Photovoltaic panel power generation prediction method, device, equipment, storage medium and program product

Abstract

The present application discloses a method for predicting the power generation of a photovoltaic panel, a device for predicting the power generation of a photovoltaic panel, a device for predicting the power generation of a photovoltaic panel, a storage medium and a computer program product, and relates to the technical field of photovoltaic panel power generation. In the present application, a method for predicting the power generation of a photovoltaic panel that considers the dynamic coupling between the local environmental flow field and the heat transfer and power generation process of the photovoltaic panel is proposed. The first model of the environmental impact on the power generation of the photovoltaic panel and the second model of the photovoltaic panel heat release on the local environmental flow field are coupled to obtain a dynamic prediction model, and then the power generation of the photovoltaic panel is predicted by the dynamic prediction model. Since the dynamic coupling relationship between the environmental impact on the power generation of the photovoltaic panel and the photovoltaic panel power generation on the environment is fully considered in the dynamic prediction model, the dynamic coupling of multiple physical processes such as heat transfer and power generation inside the photovoltaic panel and the local environmental flow field is realized, and the power generation efficiency of the photovoltaic panel is more accurately predicted.

Description

Technical Field

[0001] The present application relates to the technical field of photovoltaic panel power generation, and in particular to a method for predicting photovoltaic panel power generation, a device for predicting photovoltaic panel power generation, a device for predicting photovoltaic panel power generation, a storage medium and a computer program product. Background Art

[0002] At present, the traditional photovoltaic panel power generation prediction model only focuses on the impact of a few environmental factors on the photovoltaic panel power generation performance. For example, the existing technology CN 117895506A establishes a relationship between environmental factors and photovoltaic panel power generation performance based on real-time weather conditions, and performs a preference analysis on the power output of photovoltaic power equipment. In other words, the current traditional photovoltaic panel power generation prediction method only conducts a one-way analysis of the impact of environmental factors on photovoltaics, and only focuses on a few variables such as radiation and photovoltaic panel temperature, and does not conduct a comprehensive analysis of the photovoltaic panel power generation process, resulting in a low prediction accuracy of photovoltaic panel power generation efficiency.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present application is to provide a photovoltaic panel power generation prediction method, a photovoltaic panel power generation prediction device, a photovoltaic panel power generation prediction device, a storage medium and a computer program product, aiming to solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency.

[0005] To achieve the above purpose, the present application proposes a method for predicting the power generation of a photovoltaic panel, the method comprising:

[0006] By analyzing the environmental factors that affect the power generation of photovoltaic panels, the first model of environmental impact on the power generation of photovoltaic panels is established;

[0007] By analyzing the influence of heat release from photovoltaic panels on the local environmental flow field, a second model of the influence of heat release from photovoltaic panels on the local environmental flow field is established.

[0008] coupling the first model and the second model to form a dynamic prediction model;

[0009] The amount of electricity generated by the photovoltaic panels is predicted based on the dynamic prediction model.

[0010] In one embodiment, the first model of environmental impact on photovoltaic panel power generation is a photovoltaic panel energy balance equation, which is: the total amount of solar radiation received by the photovoltaic panel is equal to the photovoltaic panel power generation, the photovoltaic panel radiation dissipation and the convection heat release of the photovoltaic panel.

[0011] In one embodiment, the radiation dissipation of the photovoltaic panel includes the long-wave radiation of the photovoltaic panel to the sky and the roof, wherein the long-wave radiation of the photovoltaic panel to the sky is calculated based on the surface temperature of the photovoltaic panel and the sky temperature, the sky temperature is calculated based on the ambient air temperature, and the long-wave radiation of the photovoltaic panel to the roof is calculated based on the surface temperature of the photovoltaic panel and the roof temperature.

[0012] In one embodiment, the power generation power used to calculate the power generation amount of the photovoltaic panel is calculated based on the temperature change between the surface temperature of the photovoltaic panel and the reference temperature.

[0013] In one embodiment, the second model of the photovoltaic panel heat release affecting the local environmental flow field is the fluid mechanics control equation of the local environmental flow field and the heat transfer equation of the photovoltaic panel. The fluid mechanics control equation of the local environmental flow field is obtained by constructing and solving the conservation equations of mass, momentum and energy.

[0014] In one embodiment, the step of predicting the amount of power generated by a photovoltaic panel according to the dynamic prediction model includes:

[0015] The heat release of the photovoltaic panel is calculated based on the first model and the current power generation;

[0016] The temperature change of the photovoltaic panel surface is calculated based on the second model and the heat release;

[0017] The latest power generation is calculated from the temperature change, and the latest power generation of the photovoltaic panel is calculated from the latest power generation.

[0018] In addition, to achieve the above purpose, the present application also proposes a photovoltaic panel power generation prediction device, the photovoltaic panel power generation prediction device comprising:

[0019] A first model building module is used to establish a first model of environmental impact on photovoltaic panel power generation by analyzing environmental factors that affect photovoltaic panel power generation;

[0020] The second model building module is used to build a second model of the effect of heat release from photovoltaic panels on the local environmental flow field by analyzing the effect of heat release from photovoltaic panels on the local environmental flow field;

[0021] A coupling module, used for coupling the first model with the second model to form a dynamic prediction model;

[0022] The prediction module is used to predict the amount of power generated by the photovoltaic panel according to the dynamic prediction model.

[0023] In addition, to achieve the above-mentioned purpose, the present application also proposes a photovoltaic panel power generation prediction device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the photovoltaic panel power generation prediction method as described above.

[0024] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the method for predicting the power generation of photovoltaic panels as described above are implemented.

[0025] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method for predicting the power generation of photovoltaic panels as described above are implemented.

[0026] One or more technical solutions proposed in this application have at least the following technical effects:

[0027] In this application, a method for predicting the power generation of photovoltaic panels taking into account the local environmental flow field is proposed. A dynamic prediction model is obtained by coupling a first model of the impact of the environment on the power generation of photovoltaic panels and a second model of the impact of the heat release of photovoltaic panels on the local environmental flow field. The power generation of photovoltaic panels is predicted by the dynamic prediction model. Since the dynamic coupling relationship between the impact of the environment on the power generation of photovoltaic panels and the impact of the power generation of photovoltaic panels on the environment is fully considered in the dynamic prediction model, the dynamic coupling of multiple physical processes such as heat transfer and power generation in photovoltaic panels with the local environmental flow field is realized, and the power generation efficiency of photovoltaic panels is predicted more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 A schematic diagram of a process flow provided for an embodiment of a method for predicting power generation of photovoltaic panels of the present application;

[0031] Figure 2 A schematic diagram of the flow of some physical quantities provided in an embodiment of a method for predicting the power generation of photovoltaic panels of the present application;

[0032] Figure 3 A schematic diagram of error data provided for an embodiment of a method for predicting photovoltaic panel power generation of the present application;

[0033] Figure 4 This is a schematic diagram of the module structure of a device for predicting the power generation of a photovoltaic panel according to an embodiment of the present application;

[0034] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the method for predicting the power generation of photovoltaic panels in the embodiment of the present application.

[0035] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0036] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0037] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0038] The current photovoltaic panel power generation efficiency is usually less than 20%. Not all the energy absorbed by the photovoltaic panel is converted into electrical energy. The excess energy is released in the form of heat, affecting the local environmental flow field. Environmental factors such as air temperature and wind speed further affect the physical processes of photovoltaic panel heat transfer and power generation, forming a dynamic coupling process.

[0039] In traditional photovoltaic panel power generation prediction models and methods, only the impact of single or several environmental factors on the power generation performance of photovoltaic panels is paid attention to, and only a one-way analysis of the impact of environmental factors on photovoltaics is performed, without considering the dynamic coupling relationship between the local environmental flow field and the photovoltaic system. In other words, there is no comprehensive analysis of the coupling process between multiple physical processes such as heat transfer and power generation inside the photovoltaic panel and the local environmental flow field. Especially in the urban environment, the complexity and diversity of urban forms under the regional climate background form differentiated local environmental flow fields, which makes the prediction of photovoltaic panel power generation efficiency more complicated. At present, there is no technical solution to solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency based on the dynamic coupling mechanism.

[0040] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a photovoltaic panel power generation prediction device, etc. The following takes the photovoltaic panel power generation prediction device as an example to illustrate this embodiment and the following embodiments.

[0041] Based on this, the present application embodiment provides a method for predicting the power generation of a photovoltaic panel. Figure 1 , Figure 1 This is a flow chart of a first embodiment of a method for predicting photovoltaic panel power generation according to the present application.

[0042] In this embodiment, the photovoltaic panel power generation prediction method includes steps S10 to S40:

[0043] Step S10, establishing a first model of environmental impact on photovoltaic panel power generation by analyzing environmental factors that affect photovoltaic panel power generation;

[0044] In a feasible implementation, the first model of the environmental impact on the power generation of photovoltaic panels is the photovoltaic panel energy balance equation, which is: the total amount of solar radiation received by the photovoltaic panel is equal to the power generation of the photovoltaic panel, the radiation dissipation of the photovoltaic panel and the convective heat release of the photovoltaic panel.

[0045] Through energy conservation analysis, the total amount of solar radiation received by the photovoltaic panel is equal to the photovoltaic panel power generation, the photovoltaic panel radiation dissipation (i.e. long-wave radiation), and the convective heat transfer of the photovoltaic panel. The photovoltaic panel energy balance equation is thus constructed:

[0046] (1)

[0047] In the formula, and are the absorption coefficient and the total solar irradiance on the inclined photovoltaic surface, The value is determined by the parameters given by the manufacturer. is the area of ​​the photovoltaic panel plane exposed to solar irradiance, and are the long-wave radiation from the photovoltaic panels to the sky and the roof, is the power generation, is the convective heat transfer of the photovoltaic panel, that is, the heat released by the photovoltaic panel. It is the unit time.

[0048] In a feasible implementation, the radiation dissipation of the photovoltaic panel includes the long-wave radiation of the photovoltaic panel to the sky and the roof, wherein the long-wave radiation of the photovoltaic panel to the sky is calculated based on the surface temperature of the photovoltaic panel and the sky temperature, the sky temperature is calculated based on the ambient air temperature, and the long-wave radiation of the photovoltaic panel to the roof is calculated based on the surface temperature of the photovoltaic panel and the roof temperature.

[0049] Long wave radiation to the sky and roof and They are given by the following formulas:

[0050] (2)

[0051] (3)

[0052] In the formula, is the Stefan-Boltzmann constant, F1 and F2 are the shape factors of the front and back sides of the photovoltaic, respectively, is the emissivity, which can be 0.85 in this embodiment. is the surface temperature of the photovoltaic panel, is the roof temperature, is the sky temperature.

[0053] It can be obtained by the following formula:

[0054] (4)

[0055] In the formula, is the ambient air temperature.

[0056] In a feasible implementation manner, the power generation power used to calculate the power generation of the photovoltaic panel is calculated based on the temperature change between the surface temperature of the photovoltaic panel and the reference temperature.

[0057] That is, the power generation used to calculate the power generation of the photovoltaic panel in formula (1) is Determined by the following formula:

[0058] (5)

[0059] In the formula, is a reference temperature, which may be 25°C in one embodiment. and are the conversion efficiency and temperature coefficient at the reference temperature. In one embodiment, the corresponding values ​​may be initially taken as 0.2 and 0.0097°C. −1 .

[0060] The above formulas (1)-(5) can be used to determine the convective heat transfer of the photovoltaic panel: , there is no need to model complex radiation models, such as the discrete ordinate (DO) method, which only requires the total amount of solar radiation received by the photovoltaic panel ( ) minus the power output ( ) and radiative dissipation ( ) to obtain it.

[0061] Step S20, establishing a second model of the effect of heat release from photovoltaic panels on the local environmental flow field by analyzing the effect of heat release from photovoltaic panels on the local environmental flow field;

[0062] In this embodiment, by constructing and solving the conservation equations of mass, momentum and energy, the influence of heat release from photovoltaic panels on the velocity field, pressure field and temperature field in the local environmental flow field is obtained, that is, a second model of the influence of heat release from photovoltaic panels on the local environmental flow field is obtained.

[0063] In a feasible implementation, the second model of the photovoltaic panel heat release affecting the local environmental flow field is the fluid mechanics control equation of the local environmental flow field and the heat transfer equation of the photovoltaic panel. The fluid mechanics control equation of the local environmental flow field is obtained by constructing and solving the conservation equations of mass, momentum and energy.

[0064] It should be noted that in order to deal with possible eddies or curved wall flows, it is necessary to select an appropriate turbulence model. Among them, the Reynolds-averaged Navier-Stokes method and the SST k-ω turbulence closure model are used because they can accurately predict the velocity field near the solid wall.

[0065] In addition, considering that the simulation is carried out under dynamic conditions, the time term cannot be ignored in the simulation, so the continuity and momentum equations under the Reynolds-averaged Navier-Stokes method can be expressed in tensor notation and Cartesian coordinates as follows:

[0066] (6)

[0067] (7)

[0068] Among them, in formula (6) is the fluid density, is the velocity component, which represents the average velocity of the fluid in the i-th direction (usually x, y, and z directions), t is the time (this equation shows the change of density over time), It is a spatial coordinate, indicating the coordinate of the jth direction, where j can be one of the directions x, y, and z.

[0069] Among them, in formula (7) It's pressure. is the dynamic viscosity coefficient, which represents the internal friction of the fluid, also known as viscosity, is the velocity component, which represents the average velocity of the fluid in the i-th direction, similar to the continuity equation. : It represents the rate of change of momentum with time, that is, the time change of the product of density and velocity (that is, momentum). : This term represents the convection term, that is, the spatial change of momentum during the motion of the fluid. : Pressure gradient, which indicates the change in pressure on the fluid in the i-th direction, drives the flow of the fluid. : This is the viscous force term, which describes the stress in the fluid due to viscosity. : This is the volumetric strain term associated with the change in fluid volume. Used to distinguish whether they are in the same direction (when i=j =1, otherwise 0), is the Reynolds stress term, which represents the effect of velocity fluctuations in turbulence, is the volume force, which represents the external force acting on a unit volume of fluid.

[0070] (8)

[0071] in, and represents the turbulent viscosity and turbulent kinetic energy, which are calculated using the SST k-ω turbulence model.

[0072] Since the viscous dissipation can be ignored at low Mach numbers in the simulation, the energy conservation equations in the air and photovoltaic can be written as equations respectively:

[0073] (9)

[0074] (10)

[0075] Among them, in formula (9) is the fluid density, It is the total energy density, usually representing the sum of the internal energy, kinetic energy and potential energy of the fluid. For a gas or fluid, E consists of: E=e+u 2 / 2, where e is the internal energy density, u 2 / 2 is the kinetic energy density. is the thermal conductivity of the fluid, which indicates the heat conduction capacity of the fluid. is the turbulent thermal conductivity, which represents the enhancing effect of turbulence on heat transfer. Turbulence tends to increase the speed at which heat is conducted in a fluid. is the heat source term, which represents the heat source inside the system. : The rate of change of total energy with time, which indicates the change of total energy density (ρE) per unit volume with time. : This is the convective term for energy, where p is the pressure, and represents the convective transport of energy in the jth direction. : Temperature gradient, which describes the rate of change of temperature in the jth direction and affects heat conduction.

[0076] Where, ρ in formula (10) is the density of the solid material, is the specific heat capacity of the solid, is the thermal conductivity of the material, is the heat source term, i.e. the heat released by the photovoltaic panel.

[0077] It should be noted that formulas (6)-(9) are equations for solving fluid heat transfer. Formula (6) is the mass conservation equation, that is, the continuity equation, formula (7) is the momentum conservation equation, and formula (9) is the energy conservation equation. Among them, the equations for solving fluids are mainly for the local environmental flow field. In addition, formula (10) is the solid heat transfer equation, which explains the heat transfer process inside the photovoltaic panel.

[0078] The surface temperature of the photovoltaic panel can be determined by formulas (6)-(10) , for example, by CFD solution , and further determine the surface temperature of the photovoltaic panel .

[0079] In addition, it should be noted that the above formulas (6)-(10) will be affected by the convective heat transfer of the photovoltaic panel. The impact is mainly due to the heat released by photovoltaic panels It is transmitted in, forming the so-called dynamic coupling process.

[0080] Step S30, coupling the first model and the second model to form a dynamic prediction model;

[0081] Reference Figure 2 , the local environmental flow field affects the heat transfer of photovoltaic panels , resulting in the surface temperature of the photovoltaic panel The power generated by photovoltaic panels and The heat released by photovoltaic panels is calculated based on this . is the heat released by the photovoltaic panel, that is, the building environment affects the photovoltaic heat balance equation (1) In this way, a dynamic coupling process is formed.

[0082] Step S40: predicting the amount of power generated by the photovoltaic panels according to the dynamic prediction model.

[0083] In a feasible implementation manner, the step of predicting the amount of power generated by a photovoltaic panel according to the dynamic prediction model includes:

[0084] The heat release of the photovoltaic panel is calculated based on the first model and the current power generation;

[0085] The temperature change on the surface of the photovoltaic panel is calculated based on the second model and the heat release;

[0086] The latest power generation is calculated from the temperature change, and the latest power generation of the photovoltaic panel is calculated from the latest power generation.

[0087] In one embodiment, 1. First, the heat release of the photovoltaic panel is calculated according to the first model, i.e., formula (1) (at this time, a historical power generation, i.e., the current power generation, is known); 2. Second, the heat release of the photovoltaic panel is regarded as the convection heat exchange Q between the photovoltaic panel and the surrounding environment ( Figure 2 3. Then, according to the second model, namely formula (6)-(10), the accumulated temperature change over a period of time is obtained, thereby obtaining the surface temperature of the photovoltaic panel ( Figure 2 4. Then, according to formula (5) and the calculated change in the surface temperature of the photovoltaic panel, the new power generation corresponding to the surface temperature of the photovoltaic panel is calculated; 5. Finally, the latest power generation is replaced as the most recent historical power generation ( Figure 2 left arrow).

[0088] In one application scenario, the environmental factors that affect the power generation of photovoltaic panels are analyzed, and the relationship between the environment and the power generation of photovoltaic panels is established; the impact of heat release from photovoltaic panels on the local environmental flow field is analyzed, and fluid mechanics and heat transfer equations are constructed; through data exchange, the above formulas and equations are coupled to form a dynamic prediction model; based on the established model, the power generation of photovoltaic panels is calculated. In the above, by considering the dynamic coupling relationship between the local environmental flow field and the power generation efficiency of photovoltaic panels, the accuracy of the model in predicting the power generation efficiency of photovoltaic panels is improved, providing a feasible method for accurately evaluating the power generation efficiency of distributed photovoltaic systems. Figure 3 ,It can be seen that the dynamic prediction model proposed in this application is highly consistent with the actual measurement.

[0089] It should be noted that the photovoltaic panel power generation prediction method proposed in this embodiment can be applied to the prediction of photovoltaic panel power generation of photovoltaic panels installed in urban environments or non-urban environments.

[0090] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the method for predicting the power generation of photovoltaic panels in the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0091] This application also provides a photovoltaic panel power generation prediction device, please refer to Figure 4 , the photovoltaic panel power generation prediction device comprises:

[0092] A first model building module 10 is used to establish a first model of environmental impact on photovoltaic panel power generation by analyzing environmental factors that affect photovoltaic panel power generation;

[0093] The second model building module 20 is used to build a second model of the effect of heat release from photovoltaic panels on the local environmental flow field by analyzing the effect of heat release from photovoltaic panels on the local environmental flow field;

[0094] A coupling module 30, used for coupling the first model and the second model to form a dynamic prediction model;

[0095] The prediction module 40 is used to predict the amount of power generated by the photovoltaic panel according to the dynamic prediction model.

[0096] In one embodiment, the first model of environmental impact on photovoltaic panel power generation is a photovoltaic panel energy balance equation, which is: the total amount of solar radiation received by the photovoltaic panel is equal to the photovoltaic panel power generation, the photovoltaic panel radiation dissipation and the convection heat release of the photovoltaic panel.

[0097] In one embodiment, the radiation dissipation of the photovoltaic panel includes the long-wave radiation of the photovoltaic panel to the sky and the roof, wherein the long-wave radiation of the photovoltaic panel to the sky is calculated based on the surface temperature of the photovoltaic panel and the sky temperature, the sky temperature is calculated based on the ambient air temperature, and the long-wave radiation of the photovoltaic panel to the roof is calculated based on the surface temperature of the photovoltaic panel and the roof temperature.

[0098] In one embodiment, the power generation power used to calculate the power generation amount of the photovoltaic panel is calculated based on the temperature change between the surface temperature of the photovoltaic panel and the reference temperature.

[0099] In one embodiment, the second model of the photovoltaic panel heat release affecting the local environmental flow field is the fluid mechanics control equation of the local environmental flow field and the heat transfer equation of the photovoltaic panel, and the fluid mechanics control equation of the local environmental flow field is obtained by constructing and solving the mass, momentum and energy conservation equations. In one embodiment, the prediction module is also used for:

[0100] The heat release of the photovoltaic panel is calculated based on the first model and the current power generation;

[0101] The temperature change on the surface of the photovoltaic panel is calculated based on the second model and the heat release;

[0102] The latest power generation is calculated from the temperature change, and the latest power generation of the photovoltaic panel is calculated from the latest power generation.

[0103] The photovoltaic panel power generation prediction device provided in the present application adopts the photovoltaic panel power generation prediction method in the above embodiment, which can solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency. Compared with the prior art, the beneficial effects of the photovoltaic panel power generation prediction device provided in the present application are the same as the beneficial effects of the photovoltaic panel power generation prediction method provided in the above embodiment, and other technical features in the photovoltaic panel power generation prediction device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0104] The present application provides a device for predicting the power generation of a photovoltaic panel, the device comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for predicting the power generation of the photovoltaic panel in the above-mentioned embodiment one.

[0105] Reference below Figure 5 , which shows a schematic diagram of the structure of a photovoltaic panel power generation prediction device suitable for implementing the embodiment of the present application. The photovoltaic panel power generation prediction device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The photovoltaic panel power generation prediction device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0106] like Figure 5As shown, the photovoltaic panel power generation prediction device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the photovoltaic panel power generation prediction device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the photovoltaic panel power generation prediction device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the photovoltaic panel power generation prediction device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0107] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0108] The photovoltaic panel power generation prediction device provided by the present application adopts the photovoltaic panel power generation prediction method in the above embodiment, which can solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency. Compared with the prior art, the beneficial effects of the photovoltaic panel power generation prediction device provided by the present application are the same as the beneficial effects of the photovoltaic panel power generation prediction method provided by the above embodiment, and other technical features in the photovoltaic panel power generation prediction device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0109] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0110] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0111] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for predicting the power generation of photovoltaic panels in the above-mentioned embodiment.

[0112] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0113] The computer-readable storage medium may be included in the photovoltaic panel power generation prediction device; or may exist independently without being assembled into the photovoltaic panel power generation prediction device.

[0114] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the photovoltaic panel power generation prediction device, the photovoltaic panel power generation prediction device: establishes a first model of environmental impact on photovoltaic panel power generation by analyzing the environmental factors that affect the photovoltaic panel power generation; establishes a second model of photovoltaic panel heat release affecting the local environmental flow field by analyzing the impact of the photovoltaic panel heat release process on the local environmental flow field; couples the first model and the second model to form a dynamic prediction model; and predicts the photovoltaic panel power generation according to the dynamic prediction model.

[0115] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0118] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned photovoltaic panel power generation prediction method, and can solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the photovoltaic panel power generation prediction method provided in the above-mentioned embodiment, and will not be repeated here.

[0119] The present application also provides a computer program product, including a computer program, which implements the steps of the photovoltaic panel power generation prediction method as described above when the computer program is executed by a processor.

[0120] The computer program product provided in this application can solve the technical problem of low prediction accuracy of photovoltaic panel power generation efficiency. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the photovoltaic panel power generation prediction method provided in the above embodiment, which will not be repeated here.

[0121] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for predicting the power generation of a photovoltaic panel, characterized in that: The method for predicting the power generation of photovoltaic panels includes: By analyzing the environmental factors that affect the power generation of photovoltaic panels, the first model of environmental impact on the power generation of photovoltaic panels is established: ; In the formula, and are the absorption coefficient and the total solar irradiance on the inclined photovoltaic surface, is the area of ​​the photovoltaic panel plane exposed to solar irradiance, and are the long-wave radiation from the photovoltaic panels to the sky and the roof, is the power generation, is the convective heat transfer of the photovoltaic panel, that is, the heat released by the photovoltaic panel. is the unit time; By analyzing the impact of the photovoltaic panel power generation physical process on the local environmental flow field, a second model of the photovoltaic panel heat release affecting the local environmental flow field is established: ， in, is the fluid density, is the velocity component, t is the time, are spatial coordinates; ， in, It's pressure. is the dynamic viscosity coefficient, , are velocity components, representing the average velocity of the fluid in the i-th and j-th directions, respectively. : represents the rate of change of momentum over time, represents the convection term, is the pressure gradient, is the viscous force term, is the volume strain term related to the change in fluid volume, Used to distinguish whether they are in the same direction. is the Reynolds stress term, is the volume force; ， in, and represents turbulent viscosity and turbulent kinetic energy; The energy conservation equation in air is: in, is the fluid density, is the total energy density, is the thermal conductivity of the fluid, is the turbulent thermal conductivity, is the heat source term, is the rate of change of total energy with time, is the convection term of energy, p is the pressure, is the temperature gradient; The energy conservation equation in photovoltaics is: Where ρ2 is the density of the solid material, is the specific heat capacity of the solid, is the thermal conductivity of the material, is the heat released by the photovoltaic panel. is the temperature gradient, describing the rate of change of temperature in the jth direction; coupling the first model and the second model to form a dynamic prediction model; The amount of electricity generated by the photovoltaic panels is predicted based on the dynamic prediction model.

2. The method for predicting the power generation of photovoltaic panels according to claim 1, characterized in that: The radiation dissipation of photovoltaic panels includes the long-wave radiation of photovoltaic panels to the sky and the roof, wherein the long-wave radiation of photovoltaic panels to the sky is calculated based on the surface temperature of photovoltaic panels and the sky temperature, the sky temperature is calculated based on the ambient air temperature, and the long-wave radiation of photovoltaic panels to the roof is calculated based on the surface temperature of photovoltaic panels and the roof temperature.

3. The method for predicting the power generation of photovoltaic panels according to claim 1, characterized in that: The power generation used to calculate the power generation of photovoltaic panels is calculated based on the temperature change between the surface temperature of the photovoltaic panel and the reference temperature.

4. The method for predicting the power generation of photovoltaic panels according to claim 1, characterized in that: The step of predicting the amount of power generated by the photovoltaic panel according to the dynamic prediction model comprises: The heat release of the photovoltaic panel is calculated based on the first model and the current power generation; The temperature change on the surface of the photovoltaic panel is calculated based on the second model and the heat release; The latest power generation is calculated from the temperature change, and the latest power generation of the photovoltaic panel is calculated from the latest power generation.

5. A photovoltaic panel power generation prediction device, characterized in that: The photovoltaic panel power generation prediction device implements the method according to claim 1, comprising: A first model building module is used to establish a first model of environmental impact on photovoltaic panel power generation by analyzing environmental factors that affect photovoltaic panel power generation; The second model building module is used to build a second model of the effect of heat release from photovoltaic panels on the local environmental flow field by analyzing the effect of heat release from photovoltaic panels on the local environmental flow field; A coupling module, used for coupling the first model and the second model to form a dynamic prediction model; The prediction module is used to predict the amount of power generated by the photovoltaic panel according to the dynamic prediction model.

6. A photovoltaic panel power generation prediction device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for predicting the power generation of a photovoltaic panel according to any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for predicting the power generation of a photovoltaic panel according to any one of claims 1 to 4 are implemented.

8. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method for predicting the power generation of a photovoltaic panel according to any one of claims 1 to 4 are implemented.

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