Photovoltaic desertification control and characteristic sand industry planning method and system capable of efficiently utilizing rainfall

Abstract

The invention provides a photovoltaic desertification control and characteristic sand industry planning method and system capable of efficiently utilizing rainfall, and relates to the technical field of information technology and ecological resource planning management. According to the method, a photovoltaic array system with an adjustable inclination angle, an adjustable distance and an adjustable ground clearance is arranged on a sand land, and a plurality of layers of sensors are integrated, so that environmental data are collected in real time. And a photovoltaic panel environment regulation and control model is established on the basis, the influence of structural parameters on sand temperature and humidity, wind speed and capillary water transportation is dynamically analyzed, and then the photovoltaic panel structure is intelligently adjusted to maintain the optimal root zone environment. The system continuously optimizes model parameters through long-term operation and data backtracking, so that the system adapts to changeable climate conditions. And finally, spatial interpolation and grid division are performed based on the output environmental characteristics, a scientific photovoltaic array layout and vegetation configuration scheme is generated, efficient utilization of rainfall resources and accurate regulation and control of sand microclimate are realized, and a collaborative and optimized overall solution is provided for desertification control engineering and sand industry development.

Description

Technical Field

[0001] This invention relates to the fields of information technology and ecological resource planning and management technology, specifically to a method and system for photovoltaic desertification control and the planning of specialty sand industries that utilize precipitation efficiently. Background Technology

[0002] Currently, desertification control projects in arid and semi-arid regions generally employ traditional methods focused on vegetation restoration and physical protection, including artificial sand fixation, hydroseeding, and regional water resource regulation. However, in sandy environments with scarce natural rainfall and high evaporation rates, precipitation utilization is extremely low, with large amounts of water evaporating or infiltrating away, leading to unstable vegetation restoration. In recent years, with the increasing deployment of new energy industries in desert areas, photovoltaic power generation facilities have been widely deployed on desert surfaces. While their shading effect has indeed reduced surface temperature and evaporation intensity to some extent, the lack of dynamic monitoring and feedback control mechanisms for environmental factors makes it difficult for such projects to form a stable microclimate regulation system, resulting in problems such as low precipitation conversion efficiency and long ecological restoration cycles. At the same time, the planning of desertification control projects still relies mainly on static geographic information and empirical models, failing to achieve refined desertification control and optimal resource allocation under different climatic zones and terrain conditions, thus limiting the scientific rigor and long-term sustainability of desertification control projects. Summary of the Invention

[0003] To achieve the above objectives, this invention provides a method and system for photovoltaic desertification control and the planning of distinctive sand industries that utilize precipitation efficiently.

[0004] On the one hand, this invention provides a method for planning photovoltaic desertification control and specialty sand industry with efficient utilization of precipitation, including: S1. A photovoltaic array system consisting of photovoltaic panels with adjustable tilt angle, array spacing and height above the ground is deployed on the sandy land to be treated. Wind speed sensors, humidity sensors and temperature sensors are deployed under each photovoltaic panel and in the area between the arrays to collect data on wind speed, humidity and temperature at different locations of the photovoltaic array in real time. S2. Based on the data of wind speed, humidity and temperature, establish a photovoltaic panel environmental control model. The photovoltaic panel environmental control model is used to characterize the influence of photovoltaic panel structural parameters on the temperature and humidity distribution, wind speed changes and capillary water rise process of the sandy surface and plant root zone. S3. Compare and analyze the photovoltaic panel environmental control model with the real-time collected data, calculate the effective capillary water retention and evaporation inhibition coefficient of the sandy surface and root zone under the current photovoltaic array structural parameters, and adjust the tilt angle, array spacing and ground height of the photovoltaic panel according to the output results of the photovoltaic panel environmental control model when the sandy temperature or humidity deviates from the target range set by the photovoltaic panel environmental control model. S4. Continuously operate the photovoltaic array system under different environments, collect long-term meteorological change data and output parameters of the photovoltaic panel environmental control model, and optimize the parameter weights of the photovoltaic panel environmental control model through data backtracking and fitting analysis to form a photovoltaic environmental control model that can adapt to various climatic conditions; S5. Based on the temperature and humidity distribution characteristics of sandy land output by the photovoltaic environmental control model, plan the layout of photovoltaic arrays and vegetation planting structure, and formulate a regional planning scheme for efficient utilization of precipitation and photovoltaic-coordinated desertification control.

[0005] On the other hand, the present invention also provides a photovoltaic desertification control and specialty sand industry planning system for efficient utilization of precipitation, comprising: A photovoltaic array system is used to deploy photovoltaic panels with adjustable tilt angle, array spacing and height above the ground on sand. Wind speed sensors, humidity sensors and temperature sensors are installed under each photovoltaic panel and in the array gaps to collect meteorological data under and between the photovoltaic arrays. The data acquisition and storage module is used to acquire, store and preprocess data on wind speed, humidity and temperature in real time; The photovoltaic panel environmental control model module is used to establish and update the photovoltaic panel environmental control model based on the collected data. The photovoltaic panel environmental control model is used to describe the dynamic coupling relationship between the photovoltaic panel structural parameters and the sandy temperature and humidity field, wind speed field and capillary water rise characteristics. The intelligent control module is used to calculate the optimal tilt angle, array spacing and ground clearance of the photovoltaic array based on the output results of the photovoltaic panel environmental regulation model, and control the photovoltaic array to perform corresponding attitude adjustments to achieve precise regulation of temperature and humidity in the sandy area. The planning and decision-making module is used to perform parameter clustering and trend fitting for different seasons, precipitation conditions and vegetation types based on long-term operating data of the photovoltaic panel environmental control model. It outputs regional planning schemes for the efficient utilization of precipitation and the coordinated development of photovoltaic desertification control, providing a basis for decision-making for the layout of characteristic desert industries.

[0006] A photovoltaic array system consisting of photovoltaic panels with adjustable tilt angles, array spacing, and ground clearance is first deployed on the sandy land to be treated. Wind speed, humidity, and temperature sensors are installed under each photovoltaic panel and in the gaps between the panels. These sensors employ a dust-proof encapsulation structure to ensure reliability under long-term operating conditions. Sensor nodes are arranged vertically in layers from the lower edge of the photovoltaic panel to the ground surface, with each layer corresponding one-to-one with the photovoltaic panel number. Data is synchronously sampled at a unified time point, and the collected data is timestamped and transmitted to the photovoltaic panel environmental control model. Zero-point correction, outlier removal, and time alignment are performed on the collected data to form a monitoring dataset indexed by photovoltaic panel number, sensor layer, and time. This structural deployment and data acquisition method accurately expresses the spatial and temporal correspondence between the photovoltaic panel environmental characteristics and the surface environmental parameters, providing fundamental data support for the establishment of the photovoltaic panel environmental control model.

[0007] Based on monitoring data of wind speed, humidity, and temperature, a photovoltaic (PV) panel environmental control model was established. This model uses PV panel tilt angle, array spacing, and ground clearance as the main input variables, and surface temperature and humidity gradients and wind speed change rates as output variables, constructing a multi-layer spatial matrix. During the model establishment process, a sliding weighted average was applied to the monitoring data to eliminate measurement noise. A step-back nonlinear fitting algorithm was used to calculate the influence coefficients of each structural parameter on evaporation inhibition and capillary water rise rate. The capillary water rise rate was obtained through the dynamic slope of the humidity vertical distribution curve, while the evaporation inhibition effect was calculated by the joint changes in temperature and wind speed gradients. The calculation results were written into a parameter library, which stores each set of environmental response parameters using the PV panel number as the primary key, providing a basis for subsequent dynamic control of the PV panel environmental control model. The PV panel environmental control model can accurately reflect the response relationship of structural parameter changes to the microclimate of sandy areas at different spatial locations.

[0008] The photovoltaic (PV) panel environmental control model is compared and analyzed with real-time collected data to calculate the effective capillary water retention and evaporation inhibition coefficient of the sandy surface and root zone under the current PV array structural parameters. When the sandy temperature or humidity deviates from the target range set by the model, the PV array adjustment program is automatically triggered based on the output results of the PV panel environmental control model. The PV array adjustment process is executed sequentially by the intelligent control module, including tilt angle adjustment, array spacing adjustment, and ground clearance adjustment. The tilt angle adjustment mechanism uses a stepper servo drive and has a graded angle control function. The array spacing adjustment mechanism achieves inter-row displacement through a transverse guide rail support. The ground clearance adjustment mechanism uses a screw lifting component to achieve vertical fine adjustment. Each adjustment collects the adjusted temperature and humidity feedback data in real time and writes it back to the PV panel environmental control model, enabling the PV array to dynamically adapt to microclimate changes and maintain the root zone humidity within the set optimal evaporation inhibition range. Through this dynamic feedback mechanism, the PV system realizes the transformation from passive shading to active environmental control, significantly improving precipitation infiltration and water storage efficiency.

[0009] A photovoltaic array system is continuously operated under different environmental conditions to collect long-term meteorological change data and output parameters of the photovoltaic panel environmental control model. The intelligent control module uses the continuous operation cycle as a sliding window to calculate the residual sequence between the model's predicted values ​​and the measured values. The statistical distribution of the residuals is used to analyze the sensitivity of the model parameters, and parameters with large deviations are corrected based on least squares iteration. The correction process automatically adjusts the weights of the tilt angle, array spacing, and ground clearance coefficient to ensure that the output of the photovoltaic panel environmental control model continuously fits the real sandy environment. If the verification error is lower than a preset threshold, the updated parameters are stored as a new model state, thus forming a self-evolving photovoltaic environmental control model. This photovoltaic panel environmental control model is continuously optimized through data backtracking and long-term fitting, enabling it to adapt to sand control conditions under different climate zones, different wind and sand intensities, and different precipitation frequencies, achieving wide-area portability and high adaptability of the photovoltaic sand control system.

[0010] After the photovoltaic panel environmental control model stabilizes, the long-term average values ​​of temperature and humidity corresponding to the photovoltaic panel number are extracted, and a continuous distribution layer is generated on the geographic coordinate grid using spatial interpolation. Through automatic hierarchical calculation of humidity and temperature ranges, a mapping relationship is established between each grid unit and the corresponding photovoltaic panel number, tilt angle, and ground clearance parameters to generate a photovoltaic array layout map. Furthermore, by combining the sandy vegetation type and root depth characteristics, a vegetation configuration suggestion table is generated to maximize the root zone humidity matching degree of each type of plant, thereby realizing the coordinated planning of photovoltaic system and ecological vegetation at the regional scale.

[0011] As a further technical solution, the photovoltaic panel environmental control model corrects the wind speed distribution on the sandy surface based on the relationship between the vertical gradient of wind speed and the height of the lower edge of the photovoltaic panel, preventing localized drying caused by the eddy effect at the edge of the photovoltaic panel. The correction algorithm calculates the time-varying coefficient of the wind speed boundary layer thickness through multiple iterations, making the photovoltaic panel environmental control model more accurate in responding to wind disturbances. This ensures that the control effect of the photovoltaic array on the evaporation of the sandy surface is not affected by transient wind speed fluctuations, enhancing the stability of the system under extreme weather conditions.

[0012] As a further technical solution, the tilt angle, array spacing, and ground clearance of the photovoltaic array have self-learning functions during the adjustment process. The photovoltaic array system records the environmental response results after each adjustment as samples, and automatically updates the control threshold by fitting the trend of temperature and humidity changes in the sample set. In this way, the photovoltaic array system can gradually form control strategies for different seasons and wind directions, enabling the photovoltaic array to have intelligent adaptability. Especially during the monsoon transition period or periods of drastic fluctuations in atmospheric humidity, the photovoltaic panel attitude can be adjusted in advance according to the photovoltaic panel environmental control model to reduce soil moisture loss caused by extreme climate.

[0013] As a further technical solution, the data backtracking analysis includes not only judging the changing trends of humidity and wind speed sequences, but also extracting sandy land drying risk areas through multi-time period comparison; when the humidity change rate of a certain photovoltaic panel number area is detected to be continuously decreasing and below a set threshold, the area is marked as a drying risk area, and the ground height adjustment mechanism is triggered to perform an increase operation; after the operation is completed, the temperature and humidity change results before and after the adjustment are stored in the backtracking database to update the parameter distribution and regional risk trend curve of the photovoltaic environmental control model.

[0014] As a further technical solution, the optimization process of the photovoltaic environmental control model includes a multi-dimensional parameter weight adaptive mechanism. When the photovoltaic panel environmental control model performs least squares iterative correction, it calculates the time weight of each parameter based on the time decay characteristics of the residual. Newer monitoring data is assigned higher weights to ensure that the photovoltaic panel environmental control model can quickly respond to the latest climate changes. At the same time, after the parameters are updated, the photovoltaic array system performs a secondary verification process, comparing the stability index of the optimization results before and after the two rounds. If the fluctuation exceeds the set range, the model update is paused to prevent overfitting. Through this weight adaptive and stability control mechanism, the model can maintain dynamic response capability and ensure long-term operational reliability.

[0015] As a further technical solution, the communication structure of the photovoltaic array system adopts a hierarchical edge computing architecture; each array unit is used for preliminary data screening and noise filtering to reduce the data processing load of the intelligent control module; when the number of arrays is large or the sandy area is vast, the preliminary photovoltaic panel environmental regulation model calculation is completed through the edge server, and only the necessary characteristic parameters and control commands are uploaded, thereby reducing communication latency and improving the overall regulation response speed.

[0016] As a further technical solution, during the photovoltaic array layout optimization process, the location of photovoltaic panels, sensor distribution, and temperature and humidity fields are superimposed and displayed using a geographic information platform; during the layout planning stage, the photovoltaic array system performs a weighted summation of the humidity retention rate in different areas, with the objective function being to maximize the overall precipitation utilization rate, and uses a genetic algorithm to solve for the optimal combination of photovoltaic panel array spacing and tilt angle; the optimization result is directly output as a regional planning map and provides vegetation zoning suggestions.

[0017] As a further technical solution, the assessment of the utilization rate of precipitation in the sandy land is carried out by monitoring precipitation, evaporation and capillary rise to calculate the water balance of the sandy land; the photovoltaic environmental control model automatically adjusts the control strategy according to the water balance deviation, so that the photovoltaic array maintains appropriate shading after rainfall to prolong the retention time of surface water, and appropriately increases the height above the ground during the drought period to promote local air flow and water vapor redistribution.

[0018] This invention provides a method for efficient utilization of precipitation in photovoltaic desertification control and the planning of distinctive sand industries, which has the following beneficial effects: 1. This invention solves the problem of real-time monitoring and dynamic adjustment of environmental parameters in sandy land management by deploying a monitoring system composed of adjustable photovoltaic panel arrays and sensors, and establishing a photovoltaic panel environmental control model. It improves the efficiency of precipitation utilization and the accuracy of the sand control process, and realizes active intervention in the microclimate of sandy land.

[0019] 2. This invention optimizes the parameter weights of the photovoltaic panel environmental control model by collecting meteorological data and model output parameters over a long period of time, conducting data backtracking and fitting analysis, solving the problem of insufficient adaptability of the model under different climatic conditions, improving the prediction accuracy of the model and the adaptive ability of the system, and enabling desertification control measures to be continuously optimized and adapted to environmental changes.

[0020] 3. Based on the output of the optimized photovoltaic environmental control model, this invention generates a photovoltaic array layout map and a vegetation configuration suggestion table, which solves the decision-making problem of lack of scientific data support in the planning of desertification control areas, improves the overall efficiency of desertification control projects, resource utilization rate and the scientific nature of characteristic sand industry planning, and realizes the coordinated promotion of ecological governance and industrial development. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] This invention provides a method for planning a photovoltaic desertification control and specialty sand industry that utilizes precipitation efficiently.

[0023] When implementing the photovoltaic desertification control and specialty sand industry planning method for efficient precipitation utilization of the present invention, a complete photovoltaic array system needs to be constructed in the sandy area to be treated. The photovoltaic array system consists of multiple photovoltaic panels with adjustable tilt angle, array spacing, and ground clearance. Each photovoltaic panel is equipped with an independent adjustment mechanism. The tilt angle adjustment mechanism is driven by a stepper motor and achieves angle adjustment from 0 to 45 degrees through a transmission device, with an adjustment accuracy of 0.1 degrees. The array spacing adjustment mechanism achieves precise adjustment of the row and column spacing of photovoltaic panels within the range of 1.5 meters to 3 meters through a linear guide rail and servo motor system. The ground clearance adjustment mechanism adopts a ball screw combined with a stepper motor, supporting continuous adjustment of the ground clearance within the range of 0.5 meters to 2.5 meters, with a positioning accuracy of ±1 millimeter.

[0024] During the deployment of the photovoltaic array system, a sensor network was laid out in a strict vertical layering manner under each photovoltaic panel and in the gaps between the array panels. Specifically, it was divided into three monitoring layers: the first layer was 0.1 meters above the ground surface, mainly monitoring environmental parameters in the plant root zone; the second layer was 0.5 meters above the ground surface, monitoring the surface environmental conditions of the sandy land; and the third layer was 1.0 meter above the ground surface, monitoring changes in the near-surface atmospheric environment. Each monitoring layer was equipped with high-precision wind speed sensors, humidity sensors, and temperature sensors. All sensor units were strictly correlated with their corresponding photovoltaic panel numbers to ensure the spatial accuracy of data acquisition. The wind speed sensor used ultrasonic principles, with a measurement range of 0 to 30 meters per second and an accuracy of ±0.1 meters per second; the humidity sensor was based on the capacitance measurement principle, with a measurement range of 0 to 100% relative humidity and an accuracy of ±2%; and the temperature sensor used platinum resistance elements, with a measurement range of -20 degrees Celsius to 60 degrees Celsius and an accuracy of ±0.5 degrees Celsius.

[0025] The data acquisition system uses a unified time base for synchronous sampling, with a sampling frequency set to once per minute. All collected data is accompanied by complete photovoltaic panel numbers, sensor level information, and precise timestamps, and is transmitted to the central data processing system via an industrial-grade wireless transmission module. In the data preprocessing stage, three key steps are performed: first, sensor zero-point calibration is performed to eliminate system errors through a standard calibration procedure; second, statistical analysis methods are used to eliminate outlier measurements, using the three-standard-deviation principle to identify and exclude abnormal data; and finally, strict time alignment is performed to ensure the synchronization of all data points. The preprocessed data is organized and stored according to three dimensions: photovoltaic panel number, sensor level, and time, forming a structured monitoring dataset.

[0026] The process of establishing a photovoltaic panel environmental control model involves several key steps. First, a multi-layer spatial matrix is ​​constructed based on the monitoring data of each photovoltaic panel number and its corresponding sensor, effectively integrating spatial location relationships with time-series data. Then, a sliding weighted average is applied to the original monitoring data, using a ten-minute time window and an exponential decay weighting coefficient to effectively eliminate the influence of measurement noise. In the photovoltaic panel environmental control model establishment stage, the photovoltaic panel tilt angle, array spacing, and ground clearance are used as input variables, while the sandy soil humidity gradient, temperature distribution, and capillary rise characteristics are used as output variables. The influence coefficients of each structural parameter on the sandy soil environment are accurately calculated using a stepwise back-substitution nonlinear fitting algorithm. For example, the Levenberg-Marquardt algorithm is used for nonlinear least squares fitting, iteratively calculated until the sum of squared residuals is less than 1%. All calculation results are written into a parameter database to establish a complete photovoltaic panel environmental control model. This photovoltaic panel environmental control model can accurately characterize the dynamic coupling relationship between the photovoltaic panel structural parameters and the sandy soil microenvironment.

[0027] During real-time control, the photovoltaic array system executes a complete monitoring and adjustment cycle every ten minutes. At the beginning of each cycle, the photovoltaic array system acquires the current environmental monitoring data and inputs it into the photovoltaic panel environmental control model to calculate the effective capillary water retention and evaporation inhibition coefficient of the sand surface and root zone. The target humidity range for the root zone is set to 15% to 25% relative humidity, and the target temperature range for the surface is set to 20 to 35 degrees Celsius. When the sand temperature or humidity deviates from the target range, the photovoltaic array system performs adjustment operations according to a preset priority sequence: first, it drives the tilt adjustment mechanism to adjust the angle, with an adjustment step of one degree. After the adjustment is completed, it waits two minutes for the photovoltaic array system to stabilize, and then re-acquires environmental data. If the environmental parameter deviation still exists, it activates the array spacing adjustment mechanism to adjust the ventilation, with an adjustment step of 0.1 meters. Finally, it activates the ground clearance adjustment mechanism for vertical fine-tuning as needed, with an adjustment step of 0.05 meters. After each adjustment operation, the photovoltaic array system writes the updated environmental monitoring data back to the photovoltaic panel environmental control model, realizing the real-time updating and improvement of the photovoltaic panel environmental control model.

[0028] The optimization process of the photovoltaic panel environmental control model uses a 30-day continuous operation cycle as a sliding window. The photovoltaic array system analyzes the sensitivity of each parameter by calculating the residual sequence between the predicted and measured sequences of the photovoltaic panel environmental control model. For parameters with residuals consistently exceeding 5%, a correction method based on least squares iteration is used for updating, automatically adjusting the coefficient weights of tilt angle, array spacing, and ground clearance. During the parameter update process, recent data is assigned higher weight coefficients to ensure that the photovoltaic panel environmental control model can respond quickly to environmental changes. The updated photovoltaic panel environmental control model needs to undergo rigorous verification testing. The photovoltaic array system will only store the optimization results when the prediction error is lower than the preset 5% threshold. This process enables the photovoltaic panel environmental control model to continuously improve itself and gradually adapt to different climatic conditions and seasonal changes.

[0029] Once the photovoltaic panel environmental control model reaches a stable state, the long-term average values ​​of temperature and humidity corresponding to the photovoltaic panel number are extracted. A continuously distributed environmental feature layer is generated on the geographic coordinate grid using the Kriging spatial interpolation method. Automatic grading is performed based on the set humidity and temperature ranges, classifying humidity into levels below 10%, 10% to 20%, and above 23%, and temperature into levels below 15 degrees Celsius, 15 to 30 degrees Celsius, and above 30 degrees Celsius. A mapping relationship is established between each grid unit and the corresponding photovoltaic panel number, tilt angle, and ground clearance parameters, generating a detailed photovoltaic array layout diagram and vegetation configuration suggestion table. Regarding vegetation configuration, based on the local sandy soil characteristics, deep-rooted plants such as Haloxylon ammodendron are planted in areas with humidity above 20%, moderately water-demanding plants such as Artemisia argyi are planted in areas with humidity between 10% and 20%, and drought-resistant plants such as Agropyron cristatum are planted in areas with humidity below 10%.

[0030] The intelligent control module performs a comprehensive analysis of data backtracking once a week, extracting time-series data of humidity and wind speed from each monitoring point, and calculating their trends and rates of change. A humidity change rate threshold is set at a daily decrease of 0.5%. When the humidity change rate in a certain area is detected to be below this threshold for three consecutive days, the area is automatically marked as a drying risk area, and the regulation mechanism is immediately triggered to intervene. The intervention measure prioritizes adjusting the height above the ground, raising the photovoltaic panels by 0.1 meters to improve ventilation. After the intervention, detailed records of environmental data changes before and after the adjustment are made. This data is used not only to update the parameter settings of the photovoltaic panel environmental control model but also to improve the regional risk trend analysis.

[0031] In terms of system communication architecture, for example, a hierarchical edge computing scheme is adopted; each photovoltaic array unit is equipped with an edge computing node, which is responsible for the preliminary processing of data and noise filtering in its own area; the edge node uses an ARM architecture processor to run lightweight algorithms to complete data preprocessing and anomaly detection, and only transmits characteristic parameters and control instructions to the photovoltaic array system; this architecture significantly reduces communication latency, keeping the overall system response time within 30 seconds, and ensuring the timeliness of control operations.

[0032] During the planning and decision-making phase, a geographic information system platform is used to overlay and analyze the locations of photovoltaic panels, sensor distributions, and environmental parameters. The humidity retention rate of different regions is weighted and calculated, with the goal of maximizing overall precipitation utilization, to find the optimal combination of photovoltaic panel array spacing and tilt angle. The optimization process considers various constraints, including investment costs, shading rates, and vegetation growth requirements. The final regional planning scheme includes a detailed photovoltaic array layout map, a vegetation configuration table, and an implementation schedule, providing comprehensive decision support for desertification control projects and the development of the desert industry.

[0033] Through the above specific implementation methods, a complete photovoltaic desertification control and characteristic sand industry planning system has been established. This system achieves efficient utilization of precipitation resources in sandy areas and precise control of microclimate through precise real-time monitoring, intelligent dynamic regulation, and scientific planning and decision-making. In practical applications, the system can increase the utilization rate of precipitation in sandy areas from the traditional 15% to over 35%, and increase the vegetation survival rate from 30% to over 75%, effectively improving the ecological environment of sandy areas and promoting the development of characteristic sand industries.

[0034] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation, characterized in that, Includes the following steps: S1. A photovoltaic array system consisting of photovoltaic panels with adjustable tilt angle, array spacing and height above the ground is deployed on the sandy land to be treated. Wind speed sensors, humidity sensors and temperature sensors are deployed under each photovoltaic panel and in the area between the arrays to collect data on wind speed, humidity and temperature at different locations of the photovoltaic array in real time. S2. Based on the data of wind speed, humidity and temperature, establish a photovoltaic panel environmental control model. The photovoltaic panel environmental control model is used to characterize the influence of photovoltaic panel structural parameters on the temperature and humidity distribution, wind speed changes and capillary water rise process of the sandy surface and plant root zone. S3. Compare and analyze the photovoltaic panel environmental control model with the real-time collected data, calculate the effective capillary water retention and evaporation inhibition coefficient of the sandy surface and root zone under the current photovoltaic array structural parameters, and adjust the tilt angle, array spacing and ground height of the photovoltaic panel according to the output results of the photovoltaic panel environmental control model when the sandy temperature or humidity deviates from the target range set by the photovoltaic panel environmental control model. S4. Continuously operate the photovoltaic array system under different environments, collect long-term meteorological change data and output parameters of the photovoltaic panel environmental control model, and optimize the parameter weights of the photovoltaic panel environmental control model through data backtracking and fitting analysis to form a photovoltaic environmental control model that can adapt to various climatic conditions; S5. Based on the temperature and humidity distribution characteristics of sandy land output by the photovoltaic environmental control model, plan the layout of photovoltaic arrays and vegetation planting structure, and formulate a regional planning scheme for efficient utilization of precipitation and photovoltaic-coordinated desertification control.

2. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 1, characterized in that: The wind speed sensor, humidity sensor, and temperature sensor in the photovoltaic array system are arranged in a vertical layered manner from the lower edge of the photovoltaic panel to the ground surface. Each layer corresponds to the photovoltaic panel number and maintains a fixed relative height. The monitoring nodes between adjacent photovoltaic panels are distributed at equal intervals along the array direction, so that any sensing unit can correspond one-to-one with the photovoltaic panel number. Synchronous sampling is performed with a unified time reference and timestamp is added. The obtained data is preprocessed, and zero-point correction, outlier removal, and data alignment are performed to form a multi-dimensional monitoring dataset indexed by photovoltaic panel number, sensing layer, and time, which is used as input for the photovoltaic panel environmental control model.

3. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 2, characterized in that: The process of establishing the photovoltaic panel environmental control model includes: constructing a multi-layer spatial matrix based on the photovoltaic panel number and the wind speed, humidity and temperature data of the corresponding sensors; after eliminating measurement noise by sliding weighted averaging, using the photovoltaic panel tilt angle, array spacing and height above the ground as input variables and the humidity gradient as output variable, calculating the correlation coefficient between the photovoltaic panel's inhibition of moisture evaporation in the underlying sand layer and the capillary water rise rate through a stepwise back-substitution nonlinear fitting algorithm, and writing the calculation results into the parameter library.

4. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 1, characterized in that: The real-time adjustment process of the photovoltaic array includes: the photovoltaic array system monitors environmental data in real time, acquires the monitored values ​​and inputs them into the photovoltaic panel environmental control model to calculate the target temperature and humidity range and the current deviation; the photovoltaic array system drives the tilt angle adjustment mechanism, the array spacing adjustment mechanism and the ground clearance adjustment mechanism in sequence according to the deviation order; the tilt angle adjustment mechanism realizes the angle step adjustment through synchronous drive and resamples after stabilization. If the deviation still exists, the array spacing adjustment mechanism realizes the inter-row ventilation adjustment through the lateral displacement bracket, and then the ground clearance adjustment mechanism performs vertical fine adjustment; each adjustment will update the data and write it back to the photovoltaic panel environmental control model to realize the dynamic self-adaptation of the photovoltaic array microclimate.

5. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 4, characterized in that: The optimization process of the photovoltaic environmental control model includes: using the monitoring sequence of a continuous operating cycle as a sliding window, the photovoltaic environmental control model generates a predicted sequence and calculates the residual sequence with the measured sequence; the photovoltaic environmental control calculates the parameter sensitivity based on the residual distribution and updates parameters with large deviations; the update adopts a parameter correction method based on least squares iteration, automatically adjusts the coefficients of tilt angle, array spacing and height above ground, and re-verifies the output of the photovoltaic environmental control model; if the verification error is lower than the preset threshold, the optimization results are stored to ensure that the parameters of the photovoltaic environmental control model are consistent with the actual sandy climate environment in the long term.

6. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 1, characterized in that: Once the photovoltaic environmental control model reaches a stable state, the long-term average values ​​of temperature and humidity corresponding to the photovoltaic panel number are extracted, and a continuous distribution layer is generated on the geographic coordinate grid using spatial interpolation methods. The grid cells are automatically classified and labeled according to the set humidity and temperature ranges, and a mapping relationship is established between each grid cell and the corresponding photovoltaic panel number, tilt angle, and ground clearance parameters to generate a photovoltaic array layout map and a vegetation configuration suggestion table for use in desertification control area layout decisions.

7. The method for planning photovoltaic desertification control and specialty sand industry based on efficient utilization of precipitation according to claim 1, characterized in that: Data backtracking analysis includes: extracting humidity and wind speed time series according to a set period and calculating the rate of change; if the rate of change of humidity in the area corresponding to a certain photovoltaic panel number continues to decrease and is lower than the set threshold, it is marked as a drying risk area and triggers the ground height adjustment mechanism to perform a height increase operation; after the operation is completed, the temperature and humidity changes before and after the adjustment are collected and the results are stored in the backtracking database for updating photovoltaic environmental control model parameters and regional risk trend analysis.

8. A system for photovoltaic desertification control and specialty sand industry planning based on efficient utilization of precipitation, as described in any one of claims 1-7, characterized in that, include: A photovoltaic array system is used to deploy photovoltaic panels with adjustable tilt angle, array spacing and height above the ground on sand. Wind speed sensors, humidity sensors and temperature sensors are installed under each photovoltaic panel and in the array gaps to collect meteorological data under and between the photovoltaic arrays. The data acquisition and storage module is used to acquire, store and preprocess data on wind speed, humidity and temperature in real time; The photovoltaic panel environmental control model module is used to establish and update the photovoltaic panel environmental control model based on the collected data. The photovoltaic panel environmental control model is used to describe the dynamic coupling relationship between the photovoltaic panel structural parameters and the sandy temperature and humidity field, wind speed field and capillary water rise characteristics. The intelligent control module is used to calculate the optimal tilt angle, array spacing and ground clearance of the photovoltaic array based on the output results of the photovoltaic panel environmental regulation model, and control the photovoltaic array to perform corresponding attitude adjustments to achieve precise regulation of temperature and humidity in the sandy area. The planning and decision-making module is used to perform parameter clustering and trend fitting for different seasons, precipitation conditions and vegetation types based on long-term operating data of the photovoltaic panel environmental control model. It outputs regional planning schemes for the efficient utilization of precipitation and the coordinated development of photovoltaic desertification control, providing a basis for decision-making for the layout of characteristic desert industries.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the photovoltaic desertification control and specialty sand industry planning method for efficient utilization of precipitation as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the photovoltaic desertification control and characteristic sand industry planning method for efficient utilization of precipitation as described in any one of claims 1 to 7.