Photovoltaic desertification control site selection method based on air quality and geostationary meteorological satellite data

Abstract

The invention provides a photovoltaic desertification control site selection method based on air quality and static meteorological satellite data, and relates to the technical field of photovoltaic modules, and the method comprises the steps: screening inhalable particle data and fine particle data in target time air quality data; the inhalable particle data and the fine particle data are preprocessed, negative values, null values and abnormal values are removed, and the processed inhalable particle data and the processed fine particle data are obtained; detecting the change of the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data, and generating the time information of the sand and dust weather; according to the occurrence time information of the sand and dust weather, backtracking the source of the sand and dust weather by using the static meteorological satellite data to obtain the final position information of the sand source; and determining the development address of the photovoltaic power station based on the final position information of the sand source land. While photovoltaic power generation is developed, sand and dust are inhibited, and the ecological value of a photovoltaic power station is improved.

Description

Background Art

[0002] The north is prone to sandstorms in spring, which have an adverse impact on the production and life of residents in the region, traffic safety, industrial production and other factors. The cause of sandstorms is that the strong northwest wind driven by the Siberian high pressure in the dry sand source in spring blows up sand and enters the densely populated areas in the north along the wind direction. The laying of photovoltaic modules can reduce the near-surface wind speed and change the air temperature gradient. If they are laid in the sand source, they can play a strong role in suppressing sand, thereby reducing the frequency and intensity of sandstorms.

[0003] The existing PV power station site selection method is usually based on the abundance and stability of solar energy resources, taking into account the impact of terrain slope and slope aspect on solar energy resources, and also analyzing various restrictive factors such as hydrogeological conditions, the distance between roads and transmission lines, and the need to avoid nature reserves and residential areas. Although this method is relatively comprehensive, when selecting the site for PV power stations, the existing technology lacks in-depth consideration of its sand control effect and priority for sand source areas, so the potential of PV power stations in suppressing sand and dust is not fully utilized.

[0004] Therefore, the existing photovoltaic power station site selection technology does not take into account its sand control effect, and it is difficult to fully play the role of photovoltaic sand control. Therefore, there is an urgent need for a method that can combine the sand source backtracking positioning algorithm into the photovoltaic power station site selection process, so as to improve power generation and economic benefits while taking into account sand control, thereby suppressing sandstorms and enhancing its ecological value. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the present invention provides a photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data.

[0006] According to a first aspect of an embodiment of the present invention, a photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data is provided, comprising: Obtain air quality data from monitoring points in the target area; Screen the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time; Preprocessing the inhalable particulate matter data and the fine particulate matter data to remove negative values, null values ​​and abnormal values ​​to obtain processed inhalable particulate matter data and processed fine particulate matter data; Detecting the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data to generate time information of the occurrence of sandstorm weather; According to the time information of the occurrence of the sandstorm weather, the source of the sandstorm weather is traced back using the geostationary meteorological satellite data to obtain the final location information of the sand source; Based on the final location information of the sand source, the development address of the photovoltaic power station is determined.

[0007] In some example embodiments of the present invention, based on the above scheme, detecting the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data and generating the time information of the occurrence of sandstorm weather includes: Calculating the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data to obtain a time series of ratio data; Using a time series mutation identification method, respectively analyzing the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, so as to detect mutation points in the time series of the processed inhalable particulate matter data and the time series of the ratio data; When it is detected that both the time series of the inhalable particulate matter data and the time series of the ratio data have significant mutations, it is identified as sandstorm weather and the time information of the occurrence of the sandstorm weather is generated.

[0008] In some example embodiments of the present invention, based on the above scheme, the method of identifying a time series mutation is used to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, respectively, to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data, including: Calculating the difference between the measured value of the inhalable particulate matter data or the ratio data at each moment in the time series and the preset expected value; Accumulating the difference at each moment to obtain a cumulative sum; When the accumulated sum exceeds a preset threshold at the current moment, it is determined that a significant mutation occurs in the time series at the current moment.

[0009] In some example embodiments of the present invention, based on the above scheme, the method of identifying a time series mutation is used to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, respectively, to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data, including: Calculate the average measurement value in the sliding window of the target length at the current moment to obtain the current sliding window average value; Calculate the average measurement value in the sliding window of the target length within the pushback duration to obtain the pushback sliding window average value; Calculate the difference between the current sliding window average value and the pushback sliding window average value to obtain the difference value; When the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0010] In some example embodiments of the present invention, based on the above scheme, the method of identifying a time series mutation is used to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, respectively, to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data, including: Calculate the linear regression slope of the measured value in the sliding window of the target length at the current moment to obtain a first linear regression slope; Calculate the linear regression slope of the sliding window measurement value of the target length within the pushback time to obtain the second linear regression slope; The difference between the first linear regression slope and the second linear regression slope is compared, and when the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0011] In some exemplary embodiments of the present invention, based on the above scheme, according to the time information of the occurrence of the sandstorm weather, the source of the sandstorm weather is traced back using the geostationary meteorological satellite data to obtain the final location information of the sand source, including: Acquiring geostationary satellite data within a time range corresponding to the time when the sandstorm weather occurs; Preprocessing the geostationary satellite data to obtain spatial range data that meets the requirements for tracing the source of sandstorm weather; According to the time when the sandstorm weather occurs, the spatial range data is used to gradually trace back the source of the sandstorm weather in time to obtain the preliminary location of the sand source; The preliminary location of the sand source is spatially analyzed, and the dust coverage area is mapped using geographic information system tools to determine the final location information of the sand source.

[0012] In some exemplary embodiments of the present invention, based on the above scheme, the geostationary satellite data is preprocessed to obtain spatial range data that meets the requirements of wind and sand weather source tracing, including: Based on the mapping data of row and column numbers and longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, the geostationary meteorological satellite data is converted into longitude and latitude coordinates; The latitude and longitude coordinates are converted to a preset projection type, and the spatial range of the target area is cut out according to the requirements of sandstorm weather tracing, so as to obtain spatial range data that meets the requirements of sandstorm weather tracing.

[0013] According to a second aspect of an embodiment of the present invention, a photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data is provided, comprising: A data acquisition module is used to obtain air quality data of monitoring points in the target area; A data screening module, used to screen the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time; A preprocessing module, used to preprocess the inhalable particulate matter data and the fine particulate matter data, remove negative values, null values ​​and abnormal values, and obtain processed inhalable particulate matter data and processed fine particulate matter data; A time information generating module, used to detect the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data, and generate time information of the occurrence of sandstorm weather; A location information determination module is used to trace back the source of the sandstorm weather based on the time information of the occurrence of the sandstorm weather by using the geostationary meteorological satellite data to obtain the final location information of the sand source; The site selection module is used to determine the development address of the photovoltaic power station based on the final location information of the sand source.

[0014] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data in the first aspect is implemented.

[0015] According to a fourth aspect of an embodiment of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data in the first aspect.

[0016] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: In the embodiment of the present invention, accurate identification of sandstorm weather and sand sources is achieved by utilizing air quality data and geostationary meteorological satellite data, and the sand sources are incorporated into the site selection considerations for photovoltaic power stations. This allows the site selection of photovoltaic power stations to take into account both the effective use of solar energy resources and the effective improvement of the stability of the sand sources. It has the function of suppressing dust and reducing sand, thereby achieving the dual benefits of environmental governance and photovoltaic power generation.

[0017] 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 invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1A schematic diagram showing a system architecture of an exemplary application environment of a photovoltaic sand control site selection method and device based on air quality and geostationary meteorological satellite data to which an embodiment of the present invention can be applied; Figure 2 A schematic diagram of a process flow of a photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to some embodiments of the present invention is shown; Figure 3 A diagram schematically shows the PM10 index change graph of City A from March 14, 2021 to March 17, 2021 according to some embodiments of the present invention; Figure 4 A diagram schematically shows a change in the ratio of PM10 to PM2.5 in City A from March 14, 2021 to March 17, 2021 according to some embodiments of the present invention; Figure 5 The schematic diagram shows the occurrence and development process of sandstorm weather in the north around March 15, 2021 obtained according to an embodiment of the present invention; Figure 5 (a) means 13:00 on March 14, 2021; Figure 5 (b) means 14:00 on March 14, 2021; Figure 5 (c) means 14:00 on March 15, 2021; Figure 5 (d) represents 14:00 on March 16, 2021; the gray shaded area in the figure is the dust-covered area, and UTC+8 is Beijing time; Figure 6 Schematically illustrates a schematic diagram of a photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data according to some embodiments of the present invention; Figure 7 A schematic diagram schematically shows a structure of a computer system of an electronic device according to some embodiments of the present invention; Figure 8 A schematic diagram of a computer-readable storage medium according to some embodiments of the present invention is schematically shown. DETAILED DESCRIPTION

[0020] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0021] The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "the" and "the" used in the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0022] It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0023] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a photovoltaic sand control site selection method and device based on air quality and geostationary meteorological satellite data, to which an embodiment of the present invention can be applied, is shown.

[0024] like Figure 1 As shown, the system architecture 100 may include one or more terminal devices such as a desktop computer 101, a portable computer 102, a smart phone 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc. The terminal device may be various electronic devices with data processing functions, and the electronic device has a display screen, which is used to display the development address of the photovoltaic power station to the user, including but not limited to the above-mentioned desktop computers, portable computers, smart phones, etc. It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a sub-server cluster composed of multiple sub-servers.

[0025] The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data provided in the embodiment of the present invention can generally be executed by a terminal device, and accordingly, the photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data is generally arranged in the terminal device. However, it is easy for those skilled in the art to understand that the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data provided in the embodiment of the present invention can also be executed by the server 105, and accordingly, the photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data can also be arranged in the server 105, which is not particularly limited in this exemplary embodiment.

[0026] In addition, it should be understood that the underground pipeline detection method of the embodiment of the present invention can be configured as a software module. In some implementation scenarios, the photovoltaic sand control site selection scheme based on air quality and geostationary meteorological satellite data of the present invention can be deployed separately to present the development address of photovoltaic power stations in different forms. In other implementation scenarios, the photovoltaic sand control site selection scheme based on air quality and geostationary meteorological satellite data of the present invention can be deployed in other software as a functional module of the software, such as deployed in the analysis software of photovoltaic sand control site selection based on air quality and geostationary meteorological satellite data. The present invention does not place any special restrictions on the application of the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data.

[0027] Next, the embodiments of the present invention are described in detail.

[0028] like Figure 2 As shown, Figure 2 The present invention is a flowchart of a photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to an exemplary embodiment of the present invention, comprising the following steps: S210: Acquire air quality data of monitoring points in the target area; S220: Screening the inhalable particulate matter data and the fine particulate matter data in the air quality data at the target time; S230: preprocessing the inhalable particle data and the fine particle data to remove negative values, null values ​​and abnormal values ​​to obtain processed inhalable particle data and processed fine particle data; S240: Detecting a change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data, and generating time information of occurrence of sandstorm weather; S250: according to the time information of the occurrence of the sandstorm weather, using the geostationary meteorological satellite data to trace back the source of the sandstorm weather, and obtain the final location information of the sand source; S260: Determine the development address of the photovoltaic power station based on the final location information of the sand source.

[0029] The present invention can accurately identify the sand-raising conditions in the northern sand source areas by combining air quality data and geostationary meteorological satellite data in the photovoltaic sand control site selection method. Under the monitoring of air quality data, the time series analysis of the concentrations of different particulate matter (such as inhalable particulate matter and fine particulate matter) can effectively determine the occurrence time of sandstorm weather, and trace the source of sandstorms with the help of geostationary meteorological satellite data to obtain the specific scope of the sand source. Through the interactive application of this data, accurate information on the location of the sand source is obtained, laying an accurate data foundation for the priority site selection of photovoltaic power stations in the sand source areas.

[0030] On this basis, based on the site selection of the sand source, the shielding characteristics of the photovoltaic module array can be effectively utilized to increase the surface roughness, further reduce the surface wind speed, and achieve effective control of the probability of sand emission. Photovoltaic power stations can block solar radiation and reduce the surface temperature, thereby reducing the vertical convection of air caused by the increase in surface temperature. As a result, photovoltaic power stations can effectively suppress the generation of sand and dust caused by convection phenomena, and significantly reduce the dual adverse effects of sandstorms on the surrounding environment and photovoltaic power stations.

[0031] In addition, building photovoltaic power stations in sand source areas can promote vegetation recovery in sand source areas by improving water conservation conditions in sand source areas. The surface shading effect of photovoltaic modules can reduce the evaporation rate of soil moisture, improve the moisture conditions of the local environment, and provide a more suitable growth environment for vegetation in sand source areas. Therefore, the combination of the screening strategy of sand source areas and the shading effect of photovoltaic modules in the site selection process can help improve vegetation coverage, enhance surface stability, and thus reduce the impact of wind erosion, so that the ecological benefits and dust suppression effects of photovoltaic power stations can be effectively exerted.

[0032] In S210, air quality data of monitoring points in the target area are obtained.

[0033] Here, the air quality data includes air quality data collected from monitoring stations in prefecture-level cities in the northern region from the national air quality real-time release platform. The air quality data has an hourly time resolution and contains important indicators for monitoring sandstorm weather, namely the concentration values ​​of fine particulate matter (PM2.5) and inhalable particulate matter (PM10), which are important indicators for judging sandstorm weather.

[0034] The target area can be any city. Since sandstorms mainly occur in the north, in the implementation manner of the present invention, the target area is mainly determined from cities in the north. All northern cities can also be monitored simultaneously.

[0035] The present invention does not specifically limit the method for obtaining air quality data. A variety of methods can be used to obtain air quality data, such as monitoring by sensors, gas detection instruments, or remote sensing technology. The acquisition method can be selected and optimized according to the actual application scenario, measurement requirements and equipment conditions to ensure the accuracy and reliability of the data. In an embodiment of the present invention, air quality data is obtained through the national air quality real-time publishing platform, which records the specific data of air quality in various prefecture-level cities.

[0036] In S220, the inhalable particulate matter data and the fine particulate matter data in the air quality data at the target time are screened.

[0037] Fine particulate matter (PM2.5) is a pollutant with a particle size of less than 2.5 microns in the air, usually including combustion particles, organic compounds and metal particles, and is mainly used to evaluate the impact of combustion sources and fine pollutants; inhalable particulate matter (PM10) is a pollutant with a particle size of less than 10 microns, including pollen and dust particles, which can reflect the concentration changes of dust in the air. By monitoring the changes in PM2.5 and PM10 concentrations, especially the significant upward trend of PM10, a preliminary judgment can be made on the occurrence of sandstorms, thereby providing reliable basic data for subsequent identification of sandstorms and tracing of sand sources.

[0038] In addition, since sandstorms mainly occur in spring (March, April, and May), the target time may be spring. In some embodiments, the target time may also be autumn or winter, or the entire autumn and winter seasons.

[0039] In addition, you can filter the PM10 and PM2.5 data of the target area based on sensor quality or spatial location. When filtering based on sensor quality, you can filter out records with unqualified data quality or obvious outliers. When filtering based on spatial location, you can filter out PM10 and PM2.5 data in a specific area or location.

[0040] In S230, the inhalable particulate matter data and the fine particulate matter data are preprocessed to remove negative values, null values ​​and abnormal values, thereby obtaining processed inhalable particulate matter data and processed fine particulate matter data.

[0041] Here, if there are negative values ​​in the data (such as negative measurements due to sensor errors), they can be removed or replaced with zero or other reasonable values. For missing or empty data, you can choose to delete the data point, or use interpolation methods to fill in the empty values, such as linear interpolation, sample mean interpolation, or interpolation based on adjacent time points. When removing outliers, you can use statistical methods, such as screening based on the mean and standard deviation (for example, the 3 times standard deviation principle), to detect and remove outliers that are significantly deviated from the normal range; you can also use more complex algorithms, such as the interquartile range (IQR) method or machine learning-based outlier detection methods.

[0042] In addition, after removing negative values, null values ​​and outliers, the data can also be smoothed and normalized to make the processed inhalable particulate matter data and the processed fine particulate matter data more unified, which is convenient for further processing of subsequent data.

[0043] In S240, detecting the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data, and generating the time information of the occurrence of sandstorm weather includes: Calculating the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data to obtain a time series of ratio data; Using a time series mutation identification method, respectively analyzing the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, so as to detect mutation points in the time series of the processed inhalable particulate matter data and the time series of the ratio data; When it is detected that both the time series of the inhalable particulate matter data and the time series of the ratio data have significant mutations, it is identified as sandstorm weather and the time information of the occurrence of the sandstorm weather is generated.

[0044] Usually, the concentration of inhalable particulate matter in the air can be monitored by two air quality indicators, PM2.5 and PM10. Since the particle size of sand and dust is mostly in the range of 2.5-10 microns, the rapid rise of the PM10 indicator may represent the occurrence of sandstorms. However, since the PM10 indicator usually includes PM2.5 pollutants when measuring, the PM10 indicator will also rise rapidly in ordinary haze weather, and sandstorms cannot be accurately identified using only the PM10 indicator. Therefore, in order to accurately identify sandstorms, the present invention introduces an indicator, namely PM10 / PM2.5, which will also rise rapidly during sandstorms, but will not change significantly in ordinary haze weather.

[0045] After calculating the ratio of the processed inhalable particulate matter data and fine particulate matter data and generating a time series, the time series of the ratio data and the inhalable particulate matter data are analyzed to provide a double verification method for the accurate identification of sandstorm weather. This process not only takes into account the concentration changes of larger particles in the air, but also introduces the ratio changes of fine particles and larger particles, making the detection process more accurate in identifying sandstorm weather.

[0046] In time series analysis, the time series mutation identification method is used to monitor the changes in the inhalable particulate matter data and the ratio data, and the mutation points of the time series of the two can be detected separately. This process not only provides clear identification conditions for the mutation of the original data by independently analyzing the time series of the two types of data, but also avoids the risk of misjudgment caused by the change of a single data. Therefore, detecting the mutation points in the respective time series and comparing them enables this method to capture the occurrence of sandstorm weather more sensitively.

[0047] In addition, dust weather is only identified when both the time series of inhalable particulate matter data and the ratio data show significant mutations. This condition can greatly reduce the possibility of misjudgment. By introducing the double time series mutation condition, the fluctuation effect caused by general atmospheric particle changes is eliminated, thereby enhancing the accuracy and reliability of sandstorm weather judgment. Therefore, through the sandstorm discrimination based on double mutation recognition, the misjudgment caused by the fluctuation of single data in the existing technology is avoided, ensuring that the occurrence time of sandstorm weather can be accurately calibrated, providing more accurate time information for subsequent sand source tracing and photovoltaic power station site selection.

[0048] Different methods can be used to perform rapid rise detection on the two time series curves of PM10 and PM10 / PM2.5. For example, in some embodiments, the rapid rise detection on the two time series curves of PM10 and PM10 / PM2.5 includes: Calculating the difference between the measured value of the inhalable particulate matter data or the ratio data at each moment in the time series and the preset expected value; Accumulating the difference at each moment to obtain a cumulative sum; When the accumulated sum exceeds a preset threshold at the current moment, it is determined that a significant mutation occurs in the time series at the current moment.

[0049] Here, the difference The calculation method is: in, for The measured value at the moment, is the preset expected value.

[0050] The cumulative sum is expressed as: in, for The cumulative sum of time, for The cumulative sum of time, A constant used to control accumulation and growth.

[0051] In this embodiment, the expected value is determined ,constant As well as the optimal value of the preset threshold, it can be calculated using a large amount of dust process data.

[0052] In other embodiments, the rapid rise detection of two time series curves of PM10 and PM10 / PM2.5 includes: Calculate the current time Target length The average value of the measurement in the sliding window of the current sliding window is obtained ;in, for The measured value at the moment, is the window length.

[0053] Calculate pushback time Inner target length The average value of the sliding window is obtained by ; Calculate the difference between the current sliding window average and the pushback sliding window average to obtain the difference ; When the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0054] In this embodiment, the window length , Pushback duration The optimal value of the preset threshold can be calculated through a large amount of dust process data. Generally speaking, the sliding window length The value can be 3, 5, 7, etc. The shorter the sliding window, the stronger its sensitivity, but it is easy to introduce abnormal fluctuations. The longer the window, the lower the sensitivity, but the more reliable the result. It depends on the rate of change of the change to be detected. Generally speaking, during a dust storm, the transition from no dust to dust weather takes 1-2 hours. The value can be 1 or 2. , And the value of the preset threshold can take the best value in the calculation of a large number of dust processes.

[0055] In another embodiment, the rapid rise detection of the two time series curves of PM10 and PM10 / PM2.5 may also include: Calculate the current time Target length The linear regression slope of the measured value in the sliding window is obtained to obtain the first linear regression slope , X Indicates the measured value; Calculate from the current time Pushback duration Target length The linear regression slope of the sliding window measurement value is obtained to obtain the second linear regression slope ; The difference between the first linear regression slope and the second linear regression slope is compared, and when the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0056] In S250, according to the time information of the occurrence of the sandstorm weather, the source of the sandstorm weather is traced back using the geostationary meteorological satellite data to obtain the final location information of the sand source, including: Acquiring geostationary satellite data within a time range corresponding to the time when the sandstorm weather occurs; Preprocessing the geostationary satellite data to obtain spatial range data that meets the requirements for tracing the source of sandstorm weather; According to the time when the sandstorm weather occurs, the spatial range data is used to gradually trace back the source of the sandstorm weather in time to obtain the preliminary location of the sand source; The preliminary location of the sand source is spatially analyzed, and the dust coverage area is mapped using geographic information system tools to determine the final location information of the sand source.

[0057] In an embodiment of the present invention, the occurrence time of the dust process is determined by two time series curves of PM10 and PM10 / PM2.5, and the occurrence time refers to the occurrence time of the dust observed by the urban air quality index monitoring station. In the step of obtaining the geostationary satellite data within the time range corresponding to the time of occurrence of the dust weather, the time range corresponding to the time of occurrence of the dust weather can be the specific time of the occurrence of the dust weather, or it can be pushed back for a period of time before the specific time. Taking the specific time of the occurrence of the dust weather as a reference point, the starting time of the dust process can be calibrated more accurately. In some embodiments, since the time of occurrence of the dust weather monitored may have been a period of time away from the time of sand source, the time of occurrence of the dust is taken as the starting time of the time range, and on this basis, it is pushed back 1-3 days to trace its origin. The selection of this time range can ensure that the data source covers the entire process of the dust weather from the source to the monitoring station, so that the obtained data has both temporal continuity and covers the key change stages of the dust activity in the sand source, thereby providing a complete and continuous dust process data basis for subsequent analysis.

[0058] A geostationary satellite, also called a geosynchronous satellite or geostationary orbit satellite, is a satellite located approximately 35,786 kilometers (22,236 miles) above the Earth, with an orbital period equal to the Earth's rotation period. Therefore, relative to a fixed point on the Earth's surface (such as a point on the equator), a geostationary satellite will appear stationary, making them a very important tool in the fields of communications, meteorological observation, and Earth resource exploration.

[0059] Geostationary satellite data includes meteorological data, communication data, earth observation data and navigation and positioning data. Meteorological data can include cloud images, temperature, humidity, wind direction and speed and other meteorological information.

[0060] In the implementation mode of the present invention, FY-4A data is used as geostationary satellite data, which refers to data collected and transmitted from China's second-generation geostationary meteorological satellite, Fengyun-4A (FY-4A). The FY-4A satellite is a major scientific and technological achievement in China's meteorological field. It has high temporal resolution, high spatial resolution and high spectral resolution observation capabilities, and can provide multi-spectral images and data of the earth's surface and atmosphere in real time and continuously.

[0061] The geostationary satellite data is preprocessed to obtain spatial range data that meets the requirements of wind and sand weather source tracing, including: Based on the mapping data of row and column numbers and longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, the geostationary meteorological satellite data is converted into longitude and latitude coordinates; The latitude and longitude coordinates are converted to a preset projection type, and the spatial range of the target area is cut out according to the requirements of sandstorm weather tracing, so as to obtain spatial range data that meets the requirements of sandstorm weather tracing.

[0062] In some embodiments, the projection type can be a Mercator projection, an equal-area projection, a transverse Mercator projection, a Lambert conformal conic projection, or the like.

[0063] By converting satellite data into longitude and latitude coordinates and then converting the longitude and latitude coordinates to a preset projection type, the data can be displayed in a standardized manner in geographic space, thereby avoiding the problem of inconsistent spatial analysis results under different coordinate systems and ensuring the spatial accuracy of subsequent dust tracing.

[0064] According to the needs of dust weather source tracing, the spatial scope of the target area is cut out, such as the inland dust high-incidence area in East Asia (40°-50°N, 85°-120°E) to filter out redundant data from non-dust source areas. This cutting process can focus on the key source areas of dust weather, making the analysis data more targeted in space, thereby reducing the computational burden and improving the efficiency of tracing.

[0065] Through this preprocessing process, the spatial range data obtained that meets the needs of sandstorm weather source tracing not only has the accuracy of geographic coordinates and the consistency of spatial projection, but also achieves effective focusing of spatial data through cropping operations, providing more accurate data support for subsequent sandstorm source positioning and tracing analysis.

[0066] According to the time when the sandstorm occurs, the spatial range data is used to gradually trace back the source of the sandstorm to obtain the preliminary location of the sand source.

[0067] Here, step-by-step time backtracking refers to analyzing the data at each moment within the backtracking time range in chronological order. At each moment, the spatial position of the dust-covered area is extracted, and the dynamic changes of the dust-covered area are recorded. Through the cumulative analysis of the data at each time point, the diffusion direction and speed of the dust weather can be observed, so as to identify the characteristic position of the dust in the source area. Based on the superposition of step-by-step backtracking data, the source of the dust-covered area is determined. As time goes back, the dust area gradually shrinks to the earliest sand-raising position. Through this gradually shrinking dust coverage, the initial formation area of ​​the dust, that is, the preliminary location of the sand source, can be determined.

[0068] The preliminary location of the sand source is spatially analyzed, and the dust coverage area is mapped using geographic information system tools to determine the final location information of the sand source.

[0069] In this step, based on the preliminary location of the sand source determined by step-by-step time tracing back, spatial analysis tools (such as Geographic Information System, GIS) are used to evaluate its impact range in the formation of sandstorms. By analyzing the geographical characteristics, surface properties and connectivity with surrounding areas of the region, the contribution of the region to sandstorms can be more accurately identified, thereby screening out non-critical areas and making the location of the sand source more focused.

[0070] Using GIS tools and combining geostationary meteorological satellite data at different time points, the spatial boundaries of the dust-covered areas are drawn. In the GIS environment, the continuous trajectory of dust coverage is displayed by overlaying the distribution layer of dust concentration. This drawing process visualizes the diffusion path of dust, which helps to determine the direction and speed of dust weather spreading outward from the initial position, and provides a reliable basis for the spatial characteristics analysis of the sand source area.

[0071] Finally, by gradually analyzing the dust-covered areas, the scope of the sand source is further narrowed, and the area with the highest dust frequency and concentration is marked as the final location information of the sand source. Combined with the historical data of sandstorm weather, the importance of the area in the occurrence of sandstorm weather can be determined, providing specific data support for the site selection of photovoltaic power stations for sand control.

[0072] Through this process, using the spatial analysis and visualization capabilities of GIS tools, not only can the process of sand and dust diffusion be dynamically displayed, but the precise location and scope of the sand source can also be ultimately confirmed, providing a scientific basis for sand control functions and ensuring that photovoltaic site selection is more targeted.

[0073] In S260, the development address of the photovoltaic power station is determined based on the final location information of the sand source.

[0074] In some embodiments, according to the final location of the sand source, the frequency of occurrence of sandstorms, the scope of influence and the intensity of wind and sand are evaluated, the sand control potential of the photovoltaic power station in the area is clarified, and the site selection is ensured to have sand reduction benefits. A comprehensive assessment can also be conducted on the geographical environment around the sand source, including natural conditions such as surface stability, vegetation coverage, terrain, slope, etc., to determine the adaptability of the layout of photovoltaic modules in the area, so as to ensure that the photovoltaic power station can effectively suppress wind and sand and operate normally in this environment. In addition, the abundance and stability of solar energy resources can be evaluated in combination with the location of the sand source, and the average annual sunshine duration and radiation can be calculated to ensure that the site selection area has the function of sand control while meeting the resource requirements of photovoltaic power generation.

[0075] Considering that photovoltaic power stations require convenient power transmission and transportation conditions, it is also possible to analyze the accessibility of transmission lines and roads around the sand source areas, and give priority to areas close to existing power transmission infrastructure and transportation lines to reduce construction and operation costs.

[0076] In other implementations, a weighted comprehensive analysis can be conducted based on factors such as sand source characteristics, environmental adaptability, solar energy resources, and supporting facilities to select a photovoltaic power station development site that meets the requirements of sand suppression, power generation benefits, and cost feasibility. Through this multi-dimensional decision-making process, it is ensured that the photovoltaic power station can maximize resource utilization efficiency while optimizing dust suppression effects.

[0077] The present invention extracts the two air quality indicators of PM2.5 and PM10 in northern cities in March, April and May 2021, calculates PM10 / PM2.5, and uses the sliding average method to calculate whether PM10 and PM10 / PM2.5 in northern cities within this time range have increased rapidly. The results show that City A experienced an obvious sandstorm process on March 15, 2021. Figure 3 and Figure 4 As shown. Among them, Figure 3 It indicates the change of PM10 index in City A from March 14, 2021 to March 17, 2021; Figure 4 It represents the changes in PM10 / PM2.5 indicators in City A from March 14, 2021 to March 17, 2021.

[0078] Through calculation, it is found that the average PM10 in City A from 10:00 to 14:00 on March 15, 2021 was 2235μg / m3, while the average PM10 from 8:00 to 12:00 on the same day two hours ago was 666μg / m3, which has increased significantly. The difference between the two is 1569μg / m3, which is greater than the set threshold of 500μg / m3. At the same time, the PM10 / PM2.5 index of City A averaged 3.53 for five hours from 10:00 to 14:00 on March 15, 2021, and 1.05 for five hours from 8:00 to 12:00 on the same day. The difference between the two is 2.48, which is greater than the set threshold of 2. Since the increase in the sliding averages of PM10 and PM10 / PM2.5 in City A at 14:00 on March 15, 2021 was greater than the set threshold, it is determined that sandstorm weather occurred in City A at that time.

[0079] Then, the FY-4A dust detection data from March 13 to March 17, 2021 was used to track the dust weather process and trace the source of the dust. Figure 5 shown. Figure 5 The schematic diagram shows the occurrence and development process of sandstorm weather in the north around March 15, 2021 obtained according to an embodiment of the present invention; Figure 5(a) means 13:00 on March 14, 2021; Figure 5 (b) means 14:00 on March 14, 2021; Figure 5 (c) means 14:00 on March 15, 2021; Figure 5 (d) represents 14:00 on March 16, 2021; the gray shaded area in the figure is the dust-covered area, and UTC+8 is Beijing time.

[0080] It can be seen that City A was covered by sandstorms at 14:00 on March 15, 2021, and was still affected by sandstorms until 14:00 on March 16. Figure 5 (c) and Figure 5 (d) shows that this is consistent with Figure 3 and Figure 4 The phenomenon is consistent with the air quality monitoring data in the 2017 China International Aviation Expo. Based on the FY-4A dust detection data, at 14:00 on March 14, area B was covered by a large area of ​​dust, while just one hour earlier at 13:00 on March 14, there was no dust in the area or even in the upwind areas. Therefore, it can be determined that the source of the dust process was area B, that is, Figure 5 (b) The area covered by medium gray shadow is a desert with bare surface and loose surface layer, which is consistent with the characteristics of a sand source area.

[0081] At the same time, region B is rich in solar energy resources, with an annual total solar radiation of about 6000MJ / m 2 The annual sunshine hours are more than 3,200 hours. In terms of the abundance and stability of solar energy resources, it is very suitable for the development of photovoltaic power stations. Developing photovoltaic power stations here can reduce the probability of sandstorms in the area while considering power generation, improve the large-scale sandstorm weather in the north in spring, and have strong social, economic and ecological environmental significance.

[0082] According to a second aspect of an embodiment of the present invention, a photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data is also provided. Figure 6 As shown, the photovoltaic sand control site selection device 600 based on air quality and geostationary meteorological satellite data includes: The data acquisition module 610 is used to acquire the air quality data of the monitoring points in the target area; A data screening module 620, for screening the inhalable particulate matter data and the fine particulate matter data in the air quality data at the target time; A preprocessing module 630 is used to preprocess the inhalable particle data and the fine particle data to remove negative values, null values ​​and abnormal values ​​to obtain processed inhalable particle data and processed fine particle data; The time information generating module 640 is used to detect the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data, and generate the time information of the occurrence of sandstorm weather; The location information determination module 650 is used to trace back the source of the sandstorm weather based on the time information of the occurrence of the sandstorm weather by using the geostationary meteorological satellite data to obtain the final location information of the sandstorm source; The site selection module 660 is used to determine the development address of the photovoltaic power station based on the final location information of the sand source.

[0083] In an exemplary embodiment of the present invention, based on the above solution, the time information generation module 640 may further include a calculation submodule, a mutation point submodule and a sandstorm weather identification submodule. The calculation submodule is used to calculate the ratio of the processed inhalable particulate matter data and the processed fine particulate matter data to obtain a time series of the ratio data; The mutation point submodule is used to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data respectively by using the time series mutation identification method, so as to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data; The sandstorm weather identification submodule is used to identify sandstorm weather and generate time information of the occurrence of sandstorm weather when it is detected that both the time series of the inhalable particulate matter data and the time series of the ratio data have significant mutations.

[0084] In an exemplary embodiment of the present invention, based on the above solution, the location information determination module 650 may further include a data acquisition submodule, a preprocessing submodule, a preliminary location determination submodule and a final location determination submodule: The data acquisition submodule is used to acquire geostationary satellite data within a time range corresponding to the time when the sandstorm weather occurs; The preprocessing submodule is used to preprocess the geostationary satellite data to obtain spatial range data that meets the requirements of wind and sand weather source tracing; The preliminary location determination submodule is used to use the spatial range data to gradually trace back the source of the sandstorm weather according to the time when the sandstorm weather occurs, so as to obtain the preliminary location of the sand source; The final location determination submodule is used to perform spatial analysis on the preliminary location of the sand source and map the dust coverage area using geographic information system tools to determine the final location information of the sand source.

[0085] It should be noted that, although several modules and submodules of the underground pipeline detection device are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or submodules described above can be embodied in one module or unit. Conversely, the features and functions of one module or submodule described above can be further divided into multiple modules or submodules to be embodied.

[0086] In addition, in an exemplary embodiment of the present invention, an electronic device capable of implementing the above-mentioned photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data is also provided.

[0087] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0088] Refer to the following Figure 7 An electronic device 700 according to such an embodiment of the present invention is described. Figure 7 The electronic device 700 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0089] like Figure 7 As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: the at least one processing unit 710, the at least one storage unit 720, a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.

[0090] The storage unit stores program codes, which can be executed by the processing unit 710, so that the processing unit 710 performs the steps of various exemplary embodiments of the present invention described in the above “Exemplary Method” section. For example, the processing unit 710 can perform the following steps: Figure 2As shown in S210, the air quality data of the monitoring points in the target area are obtained; S220, the inhalable particle data and the fine particle data in the air quality data at the target time are screened; S230, the inhalable particle data and the fine particle data are pre-processed to remove negative values, null values ​​and abnormal values ​​to obtain processed inhalable particle data and processed fine particle data; S240, the ratio change of the processed inhalable particle data and the processed fine particle data is detected to generate the time information of the occurrence of sandstorm weather; S250, according to the time information of the occurrence of sandstorm weather, the source of sandstorm weather is traced back by using the geostationary meteorological satellite data to obtain the final location information of the sand source; S260, based on the final location information of the sand source, the development address of the photovoltaic power station is determined.

[0091] The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 721 and / or a cache memory unit 722 , and may further include a read-only memory unit (ROM) 723 .

[0092] The storage unit 720 may also include a program / utility 724 having a set (at least one) of program modules 725, such program modules 725 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0093] Bus 730 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0094] The electronic device 700 may also communicate with one or more external devices 770 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 700, and / or any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 750. Furthermore, the electronic device 700 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 760. Figure 7As shown, the network adapter 760 communicates with other modules of the electronic device 700 via the bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0095] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0096] In an exemplary embodiment of the present invention, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present invention is stored. In some possible embodiments, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to perform the steps of various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present invention.

[0097] refer to Figure 8 As shown, a program product 800 for implementing the above-mentioned photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited to this. In the present invention, the readable storage medium can be any tangible medium containing or storing a program, and the program can be used by or in combination with an instruction execution system, an apparatus or a device.

[0098] The program product may use any combination of one or more readable storage media. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0099] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, 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 may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0100] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0101] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0102] Other embodiments of the invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0103] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data, characterized in that: include: Obtain air quality data from monitoring points in the target area; Screen the inhalable particulate matter data and fine particulate matter data in the air quality data within the target time; Preprocessing the inhalable particulate matter data and the fine particulate matter data to remove negative values, null values ​​and abnormal values ​​to obtain processed inhalable particulate matter data and processed fine particulate matter data; Detecting the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data to generate time information of the occurrence of sandstorm weather; According to the time information of the occurrence of the sandstorm weather, the source of the sandstorm weather is traced back using the geostationary meteorological satellite data to obtain the final location information of the sand source; Based on the final location information of the sand source, the development address of the photovoltaic power station is determined.

2. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 1 is characterized in that: Detecting the change in the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data and generating the time information of the occurrence of sandstorm weather includes: Calculating the ratio of the processed inhalable particulate matter data to the processed fine particulate matter data to obtain a time series of ratio data; Using a time series mutation identification method, respectively analyzing the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data, so as to detect mutation points in the time series of the processed inhalable particulate matter data and the time series of the ratio data; When it is detected that both the time series of the inhalable particulate matter data and the time series of the ratio data have significant mutations, it is identified as sandstorm weather and the time information of the occurrence of the sandstorm weather is generated.

3. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 2 is characterized in that: The method of using a time series mutation identification method to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data respectively to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data includes: Calculating the difference between the measured value of the inhalable particulate matter data or the ratio data at each moment in the time series and the preset expected value; Accumulating the difference at each moment to obtain a cumulative sum; When the accumulated sum exceeds a preset threshold at the current moment, it is determined that a significant mutation occurs in the time series at the current moment.

4. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 2 is characterized in that: The method of using a time series mutation identification method to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data respectively to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data includes: Calculate the average measurement value in the sliding window of the target length at the current moment to obtain the current sliding window average value; Calculate the average measurement value in the sliding window of the target length within the pushback duration to obtain the pushback sliding window average value; Calculate the difference between the current sliding window average value and the pushback sliding window average value to obtain the difference value; When the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

5. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 2 is characterized in that: The method of using a time series mutation identification method to analyze the time series changes of the processed inhalable particulate matter data and the time series changes of the ratio data respectively to detect the mutation points in the time series of the processed inhalable particulate matter data and the mutation points in the time series of the ratio data includes: Calculate the linear regression slope of the measured value in the sliding window of the target length at the current moment to obtain a first linear regression slope; Calculate the linear regression slope of the sliding window measurement value of the target length within the pushback time to obtain a second linear regression slope; The difference between the first linear regression slope and the second linear regression slope is compared, and when the difference is greater than a preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

6. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 1 is characterized in that: According to the time information of the occurrence of the sandstorm weather, the source of the sandstorm weather is traced back using the geostationary meteorological satellite data to obtain the final location information of the sand source, including: Acquiring geostationary satellite data within a time range corresponding to the time when the sandstorm weather occurs; Preprocessing the geostationary satellite data to obtain spatial range data that meets the requirements for tracing the source of sandstorm weather; According to the time when the sandstorm weather occurs, the spatial range data is used to gradually trace back the source of the sandstorm weather in time to obtain the preliminary location of the sand source; The preliminary location of the sand source is spatially analyzed, and the dust coverage area is mapped using geographic information system tools to determine the final location information of the sand source.

7. The photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to claim 6 is characterized in that: The geostationary satellite data is preprocessed to obtain spatial range data that meets the requirements of wind and sand weather source tracing, including: Based on the mapping data of row and column numbers and longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, the geostationary meteorological satellite data is converted into longitude and latitude coordinates; The latitude and longitude coordinates are converted to a preset projection type, and the spatial range of the target area is cut out according to the requirements of sandstorm weather tracing, so as to obtain spatial range data that meets the requirements of sandstorm weather tracing.

8. A photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data, used to execute the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to obtain air quality data of monitoring points in the target area; A data screening module, used for screening the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time; A preprocessing module, used to preprocess the inhalable particulate matter and fine particulate matter data, remove negative values, null values ​​and abnormal values, and obtain processed inhalable particulate matter data and processed fine particulate matter data; A time information generating module, used to detect the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data, and generate time information of the occurrence of sandstorm weather; A location information determination module is used to trace back the source of the sandstorm weather based on the time information of the occurrence of the sandstorm weather by using the geostationary meteorological satellite data to obtain the final location information of the sand source; The site selection module is used to determine the development address of the photovoltaic power station based on the final location information of the sand source.

9. An electronic device, characterized in that: include: processor; as well as A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data as described in any one of claims 1 to 7 is implemented.

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