Multi-objective collaborative optimization photovoltaic inclination angle determination method

Abstract

The invention relates to the technical field of photovoltaic power generation system optimization, in particular to a multi-objective collaborative optimization photovoltaic dip angle determination method, which comprises the following steps of: calculating solar radiation intensity received by a photovoltaic module based on a sun trajectory algorithm by collecting resource data, engineering parameters, terrain correction parameters and economic parameters; the assembly spacing and the land utilization rate are optimized in combination with full-time shadow analysis, and the minimum value of the occupied area is determined; a dynamic weight distribution strategy is adopted, factors such as power generation capacity, land rent and operation cost are coupled to calculate annual income, and the optimal photovoltaic dip angle is solved through a segmented iterative algorithm with the purpose of maximizing the total investment internal return rate (IRR). According to the method, collaborative optimization of land resource utilization and economic benefits can be realized, and a scientific dip angle decision basis is provided for photovoltaic projects with different land costs and topographic conditions.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic power generation system optimization technology, specifically relating to a method for determining the photovoltaic tilt angle through multi-objective collaborative optimization. Background Technology

[0002] Existing photovoltaic tilt angle design methods typically only consider the amount of solar radiation received at the ground, using latitude, solar radiation, and direct irradiance as factors, and taking power generation as the objective function to obtain the maximum power generation tilt angle as the optimal tilt angle. This method has significant drawbacks: (1) Limitations of single-factor optimization: Traditional algorithms (such as the fixed tilt angle method and the latitude-based empirical formula method) only aim to maximize annual power generation, ignoring key economic factors such as land rent, component spacing, and shading. For example, when a power plant in a plain adopts a fixed tilt angle of 35°, the annual power generation increases by 5%, but the land utilization rate decreases by 20% due to the excessive shading distance between the front and rear rows, resulting in a 3% decrease in the overall investment return rate. (2) Serious waste of land resources: Existing technologies have not established a quantitative relationship between tilt angle and land utilization rate. In areas with high land rent (such as the eastern coastal areas where the rent reaches 10 yuan / m² / year), unreasonable tilt angle design will lead to a 15% to 20% decrease in the installed capacity per unit land and an increase in annual land cost of more than 2 million yuan / megawatt. (3) Lack of multi-factor coupling modeling: The interaction effects of solar radiation, component layout and land rent have not been effectively modeled. For example, in slope photovoltaic projects, although increasing the tilt angle improves the utilization rate of direct radiation, it will aggravate the shading of the rear components. It is necessary to dynamically balance the optimal combination of tilt angle and spacing.

[0003] In view of this, the present invention is hereby proposed. Summary of the Invention

[0004] To address the aforementioned technical problems in existing technologies, this invention provides a multi-objective collaborative optimization method for determining photovoltaic tilt angle. This method comprehensively considers factors such as solar radiation, land utilization rate, and land rent, and is applicable to the design and optimization of centralized photovoltaic power plants, distributed photovoltaic systems, and photovoltaic projects in complex terrain. Through multi-objective collaborative optimization, it improves the project's rate of return on investment and saves land resources.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows: A multi-objective collaborative optimization method for determining photovoltaic tilt angle includes: S1. Collect basic data, which includes at least solar radiation data, engineering parameters, land rent data, and topographic data; S2. Based on the terrain data, determine the slope correction coefficient and the aspect correction coefficient, and construct a solar trajectory model in combination with solar radiation data to calculate the solar radiation intensity received by the photovoltaic module. S3. Based on the digital elevation model and the solar motion trajectory model, conduct all-time shadow analysis, and perform quantitative calculations by coupling the number of photovoltaic module strings, the spacing of photovoltaic arrays, the installed capacity density and the land utilization rate to obtain the minimum land area and the corresponding power generation. S4. Based on the land rent data, classify the rent levels, allocate the optimization weights of land utilization rate and power generation according to the level, calculate the annual income by combining the minimum land area and power generation, and iteratively solve the problem with the internal rate of return on total investment as the objective to determine the optimal photovoltaic tilt angle.

[0006] Furthermore, the solar radiation intensity includes: solar radiation intensity with shading and solar radiation intensity without shading; The formula for calculating the solar radiation intensity under unobstructed conditions is as follows:

[0007] in, This represents the amount of direct solar radiation. This represents the amount of solar diffuse radiation. This represents the amount of solar radiation reflected. The installation tilt angle of the photovoltaic modules;

[0008] in, , Both of these can be found on the website of the National Meteorological Information Center. For ground reflectivity, The angle of incidence of sunlight; The formula for calculating the intensity of solar radiation under shading is as follows:

[0009]

[0010] in, This is the ratio of the direct solar radiation heat on the surface of the photovoltaic panel to the direct solar radiation heat obtained without shading during a certain period. Indicates time, This is a time-dependent occlusion coefficient.

[0011] Furthermore, the specific parameters for the number of coupled photovoltaic module strings, photovoltaic array spacing, installed capacity density, and land utilization rate in step S3 are as follows: Assume the total installed capacity of the system is The capacity of a single photovoltaic module is The number of component strings ; Installed capacity per unit area ,in For the number of photovoltaic modules, Rated power of a single component For the area occupied; by establishing The quadratic function relationship between the photovoltaic tilt angle and the array spacing constraint is used to solve for maximizing land utilization. Minimum value.

[0012] Furthermore, the full-time shadow analysis in step S3 specifically includes: Twelve typical days throughout the year were selected, and the shadow range at each time from 09:00 to 15:00 local true solar time was calculated for each typical day. The maximum value of the minimum spacing at all times was taken as the minimum spacing of the photovoltaic array to avoid power generation loss caused by seasonal shading.

[0013] Furthermore, the rules for determining the slope correction coefficient are as follows: The value is dynamically determined based on the terrain slope (0°-30°), ranging from 0.7 to 0.95. For every 5° increase in slope, θ... s Decrease by 0.05; the slope correction factor α s The value is determined by the following rules: 0.8-1.2 based on the angle between the slope direction and the due south direction (0°-±90°), 0.8-1.0 for east / west slopes, and 1.2 for due south slopes.

[0014] Furthermore, the step S4, which involves classifying rent levels based on land rent data and allocating optimization weights according to these levels, specifically involves: In high-rent areas, the optimization weight for land utilization is set to 0.6, and the optimization weight for power generation is set to 0.4. In low-rent areas, the optimization weight for land utilization is set to 0.4, and the optimization weight for power generation is set to 0.6. In the medium-rent zone, the weights of both are set to 0.5.

[0015] Further, in step S4, the annual income is calculated. The specific formula is as follows:

[0016] in, For power generation, Based on local electricity prices, For the operating costs of photovoltaic power plants, This represents the total installed capacity of the system. To minimize the area occupied, For land rent, This is the rent sensitivity coefficient. Land utilization rate.

[0017] Furthermore, step S4, which iteratively solves for the internal rate of return on total investment as the objective, specifically includes: Initial screening stage: Calculate the internal rate of return for different tilt angles with a step size of 5°, and lock in the tilt angle range with the optimal internal rate of return; Calculation phase: Within the locked interval, the precise value of IRR is calculated using hourly power generation data from Pvsyst software with a step size of 0.5°. Convergence condition: The iteration stops when the difference in internal rate of return between adjacent tilt angles is less than 0.01%, and the tilt angle at this point is the optimal photovoltaic tilt angle.

[0018] Furthermore, the method for calculating the minimum footprint of the photovoltaic module in step S3 includes the following sub-steps: S31. Based on the digital elevation model and solar trajectory algorithm, establish a three-dimensional shadow analysis model to calculate the minimum module spacing under different photovoltaic module tilt angles. The specific formula is as follows:

[0019] in, The solar altitude angle at noon on the winter solstice. For the length of the photovoltaic module, This is the lowest point of the component above the ground (in meters), with a default value of 0.5 meters. This is the slope correction factor. The installation tilt angle of the photovoltaic modules; S32. According to the "Design Code for Photovoltaic Power Stations", ensure that the photovoltaic modules do not shade each other during the local true solar time period from 09:00 to 15:00 every day. Calculate the photovoltaic array spacing S using the following formula:

[0020] in, The latitude of the location of the photovoltaic project; S33. Calculate the floor area based on the number, size, and reserved spacing of photovoltaic module strings. Minimum value: Let the size of the photovoltaic module string be... , Let P be the width of the photovoltaic module, P be the capacity of a single photovoltaic module, and P be the total installed capacity of the system. The number of photovoltaic module strings Installed capacity per unit area ,in For the number of photovoltaic modules, Rated power of a single component To accommodate the floor space; allow sufficient space on both sides for the photovoltaic modules. Furthermore, it is required that the lowest point of the photovoltaic module be 0.5 meters above the ground; The area The calculation formula is:

[0021] in, denoted as , where m is the number of photovoltaic module strings arranged front to back, and m is the number of photovoltaic module strings arranged left to right.

[0022] Furthermore, the formula for calculating the power generation in step S3 is as follows:

[0023] in, This represents the theoretical annual power generation of the photovoltaic power station. The amount of solar radiation received by the inclined surface; Solar irradiance under standard test conditions; This is the overall efficiency coefficient of the photovoltaic power generation system.

[0024] Compared with existing technologies, the multi-objective collaborative optimization method for determining photovoltaic tilt angle provided by this invention includes: collecting resource data, engineering parameters, terrain correction parameters, and economic parameters; calculating the solar radiation intensity received by photovoltaic modules based on a solar trajectory algorithm; optimizing module spacing and land utilization rate by combining all-time shading analysis to determine the minimum land area; and employing a dynamic weight allocation strategy to couple factors such as power generation, land rent, and operating costs to calculate annual returns, aiming to maximize the internal rate of return (IRR) of total investment, and solving for the optimal photovoltaic tilt angle through a piecewise iterative algorithm. This invention can achieve synergistic optimization of land resource utilization and economic returns, providing a scientific basis for tilt angle decision-making for photovoltaic projects with different land costs and terrain conditions. Attached Figure Description

[0025] Figure 1 A flowchart of a photovoltaic tilt angle determination method provided in an embodiment of the present invention. Detailed Implementation

[0026] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0027] It should be noted that, unless otherwise specifically stated, the relative arrangement and numerical expressions of the components and steps described in these embodiments should not be construed as limiting the scope of the invention.

[0028] The following description of exemplary embodiments is merely illustrative and is not intended to limit the invention or its application or use in any way. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but where applicable, such techniques, methods, and apparatus should be considered part of this specification.

[0029] Example 1 See Figure 1 , Figure 1 This is a flowchart of a multi-objective collaborative optimization method for determining photovoltaic tilt angle proposed in this invention. Specific steps may include: S1. Collect basic data, which includes at least solar radiation data (direct / scattered irradiance, sunshine duration), engineering parameters (resolution ≤ 1m), land rent data (accuracy to the plot level) and topographic data. Engineering parameters include: component dimensions (length × width), support structure parameters (minimum spacing coefficient between front and rear rows), and investment cost parameters (component unit price, operation and maintenance rate). Topographic data includes: slope correction factor ( ) and aspect correction factor ( Among them, the slope correction factor The value is dynamically set (0.7–0.95) based on the terrain slope (0°–30°). For every 5° increase in slope, Decrease by 0.05; Aspect correction factor The value is taken as (0.8-1.2) based on the angle between the slope aspect and the due south direction (0°~±90°), with 0.8~1.0 for east / west slopes and 1.2 for due south slopes.

[0030] S2. Radiation intensity calculation: Based on the terrain data, determine the slope correction coefficient and aspect correction coefficient, and construct a solar motion trajectory model in combination with solar radiation data to calculate the solar radiation intensity received by the photovoltaic module. The solar trajectory model is determined by the following formula:

[0031]

[0032] in, The azimuth of the sun. The total number of days the sun shines on a given day in a year. Solar hour angle, The solar altitude angle, The latitude is the local latitude.

[0033] The solar radiation received on the Earth's surface consists of direct solar radiation, diffuse solar radiation, and reflected solar radiation. Solar radiation intensity includes both the intensity of solar radiation under obstruction and the intensity of solar radiation without obstruction. The formula for calculating the solar radiation intensity under unobstructed conditions is as follows:

[0034] in, This represents the amount of direct solar radiation. This represents the amount of solar diffuse radiation. This represents the amount of solar radiation reflected. The installation tilt angle of the photovoltaic modules;

[0035] in, , Both of these can be found on the website of the National Meteorological Information Center. For ground reflectivity, The angle of incidence of sunlight; Regarding the amount of radiation received by photovoltaic panels, there is an influence of direct irradiance, which represents the ratio of direct solar radiation heat received on the surface of the photovoltaic panel to the direct solar radiation heat received without shading within a certain period (day or year). Specifically, it is defined as:

[0036] in, This is the ratio of the direct solar radiation heat on the surface of the photovoltaic panel to the direct solar radiation heat obtained without shading during a certain period. Indicates time, This is a time-dependent occlusion coefficient.

[0037] If there is shading, the formula for calculating the actual solar radiation received by the photovoltaic module is:

[0038] In most cases, when photovoltaic modules are installed according to photovoltaic power plant specifications, the direct irradiance is usually set to 1.

[0039] S3. Shadow analysis and quantification: Based on the digital elevation model and the solar motion trajectory model, conduct all-time shadow analysis, and perform quantitative calculations by coupling the number of photovoltaic module strings, photovoltaic array spacing, installed density and land utilization rate to obtain the minimum land area and the corresponding power generation. S31. All-Time Shading Analysis and Minimum Module Spacing Calculation: Based on the Digital Elevation Model (DEM) and solar trajectory algorithm, a three-dimensional shading analysis model is established. This model is used to accurately quantify and calculate the minimum installation spacing under different photovoltaic module tilt angles to avoid power generation efficiency loss caused by shading effects; the minimum module spacing under different photovoltaic module tilt angles is calculated. The specific formula is as follows:

[0040] in, The solar altitude angle at noon on the winter solstice. For the length of the photovoltaic module, This is the lowest point of the component above the ground (in meters), with a default value of 0.5 meters. This is the slope correction factor. The installation tilt angle of the photovoltaic modules; S32. Supplementary Calculation of Photovoltaic Array Spacing: According to the "Design Code for Photovoltaic Power Stations," ensure that the photovoltaic modules do not obstruct each other during the local true solar time period from 09:00 to 15:00 each day, and calculate the photovoltaic array spacing. The specific formula is as follows:

[0041] in, The latitude of the location of the photovoltaic project; S33. Calculation of Minimum Floor Space for Number of Module Strings: Calculate the floor space by considering the number and size of the photovoltaic module strings and the reserved spacing. Minimum value: Let the size of the photovoltaic module string be... ， The width of the photovoltaic module is [value], and the capacity of a single photovoltaic module is [value]. The total installed capacity of the system is ， The number of photovoltaic module strings Installed capacity per unit area ,in For the number of photovoltaic modules, Rated power of a single component To accommodate the floor space; allow sufficient space on both sides for the photovoltaic modules. Furthermore, it is required that the lowest point of the photovoltaic module be 0.5 meters above the ground; The area The calculation formula is:

[0042] in, denoted as , where m is the number of photovoltaic module strings arranged front to back, and m is the number of photovoltaic module strings arranged left to right.

[0043] S34, Power Generation Calculation Layer The theoretical power generation is calculated using the standard method, which is based on GB50797~2012 for calculating the theoretical power generation of photovoltaic power plants; the specific calculation formula is as follows:

[0044] in, This represents the theoretical annual power generation of the photovoltaic power station. The amount of solar radiation received by the inclined surface; The solar irradiance under standard test conditions is taken as 1 kW / m2; This is the overall efficiency coefficient of the photovoltaic power generation system.

[0045] S4. Weighting and IRR Iteration: Based on land rent data, rent levels are divided, and the optimal weights for land utilization and power generation are allocated according to the levels. The annual return is calculated by combining the minimum land area and power generation. The optimal photovoltaic tilt angle is determined by iteratively solving the problem with the internal rate of return on total investment as the objective.

[0046] S41. Dynamic Weight Allocation: Based on land rent data, rent levels are divided, and weights are allocated and optimized according to the levels. Specifically: In high-rent areas, the optimization weight for land utilization is set to 0.6, and the optimization weight for power generation is set to 0.4. In low-rent areas, the optimization weight for land utilization is set to 0.4, and the optimization weight for power generation is set to 0.6. In the medium-rent zone, the weights of both are set to 0.5.

[0047] S42. Annual Income Calculation: Income It is related to power generation, local electricity price, operating costs, land funds, land utilization rate, etc.; if the land rent is z (yuan / mu / year), the new rent sensitivity coefficient k (dynamically determined according to rent range: k=1.2 when r>12 yuan / m² / year in high rent range, k=1.0 when 5≤r≤12 yuan / m² / year in medium rent range, and k=0.8 when r<5 yuan / m² / year in low rent range), the electricity selling price is ω (yuan / kWh), the construction cost is a (yuan / KWp), the photovoltaic power station operating cost is b (yuan / kW / year), and the electricity price value-added tax is 13%; Calculate annual income The specific formula is as follows:

[0048] in, For power generation, Based on local electricity prices, For the operating costs of photovoltaic power plants, This represents the total installed capacity of the system. To minimize the area occupied, For land rent, The rent sensitivity coefficient (k is used to amplify the land cost weight in high-rent areas and improve regional adaptability) is used. Land utilization rate.

[0049] S43. Calculate the IRR using a piecewise iterative algorithm, specifically including: Initial screening stage: Calculate the internal rate of return for different tilt angles with a step size of 5°, and lock in the tilt angle range with the optimal internal rate of return; Calculation phase: Within the locked interval, the precise value of IRR is calculated using hourly power generation data from Pvsyst software with a step size of 0.5°. Convergence condition: The iteration stops when the difference in internal rate of return between adjacent tilt angles is less than 0.01%, and the tilt angle at this point is the optimal photovoltaic tilt angle.

[0050] Simultaneously, the income tax policy of "three years of exemption and three years of half-reduction" is embedded: income tax is 0% for the first 3 years, 12.5% ​​for the 4th to 6th years, and 25% from the 7th year onwards. The calculation formula is as follows:

[0051] in, This represents the net cash flow in year t, including income tax adjustments.

[0052] The net present value (NPV) of a conventional cash flow project is directly related to the discount rate; it is a function of the discount rate. That is, the NPV decreases as the discount rate increases. The NPV function curve crosses the horizontal axis, and the intersection of this curve and the horizontal axis represents the internal rate of return (IRR). A piecewise iterative algorithm is used to calculate the rate of return on investment, with the following formula:

[0053] in, For the first scheme Annual net cash flow The discount rate is set. This is the calculation period for the scheme.

[0054] Example 2 This embodiment uses Qingdao, a coastal city in eastern China with high land rents, as a case study. It employs a multi-objective collaborative optimization method for determining the photovoltaic tilt angle proposed in this invention. The project is located in Qingdao (land rent > 8 yuan / m² / year, belonging to a high-rent area). The theoretical optimal tilt angle using the traditional "maximize power generation" method is 30°. Trial calculations were conducted using Pvsyst software and the Meteonorm database, setting land utilization rates of 50%–100% (6 levels) and land rents of 1000–3000 yuan / mu / year (average levels). IRR calculations covered 11 levels of optimal tilt angles from -10° to 0°. Specific steps included: B1. Basic Data Collection Resource and Engineering Data: High-precision solar radiation data (National Meteorological Information Center), topographic elevation data with a resolution ≤1m, land rent at the plot level (high-rent areas); component dimensions, support parameters, investment cost parameters (component unit price, operation and maintenance rate), and the lowest point height of the component above the ground. rice.

[0055] Topographic and economic parameters: The project includes a 5° slope, with a slope correction factor. Slope correction factor (alpha_s=1.2), rent sensitivity factor Qingdao benchmark electricity price The electricity price is 1 yuan / kWh, with a value-added tax of 13% and an income tax policy of "three years of exemption and three years of half reduction".

[0056] B2. Step-by-step implementation and calculation (I) Solar Radiation and Trajectory Calculation Through formula and Calculate the solar azimuth angle for 12 typical days throughout the year (the 1st of each month). With elevation angle .

[0057] Taking the winter solstice as an example, Qingdao's latitude ,have to Noon solar altitude angle (This is a key parameter for subsequent minimum spacing calculations) .

[0058] Based on the above trajectory, the solar radiation intensity received by the photovoltaic module is calculated using the formula: When there is no obstruction When there is occlusion (Qingdao Project) Finally, take the annual average Used for calculating power generation.

[0059] (II) Minimum installation spacing and land use optimization Through formula Calculate the minimum interval between 9:00 and 15:00 on 12 typical days throughout the year, and take the maximum value (obtained from the Qingdao project trial calculation). (meters). Combined with the number of component strings. Installed capacity per unit area Find the minimum land area required to maximize land use efficiency. .

[0060] (III) Calculation of Power Generation and Economic Benefits According to the formula Calculate the theoretical annual power generation, and then use the formula Calculate the annual return. Iterate the solution with IRR as the target: in the initial screening stage, lock the range of 0° to 10° with a step size of 5°, and in the fine calculation stage, combine Pvsyst data with a step size of 0.5° to finally determine the optimal tilt angle of the Qingdao project as 5°.

[0061] B3. IRR and Technical Effectiveness Verification Referring to Table 1, the IRR changes under different land utilization rates and land costs in the Qingdao project show that the IRR increases significantly with increasing land utilization and decreasing land costs. For example, when the land utilization rate is 100% and the land cost is 1000 yuan / mu / year, the IRR reaches 10.552%; when the land utilization rate is 50% and the land cost is 3000 yuan / mu / year, the IRR is only 7.847%. This indicates that in scenarios with high rent and low land utilization, this method can effectively balance costs and benefits by reducing the tilt angle (such as 5° in Qingdao); and when land conditions are favorable, the IRR further increases, fully demonstrating the adaptability of multi-objective synergy.

[0062] Table 1. Changes in IRR with Land Capital and Land Utilization Rate at the Optimal Inclination Angle for the Qingdao Project

[0063] Meanwhile, parameter optimization verification shows that in the Qingdao 5° slope project, the IRR reaches 10.55% when the slope correction coefficient (theta_s=0.8), an increase of 0.32% compared to the uncorrected method. When the land rent increases to 15 yuan / m² / year, the optimal slope angle decreases to 3°, but the IRR still remains above 10.2%. Regarding land resource conservation, a 100% land utilization rate saves 1.4%–5.6% of land, resulting in rent savings of 750,000–7.65 million yuan over 25 years; a 70% land utilization rate saves 42% of land, resulting in rent savings of 20 million–60 million yuan over 25 years, with an IRR increase of 0.03%–2.2% compared to the traditional method, and a net profit increase of 240,000–20.27 million yuan over 25 years.

[0064] As can be seen, the Qingdao project has verified the effectiveness of the present invention in high-rent areas. The optimal economic tilt angle (5°) is significantly smaller than the traditional "maximum power generation" tilt angle (30°). Moreover, it can achieve the dual advantages of "resource utilization and economic benefits" under different land use and cost scenarios, providing a quantitative paradigm for tilt angle decision-making for photovoltaic projects in similar areas.

[0065] In summary, the present invention has the following advantages: 1. Multi-dimensional economic coupling model: For the first time, land rent, shading, and installed density are incorporated into the tilt angle optimization system, and a three-dimensional correlation model of "solar radiation - land use - cost and benefit" is established, which improves land utilization by 15% to 25% compared with traditional single-objective algorithms; 2. Terrain-adaptive shadow control: Based on the dynamic shadow spacing algorithm of DEM, it can reduce invalid land occupation by more than 30% in sloping environments; 3. Dynamic weight optimization strategy: The target weight is automatically adjusted and optimized according to the land rent level. In high rent areas, land utilization is prioritized, while in low rent areas, power generation is emphasized to achieve optimal regional adaptability. 4. Terrain Adaptive Parameter System: Innovatively introducing slope correction coefficient, aspect correction coefficient, and rent sensitivity coefficient, it achieves dynamic adaptation to complex terrain and different rent areas, improving optimization accuracy by 30% compared to traditional fixed parameter methods; 5. All-time shadow optimization method: The minimum spacing is determined by shadow overlay analysis of 12 typical days throughout the year, avoiding seasonal shading problems caused by calculation on a single winter solstice day, thereby increasing land utilization by 5% to 8%.

[0066] The above specific embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for determining the photovoltaic tilt angle through multi-objective collaborative optimization, characterized in that, include: S1. Collect basic data, which includes at least solar radiation data, engineering parameters, land rent data, and topographic data; S2. Based on the terrain data, determine the slope correction coefficient and the aspect correction coefficient, and construct a solar trajectory model in combination with solar radiation data to calculate the solar radiation intensity received by the photovoltaic module. S3. Based on the digital elevation model and the solar motion trajectory model, conduct all-time shadow analysis, and perform quantitative calculations by coupling the number of photovoltaic module strings, the spacing of photovoltaic arrays, the installed capacity density and the land utilization rate to obtain the minimum land area and the corresponding power generation. S4. Based on the land rent data, classify the rent levels, allocate the optimization weights of land utilization rate and power generation according to the level, calculate the annual income by combining the minimum land area and power generation, and iteratively solve the problem with the internal rate of return on total investment as the objective to determine the optimal photovoltaic tilt angle.

2. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The solar radiation intensity includes: solar radiation intensity with shading and solar radiation intensity without shading; The formula for calculating the solar radiation intensity under unobstructed conditions is as follows: in, This represents the amount of direct solar radiation. This represents the amount of solar diffuse radiation. This represents the amount of solar radiation reflected. The installation tilt angle of the photovoltaic modules; in, For ground reflectivity, The angle of incidence of sunlight; The formula for calculating the intensity of solar radiation under shading is as follows: in, This is the ratio of the direct solar radiation heat on the surface of the photovoltaic panel to the direct solar radiation heat obtained without shading during a certain period. Indicates time, This is a time-dependent occlusion coefficient.

3. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The specific parameters for the number of coupled photovoltaic module strings, photovoltaic array spacing, installed capacity density, and land utilization rate in step S3 are as follows: Assume the total installed capacity of the system is The capacity of a single photovoltaic module is The number of component strings ; Installed capacity per unit area ,in For the number of photovoltaic modules, Rated power of a single component For the area occupied; by establishing The quadratic function relationship between the photovoltaic tilt angle and the array spacing constraint is used to solve for maximizing land utilization. Minimum value.

4. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The full-time shadow analysis in step S3 specifically includes: Twelve typical days throughout the year were selected, and the shadow range at each time from 09:00 to 15:00 local true solar time was calculated for each typical day. The maximum value of the minimum spacing at all times was taken as the minimum spacing of the photovoltaic array to avoid power generation loss caused by seasonal shading.

5. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The rules for determining the slope correction factor are as follows: The value is dynamically determined based on the terrain slope (0°-30°), ranging from 0.7 to 0.

95. For every 5° increase in slope, θ... s Decrease by 0.05; the slope correction factor α s The value is determined by the following rules: 0.8-1.2 based on the angle between the slope direction and the due south direction (0°-±90°), 0.8-1.0 for east / west slopes, and 1.2 for due south slopes.

6. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The step S4, which involves classifying rent levels based on land rent data and allocating optimization weights according to these levels, specifically involves: In high-rent areas, the optimization weight for land utilization is set to 0.6, and the optimization weight for power generation is set to 0.

4. In low-rent areas, the optimization weight for land utilization is set to 0.4, and the optimization weight for power generation is set to 0.

6. In the medium-rent zone, both weights are set to 0.

5.

7. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The annual income is calculated in step S4. The specific formula is as follows: in, For power generation, Based on local electricity prices, For the operating costs of photovoltaic power plants, This represents the total installed capacity of the system. To minimize the area occupied, For land rent, This is the rent sensitivity coefficient. Land utilization rate.

8. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, Step S4, which iteratively solves for the internal rate of return on total investment as the objective, specifically includes: Initial screening stage: Calculate the internal rate of return for different tilt angles with a step size of 5°, and lock in the tilt angle range with the optimal internal rate of return; Calculation phase: Within the locked interval, the precise value of IRR is calculated using hourly power generation data from Pvsyst software with a step size of 0.5°. Convergence condition: The iteration stops when the difference in internal rate of return between adjacent tilt angles is less than 0.01%, and the tilt angle at this point is the optimal photovoltaic tilt angle.

9. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The method for calculating the minimum footprint of photovoltaic modules in step S3 includes the following sub-steps: S31. Based on the digital elevation model and solar trajectory algorithm, establish a three-dimensional shadow analysis model to calculate the minimum module spacing under different photovoltaic module tilt angles. The specific formula is as follows: in, The solar altitude angle at noon on the winter solstice. For the length of the photovoltaic module, This is the lowest point of the component above the ground (in meters), with a default value of 0.5 meters. This is the slope correction factor. The installation tilt angle of the photovoltaic modules; S32. According to the "Design Code for Photovoltaic Power Stations", ensure that the photovoltaic modules do not shade each other during the local true solar time period from 09:00 to 15:00 every day. Calculate the photovoltaic array spacing S using the following formula: in, The latitude of the location of the photovoltaic project; S33. Calculate the floor area based on the number, size, and reserved spacing of photovoltaic module strings. Minimum value: Let the size of the photovoltaic module string be... , Let P be the width of the photovoltaic module, P be the capacity of a single photovoltaic module, and P be the total installed capacity of the system. The number of photovoltaic module strings Installed capacity per unit area ,in For the number of photovoltaic modules, Rated power of a single component To accommodate the floor space required; allow sufficient space on both sides for the photovoltaic modules. Furthermore, it is required that the lowest point of the photovoltaic module be 0.5 meters above the ground; The area The calculation formula is: in, denoted as , where m is the number of photovoltaic module strings arranged front to back, and m is the number of photovoltaic module strings arranged left to right.

10. The photovoltaic tilt angle determination method based on multi-objective collaborative optimization according to claim 1, characterized in that, The formula for calculating the power generation in step S3 is as follows: in, This represents the theoretical annual power generation of the photovoltaic power station. The amount of solar radiation received by the inclined surface; Solar irradiance under standard test conditions; This is the overall efficiency coefficient of the photovoltaic power generation system.

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