Photovoltaic Sand Control Site Selection Method Based on Air Quality and Geostationary Meteorological Satellite Data

Abstract

The present invention provides a method for selecting a photovoltaic desert control site based on air quality and geostationary meteorological satellite data, which relates to the technical field of photovoltaic modules, and includes: screening inhalable particulate matter data and fine particulate matter data in the air quality data of the target time; preprocessing the inhalable particulate matter data and the fine particulate matter data to remove negative values, null values and outliers, so as to obtain the processed inhalable particulate matter data and the processed fine particulate matter data; detecting the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data to generate the time information of the occurrence of sandstorm weather; according to the time information of the occurrence of sandstorm weather, using the geostationary meteorological satellite data to trace back the source of the sandstorm weather to obtain the final position information of the sand source; determining the development address of the photovoltaic power station based on the final position information of the sand source. The present invention can suppress sand dust and improve the ecological value of the photovoltaic power station while developing photovoltaic power generation.

Description

Background Art

[0002] In spring, the north is vulnerable to sand and dust weather, which has an adverse impact on elements such as the production and life of residents in this area, traffic safety, and industrial production. The reason for sand and dust weather is that in spring, the dry sand source areas are lifted by the strong northwest wind driven by the Siberian high pressure and enter 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 areas, they can play a strong role in suppressing sand lifting, thereby reducing the frequency and intensity of sand and dust weather.

[0003] The existing photovoltaic power station site selection methods usually rely on the abundance and stability of solar energy resources, comprehensively consider the impact of terrain slope and aspect on solar energy resources, and at the same time analyze various restrictive factors such as hydrogeological conditions, the distance between roads and transmission lines, and the avoidance requirements of nature reserves and residential areas. Although this method is relatively comprehensive, when selecting the site of a photovoltaic power station, the existing technology lacks in-depth consideration of its sand control effect and priority weighting for sand source areas, resulting in the potential of photovoltaic power stations in suppressing sand and dust not being fully utilized.

[0004] Therefore, the existing photovoltaic power station site selection technology does not adequately consider its sand control effect and is difficult to fully play the role of photovoltaic sand control. Thus, there is an urgent need for a method that can incorporate a sand source area backtracking and positioning algorithm into the photovoltaic power station site selection process, taking into account sand control while improving power generation and economic benefits, thereby suppressing sand and dust weather and enhancing its ecological value. Summary of the Invention

[0005] 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 the first aspect of the embodiments of the present invention, a photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data is provided, including:

[0007] [[ID=2,0]]Obtain the air quality data of the monitoring points in the target area;

[0008] Screen the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time;

[0009] Preprocess the inhalable particulate matter data and fine particulate matter data to remove negative values, null values, and outliers, obtaining the processed inhalable particulate matter data and the processed fine particulate matter data;

[0010] 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 sand and dust weather;

[0011] According to the time information of the occurrence of the sand and dust weather, use the geostationary meteorological satellite data to trace back the source of the sand and dust weather, and obtain the final position information of the sand source area;

[0012] Based on the final position information of the sand source area, determine the development address of the photovoltaic power station.

[0013] In some exemplary embodiments of the present invention, based on the foregoing solution, detecting the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data, and generating the time information of the occurrence of the sand and dust weather includes:

[0014] Calculate the ratio of the processed inhalable particulate matter data and the processed fine particulate matter data to obtain the time series of the ratio data;

[0015] Use the 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, 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;

[0016] 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 sand and dust weather and the time information of the occurrence of the sand and dust weather is generated.

[0017] In some exemplary embodiments of the present invention, based on the foregoing solution, the use of the 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, 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 includes:

[0018] Calculate the difference between the measured value of each moment of the inhalable particulate matter data or the ratio data in the time series and the preset expected value;

[0019] Accumulate the differences at each moment to obtain the accumulated sum;

[0020] When the accumulated sum exceeds the preset threshold at the current moment, it is determined that a significant mutation occurs in the time series at the current moment.

[0021] In some exemplary embodiments of the present invention, based on the foregoing solution, the use of the 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, 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 includes:

[0022] Calculate the measurement average value within the sliding window of the target length at the current moment to obtain the current sliding window average value;

[0023] Calculate the measurement average value within the sliding window of the target length during the backtracking time period to obtain the backtracking sliding window average value;

[0024] Calculate the difference between the current sliding window average value and the backtracking sliding window average value to obtain the difference value;

[0025] When the difference value is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0026] In some exemplary embodiments of the present invention, based on the foregoing solution, using the time series mutation identification method, analyzing 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:

[0027] Calculate the linear regression slope of the measured values within the sliding window of the target length at the current moment to obtain the first linear regression slope;

[0028] Calculate the linear regression slope of the measured values within the sliding window of the target length during the backtracking time period to obtain the second linear regression slope;

[0029] Compare the difference between the first linear regression slope and the second linear regression slope. When the difference is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0030] In some exemplary embodiments of the present invention, based on the foregoing solution, according to the time information of the occurrence of the sand-dust weather, using the geostationary meteorological satellite data to trace back the origin of the sand-dust weather to obtain the final position information of the sand source area includes:

[0031] Obtain the geostationary satellite data within the time range corresponding to the time of the occurrence of the sand-dust weather;

[0032] Preprocess the geostationary satellite data to obtain the spatial range data that meets the requirements of sand-dust weather origin tracing;

[0033] According to the time of the occurrence of the sand-dust weather, use the spatial range data to gradually trace back the origin of the sand-dust weather in time to obtain the preliminary position of the sand source area;

[0034] Conduct a spatial analysis on the preliminary position of the sand source area, and combine with the geographic information system tool to draw the sand-dust covered area to determine the final position information of the sand source area.

[0035] In some exemplary embodiments of the present invention, based on the foregoing solution, preprocessing the geostationary satellite data to obtain spatial range data that meets the requirements for tracing the source of sand and dust weather includes:

[0036] Based on the mapping data between the row and column numbers and the longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, converting the geostationary meteorological satellite data into longitude and latitude coordinates;

[0037] Converting the longitude and latitude coordinates to a preset projection type, and cropping out the spatial range of the target area according to the requirements for tracing the source of sand and dust weather to obtain spatial range data that meets the requirements for tracing the source of sand and dust weather.

[0038] According to the second aspect of the embodiments of the present invention, there is provided a photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data, including:

[0039] A data acquisition module for acquiring air quality data of monitoring points in a target area;

[0040] A data screening module for screening inhalable particulate matter data and fine particulate matter data in the air quality data at a target time;

[0041] A preprocessing module for preprocessing the inhalable particulate matter data and the fine particulate matter data to remove negative values, null values, and outliers, and obtaining processed inhalable particulate matter data and processed fine particulate matter data;

[0042] A time information generation module for detecting the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data, and generating time information of the occurrence of sand and dust weather;

[0043] A location information determination module for tracing the source of sand and dust weather using geostationary meteorological satellite data according to the time information of the occurrence of sand and dust weather, and obtaining the final location information of the sand source area;

[0044] A site selection module for determining the development address of a photovoltaic power station based on the final location information of the sand source area.

[0045] According to the third aspect of the embodiments of the present invention, there is provided an electronic device, including: a processor; and a memory, on which computer-readable instructions are stored, 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.

[0046] According to the fourth aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored, 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 in the first aspect is implemented.

[0047] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0048] In the embodiments of the present invention, by using air quality data and geostationary meteorological satellite data, accurate identification of sandstorm weather and sand sources is achieved. Incorporating sand sources into the site selection considerations of photovoltaic power stations enables the site selection of photovoltaic power stations to not only take into account the effective utilization of solar energy resources but also effectively improve the stability of sand sources, with the function of suppressing dust and reducing sand, thus realizing the dual benefits of environmental governance and photovoltaic power generation.

[0049] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The drawings herein are incorporated into the specification and constitute a part of the present invention, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0051] Figure 1 A schematic diagram showing the 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 that can apply the embodiments of the present invention;

[0052] Figure 2 A schematic flowchart showing the photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data according to some embodiments of the present invention;

[0053] Figure 3 A schematic diagram showing the index change chart of PM10 in City A from March 14, 2021 to March 17, 2021 according to some embodiments of the present invention;

[0054] Figure 4 A schematic diagram showing the ratio change chart of PM10 and PM2.5 in City A from March 14, 2021 to March 17, 2021 according to some embodiments of the present invention;

[0055] Figure 5 A schematic diagram showing the photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data according to some embodiments of the present invention;

[0056] Figure 6 A schematic diagram showing the structure of the computer system of an electronic device according to some embodiments of the present invention;

[0057] Figure 7 A schematic diagram showing a computer-readable storage medium according to some embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0059] The terms used in the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention. The singular forms "a", "the", and "said" used in the present invention and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0060] It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, such 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 "when" or "while" or "in response to determining".

[0061] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a photovoltaic desert control site selection method and device based on air quality and geostationary meteorological satellite data to which embodiments of the present invention can be applied is shown.

[0062] As Figure 1 shown, the system architecture 100 may include one or more of terminal devices such as a desktop computer 101, a portable computer 102, a smart phone 103, etc., 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 fiber optic cables, etc. The terminal device may be various electronic devices having data processing functions, and a display screen is provided on the electronic device for presenting the photovoltaic power station development address to the user, including but not limited to the above-mentioned desktop computer, portable computer, smart phone, etc. It should be understood that Figure 1 the numbers of the terminal devices, the network, and the server in

[0063] The photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data provided by the embodiments of the present invention can generally be executed by a terminal device. Correspondingly, the photovoltaic desert control site selection device based on air quality and geostationary meteorological satellite data is generally set in the terminal device. However, those skilled in the art can easily understand that the photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data provided by the embodiments of the present invention can also be executed by the server 105. Correspondingly, the photovoltaic desert control site selection device based on air quality and geostationary meteorological satellite data can also be set in the server 105. No special limitation is made in this exemplary embodiment.

[0064] 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 desert control site selection solution based on air quality and geostationary meteorological satellite data of the present invention can be deployed independently to display the development addresses of photovoltaic power stations in different forms. In other implementation scenarios, the photovoltaic desert control site selection solution 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. For example, it can be deployed in the analysis software for photovoltaic desert control site selection based on air quality and geostationary meteorological satellite data. The present invention does not make any special restrictions on the application mode of the photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data.

[0065] Next, the embodiments of the present invention will be described in detail.

[0066] As Figure 2 shown, Figure 2 is a flowchart of a photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data shown by the present invention according to an exemplary embodiment, including the following steps:

[0067] S210: Obtain the air quality data of the monitoring points in the target area;

[0068] S220: Screen the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time;

[0069] S230: Preprocess the inhalable particulate matter data and fine particulate matter data to remove negative values, null values and outliers, and obtain the processed inhalable particulate matter data and processed fine particulate matter data;

[0070] S240: 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 sand and dust weather;

[0071] S250: According to the time information of the occurrence of sand and dust weather, use the geostationary meteorological satellite data to trace back the source of the sand and dust weather, and obtain the final position information of the sand source area;

[0072] S260: Determine the development address of the PV power station based on the final position information of the sand source area.

[0073] By combining air quality data and geostationary meteorological satellite data in the PV sand control site selection method, the present invention can accurately identify the sand blowing situation in the northern sand source areas. Under the monitoring of air quality data, the time series analysis of the concentrations of different particulate matters (such as inhalable particulate matter and fine particulate matter) can effectively judge the occurrence time of sand and dust weather, and trace the sand and dust sources with the help of geostationary meteorological satellite data, so as to obtain the specific scope of the sand source area. Through the interactive application of this data, accurate information on the location of the sand source area is obtained, laying an accurate data foundation for the priority site selection of PV power stations in the sand source area.

[0074] On this basis, based on the sand source area site selection, the shielding characteristics of the PV module array can be effectively utilized to increase the surface roughness, further reduce the surface wind speed, and effectively control the probability of sand blowing. The PV power station can block solar radiation and reduce the surface temperature, thereby reducing the vertical air convection caused by the increase in surface temperature. Thus, the PV power station can effectively inhibit the generation of sand and dust caused by the convection phenomenon, and significantly reduce the double adverse effects of sand and dust weather on the surrounding environment and the PV power station.

[0075] In addition, building a PV power station in the sand source area can promote the vegetation restoration in the sand source area by improving the water retention conditions in the sand source area. The surface shading effect of the PV module can reduce the evaporation rate of soil moisture, improve the moisture conditions in the local environment, and provide a more suitable growth environment for the vegetation in the sand source area. Thus, the combination of the sand source area screening strategy and the shading effect of the PV module during the site selection process helps to improve the vegetation coverage, enhance the surface stability, and further reduce the wind erosion effect, enabling the effective exertion of the ecological benefits and dust suppression effect of the PV power station.

[0076] In S210, obtain the air quality data of the monitoring points in the target area.

[0077] Here, the air quality data includes the air quality data of the monitoring stations in each prefecture-level city in the northern region collected from the national real-time air quality release platform. The air quality data has an hourly time resolution and contains important indicators for monitoring sand and dust weather, namely the concentration values of fine particulate matter (PM2.5) and inhalable particulate matter (PM10), which are used as important indicators for judging sand and dust weather.

[0078] The target area can be any city. Since sand and dust weather mainly affects the northern region, in the embodiments of the present invention, the target area is mainly determined from northern cities, or all northern cities can be monitored simultaneously.

[0079] The present invention does not specifically limit the method for obtaining air quality data. Multiple methods can be used to obtain air quality data, such as monitoring through sensors, gas detection instruments, or based on remote sensing technology, etc. 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 the embodiment of the present invention, the air quality data is obtained through the national real-time air quality release platform, and this data records the specific air quality data of each prefecture-level city.

[0080] In S220, filter the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time.

[0081] Fine particulate matter (PM2.5) is a pollutant with a particle size less than 2.5 micrometers in the air, usually including combustion particles, organic compounds, and metal particles, mainly used to evaluate the impact of combustion sources and fine pollutants; inhalable particulate matter (PM10) is a pollutant with a particle size less than 10 micrometers, containing pollen and dust particles, and can reflect the change in the concentration of dust in the air. By monitoring the changes in the concentrations of PM2.5 and PM10, especially the significant upward trend of PM10, a preliminary judgment can be made on the occurrence of sand-dust weather, thereby providing reliable basic data for subsequent sand-dust weather identification and sand source tracing.

[0082] In addition, since sand-dust weather mainly occurs in spring (March, April, and May), therefore, the target time can be spring. In some embodiments, the target time can also be autumn or winter, or the entire autumn and winter.

[0083] In addition, the PM10 and PM2.5 data of the target area can also be filtered based on the sensor quality or spatial location. When filtering based on the sensor quality, records with unqualified data quality or obvious outliers can be filtered out. When filtering based on the spatial location, the PM10 and PM2.5 data within the area can be filtered according to a specific area or location. [[ID=..]]

[0084] In S230, preprocess the inhalable particulate matter data and fine particulate matter data, remove negative values, null values, and outliers, and obtain the processed inhalable particulate matter data and processed fine particulate matter data.

[0085] Here, if there are negative values in the data (such as negative measurement results due to sensor errors), they can be removed or replaced with zero or other reasonable values. For missing or empty data, one 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, statistical methods can be used, such as screening based on the mean and standard deviation (e.g., the 3-sigma rule), to detect and remove outliers that deviate significantly from the normal range; more complex algorithms can also be used, such as the interquartile range method (IQR) or outlier detection methods based on machine learning.

[0086] In addition, after removing negative values, null values, and outliers, the data can be smoothed, normalized, etc., so that the processed inhalable particulate matter data and the processed fine particulate matter data are more unified, facilitating further processing of the subsequent data.

[0087] In S240, detecting the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data to generate the time information of the occurrence of sand and dust weather includes:

[0088] Calculating the ratio of the processed inhalable particulate matter data and the processed fine particulate matter data to obtain the time series of the ratio data;

[0089] Using the 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, 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;

[0090] When significant mutations occur in both the time series of the inhalable particulate matter data and the time series of the ratio data, it is identified as sand and dust weather and the time information of the occurrence of sand and dust weather is generated.

[0091] Generally, 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, a rapid increase in the PM10 indicator may indicate the occurrence of sand and dust weather. However, since the PM10 indicator usually includes PM2.5 pollutants during measurement, the PM10 indicator will also increase rapidly in ordinary haze weather, and sand and dust weather cannot be accurately identified only by using the PM10 indicator. Therefore, in order to accurately identify sand and dust weather, the present invention introduces an indicator, namely PM10 / PM2.5, which will also increase rapidly during sand and dust weather and has little change in ordinary haze weather.

[0092] After calculating the ratio of the processed inhalable particulate matter data and fine particulate matter data and generating a time series, analyzing the time series of the ratio data and the inhalable particulate matter data provides a dual verification method for the accurate identification of sand and dust weather. This process not only considers the concentration change of larger particulate matter in the air but also introduces the ratio change between fine particulate matter and larger particulate matter, thus making the detection process more accurate in discriminating sand and dust weather.

[0093] In time series analysis, using the time series mutation identification method to monitor the changes in inhalable particulate matter data and ratio data can detect the mutation points of the time series of both respectively. By independently analyzing the time series of these two types of data, this process not only provides clear identification conditions for the mutation of the original data but also avoids the risk of misjudgment caused by the change of a single data. Therefore, detecting the mutation points in their respective time series and comparing them enables this method to more sensitively capture the occurrence of sand and dust weather.

[0094] In addition, only when significant mutations occur in the time series of both inhalable particulate matter data and ratio data is it identified as sand and dust weather, and this condition can greatly reduce the possibility of misjudgment. By introducing dual time series mutation conditions, the influence of fluctuations caused by general atmospheric particle changes is excluded, thereby enhancing the accuracy and reliability of the judgment of sand and dust weather. Therefore, through the discrimination of sand and dust based on dual mutation identification, the misjudgment caused by the fluctuation of a single data in the prior art is avoided, ensuring that the occurrence time of sand and dust weather can be accurately calibrated, providing more accurate time information for subsequent backtracking of sand sources and the siting of photovoltaic power stations.

[0095] The rapid rise detection of the PM10 and PM10 / PM2.5 time series curves can be carried out in different ways. For example, in some embodiments, the rapid rise detection of the PM10 and PM10 / PM2.5 time series curves includes:

[0096] 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 a preset expected value;

[0097] Accumulating the differences at each moment to obtain an accumulated sum;

[0098] 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.

[0099] Here, the difference is calculated as:

[0100]

[0101] Wherein, is The measured value at a moment, is a preset expected value.

[0102] The cumulative sum is expressed as:

[0103]

[0104] where, is the cumulative sum at the moment of is the cumulative sum at the moment of is a constant used to control the growth of the cumulative sum.

[0105] In this embodiment, determining the best values of the expected value , the constant and the preset threshold can be calculated from a large amount of dust process data.

[0106] In some other embodiments, the rapid rise detection of the two time series curves of PM10 and PM10 / PM2.5 includes:

[0107] Calculating the measured average value within the sliding window of the target length at the current moment to obtain the current sliding window average value ; where, is the measured value at the moment of is the window length.

[0108] Calculating the measured average value within the sliding window of the target length within the backtracking duration to obtain the backtracking sliding window average value ;

[0109] Calculating the difference between the current sliding window average value and the backtracking sliding window average value to obtain the difference ;

[0110] When the difference is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0111] In this embodiment, the best values of the window length , the backtracking duration and the preset threshold can be calculated from a large amount of dust process data. Generally speaking, the sliding window length can take values such as 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 worse the sensitivity, but the more credible its result. The backtracking duration The rate of change needs to depend on the change itself to be detected. Generally speaking, during a sand-dust process, the transition from no sand-dust to a sand-dust weather occurs within 1 - 2 hours. It can take a value of 1 or 2. 、 And the value of the preset threshold can take the optimal value in the calculations of a large number of sand-dust processes.

[0112] In another embodiment, the rapid rise detection of the two time series curves of PM10 and PM10 / PM2.5 may further include:

[0113] Calculating the linear regression slope of the measured values within the sliding window of the target length at the current moment to obtain the first linear regression slope , X where

[0114] represents the measured value; Calculating the linear regression slope of the measured values of the sliding window with a target length retrograde duration ;

[0115] Comparing the difference between the first linear regression slope and the second linear regression slope, and when the difference is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

[0116] In S250, according to the time information of the occurrence of the sand-dust weather, using the geostationary meteorological satellite data to trace back the origin of the sand-dust weather, the obtained final position information of the sand source area includes:

[0117] Obtaining the geostationary satellite data within the time range corresponding to the time of the occurrence of the sand-dust weather;

[0118] Preprocessing the geostationary satellite data to obtain the spatial range data meeting the requirements of tracing the origin of the sand-dust weather;

[0119] According to the time of the occurrence of the sand-dust weather, using the spatial range data to gradually trace back the origin of the sand-dust weather in time to obtain the preliminary position of the sand source area;

[0120] Conducting spatial analysis on the preliminary position of the sand source area and combining with the geographical information system tool to draw the sand-dust covered area to determine the final position information of the sand source area.

[0121] In the embodiments of the present invention, the occurrence time of the sand-dust process is determined through two time series curves of PM10 and PM10 / PM2.5, and this occurrence time refers to the sand-dust occurrence time 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 occurrence time of the sand-dust weather, the time range corresponding to the occurrence time of the sand-dust weather can be the specific time of the occurrence of the sand-dust weather, or it can be a period of time pushed back from this specific time. Taking the specific time of the occurrence of the sand-dust weather as the reference point can more accurately calibrate the starting time of the sand-dust process. In some embodiments, since there may have been a period of time between the monitored occurrence time of the sand-dust weather and the sand-raising time at the sand source, therefore, taking the sand-dust occurrence time as the starting time of the time range, and tracing back 1 - 3 days on this basis to trace its origin. This selection of the time range can ensure that the data source covers the whole process of the sand-dust weather from the source to the monitoring station, making the obtained data have both time continuity and cover the key change stages of the sand-dust activities at the sand source, thus providing a complete and continuous data basis for subsequent analysis.

[0122] A geostationary satellite, also known as a geosynchronous satellite or a geostationary orbit satellite, refers to a satellite located at an altitude of about 35,786 kilometers (22,236 miles) above the Earth, and its revolution period is the same as 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, which makes them very important tools in the fields of communication, meteorological observation, earth resource exploration, etc.

[0123] Geostationary satellite data includes meteorological data, communication data, earth observation data, and navigation and positioning data. Meteorological data can include meteorological information such as cloud images, temperature, humidity, wind direction and wind speed.

[0124] In the embodiments of the present invention, FY-4A data is used as the geostationary satellite data. FY-4A data refers to the data collected and transmitted from the Fengyun-4A (FY-4A), the second-generation geostationary meteorological satellite in China. The FY-4A satellite is a major scientific and technological achievement in the meteorological field of China. It has the observation capabilities of high temporal resolution, high spatial resolution, and high spectral resolution, and can provide multi-spectral images and data of the Earth's surface and atmosphere in real time and continuously.

[0125] Preprocessing the geostationary satellite data to obtain the spatial range data meeting the requirements of sand-dust weather traceability includes:

[0126] Based on the mapping data of the row and column numbers and the longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, converting the geostationary meteorological satellite data into longitude and latitude coordinates;

[0127] The latitude and longitude coordinates are converted to a preset projection type, and the spatial range of the target area is clipped according to the requirements of sandstorm weather tracing, so as to obtain spatial range data that meets the requirements of sandstorm weather tracing.

[0128] 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.

[0129] 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 thus ensuring the spatial accuracy of subsequent sand and dust tracing.

[0130] Based on the needs of dust storm source tracing, the spatial scope of the target region is clipped, such as the inland dust-prone areas of East Asia (40°-50°N, 85°-120°E), to filter out redundant data from non-dust source areas. This clipping process focuses on the key source areas of dust storms, making the analysis data more spatially targeted, thereby reducing the computational burden and improving tracing efficiency.

[0131] Through this preprocessing process, the spatial range data obtained that meets the needs of wind and sand weather tracing not only has the accuracy of geographic coordinates and the consistency of spatial projection, but also achieves effective focusing of spatial data through clipping operations, providing more accurate data support for subsequent sand and dust source positioning and tracing analysis.

[0132] According to the time when the sandstorm weather occurs, the spatial range data is used to gradually trace back the time of the source of the sandstorm weather to obtain the preliminary location of the sand source.

[0133] Here, step-by-step time backtracking refers to analyzing data at each moment within the backtracking timeframe in chronological order. At each moment, the spatial location of the dust-covered area is extracted, recording the dynamic changes in the dust-covered area. By cumulatively analyzing data from each time point, the direction and speed of dust spread can be observed, thereby identifying the characteristic locations of dust sources. By superimposing the step-by-step backtracking data, the source of the dust-covered area is determined. As the time backtracking progresses, the dust-covered area gradually shrinks to the earliest dust-generating location. This gradually shrinking dust-covered area allows the initial formation area of the dust, i.e., the preliminary location of the dust source, to be determined.

[0134] Conduct spatial analysis of the preliminary location of the sand source, and use geographic information system tools to map the dust coverage area to determine the final location information of the sand source.

[0135] In this step, based on the preliminary location of the sand source determined by step-by-step time backtracking, a spatial analysis tool (such as Geographic Information System, GIS) is used to evaluate its influence range in the formation process of sand and dust weather. By analyzing the geographical features, surface properties of this area and its connectivity with surrounding areas, the contribution degree of this area in sand and dust weather can be identified more accurately, so as to screen out non-critical areas and make the positioning of the sand source more focused.

[0136] Using the GIS tool and combining the geostationary meteorological satellite data at different time points, the spatial boundary of the sand and dust covered area is drawn. In the GIS environment, the continuous trajectory of sand and dust coverage is shown by overlaying the distribution layers of sand and dust concentration. This drawing process visually shows the diffusion path of sand and dust, which helps to judge the direction and speed of the spread of sand and dust weather from the initial position, and provides a reliable basis for the spatial feature analysis of the sand source.

[0137] Finally, through the step-by-step analysis of the sand and dust covered area, the range of the sand source is further narrowed, and the area with the highest sand and dust frequency and concentration is marked as the final position information of the sand source. Combining with the historical data of sand and dust weather, the importance of this area in the occurrence process of sand and dust weather can be determined, providing specific data support for the sand control site selection of the photovoltaic power station.

[0138] Through this process, using the spatial analysis and visualization capabilities of the GIS tool, not only can the process of sand and dust diffusion be dynamically displayed, but also the precise position and range of the sand source can be finally confirmed, providing a scientific basis for the sand control function and ensuring that the photovoltaic site selection is more targeted.

[0139] In S260, based on the final position information of the sand source, the development address of the photovoltaic power station is determined.

[0140] In some embodiments, according to the finally determined sand source location, evaluate the occurrence frequency, influence range and wind-sand intensity of its sand and dust weather, clarify the sand control potential of building a photovoltaic power station in this area, and ensure that the site selection has sand reduction benefits. The geographical environment around the sand source can also be comprehensively evaluated, including natural conditions such as surface stability, vegetation coverage, terrain, slope, etc., to determine the layout adaptability of photovoltaic modules in this area, so as to ensure that the photovoltaic power station can not only effectively inhibit wind and sand, but also operate normally in this environment. In addition, the abundance and stability of solar energy resources can be evaluated in combination with the sand source location, and the average annual sunshine duration and radiation amount can be calculated to ensure that the selected area has sand control function while meeting the resource requirements of photovoltaic power generation.

[0141] 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.

[0142] 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 PV power station site that meets the requirements for sand suppression, power generation efficiency, and cost feasibility. This multi-dimensional decision-making process ensures that the PV power station maximizes resource utilization efficiency while optimizing dust suppression effectiveness.

[0143] 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 represents 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.

[0144] Through calculation, it was 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 in the five hours from 8:00 to 12:00 on the same day two hours ago was 666μg / m3, which showed a significant increase. 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 was 3.53 in the five hours from 10:00 to 14:00 on March 15, 2021, and 1.05 in the five hours from 8:00 to 12:00 on the same day. The difference between the two was 2.48, which is greater than the set threshold of 2. Since the increase in the sliding average of the two indicators of PM10 and PM10 / PM2.5 in City A at 14:00 on March 15, 2021 was greater than the set threshold, it was determined that sandstorm weather occurred in City A at that time.

[0145] Then, the FY-4A sand and dust detection data from March 13 to March 17, 2021 was used to track the sandstorm weather process and trace the source of the sand.

[0146] It can be seen that City A was covered by sandstorms at 14:00 on March 15, 2021, and continued to be affected by sandstorms until 14:00 on March 16. Figure 3 andFigure 4 This is consistent with the phenomenon shown by the air quality monitoring data in the region. Based on the FY-4A dust detection data, by backtracking in time, at 14:00 on March 14th, area B was covered by a large area of dust. However, just one hour earlier, at 13:00 on March 14th, there was no dust coverage in this area or even in the upwind area. Therefore, it can be judged that the dust source of this dust process is area B.

[0147] At the same time, area B is rich in solar energy resources. The total annual solar radiation is about 6000 MJ / m 2 , and the annual sunshine hours are more than 3200 hours. In terms of the abundance and stability of solar energy resources, it is very suitable for the development of photovoltaic power stations. Developing a photovoltaic power station in this area can reduce the probability of sand blowing in this area while considering the power generation, and improve the large-scale dust weather in spring in the north, which has strong social, economic and ecological environmental significance.

[0148] According to the second aspect of the embodiments of the present invention, there is also provided a photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data. Referring to Figure 5 as shown, the photovoltaic sand control site selection device 600 based on air quality and geostationary meteorological satellite data includes:

[0149] A data acquisition module 610, configured to acquire air quality data of monitoring points in a target area;

[0150] A data screening module 620, configured to screen inhalable particulate matter data and fine particulate matter data in the air quality data at a target time;

[0151] A preprocessing module 630, configured to preprocess the inhalable particulate matter data and the fine particulate matter data, remove negative values, null values and outliers, and obtain processed inhalable particulate matter data and processed fine particulate matter data;

[0152] A time information generation module 640, configured 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 dust weather;

[0153] A location information determination module 650, configured to use the geostationary meteorological satellite data to trace back the source of the dust weather according to the time information of the occurrence of the dust weather, and obtain the final location information of the dust source;

[0154] A site selection module 660, configured to determine the development address of a photovoltaic power station based on the final location information of the dust source.

[0155] In an exemplary embodiment of the present invention, based on the foregoing solution, the time information generation module 640 may further include a calculation sub-module, a mutation point sub-module and a dust weather recognition sub-module.

[0156] The calculation sub-module 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 ratio data;

[0157] The mutation point sub-module 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 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;

[0158] The dust weather identification sub-module is used to identify as a dust weather and generate the time information of the occurrence of the dust weather when significant mutations occur in both the time series of the inhalable particulate matter data and the time series of the ratio data.

[0159] In an exemplary embodiment of the present invention, based on the foregoing solution, the location information determination module 650 may further include a data acquisition sub-module, a preprocessing sub-module, a preliminary location determination sub-module, and a final location determination sub-module:

[0160] The data acquisition sub-module is used to acquire geostationary satellite data within a time range corresponding to the time of the occurrence of the dust weather;

[0161] The preprocessing sub-module is used to preprocess the geostationary satellite data to obtain spatial range data that meets the requirements of tracing the source of the sand and dust weather;

[0162] The preliminary location determination sub-module is used to gradually trace back the time of the dust weather source by using the spatial range data according to the time of the occurrence of the dust weather to obtain the preliminary location of the sand source;

[0163] The final location determination sub-module is used to perform spatial analysis on the preliminary location of the sand source and combine with a geographic information system tool to draw the dust-covered area to determine the final location information of the sand source.

[0164] It should be noted that although several modules and sub-modules of the underground pipeline detection device are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present invention, the features and functions of two or more of the above-described modules or sub-modules may be embodied in one module or unit. Conversely, the features and functions of one module or sub-module described above may be further divided and embodied by multiple modules or sub-modules.

[0165] In addition, in an exemplary embodiment of the present invention, an electronic device capable of implementing the above photovoltaic sand control site selection method based on air quality and geostationary meteorological satellite data is also provided.

[0166] Those skilled in the art can understand that various aspects of the present invention can be implemented as a system, a method, or a program product. Therefore, various aspects of the present invention can be specifically implemented in the following forms, namely: a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuit", "module", or "system" here.

[0167] Reference will now be made to Figure 6 to describe the electronic device 700 according to such an embodiment of the present invention. Figure 7 The illustrated electronic device 700 is merely an example and should not impose any limitation on the functions and the scope of use of the embodiments of the present invention.

[0168] As Figure 6 shown, the electronic device 700 is presented in the form of a general-purpose computing device. The components of the electronic device 700 may include, but are not limited to: at least one of the above-mentioned processing units 710, at least one of the above-mentioned storage units 720, a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.

[0169] Among them, the storage unit stores program codes, and the program codes can be executed by the processing unit 710, so that the processing unit 710 executes the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" part of the present invention. For example, the processing unit 710 may execute S210 as shown in Figure 2 to obtain the air quality data of the monitoring points in the target area; S220, to screen the inhalable particulate matter data and fine particulate matter data in the air quality data at the target time; S230, to preprocess the inhalable particulate matter data and the fine particulate matter data, remove negative values, null values, and outliers, and obtain the processed inhalable particulate matter data and the processed fine particulate matter data; S240, 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 the sand and dust weather; S250, according to the time information of the occurrence of the sand and dust weather, use the geostationary meteorological satellite data to trace back the source of the sand and dust weather and obtain the final position information of the sand source area; S260, based on the final position information of the sand source area, determine the photovoltaic power station development address.

[0170] The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 721 and / or a cache storage unit 722, and may further include a read-only storage unit (ROM) 723.

[0171] The storage unit 720 may also include a program / utilities 724 having a set (at least one) of program modules 725. Such program modules 725 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0172] The bus 730 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus structures.

[0173] The electronic device 700 may also communicate with one or more external devices 770 (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or may communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be through an input / output (I / O) interface 750. And, the electronic device 700 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 760. As Figure 6 shown, the network adapter 760 communicates with other modules of the electronic device 700 through the bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may 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, etc.

[0174] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or can be implemented by a combination of software and necessary hardware. Therefore, the technical solution according to the embodiments 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, including 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 embodiments of the present invention.

[0175] In an exemplary embodiment of the present invention, there is also provided a computer-readable storage medium, 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 program code. When the program product runs on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present invention.

[0176] Reference Figure 7 As shown, a program product 800 for implementing the above photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data according to an embodiment of the present invention is described. It can be a portable compact disc read-only memory (CD-ROM) and includes program code, and can run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In the present invention, the readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

[0177] The program product can adopt any combination of one or more readable storage media. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0178] The program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages - such as Java, C++, etc., and also including conventional procedural programming languages - such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as an independent software package, partially on the user's 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's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, by using an Internet service provider to connect through the Internet).

[0179] In addition, the above-mentioned drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present invention, rather than for the purpose of limitation. It is easy to understand that the processes shown in the above-mentioned drawings do not indicate or limit the chronological order of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously in, for example, multiple modules.

[0180] From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as 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 embodiments of the present invention.

[0181] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include known common general knowledge or conventional technical means in the technical field not disclosed by the present invention. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the claims.

Claims

1. A photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data, characterized in that Including: Obtain the air quality data of 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; Preprocess the inhalable particulate matter data and fine particulate matter data, remove negative values, null values and outliers, and obtain the processed inhalable particulate matter data and processed fine particulate matter data; 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 sand-dust weather; According to the time information of the occurrence of sand-dust weather, use the geostationary meteorological satellite data to trace back the source of the sand-dust weather and obtain the final location information of the sand source area; Based on the final location information of the sand source area, determine the development address of the photovoltaic power station; According to the time information of the occurrence of sand-dust weather, using the geostationary meteorological satellite data to trace back the source of the sand-dust weather and obtain the final location information of the sand source area includes: Obtain the geostationary satellite data within the time range corresponding to the time of the occurrence of the sand-dust weather; Preprocess the geostationary satellite data to obtain the spatial range data that meets the requirements of sand-dust weather source tracing; According to the time of the occurrence of sand-dust weather, use the spatial range data to gradually trace back the time of the sand-dust weather source to obtain the preliminary location of the sand source area; Conduct spatial analysis on the preliminary location of the sand source area, and combine with the geographic information system tool to draw the sand-dust covered area to determine the final location information of the sand source area; Preprocess the geostationary satellite data to obtain the spatial range data that meets the requirements of sand-dust weather source tracing includes: Based on the mapping data of the row and column numbers and longitude and latitude corresponding to the spatial resolution of the geostationary meteorological satellite data, convert the geostationary meteorological satellite data into longitude and latitude coordinates; Convert the longitude and latitude coordinates to the preset projection type, and cut out the spatial range of the target area according to the requirements of sand-dust weather source tracing to obtain the spatial range data that meets the requirements of sand-dust weather source tracing.

2. The photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data according to claim 1, wherein 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 sand-dust weather includes: Calculate the ratio of the processed inhalable particulate matter data and the processed fine particulate matter data to obtain the time series of the ratio data; Use the 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, 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; When it is detected that both the time series of the inhalable particulate matter data and the time series of the ratio data show significant mutations, it is identified as sand-dust weather and the time information of the occurrence of sand-dust weather is generated.

3. The photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data according to claim 2, wherein The use of the 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, 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 includes: Calculate the difference between the measured value of each moment of the inhalable particulate matter data or the ratio data in the time series and the preset expected value; Accumulate the differences at each moment to obtain an accumulated sum; When the accumulated sum exceeds the 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, wherein The method for identifying mutations in a time series 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 mutation points in the time series of the processed inhalable particulate matter data and mutation points in the time series of the ratio data, including: Calculate the measured average value within a sliding window of a target length at the current moment to obtain the current sliding window average value; Calculate the measured average value within a sliding window of a target length during the backtracking duration to obtain the backtracking sliding window average value; Calculate the difference between the current sliding window average value and the backtracking sliding window average value to obtain a difference; When the difference is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

5. The photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data according to claim 2, wherein The method for identifying mutations in a time series 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 mutation points in the time series of the processed inhalable particulate matter data and mutation points in the time series of the ratio data, including: Calculate the linear regression slope of the measured values within a sliding window of a target length at the current moment to obtain a first linear regression slope; Calculate the linear regression slope of the measured values within a sliding window of a target length during the backtracking duration to obtain a second linear regression slope; Compare the difference between the first linear regression slope and the second linear regression slope. When the difference is greater than the preset threshold, it is determined that a significant mutation occurs in the time series at the current moment.

6. A photovoltaic sand control site selection device based on air quality and geostationary meteorological satellite data, which is 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 1-5, and is characterized in that, Includes: A data acquisition module for acquiring air quality data of a monitoring point in a target area; A data screening module for screening inhalable particulate matter data and fine particulate matter data in the air quality data at a target time; A preprocessing module for preprocessing the inhalable particulate matter and fine particulate matter data, removing negative values, null values, and outliers, to obtain processed inhalable particulate matter data and processed fine particulate matter data; A time information generation module for detecting the ratio change of the processed inhalable particulate matter data and the processed fine particulate matter data, and generating time information of the occurrence of sand and dust weather; A location information determination module for using geostationary meteorological satellite data to trace back the source of sand and dust weather according to the time information of the occurrence of sand and dust weather, to obtain the final location information of the sand source area; A site selection module for determining the development address of a photovoltaic power station based on the final location information of the sand source area.

7. An electronic device, characterized in that, Includes: A processor; And A memory, on which computer-readable instructions are stored. 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 as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is executed by a processor, it implements the photovoltaic desert control site selection method based on air quality and geostationary meteorological satellite data according to any one of claims 1 to 5.

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