A method and device for planning and constructing photovoltaic panels in a photovoltaic power station

Abstract

The application provides a photovoltaic panel planning and construction method and device in a photovoltaic power station, and relates to the technical field of photovoltaic power generation, which comprises the following steps: collecting vegetation growth distribution, analyzing vegetation growth in combination with soil characteristic information to obtain vegetation shielding rate and vegetation maintenance information, and continuously optimizing to obtain an optimal construction area; in the optimal construction area, collecting dust migration distribution, analyzing in combination with a construction angle to obtain a dust shielding rate; collecting meteorological data, combining the construction angle, the dust shielding rate and the vegetation shielding rate to perform power generation prediction and obtain photovoltaic power generation information, and continuously optimizing to obtain an optimal construction angle. Through the application, the technical problem that the existing method often lacks comprehensive consideration of environmental factors in the construction area, resulting in poor precision and rationality of photovoltaic panel layout, can be solved, the scientificity, rationality and precision of photovoltaic panel layout can be improved, the technical target of efficient construction of a photovoltaic power station is achieved, and stable and reliable power generation of the photovoltaic power station is ensured.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power generation technology, and in particular to a method and apparatus for planning and constructing photovoltaic panels in a photovoltaic power station. Background Technology

[0002] A photovoltaic power station is a power generation facility that uses solar panels to directly convert sunlight into electrical energy. It is one of the important forms of renewable energy power generation. A photovoltaic power station converts photons in sunlight into electrical energy by installing photovoltaic panels on a large scale. Then, the direct current is converted into alternating current by inverters and other equipment and connected to the power grid.

[0003] As an important component of clean energy, the scientific planning and design of photovoltaic power plants directly affects power generation efficiency and subsequent maintenance costs. However, traditional planning methods often rely on experience and single geographical information for layout, ignoring complex environmental factors in the region, such as meteorological conditions and vegetation growth. Due to the lack of comprehensive consideration of environmental factors, existing photovoltaic panel planning and construction methods cannot achieve optimal layout, making it difficult to improve power generation efficiency and resulting in high subsequent maintenance costs.

[0004] In summary, existing photovoltaic panel planning and construction methods often lack comprehensive consideration of environmental factors within the construction area, resulting in poor accuracy and rationality in photovoltaic panel layout, and technical problems affecting the power generation efficiency and stability of photovoltaic power plants. Summary of the Invention

[0005] The purpose of this application is to provide a method and apparatus for planning and constructing photovoltaic panels in a photovoltaic power station, in order to solve the technical problem that existing photovoltaic panel planning and construction methods often lack comprehensive consideration of environmental factors in the construction area, resulting in poor accuracy and rationality of photovoltaic panel layout, which affects the power generation efficiency and stability of the photovoltaic power station.

[0006] In view of the above problems, this application provides a method and apparatus for planning and constructing photovoltaic panels in a photovoltaic power station.

[0007] In a first aspect, this application provides a method for planning and constructing photovoltaic panels within a photovoltaic power station, implemented through a device for planning and constructing photovoltaic panels within a photovoltaic power station. The method includes: acquiring the construction area of ​​the photovoltaic power station construction plan; randomly selecting construction areas within the construction area and randomly planning the construction angles of the photovoltaic panels; collecting regional coordinates and soil characteristic information within the construction area; collecting vegetation growth distribution within the construction area; combining the soil characteristic information to perform vegetation growth shading rate analysis and maintainability analysis of the photovoltaic panels, obtaining vegetation shading rate and vegetation maintainability information, and further optimizing the construction area to obtain an optimal construction area; within the optimal construction area, collecting dust migration distribution within the optimal construction area; combining the construction angle to perform dust shading rate analysis of the photovoltaic panels, obtaining a dust shading rate; collecting meteorological data within the construction area; combining the construction angle, dust shading rate, and vegetation shading rate to perform photovoltaic power generation prediction, obtaining photovoltaic power generation information, and further optimizing the construction angle to obtain an optimal construction angle; and continuing to plan and optimize the construction areas and construction angles of other photovoltaic panels within the construction area excluding the optimal construction area, obtaining the planning and construction results.

[0008] Secondly, this application also provides a planning and construction device for photovoltaic panels in a photovoltaic power station, used to execute a planning and construction method for photovoltaic panels in a photovoltaic power station as described in the first aspect, comprising: a construction information selection module, used to obtain the construction area of ​​the photovoltaic power station construction plan, randomly select a construction area within the construction area and randomly plan the construction angle of the photovoltaic panels, and collect regional coordinates and soil characteristic information within the construction area; a construction area optimization module, used to collect vegetation growth distribution within the construction area, combine the soil characteristic information, perform vegetation growth shading rate analysis and maintainability analysis of the photovoltaic panels, obtain vegetation shading rate and vegetation maintainability information, and continue to optimize the construction area to obtain... The system includes: an optimal construction area; a dust shading rate analysis module, used to collect dust migration distribution within the optimal construction area, and analyze the dust shading rate of the photovoltaic panels based on the construction angle to obtain the dust shading rate; a construction angle optimization module, used to collect meteorological data within the construction area, and combine the construction angle, dust shading rate, and vegetation shading rate to predict photovoltaic power generation, obtain photovoltaic power generation information, and continue to optimize the construction angle to obtain the optimal construction angle; and a construction result acquisition module, used to continue to plan and optimize the construction area and construction angle of other photovoltaic panels in the construction area other than the optimal construction area to obtain the planned construction results.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] By analyzing the vegetation shading rate and maintainability of photovoltaic panels based on vegetation growth distribution and soil characteristics in the construction area, information on vegetation shading rate and maintainability is obtained. The construction area is then further optimized to obtain the optimal construction area. Next, dust shading rate analysis of photovoltaic panels is performed based on dust migration distribution and construction angle within the optimal construction area to obtain the dust shading rate. Then, meteorological data within the construction area is collected and combined with construction angle, dust shading rate, and vegetation shading rate to predict photovoltaic power generation, obtaining photovoltaic power generation information. The construction angle is then further optimized to obtain the optimal construction angle. Finally, in areas outside the optimal construction area, the planning and optimization of construction areas and angles for other photovoltaic panels are carried out to obtain multiple optimal construction areas and angles for photovoltaic panels, which are then integrated to obtain the final planning and construction results. This method improves the scientific, rational, and precise layout of photovoltaic panels within the photovoltaic power station, achieving the technical goal of efficient construction of the photovoltaic power station. This enhances the planning and construction quality of photovoltaic panels and ensures the stable, efficient, and reliable power generation of the photovoltaic power station.

[0011] The above description is merely an overview of the technical solution of this application. To better understand the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating a method for planning and constructing photovoltaic panels within a photovoltaic power station, as described in this application.

[0014] Figure 2 This is a schematic diagram illustrating the process of obtaining the dust shading rate in the planning and construction method of photovoltaic panels in a photovoltaic power station according to this application;

[0015] Figure 3 This is a schematic diagram of the structure of a photovoltaic panel planning and construction device in a photovoltaic power station according to this application.

[0016] Explanation of reference numerals in the attached figures:

[0017] The module includes: construction information selection module 11, construction area optimization module 12, dust obstruction rate analysis module 13, construction angle optimization module 14, and construction result acquisition module 15. Detailed Implementation

[0018] This application provides a method and apparatus for planning and constructing photovoltaic panels within a photovoltaic power station. It addresses the technical problem that existing photovoltaic panel planning and construction methods often lack comprehensive consideration of environmental factors within the construction area, resulting in poor accuracy and rationality in photovoltaic panel layout, which affects the power generation efficiency and stability of the photovoltaic power station. This method improves the scientific, rational, and accurate layout of photovoltaic panels within the power station, achieving the technical goal of efficient photovoltaic power station construction. Ultimately, it enhances the quality of photovoltaic panel planning and construction, ensuring stable, efficient, and reliable power generation from the photovoltaic power station.

[0019] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0020] Example 1, please refer to the appendix. Figure 1 This application provides a method for planning and constructing photovoltaic panels in a photovoltaic power station, which is applied to a device for planning and constructing photovoltaic panels in a photovoltaic power station, and specifically includes the following steps:

[0021] Step 1: Obtain the construction area of ​​the photovoltaic power station construction plan, randomly select a construction area within the construction area and randomly plan the construction angle of the photovoltaic panels, and collect the regional coordinates and soil characteristic information within the construction area.

[0022] Specifically, firstly, the construction area of ​​the photovoltaic power station is obtained, i.e., the specific area where the photovoltaic power station will be built, which can be set according to the actual scenario. Next, the size of the area for photovoltaic panel assembly construction is obtained, i.e., the construction dimensions of the photovoltaic panel assembly, which can be set according to the equipment type and specifications. Further, using the size of the photovoltaic panel assembly area as a constraint, any area within the construction area that meets the specified size is randomly selected as the construction area, and the construction angle of the photovoltaic panels is randomly planned. The construction angle of the photovoltaic panels is a key factor affecting their power generation efficiency; the photovoltaic panel angle needs to match the local solar altitude angle and solar trajectory to maximize the reception of sunlight, thus obtaining the construction area and construction angle.

[0023] On the other hand, regional coordinates and soil characteristic information within the construction area are collected, that is, the specific location coordinates of the construction area in the construction region are obtained, and soil characteristic information within the construction area is obtained through soil characteristic survey. The soil characteristic information is used to predict vegetation growth in the subsequent area, including parameters such as soil density, particle size, and water content.

[0024] Step 2: Collect the vegetation growth distribution in the construction area, and combine it with the soil characteristic information to conduct vegetation growth shading rate analysis and maintainability analysis of the photovoltaic panels, obtain vegetation shading rate and vegetation maintainability information, and continue to optimize the construction area to obtain the optimal construction area.

[0025] Specifically, firstly, information on various vegetation types within the construction area is collected, including the types, coverage, and distribution density of different vegetation. For example, low shrubs, herbaceous plants, and tall trees each have different growth heights and morphological characteristics. This information can be obtained through remote sensing technology, drone photography, and ground surveys. Information on growth characteristics helps predict the future growth trend of vegetation and its impact on photovoltaic panels, while information on distribution patterns helps identify which areas are significantly affected by vegetation shading. Then, the information on various vegetation types is integrated to construct a vegetation growth distribution.

[0026] Next, based on the vegetation growth distribution and soil characteristic information, the shading rate and maintainability of the photovoltaic panels are analyzed. First, vegetation growth probability is predicted based on the vegetation growth distribution and soil characteristic information. For example, in suitable soil types, a certain type of vegetation has a higher growth probability; while under unfavorable soil conditions, its growth probability is lower. By analyzing this data, the future growth of different vegetation can be predicted, obtaining multiple vegetation growth probability prediction information. On the other hand, based on the maintenance cycle of the photovoltaic power station, the growth status of various types of vegetation during the maintenance cycle is analyzed, i.e., the maximum shading area. For example, fast-growing vegetation may significantly shade the photovoltaic panels for a period of time, while slower-growing vegetation has less impact, obtaining multiple maximum shading areas for vegetation. Finally, the vegetation shading rate is calculated based on multiple vegetation growth probability predictions and multiple maximum shading areas. Specifically, the shading rate is calculated by weighting the ratio of the maximum shading area to the maintenance cycle for different vegetation types based on the vegetation growth probability predictions. The vegetation shading rate is a key indicator for evaluating the impact of vegetation on photovoltaic panel layout. The higher the shading rate, the lower the power generation efficiency of the photovoltaic panels. Therefore, it is necessary to avoid installing photovoltaic panels in areas with high shading rates.

[0027] On the other hand, multiple maintenance times for various vegetation types are obtained. Weighted calculations are performed based on the ratio of multiple vegetation growth probability predictions, actual maintenance times, and preset maintenance times to obtain vegetation maintainability information. This maintainability information assesses the increased maintenance workload due to different vegetation growth states within a preset maintenance cycle, reflecting the ease or difficulty of maintaining a photovoltaic power station in a given area. Next, regional fitness is calculated based on vegetation shading rate and vegetation maintainability information. For example, regional fitness is obtained by weighted calculation of the reciprocal of vegetation shading rate and vegetation maintainability information. Vegetation shading rate and maintainability information are negatively correlated with regional fitness; that is, the higher the shading rate and maintainability, the lower the regional fitness. A higher regional fitness indicates that the vegetation in the area has less impact on photovoltaic panel construction and lower maintenance difficulty.

[0028] Finally, using the same method, fitness calculations were performed on other construction areas within the established construction region. The fitness of different areas was compared, and the area with the highest fitness was selected as the optimal construction area. This optimal construction area has a low vegetation shading rate and high maintainability, making it suitable for installing photovoltaic panels. By optimizing the construction area based on vegetation shading rate and maintainability information, the optimal construction area can be determined, reducing the impact of vegetation shading on photovoltaic panels and the workload of subsequent maintenance, thereby ensuring the long-term stable operation and efficient power generation of the photovoltaic power station.

[0029] Step 3: Within the optimal construction area, collect the dust migration distribution within the optimal construction area, and combine it with the construction angle to analyze the dust shading rate of the photovoltaic panels and obtain the dust shading rate.

[0030] Specifically, firstly, the dust migration direction and dust migration concentration within the optimal construction area are collected. The dust migration direction can be obtained through analysis of meteorological data, wind direction, and geographical environment. Dust moves with airflow, and wind direction and terrain in a specific area can accelerate or slow down dust accumulation. The dust migration concentration can be collected through air quality monitoring equipment, dust sensors, etc. In areas with higher dust concentrations, dust is more likely to accumulate on the surface of photovoltaic panels, leading to shading of sunlight and reduced power generation efficiency. Then, based on the dust migration direction and dust migration concentration, the dust migration distribution within the optimal construction area is constructed.

[0031] Then, the dust shading rate of the photovoltaic panel is analyzed based on the dust migration distribution and the installation angle. The installation angle of the photovoltaic panel affects dust accumulation; a steeper angle helps some dust to slide off automatically, while a flatter angle causes more dust to accumulate on the photovoltaic panel surface. First, the shading area caused by dust accumulation on the photovoltaic panel surface within a preset maintenance cycle is calculated based on the dust migration distribution and the installation angle. Then, the dust shading rate is calculated based on the ratio of the dust shading area to the maintenance time cycle. The dust shading rate is a key indicator for evaluating the power generation efficiency of the photovoltaic panel. A higher dust shading rate means that the photovoltaic panel surface is more prone to dust accumulation, thereby reducing the amount of sunlight received and lowering the power generation efficiency. By analyzing the dust shading rate of the photovoltaic panel based on the dust migration distribution and the installation angle, the impact of dust on the power generation efficiency of the photovoltaic panel under different installation angles can be quantified, and a basis for subsequent photovoltaic power generation prediction can be provided.

[0032] Step 4: Collect meteorological data in the construction area, combine it with the construction angle, dust shading rate and vegetation shading rate to predict photovoltaic power generation, obtain photovoltaic power generation information, and continue to optimize the construction angle to obtain the optimal construction angle.

[0033] Specifically, firstly, meteorological data is collected within the construction area, including sunlight parameters (sunshine duration, solar radiation intensity, ratio of direct to diffused light, etc.). Next, photovoltaic power generation is predicted based on the meteorological data, construction angle, dust shading rate, and vegetation shading rate. For example, a backpropagation (BP) neural network can be used to construct a power generation prediction model. This model is an iteratively optimized neural network model in machine learning, obtained through supervised training using collected sample data. The input data for the power generation prediction model includes meteorological data, construction angle, dust shading rate, and vegetation shading rate; the output data is photovoltaic power generation information, i.e., the photovoltaic power generation amount. Then, the trained power generation prediction model is used to predict the photovoltaic power generation information within the construction area based on the meteorological data, construction angle, dust shading rate, and vegetation shading rate, outputting the predicted photovoltaic power generation amount.

[0034] Next, the installation angle is randomly adjusted, specifically by randomly selecting another installation angle as the second installation angle. Dust shading rate analysis is performed based on this second installation angle, and photovoltaic power generation information is predicted using the analysis results to obtain the second photovoltaic power generation information. Then, the installation angle is further adjusted, and multiple photovoltaic power generation information (i.e., multiple photovoltaic power generation values) are predicted for multiple installation angles. Finally, the installation angle corresponding to the maximum photovoltaic power generation is selected as the optimal installation angle, thus obtaining the optimal installation angle. By randomly adjusting the installation angle and combining the prediction of dust shading rate and photovoltaic power generation information, the installation angle of the photovoltaic panels is gradually optimized, ultimately obtaining the optimal angle with the maximum power generation. This ensures that the photovoltaic panels operate under optimal conditions, maximizing power generation efficiency while reducing the impact of dust and vegetation on power generation performance, and improving the accuracy of the optimal installation angle setting.

[0035] Step 5: In the areas of the construction region other than the optimal construction area, continue to plan and optimize the construction areas and angles of other photovoltaic panels to obtain the planning and construction results.

[0036] Specifically, using the same method described above for obtaining the optimal construction area and optimal construction angle, the construction areas and angles of other photovoltaic panels are further optimized within the construction area excluding the optimal construction area, resulting in multiple optimal construction areas and angles for multiple photovoltaic panels. Finally, the optimal construction area and angle of each photovoltaic panel are combined to form an overall photovoltaic power station planning scheme, i.e., the planning and construction result. This result covers the optimal construction areas and angles of all photovoltaic panels within the entire photovoltaic power station construction area. By obtaining the planning and construction result, it can be ensured that the photovoltaic panels in different areas of the entire power station can maximize the utilization of solar resources, while reducing dust, vegetation obstruction, and maintenance difficulties.

[0037] The aforementioned method for planning and constructing photovoltaic panels within a photovoltaic power station is applied to a photovoltaic panel planning and construction device within a photovoltaic power station. It can solve the technical problem that existing photovoltaic panel planning and construction methods often lack comprehensive consideration of environmental factors within the construction area, resulting in poor accuracy and rationality of photovoltaic panel layout, which affects the power generation efficiency and stability of the photovoltaic power station. By analyzing the vegetation shading rate and maintainability of photovoltaic panels based on vegetation growth distribution and soil characteristics in the construction area, information on vegetation shading rate and maintainability is obtained. The construction area is then further optimized to obtain the optimal construction area. Next, dust shading rate analysis of photovoltaic panels is performed based on dust migration distribution and construction angle within the optimal construction area to obtain the dust shading rate. Then, meteorological data within the construction area is collected and combined with construction angle, dust shading rate, and vegetation shading rate to predict photovoltaic power generation, obtaining photovoltaic power generation information. The construction angle is then further optimized to obtain the optimal construction angle. Finally, in areas outside the optimal construction area, the planning and optimization of construction areas and angles for other photovoltaic panels are carried out to obtain multiple optimal construction areas and angles for photovoltaic panels, which are then integrated to obtain the final planning and construction results. This method improves the scientific, rational, and precise layout of photovoltaic panels within the photovoltaic power station, achieving the technical goal of efficient construction of the photovoltaic power station. This enhances the planning and construction quality of photovoltaic panels and ensures the stable, efficient, and reliable power generation of the photovoltaic power station.

[0038] Furthermore, the application includes obtaining the construction area of ​​the photovoltaic power station construction plan, randomly selecting construction areas within the construction area and randomly planning the construction angle of the photovoltaic panels, and collecting regional coordinates and soil characteristic information within the construction area.

[0039] Obtain the construction area of ​​the photovoltaic power station construction plan; randomly select a construction area within the construction area according to the size of the photovoltaic panel module construction area, and randomly set the construction angle; collect the regional coordinates within the construction area, and extract the soil characteristic information within the construction area based on the soil characteristic survey data of the construction area.

[0040] Specifically, firstly, the construction area for the photovoltaic power station is determined. This involves comprehensively considering factors such as solar resources, geographical location, and land availability to identify suitable areas for photovoltaic power station construction, which can be set according to the actual scenario. Next, the area size for photovoltaic panel module construction is determined, i.e., the coverage area of ​​a single photovoltaic panel module, which can be set according to the actual type and specifications of the photovoltaic panel modules. Further, based on the area size for photovoltaic panel module construction, any area within the designated construction area that meets the size requirement is randomly selected as the construction area. The construction angle of the photovoltaic panels is then randomly planned, including the tilt angle (the angle relative to the horizontal plane) and the azimuth angle (the angle relative to due south).

[0041] After determining the photovoltaic panel construction area, the regional coordinates within the construction area are collected. Based on these coordinates, soil characteristic information within the construction area is extracted using soil characteristic survey data. This soil characteristic survey data can be obtained through on-site surveys or existing geological data. Soil characteristic information includes parameters such as soil density, particle size, and moisture content. Obtaining this soil characteristic information supports subsequent vegetation growth analysis.

[0042] Furthermore, by collecting data on vegetation growth distribution within the construction area and combining this data with soil characteristic information, an analysis of the vegetation shading rate and maintainability of the photovoltaic panels is conducted. This application includes:

[0043] Multiple vegetation types within the construction area are collected to construct a vegetation growth distribution. Based on the soil characteristic information and the vegetation growth distribution, the growth probability of the multiple vegetation types is analyzed to obtain multiple growth probability information. Within a preset maintenance time period for the photovoltaic power station, multiple maximum shading areas of the multiple vegetation types that grow and shade the photovoltaic panels are obtained. Based on the multiple growth probability information, the ratios of the multiple maximum shading areas to the maintenance time period are weighted and calculated to obtain the vegetation shading rate. Multiple maintenance times for the multiple vegetation types are obtained, and the ratios of the multiple maintenance times to the preset maintenance time are weighted and calculated using the multiple growth probability information to obtain vegetation maintainability information. Based on the vegetation shading rate and vegetation maintainability information, regional fitness is calculated, where the magnitude of the vegetation shading rate and vegetation maintainability information is negatively correlated with the magnitude of regional fitness. The construction area is further optimized within the construction area, and the construction area with the highest regional fitness is output to obtain the optimal construction area.

[0044] Specifically, firstly, multiple vegetation categories within the construction area are collected. Different vegetation categories have different growth characteristics. For example, low shrubs, herbaceous plants, and tall trees each have different growth heights and morphological characteristics. This information can be obtained through remote sensing technology, drone photography, ground surveys, and other methods. The information on growth characteristics helps predict the future growth trend of vegetation and its impact on photovoltaic panels, while the information on distribution patterns helps identify which areas are more affected by vegetation shading. Then, the multiple vegetation categories and information are integrated to construct the vegetation growth distribution.

[0045] Next, based on the soil characteristic information and the vegetation growth distribution, the growth probability of the various vegetation types is analyzed. For example, a vegetation growth prediction model can be constructed based on machine learning, and the growth probability analysis can be performed using the vegetation growth prediction model to obtain multiple growth probability information. Then, the preset maintenance time period of the photovoltaic power station is obtained, where the maintenance time period can be set according to actual needs, such as two weeks, one month, etc.; furthermore, the maximum shading area of ​​the various vegetation types growing and shading the photovoltaic panels within the preset maintenance time period of the photovoltaic power station is obtained, where the maximum shading area can be calculated by averaging the historical growth data of different vegetation types.

[0046] Then, using growth probability information as weights, for example, the ratio of each growth probability information to the sum of multiple growth probability information as weights, the ratio of the multiple maximum shading areas to the maintenance time period is weighted based on the multiple growth probability information, and the weighted calculation result is used as the vegetation shading rate to obtain the vegetation shading rate. The vegetation shading rate is a key indicator for evaluating the impact of vegetation on photovoltaic panel layout. The higher the shading rate, the lower the power generation efficiency of the photovoltaic panel. Further, multiple maintenance times for the various vegetation categories are obtained, with each vegetation type having a different maintenance time that can be set according to the actual vegetation type. Using growth probability information as weight, the ratio of the multiple maintenance times to the preset maintenance time is weighted and calculated. The weighted calculation result is used as vegetation maintainability information, which assesses the increased maintenance workload due to the growth status of different vegetation types within a preset maintenance cycle. This information reflects the ease or difficulty of maintaining the photovoltaic power station in a certain area. Higher maintainability information indicates that the vegetation in that area requires more maintenance, increasing the maintenance cost and difficulty of the power station.

[0047] For example, if the ratio of growth probability information to the sum of multiple growth probability information is 0.1, and the maximum shading area of ​​a certain vegetation type is 2 square meters with a maintenance period of 2 weeks, then the vegetation shading rate of this vegetation type is 0.1 × (2 / 2) = 0.1. Thus, the vegetation shading rate of multiple vegetation types can be obtained by weighted calculation and summation, for example, 0.9.

[0048] For example, the ratio of each growth probability information to the sum of multiple growth probability information is used as a weight to calculate the weighted ratio of the multiple maintenance times to the preset maintenance time, which is then used as vegetation maintenance information. For instance, if the cleaning and maintenance time for a certain vegetation type is 1 hour, and the preset maintenance time is the average time of cleaning and maintenance for multiple groups of plants, which is 2 hours, then the maintenance information corresponding to that vegetation type can be 0.1 × (1 / 2) = 0.05. The weighted calculation and summation of all vegetation maintenance information yields the final vegetation maintenance information within the construction area, for example, 0.85.

[0049] Based on the impact of vegetation shading rate and vegetation maintenance information on photovoltaic power generation, the vegetation shading rate and vegetation maintenance information are weighted, with a higher weight corresponding to a greater impact. For example, the weights of vegetation shading rate and vegetation maintenance information are 0.7 and 0.3, respectively. Further, the vegetation shading rate and vegetation maintenance information are weighted and calculated. For example, the regional fitness is obtained by calculating the reciprocals of the vegetation shading rate and vegetation maintenance information. The magnitude of vegetation shading rate and vegetation maintenance information is negatively correlated with the magnitude of regional fitness; that is, the higher the vegetation shading rate and vegetation maintenance information, the lower the regional fitness. A higher regional fitness indicates that the vegetation in the region has a smaller impact on photovoltaic panel construction and is easier to maintain.

[0050] For example, the difference between 1 minus the vegetation shading rate and the difference between 1 minus the vegetation maintenance information is calculated using weighted average of vegetation shading rate and vegetation maintenance information, and is used as the regional fitness. For example, 0.7×(1-0.9)+0.3×(1-0.85)=0.115, which is the regional fitness.

[0051] Finally, using the same method for calculating the fitness of different construction areas, fitness calculations were performed on other construction areas within the original construction region. The fitness of different areas was compared, and the area with the highest fitness was selected as the optimal construction area. This optimal construction area has a low vegetation shading rate and high maintainability, making it suitable for installing photovoltaic panels. By determining the optimal construction area, the impact of vegetation shading on photovoltaic panels and the workload of subsequent maintenance can be reduced, thereby ensuring the long-term stable operation and efficient power generation of the photovoltaic power station.

[0052] Furthermore, based on the soil characteristic information and the vegetation growth distribution, the growth probability of the multiple vegetation categories is analyzed to obtain multiple growth probability information. This application also includes the following steps:

[0053] Based on historical growth monitoring data of the various vegetation categories within the vegetation growth distribution, multiple sets of soil characteristic information and multiple sets of growth probability information are obtained. Using the multiple sets of soil characteristic information and multiple sets of growth probability information, multiple vegetation growth analysis branches are trained to obtain a vegetation growth analyzer. The vegetation growth analyzer is used to analyze the soil characteristic information to obtain multiple growth probability information.

[0054] Specifically, firstly, feature extraction is performed based on historical growth monitoring data of multiple vegetation categories within the vegetation growth distribution to obtain multiple sets of sample soil feature information and multiple sets of sample growth probability information, where each set of sample soil feature information and sample growth probability information corresponds one-to-one. Next, multiple vegetation growth analysis branches are constructed based on machine learning, with one branch corresponding to each vegetation category. For example, a backpropagation (BP) neural network can be used to construct the vegetation growth analysis branches, which include an input layer, multiple hidden layers, and an output layer. The input data for the input layer is soil feature information, and the output data for the output layer is growth probability. Then, the multiple sets of sample soil feature information and multiple sets of sample growth probability information are used to supervise the training of the multiple vegetation growth analysis branches. A loss function and backpropagation algorithm can be used for supervised training to obtain the trained multiple vegetation growth analysis branches. Finally, a vegetation growth analyzer is constructed by fusing these multiple vegetation growth analysis branches.

[0055] Finally, the soil characteristic information is input into the vegetation growth analyzer for analysis, and multiple growth probability information is output. By constructing a vegetation growth analyzer based on machine learning to perform vegetation growth probability analysis, the accuracy and efficiency of vegetation growth probability prediction can be improved.

[0056] Furthermore, such as Figure 2 As shown, within the optimal construction area, dust migration distribution within the optimal construction area is collected. Combined with the construction angle, dust shading rate analysis of the photovoltaic panels is performed to obtain the dust shading rate. This application includes:

[0057] The dust migration direction and dust migration concentration within the optimal construction area are collected to obtain the dust migration distribution; based on the dust migration distribution and the construction angle, the dust shading area within the preset maintenance time period of the photovoltaic power station is predicted; the dust shading rate is calculated based on the ratio of the dust shading area to the maintenance time period.

[0058] Specifically, firstly, the dust migration direction and dust migration concentration within the optimal construction area are collected. The dust migration direction can be determined through analysis of meteorological data, wind direction, and geographical environment. Dust moves with airflow, and wind direction and terrain within a specific area can accelerate or slow down dust accumulation. For example, the most frequent wind direction within the optimal construction area can be used as the dust migration direction. The dust migration concentration can be collected through air quality monitoring equipment, dust sensors, etc. Areas with higher dust concentrations are more prone to dust accumulation on the surface of photovoltaic panels, leading to shading of sunlight and reduced power generation efficiency. For example, the average dust concentration in the optimal construction area over the past month can be obtained as the dust migration concentration. Then, based on the dust migration direction and dust migration concentration, a dust migration distribution within the optimal construction area is constructed.

[0059] Then, based on the dust migration distribution and construction angle, the dust shading area within the preset maintenance time period of the photovoltaic power station is predicted to obtain the dust shading area. The construction angle of the photovoltaic panel affects dust accumulation; a steeper angle helps some dust to slide off automatically, while a flatter angle causes more dust to accumulate on the photovoltaic panel surface. For example, a simulation model can be constructed for prediction. By analyzing the dust migration distribution and the construction angle of the photovoltaic panel, the dust accumulation on the photovoltaic panel surface within the maintenance period can be predicted. Based on information such as dust migration path and wind speed, the shading area formed by dust on the photovoltaic panel surface at a specific construction angle can be estimated. Optionally, machine learning methods can also be used. A set of sample dust migration distributions and sample construction angles can be collected as input data, and the dust shading area after the maintenance time period under different sample dust migration distributions and sample construction angles can be collected as a sample dust shading area set for supervised training. Using algorithms such as gradient descent in existing technologies, a dust shading analyzer can be trained to predict the dust shading area based on the current dust migration distribution and construction angle input. For example, 1 square meter.

[0060] Finally, the dust shading rate is calculated based on the ratio of the dust-covered area to the maintenance time cycle. The dust shading rate is a key indicator for evaluating the power generation efficiency of photovoltaic panels. A higher dust shading rate means that dust accumulates more easily on the surface of the photovoltaic panel, thus reducing the amount of sunlight received and lowering power generation efficiency. By analyzing the dust shading rate of photovoltaic panels based on dust migration distribution and the installation angle of the photovoltaic panel, the impact of dust on the power generation efficiency of photovoltaic panels under different installation angles can be quantified, providing a basis for subsequent photovoltaic power generation prediction.

[0061] Furthermore, meteorological data within the construction area is collected, and combined with the construction angle, dust obstruction rate, and vegetation obstruction rate, photovoltaic power generation prediction is performed to obtain photovoltaic power generation information. This application includes:

[0062] Light parameters within the construction area are collected as meteorological data. Sample meteorological data sets, sample construction angle sets, sample dust shading rate sets, and sample vegetation shading rate sets are collected and labeled to obtain sample photovoltaic power generation information sets. A photovoltaic power generation predictor is trained using the sample meteorological data sets, sample construction angle sets, sample dust shading rate sets, sample vegetation shading rate sets, and sample photovoltaic power generation information sets. The trained photovoltaic power generation predictor is used to perform photovoltaic power generation prediction inputs based on the meteorological data, construction angle, dust shading rate, and vegetation shading rate, and outputs photovoltaic power generation information.

[0063] Specifically, firstly, illumination parameters within the construction area are collected as meteorological data, including sunshine duration, solar radiation intensity, and the ratio of direct to diffused light. Next, based on big data, information retrieval is conducted guided by photovoltaic power generation to obtain sample meteorological data sets, sample construction angle sets, sample dust shading rate sets, and sample vegetation shading rate sets. Then, sample photovoltaic power generation information sets are collected and labeled to obtain sample photovoltaic power generation information, where the sample photovoltaic power generation information corresponds to the sample meteorological data, sample construction angle, sample dust shading rate, and sample vegetation shading rate.

[0064] Next, a photovoltaic (PV) power generation predictor is constructed based on a backpropagation (BP) neural network. This predictor is a neural network model in machine learning that can be iteratively optimized, including an input layer, hidden layers, and an output layer, used to predict PV power generation. Then, using sample meteorological data, sample construction angles, sample dust occlusion rates, and sample vegetation occlusion rates as inputs, and sample PV power generation information as supervision, the PV power generation predictor is trained using the same set of sample meteorological data, sample construction angles, sample dust occlusion rates, sample vegetation occlusion rates, and sample PV power generation information as training data. This involves continuously adjusting the network weights through forward and backward propagation processes to minimize the error between the output and the target value, resulting in a PV power generation predictor that meets the convergence criteria. Finally, the meteorological data, construction angle, dust occlusion rate, and vegetation occlusion rate are input into the trained PV power generation predictor, which outputs PV power generation information, for example, 1000W.

[0065] By constructing a photovoltaic power generation predictor based on a BP neural network, the prediction time can be reduced, and the prediction accuracy and efficiency can be improved, thereby enhancing the accuracy and reliability of the evaluation from the perspective of photovoltaic panel construction.

[0066] Furthermore, the construction angle will be further optimized to obtain the optimal construction angle. This application includes:

[0067] The construction angle is randomly adjusted, and the dust shading rate and photovoltaic power generation information are analyzed and predicted. The construction angle is further adjusted and optimized to output the construction angle with the maximum photovoltaic power generation information, thus obtaining the optimal construction angle.

[0068] Specifically, the construction angle is randomly adjusted, i.e., another construction angle is randomly selected as the second construction angle, which is different from the original construction angle. Then, dust shading rate analysis is performed based on the second construction angle, and photovoltaic power generation information is predicted in combination with the second dust shading rate to obtain the second photovoltaic power generation information, for example, 1200W. Then, the construction angle is randomly adjusted again, and multiple photovoltaic power generation information is predicted for multiple construction angles, i.e., multiple photovoltaic power generation values. Finally, the multiple photovoltaic power generation values ​​are compared, and the construction angle corresponding to the maximum photovoltaic power generation value is selected as the optimal construction angle to obtain the optimal construction angle.

[0069] By randomly adjusting the installation angle and combining the prediction of dust shading rate and photovoltaic power generation information, the installation angle of the photovoltaic panels is gradually optimized, and the optimal angle with the maximum power generation is finally obtained. This ensures that the photovoltaic panels operate under optimal conditions, maximizes power generation efficiency, reduces the impact of dust and vegetation on power generation performance, and improves the accuracy of the optimal installation angle setting.

[0070] In summary, the planning and construction method for photovoltaic panels in a photovoltaic power station provided in this application has the following technical effects:

[0071] By analyzing the vegetation shading rate and maintainability of photovoltaic panels based on vegetation growth distribution and soil characteristics in the construction area, information on vegetation shading rate and maintainability is obtained. The construction area is then further optimized to obtain the optimal construction area. Next, dust shading rate analysis of photovoltaic panels is performed based on dust migration distribution and construction angle within the optimal construction area to obtain the dust shading rate. Then, meteorological data within the construction area is collected and combined with construction angle, dust shading rate, and vegetation shading rate to predict photovoltaic power generation, obtaining photovoltaic power generation information. The construction angle is then further optimized to obtain the optimal construction angle. Finally, in areas outside the optimal construction area, the planning and optimization of construction areas and angles for other photovoltaic panels are carried out to obtain multiple optimal construction areas and angles for photovoltaic panels, which are then integrated to obtain the final planning and construction results. This method improves the scientific, rational, and precise layout of photovoltaic panels within the photovoltaic power station, achieving the technical goal of efficient construction of the photovoltaic power station. This enhances the planning and construction quality of photovoltaic panels and ensures the stable, efficient, and reliable power generation of the photovoltaic power station.

[0072] Example 2: Based on the same inventive concept as the planning and construction method of photovoltaic panels in a photovoltaic power station described in the previous examples, this application also provides a planning and construction device for photovoltaic panels in a photovoltaic power station. Please refer to the appendix. Figure 3 ,include:

[0073] The construction information selection module 11 is used to obtain the construction area of ​​the photovoltaic power station construction plan, randomly select a construction area within the construction area and randomly plan the construction angle of the photovoltaic panels, and collect the regional coordinates and soil characteristic information within the construction area; the construction area optimization module 12 is used to collect the vegetation growth distribution within the construction area, combine it with the soil characteristic information, perform vegetation growth shading rate analysis and maintainability analysis of the photovoltaic panels, obtain vegetation shading rate and vegetation maintainability information, and continue to optimize the construction area to obtain the optimal construction area; the dust shading rate analysis module 13 is used within the optimal construction area The system collects dust migration distribution within the optimal construction area and analyzes the dust shading rate of the photovoltaic panels based on the construction angle to obtain the dust shading rate. The construction angle optimization module 14 collects meteorological data within the construction area and, based on the construction angle, dust shading rate, and vegetation shading rate, performs photovoltaic power generation prediction to obtain photovoltaic power generation information and continues to optimize the construction angle to obtain the optimal construction angle. The construction result acquisition module 15 continues to plan and optimize the construction area and construction angle of other photovoltaic panels in the construction area other than the optimal construction area to obtain the planning construction results.

[0074] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0075] Obtain the construction area of ​​the photovoltaic power station construction plan; randomly select a construction area within the construction area according to the size of the photovoltaic panel module construction area, and randomly set the construction angle; collect the regional coordinates within the construction area, and extract the soil characteristic information within the construction area based on the soil characteristic survey data of the construction area.

[0076] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0077] Multiple vegetation types within the construction area are collected to construct a vegetation growth distribution. Based on the soil characteristic information and the vegetation growth distribution, the growth probability of the multiple vegetation types is analyzed to obtain multiple growth probability information. Within a preset maintenance time period for the photovoltaic power station, multiple maximum shading areas of the multiple vegetation types that grow and shade the photovoltaic panels are obtained. Based on the multiple growth probability information, the ratios of the multiple maximum shading areas to the maintenance time period are weighted and calculated to obtain the vegetation shading rate. Multiple maintenance times for the multiple vegetation types are obtained, and the ratios of the multiple maintenance times to the preset maintenance time are weighted and calculated using the multiple growth probability information to obtain vegetation maintainability information. Based on the vegetation shading rate and vegetation maintainability information, regional fitness is calculated, where the magnitude of the vegetation shading rate and vegetation maintainability information is negatively correlated with the magnitude of regional fitness. The construction area is further optimized within the construction area, and the construction area with the highest regional fitness is output to obtain the optimal construction area.

[0078] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0079] Based on historical growth monitoring data of the various vegetation categories within the vegetation growth distribution, multiple sets of soil characteristic information and multiple sets of growth probability information are obtained. Using the multiple sets of soil characteristic information and multiple sets of growth probability information, multiple vegetation growth analysis branches are trained to obtain a vegetation growth analyzer. The vegetation growth analyzer is used to analyze the soil characteristic information to obtain multiple growth probability information.

[0080] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0081] The dust migration direction and dust migration concentration within the optimal construction area are collected to obtain the dust migration distribution; based on the dust migration distribution and the construction angle, the dust shading area within the preset maintenance time period of the photovoltaic power station is predicted; the dust shading rate is calculated based on the ratio of the dust shading area to the maintenance time period.

[0082] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0083] Light parameters within the construction area are collected as meteorological data. Sample meteorological data sets, sample construction angle sets, sample dust shading rate sets, and sample vegetation shading rate sets are collected and labeled to obtain sample photovoltaic power generation information sets. A photovoltaic power generation predictor is trained using the sample meteorological data sets, sample construction angle sets, sample dust shading rate sets, sample vegetation shading rate sets, and sample photovoltaic power generation information sets. The trained photovoltaic power generation predictor is used to perform photovoltaic power generation prediction inputs based on the meteorological data, construction angle, dust shading rate, and vegetation shading rate, and outputs photovoltaic power generation information.

[0084] Furthermore, the aforementioned planning and construction device for photovoltaic panels within a photovoltaic power station is also used for:

[0085] The construction angle is randomly adjusted, and the dust shading rate and photovoltaic power generation information are analyzed and predicted. The construction angle is further adjusted and optimized to output the construction angle with the maximum photovoltaic power generation information, thus obtaining the optimal construction angle.

[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. The planning and construction method and specific examples of photovoltaic panels in a photovoltaic power station described in Embodiment 1 above are also applicable to the planning and construction device of photovoltaic panels in a photovoltaic power station in this embodiment. Through the foregoing detailed description of the planning and construction method of photovoltaic panels in a photovoltaic power station, those skilled in the art can clearly understand the planning and construction device of photovoltaic panels in a photovoltaic power station in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here. As for the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and relevant parts can be referred to in the method section.

[0087] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0088] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for planning and constructing photovoltaic panels within a photovoltaic power station, characterized in that, The methods include: The construction area of ​​the photovoltaic power station construction plan is obtained, and a construction area is randomly selected within the construction area and the construction angle of the photovoltaic panels is randomly planned. The regional coordinates and soil characteristic information of the construction area are collected. The vegetation growth distribution within the construction area is collected, and combined with the soil characteristic information, vegetation shading rate and maintainability analysis of the photovoltaic panels are performed to obtain vegetation shading rate and vegetation maintainability information. The construction area is then further optimized to obtain the optimal construction area, including: Collect multiple vegetation types within the construction area to construct a vegetation growth distribution; Based on the soil characteristic information and the vegetation growth distribution, the growth probability of the multiple vegetation categories is analyzed to obtain multiple growth probability information. Within a preset maintenance period of the photovoltaic power station, obtain the maximum shading area of ​​the photovoltaic panels caused by the growth of the various vegetation types. Based on the multiple growth probability information, the ratios of the multiple maximum shading areas and the maintenance time period are weighted and calculated to obtain the vegetation shading rate. Multiple maintenance times for the various vegetation types are obtained, and the ratios of the multiple maintenance times to the preset maintenance time are weighted using the multiple growth probability information to obtain vegetation maintenance information. The regional fitness is calculated based on the vegetation shading rate and vegetation maintenance information, wherein the magnitude of the vegetation shading rate and vegetation maintenance information is negatively correlated with the magnitude of the regional fitness. Continue to optimize the construction area within the construction region, output the construction area with the highest regional adaptability, and obtain the optimal construction area; Within the optimal construction area, the dust migration distribution within the optimal construction area is collected, and combined with the construction angle, the dust shading rate of the photovoltaic panels is analyzed to obtain the dust shading rate. Meteorological data within the construction area is collected, and combined with the construction angle, dust obstruction rate, and vegetation obstruction rate, photovoltaic power generation is predicted to obtain photovoltaic power generation information. The construction angle is then further optimized to obtain the optimal construction angle. In the construction area excluding the optimal construction area, continue to plan and optimize the construction areas and angles of other photovoltaic panels to obtain the planning and construction results.

2. The method for planning and constructing photovoltaic panels within a photovoltaic power station according to claim 1, characterized in that, The construction area of ​​the photovoltaic power station construction plan is obtained. Within the construction area, a construction zone is randomly selected and the construction angle of the photovoltaic panels is randomly planned. Regional coordinates and soil characteristic information within the construction area are collected, including: Obtain the construction area of ​​the photovoltaic power plant construction plan; Based on the size of the area where the photovoltaic panel modules are to be constructed, a construction area is randomly selected within the construction area, and the construction angle is randomly set. Collect the regional coordinates within the construction area, and extract soil characteristic information within the construction area based on the soil characteristic survey data of the construction area.

3. The method for planning and constructing photovoltaic panels within a photovoltaic power station according to claim 1, characterized in that, Based on the soil characteristic information and the vegetation growth distribution, the growth probability of the multiple vegetation categories is analyzed to obtain multiple growth probability information, including: Based on the historical growth monitoring data of the multiple vegetation categories within the vegetation growth distribution, obtain multiple sets of soil characteristic information and multiple sets of growth probability information for samples; Using the multiple sets of soil feature information and multiple sets of growth probability information of the samples, multiple vegetation growth analysis branches are trained to obtain a vegetation growth analyzer. The vegetation growth analyzer is used to analyze the soil characteristic information to obtain multiple growth probability information.

4. The method for planning and constructing photovoltaic panels within a photovoltaic power station according to claim 1, characterized in that, Within the optimal construction area, dust migration distribution within the optimal construction area is collected. Combined with the construction angle, dust shading rate analysis of the photovoltaic panels is performed to obtain the dust shading rate, including: The dust migration direction and dust migration concentration within the optimal construction area are collected to obtain the dust migration distribution; Based on the dust migration distribution and the construction angle, the dust shading area within the preset maintenance period of the photovoltaic power station is predicted. The dust blocking rate is calculated based on the ratio of the dust blocking area to the maintenance time cycle.

5. The method for planning and constructing photovoltaic panels within a photovoltaic power station according to claim 1, characterized in that, Meteorological data within the construction area is collected, and combined with the construction angle, dust obstruction rate, and vegetation obstruction rate, photovoltaic power generation prediction is performed to obtain photovoltaic power generation information, including: Collect sunlight parameters within the construction area as meteorological data; Collect sample meteorological data sets, sample construction angle sets, sample dust occlusion rate sets, and sample vegetation occlusion rate sets, and collect and label them to obtain sample photovoltaic power generation information sets; A photovoltaic power generation predictor is trained using the aforementioned set of meteorological data, set of construction angles, set of dust occlusion rates, set of vegetation occlusion rates, and set of photovoltaic power generation information. Using the trained photovoltaic power generation predictor, the photovoltaic power generation prediction input is obtained by taking the meteorological data, construction angle, dust shading rate and vegetation shading rate as the input, and the output is obtained as photovoltaic power generation information.

6. The method for planning and constructing photovoltaic panels within a photovoltaic power station according to claim 1, characterized in that, Continue to optimize the construction angle to obtain the optimal construction angle, including: The construction angle is randomly adjusted, and the dust shading rate and photovoltaic power generation information are analyzed and predicted. Continue to adjust and optimize the construction angle to find the construction angle that maximizes the output of photovoltaic power generation information, thus obtaining the optimal construction angle.

7. A planning and construction device for photovoltaic panels in a photovoltaic power station, characterized in that, The steps for implementing the planning and construction method of photovoltaic panels in a photovoltaic power station according to any one of claims 1 to 6 include: The construction information selection module is used to obtain the construction area of ​​the photovoltaic power station construction plan, randomly select a construction area within the construction area and randomly plan the construction angle of the photovoltaic panels, and collect the regional coordinates and soil characteristic information within the construction area; The construction area optimization module is used to collect the vegetation growth distribution in the construction area, combine it with the soil characteristic information, perform vegetation growth shading rate analysis and maintainability analysis of photovoltaic panels, obtain vegetation shading rate and vegetation maintainability information, and continue to optimize the construction area to obtain the optimal construction area. The dust shading rate analysis module is used to collect the dust migration distribution within the optimal construction area, and combine it with the construction angle to analyze the dust shading rate of the photovoltaic panel and obtain the dust shading rate. The construction angle optimization module is used to collect meteorological data in the construction area, combine the construction angle, dust shading rate and vegetation shading rate to predict photovoltaic power generation, obtain photovoltaic power generation information, and continue to optimize the construction angle to obtain the optimal construction angle. The construction result acquisition module is used to continue to plan and optimize the construction area and construction angle of other photovoltaic panels in the construction area other than the optimal construction area, and obtain the planning and construction results.

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