Construction System and Method for Complex Mountainous Photovoltaic Projects Based on 3D Modeling

Abstract

This invention provides a construction system and method for complex mountain photovoltaic systems based on 3D modeling, relating to the field of photovoltaic power generation technology. The invention scans the target area to generate a digital elevation model and obtains the mechanical parameters of the soil and rock mass, constructing a 3D geological model containing surface and subsurface information. Within the model, feasible installation areas are selected based on slope conditions. Furthermore, suitability indices for each support point are calculated based on bearing capacity, settlement uniformity, and slope stability scores, allowing for the selection and optimization of usable points. The optimal installation scheme is selected by evaluating the geometric stability of the point combination, and installation priorities are dynamically determined based on stability and installation spacing, achieving safe and efficient photovoltaic system layout and construction.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation technology, specifically to a construction system and method for complex mountain photovoltaic systems based on three-dimensional modeling. Background Technology

[0002] With the increasingly widespread application of photovoltaic (PV) power generation technology in complex mountainous environments, traditional PV system site selection and construction methods have revealed significant shortcomings when facing mountainous terrain with large undulations and complex geological conditions. Existing methods largely rely on two-dimensional maps and manual experience, making it difficult to accurately assess key factors such as surface slope, soil and rock mechanical properties, and slope stability. This leads to frequent problems such as unreasonable site selection, insufficient bearing capacity of support foundations, and uneven settlement, seriously affecting the safety and power generation efficiency of PV systems. Especially in areas prone to geological disasters, the lack of scientific and systematic three-dimensional geological modeling and multi-indicator comprehensive evaluation methods further increases engineering risks and construction costs.

[0003] In the prior art, CN119337640A discloses a mountain photovoltaic system and its construction method based on 3D modeling. This method uses a drone equipped with a lidar and a high-definition camera to collect topographic point cloud data and image data of the target mountain, generating a digital elevation model and a 3D terrain model. Based on geographic coordinates, time, solar trajectory, and the 3D terrain model, a ray tracing algorithm is used to perform illumination analysis, generating a light intensity distribution map and a shadow change map. Based on the illumination analysis and shadow detection results, an intelligent optimization algorithm generates the optimal photovoltaic module layout scheme, optimizing light absorption and reducing shadow coverage. According to the 3D terrain model and layout scheme, a path search algorithm is used to plan the transportation and installation paths of the photovoltaic equipment, ensuring safety and efficiency. The photovoltaic modules are precisely installed using automated equipment and a laser positioning system, and the installation is inspected by a drone, collecting post-installation image data to analyze the installation quality.

[0004] The main problems with the above scheme are: it only describes the shape of the ground without addressing the underground geological conditions, lacks an assessment of geological stability and foundation safety, and affects the safety of installation; the optimization criteria rely almost entirely on illumination analysis, which may result in situations where the theoretically optimal location is not feasible in actual engineering.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a construction system and method for complex mountain photovoltaic systems based on three-dimensional modeling, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A construction system for complex mountain photovoltaic systems based on 3D modeling, specifically comprising:

[0009] The model building module is used to scan the target area, generate a digital elevation model, and obtain the geotechnical mechanical parameters of the target area. Based on the digital elevation model and the geotechnical mechanical parameters, a three-dimensional geological model is constructed.

[0010] The preliminary screening module is used to filter all feasible installation areas in the target area based on the installation dimensions of the photovoltaic panel base, with the minimum installation conditions as constraints, in the three-dimensional geological model.

[0011] The site selection module determines the installation area of ​​each support leg in the feasible installation area based on the range of motion of each support leg of the photovoltaic panel bracket. It then traverses the potential installation sites in the support leg installation area and calculates the bearing capacity potential score, settlement uniformity score, and slope stability score for each potential installation site. Based on the three scores, it generates a suitability index for the potential installation sites and sets a suitability index threshold. It then extracts all potential installation sites with a suitability index not less than the suitability index threshold as usable sites to generate several combinations of installation sites in the feasible installation area.

[0012] The point optimization module is used to calculate the stability of each combination of installation points and select the combination of installation points with the highest stability as the optimal combination of installation points for the feasible installation area.

[0013] The comprehensive optimization module is used to select photovoltaic panel installation areas from the feasible installation areas based on the stability of the optimal location combination of each feasible installation area and the spacing between adjacent feasible installation areas.

[0014] Furthermore, the mechanical parameters of the soil and rock mass are obtained based on core sampling boreholes, including bearing capacity, cohesion, internal friction angle, and compression modulus;

[0015] The digital elevation model and soil mechanics parameters are imported into 3D modeling software to generate a 3D geological model. The 3D geological model is then divided into uniform grid cells. Each grid cell contains the surface geometry information and underground soil mechanics properties of the corresponding area. The surface geometry information includes coordinate location and surface slope.

[0016] Furthermore, the logic for determining feasible installation areas is as follows:

[0017] The minimum installation condition is that the slope angle of the ground at the location where the photovoltaic panel is installed is not greater than the maximum slope angle of the ground where the photovoltaic panel can be installed stably.

[0018] Set a window with the same size as the photovoltaic panel. Use the window to slide within the target area to traverse all areas in the target area. The area that meets the minimum installation requirements and is the same size as the window is a feasible installation area.

[0019] Furthermore, the principle for determining potential installation points is as follows: the mounting area of ​​the support leg is divided into several units with the same size as the support leg, and each unit is a potential installation point.

[0020] Furthermore, the principle underlying the calculation of the bearing capacity potential score is as follows:

[0021] Obtain the internal friction angle and cohesion of the soil at potential installation points, and set thresholds for the internal friction angle and cohesion. The formula used to calculate the bearing capacity potential score is as follows:

[0022] ;

[0023] in, Indicates the carrying capacity potential score. Indicates cohesion. Indicates the cohesion threshold. Indicates the angle of internal friction. Indicates the threshold of the internal friction angle. These represent the weighting coefficients for cohesion and the angle of internal friction, respectively. The specific weights of the two are determined based on the soil properties;

[0024] The principle underlying the calculation of settlement uniformity score is as follows:

[0025] Using the potential installation point as the center, soil compression modulus monitoring points are randomly set within a 0.5m radius around the potential installation point. The soil stiffness uniformity around the potential installation point is calculated based on the soil compression modulus at each monitoring point, and this is used as the settlement uniformity score. The formula used is:

[0026] ;

[0027] in, The score represents the uniformity of settlement. This represents the standard deviation of the soil compression modulus at monitoring points within a 0.5m radius. This represents the average soil compression modulus at monitoring points within a 0.5m radius area;

[0028] The principle underlying the calculation of slope stability scores is as follows:

[0029] Obtain the slope angle at the location of potential installation points, and determine the maximum slope angle that meets the photovoltaic panel installation requirements as the slope angle reference threshold to generate a slope stability score. The formula used is as follows:

[0030] ;

[0031] in, This indicates the slope stability score. Indicates the slope angle. This indicates the reference threshold for the slope angle.

[0032] Furthermore, the principle underlying the generation of photovoltaic panel installation point combinations is as follows:

[0033] The suitability index is calculated based on the bearing capacity potential score, settlement uniformity score, and slope stability score of potential installation points. The formula used is as follows:

[0034] ;

[0035] in, Indicates suitability index, These represent the weighting coefficients for the bearing capacity potential score, settlement uniformity score, and slope stability score, respectively. ,and ;

[0036] Minimum bearing capacity potential score, minimum settlement uniformity score, and minimum slope stability score are set, and a suitability index threshold is calculated based on these scores. A potential installation point meets these criteria. and , , At that time, the potential installation location should be reserved, where, This represents the suitability index threshold. This indicates the minimum carrying capacity potential score. This indicates the minimum settlement uniformity score. The minimum slope stability score is represented; all retained potential installation points are available points; the available points in each support installation area are arranged and combined to obtain several sets of installation point combinations.

[0037] Furthermore, the principle underlying the calculation of the stability of the installation point combination is as follows:

[0038] For each combination of installation points, randomly select one available point from that combination. Search within that combination for other available points that are closest to it and have not yet been found, and record the distance between them as the side length of the available point in the combination. Repeat this process until every available point in the combination has been found. Based on the side lengths of all available points in the combination, calculate the stability of the combination using the following formula:

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] in, This represents the average side length between available points in the installation point combination. Indicates the index of the available point side length in the installation point combination. This indicates the number of available point side lengths in the installation point combination. Indicates the first in the installation point combination The length of the side of the available point. This indicates the standard deviation of the available point side lengths in the installation point combination. This represents the coefficient of variation for the combination of installation points. This indicates the stability of the installation point combination;

[0044] For any feasible installation area, pay attention to calculating the stability of each combination of installation points, and select the combination of installation points with the highest stability as the optimal combination of installation points for that feasible installation area.

[0045] Furthermore, the logic for determining the photovoltaic panel installation area is as follows:

[0046] 1) The feasible installation area with the highest stability of the optimal location combination is selected as the photovoltaic panel installation area;

[0047] 2) With the constraint that the spacing between photovoltaic panel installation areas is not less than the minimum installation spacing, for each feasible installation area that is not used as a photovoltaic panel installation area, a priority value is calculated based on its optimal location combination stability and the minimum distance between it and all photovoltaic panel installation areas. The feasible installation area corresponding to the maximum priority value is selected as the photovoltaic panel installation area.

[0048] 3) Repeat step 2) until no feasible installation area that meets the constraints can be found as the photovoltaic panel installation area;

[0049] The mathematical expression for the priority value of each feasible installation area is as follows:

[0050] ;

[0051] in, This indicates feasibility based on the region's priority value. This indicates the stability of the optimal combination of locations within the feasible installation area. Indicates the minimum installation spacing. This represents the minimum distance between the feasible installation area and all photovoltaic panel installation areas.

[0052] This invention also provides a construction method for complex mountain photovoltaic systems based on 3D modeling. The construction method is executed by the aforementioned construction system for complex mountain photovoltaic systems based on 3D modeling, and the specific steps include:

[0053] Step 1: Scan the target area, generate a digital elevation model, and obtain the geotechnical mechanical parameters of the target area. Construct a three-dimensional geological model based on the digital elevation model and the geotechnical mechanical parameters.

[0054] Step 2: In the 3D geological model, with the minimum installation conditions as constraints, all feasible installation areas are selected in the target area based on the installation dimensions of the photovoltaic panel base;

[0055] Step 3: Determine the range of motion of each leg of the photovoltaic panel support, identify the leg installation area of ​​each leg in the feasible installation area, and traverse all potential installation points in the leg installation area. Calculate the bearing capacity potential score, settlement uniformity score, and slope stability score for each potential installation point. Generate a suitability index for the potential installation points based on the three scores, set a suitability index threshold, and extract all potential installation points with a suitability index not less than the suitability index threshold as usable points to generate several combinations of installation points in the feasible installation area.

[0056] Step 4: Calculate the stability of each installation point combination, and select the installation point combination with the highest stability as the optimal combination for the feasible installation area;

[0057] Step 5: Based on the optimal location combination stability of each feasible installation area and the spacing between adjacent feasible installation areas, select photovoltaic panel installation areas from the feasible installation areas.

[0058] Compared with the prior art, the beneficial effects of the present invention are:

[0059] This invention constructs an integrated three-dimensional geological model combining surface digital elevation models and underground soil and rock mechanical parameters, avoiding risks such as foundation instability and landslides caused by unclear geological conditions. Using the maximum surface slope angle of the photovoltaic panels as an installation constraint improves the efficiency and comprehensiveness of installation site selection. The geological conditions of the installation site are evaluated from three factors: bearing capacity, settlement uniformity, and slope angle, ensuring the practical feasibility of the subsequently optimized theoretical installation scheme.

[0060] This invention also optimizes the installation points by comparing the uniformity of the distance between the points, determining the optimal installation point from several combinations of installation points, comprehensively considering various installation situations, and ensuring that the optimal installation point can be found for each installation area; after determining the optimal installation point, the installation priority is determined based on the stability of the installation area, which reduces the probability of bracket installation failure, while taking into account both installation stability and installation density. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the system modules in an embodiment of the present invention;

[0062] Figure 2 This is a schematic diagram illustrating the change in priority as a function of stability in an embodiment of the present invention;

[0063] Figure 3 This is a schematic diagram of the method flow of an embodiment of the present invention. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0065] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0066] Example:

[0067] Please see Figures 1 to 3 The present invention provides a technical solution:

[0068] A construction system for complex mountain photovoltaic systems based on 3D modeling, specifically comprising:

[0069] The model building module is used to scan the target area, generate a digital elevation model, and obtain the geotechnical mechanical parameters of the target area. Based on the digital elevation model and the geotechnical mechanical parameters, a three-dimensional geological model is constructed.

[0070] In this embodiment, the mechanical parameters of the soil and rock mass are obtained based on core sampling boreholes, including bearing capacity, cohesion, internal friction angle and compression modulus;

[0071] The digital elevation model and soil mechanics parameters are imported into 3D modeling software to generate a 3D geological model. The 3D geological model is then divided into uniform grid cells. Each grid cell contains the surface geometry information and underground soil mechanics properties of the corresponding area. The surface geometry information includes coordinate location and surface slope.

[0072] The principle of generating a digital elevation model (DEM) by scanning the target area is as follows: A drone equipped with a LiDAR device emits laser pulses and receives reflected signals to acquire three-dimensional point cloud data of the ground surface; the acquired point cloud data is denoised, filtered, and classified to distinguish non-surface points such as vegetation and buildings; the point cloud data is converted into a raster-based DEM using Kriging interpolation, where each pixel value represents the elevation of its corresponding location; core sampling boreholes are drilled in the target area, with the drilling depth exceeding the expected influence depth of the photovoltaic support, to obtain data including bearing capacity, cohesion, and internal friction angle. The system obtains geomechanical parameters, including the compressibility modulus; it imports the digital elevation model (DEM) and geomechanical parameters into 3D geological modeling software (such as Plaxis and Civil3D), divides the area covered by the DEM into uniform grid cells, and obtains the surface information such as elevation and slope of each grid cell directly from the DEM. It also performs Kriging interpolation on the underground geomechanical parameters of the core sampling boreholes to obtain the underground geomechanical parameters of each grid cell, and constructs a 3D geological model that includes surface geometric information and underground geomechanical parameters.

[0073] The preliminary screening module is used to filter all feasible installation areas in the target area based on the installation dimensions of the photovoltaic panel base, with the minimum installation conditions as constraints, in the three-dimensional geological model.

[0074] In this embodiment, the logic for determining a feasible installation area is as follows:

[0075] The minimum installation condition is that the slope angle of the ground at the location where the photovoltaic panel is installed is not greater than the maximum slope angle of the ground where the photovoltaic panel can be installed stably.

[0076] Set a window with the same size as the photovoltaic panel. Use the window to slide within the target area to traverse all areas in the target area. The area that meets the minimum installation requirements and is the same size as the window is a feasible installation area.

[0077] The minimum installation conditions mean that the surface slope of the installation location must not exceed the maximum allowable slope for stable installation of the photovoltaic panel, ensuring that the photovoltaic panel will not be unstable or slip due to excessive slope; and each feasible installation area must be able to accommodate a whole photovoltaic panel. The specific implementation method for determining the feasible installation area is as follows: Define a window with the same size as the photovoltaic panel base, select an initial position on the digital elevation model, and start from this initial position to slide and scan the window on the digital elevation model of the target area with a sliding step size of 0.3m. Each time the window slides, determine whether the area covered by the current window can satisfy the condition that the maximum slope within the window is less than or equal to the maximum surface slope. If it is satisfied, the area covered by the window is marked as a feasible installation area. Traverse the target area to obtain all areas that meet the above conditions. Each area represents a feasible installation area.

[0078] The site selection module determines the installation area of ​​each support leg in the feasible installation area based on the range of motion of each support leg of the photovoltaic panel bracket. It then traverses the potential installation sites in the support leg installation area and calculates the bearing capacity potential score, settlement uniformity score, and slope stability score for each potential installation site. Based on the three scores, it generates a suitability index for the potential installation sites and sets a suitability index threshold. It then extracts all potential installation sites with a suitability index not less than the suitability index threshold as usable sites to generate several combinations of installation sites in the feasible installation area.

[0079] In this embodiment, the principle for determining potential installation points is as follows: based on the actual installation conditions of the photovoltaic panel bracket, the range of motion of each bracket leg in the feasible installation area is determined. The range of motion of each leg corresponds to its installation area. The leg installation area is divided into several units with the same size as the leg. Each unit is a potential installation point.

[0080] The principle underlying the calculation of bearing capacity potential score is as follows:

[0081] Obtain the internal friction angle and cohesion of the soil at potential installation points, and set thresholds for the internal friction angle and cohesion. The formula used to calculate the bearing capacity potential score is as follows:

[0082] ;

[0083] in, Indicates the carrying capacity potential score. Indicates cohesion. Indicates the cohesion threshold. Indicates the angle of internal friction. Indicates the threshold of the internal friction angle. These represent the weighting coefficients for cohesion and the angle of internal friction, respectively. The specific weights of the two are determined based on the soil properties;

[0084] The bearing capacity potential score reflects the bearing capacity of the soil at a potential installation site under the load of a photovoltaic support, i.e., its shear strength. When evaluating shear strength, both soil cohesion and internal friction angle need to be considered. Cohesion represents the inherent bond between soil particles, while the internal friction angle reflects the friction generated when soil particles slide and roll against each other, mainly originating from the surface roughness of the soil particles and the interlocking and interlocking effects between particles. Higher cohesion and a larger internal friction angle result in higher shear strength; both are directly proportional to the soil's shear strength. Therefore, both parameters must be considered simultaneously. For example, the shear strength of clay layers mainly comes from cohesion, while the shear strength of sandy layers mainly comes from the internal friction angle. (Cohesion threshold...) and internal friction angle threshold These correspond to the minimum cohesive force and internal friction angle required for photovoltaic unit installation, respectively. The greater the cohesive force and internal friction angle, the better. and The larger the value, the higher the bearing capacity potential score, the stronger the soil bearing capacity at the corresponding location, and the more stable the installation of photovoltaic panels; and The value is determined by the soil type. If the soil is mainly clay, then... If the soil is mainly composed of sand, then the value will be higher. The value is higher.

[0085] The principle underlying the calculation of settlement uniformity score is as follows:

[0086] Using the potential installation point as the center, soil compression modulus monitoring points are randomly set within a 0.5m radius around the potential installation point. The soil stiffness uniformity around the potential installation point is calculated based on the soil compression modulus at each monitoring point, and this is used as the settlement uniformity score. The formula used is:

[0087] ;

[0088] in, The score represents the uniformity of settlement. This represents the standard deviation of the soil compression modulus at monitoring points within a 0.5m radius. This represents the average soil compression modulus at monitoring points within a 0.5m radius area;

[0089] The settlement uniformity score reflects the uniformity of the soil stiffness around the potential support point. It is used to assess whether the settlement at the point may be uniform after being loaded. The larger the settlement uniformity index, the more uniform the stiffness of the surrounding soil, the more uniform the settlement after being loaded, the higher the safety, and the lower the probability of the support tilting or being damaged at a certain location. The standard deviation of the soil compression modulus reflects the degree of fluctuation in soil stiffness. This represents the average value of the soil compression modulus, reflecting the overall soil stiffness level. This represents the coefficient of variation. A larger coefficient of variation indicates more uneven soil stiffness, a lower settlement uniformity score, and a higher risk of harmful uneven settlement. Values The closer the value is to 1, the better the uniformity of soil settlement. If the soil stiffness around a support point varies greatly, the settlement between different support points may be inconsistent after the photovoltaic unit is installed, leading to stress concentration in the structure and causing deformation or damage to the support, thus affecting the overall safety of the system.

[0090] The principle underlying the calculation of slope stability scores is as follows:

[0091] Obtain the slope angle at the location of potential installation points, and determine the maximum slope angle that meets the photovoltaic panel installation requirements as the slope angle reference threshold to generate a slope stability score. The formula used is as follows:

[0092] ;

[0093] in, This indicates the slope stability score. Indicates the slope angle. This indicates the reference threshold for the slope angle.

[0094] Slope stability scoring is used to quantitatively assess the impact of the surface slope at a potential installation site on the stability of photovoltaic panel installation. It reflects whether the site is prone to foundation slippage, overturning, or overall instability due to excessive slope. The slope at the site is determined by comparing the actual slope angle with the maximum slope angle. Due to minimum installation requirements, P must not exceed [a certain value]. And the closer P is to This indicates that the greater the actual slope, The closer P is to 0, the worse the slope stability. Excessive slope stability makes it extremely prone to soil slippage or landslides; the smaller P is, the better. The closer the value is to 1, the closer it is to the ideal state. The slope stability score is inversely proportional to the slope angle.

[0095] The principle underlying the generation of photovoltaic panel installation point combinations is as follows:

[0096] The suitability index is calculated based on the bearing capacity potential score, settlement uniformity score, and slope stability score of potential installation points. The formula used is as follows:

[0097] ;

[0098] in, Indicates suitability index, These represent the weighting coefficients for the bearing capacity potential score, settlement uniformity score, and slope stability score, respectively. ,and ;

[0099] The suitability index reflects whether a location is suitable for installing photovoltaic units from a geological safety perspective. It is determined by three factors: bearing capacity potential score, settlement uniformity score, and slope stability score. It also reflects the soil's shear strength, uniformity of soil stiffness, and slope stability, avoiding three risks: exceeding the support's load-bearing capacity, uneven settlement leading to support tilting or damage, and excessive slope causing landslides or support instability. A higher suitability index indicates better overall geological safety at the location, making it more suitable for photovoltaic support installation. Bearing capacity is the most basic requirement for support safety and directly relates to whether foundation damage will occur, hence its highest weight. Uneven settlement can lead to support tilting or even damage, especially critical in complex mountainous terrain, and its weight is second highest. While slope affects stability, it was previously limited based on minimum installation conditions, and the slopes of the retained locations all meet installation requirements, differing only in safety; therefore, its weight is the lowest. , , .

[0100] Minimum bearing capacity potential score, minimum settlement uniformity score, and minimum slope stability score are set, and a suitability index threshold is calculated based on these. The minimum bearing capacity score ensures sufficient foundation bearing capacity at the installation point, preventing support settlement, tilting, or failure due to insufficient bearing capacity. Geotechnical tests are used to determine the minimum cohesion and minimum internal friction angle required for photovoltaic panel installation, which are then substituted into the formula for the bearing capacity potential score. The minimum settlement uniformity score is set to avoid uneven settlement of the support due to excessive soil stiffness differences, which could lead to structural stress concentration. The minimum settlement uniformity score is determined based on the properties of the photovoltaic panel support to ensure that throughout the entire lifespan of the photovoltaic panel, when [the following occurs], [the following occurs]: When structural stress and deformation are caused by uneven settlement, they always remain within the safe range that the photovoltaic panel support can withstand. The maximum differential settlement that the photovoltaic panel can withstand is determined based on the maximum allowable deformation of the photovoltaic panel support. The differential settlement between points should not exceed the maximum differential settlement. Soil settlement is inversely proportional to the soil compression modulus. The soil compression modulus corresponding to the point of maximum settlement and the soil compression modulus corresponding to the point of no settlement are selected and substituted into the formula for calculating the settlement uniformity score to obtain the minimum settlement uniformity score. The minimum slope stability score represents the maximum surface slope angle that exactly meets the installation constraints of the photovoltaic panel installation area. This slope angle is substituted into the slope stability score formula to obtain the minimum slope stability score. When a potential installation location meets and , , At that time, the potential installation location should be reserved, where, This represents the suitability index threshold. This indicates the minimum carrying capacity potential score. This indicates the minimum settlement uniformity score. The minimum slope stability score is represented; all retained potential installation points are available points; the available points in each support installation area are arranged and combined to obtain several sets of installation point combinations.

[0101] When selecting usable locations, they must simultaneously meet the minimum suitability index threshold, and each score must be no lower than the corresponding minimum threshold. This is to avoid situations where the suitability index threshold is met, but one of the indicators is too low, making installation impossible.

[0102] The point optimization module is used to calculate the stability of each combination of installation points and select the combination of installation points with the highest stability as the optimal combination of installation points for the feasible installation area.

[0103] In this embodiment, the principle underlying the calculation of the stability of the installation point combination is as follows:

[0104] For each combination of installation points, randomly select one available point from that combination. Search within that combination for other available points that are closest to it and have not yet been found, and record the distance between them as the side length of the available points in the combination. Repeat this process until every available point in the combination has been found. Based on the side lengths of the available points in the combination, calculate the stability of the combination using the following formula:

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] in, This represents the average side length between available points in the installation point combination. Indicates the index of the available point side length in the installation point combination. This indicates the number of available point side lengths in the installation point combination. Indicates the first in the installation point combination The length of the side of the available point. This indicates the standard deviation of the available point side lengths in the installation point combination. This represents the coefficient of variation for the combination of installation points. This indicates the stability of the installation point combination;

[0110] For any feasible installation area, pay attention to calculating the stability of each combination of installation points, and select the combination of installation points with the highest stability as the optimal combination of installation points for that feasible installation area.

[0111] Each installation point combination represents a feasible installation area. For each leg of the photovoltaic panel, a usable point is selected within its installation area; the number of usable points selected corresponds to the number of legs. Stability is measured by analyzing the geometrical uniformity of the leg points within an installation point combination. A starting point is randomly selected, and the nearest unvisited point is found, with the distance between the two points recorded. This process continues until all points have been visited, resulting in a set of side lengths. The mean and standard deviation of this set of side lengths are calculated, and the coefficient of variation is calculated based on the ratio of the standard deviation to the mean. This is used to reflect the degree of dispersion of the side length. The larger the value, the more uneven the side lengths. Taking the reciprocal gives the stability, indicating that the more uniform the side length, the higher the stability of the combination. The more uniform the side length, the more balanced the force on the support, thereby reducing the risk of damage caused by uneven settlement or stress concentration. Therefore, the standard deviation of the side length is inversely proportional to the stability of the installation point combination.

[0112] The comprehensive optimization module is used to select photovoltaic panel installation areas from the feasible installation areas based on the stability of the optimal location combination of each feasible installation area and the spacing between adjacent feasible installation areas.

[0113] In this embodiment, the logic for determining the photovoltaic panel installation area is as follows:

[0114] 1) The feasible installation area with the highest stability of the optimal location combination is selected as the photovoltaic panel installation area;

[0115] 2) With the constraint that the spacing between photovoltaic panel installation areas is not less than the minimum installation spacing, for each feasible installation area that is not used as a photovoltaic panel installation area, a priority value is calculated based on its optimal location combination stability and the minimum distance between it and all photovoltaic panel installation areas. The feasible installation area corresponding to the maximum priority value is selected as the photovoltaic panel installation area.

[0116] 3) Repeat step 2) until no feasible installation area that meets the constraints can be found as the photovoltaic panel installation area;

[0117] The mathematical expression for the priority value of each feasible installation area is as follows:

[0118] ;

[0119] in, This indicates feasibility based on the region's priority value. This indicates the stability of the optimal combination of locations within the feasible installation area. Indicates the minimum installation spacing. This represents the minimum distance between the feasible installation area and all photovoltaic panel installation areas.

[0120] When selecting feasible installation areas for photovoltaic (PV) panels, two factors are considered simultaneously: stability and density. First, feasible installation areas are ranked according to the stability of the optimal combination of locations, and the area with the highest stability is selected as the PV panel installation area. In subsequent selections, both stability and the minimum distance from the PV panel installation area are considered. While ensuring that the minimum installation spacing is not less than the required minimum, the smaller the minimum distance from the PV panel installation area, the better. The larger; based on stability and The priority value is determined jointly and calculated. The formula is expressed by Adjustments are made to balance stability and density requirements. Even if a feasible installation area has high stability, it may still be problematic if it is too far from the photovoltaic panel installation area. It will take a very small value, thus lowering the priority value; Table 1 reflects how the priority value changes with stability. This reflects that as stability increases, priority generally tends to rise, but for some points... The value is relatively large, and under this influence, the priority value is actually smaller.

[0121] Table 1. Priority Value Change Table

[0122]

[0123] Please see Figure 3 The present invention also provides a construction method for complex mountain photovoltaic systems based on three-dimensional modeling. The construction method is executed by the aforementioned construction system for complex mountain photovoltaic systems based on three-dimensional modeling, and the specific steps include:

[0124] Step 1: Scan the target area, generate a digital elevation model, and obtain the geotechnical mechanical parameters of the target area. Construct a three-dimensional geological model based on the digital elevation model and the geotechnical mechanical parameters.

[0125] Step 2: In the 3D geological model, with the minimum installation conditions as constraints, all feasible installation areas are selected in the target area based on the installation dimensions of the photovoltaic panel base;

[0126] Step 3: Determine the range of motion of each leg of the photovoltaic panel support, identify the leg installation area of ​​each leg in the feasible installation area, and traverse all potential installation points in the leg installation area. Calculate the bearing capacity potential score, settlement uniformity score, and slope stability score for each potential installation point. Generate a suitability index for the potential installation points based on the three scores, set a suitability index threshold, and extract all potential installation points with a suitability index not less than the suitability index threshold as usable points to generate several combinations of installation points in the feasible installation area.

[0127] Step 4: Calculate the stability of each installation point combination, and select the installation point combination with the highest stability as the optimal combination for the feasible installation area;

[0128] Step 5: Based on the optimal location combination stability of each feasible installation area and the spacing between adjacent feasible installation areas, select photovoltaic panel installation areas from the feasible installation areas.

[0129] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0130] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0131] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A construction system for complex mountain photovoltaics based on three-dimensional modeling, characterized by, Specifically comprising: A model construction module for scanning a target area, generating a digital elevation model, and obtaining mechanical parameters of rock-soil bodies in the target area, and constructing a three-dimensional geological model based on the digital elevation model and the mechanical parameters of the rock-soil bodies; A preliminary screening module for screening all feasible installation areas in the target area based on the installation size of the photovoltaic panel base in the three-dimensional geological model with the minimum installation condition as a constraint; A point site screening module for determining a foot installation area of each foot of the photovoltaic panel support in the feasible installation area based on the range of movement of each foot of the photovoltaic panel support, and traversing potential installation points in the foot installation area, calculating a bearing capacity potential score, a settlement uniformity score, and a slope stability score of each potential installation point, generating a suitability index of the potential installation point based on the three scores, setting a suitability index threshold, and extracting all potential installation points with a suitability index not less than the suitability index threshold as available points to generate a plurality of installation point combinations in the feasible installation area; A point site optimization module for calculating the stability of each installation point combination and selecting an installation point combination with the highest stability as an optimal point combination of the feasible installation area; A comprehensive optimization module for screening a photovoltaic panel installation area from the feasible installation area based on the stability of the optimal point combination of each feasible installation area and the spacing of adjacent feasible installation areas; The principle for calculating the stability of the installation point combination in the point site optimization module is that for each installation point combination, a usable point in the installation point combination is randomly selected, the other usable point closest to the usable point in the installation point combination is searched, and the distance between the two points is recorded as the usable point side length of the installation point combination. The above steps are repeated until each usable point in the installation point combination is searched. The stability of the installation point combination is calculated based on all the usable point side lengths of the installation point combination, and the formula is: For any feasible installation area, the stability of each installation point combination is calculated, and an installation point combination with the highest stability is selected as the optimal point combination of the feasible installation area. wherein, represents the average of the edge length of the available point positions in the installation point position combination, represents the index of the edge length of the available point positions in the installation point position combination, represents the number of the edge length of the available point positions in the installation point position combination, represents the length of the edge length of the available point positions in the installation point position combination, represents the length of the edge length of the available point positions in the installation point position combination, represents the standard deviation of the edge length of the available point positions in the installation point position combination, represents the coefficient of variation of the installation point position combination, represents the stability of the installation point position combination; The mechanical parameters of the rock-soil bodies are obtained based on core sampling drilling and include bearing capacity, cohesion, internal friction angle, and compression modulus; 2. A complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 1, characterized in that: The digital elevation model and the mechanical parameters of the rock-soil bodies are imported into a three-dimensional modeling software to generate a three-dimensional geological model, and uniform grid cells are divided in the three-dimensional geological model. Each grid cell contains surface geometric information and underground rock-soil mechanical properties of the corresponding area. The surface geometric information includes coordinate position and surface slope. The logic for determining the feasible installation area in the preliminary screening module is that:

3. A complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 1, characterized in that: The minimum installation condition is that the surface slope angle at the installation position of the photovoltaic panel is not greater than the maximum surface slope angle for stable installation of the photovoltaic panel; A window with a size consistent with the size of the photovoltaic panel is set, and the window is used to slide in the target area to traverse all areas in the target area. The areas that meet the minimum installation condition and have a size consistent with the window are the feasible installation areas. ​ 4. The complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 1, characterized in that: The principle for determining the potential installation point is to divide the foot installation area into a plurality of units consistent with the size of the foot, and each unit is a potential installation point.

5. A complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 4, characterized in that: The principle for calculating the bearing capacity potential score in the point screening module is: The internal friction angle and cohesion of the soil at the potential installation point are obtained, and the internal friction angle threshold and cohesion threshold are set. The formula for calculating the bearing capacity potential score is: wherein, denotes the bearing capacity potential score, denotes the cohesion, denotes the cohesion threshold value, denotes the internal friction angle, denotes the internal friction angle threshold value, denote the weight coefficients of the cohesion and the internal friction angle, respectively, the specific weights of both are determined based on the soil properties; The principle for calculating the settlement uniformity score is: A soil compression modulus monitoring point is randomly set within a 0.5m radius area around the potential installation point, and the soil stiffness uniformity around the potential installation point is calculated based on the soil compression modulus at the monitoring point, which is used as the settlement uniformity score. The formula is: wherein, represents the settlement uniformity score, represents the standard deviation of the soil compressive modulus of the monitoring points within a 0.5 m radius, represents the average value of the soil compressive modulus of the monitoring points within a 0.5 m radius; The principle for calculating the slope stability score is: The slope angle of the location of the potential installation point is obtained, and the maximum slope angle meeting the installation requirements of the photovoltaic panel is determined as the reference threshold of the slope angle to generate the slope stability score. The formula is: wherein, represents a slope stability score, represents a slope angle, represents a slope angle reference threshold.

6. A complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 5, characterized in that: The principle for generating the installation point combination of the photovoltaic panel in the point screening module is: The suitability index is calculated based on the bearing capacity potential score, the settlement uniformity score, and the slope stability score of the potential installation point. The formula is: wherein, represents the suitability index, respectively represent the weight coefficients of the bearing capacity potential score, the settlement uniformity score, and the slope stability score, , and ; A minimum bearing capacity potential score, a minimum settlement uniformity score and a minimum slope stability score are set, and a suitability index threshold value is calculated therefrom, and when a potential installation point satisfies and , , , the potential installation point is reserved, wherein represents the suitability index threshold value, represents the minimum bearing capacity potential score, represents the minimum settlement uniformity score, represents the minimum slope stability score; all reserved potential installation points are available points; and the available points in each foot installation area are arranged and combined to obtain a plurality of installation point combination groups.

7. A complex mountainous terrain photovoltaic construction system based on three-dimensional modeling according to claim 1, characterized in that: The logic for determining the photovoltaic panel installation area is: 1) The feasible installation area with the highest stability of the optimal point combination is determined as the photovoltaic panel installation area; 2) With the constraint that the spacing of the photovoltaic panel installation area is not less than the minimum installation spacing, for each feasible installation area that is not the photovoltaic panel installation area, the priority value is calculated based on the stability of the optimal point combination and the minimum distance to all photovoltaic panel installation areas. The feasible installation area corresponding to the maximum priority value is selected as the photovoltaic panel installation area; 3) Repeat step 2) until no feasible installation area meeting the constraint condition can be found as the photovoltaic panel installation area; Wherein, for each feasible installation area, the mathematical expression of the priority value is as follows: wherein, represents the feasible priority value by region, represents the optimal bit combination stability of the feasible installation region, represents the minimum installation distance, represents the minimum distance of the feasible installation region from all photovoltaic panel installation regions.

8. A construction method of complex mountainous photovoltaic based on three-dimensional modeling, characterized in that: The construction method is performed by the construction system for complex mountain photovoltaic based on three-dimensional modeling according to any one of claims 1-7, and the specific steps include: Step 1: Scan the target area to generate a digital elevation model and obtain the rock and soil mechanical parameters of the target area. Based on the digital elevation model and the rock and soil mechanical parameters, a three-dimensional geological model is constructed; Step 2: In the three-dimensional geological model, all feasible installation areas are screened out in the target area based on the installation size of the photovoltaic panel base with the constraint of meeting the minimum installation condition; Step 3: The activity range of each foot of the photovoltaic panel support is determined, and the foot installation area of each foot in the feasible installation area is determined. The bearing capacity potential score, the settlement uniformity score, and the slope stability score of each potential installation point are calculated. Based on the three scores, the suitability index of the potential installation point is generated, and the suitability index threshold is set. The potential installation points with a suitability index not less than the suitability index threshold are extracted as available points to generate a plurality of installation point combinations in the feasible installation area; Step 4: Calculate the stability of each installation point combination, and select the installation point combination with the highest stability as the optimal point combination of the feasible installation area; Step 5: Based on the optimal point combination stability of each feasible installation area and the distance between adjacent feasible installation areas, screen out the photovoltaic panel installation area from the feasible installation area.

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