Gradient ecological restoration system for coal mining subsidence area based on photovoltaic array and monitoring method

Abstract

The invention discloses a coal mining subsidence area gradient ecological restoration system based on a photovoltaic array and a monitoring method, and belongs to the technical field of coal mining subsidence area ecological management and new energy development cross.The system divides restoration gradients according to gradients through a subsidence area pretreatment layer; the photovoltaic array supporting unit adopts an adjustable bracket and a deep-buried pile foundation to adapt to terrains, and the spacing of photovoltaic panels is arranged in a gradient manner to balance light resources; the gradient vegetation restoration unit implements differentiated vegetation and soil improvement strategies for different slope regions; the ecological monitoring unit and the central regulation and control unit realize multi-source data acquisition and intelligent analysis; the monitoring method comprises the steps of systematic deployment, high-frequency data acquisition, cloud correlation analysis based on a mathematical model, graded early warning and automatic regulation and control, and regular evaluation and optimization. According to the invention, deep fusion and cooperative regulation and control of landform stability, ecological restoration and photovoltaic power generation of the subsidence area are realized, and the stability, benefit and intelligent level of treatment are improved.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of ecological governance and new energy development in coal mining subsidence areas, and in particular relates to a gradient ecological restoration system and monitoring method for coal mining subsidence areas based on photovoltaic arrays. Background Technology

[0002] Large-scale subsidence areas formed after coal mining are a major ecological and environmental problem facing many coal-producing regions in my country. Surface subsidence leads to fragmented terrain, soil erosion, and vegetation degradation, severely disrupting the regional ecological balance. Traditional methods for managing subsidence areas, such as simple backfilling, land leveling, and artificial revegetation, often suffer from drawbacks such as large engineering workloads, high costs, unstable restoration effects, and a lack of sustainable benefits. The restored land, due to its poor soil and water retention capacity, has a low vegetation survival rate and is prone to secondary degradation. Furthermore, these methods fail to fully utilize the vast land resources of subsidence areas to create economic value, often resulting in the inability to sustain remediation projects due to insufficient funding for subsequent maintenance.

[0003] In recent years, the "photovoltaic + ecological restoration" model has provided a new approach to the management of subsidence areas. This model attempts to construct photovoltaic power stations in subsidence areas while utilizing the space beneath the photovoltaic panels for vegetation restoration. However, current practices generally suffer from two major problems: First, the design of photovoltaic power stations is disconnected from the needs of ecological restoration. Most photovoltaic supports using fixed tilt angles cannot adapt to the continuous uneven subsidence and complex slope changes that may exist in subsidence areas, easily leading to support instability or damage. Furthermore, the fixed photovoltaic array layout often creates a uniform shading environment, failing to meet the differentiated light requirements of vegetation in different areas (such as the top, surface, and bottom of the slope). Second, there is a lack of intelligent and integrated monitoring and control methods. Existing systems typically only monitor power generation or simply observe vegetation growth, failing to perform real-time correlation analysis and coordinated control of terrain stability, soil moisture, vegetation physiological status, and photovoltaic operating parameters. This results in the inability to detect and address problems in a timely manner, limiting the stability and overall benefits of system operation.

[0004] Therefore, there is an urgent need to develop an integrated system that can deeply integrate photovoltaic engineering structures and ecological restoration technologies, and achieve intelligent monitoring and adaptive regulation, in order to solve the problems of insufficient stability, economy and sustainability in the governance of coal mining subsidence areas. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing coal mining subsidence areas, such as poor coordination, insufficient adaptability, and extensive management, and to provide a gradient ecological restoration system and monitoring method for coal mining subsidence areas based on photovoltaic arrays. This will enable efficient coordination of terrain reinforcement, gradient ecological restoration and clean energy production, and improve the stability, restoration effect and comprehensive economic benefits of the entire system through intelligent monitoring and control.

[0006] To achieve the above objectives, this invention provides a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays, comprising: The subsidence area pretreatment layer is used to level and compact the base of the coal mining subsidence area. The base is divided into three gradient areas: gentle slope area, mild slope area, and steep slope area according to the slope of 0-5°, 5-15°, and 15-25°. Each area is equipped with a water interception ditch at the edge, and the bottom of the water interception ditch is covered with an impermeable membrane. The photovoltaic array support unit is installed on the pre-treated base of the settlement area. It includes concrete piles embedded in the base, an adjustable bracket hinged to the top of the piles, and photovoltaic panels mounted on the bracket. The spacing between the photovoltaic panels is set to different values ​​depending on the area. The adjustable bracket includes a photovoltaic bracket hydraulic device hinged to the photovoltaic panels and a horizontal fixing rod fixedly connected to the bottom of the photovoltaic bracket hydraulic device. By controlling the height of the photovoltaic bracket hydraulic device, the tilt angle of the photovoltaic panels can be steplessly adjusted within the range of 15° to 30° with an adjustment accuracy of ±1°. The embedment depth of the concrete piles is 1.5 meters to 2.5 meters. The gradient vegetation restoration unit is configured with different vegetation restoration schemes for flat areas, gentle slope areas and steep slope areas. The vegetation restoration schemes include vegetation types, planting methods and soil improvement measures. The ecological monitoring unit includes soil sensors for monitoring soil parameters, vegetation monitoring equipment for monitoring vegetation growth status, and photovoltaic efficiency detectors for monitoring photovoltaic power generation performance.

[0007] Preferably, the photovoltaic panel spacing is 1.5 meters to 2 meters in flat areas, 2 meters to 2.5 meters in gentle slope areas, and 2.5 meters to 3 meters in steep slope areas; the tilt angle of the photovoltaic panel modules is adjusted to 15° to 20° in flat areas, 20° to 25° in gentle slope areas, and 25° to 30° in steep slope areas.

[0008] Preferably, the vegetation restoration scheme of the gradient vegetation restoration unit specifically includes: For flat areas, a combination of shade-tolerant and trampling-resistant herbaceous plants and shallow-rooted shrubs is used to form a lawn-shrub composite vegetation. For gentle slopes, plant deep-rooted leguminous plants and small trees, along with creeping vines; For steep slope areas, hydroseeding technology is used to plant pioneer herbs and vines, and planting bags are set up around the concrete pile foundation, filled with nutrient soil and shrub seeds.

[0009] Preferably, the gradient vegetation restoration unit further includes a microbial amendment layer, which is a compound microbial agent applied to the soil surface. The compound microbial agent contains nitrogen-fixing bacteria, phosphate-solubilizing bacteria, and actinomycetes, and the application rate is 20-30 g / m².2 The mixture should be mixed with the topsoil to a depth of 10-15cm.

[0010] Preferably, the ecological monitoring unit further includes a meteorological monitoring subunit for monitoring wind speed, precipitation, light intensity, and air temperature and humidity; and the soil sensor, vegetation monitoring equipment, photovoltaic efficiency detector, and meteorological monitoring subunit are all connected to a central control unit via a wireless communication module; the central control unit includes: The data receiving and storage module is used to receive and store various monitoring data from the ecological monitoring unit; The data analysis and early warning module is used to analyze and process the monitoring data and generate early warning information when the monitoring data exceeds a preset threshold. The instruction generation and issuance module is used to generate control instructions based on early warning information or preset strategies and issue them to the corresponding execution agencies.

[0011] This invention also provides a monitoring method for a gradient ecological restoration system in coal mining subsidence areas based on photovoltaic arrays, comprising the following steps: Step 1, System Deployment and Initialization: Complete the deployment and installation of each unit of the system, initialize the ecological monitoring unit, and set the threshold range of each monitoring parameter; Step 2: Synchronous acquisition of multi-source data: The ecological monitoring unit synchronously acquires topographic subsidence data, soil parameter data, vegetation growth data, photovoltaic operation data, and meteorological data according to a preset frequency; Step 3, Data Transmission and Cloud Processing: The central control unit sends the collected data to the cloud data platform via encrypted wireless transmission, where the cloud data platform performs preprocessing, storage, and correlation analysis on the data. Step 4, Intelligent Analysis and Dynamic Control: Based on the correlation analysis results, determine the system status and execute hierarchical early warning and closed-loop control; Step 5: Effect evaluation and strategy optimization: Regularly evaluate the ecological restoration effect and photovoltaic power generation efficiency based on long-term monitoring data, and optimize the restoration strategy or system operating parameters according to the evaluation results.

[0012] Preferably, in step 2, the terrain subsidence data is collected every 15 minutes by a GNSS monitoring station; the soil parameter data is collected every hour by a soil sensor; the vegetation growth data is collected weekly by a vegetation monitoring device (a drone equipped with a multispectral camera) and calibrated by fixed quadrats; the photovoltaic operation data is collected every 5 minutes by a photovoltaic efficiency detector (a sensor installed at the inverter); and the meteorological data is collected every hour by a meteorological monitoring subunit (meteorological station).

[0013] Preferably, the specific process of step 3 is as follows: S31. Data Upload: The central control unit synchronously uploads the pre-processed local data to the cloud data platform via an encrypted communication link; S32. Cloud Data Governance: The cloud data platform cleans, aligns, and standardizes the multi-source heterogeneous data it receives, and stores it in a distributed time-series database. S33. Multi-dimensional correlation analysis: The cloud data platform calls the built-in analysis model to perform the following calculations and analyses on the standardized data: Light-vegetation coupling analysis: Based on vegetation spectral data and light data collected by ecological monitoring units, vegetation indices are calculated for each gradient zone. With photovoltaic panel shading rate Quantitative Relationship Model ,in, Indicates the first Normalized Difference Vegetation Index at each monitoring point Indicates the first The shading rate of the photovoltaic panels corresponding to each monitoring point Indicates the first Soil temperature at each monitoring point, in degrees Celsius. Indicates the first Soil volumetric moisture content at each monitoring point This represents a function used in multiple regression analysis. Soil-PV Benefit Analysis: Based on soil nutrient and PV power generation data, this study constructs a model of how soil improvement affects the microclimate and power generation efficiency of PV panels. Impact Model ,in, Solar irradiance is expressed in watts per square meter. This indicates the ambient air temperature, expressed in degrees Celsius. This indicates the comprehensive index of soil nutrients. This represents the comprehensive influence function; Deformation-Structural Risk Analysis: Calculating Surface Subsidence Rate Based on GNSS Displacement Data With acceleration And assess its structural risk level to recent photovoltaic mounting systems. ,in, This indicates the horizontal distance between the monitored deformation point and the nearest photovoltaic support pile. This represents the risk assessment function.

[0014] Preferably, the specific process of step 4 is as follows: S41. Status Assessment and Graded Early Warning Trigger: Based on the analysis results of S33, the cloud data platform compares them with the preset macro-early warning thresholds to generate and issue three-level early warning information, including yellow, orange and red warnings; at the same time, the data analysis and early warning module of the central control unit independently performs rapid safety judgment based on local real-time data. S42. Automatic Control Command Execution: For orange-level and below warnings triggered in S41 with clearly defined logic, the platform automatically executes closed-loop control; when the soil volumetric moisture content is below the threshold, the corresponding zone's drip irrigation system is automatically activated, and the irrigation volume... When GNSS analysis indicates local slope changes At a certain angle, an adjustment command is automatically sent to the hydraulic device of the photovoltaic support in that area, and the new tilt angle is determined. When the cloud data platform's analysis model identifies the photovoltaic conversion efficiency of a specific area based on photovoltaic efficiency detector data... When the year-on-year decline in solar PV module emissions persists for several consecutive days, weather factors are ruled out, and the cause is determined to be surface dust accumulation, a closed-loop cleaning control system is triggered. Specifically, the cloud data platform generates cleaning task instructions and sends them to the central control unit. The central control unit then generates and sends instructions to drive automated cleaning robots or spray systems deployed on the photovoltaic modules to perform targeted cleaning operations. Indicates the irrigation coefficient. Indicates the target soil volumetric moisture content. This indicates the current soil volumetric moisture content. This indicates the initial tilt angle of the photovoltaic support; S43. Generating and pushing manual handling suggestions: For red alerts triggered by S41 or orange alerts that have not been alleviated after automatic adjustment by S42, the platform automatically generates and pushes a detailed handling suggestion report, which incorporates the analysis results of S33.

[0015] Preferably, step 5 specifically includes: S51. Regular comprehensive assessment: The cloud data platform summarizes and analyzes all historical data on a quarterly or annual basis, generating a comprehensive assessment report covering ecological, energy, and security dimensions; S52, Iterative Optimization of Repair Strategy: Based on the assessment report of S51, adjust and optimize the vegetation configuration, irrigation plan and support maintenance strategy for the next cycle in the cloud data platform; S53, Model Parameter Self-Learning Update: The cloud data platform uses long-term accumulated data and regulatory feedback to automatically train and iteratively update the analytical model parameters in S33.

[0016] Therefore, the present invention employs the above-mentioned gradient ecological restoration system and monitoring method for coal mining subsidence areas based on photovoltaic arrays, which has the following beneficial effects: (1) Improved the overall stability and repair effect of the system: The combination of adjustable photovoltaic support and deep-buried pile foundation gives the system the ability to adapt to small surface deformations, avoiding equipment damage and destruction of repair results caused by settlement; The gradient vegetation configuration fully considers the differences in terrain and light, which significantly improves the survival rate of vegetation and enhances the soil and water conservation effect. (2) Achieving a deep integration of ecological and economic benefits: The system not only produces clean electricity (photovoltaic power generation), but also achieves carbon sequestration and oxygen release and soil improvement through scientific vegetation restoration; the "shading effect" of the photovoltaic panels provides a suitable growing environment for shade-loving plants in summer, while the transpiration of the vegetation helps to reduce the temperature around the photovoltaic panels, which may slightly improve the power generation efficiency, forming a virtuous cycle. (3) It has achieved refined and intelligent operation and maintenance management: by deploying a dense sensor network and establishing a cloud data analysis platform, it has achieved real-time and three-dimensional monitoring of the five major elements of terrain, soil, vegetation, photovoltaics and meteorology; the intelligent early warning and automatic control functions have shortened the problem discovery and handling response time from several days or even several weeks in the traditional manual inspection mode to within a few hours, which has greatly improved management efficiency and system reliability. (4) It has strong adaptability and scalability: The core design concept of the system is "zoning management and dynamic adaptation"; gradient division, adjustable support, modular vegetation strategy, etc., make the system flexible to be applied to coal mining subsidence areas with different geological conditions and different degrees of subsidence (light, medium and heavy) by adjusting specific parameters (such as support adjustment range, vegetation variety and monitoring density), and has strong universality.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of the gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to the present invention; Figure 2 This is a flowchart illustrating the overall process of the monitoring method for the gradient ecological restoration system of coal mining subsidence areas based on photovoltaic arrays according to the present invention. Figure 3 This is a structural diagram of the adjustable bracket according to an embodiment of the present invention; Figure Labels 1. Concrete pile foundation; 2. Photovoltaic support hydraulic device; 3. Drip irrigation system; 4. Horizontal fixing rod. Detailed Implementation

[0019] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] Please see Figure 1 A gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays includes: The subsidence area pretreatment layer is used to level and compact the base of the coal mining subsidence area. The base is divided into three gradient areas: gentle slope area, mild slope area, and steep slope area according to the slope of 0-5°, 5-15°, and 15-25°. Each area is equipped with a water interception ditch at the edge, and the bottom of the water interception ditch is covered with an impermeable membrane. The photovoltaic array support unit is installed on the pre-treated foundation of the subsidence area. It includes concrete piles embedded in the foundation, an adjustable bracket hinged to the top of the piles, and photovoltaic panels mounted on the bracket. The photovoltaic panels are double-sided double-glass photovoltaic panels (450W-550W). The spacing between the panels is designed according to the "gradient adaptation principle": 1.5 to 2 meters in flat areas, 2 to 2.5 meters in gentle slope areas, and 2.5 to 3 meters in steep slope areas, to avoid the impact of shading on the growth of underlying vegetation. The adjustable bracket includes a photovoltaic bracket hydraulic device 2 hinged to the photovoltaic panels and a horizontal fixing rod 4 fixedly connected to the bottom of the photovoltaic bracket hydraulic device 2. By controlling the height of the photovoltaic bracket hydraulic device 2, the tilt angle of the photovoltaic panels can be steplessly adjusted within the range of 15° to 30°, with an adjustment accuracy of ±1°. Figure 3 As shown; the depth of concrete pile foundation 1 is 1.5 meters to 2.5 meters; the tilt angle of photovoltaic panel modules is adjusted to 15° to 20° in flat areas, 20° to 25° in gentle slope areas, and 25° to 30° in steep slope areas; the photovoltaic array support unit also includes a cable storage unit, which is located inside the adjustable bracket, with built-in tensile cables to adapt to minor surface deformations and prevent cable damage.

[0021] The gradient vegetation restoration unit is configured with different vegetation restoration schemes for flat, gentle, and steep slope areas. These schemes include vegetation species, planting methods, and soil improvement measures. Specifically, the vegetation restoration schemes for the gradient vegetation restoration unit include: For flat areas, a combination of shade-tolerant and trampling-resistant herbaceous plants and shallow-rooted shrubs is planted to form a lawn-shrub composite vegetation. Below the photovoltaic array, after soil improvement, shade-tolerant herbaceous plants (such as alfalfa and ryegrass) are planted, along with shallow-rooted shrubs (such as Amorpha fruticosa). The soil improvement plan is as follows: apply 30t of decomposed organic fertilizer + 15t of desulfurized gypsum per hectare to adjust the soil pH to 6.5-7.5, and at the same time lay geogrid (grid size 20cm×20cm) to enhance the soil's resistance to erosion. For gentle slopes, plant deep-rooted leguminous plants and small trees, along with creeping vines; for example, lay ecological bags (filled with soil + grass seeds + water-retaining agent) along the outside of the photovoltaic support columns, stacking the ecological bags to a height of 0.8-1.2m to form a slope protection zone; plant vines with strong soil-fixing ability (such as Virginia creeper and ivy) inside the bags, whose roots can penetrate the ecological bags and combine with the surface soil to improve slope stability; For steep slope areas, hydroseeding technology is used to plant pioneer herbs and vines, and planting bags are set up around the concrete pile foundation, with nutrient soil and shrub seeds inside the planting bags. The gradient vegetation restoration unit also includes a microbial amendment layer, which is a compound microbial agent applied to the soil surface. The compound microbial agent contains nitrogen-fixing bacteria, phosphate-solubilizing bacteria, and actinomycetes, and the application rate is 20-30 g / m². 2 The mixture should be 10-15cm deep with the topsoil. The ecological monitoring unit includes soil sensors for monitoring soil parameters, vegetation monitoring equipment for monitoring vegetation growth status, and photovoltaic efficiency detectors for monitoring photovoltaic power generation performance. The ecological monitoring unit also includes a meteorological monitoring subunit for monitoring wind speed, precipitation, light intensity, and air temperature and humidity. Furthermore, the soil sensors, vegetation monitoring equipment, photovoltaic efficiency detectors, and meteorological monitoring subunit are all connected to a central control unit via wireless communication modules. The central control unit includes: The data receiving and storage module is used to receive and store various monitoring data from the ecological monitoring unit; The data analysis and early warning module is used to analyze and process the monitoring data and generate early warning information when the monitoring data exceeds a preset threshold. The instruction generation and distribution module generates control instructions based on early warning information or preset strategies and distributes them to the corresponding actuators. It connects to the hydraulic adjustment device of the photovoltaic support via a PLC controller. When GNSS detects a change in surface slope exceeding 3°, it automatically adjusts the support tilt angle to ensure photovoltaic panel power generation efficiency. It connects to the drip irrigation system 3 (located on the side of the horizontal fixing rod of the adjustable support) in gentle gradient and sloping areas, automatically starting and stopping irrigation based on soil volumetric moisture content, controlling the irrigation volume at 20-30 L / m². 2 ·Second-rate; Please see Figure 2 A monitoring method for a gradient ecological restoration system in coal mining subsidence areas based on photovoltaic arrays includes the following steps: Step 1, System Deployment and Initialization: Complete the deployment and installation of each unit of the system, initialize the ecological monitoring unit, and set the threshold range of each monitoring parameter; Step 2: Synchronous Acquisition of Multi-Source Data: The ecological monitoring unit synchronously collects topographic subsidence data, soil parameter data, vegetation growth data, photovoltaic operation data, and meteorological data according to a preset frequency. Among them, topographic subsidence data is collected every 15 minutes through a GNSS monitoring station; soil parameter data is collected every hour through a soil sensor; vegetation growth data is collected weekly through vegetation monitoring equipment (a drone equipped with a multispectral camera) and calibrated through fixed quadrats; photovoltaic operation data is collected every 5 minutes through a photovoltaic efficiency detector (a sensor installed at the inverter); and meteorological data is collected every hour through a meteorological monitoring subunit (meteorological station).

[0022] Step 3: Data Transmission and Cloud Processing: The central control unit transmits the collected data to the cloud data platform via encrypted wireless transmission. The cloud data platform then preprocesses, stores, and performs correlation analysis on the data. The specific process is as follows: S31. Data Upload: The central control unit synchronously uploads the pre-processed local data to the cloud data platform via an encrypted communication link; S32. Cloud Data Governance: The cloud data platform cleans, aligns, and standardizes the multi-source heterogeneous data it receives, and stores it in a distributed time-series database. S33. Multi-dimensional correlation analysis: The cloud data platform calls the built-in analysis model to perform the following calculations and analyses on the standardized data: Light-vegetation coupling analysis: Based on vegetation spectral data and light data collected by ecological monitoring units, vegetation indices are calculated for each gradient zone. With photovoltaic panel shading rate Quantitative Relationship Model ,in, Indicates the first Normalized Difference Vegetation Index at each monitoring point Indicates the first The shading rate of the photovoltaic panels corresponding to each monitoring point Indicates the first Soil temperature at each monitoring point, in degrees Celsius. Indicates the first Soil volumetric moisture content at each monitoring point This represents a function used in multiple regression analysis. Soil-PV Benefit Analysis: Based on soil nutrient and PV power generation data, this study constructs a model of how soil improvement affects the microclimate and power generation efficiency of PV panels. Impact Model ,in, Solar irradiance is expressed in watts per square meter. This indicates the ambient air temperature, expressed in degrees Celsius. This indicates the comprehensive index of soil nutrients. This represents the comprehensive influence function; Deformation-Structural Risk Analysis: Calculating Surface Subsidence Rate Based on GNSS Displacement Data With acceleration And assess its structural risk level to recent photovoltaic mounting systems. ,in, This indicates the horizontal distance between the monitored deformation point and the nearest photovoltaic support pile. This represents the risk assessment function.

[0023] Step 4, Intelligent Analysis and Dynamic Control: Based on the correlation analysis results, determine the system status and execute hierarchical early warning and closed-loop control; the specific process is as follows: S41. Status Assessment and Graded Early Warning Trigger: Based on the analysis results of S33, the cloud data platform compares them with the preset macro-early warning thresholds to generate and issue three-level early warning information, including yellow, orange and red warnings; at the same time, the data analysis and early warning module of the central control unit independently performs rapid safety judgment based on local real-time data. Yellow Alert (Attention Level): When the average of any gradient zone Values ​​have decreased by more than 5% for two consecutive weeks, or soil moisture A settlement rate below 15% for 24 consecutive hours, or a single-point settlement rate satisfy Triggered at time; Orange Alert (Adjusted Level): When a specific area... A value below 0.3, or photovoltaic power generation efficiency A year-on-year decline of more than 8% for three consecutive days, or satisfy or risk level Triggered upon reaching intermediate level; Red Alert (Emergency Level): When the monthly cumulative displacement of the Earth's surface is detected to be >15mm, or Triggered when the advanced level is reached, or when the reading of the photovoltaic array structure tilt sensor abnormally exceeds the limit; S42. Automatic Control Command Execution: For orange-level and below warnings triggered in S41 with clearly defined logic, the platform automatically executes closed-loop control; when the soil volumetric moisture content is below the threshold, the corresponding zone's drip irrigation system is automatically activated, and the irrigation volume... When GNSS analysis indicates local slope changes At a certain angle, an adjustment command is automatically sent to the hydraulic device of the photovoltaic support in that area, and the new tilt angle is determined. When the cloud data platform's analysis model identifies the photovoltaic conversion efficiency of a specific area based on photovoltaic efficiency detector data... When the year-on-year decline in solar PV module emissions persists for several consecutive days, weather factors are ruled out, and the cause is determined to be surface dust accumulation, a closed-loop cleaning control system is triggered. Specifically, the cloud data platform generates cleaning task instructions and sends them to the central control unit. The central control unit then generates and sends instructions to drive automated cleaning robots or spray systems deployed on the photovoltaic modules to perform targeted cleaning operations. Indicates the irrigation coefficient. Indicates the target soil volumetric moisture content. This indicates the current soil volumetric moisture content. This indicates the initial tilt angle of the photovoltaic support; S43. Generating and pushing manual handling suggestions: For red alerts triggered by S41 or orange alerts that have not been alleviated after automatic adjustment by S42, the platform automatically generates and pushes a detailed handling suggestion report, which incorporates the analysis results of S33.

[0024] Step 5, Effect Evaluation and Strategy Optimization: Regularly evaluate the ecological restoration effects and photovoltaic power generation efficiency based on long-term monitoring data, and optimize restoration strategies or system operating parameters according to the evaluation results; specifically including: S51. Regular comprehensive assessment: The cloud data platform summarizes and analyzes all historical data on a quarterly or annual basis, generating a comprehensive assessment report covering ecological, energy, and security dimensions; S52, Iterative Optimization of Repair Strategy: Based on the assessment report of S51, adjust and optimize the vegetation configuration, irrigation plan and support maintenance strategy for the next cycle in the cloud data platform; S53, Model Parameter Self-Learning Update: The cloud data platform uses long-term accumulated data and regulatory feedback to automatically train and iteratively update the analytical model parameters in S33.

[0025] Example Area Overview: The subsidence area covers 50 hectares, with the following topographic slope distribution: gentle slope (<5°) 25 hectares, sloping slope (5°-15°) 15 hectares, and the area around the subsidence pit (>15°) 10 hectares; the soil type is sandy loam, pH=8.2 (alkaline), and organic matter content is 1.2% (low).

[0026] System deployment: Photovoltaic array support module: adopts 450W double-sided double-glass photovoltaic panels, with a support spacing of 2m in flat areas, 2.5m in gentle slope areas, and 5m in steep slope areas; the pile foundation is buried at a depth of 2.5m, and the hydraulic adjustment device controls the support tilt angle at 25° (the optimal power generation tilt angle in the local area). Gradient ecological restoration module: In the gentle slope area, apply 30t / hectare of organic fertilizer + 15t / hectare of desulfurized gypsum, and plant alfalfa and purple locust; in the gentle slope area, stack ecological bags (1m high) and plant ivy; in the steep slope area, build retaining walls (1.5m high), lay impermeable membrane at the bottom of the pit, and plant poplar and reeds. Intelligent monitoring module: 12 GNSS stations are deployed, 6 soil sensors are deployed at each gradient, drones conduct inspections once a week, and power sensors are installed at the photovoltaic inverter.

[0027] Running result: Ecological effects: After 12 months of operation, the vegetation coverage in the flat area increased from 35% to 90%, the soil erosion in the gentle slope area decreased by 70%, and the water quality of the artificial wetland in the steep slope area reached the Class IV standard for surface water. Energy performance: The annual photovoltaic power generation reaches 6.75 million kWh, with a power generation efficiency of over 80% (10% better than fixed-mount photovoltaic systems). Monitoring results: GNSS successfully captured two minor settlements (maximum displacement 8mm), and the platform automatically adjusted the support tilt angle, without affecting the vegetation and photovoltaics; the soil sensor issued three warnings of soil drought, and the drip irrigation system replenished water in time, and the vegetation did not wither.

[0028] Therefore, this invention employs the aforementioned photovoltaic array-based gradient ecological restoration system and monitoring method for coal mining subsidence areas, aiming to achieve synergistic effects between ecological governance and clean energy production. The system includes: a subsidence area pretreatment layer, which divides the subsidence area into three gradient zones—flat, gentle, and steep—based on slope and implements foundation treatment; a photovoltaic array support unit, which combines adjustable supports with deeply embedded concrete piles, dynamically adjusting the tilt angle (15°-30°) and spacing (1.5-3 meters) of the photovoltaic panels according to the regional slope to adapt to terrain changes and optimize light distribution; and a gradient vegetation restoration unit, which configures differentiated vegetation combinations and soil amendments for different slope areas. The invention employs effective measures and integrates an ecological monitoring unit that monitors topography, soil, vegetation, photovoltaics, and meteorology. The monitoring method utilizes the aforementioned system, along with a central control unit and cloud data platform comprised of modules for data reception and storage, analysis and early warning, and command generation and distribution. This enables high-frequency data acquisition, multi-dimensional correlation analysis based on mathematical models, tiered early warning triggering (yellow, orange, and red levels), and closed-loop management combining automatic control (such as precision irrigation and support adjustment) with manual intervention suggestions. Through "zonal governance, dynamic adaptation, and intelligent control," this invention significantly improves the stability of subsidence area restoration, resource utilization efficiency, and the level of intelligent operation and maintenance.

[0029] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays, characterized in that, include: The subsidence area pretreatment layer is used to level and compact the base of the coal mining subsidence area. The base is divided into three gradient areas: gentle slope area, mild slope area, and steep slope area according to the slope of 0-5°, 5-15°, and 15-25°. Each area is equipped with a water interception ditch at the edge, and the bottom of the water interception ditch is covered with an impermeable membrane. The photovoltaic array support unit is installed on the pre-treated base of the settlement area. It includes concrete piles embedded in the base, an adjustable bracket connected to the top of the concrete piles, and photovoltaic panels installed on the bracket. The spacing between the photovoltaic panels is set to different values ​​depending on the area. The adjustable bracket includes a photovoltaic bracket hydraulic device hinged to the photovoltaic panels and a horizontal fixing rod fixedly connected to the bottom of the photovoltaic bracket hydraulic device. By controlling the height of the photovoltaic bracket hydraulic device, the tilt angle of the photovoltaic panels can be steplessly adjusted within the range of 15° to 30° with an adjustment accuracy of ±1°. The embedment depth of the concrete piles is 1.5 meters to 2.5 meters. The gradient vegetation restoration unit is configured with different vegetation restoration schemes for flat areas, gentle slope areas and steep slope areas. The vegetation restoration schemes include vegetation types, planting methods and soil improvement measures. The ecological monitoring unit includes soil sensors for monitoring soil parameters, vegetation monitoring equipment for monitoring vegetation growth status, and photovoltaic efficiency detectors for monitoring photovoltaic power generation performance.

2. The gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 1, characterized in that: The spacing between photovoltaic panels in flat areas is 1.5 to 2 meters, in gentle slope areas it is 2 to 2.5 meters, and in steep slope areas it is 2.5 to 3 meters. The tilt angle of the photovoltaic panels is adjusted to 15° to 20° in flat areas, 20° to 25° in gentle slope areas, and 25° to 30° in steep slope areas.

3. The gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 2, characterized in that, The vegetation restoration scheme of the gradient vegetation restoration unit specifically includes: For flat areas, a combination of shade-tolerant and trampling-resistant herbaceous plants and shallow-rooted shrubs is used to form a lawn-shrub composite vegetation. For gentle slopes, plant deep-rooted leguminous plants and small trees, along with creeping vines; For steep slope areas, hydroseeding technology is used to plant pioneer herbs and vines, and planting bags are set up around the concrete pile foundation, filled with nutrient soil and shrub seeds.

4. The gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 3, characterized in that: The gradient vegetation restoration unit also includes a microbial amendment layer, which is a compound microbial agent applied to the soil surface. The compound microbial agent contains nitrogen-fixing bacteria, phosphate-solubilizing bacteria, and actinomycetes, and the application rate is 20-30 g / m². 2 The mixture should be mixed with the topsoil to a depth of 10-15cm.

5. The gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 4, characterized in that: The ecological monitoring unit also includes a meteorological monitoring subunit for monitoring wind speed, precipitation, light intensity, and air temperature and humidity. Furthermore, the soil sensor, vegetation monitoring equipment, photovoltaic efficiency detector, and meteorological monitoring subunit are all connected to a central control unit via a wireless communication module. The central control unit includes: The data receiving and storage module is used to receive and store various monitoring data from the ecological monitoring unit; The data analysis and early warning module is used to analyze and process the monitoring data and generate early warning information when the monitoring data exceeds a preset threshold. The instruction generation and issuance module is used to generate control instructions based on early warning information or preset strategies and issue them to the corresponding execution agencies.

6. A monitoring method for a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays, using the gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays as described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1, System Deployment and Initialization: Complete the deployment and installation of each unit of the system, initialize the ecological monitoring unit, and set the threshold range of each monitoring parameter; Step 2: Synchronous acquisition of multi-source data: The ecological monitoring unit synchronously acquires topographic subsidence data, soil parameter data, vegetation growth data, photovoltaic operation data, and meteorological data according to a preset frequency; Step 3, Data Transmission and Cloud Processing: The central control unit sends the collected data to the cloud data platform via encrypted wireless transmission, where the cloud data platform performs preprocessing, storage, and correlation analysis on the data. Step 4, Intelligent Analysis and Dynamic Control: Based on the correlation analysis results, determine the system status and execute hierarchical early warning and closed-loop control; Step 5: Effect evaluation and strategy optimization: Regularly evaluate the ecological restoration effect and photovoltaic power generation efficiency based on long-term monitoring data, and optimize the restoration strategy or system operating parameters according to the evaluation results.

7. The monitoring method for a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 6, characterized in that, In step 2, topographic subsidence data is collected every 15 minutes via GNSS monitoring stations; soil parameter data is collected every hour via soil sensors; vegetation growth data is collected weekly via vegetation monitoring equipment and calibrated using fixed quadrats; photovoltaic operation data is collected every 5 minutes via photovoltaic efficiency detectors; and meteorological data is collected every hour via meteorological monitoring subunits.

8. The monitoring method for a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 7, characterized in that, The specific process of step 3 is as follows: S31. Data Upload: The central control unit synchronously uploads the pre-processed local data to the cloud data platform via an encrypted communication link; S32. Cloud Data Governance: The cloud data platform cleans, aligns, and standardizes the multi-source heterogeneous data it receives, and stores it in a distributed time-series database. S33. Multi-dimensional correlation analysis: The cloud data platform calls the built-in analysis model to perform the following calculations and analyses on the standardized data: Light-vegetation coupling analysis: Based on vegetation spectral data and light data collected by ecological monitoring units, vegetation indices are calculated for each gradient zone. With photovoltaic panel shading rate Quantitative Relationship Model ,in, Indicates the first Normalized Difference Vegetation Index at each monitoring point Indicates the first The shading rate of the photovoltaic panels corresponding to each monitoring point Indicates the first Soil temperature at each monitoring point, in degrees Celsius. Indicates the first Soil volumetric moisture content at each monitoring point This represents a function used in multiple regression analysis. Soil-PV Benefit Analysis: Based on soil nutrient and PV power generation data, this study constructs a model of how soil improvement affects the microclimate and power generation efficiency of PV panels. Impact Model ,in, Solar irradiance is expressed in watts per square meter. This indicates the ambient air temperature, expressed in degrees Celsius. This indicates the comprehensive index of soil nutrients. This represents the comprehensive influence function; Deformation-Structural Risk Analysis: Calculating Surface Subsidence Rate Based on GNSS Displacement Data With acceleration And assess its structural risk level to recent photovoltaic mounting systems. ,in, This indicates the horizontal distance between the monitored deformation point and the nearest photovoltaic support pile. This represents the risk assessment function.

9. The monitoring method for a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 8, characterized in that, The specific process of step 4 is as follows: S41. Status Assessment and Graded Early Warning Trigger: Based on the analysis results of S33, the cloud data platform compares them with the preset macro-early warning thresholds to generate and issue three-level early warning information, including yellow, orange and red warnings; at the same time, the data analysis and early warning module of the central control unit independently performs rapid safety judgment based on local real-time data. S42. Automatic Control Command Execution: For orange-level and below warnings triggered in S41 with clearly defined logic, the platform automatically executes closed-loop control; when the soil volumetric moisture content is below the threshold, the corresponding zone's drip irrigation system is automatically activated, and the irrigation volume... ; When GNSS analysis indicates local slope changes At a certain angle, an adjustment command is automatically sent to the hydraulic device of the photovoltaic support in that area, and the new tilt angle is determined. When the cloud data platform's analysis model identifies the photovoltaic conversion efficiency of a specific area based on photovoltaic efficiency detector data... When the year-on-year decline in solar PV module emissions persists for several consecutive days, weather factors are ruled out, and the cause is determined to be surface dust accumulation, a closed-loop cleaning control system is triggered. Specifically, the cloud data platform generates cleaning task instructions and sends them to the central control unit. The central control unit then generates and sends instructions to drive automated cleaning robots or spray systems deployed on the photovoltaic modules to perform targeted cleaning operations. Indicates the irrigation coefficient. Indicates the target soil volumetric moisture content. This indicates the current soil volumetric moisture content. This indicates the initial tilt angle of the photovoltaic support; S43. Generating and pushing manual handling suggestions: For red alerts triggered by S41 or orange alerts that have not been alleviated after automatic adjustment by S42, the platform automatically generates and pushes a detailed handling suggestion report, which incorporates the analysis results of S33.

10. The monitoring method for a gradient ecological restoration system for coal mining subsidence areas based on photovoltaic arrays according to claim 9, characterized in that, Step 5 specifically includes: S51. Regular comprehensive assessment: The cloud data platform summarizes and analyzes all historical data on a quarterly or annual basis, generating a comprehensive assessment report covering ecological, energy, and security dimensions; S52, Iterative Optimization of Repair Strategy: Based on the assessment report of S51, adjust and optimize the vegetation configuration, irrigation plan and support maintenance strategy for the next cycle in the cloud data platform; S53, Model Parameter Self-Learning Update: The cloud data platform uses long-term accumulated data and regulatory feedback to automatically train and iteratively update the analytical model parameters in S33.

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