account the identified contour of the reflective surface of the selected heliostat, each region of interest being associated with a reflective surface of the selected heliostat;
For each selected heliostat:
- Obtain a first parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the first imaging device;
- Obtain a second parameter related to the intensity of the pixels of the region of interest corresponding to the heliostat selected in the image captured by the second imaging device;
- Determine positioning adjustments to be applied to the selected heliostat by comparing the first parameter obtained with the second parameter obtained;
- Apply the determined positioning settings to the selected heliostat.
[26]
26. The system according to claim 25, configured to:
- Convert each image captured to grayscale taking into account the regions of interest identified, so that each pixel in each region of interest has an assigned intensity value corresponding to its gray level.
[27]
27. The system according to any of claims 25 or 26, configured to:
- Determine at least one shaded / blocked region of the reflective surface of the selected heliostat in each captured image.
[28]
28. The system according to any of claims 21 to 27, wherein the imaging devices are positioned such that the radiation reflecting the reflective surface of each heliostat towards the receiver is at an angle greater than 4.65 mrad.

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同族专利:

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公开号 | 公开日

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ZA201803173B|2020-05-27|

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CN108291742A|2018-07-17|

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ES2671847B1|2019-05-14|

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WO2017064339A1|2017-04-20|

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MA42559A1|2018-10-31|

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MA42559B1|2020-09-30|

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CN108291742B|2020-05-22|

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ES2671847R1|2018-07-05|

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PCT/ES2015/070754|WO2017064339A1|2015-10-16|2015-10-16|Calibration of heliostats of a thermo-electric solar energy plant|

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