Photovoltaic module modeling and performance optimization method and system based on unmanned aerial vehicle flight model
Through drone aerial photography, real-life data of photovoltaic power stations are obtained, photovoltaic digital models and thermal models are established, and photovoltaic module layout is optimized, which solves the problem of inefficient performance evaluation and optimization methods of existing photovoltaic modules, and achieves efficient and accurate photovoltaic module performance evaluation and optimization.
Patent Information
- Application Number
- CN202411843773.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-14
- Publication Date
- 2025-03-25
AI Technical Summary
Existing PV module performance evaluation and optimization methods are inefficient, difficult to cover the entire range of photovoltaic power stations, and the models and parameters of different software tools are inconsistent, resulting in the accuracy and consistency of prediction results being challenged.
The photovoltaic module modeling and performance optimization method based on the drone aerial model is adopted to obtain real scene data through drone aerial photography, establish a photovoltaic digital model, and establish a thermal model in combination with physical and environmental parameters to carry out temperature distribution prediction and layout optimization.
It improves the efficiency and accuracy of photovoltaic module performance evaluation, achieves rapid coverage and comprehensive data acquisition of photovoltaic power plants, optimizes the layout of photovoltaic modules, improves power generation efficiency and reduces operation and maintenance costs.
Smart Images
Figure CN119692036A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of photovoltaic component modeling, and in particular relates to a photovoltaic component modeling and performance optimization method and system based on an unmanned aerial vehicle flight model. Background Art
[0002] In the existing photovoltaic power station operation and maintenance process, the performance evaluation and optimization of photovoltaic modules is a complex and time-consuming process. Traditional evaluation methods rely on manual inspection and ground measurement, which is not only inefficient but also difficult to cover the entire scope of the photovoltaic power station. In addition, the performance of photovoltaic modules varies greatly under different environmental conditions.
[0003] Different existing software tools handle horizontal total irradiance, horizontal diffuse irradiance, direct beam irradiance and solar point of direct sunlight (POA) irradiance in different ways, which leads to challenges in the consistency of prediction results. In addition, the modeling of system losses has a significant impact on the power generation potential of the system, but the parameters and functions provided by different software tools are different. Using the default values may cause the production estimate to deviate by more than 5%. Due to the differences in tool models and mathematical assumptions, it is impossible to maintain consistency. The wiring mechanisms of various software tools are different and cannot be completely unified. Conventional model parameter extraction methods are difficult to ensure the stability and reliability of model accuracy under complex outdoor environmental conditions, and cannot consider the problem of reduced model accuracy caused by performance degradation after long-term operation of photovoltaic systems. Online modeling has poor real-time performance and cannot meet the actual application needs in technical fields such as online fault diagnosis of photovoltaic systems, because various internal and external factors on site will affect the life cycle and performance of photovoltaic modules. Summary of the invention
[0004] In order to solve the above problems existing in the prior art, the present invention provides a photovoltaic component modeling and performance optimization method and system based on a UAV flight model.
[0005] In order to achieve the above object, the present invention adopts the following technical solution: Photovoltaic module modeling and performance optimization methods based on UAV flight model, including: Using a drone flying model to take aerial photos of a photovoltaic power station and obtain real-life data of photovoltaic components; modeling the photovoltaic components based on the real-life data to obtain a photovoltaic digital model; Establishing a thermal model of the photovoltaic module according to the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; predicting the thermal effect of the temperature distribution of the photovoltaic module according to the thermal model to obtain simulation analysis data; The layout of the photovoltaic modules is optimized based on the simulation analysis data.
[0006] A further improvement of the present invention is that the UAV flight model is a sensor system composed of a laser scanner and a high-resolution camera.
[0007] A further improvement of the present invention is that the photovoltaic module modeling method is: the point cloud data detected by the laser scanner is simplified by a voxel grid downsampling method to obtain standard point cloud data; the standard point cloud data and the image data collected by the high-resolution camera are aligned by a feature matching algorithm, and the aligned standard point cloud data is graphically reconstructed to obtain a real-scene digital model.
[0008] A further improvement of the present invention is that the method for constructing the photovoltaic digital model is: extracting the geometric shape information and size information of the photovoltaic components in the real-scene digital model through three-dimensional reconstruction technology and constructing a virtual analysis scene; in the virtual analysis scene, mapping the entity attributes corresponding to the real-scene digital model to the virtual component model through a parameterized method to form a photovoltaic digital model containing the geometric and physical properties of the photovoltaic components.
[0009] A further improvement of the present invention is that the physical parameters and environmental parameters of the photovoltaic module include wind speed at the panel installation location, ambient temperature, photovoltaic module surface temperature, incident solar radiation at the battery panel installation location, the upper limit of the temperature module under low wind speed and high solar radiation, material thermal conductivity, and the temperature difference between the battery and the rear surface of the photovoltaic module.
[0010] A further improvement of the present invention is that the thermal model of the photovoltaic module includes a heat conduction heat transfer model, a convection heat transfer model and a radiation heat transfer model; the heat conduction heat transfer model transfers heat through the material inside the photovoltaic module, and the material thermal conductivity of the physical parameters in the photovoltaic digital model is calculated by the calculation formula: ,in, q 1 is the conduction heat flux density, k is the thermal conductivity of the material, dT is the temperature change of the component battery, dx is the thickness change of the component material; the convection heat transfer model considers the influence of the movement of the surrounding air on the heat exchange, and the heat flow calculation formula for natural convection and forced convection is: ,in, q 2 is the convective heat flux density, h is the convective heat transfer coefficient, T s is the surface temperature of the photovoltaic module, T amb is the ambient temperature; the radiation heat transfer model considers the energy loss of the component surface in thermal radiation, and uses the Stefan-Boltzmann law to represent the heat flow, and the calculation formula is: ,in, q 3 is the radiation heat flux density, ε is the emissivity and σ is the Stefan-Boltzmann constant.
[0011] A further improvement of the present invention is that the thermal effect prediction method is: simulating the temperature field of the photovoltaic module with the help of the thermal model, predicting the photovoltaic cell temperature of the photovoltaic module under different physical parameters and environmental parameters according to the composition of the photovoltaic module, and the calculation formula is:
[0012] in, T c is the predicted component battery temperature, G T is the incident solar radiation at the location where the solar panels are installed, e is a natural number, a is the upper limit of the temperature module under low wind speed and high solar radiation, b is the component temperature variation coefficient, v is the wind speed at the panel installation location, G ref is the reference solar radiation of the photovoltaic module, Δ T For the standard 1000W / m 2 The temperature difference between the cell and the rear surface of the PV module at the radiation level is k 1. k 2. k 3 is the heat transfer coefficient of the heat conduction heat transfer model, the convection heat transfer model and the radiation heat transfer model.
[0013] A further improvement of the present invention is that the simulation analysis data includes temperature distribution data of photovoltaic components under different environmental conditions, temperature changes of photovoltaic components under solar radiation at different angles and orientations, and heat transfer characteristics under different wind speeds and directions.
[0014] A further improvement of the present invention is that the layout optimization method of the photovoltaic module is: based on the simulation analysis data of the photovoltaic module, the power generated by the photovoltaic module is evaluated through the module equivalent circuit and the maximum power point tracking algorithm, and the working point of the photovoltaic module is dynamically adjusted to ensure that the maximum power output can be obtained under various environmental conditions; The component equivalent circuit adopts a single diode equivalent circuit, which includes a dependent current source generated by photons transmitted from sunlight to the battery, a pn junction diode produced by semiconductor manufacturing, and internal series and parallel resistors; the output current of the battery of the photovoltaic module can be equivalent to:
[0015] in, I is the output current, G n is the irradiance under standard test conditions, I SC is the short-circuit current required by the photovoltaic module,k i is the temperature current constant, T n is the temperature under standard test conditions, I 0 is the reverse bias saturation current, V d is the open circuit voltage required by the photovoltaic module, V T is the thermal voltage, V is the output voltage, R S is the series resistance, R P is the parallel resistance; An MPP curve is generated based on the current-voltage characteristics of the equivalent circuit, and the maximum possible power provided from the photovoltaic unit is tracked according to the MPP curve.
[0016] Photovoltaic module modeling and performance optimization system based on UAV flight model, including: The photovoltaic digital model building module uses a drone flight model to take aerial photos of the photovoltaic power station and obtain real-life data of the photovoltaic components; and models the photovoltaic components based on the real-life data to obtain a photovoltaic digital model; A thermal model establishment and prediction module is used to establish a thermal model of the photovoltaic module based on the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; and to predict the thermal effect of the temperature distribution of the photovoltaic module based on the thermal model to obtain simulation analysis data; The analysis and optimization module optimizes the layout of the photovoltaic components based on the simulation analysis data.
[0017] Compared with the prior art, the present invention has at least the following beneficial technical effects: The photovoltaic module modeling and performance optimization method and system based on the unmanned aerial vehicle flight model provided by the present invention improve the efficiency and accuracy of photovoltaic module performance evaluation. The real-life data obtained by unmanned aerial vehicle aerial photography can quickly cover the entire photovoltaic power station, reduce the time and labor intensity required for manual inspection and ground measurement, and improve the comprehensiveness and accuracy of the data. The performance simulation and prediction of photovoltaic modules under different environmental conditions are realized. By establishing a thermal model of photovoltaic modules, the present invention can accurately simulate and predict the performance of photovoltaic modules under various environmental conditions by combining physical parameters and environmental parameters, and provide a scientific basis for the optimized operation of photovoltaic power stations. The layout of photovoltaic modules is optimized. Based on the simulation analysis data, the present invention can dynamically adjust the working point of the photovoltaic module to ensure that the maximum power output can be obtained under various environmental conditions, thereby improving the overall power generation efficiency of the photovoltaic power station. The operation and maintenance cost of the photovoltaic power station is reduced. Through the method provided by the present invention, the dependence on manual inspection and ground measurement can be reduced, the operation and maintenance cost of the photovoltaic power station can be reduced, and the operation efficiency and power generation of the photovoltaic power station can be improved. The fault diagnosis capability of the photovoltaic power station is improved, and potential problems of the photovoltaic power station can be discovered and handled in time to ensure the stable operation of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0019] Figure 1 It is a flow chart of the photovoltaic module modeling and performance optimization method based on the UAV flight model of the present invention; Figure 2 is a structural block diagram of an equivalent circuit in the present invention; Figure 3 is a schematic diagram of the photovoltaic panel layout in the present invention; Figure 4 It is a schematic diagram of the MPP curve in the present invention; Figure 5 This is a structural block diagram of the photovoltaic component modeling and performance optimization system based on the UAV flight model of the present invention. DETAILED DESCRIPTION
[0020] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.
[0021] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.
[0022] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.
[0023] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0024] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.
[0025] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.
[0026] Example 1 like Figure 1 As shown, the photovoltaic module modeling and performance optimization method based on the UAV flight model provided by the present invention includes: Aerial photography of the photovoltaic power station is carried out through the drone flight model to obtain real scene data of the photovoltaic components; photovoltaic component modeling is carried out according to the real scene data to obtain a photovoltaic digital model; Establishing a thermal model of the photovoltaic module according to the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; predicting the thermal effect of the temperature distribution of the photovoltaic module according to the thermal model to obtain simulation analysis data; The layout of the photovoltaic modules is optimized based on the simulation analysis data.
[0027] In this embodiment, the UAV flight model is a sensor system composed of a laser scanner and a high-resolution camera.
[0028] In this embodiment, the photovoltaic module modeling method is: simplifying the point cloud data detected by the laser scanner through a voxel grid downsampling method to obtain standard point cloud data; aligning the standard point cloud data and the image data collected by the high-resolution camera through a feature matching algorithm, and graphically reconstructing the aligned standard point cloud data to obtain a real-scene digital model.
[0029] In this embodiment, the method for constructing the photovoltaic digital model is: extracting the geometric shape information and size information of the photovoltaic components in the real-scene digital model through three-dimensional reconstruction technology and constructing a virtual analysis scene; in the virtual analysis scene, mapping the entity attributes corresponding to the real-scene digital model to the virtual component model through a parameterized method to form a photovoltaic digital model containing the geometric and physical properties of the photovoltaic components.
[0030] In this embodiment, the physical parameters and environmental parameters of the photovoltaic module include wind speed at the panel installation location, ambient temperature, photovoltaic module surface temperature, incident solar radiation at the panel installation location, the upper limit of the temperature module under low wind speed and high solar radiation, material thermal conductivity, and the temperature difference between the battery and the rear surface of the photovoltaic module.
[0031] In this embodiment, the thermal model of the photovoltaic module includes a heat conduction heat transfer model, a convection heat transfer model and a radiation heat transfer model; the heat conduction heat transfer model transfers heat through the material inside the photovoltaic module, and the material thermal conductivity of the physical parameters in the photovoltaic digital model is calculated by the calculation formula: ,in, q 1 is the conduction heat flux density, k is the thermal conductivity of the material, dT is the temperature change of the component battery, dx is the thickness change of the component material; the convection heat transfer model considers the influence of the movement of the surrounding air on the heat exchange, and the heat flow calculation formula for natural convection and forced convection is: ,in, q 2 is the convective heat flux density, h is the convective heat transfer coefficient, T s is the surface temperature of the photovoltaic module, T amb is the ambient temperature; the radiation heat transfer model considers the energy loss of the component surface in thermal radiation, and uses the Stefan-Boltzmann law to represent the heat flow, and the calculation formula is: ,in, q 3 is the radiation heat flux density, ε is the emissivity and σ is the Stefan-Boltzmann constant.
[0032] In this embodiment, the thermal effect prediction method is: simulating the temperature field of the photovoltaic module with the help of the thermal model, predicting the photovoltaic cell temperature of the photovoltaic module under different physical parameters and environmental parameters according to the composition of the photovoltaic module, and the calculation formula is:
[0033] in, T c is the predicted component battery temperature, G T is the incident solar radiation at the location where the solar panels are installed, e is a natural number, a is the upper limit of the temperature module under low wind speed and high solar radiation, b is the component temperature variation coefficient, v is the wind speed at the panel installation location, G ref is the reference solar radiation of the photovoltaic module, Δ T For the standard 1000W / m 2 The temperature difference between the cell and the rear surface of the PV module at the radiation level is k 1. k 2. k 3 is the heat transfer coefficient of the heat conduction heat transfer model, the convection heat transfer model and the radiation heat transfer model.
[0034] In this example, the thermal model and the prediction of thermal effects are modeled under steady-state heat transfer conditions. The photovoltaic module is operated in an open circuit state, the power from the device is ignored, the contribution of the glass surface illuminance, ground reflection and scattering to the panel is set to be constant, and the thickness of the silicon cell is assumed to be zero for the heat transfer code. The heat transfer of the glass surface is assumed to be equal on the upper and lower surfaces of the glass, and no heat transfer occurs at the edge of the specimen. The spectrum, albedo, ground scattering and average crystalline silicon absorptivity of the reflected light diffracted by the hologram are assumed to be constant and the same as the full spectrum hitting the photovoltaic cell. For the light diffracted by the hologram, its spectral range (including seasonal changes) is 450 to 950 nm, centered at ~725 nm. Since the manufacturer's specifications for the glass have a total transmittance of 90% in the visible and infrared bands and a reflectivity of 8% in the transparent area, its absorption can be ignored compared to the silicon area. The solar cell is the only heat source in the panel.
[0035] In this embodiment, the simulation analysis data includes temperature distribution data of photovoltaic modules under different environmental conditions, temperature variation of photovoltaic modules under solar radiation at different angles and orientations, and heat transfer characteristics under different wind speeds and directions.
[0036] In this embodiment, the layout optimization method of the photovoltaic module is: based on the simulation analysis data of the photovoltaic module, the power generated by the photovoltaic module is evaluated through the module equivalent circuit and the maximum power point tracking algorithm, and the working point of the photovoltaic module is dynamically adjusted to ensure that the maximum power output can be obtained under various environmental conditions.
[0037] In this embodiment, if Figure 2 and Figure 3 As shown, the component equivalent circuit adopts a single diode equivalent circuit, which includes a dependent current source generated by photons transmitted from sunlight to the battery, a pn junction diode produced by semiconductor manufacturing, and internal series and parallel resistors; the output current of the battery of the photovoltaic module can be equivalent to:
[0038] in, I is the output current, G n is the irradiance under standard test conditions, I SC is the short-circuit current required by the photovoltaic module, k i is the temperature current constant, T n is the temperature under standard test conditions, I 0 is the reverse bias saturation current, V d is the open circuit voltage required by the photovoltaic module, V T is the thermal voltage, V is the output voltage, R S is the series resistance, R P is the parallel resistance; like Figure 4 As shown, an MPP curve is generated based on the current-voltage characteristics of the equivalent circuit, and the maximum possible power provided by the photovoltaic unit is tracked according to the MPP curve.
[0039] Example 2 like Figure 5 As shown in the figure, the photovoltaic module modeling and performance optimization system based on the UAV flight model includes: The photovoltaic digital model building module uses a drone flight model to take aerial photos of the photovoltaic power station and obtain real-life data of the photovoltaic components; and models the photovoltaic components based on the real-life data to obtain a photovoltaic digital model; A thermal model establishment and prediction module is used to establish a thermal model of the photovoltaic module based on the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; and to predict the thermal effect of the temperature distribution of the photovoltaic module based on the thermal model to obtain simulation analysis data; The analysis and optimization module optimizes the layout of the photovoltaic components based on the simulation analysis data.
[0040] Example 3 The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.
[0041] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
[0042] The program code contained on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can 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 it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).
[0043] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.
[0044] In addition, it should be understood that although this specification is described in accordance with the implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation modes that can be understood by those skilled in the art. The above content is only to illustrate the technical idea of the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.
Claims
1. Photovoltaic module modeling and performance optimization method based on UAV flight model, characterized in that: include: Using a drone flying model to take aerial photos of a photovoltaic power station and obtain real-life data of photovoltaic components; modeling the photovoltaic components based on the real-life data to obtain a photovoltaic digital model; Establishing a thermal model of the photovoltaic module according to the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; predicting the thermal effect of the temperature distribution of the photovoltaic module according to the thermal model to obtain simulation analysis data; The layout of the photovoltaic modules is optimized based on the simulation analysis data.
2. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 1 is characterized in that: The UAV flight model is a sensor system composed of a laser scanner and a high-resolution camera.
3. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 2 is characterized in that: The photovoltaic module modeling method is as follows: simplifying the point cloud data detected by the laser scanner through a voxel grid downsampling method to obtain standard point cloud data; registering the standard point cloud data and the image data collected by the high-resolution camera through a feature matching algorithm, and graphically reconstructing the registered standard point cloud data to obtain a real-scene digital model.
4. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 3 is characterized in that: The photovoltaic digital model construction method is as follows: extracting the geometric shape information and size information of the photovoltaic components in the real-scene digital model through three-dimensional reconstruction technology and constructing a virtual analysis scene; mapping the entity attributes corresponding to the real-scene digital model to the virtual component model through a parameterized method in the virtual analysis scene to form a photovoltaic digital model containing the geometric and physical attributes of the photovoltaic components.
5. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 4 is characterized in that: The physical and environmental parameters of the photovoltaic module include wind speed at the panel installation location, ambient temperature, photovoltaic module surface temperature, incident solar radiation at the panel installation location, upper limit of the temperature module under low wind speed and high solar radiation, material thermal conductivity, and temperature difference between the battery and the rear surface of the photovoltaic module.
6. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 5 is characterized in that: The thermal model of the photovoltaic module includes a heat conduction heat transfer model, a convection heat transfer model and a radiation heat transfer model; the heat conduction heat transfer model transfers heat through the material inside the photovoltaic module, and is calculated by the material thermal conductivity of the physical parameters in the photovoltaic digital model, and the calculation formula is: ,in, q 1 is the conduction heat flux density, k is the thermal conductivity of the material, dT is the temperature change of the component battery, dx is the thickness change of the component material; the convection heat transfer model considers the influence of the movement of the surrounding air on the heat exchange, and the heat flow calculation formula for natural convection and forced convection is: ,in, q 2 is the convective heat flux density, h is the convective heat transfer coefficient, T s is the surface temperature of the photovoltaic module, T amb is the ambient temperature; the radiation heat transfer model considers the energy loss of the component surface in thermal radiation, and uses the Stefan-Boltzmann law to represent the heat flow, and the calculation formula is: ,in, q 3 is the radiation heat flux density, ε is the emissivity and σ is the Stefan-Boltzmann constant.
7. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 6 is characterized in that: The thermal effect prediction method is: using the thermal model to simulate the temperature field of the photovoltaic module, and predicting the photovoltaic cell temperature of the photovoltaic module under different physical parameters and environmental parameters according to the composition of the photovoltaic module. The calculation formula is: in, T c is the predicted component battery temperature, G T is the incident solar radiation at the location where the solar panels are installed, e is a natural number, a is the upper limit of the temperature module under low wind speed and high solar radiation, b is the component temperature variation coefficient, v is the wind speed at the panel installation location, G ref is the reference solar radiation of the photovoltaic module, Δ T For the standard 1000W / m 2 The temperature difference between the cell and the rear surface of the PV module at the radiation level is k 1. k 2. k 3 is the heat transfer coefficient of the heat conduction heat transfer model, the convection heat transfer model and the radiation heat transfer model.
8. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 7 is characterized in that: The simulation analysis data include temperature distribution data of photovoltaic modules under different environmental conditions, temperature variation of photovoltaic modules under solar radiation at different angles and orientations, and heat transfer characteristics under different wind speeds and directions.
9. The photovoltaic module modeling and performance optimization method based on the unmanned aerial vehicle flight model according to claim 8 is characterized in that: The layout optimization method of the photovoltaic module is as follows: based on the simulation analysis data of the photovoltaic module, the power generated by the photovoltaic module is evaluated through the module equivalent circuit and the maximum power point tracking algorithm, and the working point of the photovoltaic module is dynamically adjusted to ensure that the maximum power output can be obtained under various environmental conditions; The component equivalent circuit adopts a single diode equivalent circuit, which includes a dependent current source generated by photons transmitted from sunlight to the battery, a pn junction diode produced by semiconductor manufacturing, and internal series and parallel resistors; the output current of the battery of the photovoltaic module can be equivalent to: in, I is the output current, G n is the irradiance under standard test conditions, I SC is the short-circuit current required by the photovoltaic module, k i is the temperature current constant, T n is the temperature under standard test conditions, I 0 is the reverse bias saturation current, V d is the open circuit voltage required by the photovoltaic module, V T is the thermal voltage, V is the output voltage, R S is the series resistance, R P is the parallel resistance; An MPP curve is generated based on the current-voltage characteristics of the equivalent circuit, and the maximum possible power provided from the photovoltaic unit is tracked according to the MPP curve.
10. Photovoltaic module modeling and performance optimization system based on drone flight model, characterized in that: include: The photovoltaic digital model building module uses a drone flight model to take aerial photos of the photovoltaic power station and obtain real-life data of the photovoltaic components; and models the photovoltaic components based on the real-life data to obtain a photovoltaic digital model; A thermal model establishment and prediction module is used to establish a thermal model of the photovoltaic module based on the photovoltaic digital model combined with the physical parameters and environmental parameters of the photovoltaic module; and to predict the thermal effect of the temperature distribution of the photovoltaic module based on the thermal model to obtain simulation analysis data; The analysis and optimization module optimizes the layout of the photovoltaic components based on the simulation analysis data.