Mountain photovoltaic power station solid-soft hybrid arrangement calculation method and system

Abstract

The application discloses a mountain photovoltaic power station solid-flexible hybrid arrangement calculation method and system, and belongs to the technical field of photovoltaic power station digital design and optimization. The application first collects power station basic data, analyzes DEM data and constructs integrated terrain data set containing slope, slope direction, altitude, terrain undulation and geological information; relies on the terrain adaptation difference of two types of supports to build an adaptive partition model, sets slope classification adaptation rules, and automatically divides fixed, flexible and solid-flexible hybrid layout areas. The terrain coupling cost model is constructed by introducing the terrain complexity coefficient, and the full-cycle cost and power generation benefit correlation models of the two types of supports are respectively established; the double-target optimization model of installed capacity and full-life-cycle economic benefit is constructed with the maximization of comprehensive benefit as the target, and the optimal solid-flexible hybrid arrangement scheme is solved and output. The application solves the difficult problem of complex mountain photovoltaic support layout decision, and effectively improves the power generation efficiency and project investment income of the power station.

Description

Technical Field

[0001] This invention belongs to the field of digital design and optimization technology for photovoltaic power plants, specifically relating to a method and system for calculating the hybrid solid-flexible layout of a mountain photovoltaic power plant. Background Technology

[0002] Mountainous photovoltaics is an important scenario for the large-scale development of photovoltaics. Compared with plain photovoltaics, mountainous terrain has complex characteristics such as drastic elevation fluctuations, disordered slope changes, discrete slope aspects, crisscrossing gullies, uneven geological conditions, and large differences in wind load zones, which puts extremely high demands on the selection of photovoltaic support structures and array layout.

[0003] Addressing the industry pain points of complex mountainous terrain with its undulating terrain, discrete slope and aspect, and complex geological and wind load zoning, existing designs often employ single fixed or flexible support structures. These designs often fail to achieve adaptive support type selection, struggle to balance economic efficiency and power generation benefits, suffer from strong subjectivity in manual decision-making, and lack quantitative calculation models. This invention constructs a terrain-adaptive zoning model for fixed and flexible supports, a terrain-coupled cost-effectiveness model for fixed and flexible supports, and establishes a dual-objective hybrid layout optimization mathematical model that balances maximizing installed capacity and optimizing the entire lifecycle economy. By combining genetic algorithms and mixed-integer linear programming for joint solution, this invention achieves automatic zoning, adaptive selection, and efficient combination and layout of fixed and flexible supports in different mountainous terrain sections. It also supports quantitative comparison between single support schemes and hybrid fixed-flexible layout schemes. This invention effectively solves the problem of selecting and deploying photovoltaic supports in complex mountainous terrain, significantly improving the overall power generation efficiency and investment returns of mountainous photovoltaic power plants. It features high layout accuracy, strong adaptability, and good engineering feasibility, making it suitable for the intelligent design and optimized layout of photovoltaic power plants in various mountainous and hilly terrains. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing mountain photovoltaic support layout technologies, such as fixed selection, lack of adaptive zoning, inaccurate cost calculation, difficulty in coordinating multiple objectives, and inability to quantitatively compare and select solutions. This invention provides a method and system for calculating the hybrid solid-flexible layout of mountain photovoltaic power plants, enabling adaptive zoning selection of solid and flexible supports in different mountainous terrain areas, accurate modeling of terrain-coupled costs, intelligent optimization of capacity-economy dual objectives, and quantitative comparison and selection of multiple solutions. This solves the problem of photovoltaic support layout decision-making in complex terrains and improves the overall power generation efficiency and investment returns of the power plant.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station includes: 1) Collect basic data of the power station and perform digital elevation model (DEM) data analysis to construct DEM data of the power station range with spatial consistency and computability, including natural terrain slope, aspect, elevation, topographic relief and geological data. 2) Construct an adaptive zoning model for fixed and flexible supports. Based on the adaptation differences of natural terrain slope, aspect, altitude, terrain undulation and geological data between fixed and flexible supports, establish slope classification adaptation rules to achieve automatic zoning of the entire area and obtain fixed support deployment area, flexible support deployment area and fixed-flexible hybrid optimization area. 3) Based on the fixed support deployment area, flexible support deployment area and fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model and a power generation benefit correlation model adapted to mountain characteristics are established respectively. 4) Based on the fixed support full-cycle cost correlation model, the flexible support full-cycle cost correlation model and the power generation benefit correlation model, a multi-objective model optimization of the fixed-flexible hybrid layout is carried out. With the maximum comprehensive benefit of the mountain photovoltaic power station as the core, a dual-objective optimization model of maximizing installed capacity and optimizing the full life cycle economy is established. 5) Solve the dual-objective optimization model of maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle to obtain an optimized layout scheme for the mixed arrangement of fixed and flexible supports for mountain photovoltaic power stations.

[0006] A further improvement of this invention is that, in step 1), collecting basic power station data includes: Collect DEM data, topographic slope and aspect data, ecological red line vector boundary, geological bearing capacity zoning, wind load zoning, transportation and construction condition data of the target mountain photovoltaic power station; input equipment parameters; complete the site topographic grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

[0007] A further improvement of this invention lies in step 2), which involves constructing an adaptive zoning model for fixed and flexible supports. Based on the differences in adaptation between the fixed and flexible supports in terms of natural terrain slope, aspect, altitude, topographic relief, and geological data, a slope grading adaptation rule is established to achieve automatic zoning across the entire region, including: Fixed support adaptation zone: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation zone; Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone; Solid-flexible hybrid adaptation zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone; Further superimposed multidimensional hard constraint boundary conditions: ecological protection boundary prohibition constraint, geological bearing capacity insufficient block elimination constraint, wind load maximum span limit constraint, flexible support minimum span constraint, and drainage and ditch avoidance constraint, ultimately outputting three types of functional blocks in the site: fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area.

[0008] A further improvement of this invention is that, in step 3), based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to mountainous terrain characteristics are established, including: Fixed scaffolding full-cycle cost correlation model: The cost of fixed scaffolding is determined by the amount of pile foundation work, the number of columns, the arrangement density, and the incremental costs of transportation and construction. A cost function is constructed as follows:

[0009] in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. The unit cost of pile foundation drilling and pouring; The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. A full-cycle cost correlation model for flexible scaffolding reveals that construction costs are strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows:

[0010] in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. Power generation benefit correlation model: Combining the tilt angle adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve the coupling and matching of cost and power generation benefits.

[0011] A further improvement of this invention lies in step 4), where the multi-objective model optimization of the hybrid solid-flexible layout, with the maximization of the comprehensive benefits of the mountain photovoltaic power station as the core, establishes a dual-objective optimization model for maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle, including: The objective function includes: Objective 1: Maximize total installed capacity

[0012] Objective 2: Minimize the levelized cost of electricity (LCOE) over the entire lifecycle.

[0013] In the formula: For the installed capacity of the fixed support area; For the installed capacity of the flexible support area; Total construction and operation and maintenance costs for the entire site; Total annual power generation; Global constraints include: slope and aspect terrain adaptation constraints, solid-flexible zone boundary constraints, flexible support length and span limits, pile foundation bearing capacity constraints, ecological prohibition constraints, electrical layout constraints, unobstructed spacing constraints, and construction and maintenance access constraints.

[0014] A hybrid fixed-flexible layout calculation system for mountain photovoltaic power stations includes: Data acquisition unit: Collects basic data of the power station and performs digital elevation model (DEM) data analysis to construct DEM data of the power station area with spatial consistency and computability, including natural terrain slope, aspect, altitude, topographic relief and geological data. The first model construction unit is to construct an adaptive zoning model for fixed and flexible supports. Based on the adaptation differences of natural terrain slope, aspect, altitude, terrain undulation and geological data between fixed and flexible supports, a slope classification adaptation rule is established to achieve automatic zoning of the entire domain, resulting in a fixed support deployment area, a flexible support deployment area and a fixed-flexible hybrid optimization area. The second model construction unit: Based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to the mountainous characteristics are established respectively. The third model construction unit: Based on the fixed support full-cycle cost correlation model, the flexible support full-cycle cost correlation model and the power generation benefit correlation model, a multi-objective model optimization of the fixed and flexible hybrid layout is carried out. With the maximum comprehensive benefit of the mountain photovoltaic power station as the core, a dual-objective optimization model of maximizing installed capacity and optimizing the full life cycle economy is established. Model Solving Unit: Solve the dual-objective optimization model of maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle to obtain an optimized layout scheme for the mixed arrangement of fixed and flexible supports for mountain photovoltaic power stations.

[0015] A further improvement of this invention is that the data acquisition unit collects basic power plant data including: Collect DEM data, topographic slope and aspect data, ecological red line vector boundary, geological bearing capacity zoning, wind load zoning, transportation and construction condition data of the target mountain photovoltaic power station; input equipment parameters; complete the site topographic grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

[0016] A further improvement of this invention lies in that, in the first model construction unit, an adaptive zoning model for fixed and flexible supports is constructed. Based on the adaptation differences between the fixed and flexible supports in terms of natural terrain slope, aspect, altitude, terrain undulation, and geological data, slope classification adaptation rules are established to achieve automatic zoning across the entire region, including: Fixed support adaptation zone: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation zone; Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone; Solid-flexible hybrid adaptation zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone; Further superimposed multidimensional hard constraint boundary conditions: ecological protection boundary prohibition constraint, geological bearing capacity insufficient block elimination constraint, wind load maximum span limit constraint, flexible support minimum span constraint, and drainage and ditch avoidance constraint, ultimately outputting three types of functional blocks in the site: fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area.

[0017] A further improvement of this invention lies in that, in the second model construction unit, based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to mountainous terrain characteristics are established, including: Fixed scaffolding full-cycle cost correlation model: The cost of fixed scaffolding is determined by the amount of pile foundation work, the number of columns, the arrangement density, and the incremental costs of transportation and construction. A cost function is constructed as follows:

[0018] in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. The unit cost of pile foundation drilling and pouring; The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. A full-cycle cost correlation model for flexible scaffolding reveals that construction costs are strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows:

[0019] in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. Power generation benefit correlation model: Combining the tilt angle adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve the coupling and matching of cost and power generation benefits.

[0020] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station.

[0021] Compared with the prior art, the present invention has at least the following beneficial technical effects: 1. Achieve terrain-adaptive intelligent zoning for fixed and flexible supports. Pioneering a fixed-flexible adaptation rule based on slope grading and multi-dimensional boundary constraints, it automatically divides the system into fixed, flexible, and mixed transition zones, completely eliminating reliance on manual experience and achieving precise matching between support types and terrain conditions.

[0022] 2. Construct a realistic mountain cost model coupled with terrain. By introducing a terrain complexity coefficient, a differentiated cost function for fixed and flexible supports is established to adapt to the undulations, gullies, and construction difficulties of mountains, solving the problem of distortion in traditional plain quota cost calculation and significantly improving the accuracy of investment calculation.

[0023] 3. Achieve optimal synergy between capacity and economic objectives. By maximizing installed capacity and optimizing the levelized cost of electricity (LCOE) over the entire lifecycle, the limitations of single-objective optimization are overcome, significantly improving the overall return on investment for power plants.

[0024] 4. Multiple algorithms work together to solve the problem, resulting in a highly implementable solution. The solution combines global optimization using genetic algorithms with precise constraints from mixed-integer programming, adapting to engineering characteristics such as discrete scaffold selection and integer constraints across multiple spans. The output solution is safe, compliant, and can be directly implemented.

[0025] 5. Supports quantitative comparison of multiple options. Enables intelligent comparison of three types of options: purely fixed, purely flexible, and hybrid fixed-flexible, solving the problem of complex mountain support selection decisions and providing standardized, quantitative, and traceable decision-making basis for engineering design. Attached Figure Description

[0026] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station according to the present invention.

[0028] Figure 2 This is a structural block diagram of a hybrid solid-flexible layout calculation system for a mountain photovoltaic power station according to the present invention. Detailed Implementation

[0029] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0030] In the description of this invention, it should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0031] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0032] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0033] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0034] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0035] Example 1 like Figure 1 As shown, the present invention provides a method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station, comprising: 1. Power plant basic data acquisition and DEM data analysis Collect DEM data, topographic slope and aspect data, ecological red line vector boundaries, geological bearing capacity zoning, wind load zoning, and transportation and construction condition data for the target mountain photovoltaic power station; input equipment parameters such as photovoltaic module parameters, fixed support structure parameters, flexible support span / vertical-to-span ratio / minimum span safety threshold, material unit price, labor unit price, and transportation cost unit price, etc.; complete the site topography grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

[0036] 2. Construction of Adaptive Partition Model for Flexible-Fixed Scaffolds Based on the differences in natural terrain adaptation between fixed and flexible supports, slope-based adaptation rules are established to achieve automatic zoning across the entire area. 1) Fixed support adaptation area: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation area. The terrain has small undulations and the pile foundation construction is convenient. Using fixed supports can significantly reduce material and construction costs. 2) Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone. The advantages of flexible support, such as large span, no need for dense pile foundation, and adaptability to terrain, are utilized to avoid the problems of difficult construction on steep slopes and low installed capacity of fixed support. 3) Solid-Flexible Hybrid Adaptation Zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone, which supports the algorithm to autonomously select the optimal type.

[0037] Further superimposed multidimensional hard constraint boundary conditions include: ecological protection boundary prohibition constraints (based on national and local laws and regulations and planning documents regarding nature reserves, ecological red lines, water resource protection areas, etc.), geological bearing capacity insufficient block elimination constraints (based on geological data and soil borehole data defining landslide risk areas, erosion sensitive areas, etc.), wind load maximum span limit constraints, flexible support minimum span constraints (based on safety boundary conditions such as maximum span, minimum span, and adjacent span angle limits corresponding to different material properties and load conditions), and drainage and ditch avoidance constraints (based on drainage and ditch prohibition areas obtained from DEM model analysis). The final output is three types of functional blocks in the site: fixed support layout area, flexible support layout area, and fixed-flexible hybrid optimization area.

[0038] 3. Construction of a cost model for terrain-coupled rigid-flexible scaffolding Breaking away from the traditional fixed unit price cost model, a terrain complexity coefficient is introduced to establish a full-cycle cost correlation model for fixed supports and a full-cycle cost correlation model for flexible supports that are adapted to mountainous terrain features.

[0039] 1) Cost Coupling Model for Fixed Brackets The cost of fixed supports is determined by the amount of pile foundation work, the number of columns, the density of their arrangement, and the incremental cost of terrain-related construction. A cost function is constructed as follows:

[0040] in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. This represents the unit cost of pile foundation drilling and pouring. The model enables the quantitative calculation of incremental costs for fixed support construction under mountainous terrain conditions.

[0041] 2) Cost Coupling Model for Flexible Scaffolds The construction cost of flexible supports is strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows:

[0042] in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This model addresses the incremental cost of transporting materials in mountainous terrain. It can accurately quantify the actual construction cost of flexible supports in steep slopes, gullies, and complex terrain.

[0043] 3) Power generation benefit correlation model By combining the tilt adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve a coupling match between cost and power generation benefits.

[0044] 4. Optimization of multi-objective model for hybrid solid-flexible arrangement With the goal of maximizing the comprehensive benefits of mountain photovoltaic power stations, a dual-objective optimization model is established to maximize installed capacity and optimize the economic benefits throughout the entire life cycle.

[0045] 1) Objective function Objective 1: Maximize total installed capacity

[0046] Objective 2: Minimize the levelized cost of electricity (LCOE) over the entire lifecycle.

[0047] In the formula: For the installed capacity of the fixed support area; For the installed capacity of the flexible support area; Total construction and operation and maintenance costs for the entire site; This represents the total annual power generation.

[0048] 2) Global constraints This includes: slope and aspect terrain adaptation constraints (fixed support installation is prohibited for slopes > 20°; > 32°). Flexible supports are prohibited on steep slopes, gullies, and landslides; large-scale array arrangements are prohibited on north-facing shady slopes and in areas with a northwest / northeast eccentricity greater than 25°; the height difference between adjacent piles within the same support unit must not exceed the upper limit of the adjustable height of the column; if the difference exceeds this limit, a rigid-flexible zone must be defined, and direct rigid connection across large height differences is prohibited. Constraints on the boundaries of the rigid-flexible zones (end anchors, wind-resistant end columns, and expansion joints must be installed at the connection points; direct anchoring of flexible steel cables to rigid support columns is prohibited; the support type within a single zone must be uniform, and the slope and geological conditions within the zone must be continuous and uniform to avoid drastic topographical undulations); Limits on the length and span of flexible supports (single-layer two-cable flexible (most commonly used in mountainous areas): single span 15m~20m; minimum span ≥12m, maximum strictly prohibited from exceeding 20m; longitudinal column spacing ≤8m; double-layer cable-stayed system: single span 18m~35m; three-layer cable-beam large span (fishing boat / gully crossing): maximum single span ≤60m); Safety threshold for the sag-to-span ratio (ultimate bearing capacity state: 1). 1) Single-layer pure cable: Maximum allowable sag-to-span ratio ≤ 1 / 40 (control limit), recommended ≤ 1 / 50; 2) Double / triple-layer cable system: Maximum sag-to-span ratio ≤ 1 / 50, recommended ≤ 1 / 70; Minimum sag-to-span ratio ≥ 1 / 300, to avoid excessive cable tension and insufficient tensile bearing capacity of columns and anchors), pile foundation bearing capacity constraints (total vertical load of foundation × safety factor (conventional ≥ 1.8) ≤ characteristic value of foundation bearing capacity), ecological restrictions (basic farmland, ecological protection red line, public welfare forest land, water source protection area, river blue line, debris flow / landslide geological disaster hazard area), electrical layout constraints (the orientation and slope of the same MPPT branch string components must be consistent, the strings within the solid-flexible zone are independently divided, and cross-solid-flexible zone series connection is prohibited; DC cables should be laid along the longitudinal direction of the array as much as possible, and the voltage drop of a single DC circuit cable should be ≤ 2%; the maximum service radius of the box transformer should not exceed 500m), unobstructed spacing constraints (based on the local winter solstice 9:00~15:00). For the illumination verification period, calculate the spacing between the front and rear rows of photovoltaic arrays, the lateral spacing between arrays, and the safe distance between the arrays and surrounding tall features (mountains, trees, towers, buildings). The minimum horizontal distance between the arrays and surrounding obstacles must be ≥ obstacle height × 1.5. Construction and maintenance access constraints are also included (to meet the requirements for photovoltaic module inspection, cleaning, equipment maintenance, fault replacement, fire emergency response, and large machinery access, the net width, longitudinal slope, turning radius, and vertical clearance of the main roads, secondary maintenance access routes between arrays, and equipment maintenance platforms are limited, and the space above the access routes is strictly constrained. Main maintenance roads (for fire trucks and engineering vehicles): net road width ≥ 4m, longitudinal slope ≤ 8%, turning radius ≥ 9m; maintenance access routes between arrays: net width of the main longitudinal access route ≥ 2.5m; single-sided maintenance access route ≥ 1.2m; minimum vertical clearance of maintenance access routes under flexible supports ≥ 2.2m; in agricultural photovoltaic complementary areas, this is increased to 3.5-5m according to agricultural machinery operation needs).

[0049] 5. Model Solving and Result Output To address the characteristics of the model, which contains both continuous variables (tilt angle, spacing) and discrete integer variables (support type, number of spans, number of piles), a joint solution strategy combining genetic algorithm and mixed-integer linear programming is adopted. The genetic algorithm performs global optimization to determine the support partition boundaries and overall layout scheme. The mixed-integer linear programming accurately corrects the discrete integer constraints, solving the problems of local optima and unmet integer constraints in single algorithms, and outputs the optimal solid-flexible hybrid layout scheme.

[0050] In addition, the system solves for pure fixed support layout schemes, pure flexible support layout schemes, and hybrid fixed-flexible layout schemes respectively. An evaluation system is established from six dimensions: installed capacity, annual power generation, investment per kilowatt, cost per kilowatt-hour, construction difficulty, and structural safety. The system automatically outputs the ranking of the schemes, providing a quantitative decision-making basis for mountain photovoltaic design.

[0051] Example 2 1. Basic Data Collection: Obtain the site's DEM topographic data. The site has a slope of 0° to 32° and contains numerous undulating areas with gullies, including ecologically restricted areas and areas with varying wind load zones. Input the parameters of the 550W photovoltaic modules, the unit price of the fixed support pile foundation construction, the unit price of the flexible support cable and steel, and the premium coefficients for mountain transportation and labor.

[0052] 2. Terrain-adaptive zoning: Divide the area by slope threshold: 0°~15° is the fixed support adaptation zone; 15°~25° is the solid-flexible hybrid transition zone; 25°~32° is the flexible support exclusive zone; and ecological red line, gully avoidance, and minimum span constraints are superimposed to complete the zoning of the entire site.

[0053] 3. Terrain-coupled cost modeling: The terrain complexity coefficient is calculated grid by grid. Conventional construction costs are used in flat areas, while construction and transportation premiums are automatically added in steep slope and gully areas, generating separate cost models for fixed supports and flexible supports.

[0054] 4. Dual-objective model solution: With the objectives of maximizing installed capacity and minimizing cost per kilowatt-hour, a genetic algorithm and mixed integer linear programming are used to solve the optimal fixed-flexible hybrid scheme: densely deploying fixed supports in flat areas to improve the utilization rate of installed capacity, using large-span flexible supports in steep slope and gully areas to avoid the difficulties of pile foundation construction, and selecting the best option in transition areas.

[0055] 5. Scheme Comparison Results: Compared with the pure fixed support scheme, the mixed-row scheme increases the installed capacity by 9.2% and reduces the construction cost on steep slopes by 18.5%; compared with the pure flexible scheme, the overall unit investment is reduced by 11.3% and the cost per kilowatt-hour is reduced by 8.7%, with the comprehensive benefits being significantly better.

[0056] Example 3 like Figure 2 As shown, the present invention provides a hybrid fixed-flexible layout calculation system for mountain photovoltaic power stations, comprising: Data acquisition unit: Collects basic data of the power station and performs digital elevation model (DEM) data analysis to construct DEM data of the power station area with spatial consistency and computability, including natural terrain slope, aspect, altitude, topographic relief and geological data. The first model construction unit is to construct an adaptive zoning model for fixed and flexible supports. Based on the adaptation differences of natural terrain slope, aspect, altitude, terrain undulation and geological data between fixed and flexible supports, a slope classification adaptation rule is established to achieve automatic zoning of the entire domain, resulting in a fixed support deployment area, a flexible support deployment area and a fixed-flexible hybrid optimization area. The second model construction unit: Based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to the mountainous characteristics are established respectively. The third model construction unit: Based on the fixed support full-cycle cost correlation model, the flexible support full-cycle cost correlation model and the power generation benefit correlation model, a multi-objective model optimization of the fixed and flexible hybrid layout is carried out. With the maximum comprehensive benefit of the mountain photovoltaic power station as the core, a dual-objective optimization model of maximizing installed capacity and optimizing the full life cycle economy is established. Model Solving Unit: Solve the dual-objective optimization model of maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle to obtain an optimized layout scheme for the mixed arrangement of fixed and flexible supports for mountain photovoltaic power stations.

[0057] In the data acquisition unit of this embodiment, the basic data of the power station collected includes: Collect DEM data, topographic slope and aspect data, ecological red line vector boundary, geological bearing capacity zoning, wind load zoning, transportation and construction condition data of the target mountain photovoltaic power station; input equipment parameters; complete the site topographic grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

[0058] In the first model construction unit of this embodiment, an adaptive zoning model for fixed and flexible supports is constructed. Based on the adaptation differences between fixed and flexible supports in terms of natural terrain slope, aspect, altitude, terrain undulation, and geological data, slope classification adaptation rules are established to achieve automatic zoning across the entire domain, including: Fixed support adaptation zone: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation zone; Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone; Solid-flexible hybrid adaptation zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone; Further superimposed multidimensional hard constraint boundary conditions: ecological protection boundary prohibition constraint, geological bearing capacity insufficient block elimination constraint, wind load maximum span limit constraint, flexible support minimum span constraint, and drainage and ditch avoidance constraint, ultimately outputting three types of functional blocks in the site: fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area.

[0059] In the second model construction unit of this embodiment, a terrain-coupled fixed-flexible support cost model is constructed based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to mountainous terrain characteristics are established, including: Fixed scaffolding full-cycle cost correlation model: The cost of fixed scaffolding is determined by the amount of pile foundation work, the number of columns, the arrangement density, and the incremental costs of transportation and construction. A cost function is constructed as follows:

[0060] in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. The unit cost of pile foundation drilling and pouring; The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. A full-cycle cost correlation model for flexible scaffolding reveals that construction costs are strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows:

[0061] in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. Power generation benefit correlation model: Combining the tilt angle adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve the coupling and matching of cost and power generation benefits.

[0062] Example 4 The present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station.

[0063] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] This application is described with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0065] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0066] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0067] The key technical points of this invention are as follows: 1. It pioneered a fixed-flexible adaptation rule based on slope grading and multi-dimensional boundary constraints, which automatically divides the fixed zone, flexible zone and mixed transition zone, completely eliminating the reliance on manual experience and achieving precise matching between the support type and the terrain conditions; 2. Establish a differentiated cost function for fixed and flexible supports that adapts to the undulations, gullies, and construction difficulties of mountainous terrain, and solve the problem of distortion in the traditional cost calculation of plains quotas.

[0068] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0069] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station, characterized in that, include: 1) Collect basic data of the power station and perform digital elevation model (DEM) data analysis to construct DEM data of the power station range with spatial consistency and computability, including natural terrain slope, aspect, elevation, topographic relief and geological data. 2) Construct an adaptive zoning model for fixed and flexible supports. Based on the adaptation differences of natural terrain slope, aspect, altitude, terrain undulation and geological data between fixed and flexible supports, establish slope classification adaptation rules to achieve automatic zoning of the entire area and obtain fixed support deployment area, flexible support deployment area and fixed-flexible hybrid optimization area. 3) Based on the fixed support deployment area, flexible support deployment area and fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model and a power generation benefit correlation model adapted to mountain characteristics are established respectively. 4) Based on the fixed support full-cycle cost correlation model, the flexible support full-cycle cost correlation model and the power generation benefit correlation model, a multi-objective model optimization of the fixed-flexible hybrid layout is carried out. With the maximum comprehensive benefit of the mountain photovoltaic power station as the core, a dual-objective optimization model of maximizing installed capacity and optimizing the full life cycle economy is established. 5) Solve the dual-objective optimization model of maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle to obtain an optimized layout scheme for the mixed arrangement of fixed and flexible supports for mountain photovoltaic power stations.

2. The method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station according to claim 1, characterized in that, In step 1), the collection of basic power station data includes: Collect DEM data, topographic slope and aspect data, ecological red line vector boundary, geological bearing capacity zoning, wind load zoning, transportation and construction condition data of the target mountain photovoltaic power station; input equipment parameters; complete the site topographic grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

3. The method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station according to claim 1, characterized in that, In step 2), an adaptive zoning model for fixed and flexible supports is constructed. Based on the adaptation differences between fixed and flexible supports in terms of natural terrain slope, aspect, altitude, topographic relief, and geological data, slope classification adaptation rules are established to achieve automatic zoning across the entire region, including: Fixed support adaptation zone: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation zone; Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone; Solid-flexible hybrid adaptation zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone; Further superimposed multidimensional hard constraint boundary conditions: ecological protection boundary prohibition constraint, geological bearing capacity insufficient block elimination constraint, wind load maximum span limit constraint, flexible support minimum span constraint, and drainage and ditch avoidance constraint, ultimately outputting three types of functional blocks in the site: fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area.

4. The method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station according to claim 1, characterized in that, In step 3), based on the fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and lifecycle cost correlation models for fixed supports, flexible supports, and power generation benefit correlation models adapted to mountainous terrain characteristics are established, including: Fixed scaffolding full-cycle cost correlation model: The cost of fixed scaffolding is determined by the amount of pile foundation work, the number of columns, the arrangement density, and the incremental costs of transportation and construction. A cost function is constructed as follows: in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. The unit cost of pile foundation drilling and pouring; The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. A full-cycle cost correlation model for flexible scaffolding reveals that construction costs are strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows: in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. Power generation benefit correlation model: Combining the tilt angle adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve the coupling and matching of cost and power generation benefits.

5. The method for calculating the hybrid solid-flexible layout of a mountain photovoltaic power station according to claim 1, characterized in that, In step 4), the multi-objective model optimization of the hybrid solid-flexible layout is carried out. With the goal of maximizing the overall benefits of the mountain photovoltaic power station, a dual-objective optimization model is established, maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle. This includes: The objective function includes: Objective 1: Maximize total installed capacity Objective 2: Minimize the levelized cost of electricity (LCOE) over the entire lifecycle. In the formula: For the installed capacity of the fixed support area; For the installed capacity of the flexible support area; The total cost of construction and operation and maintenance for the entire site; Total annual power generation; Global constraints include: slope and aspect terrain adaptation constraints, solid-flexible zone boundary constraints, flexible support length and span limits, pile foundation bearing capacity constraints, ecological prohibition constraints, electrical layout constraints, unobstructed spacing constraints, and construction and maintenance access constraints.

6. A calculation system for the hybrid solid-flexible layout of a mountain photovoltaic power station, characterized in that, include: Data acquisition unit: Collects basic data of the power station and performs digital elevation model (DEM) data analysis to construct DEM data of the power station area with spatial consistency and computability, including natural terrain slope, aspect, altitude, topographic relief and geological data. The first model construction unit is to construct an adaptive zoning model for fixed and flexible supports. Based on the adaptation differences of natural terrain slope, aspect, altitude, terrain undulation and geological data between fixed and flexible supports, a slope classification adaptation rule is established to achieve automatic zoning of the entire domain, resulting in a fixed support deployment area, a flexible support deployment area and a fixed-flexible hybrid optimization area. The second model construction unit: Based on the fixed support deployment area, the flexible support deployment area, and the fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and a fixed support full-cycle cost correlation model, a flexible support full-cycle cost correlation model, and a power generation benefit correlation model adapted to the mountainous characteristics are established respectively. The third model construction unit: Based on the fixed support full-cycle cost correlation model, the flexible support full-cycle cost correlation model and the power generation benefit correlation model, a multi-objective model optimization of the fixed and flexible hybrid layout is carried out. With the maximum comprehensive benefit of the mountain photovoltaic power station as the core, a dual-objective optimization model of maximizing installed capacity and optimizing the full life cycle economy is established. Model Solving Unit: Solve the dual-objective optimization model of maximizing installed capacity and optimizing the economic efficiency throughout the entire life cycle to obtain an optimized layout scheme for the mixed arrangement of fixed and flexible supports for mountain photovoltaic power stations.

7. The hybrid fixed-flexible layout calculation system for a mountain photovoltaic power station according to claim 6, characterized in that, The data acquisition unit collects basic power plant data including: Collect DEM data, topographic slope and aspect data, ecological red line vector boundary, geological bearing capacity zoning, wind load zoning, transportation and construction condition data of the target mountain photovoltaic power station; input equipment parameters; complete the site topographic grid subdivision, calculate the topographic complexity coefficient for each grid, and characterize the degree of undulation and construction difficulty of the block.

8. The hybrid fixed-flexible layout calculation system for a mountain photovoltaic power station according to claim 6, characterized in that, In the first model construction unit, an adaptive zoning model for fixed and flexible supports is built. Based on the adaptation differences between fixed and flexible supports in terms of natural terrain slope, aspect, altitude, topographic relief, and geological data, slope classification adaptation rules are established to achieve automatic zoning across the entire region, including: Fixed support adaptation zone: The gentle slope of 15°≤slope<25° is defined as the fixed support adaptation zone; Flexible support adaptation zone: The terrain with a slope of ≥25° and a gully span of more than 3m is defined as the flexible support adaptation zone; Solid-flexible hybrid adaptation zone: The intermediate transition slope transition zone is the solid-flexible hybrid adaptation zone; Further superimposed multidimensional hard constraint boundary conditions: ecological protection boundary prohibition constraint, geological bearing capacity insufficient block elimination constraint, wind load maximum span limit constraint, flexible support minimum span constraint, and drainage and ditch avoidance constraint, ultimately outputting three types of functional blocks in the site: fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area.

9. A hybrid fixed-flexible layout calculation system for a mountain photovoltaic power station according to claim 6, characterized in that, In the second model construction unit, based on the fixed support deployment area, flexible support deployment area, and fixed-flexible hybrid optimization area, a terrain-coupled fixed-flexible support cost model is constructed. A terrain complexity coefficient is introduced, and corresponding full-cycle cost correlation models for fixed supports, flexible supports, and power generation benefit correlation models adapted to mountainous terrain characteristics are established, including: Fixed scaffolding full-cycle cost correlation model: The cost of fixed scaffolding is determined by the amount of pile foundation work, the number of columns, the arrangement density, and the incremental costs of transportation and construction. A cost function is constructed as follows: in: To determine the total number of fixed support piles; This refers to the amount of work involved in the bracket installation. This represents the terrain complexity coefficient. The unit cost of pile foundation drilling and pouring; The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. A full-cycle cost correlation model for flexible scaffolding reveals that construction costs are strongly correlated with the number of spans, the total length of the span, and the difficulty of construction due to terrain undulations. A cost function is constructed as follows: in: The total length of the flexible support under tension; To continuously deploy the number of spans; This is the terrain complexity coefficient; the greater the terrain undulation, the higher the value. This refers to the unit cost of steel cables and main steel materials. The unit price for labor costs in mountainous construction; This will increase the cost of transporting materials from mountainous areas. Power generation benefit correlation model: Combining the tilt angle adjustment capability and slope adaptability of different support types, a correlation model between block irradiation reception and power generation is established to achieve the coupling and matching of cost and power generation benefits.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the calculation method for the solid-flexible hybrid layout of a mountain photovoltaic power station according to any one of claims 1-5.

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