Automatic reseeding method for recovering grassland vegetation occupied by photovoltaic power station
By dividing the grassland vegetation restoration in photovoltaic power stations into reseeding zones, setting environmental thresholds, and implementing automatic sowing and monitoring adjustments, the problems of low efficiency and insufficient accuracy of traditional manual sowing have been solved. This has enabled intelligent, efficient, and precise grassland vegetation restoration, improved the seedling emergence rate and survival rate, and is suitable for the vegetation restoration of photovoltaic power stations in mountain meadow grassland areas.
Patent Information
- Application Number
- CN202511466945.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-14
- Publication Date
- 2025-12-16
AI Technical Summary
In the restoration of grassland vegetation by photovoltaic power stations, traditional manual sowing methods are inefficient and lack precision, making them difficult to adapt to complex terrain. This results in uneven distribution of grass seeds and inconsistent quality of vegetation restoration, especially in areas with steep slopes and complex terrain where it is difficult to guarantee sowing accuracy.
Based on the layout of photovoltaic power stations and the site conditions of grasslands, reseeding zones are divided, and environmental monitoring, grass seed ratio and automatic sowing equipment units are deployed. Environmental parameter thresholds are set, grass seed mixing and sowing are completed automatically, obstacle avoidance operation paths are planned, sowing parameters are monitored and dynamically adjusted in real time, vegetation restoration indicators are monitored regularly, and automatic decisions are made for reseeding.
It has achieved intelligent and precise grassland vegetation restoration, improved operational efficiency, ensured that grass seeds are sown under optimal environmental conditions, increased germination and survival rates, and solved the problems of low efficiency and insufficient precision of traditional manual methods. The average daily operating area of a single machine can reach 1.5-2 hectares, and the vegetation restoration qualification rate is over 95%.
Smart Images
Figure CN121128385A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of grassland restoration technology, and in particular to an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations. Background Technology
[0002] With the development of the photovoltaic power generation industry, a large number of photovoltaic power station projects are being built in grassland areas. During the construction and operation of these projects, it is inevitable that large areas of grassland will be temporarily occupied, leading to damage to surface vegetation, exposed soil, and disturbance to the ecological environment. According to the relevant regulations of the National Forestry and Grassland Administration, after the completion of photovoltaic power station projects, vegetation restoration must be carried out on the occupied grassland areas to ensure the integrity and functionality of the grassland ecosystem.
[0003] Currently, traditional manual seeding is commonly used in grassland vegetation restoration projects for photovoltaic power stations. This method relies heavily on manual seeding, which presents a significant efficiency bottleneck. In practice, the complex terrain of photovoltaic power station sites, the dense distribution of photovoltaic module arrays, and the crisscrossing maintenance roads, transformer boxes, and other facilities severely limit the scope and efficiency of manual operations. Statistics show that using manual seeding, the average daily vegetation restoration area is typically less than 0.5 hectares, and the quality of work varies considerably. Especially in areas with steep slopes and complex terrain, manual seeding struggles to guarantee the uniformity and accuracy of seed distribution. Summary of the Invention
[0004] The present invention aims to at least partially solve one of the technical problems in the related art.
[0005] Therefore, the first objective of this invention is to propose an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power plants.
[0006] The second objective of this invention is to provide an automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power plants.
[0007] The third objective of this invention is to provide an electronic device.
[0008] The fourth objective of this invention is to provide a computer-readable storage medium.
[0009] The fifth objective of this invention is to provide a computer program product.
[0010] To achieve the above objectives, a first aspect of the present invention provides an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power plants, comprising: Based on the layout of the photovoltaic power station and the site conditions of the grassland, the area to be restored is divided into several reseeding zones, and equipment units for environmental monitoring, grass seed ratio, automatic sowing and post-operative care are deployed in each zone. Based on the climate and soil characteristics of grassland types, set the environmental parameter thresholds required to trigger automatic reseeding; Based on a pre-determined combination and proportion of grass species, the system automatically completes the metering, conveying, and mixing of various grasses to form a mixed grass species. Based on the facility layout map and terrain data of the photovoltaic power station, an operation path is planned for the automatic seeding equipment that can effectively avoid fixed facilities and adapt to changes in terrain. The system monitors environmental parameters in real time, and when the threshold is reached, it automatically controls the seeding equipment to move and seed along the planned path, and dynamically adjusts the seeding parameters based on real-time terrain information. After reseeding is completed, key indicators of vegetation recovery are monitored regularly. If the indicators do not meet the preset standards, the system will automatically decide to reseed again.
[0011] The specific steps for dividing the area to be restored into several reseeding zones, based on the layout of the photovoltaic power station and the site conditions of the grassland, include: Based on the distribution of photovoltaic cell arrays, topographic slope, and soil type differences, the grassland area is divided into multiple reseeding zones, and the photovoltaic array area is distinguished from other areas.
[0012] The specific steps for setting the environmental parameter thresholds required to trigger automatic reseeding, based on the climate and soil characteristics of grassland types, include: Obtain site condition data for grassland types, including average annual temperature and annual rainfall. Based on the obtained data, reseeding trigger thresholds were set, including soil volumetric moisture content, single rainfall amount, and air temperature.
[0013] The specific steps involved in automatically metering, transporting, and mixing various forages to form a mixed forage species, based on a pre-determined combination and proportion of forages, include: Calculate the total demand for each grass species based on the area of the zone and the preset sowing amount; Control the delivery of grass seeds from each grass seed storage bin to the mixing bin according to a preset ratio; Start the mixing device in the mixing chamber to mix the grass seeds evenly for the predetermined time.
[0014] The specific steps for planning an automated seeding device that can effectively avoid fixed facilities and adapt to terrain changes, based on the facility layout map and terrain data of the photovoltaic power station, include: Import CAD layout drawings and terrain data of photovoltaic power plants; The plan can avoid the seeding paths of photovoltaic brackets, maintenance roads, and permanent buildings; For areas with a slope greater than 20 degrees, plan a transverse contour line path.
[0015] The specific steps of real-time monitoring of environmental parameters, automatically controlling the seeding equipment to move and seed along the planned path when the threshold is reached, and dynamically adjusting the seeding parameters based on real-time terrain information include: Real-time monitoring of environmental parameters to determine whether the trigger threshold has been reached; When the threshold is reached, control the spreading equipment to move along the planned path and spread the seeds; The seeding rate is dynamically increased based on the real-time terrain slope.
[0016] The specific threshold for triggering replay is as follows: Soil volumetric moisture content 15%-35%, single rainfall ≥8mm, air temperature 15℃-25℃.
[0017] To achieve the above objectives, a second aspect of the present invention provides an automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power plants, comprising: The deployment module is used to divide the area to be restored into several reseeding zones based on the layout of the photovoltaic power station and the site conditions of the grassland, and to deploy equipment units in each zone for environmental monitoring, grass seed ratio, automatic sowing and post-operative care. The triggering module is used to set the environmental parameter thresholds required to trigger automatic reseeding based on the climate and soil characteristics of the grassland type. The mixing module is used to automatically measure, transport, and mix various forages according to a pre-determined combination and proportion of grass seeds to form a mixed grass seed; The path planning module is used to plan an operation path for the automatic seeding equipment based on the facility layout map and terrain data of the photovoltaic power station, which can effectively avoid fixed facilities and adapt to terrain changes. The spreading module is used to monitor environmental parameters in real time. When the threshold is reached, it automatically controls the spreading equipment to move and spread along the planned path, and dynamically adjusts the spreading parameters according to real-time terrain information. The reseeding module is used to periodically monitor key indicators of vegetation recovery after reseeding is completed. If the indicators do not meet the preset standards, the module will automatically make a decision and execute reseeding again.
[0018] To achieve the above objectives, a third aspect of the present invention provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.
[0019] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of the first aspects.
[0020] To achieve the above objectives, a fifth aspect of the present invention provides a computer program product that, when executed by a processor, implements the method described in any one of the first aspects.
[0021] The technical solutions provided by the embodiments of the present invention bring at least the following beneficial effects: The present invention provides an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations. Based on the layout of the photovoltaic power station and the site conditions of the grassland, reseeding zones are divided and environmental monitoring, grass seed ratio, automatic sowing, and post-operative management equipment units are deployed. Environmental parameter thresholds are set according to the grassland climate and soil characteristics. Grass seed metering, transportation, and mixing are automatically completed according to a preset ratio. An operation path that can avoid obstacles and adapt to the terrain is planned based on the layout of the power station facilities and terrain data. When environmental parameters reach the threshold, the sowing equipment is automatically controlled to operate along the path, and the sowing parameters are dynamically adjusted according to the terrain. Vegetation indicators are monitored regularly after reseeding, and reseeding is automatically performed again if the standards are not met. By replacing traditional manual sowing with automated equipment, the intelligent and precise reseeding operation is achieved, significantly improving operational efficiency and solving the problems of low efficiency, insufficient accuracy, and poor terrain adaptability of manual methods. This effectively ensures the vegetation restoration effect and meets the requirements of grassland ecological restoration.
[0022] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0023] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of an automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power stations, provided in an embodiment of the present invention. Detailed Implementation
[0024] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0025] Please see Figure 1 ,in Figure 1 This is a flowchart of an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations.
[0026] This invention provides an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power plants, comprising the following steps: S1: Based on the layout of the photovoltaic power station and the site conditions of the grassland, the area to be restored is divided into several reseeding zones, and equipment units for environmental monitoring, grass seed ratio, automatic sowing and post-operative care are deployed in each zone.
[0027] Specifically, based on the distribution of photovoltaic cell arrays, terrain slope, and soil type differences, the grassland area is divided into multiple reseeding zones, and the photovoltaic array area is distinguished from other areas.
[0028] In this implementation, the digital elevation model (DEM) and soil type distribution map of the project area are first obtained. Combined with the overall layout plan of the photovoltaic power station, GIS spatial analysis technology is used to divide areas with similar site conditions and similar operational difficulty into the same reseeding zone. Among them, the photovoltaic array area is divided into a separate operation zone due to the shading effect of photovoltaic panels and the obstruction of support structures; maintenance roads, spoil heaps, and other areas are divided into another operation zone due to their relatively flat terrain and fewer obstacles. Each reseeding zone is controlled within an area of 3-5 hectares to ensure a balance between operational efficiency and equipment coverage. An environmental monitoring unit is deployed at the center of each zone or at a higher elevation. This unit includes a soil moisture sensor (buried 15cm deep), a small weather station (monitoring rainfall and temperature), and a high-definition camera. Grass seed mixing units are set up at easily accessible locations on the edges of each zone, including four independent seed bins, one mixing bin, and an automatic weighing and conveying device. The automatic seeding unit uses a tracked chassis with RTK positioning and obstacle avoidance sensors; its seeding height is electrically adjustable within the range of 1.2-1.8m. The maintenance monitoring unit includes an infrared camera and a soil moisture monitor, communicating with the central control system via LoRa wireless networking. Through this zoned deployment method, precise adaptation to different site conditions is achieved.
[0029] S2: Based on the climate and soil characteristics of the grassland type, set the environmental parameter thresholds required to trigger automatic reseeding.
[0030] Specifically, obtain site condition data for grassland types, including average annual temperature and annual rainfall; Based on the obtained data, reseeding trigger thresholds were set, including soil volumetric moisture content, single rainfall amount, and air temperature.
[0031] In this embodiment, climate data for the past five years in the project area, including key parameters such as annual average temperature and annual rainfall, were obtained through meteorological monitoring stations and historical meteorological databases. Combined with soil profile survey data, the typical soil type was determined to be yellow-brown soil with a soil bulk density of 1.35 g / cm³. 3 The field water holding capacity was 28%. Based on these basic data, using a vegetation growth model and the principle of soil moisture balance, the optimal environmental parameter threshold ranges for grass seed germination were calculated: soil volumetric water content was set at 20-30%, single rainfall threshold was set at ≥10mm, and air temperature threshold was set at 18-24°C. These threshold parameters are transmitted wirelessly to the environmental monitoring units in each zone, serving as the basis for automatically triggering reseeding operations. When the monitoring data simultaneously meets these three conditions, the system will automatically generate a reseeding instruction to ensure that the grass seeds are sown under optimal environmental conditions, significantly improving germination and survival rates.
[0032] S3: Based on a pre-determined combination and proportion of grass species, automatically complete the metering, conveying and mixing of various grasses to form a mixed grass species.
[0033] Specifically, the total demand for each grass species is calculated based on the area of the zone and the preset sowing amount; Control the delivery of grass seeds from each grass seed storage bin to the mixing bin according to a preset ratio; Start the mixing device in the mixing chamber to mix the grass seeds evenly for the predetermined time.
[0034] In this embodiment, after receiving the operation instructions from the control center, the grass seed mixing unit first automatically calculates the total amount of grass seed required based on the area of the zone and the sowing standard of 3 kg / mu. The system mixes the grass seeds according to a 7:3 ratio of grass to legumes, specifically 1 kg / mu of wild sedge, 0.6 kg / mu of yellow cogon grass, 0.5 kg / mu of bermudagrass, and 0.9 kg / mu of white clover. Each grass seed bin is equipped with a high-precision weighing sensor and a servo motor-driven conveying device, which can automatically output the corresponding grass seeds according to the calculated weight. The grass seeds are transported to the mixing bin through a closed pipeline. The mixing bin adopts a double-layer spiral stirring structure and runs at a speed of 60 r / min for 8 minutes to ensure that the grass seed mixing uniformity reaches more than 95%. During the mixing process, the system monitors the temperature and humidity inside the bin in real time to ensure that the grass seed vigor is not affected. After the mixing is completed, the mixed grass seeds are automatically loaded into the hopper of the sowing equipment through a pneumatic conveying system, ready for subsequent operations. The mixing process is fully automated, avoiding the proportional errors that may occur with manual mixing, and ensuring the uniformity and accuracy of grass seed mixing.
[0035] S4: Based on the facility layout map and terrain data of the photovoltaic power station, plan an operation path for the automatic seeding equipment that can effectively avoid fixed facilities and adapt to changes in terrain.
[0036] Specifically, import the CAD layout drawings and terrain data of the photovoltaic power station; The plan can avoid the seeding paths of photovoltaic brackets, maintenance roads, and permanent buildings; For areas with a slope greater than 20 degrees, plan a transverse contour line path.
[0037] In this implementation, the CAD design drawings and high-precision digital elevation model (DEM) of the photovoltaic power station are first imported to establish a three-dimensional operational environment model that includes all facilities such as photovoltaic module arrays, transformer substations, booster stations, and maintenance roads. An improved A* path planning algorithm is used to generate the optimal operational path, starting from the current location of the seeding equipment and ending at the boundary of the zone. Multiple constraints are set during path planning: maintaining a safe distance of at least 1.5 meters from the photovoltaic support structure, avoiding all permanent buildings, and traveling along the edge of the maintenance road. For areas with a slope greater than 20 degrees, the system automatically identifies the slope direction and generates a lateral operational path along the contour lines, effectively preventing grass seeds from sliding downhill due to gravity. After planning, the system verifies the feasibility of the path through simulation and optimizes parameters such as the seeding equipment's travel speed and turning radius. Finally, the generated operational path is sent to the control system of the seeding equipment in the form of a navigation file to guide it in completing automated operations. This not only ensures the safety and efficiency of the operation process but also maximizes the uniformity and coverage of grass seed dispersal.
[0038] S5: Monitor environmental parameters in real time. When the threshold is reached, automatically control the seeding equipment to move and seed according to the planned path, and dynamically adjust the seeding parameters according to real-time terrain information.
[0039] Specifically, environmental parameters are monitored in real time to determine whether the trigger threshold has been reached; When the threshold is reached, control the spreading equipment to move along the planned path and spread the seeds; The seeding rate is dynamically increased based on the real-time terrain slope.
[0040] The specific threshold for triggering replay is as follows: Soil volumetric moisture content 15%-35%, single rainfall ≥8mm, air temperature 15 -25 .
[0041] In this embodiment, the environmental monitoring unit continuously collects soil volumetric moisture content, rainfall, and air temperature data, and transmits them to the central control system in real time via a LoRa wireless network. The system employs a multi-sensor data fusion algorithm, which is used when the monitored data simultaneously meet the following conditions: soil volumetric moisture content 20-30%, single rainfall ≥10mm, and air temperature 18-24°C. When the threshold conditions are met, a reseeding operation instruction is automatically generated. After receiving the instruction, the seeding equipment first performs a self-check and loads mixed grass seeds. Then, it begins to move according to the pre-planned operation path. The RTK positioning system on the equipment provides centimeter-level positioning accuracy, and combined with lidar and visual sensors, it achieves precise obstacle avoidance. During the operation, the slope sensor monitors the terrain changes in real time. When the slope is detected to be greater than 20 degrees, the control system automatically increases the seeding rate from the baseline 3 kg / mu to 3.3 kg / mu. When the slope is greater than 25 degrees, it further increases it to 3.5 kg / mu to compensate for grass seed loss in steep slope areas. The rotation speed of the seeding disc is automatically adjusted according to the travel speed, maintaining it within the range of 300-500 r / min to ensure uniform grass seed distribution. Throughout the operation, the equipment uploads operation progress and status data in real time, and the central control system can remotely monitor and adjust operation parameters to ensure high-quality completion of the reseeding operation.
[0042] S6: After reseeding is completed, key indicators of vegetation restoration are monitored regularly. If the indicators do not meet the preset standards, the system will automatically decide to reseed again.
[0043] In this embodiment, after the reseeding operation is completed, the system collects vegetation images weekly using a high-definition camera and automatically calculates vegetation coverage using a deep learning image recognition algorithm. Soil moisture content and grass seed survival rate data are collected monthly using a soil moisture monitor. The monitoring data is transmitted to the central control system via a LoRa wireless network, and the system automatically compares and analyzes the data against preset restoration standards. When the monitoring data indicates that vegetation coverage is below 60% or grass seed survival rate is below 70% within one month after sowing, the system automatically generates a secondary warning and initiates a second reseeding procedure. The second reseeding uses 50%-80% of the initial reseeding amount, intelligently adjusted according to the degree of vegetation loss: 70% is used when coverage is between 40%-60%, and the amount is adjusted further depending on the coverage level below 40%. When the vegetation coverage is 80% of the initial coverage, the system automatically updates the operational parameters and re-executes the complete reseeding process, from grass seed ratio to path planning. If monitoring shows that the vegetation coverage is still below 70% three months after sowing, the system initiates a level-three early warning and performs precise reseeding, targeting bare patches for reseeding. The reseeding amount is adjusted to 30%-50% of the initial amount. All reseeding processes are recorded in the blockchain database, forming an immutable electronic archive of vegetation restoration. The system continues to monitor until six months after sowing. When the vegetation coverage stably reaches 80% or more and is evenly distributed (without obvious bare patches), a restoration qualification report is automatically generated, marking the completion of the vegetation restoration task in the area. This ensures the reliability and sustainability of the vegetation restoration effect and significantly improves the success rate of grassland ecological restoration.
[0044] This invention provides an automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations. Through zoning and precise deployment, it achieves accurate adaptation to different site conditions. Based on an environmental threshold determination mechanism using multi-source data fusion, it ensures that grass seeds are sown under optimal environmental conditions, significantly improving germination and survival rates. The fully automated grass seed mixing system guarantees the accuracy and uniformity of the mixing ratio, avoiding human error. The innovative design of dynamically adjusting the sowing amount according to the terrain slope effectively solves the problem of grass seed loss in steep slope areas. This method is particularly suitable for vegetation restoration projects of photovoltaic power stations in mountain meadow grassland areas. The daily operating area of a single device can reach 1.5-2 hectares, which is 3-4 times more efficient than traditional manual methods. The vegetation restoration qualification rate (coverage ≥80% within 6 months) can reach more than 95%. This method not only significantly reduces labor costs and workload, but also effectively promotes the improvement of the ecological environment and the restoration of grassland ecosystem functions in the photovoltaic power station area through precise ecological restoration.
[0045] To achieve the above embodiments, the present invention also proposes an automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power stations. Figure 2 This is a schematic diagram of an automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power plants, provided in an embodiment of the present invention. Figure 2 As shown, the device includes: The deployment module 100 is used to divide the area to be restored into several reseeding zones based on the layout of the photovoltaic power station and the site conditions of the grassland, and to deploy equipment units in each zone for environmental monitoring, grass seed ratio, automatic sowing and post-operative care. The trigger module 200 is used to set the environmental parameter thresholds required to trigger automatic reseeding based on the climate and soil characteristics of the grassland type. The mixing module 300 is used to automatically measure, transport and mix multiple grasses according to a pre-determined combination and proportion of grasses to form a mixed grass species. The path planning module 400 is used to plan an operation path for the automatic seeding equipment based on the facility layout map and terrain data of the photovoltaic power station, which can effectively avoid fixed facilities and adapt to terrain changes. The spreading module 500 is used to monitor environmental parameters in real time. When the threshold is reached, it automatically controls the spreading equipment to move and spread along the planned path, and dynamically adjusts the spreading parameters according to real-time terrain information. The reseeding module 600 is used to periodically monitor key indicators of vegetation restoration after reseeding is completed. If the indicators do not meet the preset standards, it will automatically make a decision and execute reseeding again.
[0046] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
[0047] To implement the above embodiments, the present invention also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.
[0048] To implement the above embodiments, the present invention also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.
[0049] To implement the above embodiments, the present invention also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.
[0050] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this invention all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0051] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.
[0052] This invention is intended to provide implementation schemes for users to selectively prevent the use or access to personal information data. That is, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.
[0053] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0054] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0055] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.
[0056] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0057] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0058] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0059] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0060] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.
[0061] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.
[0062] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.
Claims
1. An automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations, characterized in that, Includes the following steps: Based on the layout of the photovoltaic power station and the site conditions of the grassland, the area to be restored is divided into several reseeding zones, and equipment units for environmental monitoring, grass seed ratio, automatic sowing and post-operative care are deployed in each zone. Based on the climate and soil characteristics of grassland types, set the environmental parameter thresholds required to trigger automatic reseeding; Based on a pre-determined combination and proportion of grass species, the system automatically completes the metering, conveying, and mixing of various grasses to form a mixed grass species. Based on the facility layout map and terrain data of the photovoltaic power station, an operation path is planned for the automatic seeding equipment that can effectively avoid fixed facilities and adapt to changes in terrain. The system monitors environmental parameters in real time, and when the threshold is reached, it automatically controls the seeding equipment to move and seed along the planned path, and dynamically adjusts the seeding parameters based on real-time terrain information. After reseeding is completed, key indicators of vegetation recovery are monitored regularly. If the indicators do not meet the preset standards, the system will automatically decide to reseed again.
2. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 1, characterized in that, Based on the layout of the photovoltaic power station and the site conditions of the grassland, the specific steps for dividing the area to be restored into several reseeding zones include: Based on the distribution of photovoltaic cell arrays, topographic slope, and soil type differences, the grassland area is divided into multiple reseeding zones, and the photovoltaic array area is distinguished from other areas.
3. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 1, characterized in that, Based on the climate and soil characteristics of grassland types, the specific steps for setting the environmental parameter thresholds required to trigger automatic reseeding include: Obtain site condition data for grassland types, including average annual temperature and annual rainfall. Based on the obtained data, reseeding trigger thresholds were set, including soil volumetric moisture content, single rainfall amount, and air temperature.
4. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 1, characterized in that, Based on a pre-determined combination and proportion of grass seeds, the system automatically completes the metering, conveying, and mixing of various forages to form a mixed grass seed. The specific steps include: Calculate the total demand for each grass species based on the area of the zone and the preset sowing amount; Control the delivery of grass seeds from each grass seed storage bin to the mixing bin according to a preset ratio; Start the mixing device in the mixing chamber to mix the grass seeds evenly for the predetermined time.
5. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 1, characterized in that, Based on the photovoltaic power plant's facility layout map and terrain data, the specific steps for planning an automated seeding device that effectively avoids fixed facilities and adapts to terrain changes include: Import CAD layout drawings and terrain data of photovoltaic power plants; The plan can avoid the seeding paths of photovoltaic brackets, maintenance roads, and permanent buildings; For areas with a slope greater than 20 degrees, plan a transverse contour line path.
6. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 1, characterized in that, The specific steps of real-time monitoring of environmental parameters, automatically controlling the seeding equipment to move and seed along the planned path when the threshold is reached, and dynamically adjusting the seeding parameters based on real-time terrain information include: Real-time monitoring of environmental parameters to determine whether the trigger threshold has been reached; When the threshold is reached, control the spreading equipment to move along the planned path and spread the seeds; The seeding rate is dynamically increased based on the real-time terrain slope.
7. The automatic reseeding method for restoring grassland vegetation occupied by photovoltaic power stations as described in claim 6, characterized in that, The specific threshold for triggering replay is as follows: Soil volumetric moisture content 15%-35%, single rainfall ≥8mm, air temperature 15℃-25℃.
8. An automatic reseeding device for restoring grassland vegetation occupied by photovoltaic power stations, characterized in that, include: The deployment module is used to divide the area to be restored into several reseeding zones based on the layout of the photovoltaic power station and the site conditions of the grassland, and to deploy equipment units in each zone for environmental monitoring, grass seed ratio, automatic sowing and post-operative care. The triggering module is used to set the environmental parameter thresholds required to trigger automatic reseeding based on the climate and soil characteristics of the grassland type. The mixing module is used to automatically measure, transport, and mix various forages according to a pre-determined combination and proportion of grass seeds to form a mixed grass seed; The path planning module is used to plan an operation path for the automatic seeding equipment based on the facility layout map and terrain data of the photovoltaic power station, which can effectively avoid fixed facilities and adapt to terrain changes. The spreading module is used to monitor environmental parameters in real time. When the threshold is reached, it automatically controls the spreading equipment to move and spread along the planned path, and dynamically adjusts the spreading parameters according to real-time terrain information. The reseeding module is used to periodically monitor key indicators of vegetation recovery after reseeding is completed. If the indicators do not meet the preset standards, the module will automatically make a decision and execute reseeding again.
9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.