Systematic collaborative design method for mountainous agro-forestry complementary photovoltaic power station

Abstract

The application relates to a systematic collaborative design method and system for a mountainous agricultural and forestry complementary photovoltaic power station, characterized in that the method is executed in the following order of steps, and subsequent steps accept the output of previous steps and are iteratively optimized: S1: top-level planning and selection: based on a digital elevation model of a project site area, a land use type map and information of a legacy component to be utilized, S2: refined electrical design and array arrangement, S3: differentiated structural system design, S4: system integration and verification: integrating all design results of S1 to S3, performing global shadow simulation and economic review, and based on the results, iteratively optimizing the previous steps until a final scheme satisfying all constraints is obtained. According to the application, a systematic collaborative design method for a mountainous agricultural and forestry complementary photovoltaic power station realizes real systematic collaborative design, and the output scheme is globally optimal and naturally compliant.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic power generation system engineering and design methods, and in particular relates to a method for the whole system, multi-objective collaborative optimization design of mountain photovoltaic power stations with complex terrain and the need to meet specific agricultural and forestry policy constraints, from macro planning, equipment selection, array layout to structural foundation. Background Technology

[0002] With the promotion of the "photovoltaic+" composite model, photovoltaic projects that complement agriculture and forestry in mountainous areas are increasing. These projects integrate energy production and agricultural production, but face unprecedented challenges of complexity: 1) Complex natural conditions: The undulating mountainous terrain makes solar radiation analysis, shadow calculation, and engineering layout difficult; 2) Superimposed policy constraints: It is necessary to simultaneously meet the technical specifications for photovoltaic power generation and the special regulations for agricultural and forestry production, such as minimum ground clearance and array spacing; 3) Multiple economic objectives: It is necessary to pursue multiple objectives such as the lowest cost per kilowatt-hour, the highest land use efficiency, and the utilization of specific assets (such as disposing of legacy components) while meeting the above constraints; 4) Strong coupling of engineering and technology: Component selection affects electrical design, array layout affects basic engineering, and decisions at each stage are interconnected.

[0003] Existing photovoltaic power plant design processes are typically linear and modular, involving sequential or independent completion of resource assessment, equipment selection, electrical design, site layout, and structural design. This "serial" design model struggles to handle the aforementioned multi-dimensional and tightly coupled complex constraints. For example, an electrical engineer might determine a string configuration based on standard meteorological data, but this configuration may not be suitable for a locally colder depression; a site layout engineer might arrange the arrays at the technically optimal spacing, but this might violate local agricultural and forestry policies. This leads to repeated design revisions, often resulting in a suboptimal solution achieved through compromises, failing to fully realize the project's potential, and even posing technical or policy compliance risks. Summary of the Invention

[0004] The core technical problem to be solved by this invention is to overcome the limitations of existing linear and modular design methods and provide a systematic and collaborative design method that can integrate and collaboratively optimize multiple complex factors such as mountainous terrain, agricultural and forestry policies, economic objectives and engineering practices, thereby generating a globally optimal, safe, compliant and implementable overall technical solution for mountainous agricultural and forestry complementary photovoltaic power stations.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] A systematic collaborative design method for photovoltaic power stations integrating agriculture and forestry in mountainous areas is characterized by following the core principles of "global planning guidance, multi-factor coupling analysis, and differentiated collaborative design," and executing the following steps in sequence, with subsequent steps iteratively adjusted based on the optimization results of previous steps:

[0007] Step 1: Component Selection and System Capacity Top-Level Planning Based on Multiple Constraints This step aims to address the top-level questions of "what to use" and "how much to use." First, input the project boundary conditions, including the intended total construction scale, available land boundary, detailed digital elevation model, land use type map (clearly defining gardens, grasslands, etc.), information on legacy components to be absorbed, and a database of mainstream market components. Next, perform a dual analysis:

[0008] Economic and technical comparison: Establish a levelized cost of electricity (LCOE) analysis model. Using land surface type (e.g., grassland, woodland) as a key input, and by querying historical data mapping tables, quantitatively evaluate the expected back-side power generation gain of bifacial modules under these surface conditions. By comprehensively comparing the initial investment and life-cycle power generation returns of different models (e.g., P-type / N-type), different power levels, and single / bifacial modules, select the optimal module model that minimizes the LCOE (e.g., N-type bifacial 575Wp module).

[0009] Policy and Site Compatibility Analysis: Based on the land use map, apply the corresponding minimum ground clearance constraints (e.g., garden ≥ 2.5 meters, grassland ≥ 2.0 meters). Use these height constraints as a rigid input for subsequent support and foundation design. Simultaneously, if legacy components exist, consider designating a separate "digestion zone" for them during the master plan phase, physically separating it from the main area using new components, thus laying the foundation for subsequent differentiated design.

[0010] System capacity ratio optimization: Based on the selected component models and constrained by the simulation of unobstructed array arrangement, a system economic model under different capacity ratios is constructed. Through simulation calculations, the capacity ratio that optimizes the cost per kilowatt-hour for the entire station (e.g., 1:1.25) is selected to determine the matching relationship between the DC and AC capacity of the entire station.

[0011] Step 2: Refined Electrical Design and Array Generation Coupling Microclimate and Topography

[0012] This step aims to address the questions of "how to make electrical connections" and "how to arrange the space" and to achieve their synergy.

[0013] Refined string design: Weather station data is corrected for localized microclimates in mountainous areas. For regions prone to cold air accumulation, such as mountain depressions, lower extreme low-temperature values ​​are used to calculate the string series connection number, ensuring safe open-circuit voltage at low temperatures. For different zones (such as the main zone and the zone for disposing of legacy modules), the optimal series connection number is calculated independently based on the electrical parameters of each module, ensuring that their operating voltages remain within the MPPT (Multi-Level Testing) high-efficiency range of their respective inverters.

[0014] Automatic generation of variable-spacing arrays: Using a digital elevation model, component dimensions, installation tilt angle, and the minimum ground clearance determined in step one as input, and meeting the technical constraint of ensuring unobstructed views during the winter solstice period, and adhering to the legal constraint of the minimum spacing stipulated by local policy, the theoretical minimum spacing at each location point is dynamically calculated along the layout direction. The larger value is then taken from the theoretical minimum spacing and the policy spacing, resulting in a series of discrete "final spacing points." A continuous and smooth "variable-spacing curve" is generated through curve fitting, and the photovoltaic array is automatically arranged on the three-dimensional terrain based on this curve, generating a refined layout scheme that simultaneously meets technical safety and policy compliance requirements.

[0015] Step 3: Load Iteration and Differentiated Structural System Design

[0016] This step aims to address the question of "how to provide secure support," and its design is directly derived from the output of the preceding steps.

[0017] Refined wind load calculation: Based on the 3D array layout model generated in step two, the specific terrain location (mountain top, hillside, gully) of each support unit is identified. Wind load correction coefficients are introduced according to the terrain category to perform differentiated wind load calculations, especially strengthening the design values ​​for high-wind-risk areas such as mountain tops.

[0018] Differentiated support foundation design: The ground clearance determined in step one is used as the design basis for the free section length of the support. Based on the differentiated wind loads calculated in step three, the bending moment and uplift force at the base of each support column are calculated. Based on these mechanical requirements and combined with geological survey data, appropriate specifications and lengths of prestressed concrete pipe pile foundations are selected for different areas. For example, for hilltop areas 2.5 meters above ground, longer and higher-specification PHC piles are used; for gentle slope areas 2.0 meters above ground, a more economical pile type and length are adopted.

[0019] Step 4: System-wide integrated verification and economic feasibility review

[0020] This step aims for closed-loop verification and optimization. All design deliverables generated in steps one through three—including equipment lists, layout coordinates, and basic models—are integrated to form a complete digital model of the power plant. This model is then subjected to year-round shaded simulation verification, and the total investment and expected power generation of the system are recalculated. These are then substituted into the levelized cost of electricity (LCOE) model for a final economic review. If the results do not meet expectations, feedback can be provided to the aforementioned steps for parameter fine-tuning and iterative optimization until the optimal stable solution satisfying all constraints is obtained.

[0021] A systematic collaborative design system for implementing any of the above steps, characterized in that it comprises:

[0022] The planning and selection module is used to execute step one, integrating geographic information, component database, and economic model;

[0023] The electrical layout module is used to execute step two, integrating microclimate analysis, string calculation, and three-dimensional automatic layout algorithm;

[0024] The structural design module is used to execute step three, integrating load analysis and foundation selection design tools.

[0025] The integrated verification module is used to perform step four, which involves system integration, simulation, and optimization iteration.

[0026] Compared with the prior art, the technical solution provided by the embodiments of the present invention can achieve at least the following beneficial effects:

[0027] It achieves true systematic collaborative design: breaking down traditional professional barriers, it tightly couples and iterates professional designs such as resource assessment, electrical, general layout, and structure under a unified framework and process, solving the global optimization problem under complex constraints.

[0028] The output solution is globally optimal and inherently compliant: By incorporating factors such as agricultural and forestry policies and microclimates into the design algorithm, the generated solution is ensured to simultaneously meet the requirements of technical optimization, economic efficiency, and policy compliance from the outset, thus avoiding major design changes in the later stages.

[0029] The design process is refined and quantified: dynamic calculations based on terrain data replace empirical estimations, and quantitative gains based on mapping relationships replace subjective judgments, greatly improving the scientific nature, accuracy, and repeatability of the design.

[0030] Significantly improve design efficiency and quality: Through process integration and automated calculation, it reduces repetitive work and human error, shortens the design cycle, and can generate refined solutions such as "variable spacing" that are difficult to achieve with traditional methods and perfectly fit the terrain.

[0031] It has broad applicability and promotional value: This methodology is not only applicable to mountain agroforestry complementary projects, but its systematic and multi-factor coupling design concept can also provide a reference paradigm for the design of photovoltaic projects in other complex terrains (such as hills and water surfaces) or with special constraints (such as ecological red lines and cultural relic protection). Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the invention, not all embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] Unless otherwise defined, the technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in the specification and claims of this patent application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an” or “a” and similar terms do not indicate a limitation of quantity, but rather indicate the presence of at least one.

[0034] A 124MW forest-solar / grassland-solar complementary photovoltaic power station project is located in the Loess Hilly Area and needs to utilize 32,708 leftover P-type 545Wp modules.

[0035] Step 1:

[0036] Input the site DEM and land use type map (garden, grassland). Through surface type matching, the overall gain of the bifacial component in grassland and sparse woodland is evaluated to be approximately 8.4%.

[0037] Based on the comparison of longitude-based electricity cost models, the N-type bifacial 575Wp module was determined to be the new module with the best economic performance.

[0038] According to the policy, the minimum height above ground is set at 2.5 meters in park areas and 2.0 meters in grass areas.

[0039] Plan an independent area to digest legacy components.

[0040] Through volume ratio simulation, 1.25 was determined to be the optimal value.

[0041] Step 2:

[0042] The number of strings in series was calculated for both the legacy digestion area and the main area of ​​the new components. For the array located in the depression, the extreme low temperature correction was set to -29°C, and the number of strings in series was calculated to be 26.

[0043] Based on the DEM, a 28° tilt angle, and policy constraints of 8 meters (garden) / 6.5 meters (grassland net distance), the array spacing is dynamically calculated. The system automatically generates array layout diagrams with continuously varying spacing between 8 meters and 20.4 meters.

[0044] Step 3:

[0045] For arrays positioned on mountaintops, wind loads are multiplied by a correction factor of 1.3.

[0046] For the support structure in the garden area 2.5 meters above the ground, based on the increased wind load calculation, PHC300-70-AB piles with a length of 6.0 meters (3.0 meters free section) are selected. For the grassy area 2.0 meters above the ground, similar calculations are performed, and piles of the same type with a length of 5.0 meters (2.5 meters free section) are selected.

[0047] Step 4:

[0048] Integrating all designs, a digital twin model of the power plant was established. Shaded simulation and LCOE verification were performed, confirming that the levelized cost of electricity (LCOE) was 0.3056 yuan / kWh, meeting the requirements, and the scheme was finalized.

[0049] Through the above steps, this invention successfully generated an optimal overall solution integrating technology, economics, and policy for this complex project.

[0050] A systematic collaborative design system for implementing any of the above steps, characterized in that it comprises:

[0051] The planning and selection module is used to execute step one, integrating geographic information, component database, and economic model;

[0052] The electrical layout module is used to execute step two, integrating microclimate analysis, string calculation, and three-dimensional automatic layout algorithm;

[0053] The structural design module is used to execute step three, integrating load analysis and foundation selection design tools.

[0054] The integrated verification module is used to perform step four, which involves system integration, simulation, and optimization iteration.

[0055] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

Claims

1. A systematic collaborative design method for agroforestry complementary photovoltaic power stations in mountainous areas, characterized in that, The method is executed in the following sequence of steps, with subsequent steps accepting the output of preceding steps and performing iterative optimization: S1: Top-level Planning and Selection: Based on the digital elevation model of the project site, land use type map, and information on legacy components to be utilized, the following sub-steps are performed: S1.1: Determine the minimum ground clearance constraint for photovoltaic modules according to the land use type; S1.2: Based on the mapping relationship between surface type and bifacial power generation gain, evaluate the expected gain of bifacial modules and determine the optimal photovoltaic module model through comparison using the levelized cost of electricity (LCOE) model; S1.3: Plan the physical zoning of the main area for new modules and the area for utilizing legacy components; S1.4: With the constraint of unobstructed layout, through... S1: Economic simulation to determine the optimal capacity ratio of the power plant; S2: Refined electrical design and array layout: Based on the output of S1, the following sub-steps are performed: S2.1: Extreme temperature correction is performed for the mountain microclimate, and the optimal number of photovoltaic strings in series is calculated for each region; S2.2: Using the digital elevation model, component size, installation tilt angle, and ground clearance determined in S1.1 as inputs, and taking the preset no-shading condition as a technical constraint and the statutory minimum spacing corresponding to the land use type as a policy constraint, a variable spacing three-dimensional layout scheme for the photovoltaic array is dynamically calculated and generated; S3: Differentiated Structural System Design: Based on the layout scheme generated in S2, the following sub-steps are performed: S3.1: Perform differentiated wind load calculations according to the terrain location of the array units; S3.2: Using the ground clearance determined in S1.1 and the wind load calculated in S3.1 as the main inputs, design the photovoltaic support and prestressed concrete pipe pile foundation in a differentiated manner; S4: System Integration and Verification: Integrate all design results from S1 to S3, perform global shadow simulation and economic verification, and iteratively optimize the aforementioned steps based on the results until a final scheme that meets all constraints is obtained; exist In step S2.2, the specific process of generating a variable spacing 3D layout scheme includes: calculating the theoretical minimum spacing of each layout point, taking the larger value of the theoretical minimum spacing and the policy spacing to obtain the final spacing point set, fitting and generating a variable spacing curve, and automatically completing the component layout on the 3D terrain according to this curve.

2. The method according to claim 1, characterized in that, In step S1.2, the objects of the cost-per-kilowatt-hour model comparison include photovoltaic module solutions of different technology types, power levels and single- or double-sided types.

3. The method according to claim 1, characterized in that, In step S2.1, the terrain of mountain depressions or basins is negatively corrected for extreme low temperatures.

4. The method according to claim 1, characterized in that, In step S3.2, for areas with higher minimum ground clearance, the length and specifications of the free section of the prestressed concrete pipe pile foundation shall not be lower than those of the foundation in the area with lower ground clearance.

5. A systematic collaborative design system for implementing the method according to any one of claims 1-4, characterized in that, include: The planning and selection module is used to execute step S1, integrating geographic information, component database, and economic model; The electrical layout module is used to execute step S2 and integrates microclimate analysis, string calculation and three-dimensional automatic layout algorithm; The structural design module is used to execute step S3 and integrates load analysis and foundation selection design tools. The integrated verification module is used to execute step S4, which involves system integration, simulation, and optimization iteration.