Solar radiation quantity evaluation method and device, electronic equipment and storage medium

Abstract

The invention provides a solar radiation quantity evaluation method and device, electronic equipment and a storage medium, historical meteorological data of a place where a photovoltaic project is located are acquired and data cleaning is performed on the historical meteorological data, and the historical meteorological data are from various meteorological databases; performing data fusion processing on the cleaned historical meteorological data based on geographic position information of the photovoltaic project to obtain target meteorological data of a place where the photovoltaic project is located; and performing data analysis on the target meteorological data, and determining radiation quantity data of the place where the photovoltaic project is located. Compared with the prior art, the method has the advantages that the historical meteorological data is acquired from various meteorological databases, so that information from different sources can be covered to the greatest extent, and possible deviation or missing of a single data source is reduced; based on the accurate target meteorological data, the radiation quantity data of the place where the photovoltaic project is located can be calculated more accurately, and the power generation efficiency and economic benefits of a photovoltaic system are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a method and device for evaluating solar radiation, an electronic device, and a storage medium. Background Art

[0002] In the site selection process of photovoltaic power plants, meteorological data plays a vital role, especially in evaluating the light radiation of the target power plant. Light radiation is a key indicator to measure the power generation potential of photovoltaic power plants, which directly affects their power generation efficiency and economic benefits. However, the current light radiation analysis and calculation methods are relatively simple and mainly rely on basic meteorological data, such as sunshine hours, average irradiance, etc. The accuracy and completeness of these data have certain limitations.

[0003] Specifically, existing methods for analyzing and calculating light radiation often fail to fully consider the influence of multiple complex factors, such as geographical location, topography, climate conditions, atmospheric transparency, cloud cover changes, and solar altitude angle. Changes in these factors will have a significant impact on the accurate calculation of light radiation. Therefore, relying solely on simple meteorological data for analysis often fails to accurately reflect the actual light radiation situation, resulting in the inability to maximize the power generation efficiency of photovoltaic power plants.

[0004] In order to improve the site selection accuracy and power generation efficiency of photovoltaic power plants, it is urgent to develop a more accurate light radiation analysis and calculation method to achieve accurate calculation of light radiation. Summary of the invention

[0005] The present disclosure provides a method and device for evaluating solar radiation, an electronic device and a storage medium, which are mainly intended to solve the problem of low accuracy of the evaluation and calculation method for solar radiation at the location of a photovoltaic project when selecting a photovoltaic project site.

[0006] According to a first aspect of the present disclosure, there is provided a method for evaluating solar radiation, comprising:

[0007] Acquire historical meteorological data of the location of the photovoltaic project and perform data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases;

[0008] Based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project;

[0009] The target meteorological data is analyzed to determine the radiation data of the location of the photovoltaic project.

[0010] In some embodiments, the method further comprises:

[0011] Based on the radiation data, the solar energy resources at the location of the photovoltaic project are graded.

[0012] In some embodiments, the step of grading the solar energy resources at the location of the photovoltaic project based on the radiation data includes:

[0013] Based on the radiation data, calculate the average annual radiation value and monthly radiation value of the location of the photovoltaic project;

[0014] Analyze and calculate the light radiation stability coefficient of the location of the photovoltaic project by using the target meteorological data;

[0015] The solar radiation level of the location of the photovoltaic project is determined based on the light radiation stability coefficient, the annual radiation average value and the monthly radiation.

[0016] In some embodiments, the cleaned historical meteorological data is subjected to data fusion processing based on the geographic location information of the photovoltaic project to obtain target meteorological data of the location of the photovoltaic project, including:

[0017] Determine the neighboring meteorological stations of the photovoltaic project according to the geographical location information, and screen the neighboring meteorological stations to determine the target meteorological station with similar climatic conditions to the photovoltaic project;

[0018] The coupling algorithm is called to perform coupling processing on the historical meteorological data of the target meteorological station to obtain the target meteorological data.

[0019] In some embodiments, the method further comprises:

[0020] If the target weather station cannot be determined based on the geographical location information, searching and acquiring satellite observation data;

[0021] A preset algorithm is called to interpolate the observation data at the location of the photovoltaic project to obtain the target meteorological data.

[0022] According to a second aspect of the present disclosure, there is provided a device for evaluating solar radiation, comprising:

[0023] An acquisition unit, used for acquiring historical meteorological data of a location of a photovoltaic project and performing data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases;

[0024] A fusion unit, configured to perform data fusion processing on the cleaned historical meteorological data based on the geographical location information of the photovoltaic project, so as to obtain target meteorological data of the location of the photovoltaic project;

[0025] The determination unit is used to perform data analysis on the target meteorological data to determine the radiation data of the location of the photovoltaic project.

[0026] In some embodiments, the apparatus further comprises:

[0027] An assessment unit is used to grade and classify the solar energy resources at the location of the photovoltaic project based on the radiation data.

[0028] In some embodiments, the assessment unit comprises:

[0029] A first calculation module is used to calculate the annual average radiation amount and the monthly radiation amount of the location of the photovoltaic project based on the radiation amount data;

[0030] A second calculation module is used to analyze and calculate the light radiation stability coefficient of the location of the photovoltaic project by using the target meteorological data;

[0031] The first determination module is used to determine the solar radiation level of the location of the photovoltaic project according to the light radiation stability coefficient, the annual radiation average value and the monthly radiation.

[0032] In some embodiments, the fusion unit comprises:

[0033] A second determination module is used to determine the neighboring meteorological stations of the photovoltaic project according to the geographical location information, and screen the neighboring meteorological stations to determine a target meteorological station with a climatic condition similar to that of the photovoltaic project;

[0034] The processing module is used to call the coupling algorithm to perform coupling processing on the historical meteorological data of the target meteorological station to obtain the target meteorological data.

[0035] In some embodiments, the apparatus further comprises:

[0036] a search unit, configured to search and obtain satellite observation data if the target weather station cannot be determined based on the geographical location information;

[0037] The interpolation unit is used to call a preset algorithm to interpolate the observation data at the location of the photovoltaic project to obtain the target meteorological data.

[0038] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0039] at least one processor; and

[0040] a memory communicatively connected to the at least one processor; wherein,

[0041] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0042] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0043] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0044] The present disclosure provides a method and device, electronic device and storage medium for evaluating solar radiation, which obtains historical meteorological data of the location of a photovoltaic project and cleans the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases; based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project; the target meteorological data is subjected to data analysis to determine the radiation data of the location of the photovoltaic project. Compared with related technologies, by obtaining historical meteorological data from a variety of meteorological databases, information from different sources can be covered to the maximum extent, and possible deviations or omissions of a single data source can be reduced; based on accurate target meteorological data, the radiation data of the location of the photovoltaic project can be calculated more accurately, which helps to optimize the layout, orientation, tilt angle and other design parameters of the photovoltaic project, and improve the power generation efficiency and economic benefits of the photovoltaic system.

[0045] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0047] Figure 1 A schematic diagram of a process for evaluating solar radiation provided by an embodiment of the present disclosure;

[0048] Figure 2 A schematic diagram of the structure of a solar radiation assessment device provided in an embodiment of the present disclosure;

[0049] Figure 3 A schematic diagram of the structure of another device for evaluating solar radiation provided by an embodiment of the present disclosure;

[0050] Figure 4 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0051] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0052] The following describes the method and device for evaluating solar radiation, electronic device, and storage medium according to embodiments of the present disclosure with reference to the accompanying drawings.

[0053] Figure 1 A schematic flow chart of a method for evaluating solar radiation provided in an embodiment of the present disclosure.

[0054] like Figure 1 As shown, the method comprises the following steps:

[0055] Step 101, obtaining historical meteorological data of a location of a photovoltaic project and performing data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases.

[0056] In some embodiments of the present disclosure, in order to accurately evaluate the feasibility of a photovoltaic project and optimize its design parameters, it is first necessary to obtain historical meteorological data of the location of the photovoltaic project. Historical meteorological data can provide basic input information for subsequent analysis of the project. These historical meteorological data are not from a single source, but come from a variety of meteorological databases, including but not limited to the official database of the National Meteorological Administration, databases built by scientific research institutions, and databases of commercial meteorological service providers. These databases each have different advantages. Some are known for their comprehensiveness and accuracy of data, some provide high-resolution spatiotemporal data, and others can update data in real time to ensure that we obtain the most representative meteorological information.

[0057] After collecting these historical meteorological data from different channels, data cleaning is required for these historical meteorological data. It aims to identify and correct errors, omissions or inconsistencies in the data to ensure the accuracy and availability of the data. This step includes checking the completeness of the data, that is, confirming that all necessary fields are filled in and there are no missing values; verifying the accuracy of the data, such as identifying and correcting possible errors by comparing data from different sources; and dealing with outliers, that is, those values ​​that deviate significantly from the normal range, which may be caused by measurement errors or equipment failures. In addition, data cleaning also includes the unification of data formats to ensure that data from different sources can be seamlessly integrated. This involves standardization of time formats (such as unifying date and time into ISO 8601 format), conversion of data units (such as converting temperature from Fahrenheit to Celsius), and consistent processing of data types (such as converting text-formatted dates into date types).

[0058] Through this series of cleaning steps, high-quality, standardized historical meteorological data can be extracted from a variety of meteorological databases.

[0059] Step 102 , based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project.

[0060] In some embodiments of the present disclosure, based on the specific geographical location information of the photovoltaic project, the cleaned and pre-processed historical meteorological data is further fused to obtain more accurate, comprehensive and applicable target meteorological data for the location of the photovoltaic project. By integrating information from different meteorological data sources and making full use of their respective advantages, a comprehensive meteorological data set that reflects regional characteristics and has a high temporal and spatial resolution is generated.

[0061] In the process of data fusion processing, multiple meteorological data sources with the closest climate characteristics to the project location are identified and screened according to the geographical location of the photovoltaic project. These data sources may include official data from the National Meteorological Administration, precision monitoring data from scientific research institutions, real-time data from commercial meteorological service providers, etc. By comparing the data quality, coverage and update frequency of different data sources, it can be ensured that the selected data source can fully reflect the meteorological conditions of the project location.

[0062] Next, we use data fusion algorithms to integrate these historical meteorological data from different data sources. Data fusion algorithms usually include weighted average method, Kalman filter method, Bayesian network method, etc. They can intelligently assign weights, filter out noise and fuse information according to different application scenarios and data characteristics. In this process, we pay special attention to maintaining the consistency and continuity of the data to avoid data distortion or loss during the fusion process.

[0063] In addition, the special meteorological conditions of the location of the photovoltaic project should be considered, such as topography, altitude, ocean influence, etc. These factors may have a significant impact on meteorological data. Therefore, when fusing data, these special conditions will be combined and the fusion algorithm will be appropriately adjusted to ensure that the target meteorological data can truly reflect the actual meteorological conditions of the project location.

[0064] Step 103: Analyze the target meteorological data to determine the radiation data of the location of the photovoltaic project.

[0065] In some embodiments of the present disclosure, in-depth data analysis of the target meteorological data obtained through data fusion processing is performed to extract key data directly related to solar radiation from complex and changeable meteorological information, so as to provide a scientific basis for the planning, design and performance evaluation of photovoltaic projects.

[0066] In the data analysis process, according to the radiation parameters directly related to the target meteorological data, such as total radiation, direct radiation, diffuse radiation, and sunshine duration, etc. These parameters can fully reflect the abundance and distribution of solar energy resources in the location of the photovoltaic project, and are the basis for evaluating the power generation potential of the photovoltaic system.

[0067] In order to accurately obtain these radiation data, by analyzing the relationship between radiation and time series, we can reflect the changing trend of radiation on different time scales, such as daily changes, monthly changes, and interannual changes. Spatial distribution analysis can reveal the differences in radiation in different geographical locations, which helps to optimize the layout and site selection of photovoltaic projects.

[0068] The disclosed embodiments will also use mathematical models and algorithms, such as radiation transfer models, neural network prediction models, etc., to further process and predict the target meteorological data. These models can comprehensively consider the impact of various meteorological factors (such as cloud cover, atmospheric transparency, surface reflectivity, etc.) on solar radiation, thereby providing more accurate and reliable radiation prediction results.

[0069] The present disclosure provides a method for evaluating solar radiation, which obtains historical meteorological data of the location of a photovoltaic project and cleans the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases; based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project; the target meteorological data is analyzed to determine the radiation data of the location of the photovoltaic project. Compared with the related art, by obtaining historical meteorological data from a variety of meteorological databases, information from different sources can be covered to the maximum extent, and possible deviations or omissions of a single data source can be reduced; based on accurate target meteorological data, the radiation data of the location of the photovoltaic project can be calculated more accurately, which helps to optimize the layout, orientation, tilt angle and other design parameters of the photovoltaic project, and improve the power generation efficiency and economic benefits of the photovoltaic system.

[0070] As an achievable method of the embodiment of the present disclosure, after obtaining the radiation data of the location of the photovoltaic project, the grading can be performed in the following manner but not limited to: the solar energy resources at the location of the photovoltaic project are graded and classified according to the radiation data.

[0071] Furthermore, the solar energy resources at the location of the photovoltaic project are graded based on the radiation data, including: calculating the annual average radiation value and the monthly radiation values ​​at the location of the photovoltaic project based on the radiation data; analyzing and calculating the light radiation stability coefficient at the location of the photovoltaic project using the target meteorological data; and determining the solar radiation grade at the location of the photovoltaic project based on the light radiation stability coefficient, the annual average radiation value and the monthly radiation values.

[0072] Specifically, based on the radiation data obtained, in-depth analysis and calculation can be carried out to determine the solar energy resource status of the photovoltaic project site. First, these radiation data will be used to calculate the average annual radiation of the photovoltaic project site, which is a key indicator for evaluating the total amount of solar energy resources in the area. At the same time, by calculating the monthly radiation, the changing patterns of solar energy resources in different seasons can be revealed, which is crucial for the design and optimization of the operation strategy of the photovoltaic system.

[0073] In addition to the calculation of the annual average radiation and monthly radiation, the target meteorological data that has been cleaned and fused is used to deeply analyze and calculate the light radiation stability coefficient of the photovoltaic project location. The light radiation stability coefficient is an important parameter that reflects the stability and reliability of solar radiation. It can help us understand the fluctuation of solar radiation in the region and its changes under different weather conditions. By calculating the light radiation stability coefficient, the quality of solar energy resources in the photovoltaic project location can be more comprehensively evaluated, providing a more scientific basis for the design and operation and maintenance of photovoltaic systems.

[0074] After obtaining the annual average radiation, monthly radiation and light radiation stability coefficient, the solar radiation level of the photovoltaic project site will be determined based on these key indicators. The solar radiation level is a comprehensive indicator that reflects the abundance and utilization potential of solar energy resources in the region. It has important guiding significance for the site selection, design and operation strategy formulation of photovoltaic projects. By scientifically and rationally dividing the solar radiation level, we can more accurately evaluate the solar energy resource status of the photovoltaic project site and provide more powerful support for the development of the photovoltaic industry.

[0075] Further as an achievable method of the above embodiment, when fusing meteorological data, the cleaned historical meteorological data is subjected to data fusion processing based on the geographic location information of the photovoltaic project to obtain the target meteorological data of the location of the photovoltaic project, including: determining the neighboring meteorological stations of the photovoltaic project according to the geographic location information, and screening the neighboring meteorological stations to determine the target meteorological station with similar climatic conditions to the photovoltaic project; calling a coupling algorithm to couple the historical meteorological data of the target meteorological station to obtain the target meteorological data.

[0076] Specifically, when the cleaned historical meteorological data is fused based on the geographic location information of the photovoltaic project, all meteorological stations that are geographically close to the photovoltaic project are accurately identified and located using the geographic information system (GIS) technology according to the specific geographic location information of the photovoltaic project. These meteorological stations provide rich historical meteorological data resources, which are the basis for subsequent data fusion processing.

[0077] Not all data from nearby weather stations are suitable for the analysis of PV projects. Therefore, it is necessary to further screen these nearby weather stations to determine which weather stations have the most similar climate conditions to the location of the PV project. This screening process usually involves comparative analysis of historical data from weather stations, including comparison of multiple key meteorological elements such as temperature, humidity, wind speed, wind direction, and solar radiation, to ensure that the data from the selected weather stations can truly reflect the climate conditions of the location of the PV project.

[0078] After determining the target meteorological stations with similar climate conditions to the photovoltaic project, the coupling algorithm is then used to couple the historical meteorological data of these target meteorological stations. The coupling algorithm can maximize the accuracy and integrity of the data while maintaining data consistency. During the coupling process, it is necessary to consider the spatiotemporal distribution characteristics of the data from different meteorological stations, as well as the interaction between various meteorological elements, to ensure that the target meteorological data obtained can fully and accurately reflect the meteorological conditions of the photovoltaic project location.

[0079] Furthermore, when screening the target meteorological station, if it is determined that there is no meteorological station with climatic conditions similar to those of the location of the photovoltaic project, then the following methods can be used for processing, but are not limited to: if the target meteorological station cannot be determined based on the geographic location information, search and obtain satellite observation data; call a preset algorithm to interpolate the observation data of the location of the photovoltaic project to obtain the target meteorological data.

[0080] Specifically, when the target weather station with similar climate conditions cannot be directly determined based on the geographical location information of the photovoltaic project, an alternative solution will be adopted to ensure that accurate and reliable target weather data can still be obtained. The core of this alternative solution is to use satellite observation data to fill the gaps in ground weather station data.

[0081] Using satellite remote sensing technology, we can find and obtain satellite observation data related to the location of the photovoltaic project. These satellite observation data usually include information on multiple key meteorological elements such as cloud cover, surface temperature, solar radiation, etc., which can provide important clues about the atmospheric and surface conditions of the photovoltaic project location.

[0082] However, satellite observation data often have limitations in spatial and temporal resolution, so they cannot directly replace data from ground weather stations. It is necessary to call a preset interpolation algorithm to process satellite observation data. When calling the interpolation algorithm, the temporal and spatial distribution characteristics of satellite observation data, as well as factors such as the topography and climate type of the location of the photovoltaic project, are fully considered to ensure the accuracy and rationality of the interpolation results. Through interpolation processing, a more complete, continuous and accurate set of meteorological data can be obtained, which will be used as target meteorological data for subsequent photovoltaic project analysis and decision-making.

[0083] It should be noted that the embodiments of the present disclosure may include multiple steps. For the convenience of description, these steps are numbered, but these numbers do not limit the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of the present disclosure do not limit this.

[0084] Corresponding to the above-mentioned method for evaluating solar radiation, the present invention further provides a device for evaluating solar radiation. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be described in detail in the present invention.

[0085] Figure 2 A schematic diagram of a solar radiation assessment device provided in an embodiment of the present disclosure is shown in FIG. Figure 2 As shown, including:

[0086] An acquisition unit 21 is used to acquire historical meteorological data of a location of a photovoltaic project and perform data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases;

[0087] A fusion unit 22 is used to perform data fusion processing on the cleaned historical meteorological data based on the geographical location information of the photovoltaic project to obtain target meteorological data of the location of the photovoltaic project;

[0088] The determination unit 23 is used to perform data analysis on the target meteorological data to determine the radiation data of the location of the photovoltaic project.

[0089] The present disclosure provides a device for evaluating solar radiation, which obtains historical meteorological data of the location of a photovoltaic project and cleans the historical meteorological data, wherein the historical meteorological data comes from multiple meteorological databases; based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project; the target meteorological data is subjected to data analysis to determine the radiation data of the location of the photovoltaic project. Compared with the related art, by obtaining historical meteorological data from multiple meteorological databases, information from different sources can be covered to the maximum extent, and possible deviations or omissions of a single data source can be reduced; based on accurate target meteorological data, the radiation data of the location of the photovoltaic project can be calculated more accurately, which helps to optimize the layout, orientation, tilt angle and other design parameters of the photovoltaic project, and improve the power generation efficiency and economic benefits of the photovoltaic system.

[0090] Furthermore, in a possible implementation of this embodiment, as Figure 3 As shown, the device also includes:

[0091] The evaluation unit 24 is used to grade the solar energy resources at the location of the photovoltaic project according to the radiation data.

[0092] Furthermore, in a possible implementation of this embodiment, as Figure 3 As shown, the evaluation unit 24 includes:

[0093] A first calculation module 241 is used to calculate the annual average radiation amount and the monthly radiation amount of the location of the photovoltaic project based on the radiation amount data;

[0094] The second calculation module 242 is used to analyze and calculate the light radiation stability coefficient of the location of the photovoltaic project by using the target meteorological data;

[0095] The first determination module 243 is used to determine the solar radiation level of the location of the photovoltaic project according to the light radiation stability coefficient, the annual radiation average value and the monthly radiation.

[0096] Furthermore, in a possible implementation of this embodiment, as Figure 3 As shown, the fusion unit 22 includes:

[0097] The second determination module 221 is used to determine the neighboring meteorological stations of the photovoltaic project according to the geographical location information, and screen the neighboring meteorological stations to determine the target meteorological station with similar climatic conditions to the photovoltaic project;

[0098] The processing module 222 is used to call the coupling algorithm to perform coupling processing on the historical meteorological data of the target meteorological station to obtain the target meteorological data.

[0099] Furthermore, in a possible implementation of this embodiment, as Figure 3 As shown, the device also includes:

[0100] A search unit 25, configured to search and obtain satellite observation data if the target weather station cannot be determined based on the geographical location information;

[0101] The interpolation unit 26 is used to call a preset algorithm to interpolate the observation data at the location of the photovoltaic project to obtain the target meteorological data.

[0102] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principle is the same, which is not limited in this embodiment.

[0103] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0104] Figure 4A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0105] like Figure 4 As shown, the device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 302 or a computer program loaded from a storage unit 308 to a RAM (Random Access Memory) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0106] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0107] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as a method for evaluating solar radiation. For example, in some embodiments, the method for evaluating solar radiation may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the aforementioned solar radiation amount evaluation method in any other appropriate manner (for example, by means of firmware).

[0108] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0109] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0110] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0111] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0112] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0113] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0114] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0115] The various numerical numbers such as first and second involved in the present disclosure are only for the convenience of description and are not used to limit the scope of the embodiments of the present disclosure, but also indicate the order of precedence.

[0116] At least one in the present disclosure may also be described as one or more, and a plurality may be two, three, four or more, which is not limited in the present disclosure. In the embodiments of the present disclosure, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no order of precedence or size between the technical features described by the "first", "second", "third", "A", "B", "C" and "D".

[0117] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0118] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for evaluating solar radiation, characterized in that: include: Acquire historical meteorological data of the location of the photovoltaic project and perform data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases; Based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain target meteorological data of the location of the photovoltaic project; The target meteorological data is analyzed to determine the radiation data of the location of the photovoltaic project.

2. The method according to claim 1, characterized in that The method further comprises: Based on the radiation data, the solar energy resources at the location of the photovoltaic project are graded.

3. The method according to claim 2, characterized in that The step of grading the solar energy resources at the location of the photovoltaic project based on the radiation data includes: Based on the radiation data, calculate the average annual radiation value and monthly radiation value of the location of the photovoltaic project; Analyze and calculate the light radiation stability coefficient of the location of the photovoltaic project by using the target meteorological data; The solar radiation level of the location of the photovoltaic project is determined based on the light radiation stability coefficient, the annual radiation average value and the monthly radiation.

4. The method according to claim 1, characterized in that: Based on the geographical location information of the photovoltaic project, the cleaned historical meteorological data is subjected to data fusion processing to obtain the target meteorological data of the location of the photovoltaic project, including: Determine the neighboring meteorological stations of the photovoltaic project according to the geographical location information, and screen the neighboring meteorological stations to determine the target meteorological station with similar climatic conditions to the photovoltaic project; The coupling algorithm is called to perform coupling processing on the historical meteorological data of the target meteorological station to obtain the target meteorological data.

5. The method according to claim 4, characterized in that The method further comprises: If the target weather station cannot be determined based on the geographical location information, searching and acquiring satellite observation data; A preset algorithm is called to interpolate the observation data at the location of the photovoltaic project to obtain the target meteorological data.

6. A device for evaluating solar radiation, characterized in that: include: An acquisition unit, used for acquiring historical meteorological data of a location of a photovoltaic project and performing data cleaning on the historical meteorological data, wherein the historical meteorological data comes from a variety of meteorological databases; A fusion unit, configured to perform data fusion processing on the cleaned historical meteorological data based on the geographical location information of the photovoltaic project, so as to obtain target meteorological data of the location of the photovoltaic project; The determination unit is used to perform data analysis on the target meteorological data to determine the radiation data of the location of the photovoltaic project.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

9. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 5.

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