Assembly, use of assembly, and method for checking at least one parameter

Abstract

The present invention relates to an arrangement (100) for ascertaining at least one parameter for determining a component of global irradiance, the assembly comprising an evaluation / control device (110) and a camera assembly (120) having at least one camera, the at least one camera being fixed at a predetermined distance from the Earth's surface (20) while ascertaining the at least parameter, the camera assembly (120) being designed to capture camera data within a spatial field of view of approximately 360° around the camera assembly (120), the camera data being suitable for deriving information regarding solar radiation and / or the location and / or characteristics of clouds (12). The present invention also relates to the use of such an assembly, a method for ascertaining at least one parameter for determining at least one component of global irradiance, and a computer program.

Description

[Technical Field]

[0001] The present invention relates to an assembly for ascertaining at least one parameter for determining at least one component of global irradiance, to the use of the assembly for ascertaining at least one parameter for determining at least one component of global irradiance, and to a method for ascertaining at least one parameter for determining at least one component of global irradiance. [Background technology]

[0002] Cloud cameras and shadow cameras as well as corresponding assemblies and their applications are known, inter alia, from the non-patent document 1. This document describes a multi-camera assembly in which the cameras have a field of view oriented towards the sky and are able to record camera data from the sky. Shadow cameras arranged several hundred meters apart can record camera data of the Earth.

[0003] The cloud camera assembly can be used for automatic detection of the degree of cloud cover in the sky and for short-term prediction of solar radiation, for example for more efficient operation of power supply systems consisting of solar panels and diesel aggregates or battery storage units.

[0004] These cloud camera-based forecasting systems typically detect clouds in a camera image. The height and velocity of the cloud, and therefore its future position, can be determined using data from at least one second cloud camera. Forecasts of shading in specific areas can be made from the cloud positions.

[0005] Shadow camera assemblies are typically mounted on tall towers or mountain ridges overlooking the monitored area. Shadow cameras can be used to create high-resolution maps of solar radiation around the shadow camera's installation point. Shadow cameras with relatively narrow viewing angles are used. By comparing the location of cloud shadows in images across different timestamps, these systems can determine the velocity of clouds above the ground.

[0006] Solar power plant monitoring systems or solar resource measurement systems at proposed solar power plant sites often include pyranometers oriented toward the sky, and sometimes toward the ground, to measure radiation from the sky or radiation reflected from the ground. These measurements are used to evaluate the performance of the solar power plant or to assess the solar resource at the site.

[0007] Non-Patent Document 2 discloses a multi-camera assembly, consisting of six cameras, that takes images of the ground from a tall tower. [Prior art documents] [Non-patent literature]

[0008] [Non-Patent Document 1] Kuhn, P. et al. "Benchmarking three low-cost,low-maintenance cloud height measurement systems and ECMWF cloud heights against a ceilometer", Solar Energy, Vol.168, 2018, pp.140~152, DOI:10.1016 / j.solener.2018.02.050 [Non-patent document 2] "Shadow camera system for the generation of solar irradiance maps", Solar Energy, 157, 2017, 157~170.DOI:10.1016 / j.solener.2017.05.074 Summary of the Invention [Problem to be solved by the invention]

[0009] It is an object of the present invention to provide a cost-effective assembly for ascertaining at least one parameter for determining at least one component of global irradiance, wherein the measurement mechanism is located in one location.

[0010] Another object of the present invention is to provide a use of such an assembly for ascertaining at least one parameter for determining at least one component of global irradiance, the assembly cost-effectively and / or reliably ascertaining one or more parameters.

[0011] Another object of the present invention is to provide a method for ascertaining at least one parameter for determining at least one component of global irradiance, which method determines the at least one parameter cost-effectively and / or reliably. [Means for solving the problem]

[0012] These objects are solved by the features of the independent claims. Advantageous embodiments and advantages of the invention will become apparent from the further claims, the description and the drawings.

[0013] The following definitions apply to the inventive assembly for ascertaining at least one parameter for determining at least one component of global irradiance, the inventive use of the assembly, and the inventive method for ascertaining at least one parameter.

[0014] In the following, an evaluation / control device is understood to be a physical module or a logical grouping of interacting hardware and / or software components or a processor, which comprises at least one signal input for receiving camera data and at least one signal output for outputting measurement results and / or camera data.

[0015] At least one computing unit can evaluate the received camera data through corresponding programming and calculate at least one parameter and / or other measurement results. Multiple computing units can be provided, each performing one or more process steps and / or one or more evaluation steps. Additionally or alternatively, multiple computing units can be used to verify or determine one or more parameters. These or further computing units can determine one or more components of global irradiance. The calculations and / or determinations and / or verifications can be performed centrally at one location or distributed at different locations. At least one storage unit can store intermediate and / or final results and / or verified values ​​of the parameters and / or at least one component of global irradiance.

[0016] The camera data can be sent to the signal input or from the signal output via a cable or wirelessly. In the case of the inventive use of the invention and the assembly, one evaluation / control device or multiple evaluation / control devices can be involved in the evaluation and calculation. Additionally or alternatively, the evaluation can be performed at least in part on a server. The evaluation can be performed by a computer program designed to perform the calculation steps. Similarly, a computer program product can be provided in which a computer program designed to perform the calculation steps is stored.

[0017] The evaluation / control device can be understood as a physical module. However, the evaluation / control device can also be easily implemented on a server. In this case, this module is a computer program and does not have a physical presence. The evaluation / control device can retrieve data from the cloud or store data in the cloud.

[0018] A camera assembly can be understood as a camera assembly comprising a camera that captures a spatial field of view of 360° or at least approximately 360° around the camera assembly. Alternatively, a camera assembly can comprise multiple cameras that together capture a spatial field of view of at least approximately 360° around the camera assembly. A camera assembly can have a first camera and a second camera.

[0019] The spatial field of view of at least about 360° around the camera assembly is advantageously composed of a first sub-spatial field of view and a second sub-spatial field of view each of at least or at least about 180° around the camera assembly, The sub-fields of view may be arranged along a common axis, in particular the common axis may be oriented substantially vertically, or the common axis may be oriented at an oblique angle to the vertical.

[0020] A spatial field of view of at least about 360° may advantageously be a three-dimensional field of view. A partial spatial field of view of at least about 180° may be a three-dimensional partial field of view.

[0021] The camera assembly can have a common axis that can extend through the camera or through multiple cameras of the camera assembly, and the common axis can be oriented substantially vertically to form a substantially vertical axis, or can be tilted toward the vertical at an oblique angle to form an oblique axis.

[0022] Alternatively, each of the cameras can be disposed on a separate axis, which may be substantially parallel to one another or may be angled relative to one another.

[0023] The camera looking down can conveniently capture the ground below the camera looking up. The cameras can be arranged on a common holding assembly or on separate holding assemblies.

[0024] The one or more axes can be oriented substantially vertically, or the one or more axes can be oriented at an oblique angle relative to the vertical.

[0025] A small distance between the axes allows both cameras to be constantly shaded by clouds moving at approximately the same time. A small distance between the axes of a few meters, especially up to about 10 m, is advantageous.

[0026] Additionally, a field of view of at least approximately 360° can only be reconstructed with sufficient accuracy from the partial fields of view of the two cameras if they are arranged at a small distance from each other. For this purpose, a distance of approximately 10 meters or less should not be exceeded. This prevents cloud shadows in the image of the camera looking towards the ground from corresponding with sufficient accuracy to clouds in the image of the camera looking towards the sky if the distance is too long. This effect can be particularly relevant for very low clouds, at a height of several hundred meters.

[0027] The spatial field of view of at least about 360° around the camera assembly can extend in two opposing directions to provide a total spatial field of view of at least about 360°.

[0028] If the camera assembly has multiple cameras, the first camera and the second camera can form a common axis, which can be substantially vertical, can form a substantially vertical axis, or the axis can be inclined towards the vertical axis at an oblique angle, which can form an oblique axis.

[0029] When the cameras are arranged on a common axis, the field of view of the first camera can extend upward along the common axis, and the field of view of the second camera can extend downward along the common axis. Alternatively, the partial fields of view can extend along multiple axes, in particular two axes. These axes can be substantially parallel to each other or can be tilted relative to each other. One or more axes can be oriented substantially vertically. Alternatively, one or more axes can be oriented at an oblique angle relative to the vertical.

[0030] In particular, one or more axes may be positioned so that a camera looking down can capture the ground below a camera looking up.

[0031] The two axes are advantageously arranged at a small distance from each other, which allows both cameras to be constantly shaded by clouds moving at approximately the same time. A small distance between the axes of a few meters, in particular up to about 10 m, is advantageous.

[0032] Additionally, a field of view of at least approximately 360° can only be reconstructed with sufficient accuracy from the partial fields of view of the two cameras if they are arranged at a small distance from each other. For this purpose, a distance of approximately 10 meters or less should not be exceeded. This prevents cloud shadows in the image of the camera looking towards the ground from corresponding with sufficient accuracy to clouds in the image of the camera looking towards the sky if the distance is too long. This effect can be particularly relevant for very low clouds, at a height of several hundred meters.

[0033] Thus, with two cameras arranged along the same common axis, a spatial field of view of at least about 360° can be formed by sub-spatial fields of view of at least about 180° each, which form a spatial field of view of about 360°, each of which forms a hemispherical or at least nearly hemispherical field of view.

[0034] A spherical field of view of at least about 360° around the camera assembly is understood below to be a spherical field of view around a center or at least a nearly spherical field of view.

[0035] Hereinafter, a hemispherical shape is understood to include at least an approximately hemispherical shape, and similarly, a spherical shape is understood to include at least an approximately spherical shape.

[0036] A camera can be disposed at this center. The spatial field of view of at least approximately 360° can be divided into a plurality of segments. The centers can be on a common axis, which can be formed as a substantially vertical axis or an oblique axis. This allows the camera data of one segment to be evaluated independently of the camera data of the other segments.

[0037] Alternatively, a spatial field of view of at least about 360° can be reconstructed from partial fields of view of two cameras of at least about 180° when these cameras are arranged on axes extending a small distance from each other.

[0038] The camera data may be understood as cloud-related data caused by clouds. Additionally or alternatively, the camera data may be understood in the following as cloud-related data caused by cloud shadows.

[0039] Additionally or alternatively, camera data may be understood below as data related to solar radiation caused by the intensity of at least one component of global irradiance. Camera data may also be caused by the intensity of multiple components of global irradiance.

[0040] Here, the camera data can be understood as an image of the sky. Additionally or alternatively, the camera data can be understood as an image of an area of ​​the sky. Additionally or alternatively, the camera data can be understood as an image of the earth's surface. Additionally or alternatively, the camera data can be understood as an image of an area of ​​the earth's surface.

[0041] Additionally or alternatively, the camera data may be image features of one or more color channels of the image. Such image features may exist in texture and / or structure, and / or in the colors or ratios of the color channels and / or brightness. These image features may be caused by clouds or other elements of the sky. Additionally or alternatively, these image features may be caused by cloud shadows and / or other elements on the ground. Image features that are not caused by clouds and / or cloud shadows can be filtered out by an appropriate method and therefore cannot be used for evaluation.

[0042] Additionally or alternatively, the camera data may be intensity values ​​of one or more color channels and / or structural image features, particularly within the image area of ​​the sun, which intensity values ​​and structural features may be created by radiation impinging on at least one lens of each camera and by associated reflections and refractions and other optical and electronic effects.

[0043] Images and / or image features and / or intensity values ​​can be evaluated, which can include capturing a current state.

[0044] Additionally or alternatively, images and / or changes in image features and / or intensity values ​​may also be captured over time.

[0045] In the following, ascertaining a parameter is understood as capturing and / or calculating a current value of the parameter. Additionally or alternatively, in the following, ascertaining a parameter is understood as capturing and / or calculating a likely future value of the parameter. For example, a likely future value of a parameter can be ascertained based on current and / or historical camera data.

[0046] A parameter is understood below as a variable ascertained by or from camera data. This variable may be a cloud shadow position and / or a cloud feature position and / or a cloud speed and / or a cloud height. Additionally or alternatively, this variable may be a future cloud shadow position and / or a future cloud feature position and / or a future cloud speed and / or a cloud height.

[0047] Additionally or alternatively, this variable may also be a component of global irradiance and / or a combination of components of global irradiance or global irradiance. The measured or confirmed values ​​for the global irradiance components and / or combinations of components of global irradiance and / or global irradiance may be further refined.

[0048] The determination of at least one component of global irradiance may hereinafter be understood as capturing and / or calculating a current value of at least one component of global irradiance. Additionally or alternatively, the determination of at least one component of global irradiance may be understood as calculating a future value of at least one component of global irradiance.

[0049] At least one component of the global irradiance can be understood as a variable determined with or from camera data and / or parameters.

[0050] A component of global irradiance can be understood as one of the following types of solar radiation, or a combination of the following types of solar radiation: direct radiation, diffuse radiation, and radiation reflected from the Earth's surface, all of which together correspond to global irradiance.

[0051] An assembly for ascertaining at least one parameter for determining at least one component of global irradiance is proposed, which assembly comprises an evaluation / control device as well as a camera assembly.

[0052] At least one camera is fixed at a specified distance from the surface of the earth to ascertain at least one parameter, and the camera assembly is designed to capture camera data within a spatial field of view of at least approximately 360° around the camera assembly.

[0053] Conveniently, the holding assembly can secure at least one camera. In the case of two or more cameras, the cameras can be secured by the same holding assembly. Optionally, the cameras can be secured to different holding assemblies.

[0054] The spatial field of view of at least about 360° around the camera assembly is advantageously composed of a first sub-spatial field of view and a second sub-spatial field of view of at least about 180° each around the camera assembly, which are arranged along a common axis or, if two cameras are used, on two axes spaced a small distance apart from each other, in particular the common axis or axes are oriented substantially vertically, or the common axis or axes are oriented at an oblique angle to the vertical.

[0055] At least one camera of the camera assembly can be arranged on at least one axis forming a vertical or oblique axis, with the spatial field of view extending at least about 360° up and down along the vertical or oblique axis.

[0056] An upper subspatial field of view of at least about 180° and a lower subspatial field of view of at least about 180° can be formed, which have a common substantially vertical or oblique axis, in particular a substantially vertical or oblique central axis, or which are spaced apart from each other on correspondingly different axes. The upper and lower subspatial fields can form upper and lower hemispheres, respectively.

[0057] The upper and lower hemispheres may have their linear rear surfaces, i.e., their rear sides, forming a common horizontal surface, in particular a circular area, perpendicular to a substantially vertical or oblique axis, and the center of the camera assembly may be formed on the intersection of the common axis and the horizontal axis.

[0058] The at least one camera may be an RGB camera or an infrared camera. For example, the at least one camera may capture 24 frames per second, which may be accompanied by a corresponding timestamp. Other image production rates may also be selected. In addition, an extension mechanism, for example with a shading device, may be considered to reduce the interfering effects of direct sunlight.

[0059] In particular, the camera assembly can be designed to capture camera data within a field of view of at least about 360° around the camera assembly, the camera data being suitable for deriving information regarding solar radiation and / or cloud locations and / or characteristics.

[0060] The holding assembly can fix a camera for viewing at least one parameter at a specific distance above the ground. In this case, the holding assembly can be a local fixed assembly such as a suitable linkage or rig. Additionally or alternatively, the holding assembly can be a mobile assembly such as a drone that is mobile and fixes at least one camera at a specified height in a specified location.

[0061] The holding assembly can allow the camera assemblies to be arranged on a common axis to provide a spatial field of view of at least about 360°.

[0062] The evaluation results of the camera data, for example of individual color channels, can be compared with the evaluation results of other color channels. Additionally or alternatively, the evaluation results can be compared with different timestamps of the color channels. Other evaluations of the evaluation results using evaluation results with other timestamps or using evaluation results from other color channels are also possible.

[0063] In an example where the field of view of at least about 360° is comprised of two partial fields of view of at least about 180° at a specified location, the results of the evaluation of the first partial field of view of at least about 180° and the results of the evaluation of the second partial field of view of at least about 180° can be advantageously combined.

[0064] This advantageously eliminates the need to rely on estimates or values ​​from external data sources to ascertain most parameters for determining at least one component of global irradiance, thereby making it possible to more accurately and reliably ascertain parameters for a specified location than with conventional assemblies that rely on estimates and values ​​from external data sources. Furthermore, no additional sensor units are required.

[0065] Typically, the irradiance of at least one component of the global irradiance is expressed relative to the surface on which it impinges, which may be inclined relative to the Earth's surface, for example facing the Earth's surface.

[0066] This allows ascertaining from the parameters and / or directly from the camera data the current direct radiation, the current diffuse radiation, the current radiation reflected from the Earth's surface, and the current global irradiance, which advantageously allows estimating the current performance of the solar system.

[0067] Additionally, predictions of future diffuse radiation, future radiation reflected from the Earth's surface, and future global irradiance can be ascertained from the parameters by ascertaining future values ​​for solar radiation, which advantageously allows for the future performance of the solar system to be estimated.

[0068] In addition to the parameters identified to predict future solar radiation, current solar radiation values ​​can also be used.

[0069] Advantageously, a field of view of at least about 360° around the camera assembly allows the advantages of an assembly having a sky camera oriented towards the sky, also known as a cloud camera, to be combined with the advantages of an assembly having a ground camera oriented towards the ground, also known as a shadow camera, and allows the disadvantages of the sky camera and the cloud camera to be compensated for.

[0070] To achieve these advantages, camera data captured within a field of view of at least about 360° can be evaluated. For example, the camera data can be advantageously captured simultaneously at a common location and evaluated on a common axis with cameras on a common axis or a small distance apart.

[0071] Combining these advantages, a camera assembly with at least approximately a 360° field of view may be sufficient to capture enough camera data to reliably capture and / or predict desired parameters, meaning that additional cameras or other sensor units at other locations may be eliminated.

[0072] A large part of the sky can be captured and monitored, and clouds in particular can be detected long before their shadows reach the monitored area, and corresponding predictions can be made.

[0073] A further advantage of evaluating camera data recorded in a field of view of at least about 360° around the camera assembly is that some parameters, such as cloud velocity above the ground, can be accurately extracted directly from these camera data.

[0074] The portion of the ground floor that can be monitored and captured depends, among other things, on the height at which the at least one camera oriented towards the ground is arranged.

[0075] To make reliable predictions, ground cameras are typically mounted on tall towers or mountain ridges to magnify the area of ​​the ground they monitor. Due to their height, clouds hovering between the camera and the ground can prevent or complicate ground monitoring using these assemblies.

[0076] Advantageously, camera data from at least one camera oriented skyward can be used to confirm the predictions, which does not necessarily require a large portion of the ground to be monitored, so that the camera assembly can be positioned at a lower height above the ground, as opposed to known shadow camera assemblies.

[0077] For example, the holding assembly can fix at least one camera at a distance of 1 to 100 m from the ground, which is typical for albedo measurements. The minimum distance of the at least one camera from the ground can depend on the ground. For example, a height of 10 m should be selected in areas with snow, uncut grass, or arable crops on the ground to avoid interference caused by surface irregularities. Lower heights are also possible in areas with less vegetated surfaces and / or less snowfall.

[0078] Furthermore, a minimum height can be selected that allows safe identification of the gradient of the intensities of the RGB channels of at least one camera oriented towards the ground, thereby allowing reliable and accurate determination of the parameters that can be ascertained therefrom.

[0079] The maximum distance of the at least one camera oriented toward the ground prevents low clouds from complicating data capture. This maximum distance will depend on the deployment purpose and location. For example, if clouds above 500 m are of interest to the camera, the at least one camera should be installed at a height of 100 m or less to safely capture these clouds. A lower distance is advantageous if the assembly is also used to measure radiation reflected from the ground.

[0080] As the distance increases, the area included in the measurement of radiation reflected from the ground also increases, and this area can be affected by undesirable influences such as trees, reflective objects, land use, etc.

[0081] The camera assembly is fixed at a maximum height of 100m, which reduces the cost of the holding assembly. In addition, such a fixed camera assembly can be easily and quickly installed in any location, making the camera assembly adaptable.

[0082] Alternatively, the drone can simply fly at such a height and be used flexibly in multiple locations, which also allows for the location of the holding assembly to be changed once the desired parameters have been calculated.

[0083] This makes it easy and cost-effective to check the suitability of locations for solar parks, for example.

[0084] Additionally, the camera assembly can be positioned on the top edge of a structure. The structure can correspond to a solar system monitoring or contractor building, or a residential building. A tower or other tall structure is not required. A camera assembly field of view limited by the structure can make it difficult to capture camera data and verify at least one parameter.

[0085] The camera data can be advantageously viewed by the assembly of the present invention at a common location, thereby eliminating the need to transfer the camera data between two locations and translate the data from one location to the other, thereby facilitating maintenance and operation of the assembly of the present invention.

[0086] In particular, reducing the number of cameras or reducing the number of camera assemblies can reduce the expense of hardware items and therefore hardware costs.

[0087] According to a preferred embodiment of the assembly, the field of view of at least approximately 360° around the camera assembly at the designated location can be composed of a first partial field of view and a second partial field of view, each of at least approximately 180° around the camera assembly. At least one first camera captures camera data within the first partial field of view, and at least one second camera captures camera data within the second partial field of view, the two fields of view of the cameras complementing each other to form a field of view of at least approximately 360°. In particular, the cameras are each designed as a fisheye camera.

[0088] The orientation of the field of view can be selected at will. For example, the field of view can be oriented laterally, with one camera capturing a section of the ground and a section of the sky on one side, and the other camera capturing a section of the ground and a section of the sky on the opposite side. The camera positions and orientations can be freely selected, as long as a full field of view of at least approximately 360° is recorded around the camera assembly. The camera assemblies can be oriented along a common axis or along axes spaced a small distance apart, with one or more axes being oriented substantially vertically, forming a substantially vertical axis, or tilted at an oblique angle toward the vertical axis, forming an oblique axis.

[0089] Advantageously, monitoring of designated partial fields of view by separate cameras can facilitate the allocation of camera data to partial fields of view, thereby facilitating the interpretation and evaluation of the camera data.

[0090] For example, camera data can be more easily assigned to at least one component of global irradiance if it is clear in which field of view it was captured. In an alternative exemplary embodiment, a field of view of at least about 360° can be divided into three or more sub-fields of view. Additionally, additional cameras are contemplated that capture camera data in additional sub-fields of view.

[0091] According to a preferred embodiment of the assembly, the at least one first camera is capable of capturing camera data as a sky camera within a first partial field of view that is oriented towards the sky and forms an upper partial field of view.

[0092] At least one second camera can capture camera data as a ground camera within a second field of view oriented toward the Earth's surface to form a lower field of view. In particular, the camera is designed as a fisheye camera. The upper and lower partial fields of view can have a common substantially vertical or oblique axis or can be arranged on spaced axes.

[0093] The use of multiple cameras can be advantageous to eliminate the use of an omnidirectional camera.

[0094] Additionally, the camera data for each camera can be easily assigned to the upper or lower panel. Cameras can be specifically designed to monitor the sky and the ground.

[0095] Alternatively, a 360° camera having a field of view of at least about 360° around the camera assembly can capture camera data in a first partial field of view and capture camera data in a second partial field of view, particularly, the first partial field of view can form an upper partial field of view oriented toward the sky, and the second partial field of view can form a lower partial field of view oriented toward the Earth's surface.

[0096] The use of one camera can be advantageous in eliminating the need for multiple cameras, which can simplify installation. Additionally, a single camera and a reduced number of cameras can minimize potential sources of error, for example, when transmitting data or due to incorrectly orienting the camera and / or calibrating the corresponding camera. Correlating the camera data with the upper or lower partial field of view can be performed during evaluation of the camera data.

[0097] The camera used may produce high-quality images or camera data at high resolution. Alternatively, surveillance cameras may be used, which are less expensive and may provide stronger artifacts in the images. In an alternative embodiment, a camera and parabolic mirror assembly is contemplated.

[0098] In contrast to known assemblies with sky cameras that can ascertain cloud height and therefore cloud velocity above the ground, the assembly of the present invention monitors only a single upper partial field of view, whereas a standard sky camera assembly with this power range monitors at least two upper partial fields of view and includes at least two sky cameras.

[0099] In contrast to known ground camera assemblies, the assembly of the present invention monitors only a small portion of the ground, so that the ground camera can be positioned at a smaller distance from the ground than with standard ground camera assemblies.

[0100] If the camera assembly is designed with an air camera and a ground camera, the two cameras can be installed in the same location with opposite orientations.

[0101] If the camera assembly is designed with a single camera, it will automatically be located in one place.

[0102] Advantageously, the present invention can combine the benefits of cloud camera assemblies and shadow camera assemblies, thereby reducing the cost of purchasing and operating hardware items.

[0103] According to a preferred embodiment of the assembly, the at least one evaluation / control device extracts camera data associated with the sky from the captured camera data and is able to ascertain from these camera data associated with the sky at least one of the following parameters: direct radiation and / or diffuse radiation and / or global irradiance GI and / or at least a position of a cloud feature and / or an area covered by clouds in the sky and / or an angular velocity of at least one cloud in the camera image from the cloud position and / or from the position of the cloud feature in the camera image between at least two timestamps.

[0104] Cloud features are understood below as image features that are indicative of clouds. Cloud location is an estimate of the location of a cloud or cloud accumulation, since clouds are not fixed objects and it is difficult to distinguish individual clouds in a cloud formation.

[0105] In the case of a camera that monitors only the upper field of view, almost all of the camera data of this camera can be associated with the sky, so the camera data associated with the sky can be easily extracted. In the case of a camera that monitors both parts of the sky and the ground, a pre-evaluation of the camera data can enable association with the sky or the ground.

[0106] The at least one evaluation / control device can use corresponding programming methods to ascertain the angular velocity of the cloud or of multiple clouds or cloud formations from the camera images.

[0107] In a possible evaluation method for determining the location of a cloud feature and / or calculating the angular velocity of a cloud or clouds or cloud formation, an image feature corresponding to the location of the cloud or cloud formation can be identified. To calculate the angular velocity of the cloud or clouds or cloud formation, the shifts Δm, Δn of the image feature in the camera image towards the x-axis and y-axis between times t1=t0 and t2=t0+Δt can be determined.

[0108] The shift can be represented by creating a difference image d1 of one of the color channels. In this case, a first difference image d1 can be created from the camera image at a first time t1=t0 and the camera image at a second time t2=t0+Δt. Additionally, a second difference image d2 can be created from the camera image at a second time t2=t0+Δt and the camera image at a third time t3=t0+2Δt.

[0109] The difference images d1 and d2 can be deskewed. Deskewing is understood to mean that the ascertained values ​​are projected onto a horizontal plane of unknown height above the camera. The result of this projection is orthoimages o1 and o2. Image features and their locations are identified from the orthoimages o1 and o2.

[0110] In another step, the orthoimages o1 and o2 can be converted into binary images b1, b2, where, for example, 2% of the pixels each get the value 1 and the other 98% get the value 0. These 2% of pixels have the largest difference in absolute value. This makes it possible to see a sudden increase or decrease from this color channel between times t0, t0 + Δt, and t0 + 2Δt.

[0111] In another step, these binary images can be compared globally by cross-correlation, or in a more refined method, the images can be compared section by section. This shift Δm, Δn is equal to the shift at which the cross-correlation between the binary orthoimages o1, o2 reaches a maximum. This method can be performed for at least one color channel. In this way, multiple color channels can also be evaluated. Furthermore, further refinements and appropriate adjustments can be made to the procedure to determine the shift Δm, Δn of one or more clouds.

[0112] In the alternative, the image features and their shifts Δm, Δn can also be determined by other means, for example using SIFT (Scale Invariant Feature Transform) or other machine learning methods.

[0113] With the help of the known time offset t2-t1 and Δm, Δn, the angular velocity in both directions x and y can be calculated as follows: vx pix / s=Δm / (t2-t1) vy pix / s=Δn / (t2-t1)

[0114] The direct and / or diffuse radiation can be determined by at least one evaluation / control device, which may be the same evaluation / control device that already ascertains the angular velocity of the cloud, or may be a separate evaluation / control device.

[0115] As a reference, intensity values ​​of the RGB channels of at least one camera in the upper partial field of view or from camera data associated with the sky are evaluated by the evaluation / control device.

[0116] These intensity values ​​can be read directly from the corresponding camera. In a possible evaluation procedure, a physical camera model from the intensity values ​​of the RGB channels of the camera image is used to calculate the radiation (radiance) received from a specific sky region. In addition, physically motivated corrections can be applied to improve the calculation. In an alternative exemplary embodiment, the physical camera model can be replaced by a purely statistical machine-based learning model (machine learning model).

[0117] In particular, architectures using convolutional neural networks followed by fully connected neural networks can, with appropriate training, replace, mimic, or complement a camera model, or adapt the camera model to itself.

[0118] In one step of the evaluation method, which assumes a basic physical camera model, a common gamma correction for the cameras can be inverted to obtain a linearized RGB image from the RGB images of each camera.

[0119] If the corresponding camera does not perform gamma correction, this step can be eliminated, so that the gamma correction does not need to be inverted afterwards, which may occur, for example, if the corresponding camera's gamma correction is disabled or if the camera does not perform gamma correction for other reasons.

[0120] In another step of the evaluation method, for example, a pixel-by-pixel association of the image area with the sky area can be performed via the azimuth angle and the zenith / vertex angle. Instead of a pixel-by-pixel association, other associations are also possible. The azimuth angle can be indicated from south, west, north, and east.

[0121] The corresponding camera geometric calibration and transformations based on it can be applied when associating image regions with sky regions. Alternatively, the association between image regions and sky regions can be roughly performed using azimuth and zenith / vertex angles. For example, association without calibration is possible. The calibration and transformations based on it can be implemented as a machine-learning model and can be continuously improved.

[0122] In another step of the evaluation method, the intensities of the color channels of the linearized RGB image can be weighted and summed, so that the sensitivity of the corresponding camera is as uniform as possible in the visible wavelength range.

[0123] Another step in the evaluation method can be a multiplication by a broadband correction that takes into account the proportion of broadband solar radiation that comes from the non-visible wavelength range, as well as a calibration factor that takes into account the sensitivity of the camera.

[0124] Additionally, at least one correction can be applied to take into account interferences with the measurement, such as lens refraction, image saturation, the effects of the corresponding camera exposure control, etc. Additionally or alternatively, applied correction factors, such as broadband corrections, calibration factors, and interference corrections, can be partially summarized or rewritten. Additionally, these corrections can be replaced or supplemented by statistically determined corrections, in particular based on image features, for example via machine learning.

[0125] In another step of the evaluation method, the radiation (radiance) received from different sky regions can be determined by projecting the diffuse and / or direct radiation onto any horizontal or ground-inclined plane, including, for example, a ground-facing plane. Association of image regions with sky regions and integration across image regions / sky regions can be used. If necessary, global radiation can also be determined on inclined planes and on ground-facing planes.

[0126] In alternative embodiments of the method, partial steps such as applying a physical camera model and / or allocating image regions to sky regions and / or applying physically motivated corrections and / or projecting onto an arbitrary plane can be mimicked in part or in whole by so-called machine learning models for determining direct and diffuse radiation in an arbitrary plane.

[0127] In the simplest embodiment of the assembly, a value corresponding to the sum of diffuse and direct radiation can be determined by evaluating the intensities of the RGB channels from the camera data associated with the upper partial field of view or from the camera data associated with the sky. Extensions are possible to allow for the identification of separate values ​​for diffuse and direct radiation.

[0128] Advantageously, the determination of direct and / or diffuse radiation can be used to verify the performance of a solar plant at the location of the assembly of the present invention and to evaluate the solar resource at that location. No additional sensors or sensor units, such as pyranometers, are required. The radiation can be determined solely by at least one camera and its camera data.

[0129] Advantageously, knowledge of cloud-covered areas in the upper partial field of view can be used to further assess the identified radiation. For example, diffuse radiation may increase due to clouds, and direct radiation may decrease due to clouds. Different weather conditions may exist at that location. Current and future radiation conditions can be at least partially ascertained by ascertaining cloud locations and cloud velocities.

[0130] According to a preferred embodiment of the assembly, the evaluation / control device extracts camera data associated with the ground surface from the captured camera data and is able to ascertain from these camera data associated with the ground surface at least one of the following parameters: radiation reflected at the ground surface and / or the albedo of the ground surface and / or at least one cloud shadow position and / or the velocity of at least one cloud above the ground surface from the cloud shadow position between at least two timestamps.

[0131] In the case of a camera that monitors only the lower field of view, almost all of the camera data of this camera can be associated with the ground, so that the camera data associated with the ground surface can be easily extracted. In the case of a camera that monitors both parts of the sky and the ground, a pre-evaluation of the camera data can enable association with the sky or the ground.

[0132] The speed of the cloud or clouds above the ground can be ascertained from the camera image of the lower partial field of view or from camera data associated with the ground by at least one evaluation / control device, which may be one of the evaluation / control devices evaluating the camera data of the upper partial field of view or camera data associated with the sky, or may be a separate evaluation / control device.

[0133] The corresponding evaluation methods are similar to those used to determine the angular velocity of the clouds from images of the upper partial field of view or from camera data associated with the sky, respectively.

[0134] In an alternative method, the image features corresponding to the cloud shadow location or locations and their shifts Δm, Δn can also be ascertained by other means, for example using SIFT (Scale Invariant Feature Transform) or other machine learning methods.

[0135] A possible evaluation method can detect an image feature corresponding to the cloud shadow position or positions and ascertain a shift of Δm, Δn of the image feature in the camera image towards the x-axis and y-axis between times t1=t0, t2=t0+Δt, t3=t0+2Δ.

[0136] These images can be converted into orthoimages using a known height profile of the ground surface in the monitored area and geometric calibration of the camera. The projected height is known as opposed to evaluating a partial upper field of view or evaluating camera data associated with the sky. Thus, in the corresponding orthoimage, each pixel corresponds to a square subsection of the monitored area. A difference image can be calculated from the orthoimage converted to grayscale. Outputs other than grayscale are also possible. Similar to determining angular velocity, the difference image can be converted into a binary image. Cross-correlation can be used to determine shifts Δm, Δn of the image pixels, which can be related to corresponding shifts Δx, Δy of the cloud shadow in the monitored area. This "absolute" velocity quantity of the cloud shadow above the ground is calculated as follows: JPEG2025536501000002.jpg35122 where the scaling factor ksc (in m / pixel) denotes the known page length in image pixels in meters.

[0137] Since the velocity of the cloud shadow above the ground also corresponds to the velocity of the corresponding cloud above the ground, two sky cameras monitoring different upper subfields of view are advantageously not required to ascertain the cloud velocity above the ground, since the cloud velocity can be easily determined from one lower subfield of view or from camera data associated with the ground surface. Additionally, the use of estimates in the calculation of cloud velocity can be eliminated, thereby allowing a reliable and accurate value for the cloud velocity above the ground to be calculated.

[0138] Cloud velocity above the ground is hereinafter understood as the velocity of the cloud compared to an imaginary fixed point on the ground. From the determined cloud velocity and the current cloud position, future cloud positions and corresponding changes in global irradiance can be advantageously determined or predicted in a specified area.

[0139] The radiation reflected from the Earth's surface and / or the ground albedo can be ascertained by at least one evaluation / control device, which may be the same evaluation / control device that already ascertains another parameter, or which may be a separate evaluation / control device.

[0140] Ascertaining the radiation reflected from the ground is similar to ascertaining the direct radiation and / or the diffuse radiation. As a criterion, the intensity values ​​of the RGB channels of at least one camera ascertaining camera data from the lower partial field of view are evaluated by a corresponding evaluation / control device.

[0141] These intensity values ​​can be read directly from the corresponding camera if it monitors only the ground. Alternatively, relevant camera data can be separated from irrelevant camera data. In a possible evaluation method, a physical camera model from the intensity values ​​of the RGB channels of the camera image is used to calculate the radiation received from a specific ground region. In addition, physically motivated corrections can be applied to improve the calculation. In an alternative exemplary embodiment, the physical camera model can be replaced by a purely statistical machine-based learning model (machine learning model). In particular, an architecture using a convolutional neural network followed by a fully connected neural network can, with appropriate training, replace, mimic, or complement the camera model, or adapt the camera model to itself.

[0142] In one step of the evaluation method, which assumes a basic physical camera model, a linearized RGB image can be obtained from the RGB images of each camera by inverting the gamma correction common to the cameras. If the corresponding camera does not perform gamma correction, this step can be eliminated, so that the gamma correction does not need to be inverted later. This can happen, for example, if the corresponding camera's gamma correction is disabled or if the camera does not perform gamma correction for other reasons.

[0143] In another step of the evaluation method, a pixel-by-pixel association of image regions with ground regions can be performed, for example using a known height profile of the ground surface in the monitored area, where each pixel may correspond to a square subsection of the monitored area.

[0144] Alternatively, the pixel-by-pixel association of image regions with ground regions can be taken over from the determination of cloud velocity. Instead of pixel-by-pixel association, other associations are also possible.

[0145] Corresponding camera geometric calibration and transformations based thereon can be applied when associating image regions with ground regions. Additionally, associations without calibration are possible. The calibration and transformations based thereon can be implemented as machine-based learning models (machine learning models) and can be continuously improved.

[0146] In another step of the evaluation method, the intensities of the color channels of the linearized RGB image can be weighted and summed, so that the sensitivity of the corresponding camera is as uniform as possible in the visible wavelength range.

[0147] Another step in the evaluation method can be a multiplication by a broadband correction that takes into account the proportion of broadband solar radiation that comes from the non-visible wavelength range, as well as a calibration factor that takes into account the sensitivity of the camera.

[0148] Additionally, at least one correction can be applied to take into account interferences with the measurement, such as lens refraction, image saturation, the effects of the corresponding camera exposure control, etc. Additionally or alternatively, the applied correction factors, such as broadband corrections, calibration factors, corrections for interferences, etc., can be partially summarized or rewritten.

[0149] Additionally, these corrections can be replaced or supplemented by statistically determined corrections, for example via machine learning, particularly based on image features.

[0150] In another step of the evaluation method, the radiation impinging on a plane and reflected from the ground can also be checked for inclined planes and for planes oriented towards the ground.

[0151] In alternative embodiments of the evaluation method, partial steps such as applying a physical camera model and / or allocating image regions to sky regions and / or applying physically motivated corrections and / or projecting onto an arbitrary plane to determine the radiation reflected from the ground can be partially or wholly mimicked by machine learning models.

[0152] Additionally, in another step, the current albedo of the ground or a more detailed reflectance of the ground can be derived from the ascertained reflected radiation and the ascertained direct radiation and the ascertained diffuse radiation. Advantageously, the evaluation of the camera data of the lower field of view, or the camera data associated with the ground and the upper field of view or the camera data associated with the sky, makes it possible to ascertain the current albedo or reflectance of the ground in the monitored area, for example due to weather, season, or vegetation-related conditions. Thus, it is possible to eliminate reliance on less accurate estimates of the ground albedo or reflectance, respectively. This allows for a better assessment of the solar radiation in this area.

[0153] Advantageously, the reflectance or albedo and / or reflected radiation and / or direct radiation and / or diffuse radiation of the ground can be represented in an angularly resolved and spectrally resolved manner.

[0154] Additionally, the global irradiance and diffuse irradiance on any inclined surface can be calculated from the radiation from different areas of the ground, as well as from the angular and spectrally resolved reflectance of the ground or albedo, including the plane pointing to the ground. In this way, the radiation at the rear of the module can be calculated individually for each bifacial photovoltaic module, taking into account the typically complex geometry of the power plant. This mechanism can also be supported by combining with a pyranometer.

[0155] Reflectance corresponds to the reflectance factor of a surface, which is the ratio of the radiant power reflected from the surface to the radiant power that strikes the surface.

[0156] Angular resolved reflectance is understood to mean information in the sense of derived quantities such as the bidirectional reflectance distribution function, or the detailed composition of albedo, in particular black-sky albedo and white-sky albedo.

[0157] Spectrally resolved reflectance is the ratio of the radiant power reflected by a surface at a particular wavelength or range of wavelengths to the radiant power impinging on the surface at that particular wavelength or range of wavelengths.

[0158] Additionally, camera data associated with the bottom view or ground camera data, respectively, can be used to monitor for contamination or damage to the solar system and other solar collectors so that cleaning or repairs can be arranged as needed.

[0159] According to a preferred embodiment of the assembly, the at least one evaluation / control device is able to ascertain the cloud height from the velocity of the at least one cloud above the ground and the angular velocity of the at least one cloud in the camera image.

[0160] Cloud velocity above the ground can be calculated based on angular velocity vpix / s in the upper subfield of view or from sky-associated camera data, respectively. vm / s=vpix / s2tanθH2 / N Therefore, the cloud height H2 is: JPEG2025536501000003.jpg35122

[0161] The angle θ corresponds to the maximum zenith angle over which an upper field of view of 180° or at least about 180° around the camera assembly is evaluated. N corresponds to the diameter in pixels of the circular image area, representing the sky region with a zenith angle less than or equal to θ. The angle θ and the parameter N can be determined from camera images of an upper field of view of at least about 180° around the camera assembly. vm / s corresponds to the observed velocity of the cloud above the ground, and vpix / s corresponds to the observed angular velocity of the cloud. H2 corresponds to the cloud height projected above the camera assembly or above at least one camera of the camera assembly oriented skyward.

[0162] Since the distance to the ground of at least one camera is known, the actual height of the cloud above the ground at its current location can be calculated using the known height profile of the monitored area, the current cloud position and height of the cloud projected onto the camera.

[0163] In particular, the evaluation / control device can use cloud height, current cloud location, and cloud velocity above the ground to ascertain future cloud locations. From this, future shading or future global irradiance can be estimated or calculated in a specified area. This allows for more accurate short-term forecasts of solar radiation using a single co-located camera assembly, with the camera used being mounted just a few meters above the ground. Advantageously, this allows for early responses to shading or fluctuations in solar system performance to be predicted. Camera data can advantageously be viewed at a common location, making the inventive assembly easier to maintain and operate and more cost-effective.

[0164] According to a preferred embodiment of the assembly, the at least one evaluation / control device is capable of extrapolating in time and space the velocity of the clouds above the Earth's surface and / or the angular velocity of the clouds in the camera image.

[0165] This allows both the angular cloud velocity in the camera image and the cloud velocity above the surface to be averaged / extrapolated in time and space to obtain a larger temporal and spatial coverage.

[0166] This also allows for determining the cloud height and cloud velocity, respectively, of clouds whose shadows are not (yet) captured in the lower field of view or by camera data associated with the Earth's surface. Temporal and spatial extrapolation can compensate for the fact that the lower field of view covers a smaller area and therefore has fewer cloud shadows than the clouds or cloud features in the upper partial field of view. Due to the temporal and spatial extrapolation, cloud and its shadow data do not need to be used for the evaluation. Shadows of other clouds can also be used to confirm the cloud height of clouds or cloud features captured in the upper partial field of view or from camera data associated with the sky. This evaluation is less accurate than when camera data of clouds or cloud features and their shadows is used for the evaluation. However, it is possible to continuously confirm cloud height. In known systems such as lidar or ceilometer systems, cloud height is only confirmed selectively.

[0167] According to a preferred embodiment of the assembly, the at least one evaluation / control device can determine at least one current and / or future value of at least one component of global irradiance from the camera data and / or the ascertained parameters in a spectrally and / or angularly resolved manner. The angle-resolved radiation information, particularly radiance, can be weighted and integrated onto a corresponding surface of interest. Since the angle-resolved information itself may be of interest to the user, weighting and integration can be eliminated in this case. The angle-resolved capture of at least one component of global irradiance can determine the current and / or future albedo of the ground.

[0168] Furthermore, the current and / or future irradiance of radiation impinging on a plane with a known inclination relative to the ground, such as the rear of a bifacial photovoltaic module, can be advantageously determined. Additional support by a pyranometer or other suitable sensor is possible. Advantageously, no additional sensor, such as a pyranometer, is required to resolve the irradiance of components of global radiation in a spectrally and / or angularly resolved manner or to ascertain the irradiance on a plane inclined relative to the ground. This can reduce assembly costs.

[0169] According to a preferred embodiment of the assembly, the at least one evaluation / control device is capable of determining at least one component of global radiation on an inclined surface, in particular on an arbitrarily oriented surface. This advantageously makes it possible to determine the optimal angle of tilt of a solar module, including a bifacial photovoltaic module. Alternatively or additionally, if the angle of tilt is known, the current and / or expected performance of the solar module, including the bifacial photovoltaic module, can be determined.

[0170] Advantageously, the assembly of the present invention allows for the calculation of almost all parameters required to ascertain and predict at least one component of global irradiance using a single camera assembly. No additional sensors or other camera assemblies are required. In addition, the assembly of the present invention can be used to generate short-term forecasts of solar radiation. At the same time, this mechanism also allows for improved monitoring of photovoltaic power plants or other areas, such as airports.

[0171] It is proposed to use an assembly for ascertaining at least one parameter for determining at least one component of global irradiance, wherein camera data is captured within a field of view of at least approximately 360° around the camera assembly, and information regarding solar radiation and / or cloud locations and / or characteristics is derived from the camera data.

[0172] The definitions for the use of an assembly are substantially the same as for an assembly for identifying at least one parameter for determining at least one component of global irradiance, and therefore it is not necessary to repeat these definitions, such as cloud characteristics, angle-resolved reflectance and / or spectrally resolved reflectance.

[0173] Advantageously, when using the assembly, the advantages of an assembly having an air camera oriented towards the sky, also known as a cloud camera, can be combined with the advantages of an assembly having a ground camera oriented towards the ground, also known as a shadow camera, thus compensating for the disadvantages of the air camera and the ground camera due to the spatial field of view of at least about 360° around the camera assembly.

[0174] To achieve these advantages, camera data associated with a spatial field of view of at least about 360° around the camera assembly is evaluated. Additionally, the camera data for the field of view of at least about 360° around the camera assembly is advantageously captured simultaneously at a common location and evaluated with respect to this location.

[0175] Combining these advantages, a camera assembly with at least approximately a 360° field of view may be sufficient to capture enough camera data to reliably capture and / or predict desired parameters. This means that additional cameras or other sensor units at other locations can be eliminated, thereby reducing costs and the required evaluation effort.

[0176] The advantage of evaluating camera data of an upper partial field of view of at least about 180° around the camera assembly, or from evaluating camera data associated with the sky, is that a large portion of the sky can be captured and monitored, and in particular clouds can be detected long before their shadows reach the monitored area, and corresponding predictions can be made.

[0177] An advantage of evaluating camera data of at least about 180° of lower partial field of view around the camera assembly is that several parameters, such as cloud velocity above the ground, can be extracted precisely and directly from this camera data. The portion of the ground that can be monitored and captured depends, among other things, on the height at which at least one camera is disposed that captures at least about 180° of lower partial field of view around the camera assembly.

[0178] To make reliable predictions, ground cameras are typically mounted on tall towers or mountain ridges to magnify the area of ​​the ground they monitor. Due to their height, clouds hovering between the camera and the ground can prevent or complicate ground monitoring using these assemblies.

[0179] Advantageously, camera data from at least one camera oriented toward the sky or associated with the sky can be used to confirm the predictions, which does not necessarily require a large portion of the ground to be monitored. As a result, the camera assembly can be positioned at a lower height above the ground, as opposed to known shadow camera assemblies. For example, the holding assembly can fix the at least one camera at a distance of 1 to 100 m from the ground, which is typical for albedo measurements. Selecting the minimum distance of the at least one camera from the ground can depend on the ground. For example, a height of 10 m should be selected in areas with snow, uncut grass, or arable crops on the ground to avoid interference due to surface irregularities. Lower heights are also possible in areas with less vegetated surfaces and / or less snowfall.

[0180] Furthermore, a minimum height can be selected that allows safe identification of the gradient of the intensities of the RGB channels of at least one camera oriented towards the ground, thereby allowing reliable and accurate determination of the parameters that can be ascertained therefrom.

[0181] The maximum distance of the at least one camera oriented toward the ground prevents low clouds from complicating data capture. This maximum distance depends on the deployment purpose and location. For example, if clouds above 500 m are of interest to the camera, the at least one camera should be installed at a height of 100 m or less. A lower distance is advantageous if the assembly is also used to measure radiation reflected from the ground.

[0182] As the distance increases, the area included in the measurement of radiation reflected from the ground also increases, and this area can be affected by undesirable influences such as trees, reflective objects, land use, etc.

[0183] The camera assembly is fixed at a maximum height of 100m, which reduces the cost of the holding assembly. In addition, such a fixed camera assembly can be easily and quickly installed in any location, making the camera assembly adaptable.

[0184] Alternatively, the drone can simply fly at such a height and be used flexibly in multiple locations, which also allows for location changes once the desired parameters have been calculated.

[0185] The low height of the camera assembly, or the use of drones, makes it easy and cost-effective to check the suitability of a solar park site, for example: no towers or other tall structures are required.

[0186] Advantageously, the camera data can be viewed by the assembly of the present invention at a common location, thereby eliminating the need to transfer the camera data between two locations and convert the data from one location to another. In particular, reducing the number of cameras or camera assemblies can reduce the expense of hardware items and therefore hardware costs.

[0187] According to a preferred embodiment of the use of the assembly, the field of view of the camera assembly at a given position can be composed of a first partial field of view and a second partial field of view, each of which is at least approximately 180° around the camera assembly, the camera data within the first partial field of view can be captured by at least one first camera, and the camera data within the second partial field of view can be captured by at least one second camera, the two partial fields of view of the cameras complementing each other to form a spatial field of view of at least approximately 360°. Advantageously, associating the camera data with the partial fields of view can be facilitated in this way.

[0188] In particular, the camera data can be captured using at least one first camera as a sky camera within a first partial field of view that is oriented towards the sky and forming an upper partial field of view, and the camera data can be captured using at least one second camera as a ground camera within a second partial field of view that is oriented towards the ground and forming a lower partial field of view.

[0189] Alternatively, a 360° camera having a field of view of at least approximately 360° around the camera assembly can capture camera data within a first partial field of view and camera data within a second partial field of view. In particular, the first partial field of view can form an upper partial field of view oriented toward the sky, and the second partial field of view can form a lower partial field of view oriented toward the ground. In particular, in this case, the first partial field of view can form an upper partial field of view oriented toward the sky, and the second partial field of view can form a lower partial field of view oriented toward the ground.

[0190] The use of one camera can be advantageous in eliminating the need for multiple cameras, which can simplify installation. Additionally, the reduced number of cameras resulting from a single camera can minimize potential sources of error, for example, when transmitting data or due to incorrectly orienting the camera and / or due to calibrating the corresponding camera. Correlating the camera data with the upper or lower partial field of view can be performed during evaluation of the camera data.

[0191] Advantageously, the camera data of each camera can be easily associated with an upper or lower partial field of view. In contrast to known ground camera assemblies, the assembly of the present invention monitors only a small portion of the ground, so that the ground cameras or cameras capturing camera data associated with the ground can be positioned at a smaller distance from the ground than in typical ground camera assemblies.

[0192] If the camera assembly is designed with an air camera and a ground camera, the two cameras can be installed in the same location with opposite orientations.

[0193] Advantageously, the present use of an assembly can combine the benefits of a cloud camera assembly and a shadow camera assembly, thereby reducing the cost of purchasing and operating hardware items.

[0194] According to a preferred embodiment of the use of the assembly, camera data associated with the sky can be extracted from the captured camera data and at least one of the following parameters can be ascertained from these camera data associated with the sky: direct radiation and / or diffuse radiation and / or global irradiance and / or at least the position of a cloud feature and / or the area covered by clouds in the sky and / or the angular velocity of at least one cloud in the camera image from the cloud position WP and / or from the position of the cloud feature in the camera image between at least two timestamps.

[0195] Here, from the captured camera data of the upper partial field of view, an image feature corresponding to a cloud position or positions of multiple clouds or camera data associated with the sky can be detected, and shifts Δm, Δn of the image feature in the camera image towards the x-axis and y-axis between times t1=t0 and t2=t0+Δt can be ascertained.

[0196] The shift can be represented by creating a difference image d1 of one of the existing color channels. In this case, a first difference image d1 can be created from the camera image at a first time t1 = t0 and the camera image at a second time t2 = t0 + Δt. In addition, a second difference image d2 can be created from the camera image at a second time t2 = t0 + 2Δt and the camera image at a third time t3 = t0 + 2Δt. The difference images d1 and d2 can be deskewed. Deskewing is understood to mean that the ascertained values ​​are projected onto a horizontal plane of unknown height above the camera. The result of this projection is orthoimages o1 and o2. Image features and their locations are identified from the orthoimages o1 and o2.

[0197] In another step, the orthoimages o1 and o2 can be converted into binary images b1, b2, in which, for example, 2% of the pixels each get the value 1 and the other 98% get the value 0. These 2% of pixels have the largest difference in absolute value. This makes it possible to identify a sharp increase or decrease from this color channel between times t0, t0 + Δt, and t0 + 2Δt. In another step, these binary images can be compared globally by cross-correlation, or in a more precise way, the images can be compared section by section, for example.

[0198] The shifts Δm and Δn are equal to the shifts at which the cross-correlation between the binary orthoimages o1 and o2 reaches a maximum. This method can be performed for at least one color channel. In this way, multiple color channels can also be evaluated. Furthermore, further refinements and appropriate adjustments can be made to the procedure for determining the shifts Δm and Δn for one or more clouds.

[0199] In the alternative, the image features and their shifts Δm, Δn can also be determined by other means, for example using SIFT (Scale Invariant Feature Transform) or other machine learning methods.

[0200] With the help of the known time offset t2-t1 and Δm, Δn, the angular velocity in both directions x and y can be calculated as follows: vx pix / s=Δm / (t2-t1) vy pix / s=Δn / (t2-t1)

[0201] The speed of the cloud above the ground can be determined from its angular velocity. vm / s=vpix / s2tanθH2 / N

[0202] The angle θ corresponds to the maximum zenith angle over which an upper subspace field of view of at least about 180° around the camera assembly is evaluated. N corresponds to the diameter in pixels of the circular image area, representing the sky region with a zenith angle equal to or less than θ. The angle θ and the parameter N can be determined from a camera image of an upper subspace field of view of at least about 180° around the camera assembly or from camera data associated with the sky. vpix / s corresponds to the confirmed angular velocity of the cloud. H2 corresponds to the cloud height projected above the camera assembly or above at least one camera of the camera assembly oriented toward the sky. This is not known for the known cloud camera assembly and is determined in part by measurement data from other measurement assemblies elsewhere.

[0203] The basis for determining the direct and / or diffuse radiation is the intensity values ​​of the RGB channels of at least one camera monitoring the upper partial field of view or an area of ​​the upper partial field of view, which intensity values ​​can be read directly from the corresponding camera.

[0204] In a possible evaluation method, a physical camera model from the intensity values ​​of the RGB channels of the camera image is used to calculate the radiation (radiance) received from a specific sky region. In addition, physically motivated corrections can be applied to improve the calculation. In an alternative exemplary embodiment, the physical camera model can be replaced by a purely statistical machine-based learning model (machine learning model).

[0205] In particular, architectures using convolutional neural networks followed by fully connected neural networks can, with appropriate training, replace, complement, or mimic a camera model, or adapt the camera model to itself.

[0206] In one step of the evaluation method, which assumes a basic physical camera model, a linearized RGB image can be obtained from the RGB images of each camera by inverting the gamma correction common to the cameras. If the corresponding camera does not perform gamma correction, this step can be eliminated, so that the gamma correction does not need to be inverted later. This can happen, for example, if the corresponding camera's gamma correction is disabled or if the camera does not perform gamma correction for other reasons.

[0207] In another step of the evaluation method, for example, a pixel-by-pixel association of the image area with the sky area can be performed via the azimuth angle and the zenith / vertex angle. Instead of a pixel-by-pixel association, other associations are also possible. The azimuth angle can be indicated from south, west, north, and east.

[0208] The corresponding camera geometric calibration and transformations based on it can be applied when associating image regions with sky regions. Alternatively, the association between image regions and sky regions can be roughly performed using azimuth and zenith / vertex angles. For example, association without calibration is possible. The calibration and transformations based on it can be implemented as a machine-learning model and can be continuously improved.

[0209] In another step of the evaluation method, the intensities of the color channels of the linearized RGB image can be weighted and summed, so that the sensitivity of the corresponding camera is as uniform as possible in the visible wavelength range.

[0210] Another step in the evaluation method can be a multiplication by a broadband correction that takes into account the proportion of broadband solar radiation that comes from the non-visible wavelength range, as well as a calibration factor that takes into account the sensitivity of the camera.

[0211] Additionally, at least one correction can be applied to take into account interferences with the measurement, such as lens refraction, image saturation, the effects of the corresponding camera exposure control, etc. Additionally or alternatively, applied correction factors, such as broadband corrections, calibration factors, and interference corrections, can be partially summarized or rewritten. Additionally, these corrections can be replaced or supplemented by statistically determined corrections, in particular based on image features, for example via machine learning.

[0212] In another step of the evaluation method, the radiation received from different sky regions (radiance) can be determined, for example, by projection of the diffuse and / or direct radiation onto any horizontal or ground-inclined plane, including a ground-facing plane.

[0213] The association of image and sky regions and integration across image / sky regions can be used. If desired, global irradiance can also be determined on inclined planes and on planes tilted towards the ground.

[0214] In an alternative embodiment of the method, the partial steps (application of a physical camera model, allocation of image regions to sky regions, application of physically motivated corrections, projection onto an arbitrary plane) can be mimicked in part or in whole by so-called machine learning models for determining direct and diffuse radiance in an arbitrary plane.

[0215] In the simplest embodiment of the assembly, a value corresponding to the sum of diffuse and direct radiation can be ascertained by evaluating the intensities of the RGB channels from the camera data associated with the upper partial field of view or from the camera data associated with the ground. Extensions are possible to allow for the ascertainment of separate values ​​for diffuse and direct radiation.

[0216] Advantageously, the determination of direct and / or diffuse radiation can be used to verify the performance of a solar plant at the location of the assembly of the present invention and to evaluate the solar resource at that location. The radiation can be determined solely by at least one camera and its camera data, as well as by the evaluation / control device. No additional sensors or the like are required.

[0217] Advantageously, knowledge of the sky areas covered by clouds in the upper partial field of view can be used for further assessment of the identified emissions.

[0218] For example, diffuse radiation may increase due to clouds, and direct radiation may decrease due to clouds. Different weather conditions may exist at a location. Current and future radiation conditions can be ascertained, at least in part, by ascertaining cloud location and cloud velocity.

[0219] According to a preferred embodiment of the use of the assembly, the velocity of at least one cloud above the Earth's surface can be determined from captured camera data of the lower partial field of view or from camera data associated with the Earth's surface, from radiation reflected from the Earth's surface and / or from the albedo of the Earth's surface and / or from at least one cloud shadow position, and / or from the cloud shadow position between at least two timestamps.

[0220] The speed of the cloud or clouds above the ground can be ascertained from the camera image of the lower subfield of view or from camera data associated with the ground surface.

[0221] The corresponding evaluation methods are similar to those used to determine the angular velocity of the clouds from images of the upper partial field of view or from camera data associated with the sky, respectively.

[0222] In an alternative method, the image features corresponding to the location of at least one cloud shadow and their shifts Δm, Δn can also be ascertained by other means, for example using SIFT (Scale Invariant Feature Transform) or other machine learning methods.

[0223] A possible method is to detect an image feature corresponding to the cloud shadow position or positions and to ascertain a shift of Δm, Δn of the image feature in the camera image towards the x-axis and y-axis between times t1=t0, t2=t0+Δt, t3=t0+2Δ.

[0224] The shift can be represented by creating a difference image d1 of one of the existing color channels. In this case, a first difference image d1 can be created from the camera image at a first time t1 = t0 and the camera image at a second time t2 = t0 + Δt. In addition, a second difference image d2 can be created from the camera image at a second time t2 = t0 + Δt and the camera image at a third time t3 = t0 + 2Δt. The difference images d1 and d2 can be deskewed. Deskewing is understood to mean that the image is projected downward from the camera using a known height profile of the ground surface in the monitored area and a geometric calibration of the camera at the ground surface. The result of this projection is orthoimages o1 and o2. Image features and their positions are identified from the orthoimages o1 and o2. The projection height is known here, as opposed to evaluating an upper partial field of view of at least approximately 180° around the camera assembly. Thus, in the corresponding orthoimages, each pixel corresponds to a square partial section of the monitored area. The difference image can be calculated from the orthoimage converted to grayscale. Outputs other than grayscale are also possible.

[0225] Similar to checking the angular velocity, the difference image can be converted into a binary image. For example, 2% of the pixels can receive a value of 1, while the other 98% receive a value of 0. These 2% of pixels have the largest absolute difference. This makes it possible to check for a sudden increase or decrease from this color channel between times t0, t0 + Δt, and t0 + 2Δt.

[0226] In another step, these binary images can be compared globally by cross-correlation, or in a more precise way, the images can be compared section by section, for example.

[0227] The image pixel shifts Δm and Δn are equal to the shift at which the cross-correlation between the binary orthoimages o1 and o2 reaches a maximum. The displacement of the difference m in the image pixel can be attributed to the corresponding shift of the difference x and difference y in the cloud shadow within the monitored area. This method can be performed for at least one color channel. In this way, multiple color channels can also be evaluated. Furthermore, the method can be further refined and appropriately adjusted to confirm the image pixel shifts Δm and Δn of the cloud shadow or multiple cloud shadows, respectively.

[0228] This "absolute" velocity measure of the cloud shadow above the ground is calculated as follows: JPEG2025536501000004.jpg35122 where the scaling factor ksc (in m / pixel) denotes the known page length in image pixels in meters.

[0229] Since the velocity of the cloud shadow above the ground also corresponds to the velocity of the corresponding cloud above the ground, two sky cameras monitoring different upper partial fields of view are advantageously not required to ascertain the cloud velocity above the ground, as the cloud velocity can be easily ascertained from one lower partial field of view or from camera data associated with the ground surface, respectively.

[0230] In addition, the evaluation of the lower partial field of view provides more additional information than the separate evaluation of the upper partial field of view, and the use of estimates in the calculation of cloud velocity can be eliminated, making it possible to calculate reliable and accurate values ​​for cloud velocity above the ground.

[0231] Cloud velocity above the ground is hereinafter understood as the velocity of the cloud compared to an imaginary fixed point on the ground. Advantageously, future cloud positions and corresponding changes in global irradiance in a specified area can be ascertained or predicted from the ascertained cloud velocity and current cloud positions.

[0232] The radiation reflected from the Earth's surface and / or the ground's albedo can also be determined. Determining the radiation reflected from the ground is similar to determining the direct and / or diffuse radiation.

[0233] As a reference, the RGB channels of at least one camera in the lower partial field of view or the intensity values ​​of the camera data associated with the ground surface are evaluated, respectively, and these intensity values ​​can be read directly from the corresponding camera or from the camera data associated with the ground surface.

[0234] In a possible evaluation method, a physical camera model from the intensity values ​​of the RGB channels of the camera image is used to calculate the radiation received from a specific ground region. Additionally, physically motivated corrections can be applied to improve the calculation.

[0235] In alternative exemplary embodiments, the physical camera model can be replaced by a purely statistical, machine-based learning model (machine learning model). In particular, an architecture using a convolutional neural network followed by a fully connected neural network can, with appropriate training, replace, mimic, or complement the camera model, or adapt it to itself.

[0236] In one step of the evaluation method, which assumes a basic physical camera model, a linearized RGB image can be obtained from the RGB images of each camera by inverting the gamma correction common to the cameras. If the corresponding camera does not perform gamma correction, this step can be eliminated, so that the gamma correction does not need to be inverted later. This can happen, for example, if the corresponding camera's gamma correction is disabled or if the camera does not perform gamma correction for other reasons.

[0237] In another step of the evaluation method, a pixel-by-pixel association of image regions with ground regions can be performed, for example using a known height profile of the ground surface in the monitored area, where each pixel may correspond to a square subsection of the monitored area.

[0238] Alternatively, the pixel-by-pixel association of image regions with ground regions can be taken over from the determination of cloud velocity. Instead of pixel-by-pixel association, other associations are also possible.

[0239] Corresponding camera geometric calibration and transformations based thereon can be applied when associating image regions with ground regions. Additionally, associations without calibration are possible. The calibration and transformations based thereon can be implemented as machine-based learning models (machine learning models) and can be continuously improved.

[0240] In another step of the evaluation method, the intensities of the color channels of the linearized RGB image can be weighted and summed, so that the sensitivity of the corresponding camera is as uniform as possible in the visible wavelength range.

[0241] Another step in the evaluation method can be a multiplication by a broadband correction that takes into account the proportion of broadband solar radiation that comes from the non-visible wavelength range, as well as a calibration factor that takes into account the sensitivity of the camera.

[0242] Additionally, at least one correction can be applied to take into account interferences with the measurement, such as lens refraction, image saturation, the effects of the corresponding camera exposure control, etc. Additionally or alternatively, the applied correction factors, such as broadband corrections, calibration factors, corrections for interferences, etc., can be partially summarized or rewritten.

[0243] Additionally, these corrections can be replaced or supplemented by statistically determined corrections, for example via machine learning, particularly based on image features.

[0244] In another step of the evaluation method, the radiation impinging on a plane and reflected from the ground can also be checked for inclined planes and for planes oriented towards the ground.

[0245] In alternative embodiments of the method, partial steps for ascertaining radiation reflected from the ground, such as applying a physical camera model and / or allocating image regions to sky regions and / or applying physically motivated corrections and / or projecting onto an arbitrary plane, can be mimicked in part or in whole by machine learning models.

[0246] Additionally, in another step, the current albedo of the ground or a more detailed reflectance of the ground can be derived from the ascertained reflected radiation and the ascertained direct radiation and the ascertained diffuse radiation.

[0247] Advantageously, evaluation of camera data of a lower partial field of view of at least about 180° around the camera assembly, or camera data associated with the ground surface and an upper partial field of view of at least about 180° around the camera assembly, or camera data associated with the sky, allows for ascertaining the current albedo or reflectance of the ground in the monitored area, for example, due to weather, season, or vegetation-related conditions, thus eliminating reliance on less accurate estimates of ground albedo or reflectance, respectively, which allows for a better assessment of solar radiation in the area.

[0248] Advantageously, the reflectance or albedo and / or reflected radiation and / or direct radiation and / or diffuse radiation of the ground can be represented in an angularly resolved and spectrally resolved manner.

[0249] Additionally, global and diffuse irradiance on any tilted surface can be calculated from the radiation from different areas of the ground and from the angular and spectrally resolved reflectance of the ground or albedo, including the plane pointing to the ground. In this way, the radiation at the rear of the module can be calculated individually for each module of a bifacial photovoltaic module, taking into account the typically complex geometry of the power plant. This mechanism can also be supported by combining with a pyranometer.

[0250] Reflectance corresponds to the reflectance factor of a surface, which is the ratio of the radiant power reflected from the surface to the radiant power that strikes the surface.

[0251] Angular resolved reflectance is understood to mean information in the sense of derived quantities such as the bidirectional reflectance distribution function, or the detailed composition of albedo, in particular black-sky albedo and white-sky albedo.

[0252] Spectrally resolved reflectance is the ratio of the radiant power reflected by a surface at a particular wavelength or range of wavelengths to the radiant power impinging on the surface at that particular wavelength or range of wavelengths.

[0253] Additionally, camera data associated with bottom view camera data can be advantageously used to monitor for contamination or damage to photovoltaic systems and other solar collectors so that cleaning or repairs can be arranged as needed.

[0254] Advantageously, determining direct and / or diffuse radiation along with reflected radiation can be used to determine the performance of a solar plant at the location of the assembly of the present invention and to evaluate the solar resource at that location. No additional sensors or sensor units, such as pyranometers, are required. Radiation can be determined solely with at least one camera and its camera data.

[0255] According to a preferred embodiment of the use of the assembly, the height of the clouds can be ascertained from the velocity of at least one cloud above the ground and the angular velocity of at least one cloud in the camera image.

[0256] Cloud velocity above the ground can be calculated based on the angular velocity vpix / s in at least an upper partial field of view of about 180° around the camera assembly. vm / s=vpixels / s2tanθH2 / N Therefore, the cloud height H2 is: JPEG2025536501000005.jpg35122

[0257] The angle θ corresponds to the maximum zenith angle at which an upper partial field of view of at least about 180° around the camera assembly is evaluated.

[0258] N corresponds to the diameter in pixels of the circular image region, representing the sky region with a zenith angle less than or equal to θ.

[0259] The angle θ and parameter N can be determined from camera images of at least about 180° of an upper partial field of view around the camera assembly. vm / s corresponds to the confirmed velocity of the cloud above the ground, and vpix / s corresponds to the confirmed angular velocity of the cloud. H2 corresponds to the cloud height projected above the camera assembly or above at least one camera of the camera assembly oriented toward the sky. Because the distance to the ground of at least one camera is known, the known height profile of the monitored area, the current cloud position and height of the cloud projected above the camera can be used to calculate the actual height of the cloud above the ground at its current location. Refinement of the calculation is possible.

[0260] In particular, future cloud positions can be ascertained using cloud height, the current location of the clouds, and cloud velocity above the Earth's surface. From this, future shading or future global irradiance can be estimated or calculated, and therefore predicted, in a specified area. This allows for more accurate short-term forecasts of solar radiation using a single co-located camera assembly, with the camera used installed just a few meters above the ground. Advantageously, this allows for early responses to shading or fluctuations in solar system performance to be predicted. Camera data can advantageously be ascertained at a common location, making the assembly of the present invention easier to maintain and operate and more cost-effective.

[0261] According to a preferred embodiment of the use of the assembly, the cloud velocity above the Earth's surface and / or the angular velocity of the cloud in the camera image can be extrapolated in time and / or space.

[0262] Here, both the angular velocity of the clouds in the camera image and the velocity of the clouds above the ground can be averaged and / or extrapolated in time and space to obtain a larger temporal and spatial coverage. This also allows for determining the cloud height and cloud velocity of clouds whose shadows are not (yet) captured within a lower field of view of at least approximately 180° around the camera assembly. Temporal and spatial extrapolation can be used to compensate for the fact that the lower field of view covers a smaller area and therefore casts less cloud shadow than clouds captured within an upper partial field of view. Due to the temporal and spatial extrapolation, it is not necessary to use data from one cloud and its shadow for the evaluation. The shadows of other clouds can also be used to determine the cloud height of clouds captured within an upper partial field of view of at least approximately 180° around the camera assembly. This evaluation is less accurate than when camera data from the clouds and their shadows are used for the evaluation. However, it is possible to continuously confirm cloud height. With known systems, such as lidar or ceilometer systems, cloud height is only confirmed selectively.

[0263] According to a preferred embodiment of the use of the assembly, at least one current and / or future value of at least one component of global irradiance can be determined in a spectrally resolved and / or angle resolved manner from the camera data and / or the ascertained parameters.

[0264] The angle-resolved radiation information, particularly the radiance, can be weighted and integrated into a plane of interest corresponding to the projection.

[0265] The angle-resolved information itself may be of interest to the user, in which case weighting and integration can be eliminated. The angle-resolved capture of at least one component of global irradiance can determine the current and / or future albedo of the ground. Furthermore, the current and / or future irradiance of radiation impinging on a plane with a known inclination relative to the ground, such as the rear of a bifacial photovoltaic module, can be advantageously determined. Additional support by a pyranometer or other suitable sensor is possible. Advantageously, no additional sensor, such as a pyranometer, is required to resolve the irradiance of the components of global irradiance in a spectrally and / or angle-resolved manner or to ascertain the irradiance on a plane inclined relative to the Earth's surface.

[0266] According to a preferred embodiment of the use of the assembly, at least one component of the global irradiance can be determined on an inclined surface, in particular on an arbitrarily oriented surface. This advantageously makes it possible to determine the optimal angle of tilt of the solar module, including the bifacial photovoltaic module. Alternatively or additionally, if the angle of tilt of the solar module, including the bifacial photovoltaic module, is known, the current and / or expected performance can be determined.

[0267] A method for determining at least one parameter for determining at least one component of global irradiance is proposed, wherein camera data is collected at a common location within a field of view of at least about 360° around a camera assembly, and information regarding solar radiation and / or cloud locations and / or characteristics is derived from the camera data.

[0268] In particular, the method may be a computer-implemented method.

[0269] Substantially the same definitions apply to the use of an assembly and to the method for ascertaining at least one parameter for determining at least one component of global irradiance as to the assembly.

[0270] Thus, for example, repeated definitions of cloud features, angularly resolved reflectance, and spectrally resolved reflectance are eliminated at this point.

[0271] Since the evaluation steps of the method substantially correspond to the evaluation steps of the application of the device, repetitions are also omitted below, and reference is made to the description of the use of the assembly for details of the method steps.

[0272] Further evaluations are possible using evaluations with other timestamps or from other color channels, where evaluations from camera data associated with an upper partial field of view of at least about 180° around the camera assembly or associated with the sky can be combined with evaluations from camera data associated with a lower partial field of view of at least about 180° around the camera assembly or associated with the Earth's surface.

[0273] This advantageously allows for the elimination of reliance on estimates or values ​​from external sources to ascertain most parameters for determining at least one component of global irradiance, thereby allowing for more accurate and reliable ascertainment of parameters for a specified location than using standard methods for capturing and / or forecasting at least one parameter for ascertaining and / or predicting at least one component of global irradiance that rely on estimates and values ​​from external data sources.

[0274] Advantageously, by evaluating a field of view of at least about 360° around the camera assembly, the method allows the advantages of an assembly having a sky camera oriented towards the sky, also known as a cloud camera, to be combined with the advantages of an assembly having a ground camera oriented towards the ground, also known as a shadow camera, and allows the disadvantages of the sky camera and the cloud camera to be compensated for.

[0275] To achieve these advantages, camera data associated with each partial field of view is evaluated, and in addition, the camera data for each partial field of view is advantageously captured at a common location, in particular simultaneously.

[0276] Image features in one or more color channels of each sub-field of view resulting from clouds and cloud shadows and / or from radiation entering at least one lens of at least one camera may be evaluated.

[0277] Additionally, intensity values ​​of one or more color channels of each partial field of view can be evaluated, and the evaluation results of each color channel can be compared with evaluation results of other color channels or evaluation results with other time stamps.

[0278] Combining these advantages, a camera assembly with a spatial field of view of at least approximately 360° may be sufficient to capture enough camera data to reliably capture and / or predict desired parameters. This means that evaluation of camera data from other cameras at other locations or measurement data from other sensor units can be eliminated, thereby reducing costs and the time required for evaluation.

[0279] The advantage of evaluating camera data from the upper partial field of view is that a large part of the sky can be captured and monitored, and in particular clouds can be detected long before their shadows reach the monitored area, allowing corresponding predictions to be made.

[0280] The advantage of evaluating camera data from the lower subfield of view or associated with the ground surface is that some parameters, such as cloud velocity above the ground, can be extracted precisely and directly from this camera data.

[0281] The portion of the ground that can be monitored and captured depends, among other things, on the height at which the at least one camera capturing the lower partial field of view is disposed.

[0282] Advantageously, the predictions can be confirmed using camera data from an upper partial field of view or from camera data associated with the sky, respectively, which does not necessarily require a large portion of the ground to be monitored, so that the camera assembly can be positioned at a lower height above the ground, in contrast to known shadow camera assemblies.

[0283] According to a preferred embodiment of the method, the field of view of the camera assembly at the designated location can be comprised of a first sub-field of view and a second sub-field of view each of at least about 180° around the camera assembly, and camera data can be captured within the first sub-field of view using at least one first camera and within the second sub-field of view using at least one second camera, the two sub-fields of view of the cameras complementing each other to form a field of view of at least about 360°.

[0284] According to a preferred embodiment of the method, at least one first camera can capture camera data such that the sky camera can capture camera data in a first partial field of view that is oriented towards the sky and forms an upper partial field of view, and at least one second camera can be used as a ground camera to capture camera data in a second partial field of view that is oriented towards the ground and forms a lower partial field of view.

[0285] Alternatively, a 360° camera having a field of view of at least about 360° around the camera assembly can capture camera data within a first partial field of view and camera data KDE within the partial field of view. In particular, the first partial field of view can form an upper partial field of view oriented toward the sky, and the second partial field of view can form a lower partial field of view oriented toward the Earth's surface.

[0286] Advantageously, in this case the camera data of each camera can be easily associated with the upper or lower partial field of view. Advantageously, the method can combine the advantages of a cloud camera assembly and a shadow camera assembly, thereby reducing the costs of purchasing and operating hardware items.

[0287] According to a preferred embodiment of the method, camera data associated with the sky can be extracted from the captured camera data and at least one of the following parameters can be ascertained from these camera data associated with the sky: direct radiation and / or diffuse radiation and / or global irradiance and / or at least the position of a cloud feature and / or the area of ​​the sky covered by clouds and / or the angular velocity of at least one cloud in the camera image from the cloud position and / or from the position of the cloud feature in the camera image between at least two timestamps.

[0288] Advantageously, the determination of direct and / or diffuse radiation can be used to determine the performance of a solar plant at the location of the assembly of the invention and to evaluate the solar resource at that location.

[0289] The radiation can be determined solely based on the camera data, without any additional measurement data from the sensor.

[0290] Advantageously, knowledge of the sky areas covered by clouds in the upper partial field of view can be used to further assess the identified radiation. For example, diffuse radiation from clouds may increase and direct radiation from clouds may decrease. Different weather conditions may exist at that location.

[0291] Present and future radiation conditions can be ascertained at least in part by ascertaining cloud locations and cloud velocities.

[0292] More particularly, reference is made to the use of the assembly to determine the parameters.

[0293] According to a preferred embodiment of the method, camera data associated with the Earth's surface can be extracted from the captured camera data and at least one of the following parameters can be ascertained from this camera data associated with the Earth's surface: radiation reflected from the Earth's surface and / or the albedo of the Earth's surface and / or at least one cloud shadow position and / or the velocity of at least one cloud above the Earth's surface from the cloud shadow position between at least two timestamps.

[0294] The speed of the cloud or clouds above the ground can be ascertained by the method of the present invention from the camera image of the lower partial field of view or from the camera data associated with the ground surface, respectively.

[0295] The corresponding evaluation methods are similar to those used to determine the angular velocity of the clouds from images of the upper partial field of view or from camera data associated with the sky, respectively.

[0296] In an alternative method, the image features corresponding to the location of at least one cloud shadow and their shifts Δm, Δn can also be ascertained by other means, for example using SIFT (Scale Invariant Feature Transform) or other machine learning methods.

[0297] More particularly, reference is made to the use of the assembly to determine the parameters.

[0298] Advantageously, determining direct and / or diffuse radiation along with reflected radiation can be used to determine the performance of a solar plant at the location of the assembly of the present invention and to evaluate the solar resource at that location. No additional sensors or sensor units, such as pyranometers, are required. Radiation can be determined solely with at least one camera and its camera data.

[0299] According to a preferred embodiment of the method, the cloud height can be ascertained from the velocity of at least one cloud above the ground and the angular velocity of at least one cloud in the camera image.

[0300] More particularly, reference is made to the use of the assembly to determine the parameters.

[0301] In particular, future cloud positions can be ascertained using cloud height, the current location of the cloud, and cloud velocity above the Earth's surface. From this, future shading or future global irradiance can be estimated or calculated for a specified area. This allows for more accurate short-term forecasts of solar radiation using a single co-located camera assembly, where the camera used is mounted only a few meters above the ground. Advantageously, this allows for early responses to shading or variations in solar system performance to be predicted.

[0302] According to a preferred embodiment of the method, the cloud velocity above the Earth's surface and / or the angular velocity of the cloud in the camera image can be extrapolated in time and space.

[0303] Here, both the angular velocity of the clouds in the camera image and the velocity of the clouds above the surface can be averaged and / or extrapolated in time and space to obtain a larger temporal and spatial range, which also allows for the determination of cloud height and cloud velocity for clouds whose shadows are not (yet) captured in the lower field of view.

[0304] Temporal and spatial extrapolation can be used to compensate for the fact that the lower field of view covers a smaller portion and therefore less cloud cover than the clouds captured in the upper partial field of view.

[0305] Due to the temporal and spatial extrapolation, it is not necessary to use data from one cloud and its shadow for the assessment. The shadows of other clouds can also be used to determine the cloud height of clouds captured in the upper partial field of view. This assessment is less accurate than when camera data from the cloud and its shadow are used for the assessment. However, it is possible to check the cloud height continuously.

[0306] According to a preferred embodiment of the method, at least one current and / or future value of at least one component of global irradiance may be determined in a spectrally resolved and / or angle resolved manner from the camera data and / or the ascertained parameters.

[0307] The angle-resolved radiation information, particularly the radiance, can be weighted and integrated into a plane of interest corresponding to the projection.

[0308] The angle-resolved information itself may be of interest to the user, in which case weighting and integration can be eliminated. The angle-resolved capture of at least one component of global radiation can determine the current and / or future albedo of the ground. Furthermore, the current and / or future irradiance of radiation impinging on a plane with a known inclination relative to the ground, such as the rear of a bifacial photovoltaic module, can be advantageously determined. Additional support by pyranometers or other suitable sensors is possible.

[0309] Advantageously, no additional sensors, such as pyranometers, are required to resolve the irradiance of components of global radiation in a spectrally and / or angularly resolved manner or to ascertain the irradiance on a plane inclined relative to the Earth's surface.

[0310] According to a preferred embodiment of the method, at least one component of the global irradiance can be determined on a tilted surface, which advantageously allows for determining an optimal angle of tilt of solar modules, including bifacial photovoltaic modules. Alternatively or additionally, if the angle of tilt of the solar modules is known, it is possible to determine, among other things, the current and / or expected performance of the bifacial photovoltaic module.

[0311] The inventive assembly, the inventive use of the assembly, and the inventive method can be used to predict global radiance and / or to predict the components of global radiance at a particular Earth surface area that are due to cloud position and the slope of the surface on which the global radiance impinges, thereby making it possible to use the inventive assembly, the inventive use of the assembly, and the inventive method to perform short-term forecasts of solar radiation.

[0312] These forecasts have been used to run self-sufficient microgrids more efficiently through memory or targeted control of generators. Additionally, such forecasts can assist in the operation of distribution networks and the marketing of solar power plant output.

[0313] Furthermore, accurate and angle-resolved measurements of ground-reflected radiation and sky-reflected radiation can improve the monitoring of photovoltaic plants, particularly bifacial photovoltaic plants, allowing for more efficient, less labor-intensive, and automated monitoring.

[0314] By monitoring cloud cover, the inventive assembly, the inventive use of the assembly, and the inventive method can also provide input data for numerical weather models or for combined forecast models incorporating satellite data and may therefore be of interest to private and public weather services. The inventive assembly, the inventive use of the assembly, and the inventive method can also contribute to more cost-effective and complete surveillance of the airspace above, for example, airports, by monitoring cloud cover and cloud height.

[0315] Additionally, a computer program or computer program product is proposed comprising commands to cause a device of the invention to carry out the method of the invention for ascertaining at least one parameter for determining at least one component of the global irradiance GI.

[0316] Additionally, a computer program or computer program product is proposed comprising instructions to cause a computer to carry out, when the computer program is executed by a computer, a method for ascertaining at least one parameter for determining at least one component of global irradiance GI, the method comprising capturing camera data KDH, KDE from a camera assembly within at least an approximately spherical field of view around the camera assembly, and deriving from the camera data KDH, KDE information relating to solar radiation and / or cloud positions and / or characteristics. [Brief explanation of the drawings]

[0317] Further advantages will become apparent from the following description of the drawings. Exemplary embodiments of the invention are shown in the drawings. The drawings, description, and claims include a number of features in combination. Those skilled in the art will also conveniently consider features individually and combine them into more meaningful combinations.

[0318] The figure illustrates the following: [Figure 1] 1 is a schematic diagram of an assembly for capturing and / or predicting at least one parameter for determining and / or predicting at least one component of global irradiance; [Figure 2] 1 is a schematic diagram of an assembly for capturing and / or predicting at least one parameter for determining and / or predicting at least one component of global irradiance; [Figure 3] 3 is a schematic illustration of the use of the assembly from FIG. 1 or FIG. 2 and a schematic illustration of a method for capturing and / or predicting at least one parameter for determining and / or predicting at least one component of global irradiance. DETAILED DESCRIPTION OF THE INVENTION

[0319] In the figures, identical or identically acting components are identified by the same reference numerals. The figures are illustrative only and should not be understood as limiting.

[0320] The directional terms used below, together with terms such as "left," "right," "upper," "lower," "in front of," "rear," and "after," are merely to aid in better understanding of the figures and are in no way intended to limit generality. The components and elements shown, their configuration and use can be modified according to the considerations of those skilled in the art and adapted to each application.

[0321] 1 and 2 show, in schematic form, an assembly 100 of the present invention for capturing and / or predicting at least one parameter for determining and / or predicting at least one component of global irradiance GI.

[0322] The assembly 100 comprises at least one evaluation / control device 110 and a camera assembly 120 having at least one camera 122 , 124 and a holding assembly 126 .

[0323] In the illustrated exemplary embodiment, the assembly 100 includes a single evaluation / control device 110. In alternative exemplary embodiments not shown, the assembly 100 can have two or more evaluation / control devices 110. The evaluation / control device 110 is wirelessly connected to the existing cameras 122, 124 in the illustrated exemplary embodiment of the assembly 100. A data connection via a cable is also contemplated.

[0324] In this example, assembly 100 has a common axis 30 and a horizontal axis 40. Camera assembly 120 is disposed along common axis 30. Camera assembly 120 has a center 50 disposed on common axis 30. Common axis 30 is oriented substantially vertically to form a substantially vertical axis 31 (FIG. 1) or tilted toward the vertical at an oblique angle to form an oblique axis 33 (FIG. 2).

[0325] In the illustrated exemplary embodiment, the assembly 100 includes two co-located cameras 122, 124 facing in opposite directions. The two cameras 122, 124 are disposed on a common axis 30, a substantially perpendicular axis 31, or an oblique axis 33. Thus, the cameras 122, 124 share a common axis 30, a substantially perpendicular axis 31, or an oblique axis 33. In alternative exemplary embodiments not shown, the assembly 100 can have three or more co-located cameras 122, 124 or only one camera 122, 124. Each camera 122, 124 includes two sensors (not shown). The sensors are disposed along the common axis 30.

[0326] The sensors face in opposite directions along a common axis 30, with one sensor facing upward and the second sensor facing downward on the common axis 30, which may be substantially vertical or oblique.

[0327] It will be appreciated that the cameras 122 and 124 may be arranged not along a common axis 30 but on two axes, which extend substantially parallel to each other at a small distance, in particular a distance of about 10 m or less.

[0328] The spatial field of view of at least about 360° around camera assembly 120 is advantageously composed of a first sub-spatial field of view and a second sub-spatial field of view each of at least about 180° around camera assembly 120, the sub-fields being arranged along a common axis 30. In particular, common axis 30 may be oriented substantially in a vertical direction 31, forming a vertical axis 31, or may be oriented at an oblique angle relative to vertical direction 31, forming an oblique axis 33.

[0329] In an exemplary embodiment not shown, the assembly can have two axes, one of the cameras 122, 124 arranged on one axis and the other of the cameras 122, 124 arranged on the other axis, with the partial fields of view arranged along the two axes, and the two axes arranged substantially parallel and at a small distance, in particular a distance of about 10 m or less.

[0330] A holding assembly 126 secures the two cameras 122, 124 at a specified distance A relative to the ground surface 20. In the exemplary embodiment shown, the holding assembly 126 is L-shaped, although other designs are possible. For example, a drone may be considered to hold the cameras. The holding assembly secures the cameras 122, 124 such that they are positioned along a common axis 30.

[0331] The camera assembly 120 is designed to capture camera data KDH, KDE within a spatial field of view of at least approximately 360° around the camera assembly 120. The spatial field of view of at least approximately 360° extends along a common substantially vertical axis 31 or oblique axis 33, with two fields of view oriented in opposite directions along the common axis 30. Along the common axis 30, the first field of view faces upward and the second field of view faces downward.

[0332] The camera data KDH, KDE are suitable for deriving information about solar radiation and / or the position WP and / or characteristics of clouds 12. The field of view of the camera assembly 120 at a specified location consists, in the illustrated example, of an upper partial field of view oriented toward the sky 10 at least about 180° around the camera assembly and a lower field of view oriented toward the Earth's surface 20 at least about 180° around the camera assembly 120. More than two partial fields of view are also contemplated. Additionally, different orientations of the partial fields of view can be implemented.

[0333] The field of view of at least approximately 360° around the camera assembly 120 is understood to be at least a substantially spherical field of view around a center 50. At this center 50, two cameras 122, 124 are arranged. The two cameras 122, 124 are here arranged along a common axis 30, which can be oriented substantially vertically, forming a substantially vertical axis, or can be tilted at an oblique angle relative to the vertical axis, forming an oblique axis. The center 50 consists of the intersection of the common axis 30 and the horizontal axis 40.

[0334] At least one camera 122, 124 can be understood as an RGB camera or an infrared camera. In the illustrated exemplary embodiment of the assembly 100, the cameras 122, 124 are designed as RGB cameras with fisheye lenses. In an alternative exemplary embodiment not shown, instead of a camera with a fisheye lens, other mechanisms with parabolic mirrors are conceivable.

[0335] For example, the cameras 122, 124 may record 24 frames per second with corresponding timestamps. Other image production rates may be selected. Additionally, enhancements, such as with shading devices, may be considered to reduce the interfering effects of direct sunlight.

[0336] In the illustrated exemplary embodiment, the assembly 100 comprises at least a sky camera 122 associated with the sky that captures camera data KDH within an upper partial field of view of at least approximately 180 degrees around the camera assembly 120 .

[0337] Additionally, assembly 100 in the illustrated exemplary embodiment includes at least one ground camera 124 associated with the ground surface 20 that captures camera data KDE within a lower field of view of at least approximately 180 degrees around camera assembly 120. The upper and lower partial fields of view extend along a common axis 30.

[0338] In the exemplary embodiment of the assembly 100 shown, the evaluation / control device 110 determines the following parameters from the captured camera data KDH of an upper partial field of view of at least about 180° around the camera: (i) Directly emitted DNI; and / or (ii) diffuse emission diffI; and / or (iii) global irradiance GI; and / or (iv) the location WP of at least one cloud feature 12; and / or (v) areas of the sky covered by clouds 12; and / or (vi) the angular velocity vpix / s of at least one cloud 12 in the camera image from the cloud position WP and / or from the position of the cloud feature 12 in the camera image between at least two timestamps; Check at least one of the following:

[0339] Cloud features are image features of the captured image that can be associated with clouds 12 and / or cloud formations.

[0340] In the exemplary embodiment of the assembly 100 shown, the evaluation / control device 110 determines the following parameters from the captured camera data KDE of a lower partial field of view of at least about 180° around the camera assembly: (i) ERS radiation reflected from the Earth's surface; and / or (ii) the albedo AL of the Earth's surface; and / or (iii) at least one cloud shadow location SP; and / or (iv) the velocity v m / s of at least one cloud 12 above the Earth's surface 20 from the cloud shadow position SP between at least two time stamps; Check at least one of the following:

[0341] In the exemplary embodiment of the assembly 100 shown, the evaluation / control device 110 ascertains the emission from each region of a spatial field of view of at least about 360° from the intensity values ​​I of the RGB channels in the camera image.

[0342] Based on this, the albedo AL of the ground surface 20 or a more detailed reflectance of the ground surface 20 can be derived.

[0343] To determine the velocities vm / s and vpix / s of the cloud 12 and cloud shadow 22, respectively, the corresponding cameras 122, 124 capture image sequences at short intervals as camera data KDH, KDE. The image sequences determine the shift of image features between capture times. From this, the movement of the cloud 12 in the sky 10 can be ascertained. At the same time, the movement of the corresponding cloud shadow 22 on the ground 20 can be determined.

[0344] Because of the known time interval between images, this motion can be translated into a velocity v m / s of the cloud 12 above the Earth's surface 20 and an angular velocity v pix / s of the cloud 12 in the camera image.

[0345] In the illustrated exemplary embodiment of the assembly 100, the at least one evaluation / control device 110 ascertains the heights H1, H2 of the clouds 12 from the velocity vm / s of the at least one cloud 12 above the Earth's surface 20 and the angular velocity vpix / s of the at least one cloud 12 in the camera image.

[0346] H1 corresponds to the distance between the cloud 12 and the opposite ground surface 20.

[0347] H2 corresponds to the distance between the upwardly oriented camera 122 and the height of the cloud 12 projected above the upwardly oriented camera 122. H2 can be determined from the cloud velocity v m / s. H1 can be determined from the known distance A of the cameras 122, 124 to the ground 20 and the known height profile of the monitored area.

[0348] The evaluation / control device 110 uses the heights H1, H2 of the clouds 12 and the cloud velocity vm / s above the Earth's surface 20 to ascertain the future cloud position WP and the future shading or global irradiance GI for a specified horizontal or slope region.

[0349] In the illustrated exemplary embodiment, the at least one evaluation / control device 110 extrapolates in time and space the velocity vm / s of the cloud 12 above the Earth's surface 20 and the angular velocity vpix / s of the cloud 12 in the camera image. In an alternative exemplary embodiment not shown, it is possible to capture only the velocity vm / s, vpix / s of the cloud 12 whose cloud shadow 22 is measured from a lower partial field of view of at least about 180° around the camera assembly.

[0350] In the exemplary embodiment of the assembly 100 shown, the at least one evaluation / control device 110 ascertains at least a current value and / or a future value of at least one component of the global irradiance intensity GI in a spectrally and / or angle-resolved manner from the camera data KDH, KDE and / or the ascertained parameters.

[0351] In the exemplary embodiment of the assembly 100 shown, the at least one evaluation / control device 110 ascertains at least one component of the global irradiance GI on the inclined surface.

[0352] FIG. 3 shows a schematic diagram of the use of the assembly from FIG. 1 or FIG. 2 and a schematic diagram of a method 200 for capturing and / or predicting at least one parameter for determining and / or predicting at least one component of global irradiance GI.

[0353] In method steps S212 and S214, camera data KDH, KDE are captured at a common location within a spatial field of view of at least about 360° around camera assembly 120. Information regarding solar radiation and / or cloud 12 position WP and / or characteristics is derived from the camera data KDH, KDE.

[0354] In the described exemplary embodiment, the spatial field of view of at least approximately 360° around the camera assembly is composed of an upper partial field of view oriented toward the sky 10 of at least approximately 180° around the camera assembly 120 and a lower partial field of view oriented toward the Earth's surface 20 of at least approximately 180° around the camera assembly 120.

[0355] In method step S212, camera data KDH is captured with at least one sky camera 122 within an upper partial field of view of at least about 180° around a camera assembly associated with the sky 10. In method step S214, camera data KDE is captured with at least one ground camera 124 within a lower field of view of at least about 180° around a camera assembly associated with the Earth 20. Method steps S212 and S214 can be performed simultaneously or at offset times. In an alternative method step, the camera data KDE, KDH can be first associated with the Earth and sky 10. In the illustrated exemplary embodiment, this step is eliminated because the upper and lower fields of view allow for unambiguous association of the camera data.

[0356] In method step S222, the following is determined from the captured camera data KDH of at least about a 180° upper field of view around the camera assembly: (i) Directly emitted DNI; and / or (ii) Diffuse emission DiffI; and / or (iii) global irradiance GI; and / or (iv) areas of the sky covered by clouds; and / or (v) at least one cloud location WP; and / or (vi) The angular velocity vpix / s of the cloud 12 in the camera image from the cloud position WP and / or from the positions of the two timestamps is ascertained.

[0357] In method step S224, the following is determined from the captured camera data KDE of a lower field of view of at least about 180 degrees around the camera assembly: (i) ERS radiation reflected from the Earth's surface; and / or (ii) the albedo AL of the Earth's surface; and / or (iii) at least one cloud shadow location SP; and / or (iv) The velocity v m / s of at least one cloud 12 above the Earth's surface 20 from the cloud shadow position SP between at least two timestamps is determined.

[0358] The intensity value I of at least one color channel of the corresponding camera 122, 124 is evaluated to ascertain the direct radiation DNI and / or the diffuse radiation DiffI and / or the radiation ERS reflected from the Earth's surface 20.

[0359] In method step S230, the global irradiance GI is calculated from the components DiffI, DNI, ERS of the global irradiance GI as determined in method steps S222 and S224. Also, at least one component DiffI, DNI, ERS of the global irradiance GI can be determined on a surface inclined towards the Earth's surface 20.

[0360] In method step S230, the heights H1, H2 of the clouds 12 are ascertained from the velocity vm / s of the at least one cloud 12 above the Earth's surface 20 and the angular velocity vpix / s of the at least one cloud 12 in the camera image.

[0361] In this context, the velocity vm / s of the cloud 12 above the Earth's surface 20 and the angular velocity vpix / s of the cloud 12 in the camera image can be extrapolated in time and space.

[0362] In method step S240, the heights H1, H2 of the clouds 12 and the cloud speed vm / s above the Earth's surface 20 can be used to ascertain a future cloud position WP and to ascertain a forecast of future shading and / or future global irradiance GI for a specified area.

[0363] The current and / or future values ​​of the components DiffI, DNI, ERS of the global irradiance GI ascertained in method steps S222 and S224 can be ascertained from the camera data KDH, KDE and / or the ascertained parameters at least in a spectrally and / or angularly resolved manner.

[0364] The method 200 is implemented in a computer program including instructions to cause the device 100 to ascertain at least one parameter for determining at least one component of the global irradiance GI. The computer program may be part of a computer program product.

[0365] The computer program or computer program product comprises instructions that, when executed by a computer, cause the computer to carry out a method 200 for ascertaining at least one parameter for determining at least one component of global irradiance GI, comprising the following steps: capturing camera data KDH, KDE from the camera assembly 120 within a spherical field of view around the camera assembly 120; - Deriving information about the solar radiation and / or the position (WP) and / or properties of the clouds 12 from the camera data KDH, KDE is carried out. [Explanation of symbols]

[0366] 10 sky 12 clouds 20 Surface 22 Shadow of the Clouds 30 common axis 31 vertical direction, vertical axis 33 Diagonal Axis 40 horizontal axis 50 Center of camera assembly 100 Assembly 110 Evaluation / Control Devices 120 Camera Assembly 122 Sky Camera 124 Ground Camera 126 Retaining Assembly 200 ways S212~S240 Method steps KDH,KDE camera data WP cloud position SP cloud position vpix / s angular velocity vm / s velocity above ground I Color channel intensity H1 Cloud height above the ground H2 Cloud height from highest point of camera assembly A Camera assembly distance to the ground GI global irradiance DiffI Diffuse radiation DNI direct radiation ERS Radiation reflected from the Earth's surface

Claims

1. 1. An assembly (100) for ascertaining at least one parameter for determining at least one component of global irradiance GI, comprising: an evaluation / control device (110) and a camera assembly (120) having at least one camera (122, 124); the at least one camera (122, 124) is fixed at a predefined distance (A) from the ground surface (20) at least while ascertaining the parameters; the camera assembly (120) is designed to capture camera data (KDH, KDE) within a spatial field of view of at least approximately 360° around the camera assembly (120); Assembly (100), wherein said camera data KDH, KDE are suitable for deriving information about the solar radiation and / or the position (WP) and / or properties of clouds (12).

2. at least one first camera (122) captures camera data within a first partial field of view; at least one second camera (124) captures camera data within a second partial field of view; the two partial fields of view of the cameras (122, 124) complement each other to form a field of view of at least about 360°; In particular, at least said first camera (122) as a sky camera (123) captures camera data KDH within said first partial field of view oriented towards the sky (10) and forming an upper partial field of view, the at least one second camera (124) as a ground camera (125) captures camera data (KDE) within the second partial field of view (FOV) directed towards the ground surface (20) and forming a lower partial field of view; In particular, said cameras (122, 124) are each designed as a fisheye camera, or a 360° camera having a spatial field of view of at least approximately 360° around the camera assembly (120) capturing camera data (KDH) within a first partial field of view and capturing camera data (KDE) within a second partial field of view; 2. The assembly according to claim 1, wherein in particular the first partial field of view forms an upper partial field of view oriented towards the sky (10) and the second partial field of view forms a lower partial field of view oriented towards the Earth's surface (20).

3. the field of view of at least about 360° around the camera assembly (120) is composed of the first sub-spatial field of view and the second sub-spatial field of view each of at least about 180° around the camera assembly (120); The partial fields of view are arranged to overlap each other, In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes that run substantially parallel to one another at a small distance, said at least one axis (30) being oriented in a substantially vertical direction (31); or In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes that run substantially parallel to one another at a small distance, 3. An assembly according to claim 1 or 2, wherein said at least one axis (30) is oriented at an oblique angle to the vertical direction (31).

4. The evaluation / control device (110) obtains KDH camera data associated with the sky (10) from the captured camera data KDH, KDE, and determines from this camera data KDH associated with the sky (10) the following parameters: (i) direct radiation DNI; and / or (ii) diffuse emission DiffI; and / or (iii) global irradiance GI; and / or (iv) the location of at least one cloud feature; and / or (v) areas of the sky covered by clouds; and / or (vi) the angular velocity vpix / s of at least one cloud (12) in the camera image from a cloud position WP and / or from the position of a cloud feature in the camera image between at least two timestamps; 4. The assembly according to claim 1, wherein the assembly is configured to check at least one of the following:

5. The evaluation / control device (110) obtains KDE camera data associated with the surface (20) from the captured camera data KDH, KDE, and determines from this camera data KDE associated with the surface (20) the following parameters: (i) the radiation ERS reflected at the Earth's surface (20); and / or (ii) the albedo AL of the Earth's surface (20); and / or (iii) at least one cloud shadow location SP; and / or (iv) the velocity v m / s of at least one cloud (12) above the Earth's surface (20) from the cloud shadow position SP between at least two time stamps; 5. The assembly according to claim 1, wherein the assembly is configured to check at least one of the following:

6. the evaluation / control device (110) ascertains heights (H1, H2) of at least one cloud (12) from the velocity vm / s of the at least one cloud (12) above the ground surface (20) and the angular velocity vpix / s of the at least one cloud (12) in the camera image; In particular, at least one evaluation / control device (110) ascertains a future cloud position WP using said cloud heights (H1, H2) and said cloud velocity vm / s above said Earth's surface (20), 6. An assembly according to claim 4 or 5, from which future shading of a specified area or future global irradiance GI is ascertained.

7. 7. The assembly according to claim 4, wherein the at least one evaluation / control device (110) extrapolates in time and space the velocity vm / s of the clouds (12) above the ground surface (20) and / or the angular velocity vpix / s of the clouds (12) in the camera image.

8. 8. The assembly according to claim 4, wherein the at least one evaluation / control device (110) determines actual and / or future values ​​of at least one component of the global irradiance GI from the camera data KDH, KDE and / or the ascertained parameters in a spectrally or angularly resolved manner.

9. 9. The assembly according to claim 8, wherein at least one evaluation / control device (110) determines at least one component of the global irradiance GI on an inclined surface, in particular on an arbitrarily oriented surface.

10. Use of an assembly (100) according to any one of claims 1 to 9 for ascertaining at least one parameter for determining at least one component of the global irradiance GI, comprising: camera data KDH, KDE is recorded within a spatial field of view of at least approximately 360° around said camera assembly (120); Use, wherein information regarding solar radiation and / or cloud position and / or characteristics is derived from said camera data KDH, KDE.

11. camera data is captured within a first partial field of view using at least one first camera (122), and camera data is captured within a second partial field of view using at least one second camera (124); the two partial fields of view of the cameras (122, 124) complement each other to form a field of view of at least about 360°; In particular, the camera data KDH are captured using at least one first camera (122) as a sky camera (123) within said first partial field of view, oriented towards the sky (10) and forming an upper partial field of view, camera data KDE is captured using at least one second camera (124) as a ground camera (125) within said second partial field of view, directed towards the Earth's surface (20) and forming a lower partial field of view; or Using a 360° camera having a spatial field of view of at least approximately 360° around the camera assembly (120), camera data KDH is captured within a first partial field of view and camera data KDE is captured within a second partial field of view; 11. The use according to claim 10, in particular, wherein the first partial field of view forms an upper partial field of view oriented towards the sky (10) and the second partial field of view forms a lower partial field of view oriented towards the Earth's surface (20).

12. the field of view of at least about 360° around the camera assembly (120) is composed of the first and second sub-spatial fields of view, each of at least about 180° around the camera assembly (120), the sub-fields of view being arranged to overlap one another; In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes that run substantially parallel to one another at a small distance, said at least one axis (30) being oriented in a substantially vertical direction (31); or In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes that run substantially parallel to one another at a small distance, 12. Use according to claim 10 or 11, wherein said at least one axis (30) is oriented at an oblique angle to the vertical direction (31).

13. camera data KDH associated with the sky (10) is obtained from the captured camera data KDH, KDE; The following parameters: (i) direct radiation DNI; and / or (ii) diffuse emission DiffI; and / or (iii) global irradiance GI; and / or (iv) the location of at least one cloud feature; and / or (v) areas of the sky covered by clouds; and / or (vi) the angular velocity vpix / s of at least one cloud (12) in the camera image from a cloud position WP and / or from the position of a cloud feature in the camera image between at least two timestamps; Use according to any one of claims 10 to 12, wherein at least one of the following is ascertained from these camera data KDH associated with said sky (10).

14. KDE camera data associated with the surface (20) is obtained from the captured camera data KDH, KDE and includes the following parameters: (i) the radiation ERS reflected at the Earth's surface (20); and / or (ii) the albedo AL of the Earth's surface (20); and / or (iii) at least one cloud shadow location SP; and / or (iv) the velocity v m / s of at least one cloud (12) above the Earth's surface (20) from the cloud shadow position SP between at least two time stamps; Use according to any one of claims 10 to 13, wherein at least one of the following is ascertained from these camera data KDE associated with said surface (20).

15. the heights (H1, H2) of the clouds (12) are ascertained from the velocity vm / s of at least one cloud (12) above the ground surface (20) and the angular velocity vpix / s of at least one cloud (12) in the camera image; 15. The use according to claim 14, in particular, wherein future cloud positions WP and future shading and / or global irradiance GI of a specified area are ascertained using the cloud heights (H1, H2) and the cloud velocity vm / s above the Earth's surface (20).

16. 16. Use according to claim 14 or 15, wherein the velocity vm / s of clouds (12) above the Earth's surface (20) and / or the angular velocity vpix / s of clouds (12) in the camera image are extrapolated in time and space.

17. 17. Use according to any one of claims 10 to 16, wherein at least one current and / or future value of at least one component of the global irradiance GI is determined in a spectrally and / or angularly resolved manner from the camera data KDH, KDE and / or the ascertained parameters.

18. 18. Use according to claim 17, wherein at least one component of the global irradiance GI is determined on an inclined surface, in particular on an arbitrarily oriented surface.

19. A method (200), in particular a computer-implemented method, for ascertaining at least one parameter for determining at least one component of the global irradiance GI, comprising: A method (200) in which camera data (KDH, KDE) are collected at a common location within a spatial field of view of at least approximately 360° around the camera assembly (120), and information regarding the position (WP) and / or characteristics of solar radiation and / or clouds (12) is derived from the camera data (KDH, KDE).

20. camera data is captured within a first partial field of view using at least one first camera (122), and camera data is captured within a second partial field of view using at least one second camera (124); the two partial fields of view of the cameras (122, 124) complement each other to form a field of view of at least about 360°; In particular, the camera data KDH are captured using at least one first camera (122) as an air camera (123) in a first partial field of view, in this case oriented towards the sky (10) and forming an upper partial field of view, and the camera data KDE are captured using at least one second camera (124) as a ground camera (125) in a second partial field of view, in this case oriented towards the earth's surface (20) and forming a lower partial field of view, or Using a 360° camera having a field of view of at least approximately 360° around the camera assembly (120), camera data KDH is captured within a first partial field of view and camera data KDE is captured within a second partial field of view; 20. The method of claim 19, wherein in particular the first partial field of view forms an upper partial field of view oriented towards the sky (10) and the second partial field of view forms a lower partial field of view oriented towards the Earth's surface (20).

21. the field of view of at least about 360° around the camera assembly (120) is composed of the first sub-spatial field of view and the second sub-spatial field of view each of at least about 180° around the camera assembly (120); The partial fields of view are arranged to overlap each other, In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes extending substantially parallel to one another at a small distance, the at least one axis (30) being oriented in a substantially vertical direction (31), or In particular, the partial fields of view are arranged along at least one axis (30) or are arranged overlapping one another along two axes that run substantially parallel to one another at a small distance, 21. The method according to claim 19 or 20, wherein said at least one axis (30) is oriented at an oblique angle to the vertical direction (31).

22. The camera data KDH associated with the sky (10) is obtained from the captured camera data KDH, KDE and includes the following parameters: (i) direct radiation DNI; and / or (ii) diffuse emission DiffI; and / or (iii) global irradiance GI; and / or (iv) areas of the sky covered by clouds; and / or (v) at least one cloud location WP; and / or (vi) the angular velocity vpix / s of at least one cloud (12) in the camera image from a cloud position WP and / or from the position of a cloud feature in the camera image between at least two timestamps; At least one of the 22. The method according to any one of claims 19 to 21, wherein the sky (10) is ascertained from these camera data KDH associated with the sky (10).

23. KDH camera data associated with the surface (20) is obtained from the captured camera data KDH, KDE and includes the following parameters: (i) the radiation ERS reflected at the Earth's surface (20); and / or (ii) the albedo AL of the Earth's surface (20); and / or (iii) at least one cloud shadow location SP; and / or (iv) the velocity v m / s of at least one cloud (12) above the Earth's surface (20) from a cloud shadow position SP between at least two time stamps; 23. The method according to any one of claims 19 to 22, wherein at least one of the following is ascertained from these camera data KDH associated with the surface (20).

24. the heights (H1, H2) of the clouds (12) are ascertained from the velocity vm / s of at least one cloud (12) above the ground surface (20) and the angular velocity vpix / s of at least one cloud (12) in the camera image; 24. The method according to claim 23, wherein in particular a future cloud position WP is ascertained using the heights (H1, H2) of the clouds (12) and the cloud velocity vm / s above the Earth's surface (20), and a future shading and / or a future global irradiance GI of a specified area is ascertained therefrom.

25. 25. The method according to any one of claims 23 to 24, wherein the velocity vm / s of clouds (12) above the Earth's surface (20) and / or the angular velocity vpix / s of clouds (12) in the camera image are extrapolated in time and space.

26. 26. The method according to any one of claims 19 to 25, wherein at least one current and / or future value of at least one component of the global irradiance GI is ascertained from the camera data KDH, KDE and / or the ascertained parameters in a spectrally and / or angularly resolved manner.

27. 27. The method according to claim 26, wherein at least one component of the global irradiance GI is ascertained on an inclined surface, in particular on an arbitrarily oriented surface.

28. 28. A computer program or computer program product comprising instructions for causing an assembly (100) according to any one of claims 1 to 9 to perform a method (200) for ascertaining at least one parameter for determining at least one component of the global irradiance GI according to any one of claims 19 to 27.

29. 28. A method (200) for ascertaining at least one parameter for determining at least one component of the global irradiance GI according to any one of claims 19 to 27, said method or computer program product being characterized in that, when said computer program is executed by a computer, said method comprises: capturing camera data KDH, KDE by a camera assembly (120) within a spherical field of view around said camera assembly (120); deriving information about the position (WP) and / or characteristics of the solar radiation and / or clouds (12) from said camera data (KDH, KDE); a computer program or computer program product comprising instructions for causing said computer to carry out the method (200),

Images