A method and device for predicting solar radiation for a photovoltaic panel

Abstract

The present disclosure provides a photovoltaic panel solar radiation prediction method and device, the method comprising collecting sky images and synthesizing HDR images; analyzing sky radiation information according to the HDR images; establishing a real-time sky model according to the sky radiation information; and calculating the incident radiation of the photovoltaic panel, which includes direct solar radiation, sky scattered radiation and ground reflected radiation. The photovoltaic panel solar radiation prediction method and device provided by the present disclosure realize the prediction of the photovoltaic panel solar radiation in a complex shielding environment, effectively avoid the defect that the ideal sky model cannot describe the actual external environment by constructing a high-resolution sky radiation field facing the shielding; and improve the distribution accuracy of the photovoltaic panel surface incident radiation in the time and space dimensions by fusing the HDR images and the real-time sky model and combining the shielding relationship.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of photovoltaic power generation, and particularly relates to a photovoltaic panel solar radiation amount prediction method and device. BACKGROUND

[0002] Photovoltaic power generation systems have been widely applied in many fields such as buildings, transportation, agriculture, etc., for realizing clean energy supply. Among them, building integrated photovoltaics (BIPV) is an important photovoltaic application form in recent years, and the components thereof are not only used for power generation, but also have functions such as sun-shading and enclosure. Due to the high dynamicity of the installation angle, shielding condition and radiation condition of the photovoltaic panel, the error of the traditional photovoltaic panel solar radiation amount prediction method is large in actual application.

[0003] The currently commonly used photovoltaic panel solar radiation amount prediction method mainly depends on the radiation data of a weather station and the calculation of an idealized uniform sky model, and cannot accurately reflect the real irradiation receiving condition of the photovoltaic panel under a specific building scene. Especially in the case of complex shielding (such as trees, buildings, dynamic components) and adjustable components (such as photovoltaic louvers), the error is significant. The shielding condition and the received incident solar radiation amount of the photovoltaic component are important factors affecting the solar radiation amount of the photovoltaic panel, and the above error will affect the accurate prediction of the solar radiation amount of the photovoltaic panel. SUMMARY

[0004] The purpose of the present disclosure is to provide a photovoltaic panel solar radiation amount prediction method and device, which can solve one or more of the above technical problems.

[0005] The present disclosure proposes a photovoltaic panel solar radiation amount prediction method and device to solve the above problems.

[0006] In order to solve at least one of the above technical problems, the present disclosure proposes the following technical solutions:

[0007] In a first aspect, a photovoltaic panel solar radiation amount prediction method is provided, comprising the following steps:

[0008] Collecting a sky image and synthesizing an HDR image;

[0009] Analyzing sky radiation information according to the HDR image;

[0010] Establishing a real-time sky model according to the sky radiation information;

[0011] Calculating the incident radiation amount of the photovoltaic panel, which includes direct solar radiation, sky scattered radiation and ground reflected radiation.

[0012] In a second aspect, a photovoltaic panel solar radiation prediction device is provided for performing any one of the photovoltaic panel solar radiation prediction methods described above, and the device comprises:

[0013] a sky image acquisition module configured to acquire sky images and synthesize HDR images;

[0014] an image analysis module configured to analyze sky radiation information based on the HDR images;

[0015] a sky model establishment module configured to establish a real-time sky model based on the sky radiation information;

[0016] an incident radiation amount calculation module configured to calculate the incident radiation amount of the photovoltaic panel, wherein the incident radiation amount of the photovoltaic panel includes direct solar radiation, sky scattered radiation, and ground reflected radiation.

[0017] In a third aspect, a photovoltaic panel solar radiation prediction apparatus is provided, and the photovoltaic panel solar radiation prediction apparatus comprises 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, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to perform any one of the photovoltaic panel solar radiation prediction methods described above.

[0018] In a fourth aspect, a computer-readable storage medium is provided, and the computer-readable storage medium stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to perform any one of the photovoltaic panel solar radiation prediction methods described above.

[0019] The present disclosure has the beneficial effect of realizing the prediction of the photovoltaic panel solar radiation in a complex occlusion environment, effectively avoiding the defect that the ideal sky model cannot describe the actual external environment by constructing a high-resolution sky radiation field facing the occlusion; the distribution accuracy of the photovoltaic panel surface incident radiation in the time and space dimensions is improved by fusing the HDR image and the real-time sky model and combining the occlusion relationship; the power generation error caused by the traditional model ignoring the heat loss or the fixed temperature setting is overcome; the prediction method has good expansibility and can be applied to both the fixed building integrated photovoltaic system and the active photovoltaic component with attitude adjustment capability; at the same time, the high-precision modeling capability of the full-sky radiation distribution, especially the ability to identify the non-uniform sky brightness distribution under overcast conditions, significantly improves the radiation calculation accuracy in variable weather conditions (such as overcast, local shadow, and thin cloud), so that the model has high control precision in different meteorological conditions such as sunny and overcast days, and is suitable for dynamic simulation and optimization of the annual operation performance of the photovoltaic system.

[0020] In addition, in the technical solutions of the present disclosure, any unmentioned part can be realized by using conventional means in the field. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0022] Figure 1 A flow chart of a photovoltaic panel solar radiation amount prediction method provided by an embodiment of the present disclosure.

[0023] Figure 2 A structural schematic diagram of a photovoltaic panel solar radiation amount prediction device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be described clearly and completely in the following with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some embodiments of the present disclosure, but not all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present disclosure.

[0025] Embodiment 1:

[0026] With reference to the drawings in the specification, Figure 1 , a photovoltaic panel solar radiation amount prediction method provided by an embodiment of the present disclosure is shown, which includes the following steps:

[0027] Step 1: Collecting sky images and synthesizing HDR images;

[0028] Step 2: Analyzing sky radiation information according to the HDR images;

[0029] Step 3: Establishing a real-time sky model according to the sky radiation information;

[0030] Step 4: Calculating the incident radiation amount of the photovoltaic panel, which includes the direct solar radiation, sky scattered radiation and ground reflected radiation.

[0031] In step 1, collecting sky images and synthesizing HDR images can include the following steps:

[0032] Step 1.1: Set up a sky image acquisition module, which can continuously acquire a plurality of low dynamic range (LDR) images according to a pre-set exposure sequence;

[0033] Step 1.2: Synthesize the plurality of acquired LDR images into a single HDR image;

[0034] Step 1.3: Determine whether the synthesized HDR image needs to be calibrated for brightness, and if so, calibrate the HDR image for brightness.

[0035] The sky image acquisition module can be set as a high dynamic range sky image acquisition module, which is used to obtain the brightness distribution of the outdoor sky in real time. In an optional embodiment, the sky image acquisition module can be configured to have a dynamic brightness range of 10 7 :1 or more, so that the sky image acquisition module can accurately capture the brightness characteristics of the direct sunlight and the shadow area.

[0036] The sky image acquisition module can be set in the safe area of the photovoltaic panel. The sky image acquisition module can include a camera, and the sky image acquisition module can also use a Raspberry Pi combined with a fisheye lens and an ND light reduction lens to complete panoramic shooting of the sky hemisphere.

[0037] 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 be processed for image range clipping and image vignetting calibration. The HDR image can be used to identify buildings, vegetation, shading components, and other shaded areas.

[0038] In step 1.3, determining whether the synthesized HDR image needs to be calibrated for brightness, and if so, calibrating the HDR image for brightness can include the following steps:

[0039] Setting an illuminometer in front of the camera lens or fisheye lens of the sky image module, the illuminometer being used to acquire the vertical illuminance value in front of the camera lens ,

[0040] Extracting the brightness value of each pixel from the synthesized HDR image , and calculating the vertical illuminance value of the HDR image , the calculation formula being shown as formula (1):

[0041]

[0042] In the formula, represents the vertical illuminance value of the HDR image, with units of lx, represents the brightness value of the i-th pixel, i being a natural number, with units of cd / m 2 , denotes the incident angle of the i-th pixel, denotes the solid angle of the i-th pixel;

[0043] If , it is determined that the synthesized HDR image does not need to be subjected to luminance calibration;

[0044] If , it indicates that there is a possibility of saturation or overflow in the highlight area of the sun in the HDR image, and it is determined that the synthesized HDR image needs to be subjected to luminance calibration to compensate for the energy loss in the highlight area of the HDR image;

[0045] The luminance calibration of the HDR image comprises:

[0046] According to the measured vertical illuminance value and the luminance value required by the pixel is inversely calculated according to formula (1) , that is, substituting into the left side of formula (1), the calculated luminance value is denoted as ,

[0047] According to the calculated luminance value required by the pixel , the HRD image is adjusted to complete the luminance calibration of the HDR image, and the adjusted image should satisfy formula (2):

[0048]

[0049] In the formula, denotes the vertical illuminance value of the HRD image after luminance calibration, denotes the measured vertical illuminance value, and the corresponding visible light irradiance value of the HDR image is obtained by using formula (3) :

[0050]

[0051] In the formula, unit: W / m 2 , and a and b are fitting parameter values of the total radiation of the visible light band and the calculated vertical illuminance of the HDR image, and a and b can be obtained by measurement.

[0052] Therefore, without introducing additional HDR images, the physical calibration of the HDR image is realized through the processing after the image synthesis, and then the mapping relationship between the pixel luminance value and the visible light band irradiance is established.

[0053] In step 2, the sky radiation information can be analyzed according to the HDR image, which can comprise the following steps:

[0054] Step 2.1: Output the total radiation of the HRD image in the visible light band , the total radiance in the full waveband is converted ;

[0055] Step 2.2: the total radiance in the full waveband is decomposed into direct radiance and diffuse radiance.

[0056] Specifically, the HDR image can output the total radiance in the visible light waveband The total radiance in the visible light waveband can be extended to the total radiance in the full waveband ranging from 300nm to 2700nm through a visible light-full waveband extension model. The visible light-full waveband extension model can select a spectral fitting function or an empirical conversion factor.

[0057] The total radiance in the visible light waveband and the conversion formula of the total radiance in the full waveband is as follows:

[0058]

[0059] In the formula, The unit of is W / m 2 , and c and d are fitting parameter values of the total radiance in the full waveband and the total radiance in the visible light waveband calculated by the HDR image, and c and d can be obtained through measurement.

[0060] In step 2.2, decomposing the total radiance in the full waveband into direct radiance and diffuse radiance can include the following steps:

[0061] The sun is extracted from the HDR image to obtain the vertical illuminance value of the sun;

[0062] The vertical illuminance value of the HDR image before the sun is extracted is obtained;

[0063] The ratio of the vertical illuminance contribution value of the sun and the vertical illuminance contribution value of the HDR image is equal to the ratio of the direct radiance and the total radiance in the full waveband,

[0064] The direct radiance is calculated according to the total radiance in the full waveband, the vertical illuminance contribution value of the sun and the vertical illuminance contribution value of the HDR image,

[0065] The diffuse radiance is calculated according to the total radiance in the full waveband and the direct radiance;

[0066] The formula involved is as follows:

[0067]

[0068] In the formula, represents the total radiance in the full waveband, represents the direct radiance, represents the diffuse radiance, represents the vertical illuminance value of the sun, a vertical illuminance value of the HDR image after luminance calibration, represents the solar zenith angle, in °, whose value is complementary to the solar altitude angle.

[0069] In step 3, the real-time sky model is established according to the sky radiation information, which can specifically include: constructing a real-time sky model according to the sky luminance distribution in the HDR image, mapping the HDR image data to a plurality of sky patches, the number of sky patches can be 145, 580, 1305, 2320, 3625 or 5220, and the real-time sky model can calculate the scattering radiation of each sky patch.

[0070] In an optional embodiment, the real-time sky model can be a Perez sky model.

[0071] Specifically, the calculation of the scattering radiation of the sky patch can be realized by using Radiance software.

[0072] In step 4, the incident radiation amount of the photovoltaic panel is calculated, including the following steps:

[0073] Step 4.1: calculating the solar direct radiation irradiating the surface of the photovoltaic panel according to the direct radiation, the area of the photovoltaic panel and the projection area of the sun on the photovoltaic panel.

[0074] Step 4.2: calculating the sky scattering radiation of each sky patch to the photovoltaic panel according to the real-time sky model, and adding the calculation results of all sky patches to obtain the sky scattering radiation incident on the photovoltaic panel.

[0075] Step 4.3: dividing the ground into a plurality of ground patches, calculating the ground reflection radiation of each ground patch to the photovoltaic panel, and adding the calculation results of all ground patches to obtain the ground reflection radiation incident on the photovoltaic panel.

[0076] Since the incident radiation amount of the photovoltaic panel is composed of three parts of radiation, namely the solar direct radiation, the sky scattering radiation and the ground reflection radiation, when calculating, the influence of the shelter on the incident radiation amount of the photovoltaic panel needs to be considered.

[0077] In step 4.1, the calculation method of the solar direct radiation irradiating the surface of the photovoltaic panel is shown in formula (7):

[0078]

[0079] In the formula, represents the included angle between the solar direction vector and the normal vector of the photovoltaic panel surface, represents the direct radiation, which is calculated by step 2.2, S represents the area of the photovoltaic panel, and the unit is m 2 , A is the projected area of the sun on the PV panel through the obstruction, unit is m 2 .

[0080] In step 4.2, according to the real-time sky model, the sky hemisphere is discretized into n sky patches according to the Reinhart distribution, and the sky scattered radiation of each sky patch to the PV panel is calculated respectively, and the calculation formula is shown as formula (8), and the sky scattered radiation of each sky patch calculated is summed according to formula (9) to obtain the sky scattered radiation incident on the PV panel.

[0081]

[0082] In the formula, indicates the included angle between each sky patch vector and the surface normal vector of the PV panel, indicates the solid angle of the kth sky patch, indicates the scattered radiation of the kth sky patch, which is calculated by step 3, is the projected area of the kth sky patch on the PV panel through the obstruction, indicates the sky scattered radiation of the kth sky patch, and S indicates the area of the PV panel, indicates the sky scattered radiation incident on the PV panel.

[0083] Therefore, the projected area of each sky patch on the PV panel through the obstruction is taken as the obstruction area, and the calculation of the sky scattered radiation is further realized.

[0084] In step 4.3, when calculating the ground reflected radiation, the ground is regarded as a radiation source, and the sunlight modeling tool radiance gendaylit can be used for calculation. The ground is divided into several ground patches according to the Reinhart distribution, and since the ground reflected radiation can also be regarded as scattering, the ground can be divided into m ground patches, and m can be 145, 580, 1305, 2320, 3625 or 5220. The solar radiation reflected from the ground can also be blocked by the obstacle, so the calculation formula of the ground reflected radiation incident on the PV panel is shown as formula (10) and formula (11).

[0085]

[0086]

[0087] In the formula, indicates the included angle between each ground patch vector and the surface normal vector of the PV panel, indicates the solid angle of the e-th ground patch, The amount of scattered radiation of the e-th ground patch, the ground is regarded as a uniform radiation source, and the amount of scattered radiation of the ground patch is calculated by using the gendaylit tool of Radiance. In order to consider the ground reflected radiation in different directions, the ground is modeled as a hemisphere, and m ground patches are divided, The projection area of the e-th ground patch on the photovoltaic panel through the shelter, The ground reflected radiation of the e-th ground patch, S represents the area of the photovoltaic panel, The sky scattered radiation incident on the photovoltaic panel.

[0088] In the calculation of step 4, the calculation method of the projection area of the sun, sky patch or ground patch on the photovoltaic panel through the shelter can include the following steps:

[0089] Suppose there is a shelter plane S and a photovoltaic panel plane F illuminated, suppose the sun direct light comes from a certain direction, and its direction vector is r s (ray x , ray y , ray z ) determined by the solar elevation angle and the azimuth angle, the direction vectors of the sky patch and the ground patch are (ray x_patch , ray y_patch , ray z_patch );The parametric equation of the vertex of the shelter plane is (S x , S y , S z ), wherein the parametric equation of the vertex of the shelter plane represents the xyz coordinates of each vertex of the shelter plane S, and a point (x0, y0, z0) is taken on the illuminated photovoltaic panel plane to define its normal N (n x , n y , n z );

[0090] Wherein, the direction vector r s (ray x , ray y , ray z ) of the sun direct light is calculated as follows

[0091]

[0092] In the formula, is the solar elevation angle, is the solar azimuth angle.

[0093] The calculation formula of the direction vector (ray x_patch , ray y_patch , ray z_patch ) of the sky patch and the ground patch is as follows:

[0094]

[0095] where the zenith angle range of the corresponding spherical cap sector of the sky patch or ground patch is and the azimuth angle range of the corresponding spherical cap sector of the sky patch or ground patch is The zenith angle range and the azimuth angle range can be directly obtained from Reinhar model of radiance software, which is generally related to the total number of sky patches or ground patches (145, 580, 1305, 2320, 3625 or 5220).

[0096] The solar azimuth angle and the solar altitude angle can be calculated by using true solar time, and the calculation formula is as follows:

[0097]

[0098] where TST represents true solar time, the standard time is local time, for example, Beijing time UTC+8, the longitude correction is 4x (local longitude - central longitude of time zone), and EOT represents time difference, in minutes.

[0099] The time difference EOT is calculated by using an approximate formula, and the formula is as follows:

[0100]

[0101] where EOT represents time difference, in minutes, B is 360° / 365 (A-81), A represents the A-th day of the year, and the value range of A is 1-365.

[0102] The solar hour angle H represents the angular position of the sun on the equator, and the noon is 0°, the morning is positive, and the afternoon is negative. The calculation formula of the solar hour angle H is as follows:

[0103]

[0104] where H is the solar hour angle, in °.

[0105] Then the expression of the solar altitude angle and the solar azimuth angle is as follows:

[0106]

[0107]

[0108] where is the solar altitude angle, η is the local latitude, δ is the solar declination, is the solar azimuth angle, all in °.

[0109] The method for calculating the projection area of the radiation source on the photovoltaic panel includes:

[0110] The projection ratio coefficient t is calculated, and when the radiation source is the sun, the formula (26) is shown as follows:

[0111]

[0112] When the radiation source is the sky segment or the ground segment, ray x , ray y and ray z in the formula (26) are respectively replaced by ray x_patch , ray y_patch and ray z_patch .

[0113] The projection points of all the vertices of the shelter on the photovoltaic panel surface are calculated to obtain the projection polygon P' of the shelter on the photovoltaic panel plane, and when the radiation source is the sun, the formula for calculating the projection point coordinates Y of the shelter vertices on the photovoltaic panel is shown in the formula (27):

[0114]

[0115] When the radiation source is the sky segment or the ground segment, ray x , ray y and ray z in the formula (27) are respectively replaced by ray x_patch , ray y_patch and ray z_patch .

[0116] The intersection Sd of the projection polygon P' and the photovoltaic panel plane F is calculated by the geometric Boolean operation, and the formula (28) is shown as follows:

[0117]

[0118] The area of Sd is calculated, which is the projection area of the radiation source on the photovoltaic panel. The area of Sd can also be calculated according to the classical polygon area calculation method, that is, the polygon Sd is disassembled into several triangles, the area of each triangle is calculated according to the triangle area formula, and the sum of the areas of all the triangles is obtained, which is the area of Sd. The shoelace formula (29) can also be used to calculate the polygon area, and specifically, the vertices of a polygon Sd are sequentially (a1, b1), (a2, b2), …, (a q , b q ) in clockwise or counterclockwise order, and the area calculation formula of Sd is as follows:

[0119]

[0120] The incident radiation amount of the calculated photovoltaic panel of step 4 can be performed after each HDR image synthesis, and the time interval for shooting the HDR image can be set to be not less than 3 minutes.

[0121] The calculation of step 4 can be applied to fixed photovoltaic systems and dynamic component systems, which can include photovoltaic louvers or tracking supports. When the inclination, orientation and real-time attitude angle of the dynamic component are adjusted, only the coordinates of the shelter plane and the photovoltaic panel plane need to be adjusted to realize the calculation.

[0122] Therefore, for the three-dimensional space orientation of the actual photovoltaic panel and the complex shelter environment, a geometric projection model between the photovoltaic panel and the sky patch is constructed, and the scattering radiation contribution of each sky patch to the surface of the photovoltaic panel is calculated block by block; based on the simulation of the sun azimuth and path, combined with the identification result of the shelter image, the incident amount of direct radiation is estimated; at the same time, the ground reflection modeling is introduced, and the ground is regarded as a secondary source of radiation, and the incident scattering component contributed by the ground reflection to the photovoltaic panel is estimated. The three types of radiation comprehensively constitute the hourly incident energy spectrum of the photovoltaic panel, and the distribution accuracy of the incident radiation on the surface of the photovoltaic panel in the time and space dimensions is improved.

[0123] The technical scheme provided by the present disclosure has the following beneficial effects compared with the prior art:

[0124] (1) Real and reliable radiation input: the real brightness field information containing the sun, sky and shelter is obtained by using the sky image acquisition module, the high-resolution sky radiation field facing the shelter is constructed through pixel-level brightness calculation and illumination sensor joint calibration, and the defects that the traditional ideal sky model cannot describe the actual external environment are effectively avoided;

[0125] (2) Enhance the accuracy of radiation decomposition: through the fusion of HDR image and real-time sky model, the incident radiation amount of the photovoltaic panel is accurately decomposed into three components of solar direct radiation, sky scattering and ground reflection, and the distribution accuracy of the incident radiation on the surface of the photovoltaic panel in the time and space dimensions is improved combined with the three-dimensional attitude of the component and the shelter relationship;

[0126] (3) Support dynamic prediction and control: the system supports hourly image input and dynamic update of component attitude, and is suitable for power generation prediction and strategy optimization in the scene of rapid change of sunlight or dynamic sunshade system.

[0127] Embodiment 2:

[0128] The present disclosure also provides a photovoltaic panel solar radiation amount prediction device for executing any one of the aforementioned photovoltaic panel solar radiation amount prediction methods, comprising,

[0129] The sky image acquisition module 11 is used for acquiring sky images and synthesizing HDR images;

[0130] The image analysis module 12 is configured to analyze sky radiation information according to the HDR image.

[0131] The sky model establishing module 13 is configured to establish a real-time sky model according to the sky radiation information.

[0132] The incident radiation amount calculation module 14 is configured to calculate the incident radiation amount of the photovoltaic panel, which includes the direct solar radiation, the sky scattered radiation and the ground reflected radiation.

[0133] The photovoltaic panel solar radiation amount prediction method provided by the present disclosure has the advantages that the photovoltaic panel solar radiation amount in a complex shielding environment is predicted, 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, the distribution accuracy of the photovoltaic panel surface incident radiation in the time and space dimensions is improved by fusing the HDR image and the real-time sky model and combining the shielding relationship, and the power generation error caused by the traditional model ignoring the heat loss or the fixed temperature setting is overcome. The prediction method has good expansibility and can be applied to both the fixed building-integrated photovoltaic system and the active photovoltaic component with the posture adjustment capability.

[0134] The device provided in the above embodiment is only taken as an example in the implementation of the functions thereof, and in actual application, the above functions can be completed by different functional modules according to the needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions. In addition, the device and the method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described here.

[0135] Embodiment 3

[0136] The present disclosure provides a photovoltaic panel solar radiation amount prediction device, which comprises:

[0137] one or more processors and a memory.

[0138] The photovoltaic panel solar radiation amount prediction device can further comprise an input device and an output device.

[0139] The memory is a non-volatile computer readable storage medium, which can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to a photovoltaic panel solar radiation amount prediction method in the embodiments of the present disclosure. The processor executes various function applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory, that is, implements a photovoltaic panel solar radiation amount prediction method in the above method embodiments.

[0140] The memory can include a program storage area and a data storage area. The program storage area can store an operating system and applications required by at least one function. The data storage area can store data created according to use of a photovoltaic panel solar radiation amount prediction device, and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory such as at least one disk storage device, a flash memory device, or other non-volatile solid state memory device. In some embodiments, the memory can optionally include memory that is remotely located with respect to the processor, and these remote memories can be connected to a photovoltaic panel solar radiation amount prediction device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0141] The input device can receive inputted digital or character information, and generate signal input related to user settings and function control. The output device can include a display device such as a display screen.

[0142] One or more modules are in the memory, and when executed by one or more processors, perform a photovoltaic panel solar radiation amount prediction method of any of the above method embodiments.

[0143] The photovoltaic panel solar radiation amount prediction device described above can perform the method provided by the embodiments of the present disclosure, and has the corresponding function modules and beneficial effects of performing the method. Technical details not described in detail in the embodiments can refer to the method provided by the embodiments of the present disclosure.

[0144] Embodiment 4:

[0145] In another aspect, the embodiment 4 of the present disclosure provides a computer readable storage medium, and the storage medium stores 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, a server, or a network device, etc.) to perform the related steps in the above method embodiments.

[0146] The above-described embodiments are merely illustrative for the present disclosure and the units or modules illustrated as separate parts can or can not be physically separate, and the parts illustrated as units can or can not be physical units and can be located in one place or distributed on multiple network units. Some or all of the modules can be selected to achieve the purpose of the embodiments according to actual needs. Those of ordinary skill in the art can understand and implement without creative labor.

[0147] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and the necessary general hardware platform from the above description of the embodiments, and of course, the embodiments can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (possibly a personal computer, a server, or a network device, etc.) execute the methods of the various embodiments or some parts of the embodiments.

[0148] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present disclosure, and not to limit them; although the present disclosure has been described in detail with reference to the foregoing examples, those of ordinary skill in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for some of the technical features; and these modifications or replacements do not make the corresponding technical solutions essentially depart from the spirit and scope of the technical solutions of the various embodiments of the present disclosure.

Claims

1. A method for predicting the solar radiation amount of a photovoltaic panel, characterized in that, The method comprises the following steps: collecting sky images and synthesizing HDR images; analyzing sky radiation information according to the HDR images; establishing a real-time sky model according to the sky radiation information; calculating the incident radiation of the photovoltaic panel, which includes direct solar radiation, sky scattered radiation and ground reflected radiation; The calculation of the incident radiation of the photovoltaic panel includes: According to the direct radiation, the area of the photovoltaic panel and the projection area of the sun on the shelter on the photovoltaic panel, the direct solar radiation irradiating the surface of the photovoltaic panel is calculated. According to the real-time sky model, the sky is divided into pieces, and the sky scattered radiation of each sky piece to the photovoltaic panel is calculated respectively, and the calculation results of all sky pieces are added to obtain the sky scattered radiation incident on the photovoltaic panel. The ground is regarded as a radiation source, and the ground is divided into several ground pieces, and the ground reflected radiation of each ground piece to the photovoltaic panel is calculated respectively, and the calculation results of all ground pieces are added to obtain the ground reflected radiation incident on the photovoltaic panel. The projection area of each sky piece on the photovoltaic panel through the shelter is taken as the shelter area, and the calculation of the sky scattered radiation is realized. The calculation formula of the ground reflected radiation incident on the photovoltaic panel is as follows, wherein, denotes the angle between each ground patch vector and the surface normal vector of the photovoltaic panel, denotes the solid angle of the e-th ground patch, denotes the scattered radiation of the e-th ground patch, the ground is considered as a uniform radiation source and the scattered radiation of the ground patch is calculated; the ground is modeled as a hemisphere and divided into m ground patches, is the projected area of the e-th ground patch on the photovoltaic panel through the occluder, denotes the ground reflected radiation of the e-th ground patch, S denotes the area of the photovoltaic panel, denotes the sky scattered radiation incident on the photovoltaic panel.

2. The photovoltaic panel solar radiation prediction method according to claim 1, characterized in that, collecting sky images and synthesizing HDR images comprises: setting a sky image collection module, which can continuously collect a plurality of LDR images according to a pre-set exposure sequence; synthesizing the collected LDR images into a single HDR image; determining whether the synthesized HDR image needs to be calibrated in brightness, and if so, calibrating the HDR image in brightness; wherein determining whether the synthesized HDR image needs to be calibrated in brightness, and if so, calibrating the HDR image in brightness comprises: providing a light meter in front of the camera lens of the sky image module, the light meter configured to capture a vertical illuminance value in front of the camera lens , extracting a luminance value for each pixel from the synthesized HDR image and calculating a vertical illuminance value for the HDR image ; If then it is determined that the synthesized HDR image needs luminance calibration; calibrating the HDR image in brightness comprises: According to the measured vertical illuminance value The luminance value required for calculating the pixel , According to the calculated required luminance value of the pixel The adjustment of the HRD image is completed, and the luminance calibration of the HDR image is completed.

3. The photovoltaic panel solar radiation prediction method according to claim 1, characterized in that, analyzing sky radiation information according to the HDR images comprises: Outputting the total radiation of the HRD image in the visible light band , converting into the total radiation of the full band ; decomposing the total radiation of the full waveband into direct radiation and scattered radiation.

4. The photovoltaic panel solar radiation prediction method according to claim 3, characterized in that, decomposing the total radiation of the full waveband into direct radiation and scattered radiation comprises: extracting the sun from the HDR image to obtain the vertical illuminance contribution value of the sun; obtaining the vertical illuminance contribution value of the HDR image before the sun is extracted; the ratio of the vertical illuminance contribution value of the sun to the vertical illuminance contribution value of the HDR image is equal to the ratio of the direct radiation to the total radiation of the full waveband, calculating the direct radiation according to the total radiation of the full waveband, the vertical illuminance contribution value of the sun and the vertical illuminance contribution value of the HDR image, calculating the scattered radiation according to the total radiation of the full waveband and the direct radiation.

5. The photovoltaic panel solar radiation prediction method according to claim 1, characterized in that, the method for calculating the projection area of the radiation source on the photovoltaic panel on the shelter comprises: calculating the projection proportion coefficient of the shelter on the photovoltaic panel; calculating the projection points of all vertices of the shelter on the surface of the photovoltaic panel to obtain the projection polygon of the shelter on the plane of the photovoltaic panel; calculating the intersection Sd of the projection polygon and the photovoltaic panel; The area of Sd is calculated, i.e. the projection area of the radiation source on the photovoltaic panel.

6. A photovoltaic panel solar radiation forecast device for performing a photovoltaic panel solar radiation forecast method according to any one of claims 1 to 5, characterized in that, The method comprises the steps of: an image acquisition module for acquiring sky images and synthesizing an HDR image; an image analysis module for analyzing sky radiation information according to the HDR image; a sky model establishing module for establishing a real-time sky model according to the sky radiation information; an incident radiation amount calculation module for calculating the incident radiation amount of the photovoltaic panel, which includes direct solar radiation, sky scattered radiation and ground reflected radiation.

7. A photovoltaic panel solar radiation amount prediction device characterized by comprising: The photovoltaic panel solar radiation amount prediction device comprises a processor and a memory, and the memory stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the photovoltaic panel solar radiation amount prediction method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the photovoltaic panel solar radiation amount prediction method according to any one of claims 1-5.

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