Method and device for predicting solar radiation quantity of photovoltaic panel

Abstract

The invention provides a photovoltaic panel solar radiation quantity prediction method and device. The method comprises the steps of collecting a sky image and synthesizing the sky image into an HDR image; analyzing sky radiation information according to the HDR image; establishing a real-time sky model according to the sky radiation information; and calculating the incident radiation quantity of the photovoltaic panel, wherein the incident radiation quantity of the photovoltaic panel comprises direct solar radiation, sky scattering radiation and ground reflection radiation. According to the photovoltaic panel solar radiation quantity prediction method and device provided by the invention, the prediction of the solar radiation quantity of the photovoltaic panel in a complex shielding environment is realized, and the defect that an ideal sky model cannot describe an actual external environment is effectively avoided by constructing a shielding-oriented high-resolution sky radiation field; through fusion of the HDR image and the real-time sky model and in combination with the shielding relationship, the distribution accuracy of the incident radiation on the surface of the photovoltaic panel in time and space dimensions is improved.

Description

Technical Field

[0001] This disclosure relates to the field of photovoltaic power generation technology, and in particular to a method and apparatus for predicting solar radiation from photovoltaic panels. Background Technology

[0002] Photovoltaic power generation systems have been widely used in various fields such as construction, transportation, and agriculture to achieve clean energy supply. Among them, building integrated photovoltaic (BIPV) systems have become an important form of photovoltaic application in recent years. Their components not only generate electricity but also serve architectural functions such as shading and building envelope. However, due to the highly dynamic nature of photovoltaic panel installation angles, shading conditions, and radiation conditions, traditional methods for predicting solar radiation from photovoltaic panels have significant errors in practical applications.

[0003] Currently used methods for predicting solar radiation from photovoltaic (PV) panels largely rely on meteorological station radiation data and calculations based on idealized uniform sky models. These methods cannot accurately reflect the actual radiation reception of PV panels under specific building scenarios. The errors are particularly significant in cases with complex obstructions (such as trees, buildings, and dynamic components) and adjustable components (such as PV louvers). The obstruction conditions of PV components and the amount of incident solar radiation received are crucial factors affecting the solar radiation received by PV panels; the aforementioned errors will impact the accuracy of solar radiation prediction. Summary of the Invention

[0004] The purpose of this disclosure is to provide a method and apparatus for predicting solar radiation from photovoltaic panels, which can solve one or more of the problems mentioned above in the prior art.

[0005] This disclosure addresses the aforementioned problems by proposing a method and apparatus for predicting solar radiation from photovoltaic panels.

[0006] To solve at least one of the above-mentioned technical problems, this disclosure proposes the following technical solution: Firstly, a method for predicting solar radiation from photovoltaic panels is provided, including the following steps: Acquire sky images and synthesize HDR images; Analyze sky radiation information based on HDR images; Establish a real-time sky model based on sky radiation information; The incident radiation on the photovoltaic panel is calculated, which includes direct solar radiation, sky diffuse radiation, and ground reflected radiation.

[0007] Secondly, a photovoltaic panel solar radiation prediction device is provided for performing any of the above-mentioned photovoltaic panel solar radiation prediction methods, the device comprising: The sky image acquisition module is used to acquire sky images and synthesize HDR images; The image analysis module is used to analyze sky radiation information based on HDR images; The sky model building module is used to build a real-time sky model based on sky radiation information. The incident radiation calculation module is used to calculate the incident radiation of the photovoltaic panel, which includes direct solar radiation, sky diffuse radiation, and ground reflected radiation.

[0008] Thirdly, a photovoltaic panel solar radiation prediction device is provided, which includes at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded by the processor and executed by any of the photovoltaic panel solar radiation prediction methods disclosed above.

[0009] Fourthly, a computer-readable storage medium is provided, which stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded by a processor and executed by any of the above-described photovoltaic panel solar radiation prediction methods of this disclosure.

[0010] The beneficial effects of this disclosure are: it enables the prediction of solar radiation from photovoltaic panels under complex shading environments; by constructing a high-resolution sky radiation field oriented towards shading, it effectively avoids the shortcomings of ideal sky models in describing the actual external environment; by fusing HDR images with real-time sky models and combining them with shading relationships, it improves the accuracy of the distribution of incident radiation on the photovoltaic panel surface in both time and space dimensions; it overcomes the power generation errors caused by traditional models ignoring heat loss or setting fixed temperatures; the prediction method has good scalability, applicable to both fixed building-integrated photovoltaic systems and active photovoltaic components with attitude adjustment capabilities; and its high-precision modeling capability for the entire sky radiation distribution, especially in identifying non-uniform sky brightness distribution under cloudy conditions, significantly improves the accuracy of radiation calculation in variable weather environments (such as cloudy, partial shadows, and thin clouds), enabling the model to have high control accuracy under different meteorological conditions such as sunny and cloudy days, and is suitable for dynamic simulation and optimization of the annual operating performance of photovoltaic systems.

[0011] Furthermore, unless otherwise specified in this disclosure, all technical solutions can be implemented using conventional methods in the field. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a method for predicting solar radiation from a photovoltaic panel, provided as an embodiment of this disclosure.

[0014] Figure 2 This is a schematic diagram of a photovoltaic panel solar radiation prediction device provided in one embodiment of the present disclosure. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0016] Example 1: Reference manual attached Figure 1 This illustration shows a method for predicting solar radiation from a photovoltaic panel according to an embodiment of the present disclosure, comprising the following steps: Step 1: Acquire sky images and synthesize HDR images; Step 2: Analyze sky radiation information based on HDR images; Step 3: Establish a real-time sky model based on sky radiation information; Step 4: Calculate the incident radiation of the photovoltaic panel. The incident radiation of the photovoltaic panel includes direct solar radiation, sky diffuse radiation, and ground reflected radiation.

[0017] In step 1, acquiring sky images and synthesizing HDR images may include the following steps: Step 1.1: Set up the sky image acquisition module. The sky image acquisition module can continuously acquire a number of low dynamic range (LDR) images according to a pre-set exposure sequence. Step 1.2: Combine the acquired LDR images into a single HDR image; Step 1.3: Determine whether the synthesized HDR image needs brightness calibration. If so, perform brightness calibration on the HDR image.

[0018] The sky image acquisition module can be configured as a high dynamic range sky image acquisition module, used to acquire the brightness distribution of the outdoor sky in real time. In an optional embodiment, the sky image acquisition module can be configured with 10... 7 With a dynamic brightness range of over 1, the sky image acquisition module can accurately capture the brightness characteristics of areas under direct sunlight and in shadow.

[0019] The sky image acquisition module can be installed within a safe area of ​​the photovoltaic panels. The sky image acquisition module can include a camera, and can also utilize a Raspberry Pi combined with a fisheye lens and an ND filter to achieve panoramic capture of the sky hemisphere.

[0020] In step 1.2, an image synthesis algorithm, such as an HDR imaging algorithm, can be used to generate a single high dynamic range (HDR) image. The synthesized HDR image can then undergo image cropping and vignetting correction. It can also identify occluded areas such as buildings, vegetation, and shading components based on the HDR image.

[0021] In step 1.3, it is determined whether the synthesized HDR image needs brightness calibration. If so, brightness calibration of the HDR image may include the following steps: A lux meter is placed in front of the camera lens or fisheye lens of the sky image module. The lux meter is used to collect the vertical illuminance value in front of the camera lens. , Extract the luminance value of each pixel from the synthesized HDR image. And calculate the vertical illuminance value of the HDR image. The calculation formula is shown in formula (1):

[0022] In the formula, This represents the vertical illuminance value of an HDR image, measured in lx. This represents the brightness value of the i-th pixel, where i is a natural number and the unit is cd / m². 2 , This represents the angle of incidence of the i-th pixel. Represents the solid angle of the i-th pixel; like If so, the synthesized HDR image is determined to require no brightness calibration; like This indicates that there is a possibility of saturation or overflow in the bright areas of the sun in the HDR image, and it is determined that the synthesized HDR image needs brightness calibration to compensate for the energy loss in the bright areas of the HDR image. Brightness calibration for HDR images includes: Based on the measured vertical illuminance value And the required brightness value of the pixel is calculated using formula (1). Soon Substituting into the left side of formula (1), the calculated brightness value is denoted as: , Based on the calculated brightness value of the pixel Adjust the HRD image to complete the brightness calibration of the HDR image. The adjusted image should meet the requirements of formula (2):

[0023] In the formula, This represents the vertical illuminance value of the HRD image after brightness calibration. The measured vertical illuminance value is used to calculate the visible light irradiance value corresponding to the HDR image using equation (3). :

[0024] In the formula, The unit is W / m 2 a and b are the fitting parameters of the total radiation in the visible light band and the vertical illuminance calculated from the HDR image. a and b can be obtained through measurement.

[0025] Therefore, without introducing additional HDR images, physical calibration of HDR images is achieved through post-image synthesis processing, thereby establishing a mapping relationship between pixel brightness values ​​and visible light irradiance.

[0026] In step 2, analyzing sky radiation information based on HDR images may include the following steps: Step 2.1: Output the total radiation in the visible light band of the HRD image. Converted to total radiation across the entire wavelength band ; Step 2.2: Decompose the total radiation across the entire band into direct radiation and diffuse radiation.

[0027] Specifically, HDR images can output total radiation in the visible light band. The total radiation in the visible light band can be extended to the full-band radiation range of 300nm to 2700nm using a visible light-full-band extension model. The visible light-full-band extension model can use a spectral fitting function or an empirical conversion factor.

[0028] Total radiation in the visible light band Total radiation across the entire band The conversion formula is as follows:

[0029] In the formula, The unit is W / m 2 c and d are the fitting parameters of the total radiation in the visible light band calculated from the total radiation in the entire band and the HDR image. c and d can be obtained by measurement.

[0030] In step 2.2, decomposing the total radiation across the entire band into direct radiation and scattered radiation may include the following steps: Extract the sun from the HDR image to obtain the sun's vertical illuminance value; Obtain the vertical illuminance value of the HDR image in front of the sun; The ratio of the sun's vertical illuminance contribution to the vertical illuminance contribution of an HDR image is equal to the ratio of direct radiation to total radiation across the entire wavelength range. Direct radiation was calculated based on the total radiation across the entire wavelength band, the solar vertical illuminance contribution, and the vertical illuminance contribution from the HDR image. The scattered radiation is calculated based on the total radiation and direct radiation across the entire wavelength band. The formulas involved are as follows:

[0031] in, Indicates the total radiation across the entire frequency band. Indicates direct radiation. Indicates scattered radiation. This represents the vertical illuminance value of the sun. This represents the vertical illuminance value of the HDR image after brightness calibration. It represents the solar zenith angle, with the unit being °, and its value is complementary to the solar altitude angle.

[0032] In step 3, a real-time sky model is established based on sky radiation information. Specifically, this may include constructing a real-time sky model based on the sky brightness distribution in the HDR image, mapping the HDR image data into several sky segments, and the number of sky segments may be 145, 580, 1305, 2320, 3625 or 5220. The real-time sky model can calculate the scattered radiation of each sky segment.

[0033] In an optional embodiment, the real-time sky model can be the Perez sky model.

[0034] Specifically, the Radiance software can be used to calculate the scattered radiation of sky segments.

[0035] In step 4, the incident radiation on the photovoltaic panel is calculated, including the following steps: Step 4.1: Calculate the direct solar radiation hitting the surface of the photovoltaic panel based on the direct radiation, the area of ​​the photovoltaic panel, and the projected area of ​​the sun on the photovoltaic panel of the obstruction. Step 4.2: Based on the real-time sky model, calculate the sky-scattered radiation of each sky segment to the photovoltaic panel, and add up the calculation results of all sky segments to obtain the sky-scattered radiation incident on the photovoltaic panel; Step 4.3: Treat the ground as a radiation source, divide the ground into several ground segments, calculate the ground reflected radiation of each ground segment to the photovoltaic panel, and add the calculation results of all ground segments to obtain the ground reflected radiation incident on the photovoltaic panel.

[0036] Since the incident radiation on a photovoltaic panel consists of three parts—direct solar radiation, sky diffuse radiation, and ground reflected radiation—the impact of obstructions on the incident radiation on the photovoltaic panel needs to be considered during calculations.

[0037] In step 4.1, the calculation method for the direct solar radiation irradiating the photovoltaic panel surface is shown in formula (7):

[0038] In the formula, This represents the angle between the solar direction vector and the normal vector of the photovoltaic panel surface. Direct radiation is represented by S, calculated in step 2.2, and the area of ​​the photovoltaic panel is in square meters (m²). 2 , The solar projection area of ​​the obstruction onto the photovoltaic panel is expressed in square meters (m²). 2 .

[0039] In step 4.2, according to the real-time sky model, the sky hemisphere is discretized into n sky segments according to the Reinhart distribution. The sky scattering radiation of each sky segment to the photovoltaic panel is calculated. The calculation formula is shown in formula (8). The sky scattering radiation of each sky segment is calculated and summed according to formula (9) to obtain the sky scattering radiation incident on the photovoltaic panel.

[0040]

[0041] In the formula, This represents the angle between the sky segment vector and the normal vector of the photovoltaic panel surface for each day. This represents the solid angle of the k-th sky segment. The scattered radiation of the k-th sky patch is calculated in step 3. Let be the projected area of ​​the photovoltaic panel on the k-th sky segment after passing through the obstruction. Let S represent the sky diffuse radiation of the k-th sky segment, and S represent the area of ​​the photovoltaic panel. This represents the sky-scattered radiation incident on the photovoltaic panel.

[0042] Therefore, the projected area of ​​each sky segment onto the photovoltaic panel after passing through the obstruction is taken as the obstruction area, thereby realizing the calculation of sky diffuse radiation.

[0043] In step 4.3, when calculating ground-reflected radiation, the ground is considered as a radiation source, and the solar modeling tool radiance gendaylit can be used for calculation. The ground is divided into several ground segments according to the Reinhart distribution. Since ground-reflected radiation can also be regarded as scattering, the calculation method of sky-scattered radiation can be referred to, and the ground is divided into m ground segments, where m can be 145, 580, 1305, 2320, 3625, or 5220. Solar radiation reflected from the ground may also be blocked by obstacles, so the calculation formula for ground-reflected radiation incident on the photovoltaic panel is shown in formulas (10) and (11).

[0044]

[0045]

[0046] In the formula, This represents the angle between each ground segment vector and the normal vector of the photovoltaic panel surface. This represents the solid angle of the e-th ground segment. Let represent the amount of scattered radiation in the e-th ground patch. The ground is considered a uniform radiation source, and the gendaylit tool of Radiance is used to calculate the scattered radiation in each patch. To account for ground reflection radiation in different directions, the ground is modeled as a hemisphere and divided into m patches. Let be the projected area of ​​the photovoltaic panel on the e-th ground segment after passing through the obstruction. This represents the ground-reflected radiation of the e-th ground segment, where S represents the area of ​​the photovoltaic panel. This represents the sky-scattered radiation incident on the photovoltaic panel.

[0047] In step 4, the calculation method for the projected area of ​​the sun, sky, or ground segments onto the photovoltaic panel after passing through obstructions may include the following steps: Suppose there exists a shading plane S and an illuminated photovoltaic panel plane F, and that the direct sunlight shines from a specific direction with direction vector r. s (ray x ray y ray z The direction vectors of the sky and ground segments are determined by the solar altitude angle and azimuth angle, and are ray ( x_patch ray y_patch ray z_patch The vertex parametric equations of the occluding plane are (S) xS y S z The vertex parametric equations of the shading plane S represent the x, y, and z coordinates of each vertex of the shading plane S. A point (x0, y0, z0) is taken on the illuminated photovoltaic panel plane to define its normal N(n). x n y n z ); Wherein, the direction vector r of direct sunlight s (ray x ray y ray z The calculation formula for ) is as follows:

[0048] In the formula, The solar altitude angle, This is the solar azimuth angle.

[0049] The direction vectors of the sky and ground segments (ray) x_patch ray y_patch ray z_patch The calculation formula for ) is as follows:

[0050] In the formula, the zenith angle range of the spherical cap sector corresponding to the sky segment or ground segment is: The azimuth range of the spherical cap sector corresponding to the sky segment or ground segment is: The zenith angle and azimuth angle ranges of the spherical cap sector can be obtained directly from the Reinhar model in the Radiance software, and are generally related to the total number of sky or ground segments (145, 580, 1305, 2320, 3625 or 5220).

[0051] The solar azimuth and solar altitude angles can be calculated using true solar time, using the following formulas:

[0052] In the formula, TST represents true solar time, the standard time is the local time, such as Beijing time UTC+8, the longitude is corrected to 4×(local longitude - central longitude of the time zone), and EOT represents the time difference, in minutes.

[0053] EOT (Early Time Over Time) is calculated using an approximate formula, as follows:

[0054] In the formula: EOT represents the time difference in minutes, B is 360° / 365(A-81), and A represents the Ath day of the year, with the value of A ranging from 1 to 365.

[0055] The solar hour angle H represents the angular position of the sun on the equator, with 0° at noon, positive in the morning, and negative in the afternoon. The formula for calculating the solar hour angle H is:

[0056] In the formula, H is the solar hour angle, and the unit is °.

[0057] The expressions for the solar altitude angle and solar azimuth angle are as follows:

[0058]

[0059] In the formula, η is the solar altitude angle, η is the local latitude, and δ is the solar declination. The values ​​represent the solar azimuth angle, all in degrees.

[0060] Methods for calculating the projected area of ​​a radiation source on a photovoltaic panel due to an obstruction include: The projection scale factor t is calculated as follows when the radiation source is the sun:

[0061] When the radiation source is a patch of sky or a patch of ground, the ray in formula (26) will be... x ray y and ray z Replace each with ray x_patch ray y_patch and ray z_patch .

[0062] Calculate the projection points of all vertices of the shading object onto the surface of the photovoltaic panel to obtain the projection polygon P′ of the shading object on the photovoltaic panel plane. When the radiation source is the sun, the calculation formula for the coordinates Y of the projection points of the vertices of the shading object onto the photovoltaic panel is shown in formula (27):

[0063] When the radiation source is a patch of sky or a patch of ground, the ray in formula (27) will be... x ray y and ray z Replace each with ray x_patch ray y_patch and ray z_patch .

[0064] The intersection Sd of the projected polygon P′ and the photovoltaic panel plane F is calculated using geometric Boolean operations, as shown in formula (28):

[0065] The area of ​​Sd is calculated as the projected area of ​​the radiation source onto the photovoltaic panel. The area of ​​Sd can also be calculated using the classic polygon area calculation method, which involves decomposing the polygon Sd into several triangles, calculating the area of ​​each triangle using the triangle area formula, and summing the areas of all triangles to obtain the area of ​​Sd. Alternatively, the area of ​​a polygon can be calculated using the shoelace formula (29), specifically: Let the vertices of a polygon Sd be, in clockwise or counterclockwise order: (a1, b1), (a2, b2), ..., (a...). q b q If the area of ​​Sd is ), then the formula for calculating the area of ​​Sd is:

[0066] The calculation of the incident radiation of the photovoltaic panel in step 4 can be performed after each HDR image synthesis, and the time interval between each HDR image capture can be set to no less than 3 minutes.

[0067] The calculation in step 4 can be applied to both fixed photovoltaic systems and dynamic component systems. Dynamic component systems can include photovoltaic louvers or tracking brackets. When the tilt angle, orientation, and real-time attitude angle of the dynamic components are adjusted, the calculation can be achieved simply by adjusting the coordinates of the plane of the obstruction and the plane of the photovoltaic panel.

[0068] Therefore, considering the actual three-dimensional spatial orientation of photovoltaic panels and complex shading environments, a geometric projection model between the photovoltaic panel and sky segments is constructed. The contribution of each sky segment to the scattered radiation on the photovoltaic panel surface is calculated block by block. Based on solar azimuth and path simulation, combined with shading image recognition results, the direct radiation incident amount is estimated. Simultaneously, ground reflection modeling is introduced, treating the ground as a secondary radiation source, to estimate its reflected scattering component to the photovoltaic panel. These three types of radiation are combined to construct an hourly incident energy spectrum for the photovoltaic panel, improving the accuracy of the temporal and spatial distribution of incident radiation on the photovoltaic panel surface.

[0069] Compared with the prior art, the technical solution provided in this disclosure has the following advantages: (1) The radiation input is real and reliable: The sky image acquisition module is used to obtain real brightness field information including the sun, sky and occlusions. Through pixel-level brightness calculation and joint calibration with illuminance sensor, a high-resolution sky radiation field oriented to occlusion is constructed, which effectively avoids the defect that the traditional ideal sky model cannot describe the actual external environment. (2) Enhanced radiation decomposition accuracy: By fusing HDR images with a real-time sky model, the incident radiation of the photovoltaic panel is accurately decomposed into three components: direct sunlight, sky scattering and ground reflection. Combined with the three-dimensional orientation and shading relationship of the components, the accuracy of the distribution of incident radiation on the photovoltaic panel surface in time and space is improved. (3) Support for dynamic prediction and control: The system supports hourly image input and dynamic update of component posture, which is suitable for power generation prediction and strategy optimization in scenarios with rapid changes in sunlight or dynamic shading systems.

[0070] Example 2: This disclosure also provides a photovoltaic panel solar radiation prediction device for performing any of the aforementioned photovoltaic panel solar radiation prediction methods, including... Sky image acquisition module 11 is used to acquire sky images and synthesize HDR images; Image analysis module 12 is used to analyze sky radiation information based on HDR images; Sky model building module 13 is used to build a real-time sky model based on sky radiation information; The incident radiation calculation module 14 is used to calculate the incident radiation of the photovoltaic panel, which includes direct solar radiation, sky diffuse radiation and ground reflected radiation.

[0071] The beneficial effects of this disclosure are: it enables the prediction of solar radiation from photovoltaic panels under complex shading environments; by constructing a high-resolution sky radiation field oriented towards shading, it effectively avoids the shortcomings of ideal sky models in describing the actual external environment; by fusing HDR images with real-time sky models and combining them with shading relationships, it improves the accuracy of the distribution of incident radiation on the surface of photovoltaic panels in the temporal and spatial dimensions; it overcomes the power generation errors caused by traditional models ignoring heat loss or setting fixed temperatures; and the prediction method has good scalability, applicable to both fixed building-integrated photovoltaic systems and active photovoltaic components with attitude adjustment capabilities.

[0072] The apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0073] Example 3: This disclosure provides a photovoltaic panel solar radiation prediction device, which includes: One or more processors and memory.

[0074] The photovoltaic panel solar radiation prediction equipment may also include: an input device and an output device.

[0075] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to a photovoltaic panel solar radiation prediction method in this embodiment of the present disclosure. The processor executes various server functions and data processing by running the non-volatile software programs, instructions, and modules stored in the memory, thereby implementing the photovoltaic panel solar radiation prediction method described in the above embodiment.

[0076] The memory may include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of a photovoltaic panel solar radiation prediction device, etc. Furthermore, the memory may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to a photovoltaic panel solar radiation prediction device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0077] The input device can receive input digital or character information, and generate signal inputs related to user settings and function control. The output device may include display devices such as a display screen.

[0078] One or more modules reside in memory and, when executed by one or more processors, perform a photovoltaic panel solar radiation prediction method in any of the above method embodiments.

[0079] The aforementioned photovoltaic panel solar radiation prediction device can execute the method provided in the embodiments of this disclosure, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in the method provided in the embodiments of this disclosure.

[0080] Example 4: On the other hand, Embodiment 4 of this disclosure provides a computer-readable storage medium storing one or more programs including execution instructions. The execution instructions can be read and executed by a device (including but not limited to a computer, server, or network device) to perform the relevant steps in the above method embodiments.

[0081] The embodiments described above are merely illustrative. The units or modules described as separate components may or may not be physically separate. Components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0082] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the prior art, can be expressed in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit them. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure.

Claims

1. A method for predicting solar radiation from photovoltaic panels, characterized in that, Includes the following steps: Acquire sky images and synthesize HDR images; Analyze sky radiation information based on HDR images; Establish a real-time sky model based on sky radiation information; The incident radiation on the photovoltaic panel is calculated, which includes direct solar radiation, sky diffuse radiation, and ground reflected radiation.

2. The method for predicting solar radiation from a photovoltaic panel according to claim 1, characterized in that, Acquiring sky images and synthesizing HDR images includes: A sky image acquisition module is provided, which can continuously acquire several LDR images according to a preset exposure sequence; Several acquired LDR images are combined into a single HDR image; Determine whether the synthesized HDR image needs brightness calibration; if so, perform brightness calibration on the HDR image. Specifically, determining whether the synthesized HDR image needs brightness calibration, and if so, performing brightness calibration on the HDR image includes: A lux meter is placed in front of the camera lens of the sky image module. The lux meter is used to collect the vertical illuminance value in front of the camera lens. , Extract the luminance value of each pixel from the synthesized HDR image. And calculate the vertical illuminance value of the HDR image. ; like If so, the synthesized HDR image is determined to require brightness calibration; Brightness calibration for HDR images includes: Based on the measured vertical illuminance value Calculate the brightness value required for the pixel , Based on the calculated brightness value of the pixel Adjust the HRD image to complete the brightness calibration of the HDR image.

3. The method for predicting solar radiation from a photovoltaic panel according to claim 1, characterized in that, Analysis of sky radiation information based on HDR images includes: Output the total radiation in the visible light band of the HRD image. Converted to total radiation across the entire wavelength band ; The total radiation across the entire spectrum is decomposed into direct radiation and diffuse radiation.

4. The method for predicting solar radiation from a photovoltaic panel according to claim 3, characterized in that, The total radiation across the entire wavelength band is decomposed into direct radiation and scattered radiation, including: Extract the sun from the HDR image to obtain the sun's vertical illuminance contribution value; Obtain the vertical illuminance contribution value of the extracted HDR image in front of the sun; The ratio of the sun's vertical illuminance contribution to the vertical illuminance contribution of an HDR image is equal to the ratio of direct radiation to total radiation across the entire wavelength range. Direct radiation was calculated based on the total radiation across the entire wavelength band, the solar vertical illuminance contribution, and the vertical illuminance contribution from the HDR image. The scattered radiation is calculated based on the total radiation and direct radiation across the entire wavelength band.

5. The method for predicting solar radiation from a photovoltaic panel according to claim 4, characterized in that, The calculation of incident radiation on a photovoltaic panel includes: Calculate the direct solar radiation hitting the surface of the photovoltaic panel based on the direct radiation, the area of ​​the photovoltaic panel, and the projected area of ​​the sun on the photovoltaic panel of the obstruction. Based on the real-time sky model, the sky is divided into segments, and the sky-scattered radiation of each sky segment to the photovoltaic panel is calculated. The calculation results of all sky segments are added together to obtain the sky-scattered radiation incident on the photovoltaic panel. The ground is considered as a radiation source. The ground is divided into several ground segments. The ground reflected radiation of each ground segment to the photovoltaic panel is calculated separately. The calculation results of all ground segments are added together to obtain the ground reflected radiation incident on the photovoltaic panel.

6. The method for predicting solar radiation from a photovoltaic panel according to claim 5, characterized in that, Methods for calculating the projected area of ​​a radiation source on a photovoltaic panel due to an obstruction include: Calculate the projection scaling factor of the obstruction onto the photovoltaic panel; Calculate the projection points of all vertices of the obstruction onto the surface of the photovoltaic panel to obtain the projected polygon of the obstruction on the plane of the photovoltaic panel; Calculate the intersection Sd of the projected polygon and the photovoltaic panel; The area of ​​Sd is calculated as the projected area of ​​the radiation source onto the photovoltaic panel, representing the area of ​​the obstruction.

7. A photovoltaic panel solar radiation prediction device, used to execute the photovoltaic panel solar radiation prediction method according to any one of claims 1-6, characterized in that, include: The sky image acquisition module is used to acquire sky images and synthesize HDR images; The image analysis module is used to analyze sky radiation information based on HDR images; The sky model building module is used to build a real-time sky model based on sky radiation information. The incident radiation calculation module is used to calculate the incident radiation of the photovoltaic panel, which includes direct solar radiation, sky diffuse radiation, and ground reflected radiation.

8. A photovoltaic panel solar radiation prediction device, characterized in that, The photovoltaic panel solar radiation prediction device includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the photovoltaic panel solar radiation prediction method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or instruction set is loaded and executed by a processor to implement the photovoltaic panel solar radiation prediction method according to any one of claims 1-6.

Images