Meteorological data processing method and device for offshore photovoltaic project, equipment and product

Abstract

The invention relates to a marine photovoltaic project-oriented meteorological data processing method and device, electronic equipment and a computer program product, and relates to the technical field of computers. The method comprises the following steps: acquiring key meteorological data corresponding to key monitoring points in an offshore photovoltaic area; determining a first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area; determining first meteorological data corresponding to the photovoltaic unit according to the key meteorological data and the photovoltaic point location distance between the photovoltaic unit and the key monitoring point location; and determining a second position factor corresponding to the key monitoring point position, and determining second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data. The meteorological data of each photovoltaic unit can be accurately calculated under the condition that limited key monitoring points are set, fine monitoring and management of different photovoltaic units are achieved, and the meteorological data are used for evaluating the working environment conditions of the photovoltaic units.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a meteorological data processing method for offshore photovoltaic projects, a meteorological data processing device for offshore photovoltaic projects, an electronic device, and a computer program product. Background Art

[0002] Offshore photovoltaic projects differ significantly from conventional land-based photovoltaic projects. For example, individual mounting brackets are larger, pile foundation spacing is wider, and the supporting structure is significantly affected by the marine environment. To ensure safety throughout the project's construction and service life, on-site environmental monitoring and research are essential.

[0003] Marine meteorology is a key area of ​​monitoring, encompassing wind conditions, temperature, air pressure, humidity, rainfall, sunshine, and other factors. Due to the large size of offshore photovoltaic areas and the varying environments of different photovoltaic units, for example, wind conditions are highly correlated with the array location of each photovoltaic unit. Given the limited number of monitoring points, obtaining meteorological data for each photovoltaic unit is crucial for achieving refined monitoring.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0005] The purpose of the present disclosure is to provide a meteorological data processing method for offshore photovoltaic projects, a meteorological data processing device for offshore photovoltaic projects, an electronic device, a computer-readable storage medium and a computer program product, thereby at least to a certain extent overcoming the problem that meteorological monitoring schemes for offshore photovoltaic projects cannot obtain accurate meteorological data at different locations.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0007] According to a first aspect of the present disclosure, a meteorological data processing method for an offshore photovoltaic project is provided, comprising: obtaining key meteorological data corresponding to key monitoring points in an offshore photovoltaic area; determining a first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area; determining the first meteorological data corresponding to the photovoltaic unit based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; determining a second position factor corresponding to the key monitoring point, and determining the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data.

[0008] In an exemplary embodiment of the present disclosure, obtaining key meteorological data corresponding to key monitoring points in an offshore photovoltaic area includes: determining the key monitoring points, wherein the key monitoring points are determined based on the corner positions of the offshore photovoltaic area; obtaining meteorological monitoring data collected by meteorological sensors at each of the key monitoring points, and using the meteorological monitoring data as the key meteorological data.

[0009] In an exemplary embodiment of the present disclosure, determining the first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area includes: determining a first distance parameter between the photovoltaic unit and the overall area boundary of the offshore photovoltaic area, the first distance parameter being the distance between the photovoltaic unit and the overall area boundary in multiple specified directions; determining the field sub-area in which the photovoltaic unit is located, and determining a second distance parameter between the photovoltaic unit and the sub-area boundary of the field sub-area, the second distance parameter being the distance between the photovoltaic unit and the sub-area boundary in multiple specified directions; and performing weighted processing on the first distance parameter and the second distance parameter to obtain the first position factor.

[0010] In an exemplary embodiment of the present disclosure, the first meteorological data corresponding to the photovoltaic unit is determined based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point, including: taking the distance between the photovoltaic unit and the key monitoring point as the photovoltaic point distance; interpolating the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data; or weighting the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data.

[0011] In an exemplary embodiment of the present disclosure, the interpolation processing of the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data includes: obtaining the point weight corresponding to each of the key monitoring points, the point weight being determined based on the photovoltaic point distance; determining the point distribution characteristics of the key monitoring points, and determining the corresponding interpolation calculation model according to the point distribution characteristics; and using the interpolation calculation model, interpolating the key meteorological data based on the point weight to obtain the first meteorological data.

[0012] In an exemplary embodiment of the present disclosure, determining the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data includes: determining the meteorological data type corresponding to the first meteorological data; determining a matching data correction method based on the meteorological data type; and correcting the first meteorological data based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data.

[0013] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial temperature data, and the second meteorological data includes corrected temperature data. The first meteorological data is corrected based on the data correction method, the first position factor, and the second position factor to obtain the second meteorological data, including: when the meteorological data type is a temperature data type, determining the data correction method as a forward correction method; and correcting the initial temperature data in combination with the forward correction method, the first position factor, and the second position factor to obtain the corrected temperature data.

[0014] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial wind speed data, and the second meteorological data includes corrected wind speed data. The first meteorological data is corrected based on the data correction method, the first position factor, and the second position factor to obtain the second meteorological data, including: when the meteorological data type is a wind speed data type, determining the data correction method as a negative correction method; and correcting the initial wind speed data in combination with the negative correction method, the first position factor, and the second position factor to obtain the corrected wind speed data.

[0015] According to a second aspect of the present disclosure, a meteorological data processing device for an offshore photovoltaic project is provided, including: a key data acquisition module for acquiring key meteorological data corresponding to key monitoring points in an offshore photovoltaic area; a first position factor determination module for determining a first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area; a first meteorological data determination module for determining the first meteorological data corresponding to the photovoltaic unit based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; a second meteorological data determination module for determining a second position factor corresponding to the key monitoring point, and determining the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data.

[0016] In an exemplary embodiment of the present disclosure, the key data acquisition module includes a key data acquisition unit, which is used to: determine the key monitoring points, where the key monitoring points are determined based on the corner positions of the offshore photovoltaic area; obtain meteorological monitoring data collected by meteorological sensors at each of the key monitoring points, and use the meteorological monitoring data as the key meteorological data.

[0017] In an exemplary embodiment of the present disclosure, the first position factor determination module includes a first position factor determination unit, which is used to: determine a first distance parameter between the photovoltaic unit and the overall area boundary of the offshore photovoltaic area, the first distance parameter being the distance between the photovoltaic unit and the overall area boundary in multiple specified directions; determine the field sub-area in which the photovoltaic unit is located, and determine a second distance parameter between the photovoltaic unit and the sub-area boundary of the field sub-area, the second distance parameter being the distance between the photovoltaic unit and the sub-area boundary in multiple specified directions; and perform weighted processing on the first distance parameter and the second distance parameter to obtain the first position factor.

[0018] In an exemplary embodiment of the present disclosure, the first meteorological data determination module includes a first meteorological data determination unit, which is used to: take the distance between the photovoltaic unit and the key monitoring point as the photovoltaic point distance; interpolate the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data; or weight the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data.

[0019] In an exemplary embodiment of the present disclosure, the first meteorological data determination unit includes a meteorological data determination subunit, which is used to: obtain the point weight corresponding to each of the key monitoring points, where the point weight is determined based on the photovoltaic point distance; determine the point distribution characteristics of the key monitoring points, and determine the corresponding interpolation calculation model according to the point distribution characteristics; and use the interpolation calculation model to interpolate the key meteorological data based on the point weight to obtain the first meteorological data.

[0020] In an exemplary embodiment of the present disclosure, the second meteorological data determination module includes a second meteorological data determination unit, which is used to: determine the meteorological data type corresponding to the first meteorological data; determine a matching data correction method based on the meteorological data type; and correct the first meteorological data based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data.

[0021] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial temperature data, the second meteorological data includes corrected temperature data, and the second meteorological data determination unit includes a first correction subunit, which is used to: when the meteorological data type is a temperature data type, determine the data correction method as a forward correction method; and correct the initial temperature data in combination with the forward correction method, the first position factor and the second position factor to obtain the corrected temperature data.

[0022] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial wind speed data, the second meteorological data includes corrected wind speed data, and the second meteorological data determination unit includes a second correction subunit, which is used to: when the meteorological data type is a wind speed data type, determine the data correction method as a negative correction method; and correct the initial wind speed data in combination with the negative correction method, the first position factor and the second position factor to obtain the corrected wind speed data.

[0023] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, a meteorological data processing method for an offshore photovoltaic project according to any one of the above items is implemented.

[0024] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the meteorological data processing method for an offshore photovoltaic project according to any one of the above items is implemented.

[0025] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements any one of the above-mentioned meteorological data processing methods for offshore photovoltaic projects.

[0026] The technical solution provided by the present disclosure may have the following beneficial effects:

[0027] The meteorological data processing method for offshore photovoltaic projects in the exemplary embodiments of this disclosure can, on the one hand, accurately calculate meteorological data for each photovoltaic unit, while maintaining a limited number of key monitoring points, enabling refined monitoring and management of each photovoltaic unit. Furthermore, the calculated, precise meteorological data at different locations can be used to assess the operating environment of the photovoltaic units.

[0028] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0030] Figure 1 A flowchart of a meteorological data processing method for an offshore photovoltaic project according to an exemplary embodiment of the present disclosure is schematically shown;

[0031] Figure 2 A schematic diagram schematically illustrates key monitoring points set according to an exemplary embodiment of the present disclosure;

[0032] Figure 3 Schematically shows a flow chart of determining a first location factor corresponding to a photovoltaic unit according to an exemplary embodiment of the present disclosure;

[0033] Figure 4 Schematically illustrates a flow chart of performing correction processing on first meteorological data to obtain second meteorological data according to an exemplary embodiment of the present disclosure;

[0034] Figure 5 Schematically shows a block diagram of a meteorological data processing device for an offshore photovoltaic project according to an exemplary embodiment of the present disclosure;

[0035] Figure 6 A block diagram schematically illustrates an electronic device according to an exemplary embodiment of the present disclosure;

[0036] Figure 7 A schematic diagram schematically illustrates a computer-readable storage medium according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the drawings represent like or similar parts, and thus repetitive description thereof will be omitted.

[0038] In addition, the described features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, well-known structures, methods, devices, implementations, materials or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0039] The blocks shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. Specifically, these functional entities may be implemented in software, or in one or more software-hardened modules, or in different networks and / or processor devices and / or microcontroller devices.

[0040] In offshore photovoltaic projects, meteorological monitoring at the project site is often limited to representative locations due to the large size of the offshore photovoltaic field. This method of setting up monitoring points to monitor meteorological data at key locations cannot accurately obtain meteorological data at different locations.

[0041] Based on this, in this example embodiment, a meteorological data processing method for offshore photovoltaic projects is first provided. The meteorological data processing method for offshore photovoltaic projects disclosed in the present invention can be implemented using a server, or the method disclosed in the present invention can be implemented using a terminal device. The terminals described in the present invention may include mobile terminals such as mobile phones, tablet computers, laptops, PDAs, personal digital assistants (PDAs), and fixed terminals such as desktop computers. Figure 1 The following schematically illustrates a flow chart of a meteorological data processing method for an offshore photovoltaic project according to some embodiments of the present disclosure. Figure 1 The meteorological data processing method for offshore photovoltaic projects may include the following steps:

[0042] Step S110, obtaining key meteorological data corresponding to key monitoring points in the offshore photovoltaic area;

[0043] Step S120, determining a first location factor corresponding to any photovoltaic unit in the offshore photovoltaic area;

[0044] Step S130, determining first meteorological data corresponding to the photovoltaic unit according to the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point;

[0045] Step S140 , determining a second location factor corresponding to the key monitoring point, and determining second meteorological data corresponding to the photovoltaic unit based on the first location factor, the second location factor and the first meteorological data.

[0046] The meteorological data processing method for offshore photovoltaic projects in this example embodiment accurately calculates meteorological data for each photovoltaic unit, enabling refined monitoring and management of each unit, even at a limited number of key monitoring points. Furthermore, the precise meteorological data calculated for each location can be used to assess the operating environment of each photovoltaic unit.

[0047] The following further describes the meteorological data processing method for an offshore photovoltaic project in this exemplary embodiment.

[0048] In an exemplary embodiment of the present disclosure, for step S110, key meteorological data corresponding to key monitoring points in the offshore photovoltaic area are obtained, including: determining the key monitoring points, where the key monitoring points are determined based on the corner positions of the offshore photovoltaic area; obtaining meteorological monitoring data collected by meteorological sensors at each key monitoring point, and using the meteorological monitoring data as key meteorological data.

[0049] Among them, the offshore photovoltaic area, also known as the offshore photovoltaic field area, can be the area on the sea where the offshore photovoltaic project is located. The key monitoring points can be points formed by setting monitoring points at pre-set key points. The corner point position can refer to the intersection of the sides of the polygon, that is, the position of the vertex of the polygon. Meteorological sensors can be devices that detect meteorological parameters in digital or analog form, and can monitor temperature, humidity, air pressure, wind speed, wind direction, precipitation and other factors in real time, providing data support for weather forecasting, climate research and site management of offshore photovoltaic projects. Meteorological monitoring data can be data collected in real time by meteorological sensors. Key meteorological data can be meteorological monitoring data collected from all key monitoring points in the offshore photovoltaic area.

[0050] Since the offshore photovoltaic area is relatively large in offshore photovoltaic projects, some key points can usually be identified within the offshore photovoltaic area and monitoring points can be set up at these key points to monitor meteorological data. Figure 2 , Figure 2 The following schematically shows a schematic diagram of the key monitoring points set according to an exemplary embodiment of the present disclosure. Figure 2 In the PV system, monitoring points can be set based on the corner locations of the offshore photovoltaic area. For longer sides, additional monitoring points can be added in the middle of the side. For example, six monitoring points (①-⑥) can be set based on the corner locations as key monitoring points.

[0051] After identifying key monitoring points, meteorological monitoring data collected by meteorological sensors at these key monitoring points can be obtained as key meteorological data. For example, real-time meteorological data such as wind conditions, temperature, air pressure, humidity, rainfall, and sunshine collected by meteorological sensors can be used as key meteorological data. The key meteorological data collected through the above steps forms the basis for the subsequent calculation of meteorological data corresponding to each photovoltaic unit.

[0052] In an exemplary embodiment of the present disclosure, for step S120, the first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area is determined, including: determining a first distance parameter between the photovoltaic unit and the overall area boundary of the offshore photovoltaic area, the first distance parameter being the distance between the photovoltaic unit and the overall area boundary in multiple specified directions; determining the field sub-area in which the photovoltaic unit is located, determining a second distance parameter between the photovoltaic unit and the sub-area boundary of the field sub-area, the second distance parameter being the distance between the photovoltaic unit and the sub-area boundary in multiple specified directions; and performing weighted processing on the first distance parameter and the second distance parameter to obtain the first position factor.

[0053] Among them, the photovoltaic unit can refer to the basic component of the offshore photovoltaic project that has independent power generation capacity and can be centrally connected to the grid. The photovoltaic unit can be a basic component unit of a photovoltaic power station, also known as a photovoltaic unit power generation module. The photovoltaic unit can be a certain number of photovoltaic component strings collected through a DC combiner box, and then inverted by an inverter and boosted by an isolated booster substation to a power supply that meets the frequency and voltage requirements of the grid. The first position factor can be the position factor corresponding to the photovoltaic unit. The first distance parameter can be a parameter calculated based on the distance between the location of the photovoltaic unit and the regional boundary of the entire offshore photovoltaic area. The second distance parameter can be a parameter calculated based on the distance between the location of the photovoltaic unit and the sub-region boundary of the sub-region of the site.

[0054] refer to Figure 3 , Figure 3 The flowchart of determining the first location factor corresponding to a photovoltaic unit according to an exemplary embodiment of the present disclosure is schematically shown. For any photovoltaic unit in an offshore photovoltaic area, the corresponding first location factor can be determined by the following steps:

[0055] In step S310, a first distance parameter is determined between the photovoltaic unit and the overall regional boundary of the offshore photovoltaic area. The first distance parameter is the distance between the photovoltaic unit and the overall regional boundary in multiple specified directions. The overall regional boundary can be the boundary corresponding to the offshore photovoltaic area. For any photovoltaic unit in the offshore photovoltaic field, the location factor of the photovoltaic unit is calculated based on factors such as the number of photovoltaic units around it and the distance to the boundary. Specifically, the distance between the photovoltaic unit and the overall regional boundary corresponding to the entire offshore photovoltaic area in four directions (such as due north, due south, due east, and due west) is obtained to obtain four first distance parameters.

[0056] In step S320, the subregion of the field area in which the photovoltaic unit is located is determined, and a second distance parameter is determined between the photovoltaic unit and the subregion boundary of the field subregion. The second distance parameter is the distance between the photovoltaic unit and the subregion boundary in multiple specified directions. The subregion boundary can be the boundary of a subregion obtained by dividing the entire offshore photovoltaic area according to the channel. For any photovoltaic unit, the distance between the photovoltaic unit and the subregion boundary in four directions (e.g., due north, due south, due east, and due west) is obtained to obtain four second distance parameters.

[0057] In step S330, the first and second distance parameters are weighted to obtain a first location factor. After obtaining the eight first and second distance parameters, the eight distance parameters are weighted to obtain the first location factor corresponding to the PV unit. A larger first location factor indicates that the PV unit is closer to the center of the region and farther from the boundary. The first location factor calculated through these steps can be used as the basis for subsequent position correction of meteorological data.

[0058] It is easy for those skilled in the art to understand that in some other exemplary embodiments of the present disclosure, other directions can be selected for the distance parameter determination process according to specific needs, such as selecting northeast, southeast, southwest, northwest and other directions. The present disclosure does not impose any special limitation on the specific direction selected.

[0059] In an exemplary embodiment of the present disclosure, for step S130, the first meteorological data corresponding to the photovoltaic unit is determined based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point, including: taking the distance between the photovoltaic unit and the key monitoring point as the photovoltaic point distance; interpolating the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data; or weighting the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data.

[0060] The photovoltaic point distance may be the distance between the photovoltaic unit and the key monitoring point. The first meteorological data may be meteorological data corresponding to a photovoltaic unit obtained by interpolating or weighting the key meteorological data based on the photovoltaic point distance. The first meteorological data may be meteorological data of a photovoltaic unit without position correction.

[0061] For a photovoltaic unit, assuming that the location coordinates of the photovoltaic unit are (x0, y0), the coordinates of multiple key monitoring points in the offshore photovoltaic area are (x i ,y i ), the key meteorological data corresponding to each key monitoring point is M i (i=1,2,…,n), the distance between the PV unit and each key monitoring point is calculated using the Euclidean distance formula as shown in Formula 1.

[0062]

[0063] Where d is the distance between the photovoltaic points; (x0, y0) can be the position coordinates corresponding to the photovoltaic unit; (x i ,y i ) can be the location coordinates corresponding to each key monitoring point.

[0064] After calculating the distance to the photovoltaic point, the acquired key meteorological data can be interpolated based on the photovoltaic point distance to obtain the first meteorological data. Furthermore, the key meteorological data can be weighted based on the photovoltaic point distance to obtain the first meteorological data. When weighting the key meteorological data, a point weight corresponding to each key monitoring point can be determined based on the photovoltaic point distance. The multiple key meteorological data can then be weighted based on the point weights to obtain the first meteorological data. Through this processing, meteorological data corresponding to each photovoltaic unit can be obtained, allowing the meteorological data at each location to be used to assess the operating environment of the photovoltaic unit.

[0065] In an exemplary embodiment of the present disclosure, key meteorological data are interpolated according to the distance of photovoltaic points to obtain first meteorological data, including: obtaining the point weight corresponding to each key monitoring point, the point weight is determined based on the distance of photovoltaic points; determining the point distribution characteristics of the key monitoring points, and determining the corresponding interpolation calculation model according to the point distribution characteristics; using the interpolation calculation model, interpolating the key meteorological data based on the point weight to obtain the first meteorological data.

[0066] Among them, the point weight can be the calculation weight corresponding to the key monitoring point. The point distribution characteristic can be the distribution characteristic of the key monitoring points in the offshore photovoltaic area. For example, the point distribution characteristic can include the linear distribution characteristic and the spatial distribution characteristic, etc. The interpolation calculation model can be a model that calculates the first meteorological data using the interpolation algorithm.

[0067] For each key monitoring point, the point weight corresponding to each key monitoring point can be calculated separately. For example, the point weight can be calculated by the power of the reciprocal of the distance. For example, the point weight is shown in Formula 2.

[0068]

[0069] Among them, ω i can be the point weight corresponding to the i-th key monitoring point; d j is the photovoltaic point distance between the photovoltaic unit and the key monitoring point; p is a constant greater than 0. For example, the value of p can be 2; the closer the key point is, the greater the weight.

[0070] After determining the point weight of each key monitoring point, the point distribution characteristic of the key monitoring point is determined. For example, the key monitoring points can be linearly distributed. In addition, due to the complexity of the on-site environment of the offshore photovoltaic project, multiple key monitoring points show spatial correlation, etc. According to the point distribution characteristic presented by the key monitoring points, an interpolation calculation model adapted to it is selected.

[0071] For example, when the key monitoring points are linearly distributed, that is, multiple key monitoring points are distributed along a straight line. Given two key monitoring points A(x1, y1) and B(x2, y2), and the corresponding key meteorological data are M1 and M2 respectively. The photovoltaic unit is located at x0, and x1 < x0 < x2. After determining the point weights ω1 and ω2 corresponding to the two key monitoring points A and B, the first meteorological data M0 corresponding to the photovoltaic unit x0 can be calculated through the linear interpolation model, as shown in Formula 3.

[0072] M0 = ω1M1 + ω2M2 (Formula 3)

[0073] Among them, M0 can be the first meteorological data corresponding to the photovoltaic unit x0; ω1 can be the point weight corresponding to the key monitoring point A; ω2 can be the point weight corresponding to the key monitoring point B; M1 can be the key meteorological data corresponding to the key monitoring point A; M2 can be the key meteorological data corresponding to the key monitoring point B.

[0074] For another example, when multiple key monitoring points show spatial correlation, that is, the locations of multiple key monitoring points are relatively random and have a certain spatial structure, an interpolation calculation model constructed based on the Kriging interpolation method can be used to perform interpolation calculations to obtain the first meteorological data.

[0075] Specifically, the variogram is calculated based on the known meteorological data from multiple key monitoring points to describe the spatial variation of the meteorological data. The kriging equations are then solved to obtain the point weights for each key point. Finally, the first meteorological data for the PV unit is calculated. The specific calculation method is shown in Equation 4.

[0076]

[0077] Wherein, M0 may be the first meteorological data corresponding to the photovoltaic unit x0; ω i It can be the point weight corresponding to the i-th key monitoring point; M i It can be the key meteorological data corresponding to the i-th key monitoring point.

[0078] While kriging interpolation is relatively complex, it fully leverages the spatial structure of the data and generally achieves high accuracy in meteorological data interpolation. In practical applications, the appropriate interpolation method must be selected based on factors such as the specific characteristics of the meteorological data, the distribution of key points, and the required computational accuracy. Furthermore, methods such as cross-validation can be used to evaluate the accuracy of interpolation results and optimize and adjust the interpolation method. By interpolating key meteorological data, the first meteorological data corresponding to each photovoltaic unit can be obtained.

[0079] In an exemplary embodiment of the present disclosure, for step S140, the second meteorological data corresponding to the photovoltaic unit is determined based on the first position factor, the second position factor and the first meteorological data, including: determining the meteorological data type corresponding to the first meteorological data; determining a matching data correction method based on the meteorological data type; and correcting the first meteorological data based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data.

[0080] refer to Figure 4 , Figure 4 A flowchart of correcting first meteorological data to obtain second meteorological data according to an exemplary embodiment of the present disclosure is schematically shown. Before correcting the first meteorological data, in step S410, the meteorological data type corresponding to the first meteorological data can be determined. For example, the meteorological data type can be a specific type of meteorological data, and the meteorological data type can include but is not limited to wind conditions, temperature, air pressure, humidity, rainfall, sunshine, etc.

[0081] In step S420, a matching data correction method is determined based on the meteorological data type. Different data correction methods are required for different meteorological data types. The data correction method may be a specific method for correcting the position of the first meteorological data based on the location factors of the photovoltaic units and key monitoring points. Therefore, a matching data correction method is determined for each meteorological data type.

[0082] In step S430, the first meteorological data is corrected based on the data correction method, the first location factor, and the second location factor to obtain second meteorological data. Using the selected data correction method, the first meteorological data is corrected based on the location factor of the key monitoring point and the location factor of the photovoltaic unit to obtain second meteorological data. By correcting the first meteorological data, accurate meteorological data for each photovoltaic unit location can be obtained.

[0083] In an exemplary embodiment of the present disclosure, the first meteorological data is corrected based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data, including: when the meteorological data type is a temperature data type, determining the data correction method as a forward correction method; combining the forward correction method, the first position factor and the second position factor to correct the initial temperature data to obtain corrected temperature data.

[0084] The initial temperature data may be the temperature and meteorological data of a photovoltaic unit without position correction. The corrected temperature data may be the temperature and meteorological data of a photovoltaic unit after position correction. The forward correction method may be a method of performing position correction on the meteorological data based on a positive correlation between the position factor and the meteorological data.

[0085] During the meteorological data correction process, if the meteorological data type is temperature, a forward correction method can be used. Specifically, the corrected meteorological data is positively correlated with the location factor during data correction. The initial temperature data is forward-corrected based on the first and second location factors to generate corrected temperature data. During the correction process, the larger the location factor corresponding to the PV unit or key monitoring point, the higher the temperature. The temperature-corrected data calculated through these steps can be used to assess the environmental conditions of the PV unit's operating environment.

[0086] In an exemplary embodiment of the present disclosure, the first meteorological data is corrected based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data, including: when the meteorological data type is a wind speed data type, determining the data correction method as a negative correction method; combining the negative correction method, the first position factor and the second position factor to correct the initial wind speed data to obtain corrected wind speed data.

[0087] The initial wind speed data may be the wind speed meteorological data of a photovoltaic unit without position correction. The corrected wind speed data may be the wind speed meteorological data of a photovoltaic unit after position correction. The negative correction method may be a method of performing position correction on the meteorological data based on the negative correlation between the position factor and the meteorological data.

[0088] During the meteorological data correction process, if the meteorological data type is wind speed data, a negative correction method can be used. That is, during data correction, the corrected meteorological data is negatively correlated with the location factor. The initial wind speed data is negatively corrected based on the first and second location factors to obtain the corrected wind speed data. During the correction process, the larger the location factor corresponding to the photovoltaic unit or key monitoring point, the lower the wind speed.

[0089] After the above correction steps, the calculated second meteorological data is used as the final meteorological data of the photovoltaic unit, so that for the photovoltaic unit without a monitoring point, the meteorological data can be accurately calculated and its working environment condition can be evaluated.

[0090] It should be noted that the terms "first" and "second" used in the present disclosure are only used to distinguish different meteorological data and different location factors, and should not impose any limitations on the present disclosure.

[0091] In summary, the meteorological data processing method for offshore photovoltaic projects disclosed in the present invention obtains key meteorological data corresponding to key monitoring points in the offshore photovoltaic area; determines the first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area; determines the first meteorological data corresponding to the photovoltaic unit based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; determines the second position factor corresponding to the key monitoring point, and determines the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data. On the one hand, in the case of setting a limited number of key monitoring points, the meteorological data of each photovoltaic unit can be accurately calculated to achieve refined monitoring and management of different photovoltaic units. On the other hand, the calculated accurate meteorological data of different locations can be used to evaluate the working environment conditions of the photovoltaic unit. On the other hand, by correcting the first meteorological data to obtain the second meteorological data, accurate meteorological data for each location can be obtained, providing a data basis for achieving refined monitoring and management.

[0092] It should be noted that although the steps of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all steps must be performed to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0093] In addition, in this exemplary embodiment, a meteorological data processing device for offshore photovoltaic projects is also provided. Figure 5 The meteorological data processing device 500 for offshore photovoltaic projects may include: a key data acquisition module 510, a first location factor determination module 520, a first meteorological data determination module 530 and a second meteorological data determination module 540.

[0094] Specifically, the key data acquisition module 510 is used to obtain key meteorological data corresponding to key monitoring points in the offshore photovoltaic area; the first position factor determination module 520 is used to determine the first position factor corresponding to any photovoltaic unit in the offshore photovoltaic area; the first meteorological data determination module 530 is used to determine the first meteorological data corresponding to the photovoltaic unit based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; the second meteorological data determination module 540 is used to determine the second position factor corresponding to the key monitoring point, and determine the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data.

[0095] In an exemplary embodiment of the present disclosure, the key data acquisition module 510 includes a key data acquisition unit, which is used to: determine key monitoring points, where the key monitoring points are determined based on the corner points of the offshore photovoltaic area; obtain meteorological monitoring data collected by meteorological sensors at each key monitoring point, and use the meteorological monitoring data as key meteorological data.

[0096] In an exemplary embodiment of the present disclosure, the first position factor determination module 520 includes a first position factor determination unit, which is used to: determine a first distance parameter between the photovoltaic unit and the overall area boundary of the offshore photovoltaic area, the first distance parameter being the distance between the photovoltaic unit and the overall area boundary in multiple specified directions; determine the field sub-area in which the photovoltaic unit is located, and determine a second distance parameter between the photovoltaic unit and the sub-area boundary of the field sub-area, the second distance parameter being the distance between the photovoltaic unit and the sub-area boundary in multiple specified directions; and perform weighted processing on the first distance parameter and the second distance parameter to obtain a first position factor.

[0097] In an exemplary embodiment of the present disclosure, the first meteorological data determination module 530 includes a first meteorological data determination unit, which is used to: take the distance between the photovoltaic unit and the key monitoring point as the photovoltaic point distance; interpolate the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data; or weight the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data.

[0098] In an exemplary embodiment of the present disclosure, the first meteorological data determination unit includes a meteorological data determination sub-unit, which is used to: obtain the point weight corresponding to each key monitoring point, where the point weight is determined based on the distance between the photovoltaic points; determine the point distribution characteristics of the key monitoring points, and determine the corresponding interpolation calculation model based on the point distribution characteristics; and use the interpolation calculation model to interpolate the key meteorological data based on the point weight to obtain the first meteorological data.

[0099] In an exemplary embodiment of the present disclosure, the second meteorological data determination module 540 includes a second meteorological data determination unit, which is used to: determine the meteorological data type corresponding to the first meteorological data; determine a matching data correction method based on the meteorological data type; and correct the first meteorological data based on the data correction method, the first position factor and the second position factor to obtain the second meteorological data.

[0100] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial temperature data, the second meteorological data includes corrected temperature data, and the second meteorological data determination unit includes a first correction subunit, which is used to: when the meteorological data type is a temperature data type, determine the data correction method as a forward correction method; and combine the forward correction method, the first position factor and the second position factor to correct the initial temperature data to obtain corrected temperature data.

[0101] In an exemplary embodiment of the present disclosure, the first meteorological data includes initial wind speed data, the second meteorological data includes corrected wind speed data, and the second meteorological data determination unit includes a second correction subunit, which is used to: when the meteorological data type is a wind speed data type, determine the data correction method as a negative correction method; and correct the initial wind speed data in combination with the negative correction method, the first position factor and the second position factor to obtain corrected wind speed data.

[0102] The specific details of the virtual modules of the above-mentioned meteorological data processing devices for offshore photovoltaic projects have been described in detail in the corresponding meteorological data processing methods for offshore photovoltaic projects. The undisclosed details can be found in the implementation methods of the method section, and will not be repeated here.

[0103] It should be noted that while the detailed description above mentions several modules or units of the meteorological data processing device for offshore photovoltaic projects, this division is not mandatory. In fact, according to embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in a single module or unit. Conversely, the features and functions of a single module or unit described above can be further divided and embodied by multiple modules or units.

[0104] The exemplary embodiments of the present disclosure further provide a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned meteorological data processing method for offshore photovoltaic projects.

[0105] In one embodiment, the computer program product may be a tangible product containing the computer program, such as a computer-readable storage medium storing the computer program. Figure 6 , Figure 6 The following schematically illustrates a computer-readable storage medium according to an exemplary embodiment of the present disclosure. The computer-readable storage medium 600 may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk drive (HDD), solid-state drive (SSD), and the like. For example, the computer program product may be implemented as a non-volatile storage medium storing a computer program, such as a read-only memory, a NAND flash memory (NANDFlash), and the like.

[0106] In one embodiment, the computer program product may be an intangible product containing a computer program. For example, the computer program product may be implemented as a virtual digital product, such as a digital file such as an executable file or installation package storing the computer program.

[0107] The code of the computer program can be written in one or more programming languages. Programming languages ​​include C, Java, C++, etc. The program code can be executed entirely on the user computing device, partially on the user computing device, or as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (e.g., via an Internet connection provided by a carrier).

[0108] Computer programs can be carried or transmitted via electrical, magnetic, optical, electromagnetic, infrared, or other signals. Electronic devices can convert signals carrying computer programs into digital signals, thereby executing the computer programs. When the computer program is executed on an electronic device, its code causes the electronic device to execute (more specifically, the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, such as the aforementioned meteorological data processing method for offshore photovoltaic projects.

[0109] The exemplary embodiments of the present disclosure further provide an electronic device, which may include a processor and a memory. The memory stores executable instructions for the processor, such as a computer program. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of the present disclosure. The electronic device may also include a display for displaying a graphical user interface.

[0110] Reference below Figure 7 , the electronic device is exemplarily described in the form of a general-purpose computing device. It should be understood that Figure 7 The electronic device 700 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0111] like Figure 7 As shown, the electronic device 700 may include a processor 710 , a memory 720 , a bus 730 , an I / O (input / output) interface 740 , a network adapter 750 , and a display 760 .

[0112] The memory 720 may include volatile memory, such as RAM 721 and cache unit 722, and may also include non-volatile memory, such as ROM 723. The memory 720 may also include one or more program modules 724. Such program modules 724 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each of these examples, or some combination thereof, may include an implementation of a network environment. For example, the program modules 724 may include the modules described above.

[0113] The processor 710 may include one or more processing units, for example: the processor 710 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit), etc.

[0114] The processor 710 may be configured to execute executable instructions stored in the memory 720 , such as executing the aforementioned meteorological data processing method for offshore photovoltaic projects.

[0115] The bus 730 is used to connect different components of the electronic device 700 and may include a data bus, an address bus, and a control bus.

[0116] The electronic device 700 can communicate with one or more external devices 800 (eg, a keyboard, a mouse, an external controller, etc.) through the I / O interface 740 .

[0117] The electronic device 700 can communicate with one or more networks via the network adapter 750. For example, the network adapter 750 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. The network adapter 750 can communicate with other modules of the electronic device 700 via the bus 730.

[0118] The electronic device 700 may display a graphical user interface via the display 760 , such as an interface displaying accurate meteorological data corresponding to each photovoltaic unit.

[0119] although Figure 7 Not shown, other hardware and / or software modules may also be provided in the electronic device 700, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0120] As can be seen from the above, the technical solutions of the present disclosure can be implemented as methods, devices, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation that combines hardware and software aspects, such as "circuit", "module" or "system".

[0121] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. Those skilled in the art will easily think of other embodiments based on the specific embodiments provided by the present disclosure. Therefore, the specific embodiments provided by the present disclosure are merely exemplary, and the scope and spirit of the present disclosure are indicated by the claims, which should cover any variations, uses or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the field of the present technology that are not disclosed in the present disclosure.

Claims

1. A meteorological data processing method for offshore photovoltaic projects, characterized in that: include: Obtain key meteorological data corresponding to key monitoring points in the offshore photovoltaic area; Determine a first location factor corresponding to any photovoltaic unit in the offshore photovoltaic area; Determining first meteorological data corresponding to the photovoltaic unit according to the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; A second location factor corresponding to the key monitoring point is determined, and second meteorological data corresponding to the photovoltaic unit is determined based on the first location factor, the second location factor, and the first meteorological data.

2. The method according to claim 1, characterized in that The acquisition of key meteorological data corresponding to key monitoring points in the offshore photovoltaic area includes: Determining the key monitoring point, wherein the key monitoring point is determined based on the corner point position of the offshore photovoltaic area; Acquire meteorological monitoring data collected by meteorological sensors at each of the key monitoring points, and use the meteorological monitoring data as the key meteorological data.

3. The method according to claim 1, characterized in that Determining the first location factor corresponding to any photovoltaic unit in the offshore photovoltaic area includes: determining a first distance parameter between the photovoltaic unit and an overall area boundary of the offshore photovoltaic area, the first distance parameter being a distance between the photovoltaic unit and the overall area boundary in a plurality of specified directions; Determine a field sub-region where the photovoltaic unit is located, and determine a second distance parameter between the photovoltaic unit and a sub-region boundary of the field sub-region, where the second distance parameter is a distance between the photovoltaic unit and the sub-region boundary in multiple specified directions; The first distance parameter and the second distance parameter are weighted to obtain the first location factor.

4. The method according to claim 1, wherein The determining, based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point, first meteorological data corresponding to the photovoltaic unit includes: The distance between the photovoltaic unit and the key monitoring point is used as the photovoltaic point distance; Performing interpolation processing on the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data; or The key meteorological data is weighted according to the photovoltaic point distance to obtain the first meteorological data.

5. The method according to claim 4, characterized in that The interpolation processing of the key meteorological data according to the photovoltaic point distance to obtain the first meteorological data includes: Obtaining a point weight corresponding to each of the key monitoring points, wherein the point weight is determined based on the distance between the photovoltaic points; Determining the point distribution characteristics of the key monitoring points, and determining a corresponding interpolation calculation model according to the point distribution characteristics; The interpolation calculation model is used to interpolate the key meteorological data based on the point weights to obtain the first meteorological data.

6. The method according to claim 1, characterized in that The determining, based on the first location factor, the second location factor, and the first meteorological data, second meteorological data corresponding to the photovoltaic unit includes: determining a meteorological data type corresponding to the first meteorological data; Determining a matching data correction method according to the meteorological data type; Based on the data correction method, the first location factor, and the second location factor, the first meteorological data is corrected to obtain the second meteorological data.

7. The method according to claim 6, characterized in that The first meteorological data includes initial temperature data, and the second meteorological data includes corrected temperature data. Correcting the first meteorological data based on the data correction method, the first location factor, and the second location factor to obtain the second meteorological data includes: When the meteorological data type is a temperature data type, the data correction mode is determined to be a forward correction mode; The initial temperature data is corrected by combining the forward correction method, the first position factor, and the second position factor to obtain the corrected temperature data.

8. The method according to claim 6, characterized in that The first meteorological data includes initial wind speed data, and the second meteorological data includes corrected wind speed data. Correcting the first meteorological data based on the data correction method, the first location factor, and the second location factor to obtain the second meteorological data includes: When the meteorological data type is a wind speed data type, the data correction mode is determined to be a negative correction mode; The initial wind speed data is corrected by combining the negative correction method, the first position factor, and the second position factor to obtain the corrected wind speed data.

9. A meteorological data processing device for offshore photovoltaic projects, characterized in that: include: Key data acquisition module, used to obtain key meteorological data corresponding to key monitoring points in the offshore photovoltaic area; A first location factor determination module is configured to determine a first location factor corresponding to any photovoltaic unit within the offshore photovoltaic area; A first meteorological data determination module is configured to determine first meteorological data corresponding to the photovoltaic unit based on the key meteorological data and the photovoltaic point distance between the photovoltaic unit and the key monitoring point; The second meteorological data determination module is used to determine the second position factor corresponding to the key monitoring point, and determine the second meteorological data corresponding to the photovoltaic unit based on the first position factor, the second position factor and the first meteorological data.

10. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the meteorological data processing method for an offshore photovoltaic project according to any one of claims 1 to 8.

11. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the meteorological data processing method for an offshore photovoltaic project according to any one of claims 1 to 8 is implemented.

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