Method and device for correcting solar radiation of photovoltaic field based on numerical model

Abstract

The application relates to the technical field of meteorological algorithm research, in particular to a photovoltaic station solar radiation correction method and device based on a numerical model, which comprises the following steps: obtaining the content of water particles in each layer of atmosphere above a target photovoltaic station based on an optimized WRF model, determining the current atmospheric state of each layer of atmosphere and the weakening correction coefficient of each layer of atmosphere to solar radiation, layer by layer calculating the reduction amount of solar radiation irradiance of each layer of atmosphere on the solar radiation transmission path from the top layer of atmosphere to the target photovoltaic station by using the weakening correction coefficient of each layer of atmosphere to solar radiation, obtaining the final solar radiation irradiance reduced by the bottom layer of atmosphere, and correcting the actual received solar radiation irradiance of the target photovoltaic station according to the final solar radiation irradiance.

Description

Technical Field

[0001] This application relates to the field of meteorological algorithm research technology, and in particular to a method and device for correcting solar radiation at photovoltaic power stations based on numerical models. Background Technology

[0002] Numerical weather prediction, also known as numerical weather forecasting, weather numerical prediction, or numerical forecasting, is a method of predicting the atmospheric state at future times based on the known atmospheric state at the initial and boundary conditions, using the current weather conditions as input, and solving the atmospheric kinematic equations numerically. Relying on numerical weather prediction, meteorological operations can now achieve seamless timescale weather forecasts, such as short-term (0-a few hours), short-term (1-3 days), medium-term (4-9 days), and extended-term (10-30 days). In terms of spatial resolution, regional scale numerical models can currently reach the hundreds of meters level, and through coupling with other models (such as LES (Linear Expenditure System) models), even resolutions within hundreds of meters can be achieved, realizing ultra-high resolution and high-resolution simulations.

[0003] Since its successful trials in the 1950s, numerical weather prediction has evolved over 70 years into a complex and rigorous interdisciplinary system, transforming weather forecasting from a traditional statistical and empirical method based on weather maps into an objective and quantitative science. The history of numerical weather prediction, from its initial conception 100 years ago to its 70-year development and application, demonstrates that its progress is built upon years of steady and continuous scientific understanding and technological advancements. In short, numerical weather prediction is a comprehensive reflection of meteorological science and technology, and a crucial component of core technologies for safeguarding national welfare and defense security.

[0004] Numerical models are influenced by computable models, and errors are introduced by initial fields, boundary conditions, parameterization schemes, etc. Chaos theory makes it difficult for numerical models to make accurate long-term forecasts. Therefore, the forecast data of numerical models often have systematic deviations from actual observations.

[0005] Among related technologies, weather forecasting is mainly conducted using the WRF (Weather Research and Forecasting) numerical model, the GRAPES_Meso model, or large eddy simulation techniques. The WRF numerical model is a new generation of mesoscale numerical model system jointly developed by the National Center for Atmospheric Research, the National Center for Environmental Prediction, and multiple universities, research institutes, and operational departments. It features advanced design concepts, uses Fortran90 for model programming, and is flexible, efficient, and widely applicable. Its key features include advanced data assimilation techniques, powerful nesting capabilities, and advanced physical processes, particularly excelling in processing convection and mesoscale precipitation. The WRF model system primarily consists of a preprocessing system (WPS), the WRF master model, and post-processing, such as the NCL (The NCAR Command). The model is composed of three parts: Language (data visualization language), ARWpost, etc. Among them, the WRF master model system is the core part, which considers a complete range of physical process options, such as microphysics, cumulus convection, planetary boundary layer, land surface processes, radiation and surface layer, etc. There are rich parameterization schemes to choose from in each physical process, generating the sources and sinks of dynamics, heat and water vapor required by the model, and having a forcing and driving effect on the dynamic and thermodynamic processes of the model.

[0006] The mesoscale version of the GRAPES_Meso (Global Regional Assimilation and Prediction System_Meso) model is a new generation of global / regional integrated numerical weather prediction system independently developed by the Chinese Academy of Meteorological Sciences. It mainly consists of a fully compressible dynamic framework and physical parameterization schemes. The GRAPES_Meso model is a short-term weather forecasting model capable of accurately predicting weather conditions under different conditions globally and in China. It has played an important role in actual meteorological operations at the national and regional levels. The dynamic framework of the GRAPES_Meso model uses a vertically aligned topographic-following coordinate system, a semi-implicit and semi-Lagrange temporal convection scheme for time integration discretization, and in the horizontal space, an Arakawa-C grid variable distribution, a second-order accurate central difference scheme, and a non-vertically discretized hydrostatic approximation scheme. Its main physical processes include radiative transfer, turbulent mixing, wet convection, grid-scale precipitation processes, land surface processes, and sub-grid-scale topographic gravity wave drag. The parameterization schemes describing each physical process can be freely combined and selected.

[0007] Large eddy simulation (LES) is widely used in the simulation of boundary layer turbulence, yielding a series of detailed and reliable high-resolution atmospheric turbulence information. The basic idea of ​​LES is that turbulent motion consists of many eddies of different sizes. A sufficiently fine grid scale (below 100m) is used to separate large and small eddies. Since large-scale eddies carry most of the turbulent energy, they can be directly simulated; while small-scale eddies are generated through nonlinear interactions, are not directly related to the instability of motion or boundary problems, and mostly play a dissipative role, making them easier to parameterize and close. Early LES studies focused on typical convective boundary layers with obvious large eddy characteristics. With advancements in computer technology, LES has been extended to stable boundary layers with more complex boundaries and less pronounced large eddy characteristics, as well as to non-uniform underlying surfaces. Furthermore, LES models possess extremely high grid resolution and three-dimensional simulation effects of boundary layer turbulence, making them suitable for studying various physical processes, such as deep and shallow convection and warm cloud precipitation convection. Based on the unique advantages of large eddy simulation (LES) technology in boundary layer research, more and more mesoscale models hope to introduce high-resolution boundary layer schemes (LES mechanisms) into numerical prediction models, so as to significantly improve the simulation effect of boundary layers in mesoscale models. At the same time, it is also crucial to introduce a compensation mechanism for the inherent dissipation problem in the advection scheme of mesoscale models.

[0008] However, the above numerical models have corresponding advantages, but also have some disadvantages: (1) The WRF numerical model has advanced data assimilation technology, powerful nesting capabilities, moderate computational cost, and rich physical parameterization schemes. However, the WRF numerical model is a traditional regional model with lateral boundary restrictions (bidirectional information communication cannot be carried out inside and outside the regional grid), and it cannot directly achieve ultra-high resolution simulation and capture turbulent motion in the atmospheric boundary layer; (2) The GRAPES_Meso model has rich combinations of physical parameterization schemes, moderate computational cost, and good simulation effect in China. However, the GRAPES_Meso model cannot achieve accurate global simulation, still has a gap with the world's mainstream numerical prediction models, and is highly dependent on the initial field and boundary conditions; (3) Large eddy simulation technology can achieve ultra-high resolution simulation, directly capture most of the turbulent motion in the atmospheric boundary layer, and has advantages in capturing small-scale atmospheric motion in complex terrain and non-uniform underlying surfaces. However, large eddy simulation technology requires a lot of computational resources, has a high computational cost, and needs to be coupled with mesoscale numerical models.

[0009] Therefore, it can be concluded from the above that the relevant technologies have the following problems:

[0010] (1) Currently, the accuracy of photovoltaic power generation and output prediction is generally low, with meteorological factors having the most significant impact. For photovoltaic prediction, the atmospheric conditions above the power station, especially cloud and precipitation processes, are one of the most important factors affecting the solar radiation received by the power station. There is a lack of means in related technologies to effectively correct the solar radiation prediction results of the power station by identifying different atmospheric conditions;

[0011] (2) The simulation resolution of global / regional numerical prediction models in related technologies is generally coarse, which is insufficient for the fine simulation of atmospheric conditions above photovoltaic power stations in the simulation area, especially cloud and precipitation processes, which can easily cause large errors.

[0012] (3) At present, there are limited means of observation of gas components, aerosol particle size and concentration and cloud microphysical characteristics (phase state and content of water particles in clouds) in the atmosphere, and observation data are lacking. High-resolution numerical simulation methods can be used to directly and quantitatively analyze the state of the entire atmosphere in the simulation area, especially the cloud microphysical characteristics, so as to accurately correct the solar radiation of the station. Summary of the Invention

[0013] This application provides a method and apparatus for correcting solar radiation at photovoltaic power plants based on numerical models. This addresses the problems in related technologies, such as the lack of effective observation of gas components, aerosol particle size and concentration, and cloud microphysical characteristics (phase state and content of water-bearing particles) in the atmosphere above photovoltaic power plants; the inability to effectively correct solar radiation prediction results by identifying different atmospheric states; the resulting low accuracy of photovoltaic predictions; and the insufficient ability to refine the simulation of atmospheric conditions above photovoltaic power plants within the simulation area due to the generally coarse simulation resolution used in global / regional numerical prediction models in related technologies.

[0014] The first aspect of this application provides a method for correcting solar radiation at photovoltaic power plants based on numerical models, the method comprising:

[0015] The content of water-based particles in each atmospheric layer above the target photovoltaic power station is obtained based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area.

[0016] The current atmospheric state of each layer of atmosphere above the target photovoltaic power station is determined based on the content of water-based particles in each layer of atmosphere above the target photovoltaic power station, and the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station to solar radiation is determined based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station.

[0017] By using the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station to calculate the reduction of solar irradiance by each atmospheric layer along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station, the final solar irradiance after reduction by the bottom atmosphere is obtained, and the actual solar irradiance received by the target photovoltaic power station is corrected based on the final solar irradiance after reduction by the bottom atmosphere.

[0018] Optionally, in one embodiment of this application, before obtaining the content of water-based particles in each atmospheric layer above the target photovoltaic power station based on the optimized WRF model, the method further includes:

[0019] A target simulation area is constructed with the target photovoltaic power station as the center, and basic data within the target simulation area is obtained;

[0020] A WRF model is constructed based on the aforementioned basic data, and the WRF model is optimized by setting the optimal combination strategy of physical parameterization schemes to obtain an optimized WRF model. Calculations are performed based on the optimized WRF model, and the content of water-based particles in each layer of atmosphere above the target photovoltaic power station is obtained according to the calculation results.

[0021] Optionally, in one embodiment of this application, constructing the target simulation area centered on the target photovoltaic power station includes:

[0022] Centered on the target photovoltaic power station, a first preset number of nested patterns are set in the horizontal direction using a preset grid distribution, and a second preset number of atmospheric layer distributions are set in the vertical direction using a hybrid vertical coordinate system.

[0023] The target simulation region is obtained based on the nesting pattern and the atmospheric layer distribution.

[0024] Optionally, in one embodiment of this application, determining the current atmospheric state of each atmospheric layer above the target photovoltaic power station based on the content of water-based particles in each atmospheric layer above the target photovoltaic power station includes:

[0025] Obtain the cloud droplet content in the target atmospheric layer;

[0026] The current initial atmospheric state of the target layer is determined based on the cloud droplet content in the target layer atmosphere.

[0027] If the cloud droplet content is greater than the first preset content threshold, then the current initial atmospheric state of the target layer is determined to be a cloudy state.

[0028] If the cloud droplet content is less than or equal to the first preset content threshold, then the current initial atmospheric state of the target layer is determined to be cloudless.

[0029] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the method further includes:

[0030] If the current initial atmospheric state of the target layer is cloudless, then determine whether the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold.

[0031] If the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold, then the current atmospheric state of the target layer is determined to be clear sky.

[0032] If the cloud droplet content in the target layer is greater than the second preset content threshold and less than the first preset content threshold, then the current atmospheric state of the target layer is determined to be an aerosol atmosphere.

[0033] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the method further includes:

[0034] If the initial atmospheric state of the target layer is cloudy, then the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere are obtained, and the current atmospheric state of the target layer is determined based on the cloud droplet content, the ice crystal content, the raindrop content, the snow crystal content, and the graupel content.

[0035] If the cloud droplet content is greater than the first preset content threshold, and the raindrop content is greater than the first preset content threshold, then the current atmospheric state of the target layer is determined to be a liquid cloud.

[0036] If both the ice crystal content and the snow crystal content are greater than the second preset content threshold, and the graupel content is greater than the first preset content threshold, then the current atmospheric state of the target layer is determined to be an ice phase cloud.

[0037] If the cloud droplet content, raindrop content, and graupel content are all greater than the first preset content threshold, and the ice crystal content and snow crystal content are all greater than the second preset content threshold, then the current atmospheric state of the target layer is determined to be a mixed phase cloud.

[0038] Optionally, in one embodiment of this application, determining the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station for solar radiation based on the current atmospheric state of each atmospheric layer above the target photovoltaic power station includes:

[0039] If the current atmospheric state is clear sky, then the first attenuation correction coefficient of the target layer atmosphere to solar radiation is determined based on the clear sky atmosphere.

[0040] If the current atmospheric state is an aerosol atmosphere, then the second attenuation correction coefficient of the target layer atmosphere on solar radiation is determined based on the aerosol atmosphere;

[0041] If the current atmospheric state is a liquid phase cloud, an ice phase cloud, or a mixed phase cloud, then the third attenuation correction coefficient of the target layer atmosphere to solar radiation is determined based on the liquid phase cloud, the ice phase cloud, or the mixed phase cloud.

[0042] Optionally, in one embodiment of this application, the step of calculating the reduction in solar irradiance by each layer of atmosphere along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station using the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station, to obtain the final solar irradiance after reduction by the bottom atmosphere, and correcting the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the bottom atmosphere, includes:

[0043] Obtain the incident solar radiation irradiance of the upper atmosphere;

[0044] Following the order from the top layer of the atmosphere to the bottom layer of the atmosphere, based on the incident solar irradiance of the top layer of the atmosphere and the preset solar radiation transfer equation, the incident solar irradiance and the reduced solar irradiance of each layer of the atmosphere are calculated sequentially to obtain the final solar irradiance after reduction by the bottom layer of the atmosphere.

[0045] The actual solar irradiance received by the target photovoltaic power station is corrected based on the final solar irradiance after reduction by the lower atmosphere.

[0046] The incident solar irradiance of the current computational layer atmosphere is the solar irradiance after reduction by the previous layer of atmosphere. The reduced solar irradiance of the current computational layer atmosphere is calculated by inputting the incident solar irradiance of the current computational layer atmosphere and the reduction correction coefficient of the current computational layer atmosphere to the preset solar radiation transfer equation. If the current computational layer is the top layer, then the incident solar irradiance of the current computational layer atmosphere is the incident solar irradiance of the top layer of atmosphere.

[0047] A second aspect of this application provides a solar radiation correction device for photovoltaic power plants based on a numerical model, comprising:

[0048] The water content acquisition module is used to acquire the content of water particles in each layer of atmosphere above the target photovoltaic power station based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area.

[0049] The atmospheric state determination module is used to determine the current atmospheric state of each layer of atmosphere above the target photovoltaic power station based on the content of water-based particles in each layer of atmosphere above the target photovoltaic power station, and to determine the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station on solar radiation based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station.

[0050] The solar radiation correction module for the target photovoltaic power station is used to calculate the reduction of solar irradiance by each layer of atmosphere along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station by using the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station. The module obtains the final solar irradiance after reduction by the bottom atmosphere and corrects the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the bottom atmosphere.

[0051] Optionally, in one embodiment of this application, before obtaining the content of water-based particles in each atmospheric layer above the target photovoltaic power station based on the optimized WRF model, the water-based particle content acquisition module further includes:

[0052] The target simulation area setting and basic data acquisition unit is used to construct a target simulation area centered on the target photovoltaic power station and acquire basic data within the target simulation area;

[0053] The model building and optimization unit is used to build a WRF model based on the basic data, and optimize the WRF model by setting the optimal physical parameterization scheme combination strategy to obtain the optimized WRF model. The optimized WRF model is then used for calculation to obtain the content of water particles in each layer of atmosphere above the target photovoltaic station based on the calculation results.

[0054] Optionally, in one embodiment of this application, the target simulation area setting and basic data acquisition unit includes:

[0055] The target simulation area division unit is used to set a first preset number of nested patterns in the horizontal direction using a preset grid distribution with the target photovoltaic station as the center, and to set a second preset number of atmospheric layer distributions in the vertical direction using a hybrid vertical coordinate system.

[0056] The simulation region acquisition unit obtains the target simulation region based on the nesting pattern and the atmospheric layer distribution.

[0057] Optionally, in one embodiment of this application, the atmospheric state determination module includes:

[0058] The cloud droplet content acquisition unit is used to acquire the cloud droplet content in the target atmospheric layer.

[0059] An initial atmospheric state determination unit is used to determine the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere.

[0060] A cloud state determination unit is used to determine that the current initial atmospheric state of the target layer is a cloud state if the cloud droplet content is greater than a first preset content threshold.

[0061] The cloudless state determination unit is used to determine that the current initial atmospheric state of the target layer is cloudless if the cloud droplet content is less than or equal to the first preset content threshold.

[0062] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the cloudless state determination unit includes:

[0063] The cloud droplet content determination subunit is used to determine whether the cloud droplet content in the target layer atmosphere is equal to a second preset content threshold if the current initial atmospheric state of the target layer is cloudless.

[0064] The clear sky atmosphere determination subunit is used to determine that the current atmospheric state of the target layer is clear sky if the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold.

[0065] The aerosol atmosphere determination subunit is used to determine the current atmospheric state of the target layer as an aerosol atmosphere if the cloud droplet content in the target layer is greater than a second preset content threshold and less than a first preset content threshold.

[0066] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the cloud state determination unit includes:

[0067] The current atmospheric state determination unit is used to obtain the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere if the current initial atmospheric state of the target layer is a cloudy state, and determine the current atmospheric state of the target layer based on the cloud droplet content, the ice crystal content, the raindrop content, the snow crystal content, and the graupel content;

[0068] The liquid cloud determination subunit is used to determine that the current atmospheric state of the target layer is a liquid cloud if the cloud droplet content is greater than the first preset content threshold and the raindrop content is greater than the first preset content threshold.

[0069] The ice phase cloud determination subunit is used to determine that the current atmospheric state of the target layer is an ice phase cloud if the ice crystal content and the snow crystal content are both greater than the second preset content threshold, and the graupel content is greater than the first preset content threshold.

[0070] The mixed-phase cloud determination subunit is used to determine that the current atmospheric state of the target layer is a mixed-phase cloud if the cloud droplet content, the raindrop content, and the graupel content are all greater than the first preset content threshold, and the ice crystal content and the snow crystal content are all greater than the second preset content threshold.

[0071] Optionally, in one embodiment of this application, the atmospheric state determination module includes:

[0072] The first attenuation correction coefficient determination unit is used to determine the first attenuation correction coefficient of the target layer atmosphere to solar radiation based on the clear sky atmosphere if the current atmospheric state is clear sky atmosphere.

[0073] The second attenuation correction coefficient determination unit is used to determine the second attenuation correction coefficient of the target layer atmosphere to solar radiation based on the aerosol atmosphere if the current atmospheric state is an aerosol atmosphere.

[0074] The third attenuation correction coefficient determination unit is used to determine the third attenuation correction coefficient of the target atmospheric layer on solar radiation based on the liquid cloud, the ice cloud, or the mixed-phase cloud if the current atmospheric state is a liquid cloud, an ice cloud, or a mixed-phase cloud.

[0075] Optionally, in one embodiment of this application, the target photovoltaic power station solar radiation correction module includes:

[0076] A solar radiation irradiance acquisition unit is used to acquire the incident solar radiation irradiance of the top layer of the atmosphere;

[0077] The solar irradiance calculation unit is used to calculate the incident solar irradiance and the reduced solar irradiance of each layer of the atmosphere in sequence from the top layer of the atmosphere to the bottom layer of the atmosphere, based on the incident solar irradiance of the top layer of the atmosphere and the preset solar irradiance transfer equation, so as to obtain the final solar irradiance after reduction by the bottom layer of the atmosphere.

[0078] A solar irradiance correction unit is used to correct the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the lower atmosphere.

[0079] The incident solar irradiance of the current computational layer atmosphere is the solar irradiance after reduction by the previous layer of atmosphere. The reduced solar irradiance of the current computational layer atmosphere is calculated by inputting the incident solar irradiance of the current computational layer atmosphere and the reduction correction coefficient of the current computational layer atmosphere to the preset solar radiation transfer equation. If the current computational layer is the top layer, then the incident solar irradiance of the current computational layer atmosphere is the incident solar irradiance of the top layer of atmosphere.

[0080] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for correcting solar radiation at photovoltaic power plants based on numerical models as described in the above embodiments.

[0081] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for correcting solar radiation at photovoltaic power plants based on numerical models.

[0082] A fifth aspect of this application provides a computer program, which, when executed, is used to implement the above-described method for correcting solar radiation at photovoltaic power plants based on numerical models.

[0083] Therefore, this application has at least the following beneficial effects:

[0084] (1) By building a high-resolution numerical model system, it is possible to achieve fine simulation of various meteorological elements in the simulation area and accurately identify the state of the entire atmospheric layer above the photovoltaic power station; (2) By calculating the amount of solar radiation reduction by each layer of atmosphere on the radiation transmission path, it is possible to accurately correct the photovoltaic resources of the power station, improve the accuracy of photovoltaic resource prediction and reduce the calculation cost; (3) It can provide technical support and decision-making basis for the site selection, operation, power prediction and power generation efficiency improvement of the target photovoltaic power station, and has extremely high innovation and practical application value.

[0085] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0086] Figure 1 This is a flowchart of a method for correcting solar radiation at a photovoltaic power station based on a numerical model, according to an embodiment of this application.

[0087] Figure 2 This is a technical flowchart according to one embodiment of the present application;

[0088] Figure 3 This is a flowchart of an atmospheric state identification and photovoltaic power station solar radiation correction module according to an embodiment of this application;

[0089] Figure 4 This is a schematic diagram simulating cloud water content, disturbance wind vector, and terrain distribution in a region at a certain time in the afternoon according to an embodiment of this application;

[0090] Figure 5 This is a schematic diagram simulating snow content, disturbance wind vector, and terrain distribution in a simulated area at a certain time in the afternoon according to an embodiment of this application;

[0091] Figure 6 This is a schematic diagram of the graupel content, disturbance wind vector, and terrain distribution in a simulated area at a certain time in the afternoon according to an embodiment of this application;

[0092] Figure 7 This is a schematic diagram simulating rainfall content, disturbance wind vector, and terrain distribution in a region at a certain time in the afternoon according to an embodiment of this application;

[0093] Figure 8 This is a block diagram of a photovoltaic power station solar radiation correction device based on a numerical model, according to an embodiment of this application.

[0094] Figure 9 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0095] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0096] The following description, with reference to the accompanying drawings, illustrates a method and apparatus for correcting solar radiation at photovoltaic (PV) power plants based on numerical models. Addressing the issues mentioned in the background art, such as the lack of effective observation of gas composition, aerosol particle size and concentration, and cloud microphysical characteristics (phase state and content of water-bearing particles) in the atmosphere above PV power plants, the inability to effectively correct solar radiation prediction results by identifying different atmospheric states, resulting in low accuracy of PV predictions, and the insufficient ability to finely simulate the atmospheric state above PV power plants within the simulation area due to the generally coarse simulation resolution of global / regional numerical prediction models in related technologies, this application provides a method and apparatus for correcting solar radiation at PV power plants based on numerical models. A method for correcting solar radiation at photovoltaic power plants is proposed. In this method, the content of water-derived particles in each atmospheric layer above the target photovoltaic power plant is obtained based on an optimized WRF model. The current atmospheric state of each atmospheric layer and the attenuation correction coefficient of each atmospheric layer on solar radiation are determined. Using the attenuation correction coefficient of each atmospheric layer on solar radiation, the reduction of solar irradiance by each atmospheric layer along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power plant is calculated layer by layer. The final solar irradiance after reduction by the bottom atmosphere is obtained, and the actual solar irradiance received by the target photovoltaic power plant is corrected based on the final solar irradiance. This solves the problems in related technologies, such as the lack of effective observation of gas composition, aerosol particle size and concentration, and cloud microphysical characteristics (phase state and content of water particles in clouds) in the atmosphere above photovoltaic power stations, the inability to effectively correct the solar radiation prediction results of the power stations by identifying different atmospheric states, resulting in low accuracy of photovoltaic predictions for the power stations, and the insufficient ability to finely simulate the atmospheric state above photovoltaic power stations in the simulation area due to the generally coarse simulation resolution of global / regional numerical prediction models in related technologies.

[0097] Accurate prediction of photovoltaic power and output largely depends on accurate prediction of the actual amount of solar radiation received by the photovoltaic power station. During the downward transmission of solar radiation from the top of the atmosphere to the power station, it is subject to scattering and absorption by various atmospheric components (such as O3, CO2, and water vapor), aerosol particles, and cloud water particles. This reduces the actual amount of solar radiation reaching the power station. Therefore, it is necessary to accurately identify the state of the entire atmospheric layer above the power station and calculate the reduction in solar radiation by each atmospheric layer along the radiation transmission path. This allows for precise correction of the photovoltaic resources at the power station, improving the accuracy of photovoltaic resource prediction and providing technical support and decision-making basis for photovoltaic power station site selection, operation, power prediction, and improvement of power generation efficiency. Specific operational methods are discussed in the following examples.

[0098] like Figure 1The diagram shown is a flowchart of a method for correcting solar radiation at a photovoltaic power station based on a numerical model, according to an embodiment of this application.

[0099] like Figure 1 As shown, the method for correcting solar radiation at photovoltaic power plants based on numerical models includes the following steps:

[0100] In step S101, the content of water-based particles in each layer of atmosphere above the target photovoltaic power station is obtained based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area.

[0101] Optionally, in one embodiment of this application, before obtaining the content of water-based particles in each layer of atmosphere above the target photovoltaic power station based on the optimized WRF model, the method further includes: constructing a target simulation region centered on the target photovoltaic power station and obtaining basic data within the target simulation region; constructing a WRF model based on the basic data, and optimizing the WRF model by setting an optimal combination strategy of physical parameterization schemes to obtain an optimized WRF model; performing calculations based on the optimized WRF model, and obtaining the content of water-based particles in each layer of atmosphere above the target photovoltaic power station based on the calculation results.

[0102] Optionally, in one embodiment of this application, constructing a target simulation area centered on the target photovoltaic power station includes: setting a first preset number of nested patterns in the horizontal direction using a preset grid distribution centered on the target photovoltaic power station, and setting a second preset number of atmospheric layer distributions in the vertical direction using a hybrid vertical coordinate system; and obtaining the target simulation area based on the nested patterns and atmospheric layer distributions.

[0103] The preset grid distribution, the first preset quantity, and the second preset quantity can all be selected by those skilled in the art according to the actual simulation needs, and are not specifically limited here.

[0104] Specifically, in this embodiment of the application, a target simulation area is constructed with the target photovoltaic power station as the center, and basic data within the target simulation area is obtained. The basic data within the target simulation area may include initial field data and high-resolution terrain data.

[0105] It should be noted that the embodiments of this application use FNL (Final Reanalysis Data) reanalysis data, which is produced jointly by the National Center for Meteorological and Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) and is updated every 6 hours with a spatial resolution of 1°×1°, as the initial field of the numerical model. It adopts a relatively advanced global data assimilation system and the most complete database to perform quality control and assimilation processing on observation data from various sources, thereby obtaining a complete reanalysis data dataset. It not only contains a wide variety of meteorological elements and has data covering a large global area, but also can extend over a long period of time and is widely used in analysis and research.

[0106] Furthermore, due to the complex terrain of the simulation area, the default terrain data in the WRF model cannot clearly display the complete terrain within the simulation area, which will increase the calculation error. Therefore, this embodiment uses high-resolution terrain data instead of the default low-resolution terrain data in the model. Adding high-resolution terrain data to the WRF model can more accurately depict the terrain features within the simulation area, matching the high-resolution numerical model, thereby improving the accuracy of the simulation and making the simulation of meteorological elements under high-resolution conditions more reasonable.

[0107] Specifically, such as Figure 2 As shown, in this embodiment, the target photovoltaic power station is first set as the center of the target simulation area. A first preset number of nested patterns are set in the horizontal direction using a preset grid distribution (e.g., Arakawa C grid). A second preset number (i layers) of atmospheric layer distribution is set in the vertical direction using a hybrid vertical coordinate system. The hybrid vertical coordinate system is a terrain-following mass coordinate at the lower layers and is converted to isobaric surface coordinates at the upper layers. Preferably, in this embodiment, 5 nested patterns can be set in the horizontal direction and 71 atmospheric layer distributions can be set in the vertical direction, thereby obtaining the target simulation area based on the set 5 nested patterns and 71 atmospheric layer distributions.

[0108] Secondly, this application embodiment constructs a WRF model based on basic data, and optimizes the WRF model by setting an optimal physical parameterization scheme combination strategy to obtain an optimized WRF model. This optimized WRF model achieves the best simulation effect suitable for high-resolution numerical simulation of field stations. The optimal physical parameterization scheme combination strategy is shown in Table 1.

[0109] Table 1

[0110]

[0111]

[0112] Finally, after obtaining the optimized WRF model, this embodiment of the application performs calculations based on the optimized WRF model, and obtains the content of water-based particles in each layer of atmosphere above the target photovoltaic power station based on the calculation results.

[0113] In step S102, the current atmospheric state of each layer of atmosphere above the target photovoltaic power station is determined based on the content of water-based particles in each layer of atmosphere above the target photovoltaic power station, and the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station to solar radiation is determined based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station.

[0114] Optionally, in one embodiment of this application, determining the current atmospheric state of each atmospheric layer above the target photovoltaic power station based on the content of water-based particles in each atmospheric layer includes: obtaining the cloud droplet content in the target atmospheric layer; determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target atmospheric layer; if the cloud droplet content is greater than a first preset content threshold, then determining the current initial atmospheric state of the target layer as a cloudy state; if the cloud droplet content is less than or equal to the first preset content threshold, then determining the current initial atmospheric state of the target layer as a cloudless state.

[0115] The first preset content threshold can be set by those skilled in the art according to actual testing needs, or set through a limited number of simulations, and is not specifically limited here.

[0116] Specifically, based on the content of water-derived particles in each atmospheric layer above the target photovoltaic power station calculated using the optimized WRF model in this embodiment, the atmospheric state above the target photovoltaic power station is identified and analyzed layer by layer. This allows for the calculation of the total scattering reduction of solar radiation by the entire atmospheric layer above the target photovoltaic power station, ultimately yielding an accurate simulation result of the solar irradiance received by the target photovoltaic power station. Based on this simulation result, the actual solar irradiance received by the target photovoltaic power station is corrected. The water-derived particle content includes cloud droplet content Qc, ice crystal content Qi, raindrop content Qr, snow crystal content Qs, and graupel content Qg. Therefore, the atmospheric state of each atmospheric layer above the target photovoltaic power station and its reduction of solar irradiance are quantitatively analyzed based on the water-derived particle content in each layer.

[0117] Specifically, such as Figure 3As shown, based on the different effects and degrees of solar radiation scattering by different atmospheric components, the initial atmospheric state of each layer above the target photovoltaic power station can be divided into two conditions: cloudy and cloudless. Further, when the initial atmospheric state is cloudless, the current atmospheric state of each layer above the target photovoltaic power station can be divided into two types: clear sky (no aerosols or low aerosol content, mainly air molecules) and aerosol atmosphere (high aerosol content). When the initial atmospheric state is cloudy, based on the phase and content of the main water-forming particles within the clouds, the current atmospheric state of each layer above the target photovoltaic power station can be divided into three types: liquid phase cloud (clouds mainly composed of liquid phase water-forming particles (cloud droplets and raindrops)), ice phase cloud (clouds mainly composed of ice phase water-forming particles (ice crystals, snow, and graupel)), and mixed phase cloud (clouds with roughly equal contents of liquid and ice phase particles).

[0118] The initial atmospheric state of each layer of atmosphere above the target photovoltaic power station can be determined by the cloud droplet content in each layer of atmosphere above the target photovoltaic power station. Therefore, the initial atmospheric state of each layer of atmosphere above the target photovoltaic power station is obtained based on the cloud droplet content calculated by the optimized WRF model. That is, the top layer of atmosphere can be defined as the target layer atmosphere, and the initial atmospheric state of the target layer atmosphere is determined. First, the cloud droplet content in the target layer atmosphere is obtained, and the initial atmospheric state of the target layer is obtained based on the cloud droplet content. Second, when the cloud droplet content is greater than a first preset content threshold (e.g., 0.1), the initial atmospheric state of the target layer is determined to be a cloudy state. When the cloud droplet content is less than or equal to the first preset content threshold, the initial atmospheric state of the target layer is determined to be a cloudless state.

[0119] It should be noted that the target layer in this application embodiment can be the top layer (i.e., the first layer) above the target photovoltaic station, or any other layer. The target layer in this application embodiment is the top layer as an example, and there is no specific limitation.

[0120] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the method further includes: if the current initial atmospheric state of the target layer is a cloudless state, then determining whether the cloud droplet content in the target layer atmosphere is equal to a second preset content threshold; if the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold, then determining that the current atmospheric state of the target layer is a clear sky atmosphere; if the cloud droplet content in the target layer atmosphere is greater than the second preset content threshold and less than the first preset content threshold, then determining that the current atmospheric state of the target layer is an aerosol atmosphere.

[0121] The second preset content threshold can be set by those skilled in the art according to actual testing needs, or set through a limited number of simulations, and is not specifically limited here.

[0122] Specifically, after obtaining the current initial atmospheric state of the target layer in the embodiments of the present application, the current atmospheric state of the target layer is further determined based on the current initial atmospheric state of the target layer, that is, the current atmospheric state when the target layer is in a cloudy state and the current atmospheric state when the target layer is in a cloudless state.

[0123] Specifically, as Figure 3 shown, if the current initial atmospheric state of the target layer in the embodiments of the present application is a cloudless state, it is further determined whether the cloud droplet content in the atmosphere of the target layer is equal to the second preset content threshold (for example, 0). If the cloud droplet content in the atmosphere of the target layer is equal to the second preset content threshold, that is, when Qc = 0, it is determined that the current atmospheric state of the target layer is clear sky atmosphere; if the cloud droplet content in the atmosphere of the target layer is greater than the second preset content threshold and less than the first preset content threshold, that is, 0 < Qc < 0.1, it is determined that the current atmospheric state of the target layer is aerosol atmosphere.

[0124] Optionally, in an embodiment of the present application, after determining the current initial atmospheric state of the target layer according to the cloud droplet content in the atmosphere of the target layer, it further includes: if the current initial atmospheric state of the target layer is a cloudy state, obtain the ice crystal content, raindrop content, snow crystal content, and graupel content in the atmosphere of the target layer, and determine the current atmospheric state of the target layer according to the cloud droplet content, ice crystal content, raindrop content, snow crystal content, and graupel content; if the cloud droplet content is greater than the first preset content threshold and the raindrop content is greater than the first preset content threshold, it is determined that the current atmospheric state of the target layer is liquid-phase cloud; if both the ice crystal content and the snow crystal content are greater than the second preset content threshold and the graupel content is greater than the first preset content threshold, it is determined that the current atmospheric state of the target layer is ice-phase cloud; if the cloud droplet content, raindrop content, and graupel content are all greater than the first preset content threshold and the ice crystal content and the snow crystal content are all greater than the second preset content threshold, it is determined that the current atmospheric state of the target layer is mixed-phase cloud.

[0125] Specifically, as Figure 3As shown in this embodiment, if the initial atmospheric state of the target layer is a cloudy state, the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere are further obtained. If the cloud droplet content is greater than a first preset content threshold and the raindrop content is greater than the first preset content threshold, i.e., Qc>0.1 and Qr>0.1, then the current atmospheric state of the target layer is determined to be a liquid phase cloud. If the ice crystal content and snow crystal content are both greater than a second preset content threshold and the graupel content is greater than the first preset content threshold, i.e., Qi>0, Qs>0, and Qg>0.1, then the current atmospheric state of the target layer is determined to be an ice phase cloud. If the cloud droplet content, raindrop content, and graupel content are all greater than the first preset content threshold and the ice crystal content and snow crystal content are both greater than the second preset content threshold, i.e., Qc>0.1, Qi>0, Qs>0, Qr>0.1, and Qg>0.1, then the current atmospheric state of the target layer is determined to be a mixed phase cloud.

[0126] The content of water-forming particles and the corresponding atmospheric states in each atmospheric layer above the aforementioned target photovoltaic power stations are shown in Table 2.

[0127] Table 2

[0128]

[0129] Optionally, in one embodiment of this application, determining the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station for solar radiation based on the current atmospheric state of each atmospheric layer above the target photovoltaic power station includes: if the current atmospheric state is clear sky, then determining a first attenuation correction coefficient of the target atmospheric layer for solar radiation based on clear sky; if the current atmospheric state is aerosol atmosphere, then determining a second attenuation correction coefficient of the target atmospheric layer for solar radiation based on aerosol atmosphere; if the current atmospheric state is liquid phase cloud, ice phase cloud, or mixed phase cloud, then determining a third attenuation correction coefficient of the target atmospheric layer for solar radiation based on liquid phase cloud, ice phase cloud, or mixed phase cloud.

[0130] Specifically, in this embodiment, if the current atmospheric state of the target layer above the target photovoltaic power station is clear air (Qc = 0), the atmosphere is dominated by air molecules, whose particle radii are much smaller than the radiation wavelength. At this time, the atmospheric scattering attenuation of solar radiation follows Rayleigh scattering. In Rayleigh scattering, the proportion of scattered light in the forward and backward directions is roughly equal, resulting in a small reduction in solar radiation. Rayleigh scattering also makes clear air appear light blue. Therefore, under clear air conditions, the reduction in solar radiation is minimal, resulting in the highest solar irradiance and photovoltaic power generation efficiency for the target photovoltaic power station. Thus, under clear air conditions, the first attenuation correction coefficient for solar radiation at the target layer atmosphere can be determined based on the clear air conditions, defined as k. ex =Cλ -4 Where C = 1.0563 × 10-30 m 3 λ is the radiation wavelength.

[0131] Furthermore, if the current atmospheric state of the target layer above the target photovoltaic power station is an aerosol atmosphere, containing a significant amount of aerosol particles with radii approximately equal to the radiation wavelength, but whose size and quantity are insufficient to form clouds, then the atmospheric scattering of solar radiation is Mie scattering. In Mie scattering, the proportion of forward-scattered light in the total scattered light is relatively large, and the degree of scattering of solar radiation is related to the size of the aerosol particles; the larger the aerosol particles, the stronger the scattering effect on solar radiation. When there are many aerosol particles in the atmosphere, the sky often appears grayish-white. Therefore, under aerosol atmospheric conditions, the reduction of solar radiation by the atmosphere is greater than under clear-sky conditions, which has a certain impact on the power output of the target photovoltaic power station. Thus, a second attenuation correction coefficient for solar radiation by the target layer atmosphere can be determined based on the aerosol atmosphere, defined as k. ex =Cλ -b Where C = 1.0563 × 10 -30 m 3 λ is the radiation wavelength, and the value of b is related to the size of the aerosol particles. For general aerosols, the value of b is approximately between 1 and 2.

[0132] Furthermore, when clouds form over the target photovoltaic (PV) power station, the scattering by cloud droplets and ice crystals (water-bearing particles) makes the cloud surface a strong reflector. This further increases the reduction of solar radiation reaching the target PV power station, making accurate prediction of PV resources more difficult and reducing the accuracy of PV output prediction. In addition, clouds may form short-term precipitation events near the power station, further impacting the station's solar radiation reception. At the microscopic level, the degree to which clouds weaken solar radiation is closely related to the type (phase) and content (cloud water content) of water-bearing particles within the cloud. When the current atmospheric state of the target layer above the target photovoltaic power station is a liquid phase cloud, the cloud is mainly composed of liquid phase water particles (cloud droplets and raindrops), also known as a warm cloud. The cloud body is mainly distributed below the 0°C layer, the overall cloud height is low, and the development is relatively shallow. Its reduction of solar radiation is lower than that of ice phase clouds and mixed phase clouds. When the current atmospheric state of the target layer above the target photovoltaic power station is an ice phase cloud, the cloud is mainly composed of ice phase water particles (ice crystals, snow, and graupel), also known as a cold cloud. The cloud body is mainly distributed above the 0°C layer, and the cloud top temperature can be as low as -50°C. Under natural conditions, ice-phase clouds and liquid-phase clouds are relatively rare, with mixed-phase clouds being the dominant type. When the current atmospheric state of the target layer above the target photovoltaic power station is a mixed-phase cloud, the reduction of solar radiation by the mixed-phase cloud is the greatest. The content of liquid-phase and ice-phase particles in the cloud is roughly equal, the cloud body is deep and the cloud volume is huge, with horizontal and vertical scales generally 5-6 km, and some cumulonimbus clouds can reach tens of kilometers. In the upper layer of the cloud, ice-phase particles (ice crystals, snow crystals) are the main components, while in the middle layer, supercooled water droplets (cloud droplets above the 0°C layer that have not frozen and exist in liquid form) and graupel particles (solid particles formed by the collision of supercooled water droplets with ice crystals falling from the upper layer) are the main components. In the lower layer of the cloud (below the 0°C layer), liquid-phase particles (cloud droplets, raindrops) are the main components. Therefore, the type and content of water-phase particles contained in the cloud vary at different altitudes, which also reduces solar radiation layer by layer, resulting in less solar radiation reaching the ground surface and greatly affecting the power output efficiency of the target photovoltaic power station. Therefore, the third attenuation correction factor for solar radiation in the target atmospheric layer under liquid phase clouds, ice phase clouds, or mixed phase clouds can be defined as k. ex =128q w , where q w Water content of a single cloud layer (unit: g / m³) 3 ), that is, the sum of the contents of all water-forming substances in a single layer, i.e., q w =ρ w *(Qc+Qr)+ρ i *(Qi+Qs+Qg), ρ w ρ i These are the densities of liquid water and solid water, respectively.

[0133] In step S103, the reduction of solar irradiance by each layer of atmosphere above the target photovoltaic power station is calculated layer by layer using the attenuation correction coefficient of each layer of atmosphere on solar radiation. The final solar irradiance after reduction by the bottom atmosphere is obtained, and the actual solar irradiance received by the target photovoltaic power station is corrected based on the final solar irradiance after reduction by the bottom atmosphere.

[0134] Optionally, in one embodiment of this application, the reduction in solar irradiance of each atmospheric layer along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station is calculated layer by layer using the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station. This yields the final solar irradiance after reduction by the bottom atmosphere. The actual solar irradiance received by the target photovoltaic power station is then corrected based on this final solar irradiance after reduction by the bottom atmosphere. This includes: obtaining the incident solar irradiance at the top of the atmosphere; and sequentially calculating the incident solar irradiance and the reduced solar irradiance of each atmospheric layer according to the order from the top to the bottom of the atmosphere, based on the incident solar irradiance at the top of the atmosphere and a preset solar radiation transmission equation. The solar irradiance is obtained by reducing the solar irradiance after the reduction by the lower atmosphere. The actual solar irradiance received by the target photovoltaic power station is corrected based on the final solar irradiance after the reduction by the lower atmosphere. The incident solar irradiance of the current calculation layer atmosphere is the solar irradiance after reduction by the upper atmosphere. The solar irradiance after reduction by the current calculation layer atmosphere is calculated by inputting the incident solar irradiance of the current calculation layer atmosphere and the reduction correction coefficient of the current calculation layer atmosphere to the preset solar radiation transmission equation. If the current calculation layer is the top layer, the incident solar irradiance of the current calculation layer atmosphere is the incident solar irradiance of the top atmosphere.

[0135] The current calculation layer atmosphere is any layer of the entire atmosphere above the target photovoltaic power station, that is, any layer from the top atmosphere to the bottom atmosphere above the target photovoltaic power station. The preset solar radiation transfer equation can be selected by those skilled in the art according to actual test requirements, and no specific limitation is made here.

[0136] Specifically, in this embodiment, the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station is determined based on the current atmospheric state of each atmospheric layer. Then, using this attenuation correction coefficient, the reduction in solar irradiance by each atmospheric layer along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station is calculated layer by layer. Finally, the final solar irradiance after reduction by the bottom atmosphere is obtained. The solar radiation transmission equation in the atmosphere is shown below:

[0137]

[0138] In this embodiment, the atmosphere is arranged with 71 layers in the vertical direction. E(i) is the solar irradiance E0(i) incident from the top of the i-th layer of atmosphere, which is weakened by the atmosphere and reaches the bottom of the i-th layer. At the same time, E(i) is also the solar irradiance E0(i+1) incident from the top of the (i+1)-th layer of atmosphere (the layer below the i-th layer). This process is repeated until the solar irradiance at the bottom of the last layer of atmosphere, i.e., E(i), where i = 70, is the solar irradiance finally received by the target photovoltaic power station. The term represents the total attenuation of solar radiation by the atmosphere due to scattering, where the thickness of the i-th atmospheric layer is l.

[0139] Specifically, in this embodiment of the application, the incident solar irradiance and the reduced solar irradiance of each atmospheric layer are calculated sequentially from the top layer to the bottom layer, based on the incident solar irradiance of the top layer and the preset solar irradiance transfer equation, until the final solar irradiance after reduction by the bottom layer is obtained.

[0140] In other words, firstly, the incident solar irradiance at the top of the atmosphere is obtained. The incident solar irradiance at the top of the atmosphere and the attenuation correction coefficient of the solar radiation at the top of the atmosphere are input into a preset solar radiation transfer equation. The solar irradiance after reduction by the top of the atmosphere is calculated. The solar irradiance after reduction by the top of the atmosphere is then used as the incident solar irradiance of the next layer below the top of the atmosphere, i.e., the second layer. The incident solar irradiance of the second layer and the attenuation correction coefficient of the solar radiation at the second layer are input into the preset solar radiation transfer equation. The solar irradiance after reduction by the second layer is calculated. This process is repeated until the final solar irradiance after reduction by the bottom atmosphere is obtained. The actual solar irradiance received by the target photovoltaic power station is then corrected based on the final solar irradiance after reduction by the bottom atmosphere.

[0141] For example, this application embodiment can automatically calculate the content of five types of aqueous particles in the target simulation area layer by layer from the top of the atmosphere downwards in the vertical direction. Taking the top atmosphere, i.e. the first layer of atmosphere, as an example, this application embodiment determines that the first layer of atmosphere is a clear sky atmosphere based on the judgment conditions in Table 2. At this time, under the clear sky atmosphere condition, the atmospheric attenuation correction coefficient for solar radiation can be obtained as k. ex =Cλ -4Substituting the solar irradiance E0(0) incident on the first layer of atmosphere (known) and the weakening correction coefficient into the aforementioned preset solar radiation transmission equation, the solar irradiance E(0) reaching the bottom of the first layer of atmosphere after weakening by the first layer of atmosphere is calculated. The solar irradiance E(0) at the bottom of the first layer of atmosphere is then used as the solar irradiance E0(1) incident on the second layer of atmosphere. This process continues vertically from top to bottom until the solar irradiance E(70) at the bottom of the last layer of atmosphere is calculated. This solar irradiance is then used as the final solar irradiance of the target photovoltaic power station after being reduced by the bottom layer of atmosphere. The actual solar irradiance received by the target photovoltaic power station is then corrected based on the final solar irradiance after being reduced by the bottom layer of atmosphere.

[0142] In summary, to facilitate a clearer understanding of the simulation scheme of the embodiments of this application by those skilled in the art, a specific embodiment will be discussed below.

[0143] This application's embodiments use a Python meteorological data visualization program to process and plot the simulation results. For example... Figure 4 As shown, the spatial distribution of cloud water content Qc above the station in the simulated area at a certain time in the afternoon is shown. At this time, there is abundant supercooled cloud water in the afternoon convective clouds. There are two high value centers of supercooled cloud water, located at 6.5km in the 0℃ to -10℃ layer and near 8km in the -10℃ to -20℃ layer. The large amount of supercooled cloud water in the clouds is conducive to the rapid growth of ice particles.

[0144] Furthermore, such as Figure 5 and Figure 6 As shown, in the stronger convective clouds in the afternoon, the ice crystal content is relatively small and located at higher levels, resulting in a relatively low snow content in the clouds. At this time, the graupel content in the clouds increases rapidly, with high graupel content appearing in areas of high supercooled cloud water, reaching a maximum of 1.5 g / kg. -1 This indicates that supercooled cloud water plays an important role in the formation of graupel particles, and that the ice phase process in the cloud is relatively strong.

[0145] like Figure 7 As shown, this is the afternoon convection phase, with rainfall distributed below -10°C. The area with the highest rainfall content is located near the zero-degree layer, at 0.6 g / kg. -1 The clouds contain a large amount of supercooled rainwater.

[0146] In summary, at this point, convective clouds have formed over the target simulation area, satisfying the conditions Qc>0.1, Qi>0, Qs>0, Qr>0.1, and Qg>0.1. This indicates that the atmosphere is in a mixed-phase cloud state, with the cloud height reaching approximately 9 km. Above 9 km, Qc=0, indicating that the upper atmosphere is in a clear-sky state. Subsequently, the solar radiation correction module of the target photovoltaic power station calculates the reduction of solar radiation by each layer of the atmosphere along the radiation transmission path according to the preset solar radiation transmission equation. Finally, the accurate correction result of the actual solar radiation irradiance received by the target photovoltaic power station can be obtained.

[0147] Therefore, the embodiments of this application have the following beneficial effects:

[0148] (1) Based on the problem that the accuracy of photovoltaic power and output prediction is generally low, this application proposes a method for correcting the solar radiation of photovoltaic power plants based on numerical models. This method can accurately identify the state of the entire atmosphere above the power plant and calculate the reduction of solar radiation by each layer of atmosphere along the radiation transmission path, so as to achieve accurate correction of photovoltaic resources of the power plant, improve the accuracy of photovoltaic resource prediction, and provide technical support and decision-making basis for photovoltaic power plant site selection, operation, power prediction, and power generation efficiency improvement.

[0149] (2) Based on the results of high-resolution numerical models, the embodiments of this application can innovatively identify the phase state and content of atmospheric components, aerosol particles and major water particles in the entire life cycle of clouds, thereby enabling accurate correction of the prediction results of photovoltaic resources at the site, which has high innovation and practicality.

[0150] (3) The embodiments of this application use a high-resolution numerical simulation method with an innermost resolution of up to 333m, which realizes the fine simulation of various meteorological elements in the simulation area, and can accurately identify the atmospheric state above the station and accurately correct the amount of solar radiation received by the station to make up for the deficiencies of observation methods. It has high research and application value.

[0151] According to the numerical model-based solar radiation correction method for photovoltaic power plants proposed in this application, the content of water-derived particles in each atmospheric layer above the target photovoltaic power plant is obtained based on the optimized WRF model. The current atmospheric state of each atmospheric layer and the attenuation correction coefficient of each atmospheric layer on solar radiation are determined. The attenuation correction coefficient of each atmospheric layer on solar radiation is used to calculate the reduction of solar irradiance of each atmospheric layer on the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power plant layer by layer. The final solar irradiance after reduction by the bottom atmosphere is obtained, and the actual solar irradiance received by the target photovoltaic power plant is corrected according to the final solar irradiance. This solves the problems in related technologies, such as the lack of effective observation of gas composition, aerosol particle size and concentration, and cloud microphysical characteristics (phase state and content of water particles in clouds) in the atmosphere above photovoltaic power stations, the inability to effectively correct the solar radiation prediction results of the power stations by identifying different atmospheric states, resulting in low accuracy of photovoltaic predictions for the power stations, and the insufficient ability to finely simulate the atmospheric state above photovoltaic power stations in the simulation area due to the generally coarse simulation resolution of global / regional numerical prediction models in related technologies.

[0152] Next, referring to the accompanying drawings, a control device for a photovoltaic power station solar radiation correction device based on a numerical model, according to an embodiment of this application, is described.

[0153] Figure 8 This is a block diagram of a photovoltaic power station solar radiation correction device based on a numerical model, according to an embodiment of this application.

[0154] like Figure 8 As shown, the solar radiation correction device 10 for photovoltaic power plants based on numerical models includes: a water content acquisition module 100, an atmospheric state determination module 200, and a target photovoltaic power plant solar radiation correction module 300.

[0155] Among them, the water content acquisition module 100 is used to acquire the content of water particles in each layer of atmosphere above the target photovoltaic station based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area.

[0156] Atmospheric state determination module 200 is used to determine the current atmospheric state of each layer of atmosphere above the target photovoltaic power station based on the content of water particles in each layer of atmosphere above the target photovoltaic power station, and to determine the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station to solar radiation based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station.

[0157] The target photovoltaic power station solar radiation correction module 300 is used to calculate the reduction of solar irradiance by each layer of atmosphere along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station by using the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station. The module obtains the final solar irradiance after reduction by the bottom atmosphere and corrects the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the bottom atmosphere.

[0158] Optionally, in one embodiment of this application, before obtaining the content of water-based particles in each atmospheric layer above the target photovoltaic power station based on the optimized WRF model, the water-based particle content acquisition module 100 further includes:

[0159] The target simulation area setting and basic data acquisition unit is used to construct the target simulation area with the target photovoltaic power station as the center and acquire the basic data within the target simulation area;

[0160] The model building and tuning unit is used to build a WRF model based on basic data, and to tune and optimize the WRF model by setting the optimal combination strategy of physical parameterization schemes to obtain the optimized WRF model. Calculations are performed based on the optimized WRF model, and the content of water particles in each layer of atmosphere above the target photovoltaic power station is obtained according to the calculation results.

[0161] Optionally, in one embodiment of this application, the target simulation region setting and basic data acquisition unit includes:

[0162] The target simulation area division unit is used to set a first preset number of nested patterns in the horizontal direction with the target photovoltaic power station as the center and a second preset number of atmospheric layer distributions in the vertical direction using a hybrid vertical coordinate system.

[0163] The simulation region acquisition unit obtains the target simulation region based on the nesting pattern and atmospheric layer distribution.

[0164] Optionally, in one embodiment of this application, the atmospheric state determination module 200 includes:

[0165] The cloud droplet content acquisition unit is used to acquire the cloud droplet content in the target atmospheric layer.

[0166] The initial atmospheric state determination unit is used to determine the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere.

[0167] The cloud state determination unit is used to determine that the current initial atmospheric state of the target layer is a cloud state if the cloud droplet content is greater than a first preset content threshold.

[0168] The cloudless state determination unit is used to determine that the current initial atmospheric state of the target layer is cloudless if the cloud droplet content is less than or equal to a first preset content threshold.

[0169] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the cloudless state determination unit includes:

[0170] The cloud droplet content determination subunit is used to determine whether the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold if the current initial atmospheric state of the target layer is cloudless.

[0171] The clear sky atmosphere determination subunit is used to determine the current atmospheric state of the target layer as clear sky if the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold.

[0172] The aerosol atmosphere determination subunit is used to determine the current atmospheric state of the target layer as an aerosol atmosphere if the cloud droplet content in the target layer is greater than a second preset content threshold and less than a first preset content threshold.

[0173] Optionally, in one embodiment of this application, after determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, a cloud state determination unit is provided, including:

[0174] The current atmospheric state determination unit is used to obtain the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere if the current initial atmospheric state of the target layer is a cloudy state, and to determine the current atmospheric state of the target layer based on the cloud droplet content, ice crystal content, raindrop content, snow crystal content, and graupel content.

[0175] The liquid cloud determination subunit is used to determine the current atmospheric state of the target layer as a liquid cloud if the cloud droplet content is greater than a first preset content threshold and the raindrop content is greater than a first preset content threshold.

[0176] The ice phase cloud determination subunit is used to determine the current atmospheric state of the target layer as ice phase cloud if both the ice crystal content and snow crystal content are greater than the second preset content threshold and the graupel content is greater than the first preset content threshold.

[0177] The mixed-phase cloud determination subunit is used to determine the current atmospheric state of the target layer as a mixed-phase cloud if the cloud droplet content, raindrop content, and graupel content are all greater than the first preset content threshold, and the ice crystal content and snow crystal content are all greater than the second preset content threshold.

[0178] Optionally, in one embodiment of this application, the atmospheric state determination module 200 includes:

[0179] The first weakening correction coefficient determination unit is used to determine the first weakening correction coefficient of the target layer atmosphere on solar radiation based on the clear sky atmosphere if the current atmospheric state is clear sky atmosphere.

[0180] The second weakening correction coefficient determination unit is used to determine the second weakening correction coefficient of the target layer atmosphere on solar radiation based on the aerosol atmosphere if the current atmospheric state is an aerosol atmosphere.

[0181] The third weakening correction coefficient determination unit is used to determine the third weakening correction coefficient of the target layer atmosphere to solar radiation based on the liquid phase cloud, ice phase cloud or mixed phase cloud if the current atmospheric state is liquid phase cloud, ice phase cloud or mixed phase cloud.

[0182] Optionally, in one embodiment of this application, the solar radiation correction model 300 for the target photovoltaic power station includes:

[0183] The solar irradiance acquisition unit is used to acquire the incident solar irradiance in the top layer of the atmosphere.

[0184] The solar irradiance calculation unit is used to calculate the incident solar irradiance and the reduced solar irradiance of each atmospheric layer in sequence from the top layer to the bottom layer, based on the incident solar irradiance of the top layer and the preset solar irradiance transfer equation, so as to obtain the final solar irradiance after reduction by the bottom layer of the atmosphere.

[0185] The solar irradiance correction unit is used to correct the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the lower atmosphere.

[0186] The incident solar irradiance of the current computational layer is the solar irradiance after reduction by the layer above it. The reduced solar irradiance of the current computational layer is calculated by inputting the incident solar irradiance of the current computational layer and the reduction correction coefficient of the current computational layer to the preset solar radiation transfer equation. If the current computational layer is the top layer, the incident solar irradiance of the current computational layer is the incident solar irradiance of the top layer of the atmosphere.

[0187] According to the numerical model-based solar radiation correction device for photovoltaic power plants proposed in this application, the content of water-derived particles in each atmospheric layer above the target photovoltaic power plant is obtained based on the optimized WRF model. The current atmospheric state of each atmospheric layer and the attenuation correction coefficient of each atmospheric layer on solar radiation are determined. The attenuation correction coefficient of each atmospheric layer on solar radiation is used to calculate the reduction of solar irradiance of each atmospheric layer on the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power plant layer by layer. The final solar irradiance after reduction by the bottom atmosphere is obtained, and the actual solar irradiance received by the target photovoltaic power plant is corrected according to the final solar irradiance. This solves the problems in related technologies, such as the lack of effective observation of gas composition, aerosol particle size and concentration, and cloud microphysical characteristics (phase state and content of water particles in clouds) in the atmosphere above photovoltaic power stations, the inability to effectively correct the solar radiation prediction results of the power stations by identifying different atmospheric states, resulting in low accuracy of photovoltaic predictions for the power stations, and the insufficient ability to finely simulate the atmospheric state above photovoltaic power stations in the simulation area due to the generally coarse simulation resolution of global / regional numerical prediction models in related technologies.

[0188] Figure 9 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0189] The memory 901, the processor 902, and the computer program stored on the memory 901 and capable of running on the processor 902.

[0190] When the processor 902 executes the program, it implements the method for correcting solar radiation at photovoltaic power stations based on numerical models provided in the above embodiments.

[0191] Furthermore, electronic devices also include:

[0192] Communication interface 903 is used for communication between memory 901 and processor 902.

[0193] The memory 901 is used to store computer programs that can run on the processor 902.

[0194] The memory 901 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0195] If the memory 901, processor 902, and communication interface 903 are implemented independently, then the communication interface 903, memory 901, and processor 902 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0196] Optionally, in a specific implementation, if the memory 901, processor 902, and communication interface 903 are integrated on a single chip, then the memory 901, processor 902, and communication interface 903 can communicate with each other through an internal interface.

[0197] The processor 902 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0198] This application also provides a computer program that can run computer instructions. When these computer instructions are executed by a processor, they implement the method for correcting solar radiation at photovoltaic power stations based on numerical models provided in this application.

[0199] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for correcting solar radiation at photovoltaic power stations based on numerical models.

[0200] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0201] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0202] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0203] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). In addition, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically by optically scanning paper or other media, then editing, interpreting or otherwise processing them as necessary, and then storing them in computer memory.

[0204] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0205] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0206] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0207] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for correcting solar radiation at photovoltaic power plants based on numerical models, characterized in that, Includes the following steps: The content of water-based particles in each atmospheric layer above the target photovoltaic power station is obtained based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area. The current atmospheric state of each layer of atmosphere above the target photovoltaic power station is determined based on the content of water-based particles in each layer of atmosphere above the target photovoltaic power station, and the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station to solar radiation is determined based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station. Using the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station, the reduction in solar irradiance along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station is calculated layer by layer, resulting in the final solar irradiance after reduction by the bottom atmosphere. The actual solar irradiance received by the target photovoltaic power station is then corrected based on this final solar irradiance after reduction by the bottom atmosphere. The step of determining the attenuation correction coefficient of solar radiation for each atmospheric layer above the target photovoltaic power station based on the current atmospheric state of each atmospheric layer above the target photovoltaic power station includes: If the current atmospheric state is clear sky, then a first attenuation correction coefficient for solar radiation in the target layer atmosphere is determined based on the clear sky atmosphere; wherein, The first weakening correction factor is: k ex =Cλ -4 Where, k ex The first weakening correction coefficient is C = 1.0563 × 10⁻⁶. -30 m 3 λ is the radiation wavelength; If the current atmospheric state is an aerosol atmosphere, then a second attenuation correction coefficient for solar radiation in the target layer atmosphere is determined based on the aerosol atmosphere; wherein, The second weakening correction factor is: k ex =Cλ -b Where, k ex The second weakening correction factor is C = 1.0563 × 10⁻⁶. -30 m 3 λ is the radiation wavelength, and the value of b is related to the size of the aerosol particles. For general aerosols, the value of b is between 1 and 2. If the current atmospheric state is a liquid-phase cloud, an ice-phase cloud, or a mixed-phase cloud, then a third attenuation correction factor for solar radiation in the target atmospheric layer is determined based on the liquid-phase cloud, the ice-phase cloud, or the mixed-phase cloud; wherein, The third weakening correction factor is: k ex =128q w Where, k ex q is the third weakening correction coefficient. w q represents the water content of a single cloud layer. w The unit is g / m 3 That is, the sum of the contents of all water-forming substances in a single layer, i.e.: q w =ρ w ×(Qc+Qr)+ρ i ×(Qi+Qs+Qg), where ρ w ρ i Qc represents the density of liquid water and solid water, Qr represents the cloud droplet content, Qr represents the raindrop content, Qi represents the ice crystal content, Qs represents the snow crystal content, and Qg represents the graupel content. The process involves calculating the reduction in solar irradiance by each atmospheric layer along the solar radiation transmission path from the top of the atmosphere to the target photovoltaic power station using the attenuation correction coefficient of each atmospheric layer above the target photovoltaic power station. This yields the final solar irradiance after attenuation by the bottom atmosphere. The actual solar irradiance received by the target photovoltaic power station is then corrected based on this final solar irradiance after attenuation by the bottom atmosphere, including: Obtain the incident solar radiation irradiance of the upper atmosphere; Following the order from the top to the bottom of the atmosphere, based on the incident solar irradiance of the top atmosphere and the preset solar radiation transfer equation, the incident solar irradiance and the reduced solar irradiance of each layer of the atmosphere are calculated sequentially to obtain the final solar irradiance after reduction by the bottom atmosphere. The actual solar irradiance received by the target photovoltaic power station is corrected based on the final solar irradiance after reduction by the lower atmosphere. Wherein, the incident solar irradiance of the current computational layer atmosphere is the reduced solar irradiance of the layer preceding it. This reduced solar irradiance is calculated by inputting the incident solar irradiance of the current computational layer atmosphere and the attenuation correction coefficient of the current computational layer atmosphere into the preset solar radiation transport equation. Wherein, if the current computational layer is the top layer, then the incident solar irradiance of the current computational layer atmosphere is the incident solar irradiance of the top layer atmosphere. The preset solar radiation transfer equation is as follows: Where E(i) is the solar irradiance incident from the top of the i-th atmospheric layer, E0(i) is the solar irradiance reaching the bottom of the i-th atmospheric layer after being weakened by the atmosphere, and E(i) is also the solar irradiance E0(i+1) incident from the top of the (i+1)-th atmospheric layer, where the (i+1)-th layer is the layer below the i-th atmospheric layer. The total attenuation of solar radiation by the atmosphere due to scattering is given by the thickness of the i-th atmospheric layer. .

2. The method according to claim 1, characterized in that, Before obtaining the content of water-based particles in each atmospheric layer above the target photovoltaic power station based on the optimized WRF model, the following steps are also included: A target simulation area is constructed with the target photovoltaic power station as the center, and basic data within the target simulation area is obtained; A WRF model is constructed based on the aforementioned basic data, and the WRF model is optimized by setting the optimal combination strategy of physical parameterization schemes to obtain an optimized WRF model. Calculations are performed based on the optimized WRF model, and the content of water-based particles in each layer of atmosphere above the target photovoltaic power station is obtained according to the calculation results.

3. The method according to claim 2, characterized in that, The construction of the target simulation area centered on the target photovoltaic power station includes: Centered on the target photovoltaic power station, a first preset number of nested patterns are set in the horizontal direction using a preset grid distribution, and a second preset number of atmospheric layer distributions are set in the vertical direction using a hybrid vertical coordinate system. The target simulation region is obtained based on the nesting pattern and the atmospheric layer distribution.

4. The method according to claim 1, characterized in that, The step of determining the current atmospheric state of each atmospheric layer above the target photovoltaic power station based on the content of water-based particles in each atmospheric layer above the target photovoltaic power station includes: Obtain the cloud droplet content in the target atmospheric layer; The current initial atmospheric state of the target layer is determined based on the cloud droplet content in the target layer atmosphere. If the cloud droplet content is greater than the first preset content threshold, then the current initial atmospheric state of the target layer is determined to be a cloudy state. If the cloud droplet content is less than or equal to the first preset content threshold, then the current initial atmospheric state of the target layer is determined to be cloudless.

5. The method according to claim 4, characterized in that, After determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the method further includes: If the initial atmospheric state of the target layer is cloudless, then determine whether the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold. If the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold, then the current atmospheric state of the target layer is determined to be clear sky. If the cloud droplet content in the target layer is greater than the second preset content threshold and less than the first preset content threshold, then the current atmospheric state of the target layer is determined to be an aerosol atmosphere.

6. The method according to claim 4, characterized in that, After determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the method further includes: If the initial atmospheric state of the target layer is cloudy, then the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere are obtained, and the current atmospheric state of the target layer is determined based on the cloud droplet content, the ice crystal content, the raindrop content, the snow crystal content, and the graupel content. If the cloud droplet content is greater than the first preset content threshold, and the raindrop content is greater than the first preset content threshold, then the current atmospheric state of the target layer is determined to be a liquid cloud. If both the ice crystal content and the snow crystal content are greater than the second preset content threshold, and the graupel content is greater than the first preset content threshold, then the current atmospheric state of the target layer is determined to be an ice phase cloud. If the cloud droplet content, raindrop content, and graupel content are all greater than the first preset content threshold, and the ice crystal content and snow crystal content are all greater than the second preset content threshold, then the current atmospheric state of the target layer is determined to be a mixed phase cloud.

7. A solar radiation correction device for photovoltaic power plants based on numerical models, characterized in that, include: The water content acquisition module is used to acquire the content of water particles in each layer of atmosphere above the target photovoltaic power station based on the optimized WRF model. The optimized WRF model is obtained by optimizing the WRF model constructed based on the basic data in the target simulation area. The atmospheric state determination module is used to determine the current atmospheric state of each layer of atmosphere above the target photovoltaic power station based on the content of water-based particles in each layer of atmosphere above the target photovoltaic power station, and to determine the attenuation correction coefficient of each layer of atmosphere above the target photovoltaic power station on solar radiation based on the current atmospheric state of each layer of atmosphere above the target photovoltaic power station. The target photovoltaic (PV) power plant solar radiation correction module is used to calculate, layer by layer, the reduction in solar irradiance along the solar radiation transmission path from the top of the atmosphere to the target PV power plant using the attenuation correction coefficient of each atmospheric layer above the target PV power plant. This yields the final solar irradiance after reduction by the bottom atmosphere, and the module then corrects the actual solar irradiance received by the target PV power plant based on this final solar irradiance. The atmospheric state determination module includes: The first attenuation correction coefficient determination unit is used to determine, if the current atmospheric state is clear air, a first attenuation correction coefficient of the target layer atmosphere for solar radiation based on the clear air atmosphere; wherein, The first weakening correction factor is: k ex =Cλ -4 Where, k ex The first weakening correction coefficient is C = 1.0563 × 10⁻⁶. -30 m 3 λ is the radiation wavelength; The second attenuation correction coefficient determination unit is used to determine, if the current atmospheric state is an aerosol atmosphere, a second attenuation correction coefficient of the target layer atmosphere on solar radiation based on the aerosol atmosphere; wherein... The second weakening correction factor is: k ex =Cλ -b Where, k ex The second weakening correction factor is C = 1.0563 × 10⁻⁶. -30 m 3 λ is the radiation wavelength, and the value of b is related to the size of the aerosol particles. For general aerosols, the value of b is between 1 and 2. The third attenuation correction coefficient determination unit is used to determine the third attenuation correction coefficient of the target atmospheric layer on solar radiation based on the liquid-phase cloud, the ice-phase cloud, or the mixed-phase cloud if the current atmospheric state is a liquid-phase cloud, the ice-phase cloud, or the mixed-phase cloud; wherein, The third weakening correction factor is: k ex =128q w Where, k ex q is the third weakening correction coefficient. w q represents the water content of a single cloud layer. w The unit is g / m 3 That is, the sum of the contents of all water-forming substances in a single layer, i.e.: q w =ρ w ×(Qc+Qr)+ρ i ×(Qi+Qs+Qg), where ρ w ρ i Qc represents the density of liquid water and solid water, Qr represents the cloud droplet content, Qr represents the raindrop content, Qi represents the ice crystal content, Qs represents the snow crystal content, and Qg represents the graupel content. The solar radiation correction module for the target photovoltaic power station includes: A solar radiation irradiance acquisition unit is used to acquire the incident solar radiation irradiance of the top layer of the atmosphere; The solar irradiance calculation unit is used to calculate the incident solar irradiance and the reduced solar irradiance of each layer of the atmosphere in sequence from the top layer to the bottom layer of the atmosphere, based on the incident solar irradiance of the top layer of the atmosphere and the preset solar irradiance transfer equation, so as to obtain the final solar irradiance after reduction by the bottom layer of the atmosphere. A solar irradiance correction unit is used to correct the actual solar irradiance received by the target photovoltaic power station based on the final solar irradiance after reduction by the lower atmosphere. Wherein, the incident solar irradiance of the current computational layer atmosphere is the reduced solar irradiance of the layer preceding it. This reduced solar irradiance is calculated by inputting the incident solar irradiance of the current computational layer atmosphere and the attenuation correction coefficient of the current computational layer atmosphere into the preset solar radiation transport equation. Wherein, if the current computational layer is the top layer, then the incident solar irradiance of the current computational layer atmosphere is the incident solar irradiance of the top layer atmosphere. The preset solar radiation transfer equation is as follows: Where E(i) is the solar irradiance incident from the top of the i-th atmospheric layer, E0(i) is the solar irradiance reaching the bottom of the i-th atmospheric layer after being weakened by the atmosphere, and E(i) is also the solar irradiance E0(i+1) incident from the top of the (i+1)-th atmospheric layer, where the (i+1)-th layer is the layer below the i-th atmospheric layer. The total attenuation of solar radiation by the atmosphere due to scattering is given by the thickness of the i-th atmospheric layer. .

8. The apparatus according to claim 7, characterized in that, Before obtaining the content of water-based particles in each atmospheric layer above the target photovoltaic power station based on the optimized WRF model, the water-based particle content acquisition module further includes: The target simulation area setting and basic data acquisition unit is used to construct a target simulation area centered on the target photovoltaic power station and acquire basic data within the target simulation area; The model building and optimization unit is used to build a WRF model based on the basic data, and optimize the WRF model by setting the optimal physical parameterization scheme combination strategy to obtain the optimized WRF model. The optimized WRF model is then used for calculation to obtain the content of water particles in each layer of atmosphere above the target photovoltaic station based on the calculation results.

9. The apparatus according to claim 8, characterized in that, The target simulation area setting and basic data acquisition unit includes: The target simulation area division unit is used to set a first preset number of nested patterns in the horizontal direction using a preset grid distribution with the target photovoltaic station as the center, and to set a second preset number of atmospheric layer distributions in the vertical direction using a hybrid vertical coordinate system. The simulation region acquisition unit obtains the target simulation region based on the nesting pattern and the atmospheric layer distribution.

10. The apparatus according to claim 7, characterized in that, The atmospheric state determination module includes: The cloud droplet content acquisition unit is used to acquire the cloud droplet content in the target atmospheric layer. An initial atmospheric state determination unit is used to determine the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere. A cloud state determination unit is used to determine that the current initial atmospheric state of the target layer is a cloud state if the cloud droplet content is greater than a first preset content threshold. The cloudless state determination unit is used to determine that the current initial atmospheric state of the target layer is cloudless if the cloud droplet content is less than or equal to the first preset content threshold.

11. The apparatus according to claim 10, characterized in that, After determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the cloudless state determination unit includes: The cloud droplet content determination subunit is used to determine whether the cloud droplet content in the target layer atmosphere is equal to a second preset content threshold if the current initial atmospheric state of the target layer is cloudless. The clear sky atmosphere determination subunit is used to determine that the current atmospheric state of the target layer is clear sky if the cloud droplet content in the target layer atmosphere is equal to the second preset content threshold. The aerosol atmosphere determination subunit is used to determine the current atmospheric state of the target layer as an aerosol atmosphere if the cloud droplet content in the target layer is greater than a second preset content threshold and less than a first preset content threshold.

12. The apparatus according to claim 10, characterized in that, After determining the current initial atmospheric state of the target layer based on the cloud droplet content in the target layer atmosphere, the cloud state determination unit includes: The current atmospheric state determination unit is used to obtain the ice crystal content, raindrop content, snow crystal content, and graupel content in the target layer atmosphere if the current initial atmospheric state of the target layer is a cloudy state, and determine the current atmospheric state of the target layer based on the cloud droplet content, the ice crystal content, the raindrop content, the snow crystal content, and the graupel content; The liquid cloud determination subunit is used to determine that the current atmospheric state of the target layer is a liquid cloud if the cloud droplet content is greater than the first preset content threshold and the raindrop content is greater than the first preset content threshold. The ice phase cloud determination subunit is used to determine that the current atmospheric state of the target layer is an ice phase cloud if the ice crystal content and the snow crystal content are both greater than a second preset content threshold, and the graupel content is greater than the first preset content threshold. The mixed-phase cloud determination subunit is used to determine that the current atmospheric state of the target layer is a mixed-phase cloud if the cloud droplet content, the raindrop content, and the graupel content are all greater than the first preset content threshold, and the ice crystal content and the snow crystal content are all greater than the second preset content threshold.

13. An electronic device, characterized in that, include: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for correcting solar radiation at a photovoltaic power station based on a numerical model as described in any one of claims 1-6.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the method for correcting solar radiation at photovoltaic power plants based on numerical models as described in any one of claims 1-6.

15. A computer program, characterized in that, When the computer program is executed, it is used to implement the method for correcting solar radiation at photovoltaic power plants based on numerical models as described in any one of claims 1-6.

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