A building roof photovoltaic array optimal tilt angle cooperative optimization method, device, equipment and medium

Abstract

The present application relates to the field of photovoltaic array, and particularly relates to a building roof photovoltaic array optimal tilt angle cooperative optimization method, device, equipment and medium. According to the solar radiation data, the component electrical parameter and the preset tilt angle, the full life cycle power generation of a single photovoltaic component under the preset tilt angle is obtained. According to the preset tilt angle, the geometric size of the single photovoltaic component, the site size and the true solar time shadow constraint, the maximum installed capacity and the total number of components under the preset tilt angle are obtained. According to the full life cycle power generation of the single photovoltaic component, the total number of components, the maximum installed capacity and the cost parameter, the levelized cost of electricity under the preset tilt angle is calculated. According to the levelized cost of electricity corresponding to each preset tilt angle in the preset tilt angle range, the preset tilt angle with the lowest levelized cost of electricity is determined as the optimal tilt angle. A new efficiency increasing path is provided for photovoltaic investment in high rent scenarios.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic arrays, and more specifically to a method, apparatus, equipment, and medium for the coordinated optimization of the optimal tilt angle of a building rooftop photovoltaic array. Background Technology

[0002] The tilt angle of a distributed photovoltaic (PV) power station is the angle between the plane of a PV module or PV array and the horizontal plane, measured in degrees (°). It is used to characterize the degree of tilt of the module plane during PV system installation.

[0003] Traditional design methods typically prioritize finding the optimal tilt angle that maximizes radiation reception, and then design the array layout within this tilt angle. This approach fails to establish a quantitative coupling relationship between tilt angle variations and array spacing, installed capacity, and system cost. In scenarios with limited roof area, pursuing a high tilt angle often leads to increased row spacing, significantly reducing the total installed capacity and causing a surge in fixed rental costs per unit of electricity, deviating from the economic objective of minimizing the levelized cost of electricity (LCOE). Summary of the Invention

[0004] The purpose of this invention is to provide a method, device, equipment, and medium for the coordinated optimization of the optimal tilt angle of a building rooftop photovoltaic array, which solves the problems in the prior art.

[0005] This invention is achieved through the following technical solution:

[0006] In a first aspect, embodiments of the present invention provide a method for collaborative optimization of the optimal tilt angle of a building rooftop photovoltaic array, comprising:

[0007] Acquire solar irradiance data for the region where the photovoltaic array is located, electrical parameters and geometric dimensions of individual photovoltaic modules in the photovoltaic array, cost parameters and site dimensions for constructing the photovoltaic array, wherein the site dimensions are the site dimensions within the building roof area;

[0008] Based on the solar irradiance data, the electrical parameters of the components, and the preset tilt angle, the total life-cycle power generation of the single photovoltaic module at the preset tilt angle is obtained;

[0009] The maximum installed capacity and the total number of modules are obtained by arranging them according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints.

[0010] Based on the total life-cycle power generation of a single photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters, the levelized cost per kilowatt-hour at the preset tilt angle is calculated.

[0011] Based on the levelized cost of electricity (LCOE) corresponding to each preset tilt angle within the preset tilt angle range, the preset tilt angle with the lowest LCOE is determined as the optimal tilt angle.

[0012] Preferably, the step of obtaining the total life-cycle power generation of a single photovoltaic module at the preset tilt angle based on the solar irradiance data, the module's electrical parameters, and the preset tilt angle includes:

[0013] Based on the characteristic point data under standard test conditions provided in the specification sheet of the single photovoltaic module, a nonlinear least squares optimization model is constructed. The objective function of the nonlinear least squares optimization model is defined as the sum of squared residuals at the characteristic points, including open circuit points, short circuit points, and maximum power points.

[0014] The parameters of the single diode model are obtained by iteratively solving for the parameter combination that minimizes the objective function.

[0015] Based on the total effective irradiance of the photovoltaic module, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters. The total effective irradiance is obtained based on the solar irradiance data and the preset tilt angle.

[0016] The real-time maximum output power of the single photovoltaic module at each moment in a typical meteorological year is calculated based on the corrected photoelectric conversion model parameters.

[0017] Based on the preset system efficiency, component degradation rate, and all real-time maximum output power, the total life-cycle power generation of the single photovoltaic module is calculated.

[0018] Preferably, the step of correcting the photoelectric conversion model parameters of the photovoltaic module based on the effective total irradiance of the photovoltaic module to obtain the corrected photoelectric conversion model parameters includes:

[0019] Based on the total horizontal radiation, horizontal scattered radiation, and normal direct radiation in the solar irradiance data, combined with the solar zenith angle and the preset tilt angle, the frontal irradiance is calculated using the Perez anisotropic scattering model.

[0020] Based on the geometric arrangement of the photovoltaic array determined by the preset tilt angle, the ground coverage rate is calculated, wherein the ground coverage rate is used to characterize the proportion of the photovoltaic array projection area to the total site area;

[0021] Based on the ground coverage, surface reflectivity, and component bifaciality, the back irradiance is calculated using an infinitely long array window factor model.

[0022] The effective total irradiance of the photovoltaic module is calculated based on the front irradiance and the back irradiance.

[0023] Based on the effective total irradiance and ambient temperature, the operating temperature of the photovoltaic module is calculated using a photovoltaic module thermal model.

[0024] Based on the effective total irradiance and the operating temperature, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters.

[0025] Preferably, the step of correcting the photoelectric conversion model parameters of the photovoltaic module based on the effective total irradiance and the operating temperature to obtain the corrected photoelectric conversion model parameters includes:

[0026] Based on the effective total irradiance, the photocurrent is corrected according to a linear relationship;

[0027] Based on the effective total irradiance, the parallel resistance is corrected according to an inverse proportional relationship;

[0028] Based on the operating temperature, an exponential model including the cubic term of bandgap energy and temperature is used to correct the reverse saturation current.

[0029] Keep the series resistance constant;

[0030] Based on the corrected photocurrent, parallel resistance, and reverse saturation current, the corrected photoelectric conversion model parameters are obtained.

[0031] Preferably, the step of arranging the photovoltaic modules according to the preset tilt angle, the geometric dimensions of each individual photovoltaic module, the site dimensions, and the true solar time shading constraint to obtain the maximum installed capacity and the total number of modules at the preset tilt angle includes:

[0032] Based on the target observation time on the winter solstice, convert the local time to true solar time;

[0033] Calculate the solar altitude angle and solar azimuth angle based on the true solar time;

[0034] Based on the solar altitude angle, solar azimuth angle, preset tilt angle, and component inclined surface length, calculate the projection length of the shadow cast by the front array on the rear array in the north-south direction;

[0035] Calculate the minimum row spacing based on the projection length;

[0036] Based on the geometric dimensions, the minimum row spacing, the site dimensions, and the component installation gap, the maximum number of installable rows and columns are calculated using an integer programming algorithm to obtain the maximum installed capacity and the total number of components. The calculation of the number of columns satisfies the even number constraint to adapt to the support structure.

[0037] Preferably, the step of calculating the levelized cost of electricity (LCOE) at the preset tilt angle based on the total life-cycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters includes:

[0038] The total power generation of the photovoltaic array over its entire life cycle is calculated based on the total power generation of each individual photovoltaic module and the total number of modules.

[0039] Calculate the fixed rental cost allocated per unit of electricity generation based on the maximum installed capacity and the land rent in the cost parameters.

[0040] The initial investment and operating expenses are calculated based on the cost parameters to obtain the total life cycle cost. The initial investment includes the cost of the support structure, the cost of the components, the cost of the inverter and the balancing system, and the installation cost. The operating expenses include the operation and maintenance costs and the fixed rental costs.

[0041] Based on the total life-cycle cost and total life-cycle power generation, the levelized cost per kilowatt-hour at the preset tilt angle is calculated using the net present value method.

[0042] Preferably, the cost of the support structure is obtained in the following way:

[0043] The wind load shape coefficient is determined based on the preset tilt angle and the standard wind pressure at the location of the photovoltaic array;

[0044] The standard value of wind load is calculated based on the wind load shape coefficient, the standard wind pressure, the preset wind pressure height variation coefficient, and the wind vibration coefficient.

[0045] The design surface load is obtained by combining the load effects based on the standard value of wind load and the preset component dead load.

[0046] The design surface load is converted into a line load acting on the purlins according to the preset purlin spacing, and the purlins are used to support the photovoltaic array;

[0047] Based on the line load, the controlling design bending moment of the purlin is calculated according to the preset structural mechanics model;

[0048] Based on the aforementioned controlling design bending moment, select the steel profile that meets the strength requirements and has the smallest mass per unit length from the pre-set standard steel profile library;

[0049] Calculate the total steel consumption based on the selected steel profiles, total purlin length, number of support sets, and rear column length;

[0050] Calculate the cost of the support structure based on the total amount of steel used and the unit price of steel.

[0051] Secondly, embodiments of the present invention provide a device for coordinating and optimizing the optimal tilt angle of a building rooftop photovoltaic array, comprising:

[0052] The acquisition module is used to acquire solar irradiance data of the area where the photovoltaic array is located, the electrical parameters and geometric dimensions of individual photovoltaic modules of the photovoltaic array, and the cost parameters and site dimensions for constructing the photovoltaic array.

[0053] The power generation calculation module is used to obtain the total life cycle power generation of a single photovoltaic module at the preset tilt angle based on the solar irradiance data, the electrical parameters of the module, and the preset tilt angle.

[0054] The arrangement module is used to arrange the photovoltaic modules according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints, so as to obtain the maximum installed capacity and the total number of modules under the preset tilt angle.

[0055] The cost calculation module is used to calculate the levelized cost of electricity (LCOE) at the preset tilt angle based on the total life-cycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters.

[0056] The tilt angle determination module is used to determine the optimal tilt angle based on the levelized cost of electricity corresponding to each preset tilt angle within the preset tilt angle range, with the preset tilt angle having the lowest levelized cost of electricity.

[0057] Thirdly, embodiments of the present invention provide an electronic device, including: at least one processor, at least one memory, and computer program instructions stored in the memory, which, when executed by the processor, implement the method of the first aspect described above.

[0058] Fourthly, embodiments of the present invention provide a storage medium storing computer program instructions, which, when executed by a processor, implement the method of the first aspect described above.

[0059] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0060] 1) A closed-loop feedback mechanism based on tilt angle, spacing, GCR, and back-side gain was constructed to correct the underestimation of the power generation potential of high-tilt-angle schemes by traditional methods. Traditional design methods often calculate bifacial gain in isolation (usually using a fixed coefficient), ignoring the decisive influence of array arrangement on the back-side radiation field. This invention considers a dynamic linkage model between tilt angle and ground coverage (GCR). On the one hand, as the tilt angle increases, to meet the unobstructed requirement, the array spacing is forced to increase, the GCR decreases, and thus significantly increases the radiative flux reflected from the ground to the back of the module. This closed-loop feedback mechanism can accurately capture the physical advantages of high-tilt-angle schemes in back-side gain, effectively correcting the selection bias caused by the underestimation of high-tilt-angle power generation by traditional methods, and providing a scientific calculation basis for the potential release of bifacial modules.

[0061] 2) This invention achieves dynamic quantification of structural mechanics based on tilt angle, load, selection, and cost, filling the gap in refined cost estimation for support structures during the planning stage. Addressing the technical pain point of traditional cost estimation neglecting the nonlinear impact of tilt angle changes on support structure costs, this invention proposes an algorithm for calculating wind loads at varying tilt angles and for automatically selecting steel profiles. This algorithm can respond in real-time to changes in wind pressure / sucking coefficients at different tilt angles, automatically adjusting purlin cross-sections and steel consumption. This innovation not only avoids the economic losses missed by low-tilt schemes due to overestimating support structure costs but also effectively prevents structural safety hazards and cost surges caused by neglecting the dramatic increase in wind load in high-tilt schemes, significantly improving the engineering accuracy of project cost estimates.

[0062] 3) This invention solves the economic trade-off between per-watt efficiency and installed capacity in confined spaces, uncovering the hidden value of low-tilt, high-density layouts. In distributed scenarios with high rooftop rents and limited space, traditional methods that simply maximize per-watt power generation often lead to reduced installed capacity and increased rent amortization costs. This invention integrates shading analysis and integer programming layout to construct a fully parameterized iterative optimization system with LCOE as the objective function. This system can automatically weigh the combined benefits of sacrificing a small amount of per-watt power generation for increased installed capacity and reduced rent amortization, accurately identifying low-tilt intervals that are easily overlooked by traditional methods, providing a new efficiency-enhancing path for photovoltaic investment in high-rent scenarios. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0064] Figure 1A flowchart illustrating the optimal tilt angle optimization method for building rooftop photovoltaic arrays provided by this invention;

[0065] Figure 2 This is a schematic diagram of the steel support design provided by the present invention;

[0066] Figure 3 A schematic diagram of the structure of the optimal tilt angle collaborative optimization device for building roof photovoltaic arrays provided by the present invention;

[0067] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0069] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0070] It should be noted that all actions involving the acquisition of signals, information, or data in this invention are carried out in compliance with the relevant data protection laws and regulations of the locality and with authorization from the owner of the relevant device.

[0071] Example 1

[0072] Please see Figure 1 This invention provides a method for collaborative optimization of the optimal tilt angle of a building rooftop photovoltaic array, comprising:

[0073] S1. Obtain solar irradiance data of the area where the photovoltaic array is located, the electrical parameters and geometric dimensions of the individual photovoltaic modules of the photovoltaic array, and the cost parameters and site dimensions for constructing the photovoltaic array, wherein the site dimensions are the site dimensions within the building roof area;

[0074] Specifically, solar irradiance data refers to the temporal and spatial distribution of solar radiation energy received at the site of a photovoltaic power station, which can be provided in the form of a typical meteorological year dataset. This dataset includes typical meteorological year (TMY) data, containing hourly total horizontal irradiance. Horizontal scattered radiation Normal direct radiation Ambient temperature and wind speed The data needs to be time zone calibrated and converted to UTC time.

[0075] The electrical parameters of photovoltaic modules refer to the core technical indicators characterizing the photoelectric conversion performance of the modules, measured under standard test conditions. These indicators include open-circuit voltage, short-circuit current, maximum power point voltage and current, maximum module power, and temperature coefficient. For example, the standard test condition (STC) parameters provided in the module product manual for digital entry include: nominal maximum power. Open circuit voltage Short-circuit current Maximum power point voltage Maximum power point current Number of solar cells in series Component bifaciality Temperature coefficient: The temperature coefficient of the short-circuit current must be explicitly entered. (Unit: A / ℃), Open-circuit voltage temperature coefficient (Unit: V / ℃) and maximum power temperature coefficient (Unit: % / ℃).

[0076] Module geometry refers to the external outline dimensions of a single photovoltaic module in physical space, mainly including length, width, and thickness.

[0077] Cost parameters refer to the economic quantitative indicators related to the construction, operation, and financial evaluation of photovoltaic power plants, including equipment unit price, land rent, labor installation rate, operation and maintenance costs, and financial discount rate.

[0078] Site dimensions refer to the effective outline dimensions of the roof or ground that can be used to install a photovoltaic array, and are usually defined by two dimensions: length and width.

[0079] Before optimization calculations begin, it is necessary to collect and confirm all fundamental input data affecting the performance and economic benefits of the photovoltaic system. This step provides a complete and consistent data foundation for subsequent modeling and calculations. By systematically integrating parameters from multiple fields such as meteorology, power electronics, structural engineering, and economics, a comprehensive dataset capable of characterizing the project's specific boundary conditions is formed. This dataset ensures that subsequent physical and economic model calculations have a realistic basis, avoiding calculation biases caused by incomplete or inconsistent input data. The comprehensiveness and accuracy of the input data are prerequisites for the reliability of all subsequent analytical results.

[0080] S2. Based on the solar irradiance data, the electrical parameters of the module, and the preset tilt angle, obtain the total life-cycle power generation of the single photovoltaic module at the preset tilt angle;

[0081] Specifically, based on the acquired solar irradiance data and module electrical parameters, combined with an assumed preset tilt angle, an energy output assessment model for photovoltaic modules at that tilt angle is established. First, based on solar geometry, the solar radiation data on the horizontal plane is converted into the incident radiation on the tilted module plane, which is the irradiance received on the front of the module. Simultaneously, the radiant energy received on the back of the bifacial module, reflected or scattered by the ground and surrounding environment, needs to be considered; the magnitude of this back-side irradiance is closely related to the array's geometric arrangement. Next, the actual operating temperature of the module is calculated by combining the irradiance and ambient temperature, and the standard electrical parameters of the module are corrected for operating conditions based on this temperature. Finally, using the module's current-voltage characteristic model, its output power under typical yearly meteorological conditions is calculated hourly, and accumulated over time and efficiency losses to obtain the predicted total power generation over its entire life cycle.

[0082] This step establishes a positive physical mapping relationship from meteorological resources and component characteristics to energy output. By building and solving a dynamic physical model, multiple variables such as solar radiation, component temperature, and electrical characteristics are linked to the final power generation output. The model considers the direct effect of tilt angle changes on the front radiation received by the components, as well as the coupling effect of indirectly affecting the back radiation through changes in array spacing. This modeling approach allows the evaluation of power generation performance at different tilt angles to move beyond fixed empirical coefficients and instead rely on dynamic calculations based on physical principles and related to the actual array arrangement. This provides a more accurate power generation input for subsequent economic comparisons, avoiding decision-making biases caused by overestimating or underestimating power generation potential.

[0083] In some embodiments, S2, based on the solar irradiance data, the electrical parameters of the module, and the preset tilt angle, the total life-cycle power generation of the single photovoltaic module at the preset tilt angle is obtained, including:

[0084] S21. Based on the feature point data under the standard test conditions provided in the component specification sheet of the single photovoltaic module, a nonlinear least squares optimization model is constructed. The objective function of the nonlinear least squares optimization model is defined as the sum of squared residuals at the feature points. The feature points include open circuit points, short circuit points, and maximum power points.

[0085] Specifically, the component datasheet provides standard test conditions, such as a unified test environment with an irradiance of 1000 W / m², a spectrum of AM1.5, and a cell temperature of 25°C. Feature point data includes the component's open-circuit voltage, short-circuit current, maximum power point voltage, and current measured under these conditions. A nonlinear least-squares optimization model is used to solve for five physical parameters of the single-diode model: photocurrent, reverse saturation current, series resistance, parallel resistance, and ideality factor. The objective function is defined as the weighted sum of the squares of the deviations between the calculated and measured values ​​at the open-circuit point, short-circuit point, and maximum power point; the weighting coefficients are used to balance the fitting accuracy at different feature points.

[0086] This step uses mathematical optimization methods to extract complete physical model parameters from limited component manufacturing data. Based on the single-diode equations, a system of equations concerning the matching conditions of feature points is established. Since the system of equations is nonlinear and has more unknowns than equations, it is transformed into a least-squares optimization problem. An iterative algorithm is used to find the parameter combination that minimizes the objective function, thereby obtaining model parameters that accurately reproduce the standard test characteristics of the component. This provides accurate benchmark parameters for subsequent power generation simulations under various real-world environments.

[0087] Furthermore, to accurately predict the power generation performance of the module under various non-standard operating conditions, a single-diode model is used to describe the module's current-voltage characteristics. This model includes five key physical parameters: photocurrent... Reverse saturation current Series resistors Parallel resistors and ideal factor .

[0088] Typically, feature point data provided in the manufacturer's specifications is used to construct a nonlinear least squares optimization model. Objective function Defined as the sum of squared residuals at feature points, iteratively solved for the parameter combination that minimizes the error. :

[0089] ;

[0090] in, For open circuit voltage, For short-circuit current, For the maximum power point voltage, The maximum power point current is represented by the first three terms, which represent the constraints of zero open-circuit current, zero short-circuit voltage, and maximum power point matching, respectively. The fourth term represents the constraint that the power-voltage derivative at the maximum power point is zero. The output power of the photovoltaic module, These are the weighting coefficients. The output current is calculated based on the following diode equation:

[0091] ;

[0092] ;

[0093] in, For output voltage, For photocurrent, It is the reverse saturation current. Thermoelectric voltage, Boltzmann's constant, For elementary charge, This refers to absolute temperature.

[0094] S22. Obtain the single diode model parameters by iteratively solving for the parameter combination that minimizes the objective function;

[0095] Specifically, iterative solution refers to the computational process of starting from an initial parameter guess and continuously updating the parameters according to specific mathematical rules, so that the objective function value gradually decreases and eventually approaches the minimum value. Parameter combination here specifically refers to a set of specific values ​​that constitute the single-diode equivalent circuit model, and these values ​​collectively determine the model's current and voltage output characteristics.

[0096] This step performs specific numerical calculations to extract the model parameters. The process relies on an optimization algorithm that searches within the possible value space of the parameters. The driving force behind the search is to continuously decrease the value of the objective function defined in step S21. Each iteration calculates the objective function value and its gradient information based on the current parameters, determining the direction and step size of the parameter adjustment for the next step. This process continues until a preset convergence condition is met, such as the change in the objective function value being less than a certain threshold or reaching the maximum number of iterations. At this point, the parameter combination output by the algorithm is the optimal solution that best fits the model prediction to the standard test data. Through this automated numerical solution process, single-diode model parameters matching the specific component model are obtained, including photocurrent, reverse saturation current, series resistance, parallel resistance, and ideality factor. These parameters are a digital representation of the component's physical characteristics, providing an accurate benchmark for further correction of model behavior under varying irradiance and temperature conditions.

[0097] S23. Based on the effective total irradiance of the photovoltaic module, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters. The effective total irradiance is obtained based on the solar irradiance data and the preset tilt angle.

[0098] Specifically, the effective total irradiance of a photovoltaic (PV) module refers to the total power density of solar radiation that actually acts on the module and participates in the photoelectric conversion process. It includes direct radiation, diffuse radiation, and ground-reflected radiation received on the front of the module, as well as, for bifacial modules, reflected and diffused radiation received on the back from the ground and the environment. Correcting the photoelectric conversion model parameters involves adjusting the model parameter values ​​extracted from standard test conditions based on the non-standard conditions encountered by PV modules in actual operating environments, so that the model can accurately predict the module's performance in real-world conditions.

[0099] This step adapts the component model under standard test conditions to the ever-changing real-world operating environment. The core of this process is identifying model parameters significantly affected by environmental factors and establishing quantitative correction relationships between these parameters and measurable external physical quantities. Effective total irradiance, as a measure of input energy, directly affects the magnitude of the photocurrent within the component; therefore, the photocurrent parameter needs to be proportionally corrected based on the ratio of effective total irradiance to standard test irradiance. Simultaneously, changes in irradiance also affect the shunt loss characterized by the parallel resistance within the component. This resistance value is typically corrected to be inversely proportional to irradiance to simulate the relatively increased loss under low-light conditions. Furthermore, the actual operating temperature of the component significantly alters the intrinsic properties of the semiconductor material, primarily reflected in the reverse saturation current parameter that determines the open-circuit voltage. This parameter needs to be corrected based on an exponential relationship model that includes the operating temperature and the material's bandgap energy. Series resistance, mainly affected by the manufacturing process, is usually considered a constant that does not change with operating conditions. By applying this series of correction formulas based on semiconductor physics, the standard test model is dynamically adjusted to a real-time model applicable to the effective total irradiance and operating temperature of the current specific hour, thereby ensuring the accuracy of power generation simulation.

[0100] In some embodiments, S23, based on the effective total irradiance of the photovoltaic module, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters, including:

[0101] S231. Based on the total horizontal radiation, horizontal scattered radiation, and normal direct radiation in the solar irradiance data, combined with the solar zenith angle and the preset tilt angle, the Perez anisotropic scattering model is used to calculate the frontal irradiance.

[0102] Specifically, in solar irradiance data, total horizontal radiation refers to the total solar radiation energy received on a horizontal surface, including direct and scattered components; horizontal scattered radiation refers to the portion that reaches the horizontal surface after being scattered by the atmosphere; normal direct radiation refers to the direct radiation energy received per unit area perpendicular to the direction of sunlight. The solar zenith angle is the angle between the sun's rays and the local zenith direction. The preset tilt angle is the angle between the photovoltaic module's plane and the horizontal plane. The Perez anisotropic scattering model is a radiation calculation model that decomposes horizontal surface scattered radiation into three components: a bright area surrounding the sun, a horizontally uniform band, and a bright area at the horizon, and calculates their respective contributions on the tilted surface. Front irradiance refers to the total solar radiation power received per unit area on the front surface of the tilted photovoltaic module.

[0103] The goal of this step is to accurately convert solar radiation observations on the horizontal plane into incident radiation values ​​on the tilted assembly plane. The process begins by calculating the solar zenith angle and azimuth angle based on the sun's position. The Perez model decomposes the horizontally scattered radiation into three components with different directional distribution characteristics based on atmospheric transparency and solar position parameters. Combining the assembly tilt angle and azimuth angle, the projection contribution of these three scattered components, as well as the normal direct radiation, onto the assembly plane is calculated. The ground-reflected radiation component is also calculated and incorporated based on the tilt angle and surface reflectivity. Finally, these radiation components from different paths are vector- or scalar synthesized to obtain the total radiative intensity on the tilted plane, i.e., the frontal irradiance. This calculation provides an accurate radiative input for evaluating the energy capture capability of the assembly at different tilt angles.

[0104] S232. Calculate the ground coverage rate based on the geometric arrangement of the photovoltaic array determined by the preset tilt angle, wherein the ground coverage rate is used to characterize the proportion of the photovoltaic array projection area to the total site area.

[0105] Specifically, the geometric arrangement of the photovoltaic array is determined by the preset tilt angle, module size, array spacing, and orientation. Ground coverage is a dimensionless parameter characterizing the density of the photovoltaic array's projection on the ground; its value is equal to the sum of the orthographic projection areas of all photovoltaic modules on the horizontal plane divided by the total area of ​​the site occupied by the array.

[0106] This step quantifies the impact of tilt angle variations on the array's spatial layout. The implementation is based on the minimum row spacing and component arrangement determined in step S3, which satisfy the shading constraints. At a given tilt angle, the projected length of a single component on the horizontal plane is equal to its slope length multiplied by the cosine of the tilt angle. Combining this projected length, component width, and array row and column spacing, the total projected area of ​​a row or array unit can be calculated. Summing the projected areas of all components across the entire site and dividing by the total usable area yields the ground cover. This parameter is a key variable connecting the geometric layout to the back-side irradiance environment; its value decreases as the tilt angle increases because larger tilt angles require larger row spacing to avoid shading, leading to an increase in the exposed ground area.

[0107] S233. Based on the ground coverage, surface reflectivity and component bifaciality, the back irradiance is calculated using the infinite long array window factor model.

[0108] Specifically, surface reflectivity is the ability of the Earth's surface to reflect solar radiation, and its value is usually determined based on the ground material. The bifaciality of a module is the ratio of the power generation efficiency of the back side to the power generation efficiency of the front side of a bifacial photovoltaic module. The infinite-length array window factor model is a simplified geometrical-optical model used to calculate the amount of reflected radiation from the ground and scattered radiation from the sky received on the back side of a regularly arranged bifacial module array. Backside irradiance refers to the solar radiation power received per unit area on the back surface of a photovoltaic module.

[0109] This step calculates the radiation gain on the back of the modules based on the specific array layout. The implementation simplifies the photovoltaic array into a periodic structure composed of parallel, infinitely long objects with identical cross-sectional shapes. The core of the model is calculating the visibility ratio of a point on the back of the module to the ground reflection area and the sky area, i.e., the window factor. Ground cover directly determines the effective area and shading relationship of the reflective surface. Combining surface reflectivity and total horizontal radiation, the reflected radiation flux reaching the ground can be calculated. By integrating the window factor, the amount of reflected radiation reaching the back of the module is obtained. Simultaneously, the model also calculates the sky-scattered radiation component received by the back of the module after being blocked by the front-row modules. Adding the reflected and scattered radiation components and making appropriate corrections based on the module's height above the ground, the final irradiance on the back of the module is obtained. This model quantitatively reveals the negative correlation between back-side gain and ground cover: the lower the GCR (more exposed ground), the higher the ground-reflected radiation received by the back of the module.

[0110] Furthermore, at a given inclination angle Below, using the Perez anisotropic scattering model, based on , zenith angle and Calculate the total frontal irradiance of the tilted plane of the module under local solar conditions. This model accurately takes into account the non-uniformity of sky-scattered light distribution and the ground-reflected component.

[0111] Introducing ground coverage and surface reflectivity The reflected and scattered irradiance received on the back of the component is calculated using an infinitely long array window factor model. .

[0112] Effective total irradiance The calculation is as follows:

[0113] ;

[0114] in For dihedrality, The factor for shading loss due to the rear support bracket is typically taken as 0.03-0.05. This... Feedback S236 is used for the correction calculation of each factor, forming a closed-loop iteration.

[0115] S234. Calculate the total effective irradiance of the photovoltaic module based on the front irradiance and the back irradiance;

[0116] Specifically, the effective total irradiance is the equivalent single-sided irradiance used to calculate the total output power of a bifacial photovoltaic module. It converts the radiation input from both the front and back sides to the module's front efficiency benchmark.

[0117] This step combines the radiation inputs from the front and back sides into an equivalent irradiance value driving a single-diode model. The implementation follows the principle of energy superposition. The front irradiance is directly used as the primary input. The back irradiance needs to be multiplied by the module's bifaciality to convert it into an electrical contribution equivalent to the front efficiency. Simultaneously, shading losses caused by the support beams and other components on the back side must be considered; therefore, a back shading loss coefficient less than 1 is introduced to reduce the back contribution. Ultimately, the effective total irradiance equals the front irradiance plus the back irradiance after bifaciality conversion and shading loss reduction. This parameter is the direct energy input for subsequent calculations of the operating temperature and electrical parameter corrections; it comprehensively reflects the combined impact of tilt angle changes on the total energy received by the module through both the front incident angle and the back gain.

[0118] S235. Based on the effective total irradiance and ambient temperature, calculate the operating temperature of the photovoltaic module using a photovoltaic module thermal model;

[0119] Specifically, a photovoltaic module thermal model is a mathematical model that describes the relationship between the module's operating temperature and ambient temperature, received irradiance, and heat dissipation conditions. For example, the Faiman steady-state thermal model states that the operating temperature is the actual temperature of the photovoltaic cell when it generates electricity, which significantly affects its electrical output characteristics.

[0120] This step predicts the thermal state of the components during actual operation. The implementation employs a steady-state or transient model based on thermal equilibrium. Taking the Faiman steady-state model as an example, its physical basis is that a portion of the radiant energy received by the components (total effective irradiance) is converted into electrical energy, and the remainder is converted into heat energy, which is dissipated into the environment through convection and radiation. The model formula is typically expressed as the operating temperature equal to the ambient temperature plus the ratio of the total effective irradiance to a total heat loss coefficient. The total heat loss coefficient includes a constant term representing natural convection and radiation, and a term proportional to wind speed to characterize the enhanced effect of forced convection cooling. The ambient temperature at the current moment is input. Wind speed The effective total irradiance calculated in step S234 can be used to determine the operating temperature of the module. This temperature is a key variable for correcting voltage-related parameters (such as reverse saturation current).

[0121] Operating temperature of the Faiman steady-state model calculation component :

[0122] ;

[0123] in The effective total irradiance includes bifacial gain. These are the constant heat loss coefficient (usually taken as 29.0 W / m²K) and the wind speed heat loss coefficient (usually taken as 1.5 W / m²s / m).

[0124] S236. Based on the effective total irradiance and the operating temperature, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters.

[0125] Specifically, correcting the photoelectric conversion model parameters refers to adjusting the model parameters (such as photocurrent, reverse saturation current, and parallel resistance) extracted under standard test conditions to their actual values ​​at the current effective total irradiance and operating temperature, based on semiconductor physics principles. The corrected photoelectric conversion model parameters are a set of parameters that can accurately predict the output characteristics of the component under the current specific operating conditions.

[0126] This step completes the final adaptation of the model from standard operating conditions to actual operating conditions. The implementation process applies a series of experimentally validated physical correction formulas. The photogenerated current is corrected to be proportional to the total effective irradiance, reflecting the linear relationship between the number of incident photons and the generated current. The parallel resistance is corrected to be inversely proportional to the total effective irradiance to simulate the effect of relatively increased shunt losses under low irradiance. The correction for the reverse saturation current is crucial; it follows semiconductor PN junction theory, its value is proportional to the cube of the operating temperature, and exponentially related to the bandgap energy of the material, which determines the characteristic that the open-circuit voltage of the component decreases with increasing temperature. The series resistance is generally considered a constant related only to the manufacturing process. By systematically applying these corrections, the original STC-based static model is transformed into a dynamic model whose parameters can respond in real time to changes in irradiance and temperature, thus laying the foundation for accurate hourly power generation simulation.

[0127] In some embodiments, S236, based on the effective total irradiance and the operating temperature, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters, including:

[0128] Based on the effective total irradiance, the photocurrent is corrected according to a linear relationship;

[0129] Based on the effective total irradiance, the parallel resistance is corrected according to an inverse proportional relationship;

[0130] Based on the operating temperature, an exponential model including the cubic term of bandgap energy and temperature is used to correct the reverse saturation current.

[0131] Keep the series resistance constant;

[0132] Based on the corrected photocurrent, parallel resistance, and reverse saturation current, the corrected photoelectric conversion model parameters are obtained.

[0133] Specifically, photocurrent With irradiance Linear change:

[0134] ;

[0135] The reference irradiance under standard test conditions. The reference photocurrent under standard test conditions. The temperature coefficient of short-circuit current. This is the reference battery temperature under standard test conditions.

[0136] Among them, parallel resistors Inversely proportional to irradiance, to simulate efficiency degradation under low light:

[0137] ;

[0138] This is the reference parallel resistor under standard test conditions.

[0139] Reverse saturation current The correction takes into account the variation of intrinsic carrier concentration in semiconductor materials with temperature, and typically employs methods that include bandgap energy. and temperature cube term The bandgap energy is described by an exponential model. This is a core physical property of semiconductor materials (such as silicon used in photovoltaic modules). It represents the minimum energy required to excite an electron from the valence band to the conduction band. This physical mechanism governs the negative correlation between module voltage and temperature, and its specific formula is as follows:

[0140] ;

[0141] The reference reverse saturation current under standard test conditions. For semiconductor materials at reference temperature The band gap energy below, Boltzmann constant, series resistance Assume it to be a constant.

[0142] S24. Calculate the real-time maximum output power of the single photovoltaic module at each moment in a typical meteorological year based on the corrected photoelectric conversion model parameters;

[0143] Specifically, the typical meteorological year refers to the meteorological conditions corresponding to 8760 hours in the TMY dataset. The real-time maximum output power is obtained by solving the power maximization problem of the modified single-diode model, typically using numerical methods such as the Newton-Raphson method.

[0144] This step calculates the theoretical maximum output of the component under hourly varying conditions. For each hour, the corresponding effective total irradiance and ambient temperature are input into the corrected model to form the specific current-voltage equation for that moment. A numerical iterative algorithm is used to find the operating point voltage and current that maximize the output power; their product is the maximum output power for that hour. This process is repeated 8760 times to generate a complete annual power generation time series.

[0145] S25. Based on the preset system efficiency, component attenuation rate, and all real-time maximum output power, calculate the total life-cycle power generation of the single photovoltaic module.

[0146] Specifically, system efficiency includes a comprehensive reduction factor for inverter efficiency, line loss, dust loss, etc. Component degradation rate adopts a two-stage model combining initial year degradation and subsequent linear degradation.

[0147] This step accumulates the power generation while considering system losses and performance degradation. First, the real-time maximum output power over 8760 hours is summed to obtain the theoretical power generation for the first year. Multiplying this by the system efficiency coefficient yields the grid-connected power for the first year. Then, the power generation for subsequent years is calculated using a degradation model: the first-year power generation is reduced by the first-year degradation rate, and then reduced linearly each year thereafter. The power generation for each year over the lifecycle is summed to obtain the predicted total power generation over the entire lifecycle. This result integrates instantaneous power simulation, system losses, and long-term degradation to form a complete power generation assessment.

[0148] Furthermore, the real-time parameters modified by S236 are substituted into the single-diode equation, and the solution is obtained using a numerical method (Newton-Raphson method). The maximum value of is the maximum DC output power at the current moment. .

[0149] For the first year's 8760 hours The total power generation in the first year is obtained by summing the results. Combined with the component degradation curve (first-year degradation rate) linear decay rate ), calculate the total power generation over the entire life cycle (e.g., 25 years). :

[0150] ;

[0151] in The overall system efficiency includes inverter efficiency, line loss, and dust loss.

[0152] S3. Arrange the photovoltaic modules according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints to obtain the maximum installed capacity and the total number of modules under the preset tilt angle;

[0153] Specifically, true solar time shading constraint refers to the geometric conditions set to ensure that there is no shading between the front and rear rows of photovoltaic arrays during a specific critical period on the winter solstice, the day with the shortest daylight hours of the year. This constraint typically requires that, between 9:00 AM and 3:00 PM local true solar time on the winter solstice, the rear row of modules is not completely covered by the shadow of the front row of modules.

[0154] Based on a given preset tilt angle, the geometric profile of individual modules, and the boundary dimensions of the installation site, the photovoltaic modules are arranged in a planar configuration while satisfying the aforementioned true solar time shading constraints. The process begins by calculating the minimum front-to-back row spacing necessary to meet the unshaded requirements at a specific tilt angle, based on the laws of solar motion. Then, using this minimum spacing as a constraint, a spatial layout algorithm is employed to arrange the modules in a two-dimensional configuration within the given site area. This algorithm aims to maximize site area utilization, calculating the maximum number of modules that can be accommodated while adhering to safe installation gaps and edge allowances between modules. Multiplying this maximum number of modules by the nominal power of a single module yields the maximum installed capacity that the site can support at that preset tilt angle. Simultaneously, the total number of modules is also directly determined.

[0155] This step transforms optical shading constraints into geometric spacing constraints, and further, through spatial planning, into a quantifiable result for the installed capacity. It reveals the inherent contradiction between tilt angle selection and site utilization efficiency: larger tilt angles typically require larger row spacing to avoid shading, potentially allowing for fewer components to be installed within a limited site, thus reducing the total installed capacity; conversely, smaller tilt angles allow for a more compact layout. Through this calculation, the impact of tilt angle variations on system size is quantitatively expressed, meaning that each candidate tilt angle corresponds to a defined maximum installed capacity and total number of components. This quantification is a crucial bridge connecting physical design and economic evaluation, enabling subsequent economic analysis to fully consider changes in the initial system investment due to tilt angle variations.

[0156] In some embodiments, S3 involves arranging the photovoltaic modules according to the preset tilt angle, the geometric dimensions of each module, the site dimensions, and the true solar time shading constraint to obtain the maximum installed capacity and the total number of modules at the preset tilt angle, including:

[0157] S31. Convert local time to true solar time based on the target observation time on the winter solstice;

[0158] S32. Calculate the solar altitude angle and solar azimuth angle based on the true solar time;

[0159] S33. Based on the solar altitude angle, solar azimuth angle, preset tilt angle, and component inclined surface length, calculate the projection length of the shadow generated by the front array on the rear array in the north-south direction.

[0160] S34. Calculate the minimum row spacing based on the projection length;

[0161] S35. Based on the geometric dimensions, the minimum row spacing, the site dimensions, and the component installation gap, calculate the maximum number of installable rows and columns using an integer programming algorithm to obtain the maximum installed capacity and the total number of components. The calculation of the number of columns satisfies the even number constraint to adapt to the support structure.

[0162] Specifically, the process begins by converting the preset local observation time to local true solar time, reflecting the actual position of the sun, and calculating the solar altitude angle and azimuth angle accordingly. Then, using these angles, the preset tilt angle of the components, and their slope lengths, the projected length of the shadow cast by the front-row components on the rear-row mounting plane is calculated in the north-south direction through spatial geometry. Based on this projected length, the minimum center-to-center distance between the front and rear rows is determined to meet the unobstructed condition. Finally, using this minimum row spacing, the geometric dimensions of the components, and the component installation gaps as constraints, within the given site plan dimensions, an integer programming algorithm is used to calculate the maximum number of rows and columns of components that can be accommodated. The column count calculation must satisfy an even number constraint to ensure matching with the mounting holes of the standard support beams. Finally, the maximum installed capacity and the total number of components are obtained from the number of rows, columns, and the power of a single component. This process combines the laws of solar motion, geometric shading conditions, and site spatial constraints, achieving a quantitative transformation from optical constraints to a specific engineering layout scheme.

[0163] Furthermore, at each iteration, given the tilt angle Calculate the maximum installed capacity that meets the relevant unobstructed requirements.

[0164] 1. Calculation of shadow length during true solar time

[0165] To ensure the accuracy of shadow calculations, the target observation time (e.g., 09:00 to 15:00) on the design reference date (winter solstice) needs to be converted from local time to standard UTC time. This mapping is performed using longitude correction and mean time difference formulas.

[0166] ;

[0167] Coordinated Universal Time (UTC) is a globally unified time standard used in applications requiring an absolute time reference, such as meteorological data and astronomical calculations.

[0168] True solar time is local time defined based on the actual apparent position of the sun in the sky, with noon corresponding to the moment when the sun is on the local meridian.

[0169] The geographical longitude of the project location is expressed in degrees, with east longitude being positive and west longitude being negative.

[0170] Mean time difference is the difference in minutes between true solar time and mean solar time caused by the Earth's orbital eccentricity and obliquity of the ecliptic. Its value varies with time (dates in a year) and can be obtained through formulas or lookup tables.

[0171] Based on the mapped time, the corresponding solar altitude angle is calculated using astronomical algorithms. and solar azimuth .

[0172] Construct the geometric model of the front and rear rows of shadows in the array. Let the length of the component's inclined plane be... The angle of inclination is The array azimuth angle is (Typically 180°). Calculate the length of the shadow cast by the front row array on the back row in the north-south direction. :

[0173] ;

[0174] 2. Minimum line spacing calculation

[0175] To ensure no obstruction within the time window on the winter solstice, the minimum row spacing of the array is... Must meet:

[0176] ;

[0177] 3. Roof layout with integer proportions

[0178] Based on available roof dimensions (length) ,Width ), component geometry and installation gap Calculate the maximum number of rows. Number of columns The number of columns needs to be calculated by considering margins. And even-number constraints are used to adapt to the support structure:

[0179] ;

[0180] ;

[0181] This yields the total installed capacity at that tilt angle. ,in Specify the nominal maximum power of the components; and calculate the ground coverage. , used to calculate backside gain.

[0182] S4. Calculate the levelized cost of electricity (LCOE) at the preset tilt angle based on the total life-cycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters.

[0183] Specifically, the levelized cost of electricity (LCOE) is a key indicator used to evaluate the economic viability of a power generation project throughout its entire lifecycle. It is defined as the average cost per unit of electricity generated, obtained by dividing the present value of all costs over the project's lifecycle by the present value of all electricity generated.

[0184] This step aims to calculate the levelized cost of electricity (LCOE) under a specific preset tilt angle scheme. The calculation process first multiplies the total lifetime power generation of a single module obtained in step S2 with the total number of modules obtained in step S3 to obtain the predicted total lifetime power generation of the entire photovoltaic array system. Simultaneously, based on the maximum installed capacity and total number of modules determined in step S3, combined with the cost parameters from step S1, the total system cost under this scheme can be calculated. The total system cost includes equipment purchase and installation costs directly related to the installed capacity, material costs related to the support structure design, and ongoing operation and maintenance costs and site rental costs throughout the lifecycle. Among these, the support structure cost, land rental, and other sub-costs closely related to the tilt angle and layout need to be dynamically calculated based on their corresponding relationships. Finally, using the discounted cash flow method, the costs incurred and the power generation generated in each year are discounted to the same baseline point in time; the ratio of their present values ​​is the LCOE under this tilt angle scheme.

[0185] This step transforms technical parameters into economic indicators. It integrates power generation performance, system scale, and various cost factors into a unified economic evaluation framework. By calculating the levelized cost of electricity (LCOE), the economics of different technical solutions are normalized to a comparable value. This method comprehensively reflects the multiple and complex impacts of choosing different tilt angles: for example, a high tilt angle may result in slightly higher power generation per unit area, but may also lead to reduced installed capacity and increased structural costs; a low tilt angle may sacrifice a small amount of power generation efficiency per unit area, but in exchange for higher installed capacity density and lower unit capacity cost. As a comprehensive indicator, the LCOE balances the relationship between power generation revenue and investment costs and operating expenses, providing an objective and quantitative basis for judging the economic merits of different tilt angle solutions.

[0186] In some embodiments, S4, calculating the levelized cost of electricity (LCOE) at the preset tilt angle based on the total lifecycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters, includes:

[0187] S41. Calculate the total power generation of the photovoltaic array over its entire life cycle based on the total power generation of a single photovoltaic module and the total number of modules.

[0188] Specifically, the goal of this step is to extend the power generation predicted based on individual component models to the total system output according to the actual installed scale. This is achieved by multiplying the total lifecycle power generation of a single photovoltaic module (a scalar value in kilowatt-hours) calculated in step S2 with the total number of modules determined in step S3 (an integer). The physical meaning of this operation is that it assumes all modules in the array have consistent performance under the same environmental conditions and arrangement, and ignores minor performance differences between modules and mismatch losses caused by local shading, thus linearly extrapolating the results of the individual model to the entire array. The calculated total lifecycle power generation of the photovoltaic array serves as a benchmark value for the total system energy output used in economic evaluation, and as the basis for calculating the power generation cash flow in the subsequent levelized cost of electricity (LCOE) formula.

[0189] S42. Calculate the fixed rental cost allocated per unit of power generation based on the maximum installed capacity and the land rent in the cost parameters;

[0190] Specifically, this step aims to reasonably amortize a fixed cost, which is not directly linearly related to power generation, onto each unit of power generation. The process begins by calculating the total annual fixed rental expenditure based on the land rent per unit price and the total leased site area stipulated in the cost parameters. Since this total rental expenditure is a fixed expense and does not change with actual installed capacity or power generation, its unit cost amortization must be linked to system output. The specific calculation method is to first accumulate the annual rental expenditure over the entire project lifecycle to obtain the total rental expenditure; then, divide this total rental expenditure by the total power generation of the photovoltaic array over its entire lifecycle, calculated in step S41. The quotient is the fixed rental cost allocated per unit of power generation. This value reflects the fixed site occupancy cost required for each kilowatt-hour of electricity generated under a given site and installation scheme, and is one of the key factors affecting the economics of choosing a high-density or low-density layout scheme within a limited area.

[0191] S43. Calculate the initial investment and operating expenses based on the cost parameters to obtain the total life cycle cost. The initial investment includes the cost of the support structure, the cost of the components, the cost of the inverter and the balancing system, and the installation cost. The operating expenses include the operation and maintenance costs and the fixed rental costs.

[0192] Specifically, this step systematically collects and discounts all cash outflows throughout the project's entire lifecycle. The process categorizes costs into one-time investments and ongoing expenditures. Initial investment is calculated by aggregating the costs of various equipment and engineering works: the cost of the support structure is dynamically calculated using step S4; the component purchase cost is derived by multiplying the component unit price by the total number of components obtained in step S3; the inverter and balancing system costs are typically estimated based on the maximum installed capacity at a per-watt price; and installation costs can be calculated as a certain percentage of the aforementioned equipment costs or a unit capacity price. Operating expenses consist of two parts: first, annual operation and maintenance costs calculated as a certain percentage or fixed rate of the initial investment; and second, annual fixed rental expenses calculated in step S42. Then, an annual cash flow sequence is constructed from the initial year (year 0 or year 1) to the project's end year (e.g., year 25): the initial year represents a negative total initial investment, and each subsequent year represents a negative total operating expense. By selecting the financial discount rate set in the cost parameters, each of these future cash outflows is discounted to the same point in time at the beginning of the project and summed. The sum is the present value of the total life-cycle cost. This calculation unifies costs incurred at different times onto the same economic value scale.

[0193] S44. Based on the total life-cycle cost and the total life-cycle power generation, calculate the levelized cost per kilowatt-hour at the preset tilt angle using the net present value method.

[0194] Specifically, this step calculates and outputs the final economic comparison index based on the net present value (NPV) method. The process first requires constructing a power generation revenue cash flow sequence corresponding to the cost cash flow. The total lifecycle power generation calculated in step S41 is decomposed into a predicted power generation sequence for each year of the project's lifecycle, using the component decay model used in step S2. Using the same financial discount rate as in step S43, the power generation for each future year is discounted to the beginning of the project period, and the sum is obtained to obtain the present value of the total lifecycle power generation. Finally, a division operation is performed: the present value of the total lifecycle cost obtained in step S43 is used as the numerator, and the present value of the total lifecycle power generation obtained here is used as the denominator. The quotient obtained by dividing the two is the levelized cost per kilowatt-hour (LCOE) under the preset tilt angle. This index represents the revenue required to cover all lifecycle costs (discounted to present value) under the current scheme, on average, for each kilowatt-hour generated (also discounted to present value). The lower this value, the better the economics of the tilt angle scheme. By repeating this process across different tilt angles, the optimal tilt angle with the lowest LCOE can be compared and selected.

[0195] In some embodiments, the cost of the support structure is obtained in the following ways:

[0196] The wind load shape coefficient is determined based on the preset tilt angle and the standard wind pressure at the location of the photovoltaic array;

[0197] The standard value of wind load is calculated based on the wind load shape coefficient, the standard wind pressure, the preset wind pressure height variation coefficient, and the wind vibration coefficient.

[0198] The design surface load is obtained by combining the load effects based on the standard value of wind load and the preset component dead load.

[0199] The design surface load is converted into a line load acting on the purlins according to the preset purlin spacing, and the purlins are used to support the photovoltaic array;

[0200] Based on the line load, the controlling design bending moment of the purlin is calculated according to the preset structural mechanics model;

[0201] Based on the aforementioned controlling design bending moment, select the steel profile that meets the strength requirements and has the smallest mass per unit length from the pre-set standard steel profile library;

[0202] Calculate the total steel consumption based on the selected steel profiles, total purlin length, number of support sets, and rear column length;

[0203] Calculate the cost of the support structure based on the total amount of steel used and the unit price of steel.

[0204] Specifically:

[0205] 1. Calculation of shape coefficient for wind load with variable tilt angle

[0206] Based on the current tilt angle According to relevant standards, piecewise linear interpolation is used to determine the wind load shape coefficient. .

[0207] Wind pressure operating coefficient :

[0208] ;

[0209] Air suction coefficient :

[0210] ;

[0211] 2. Calculation of controlling bending moment under wind pressure / wind suction conditions

[0212] Combined with standard wind pressure Wind vibration coefficient (Take 1.2), wind pressure height variation coefficient (Based on altitude) (Based on roughness category lookup table interpolation), first calculate the wind pressure and wind load per unit area. Wind suction load :

[0213] ;

[0214] ;

[0215] Next, load effect combinations are performed to calculate the wind pressure design load per unit area. Wind suction design load (Considering dead load) With wind load (most unfavorable combination)

[0216] Condition 1 (Wind Pressure Control): A combination controlled by variable load effects is adopted, with a dead load partial factor of 1.3.

[0217] ;

[0218] Operating Condition 2 (Wind Suction Control): The partial factor for constant load is taken as 1.3.

[0219] ;

[0220] The design surface load is converted into a wind pressure line load acting on the purlins. Wind suction line load ( (Purlin spacing)

[0221] ;

[0222] Using the bending moment at the purlin support as the controlling index, and calculating according to the continuous beam model, the support bending moment coefficient is usually taken as -0.105 to calculate the maximum design bending moment. :

[0223] ;

[0224] in, This refers to the horizontal distance between the support piles of two adjacent photovoltaic array components.

[0225] 3. Iterative Selection of Standard Steel Silos

[0226] The system iterates through a pre-set database of standard cold-formed thin-walled steel sections. For each type of steel section, its bending strength is verified. Does it meet the requirements?

[0227] ;

[0228] in The effective section modulus of the steel section. The plastic development coefficient is taken as 1.05 for wind pressure conditions and 1.20 for wind suction conditions. The design strength of the steel is set (usually 215 N / mm²). All steel sections that meet the strength requirements are selected, and then the mass per unit length is chosen from them. The smallest model.

[0229] 4. Quantification of Dynamic Stent Costs

[0230] Calculate the total purlin length and number of support groups based on the layout results. Total steel consumption. The calculation formula is:

[0231] ;

[0232] in, Total length of purlins, Number of support groups For the length of the strut, The length of the inclined beam. The mass of steel per unit length, and the length of the rear column. ,in, This refers to the height of the fixed portion of the rear column. This is the length of the photovoltaic module along the tilt direction.

[0233] Combined with steel unit price Calculate the total bracket cost and convert it into a dynamic bracket cost per unit watt. :

[0234] .

[0235] in, For the total installed capacity of the array, and for the tilt angle This formula is a function of [function name missing]. It amortizes the total steel cost of the array based on the installed capacity. The steel cost per unit installed capacity is obtained, expressed in yuan / watt.

[0236] S5. Based on the levelized cost per kilowatt-hour corresponding to each preset tilt angle within the preset tilt angle range, determine the preset tilt angle with the lowest levelized cost per kilowatt-hour as the optimal tilt angle.

[0237] Specifically, the preset tilt angle range refers to a set of tilt angle values ​​that are pre-set based on comprehensive factors such as engineering experience, geographical latitude, and structural safety, and are available for searching and comparison.

[0238] This step is the decision-making stage of the entire optimization process. Following a preset step size, each candidate tilt angle value is systematically traversed within a defined tilt angle range. For each traversed candidate tilt angle, steps S2 to S4 are executed sequentially to obtain the levelized cost of electricity (LCOE) calculation result for that tilt angle. After calculating all candidate tilt angles, all results are compared and analyzed to identify the one with the smallest LCOE value. The specific tilt angle value corresponding to this minimum value is selected as the economically optimal tilt angle under the current project boundary conditions and is used as the final design output.

[0239] This step enables automated optimization based on an objective function. It encapsulates the computational process built in the preceding steps into a function whose input is the tilt angle and output is the levelized cost of electricity (LCOE). By systematically evaluating the value of this function within its domain, the independent variable that minimizes the objective function can be found. This method avoids the limitations of relying on experience or a single performance indicator for decision-making, and systematically explores the overall impact of tilt angle changes on the economic benefits throughout the project's life cycle. The final output optimal tilt angle is a comprehensive optimal solution that balances multiple factors such as power generation, installed capacity, structural costs, and land costs, aiming to achieve optimal overall project economics rather than the optimization of a single technical indicator.

[0240] For example:

[0241] 1. Economic Benefits and Cost Accounting

[0242] Construct a life-cycle cost model that takes into account initial investment and operating expenses.

[0243] Initial investment Includes component costs Inverter cost Installation fee and BOS cost and the dynamic stent cost calculated by S4 .

[0244] ;

[0245] Operating expenses This includes operation and maintenance costs and fixed rental amortization. Fixed rental amortization is a key variable affecting optimization; its annual expenditure is a constant and does not decrease with a reduction in the number of installed machines.

[0246] ;

[0247] The rooftop rent per unit area, The length of the roof. This refers to the width of the roof.

[0248] 2. Discounted Cash Flow and LCOE Calculation

[0249] Calculate the levelized cost of electricity (LCO) at the current tilt angle using the net present value (NPV) method. :

[0250] ;

[0251] in, Here, r represents the maintenance cost, and r is the discount rate.

[0252] 3. Global Iterative Optimization

[0253] exist Within the interval, with The algorithm iterates over a set step size. Each iteration sequentially executes the above steps to generate a sensitivity curve of LCOE as a function of tilt angle, identifying the tilt angle corresponding to the LCOE minimum point. As the final design solution.

[0254] The following specific examples illustrate this embodiment.

[0255] This embodiment selects the rooftop of an existing building in a coastal city in Northeast China as the implementation object. The method described in this invention is applied to perform full-parameter iterative optimization within a preset tilt angle range.

[0256] 1. Construction of basic parameters for the example

[0257] According to the method of this invention, the first step is to construct a set of basic parameters covering all dimensions of the project:

[0258] Geographical and meteorological environment: Setting standard wind pressure The surface roughness category is B. Local typical meteorological year (TMY) data are used, and the full life cycle investigation period is set at 25 years.

[0259] Project site conditions: The effective layout dimension of the roof is length Width .

[0260] Photovoltaic module selection: N-type BC (BackContact) high-efficiency monocrystalline modules are selected. These modules feature high conversion efficiency and a low temperature coefficient, with a nominal power output of [missing information]. For the 650W range, the first-year degradation rate is... Annual decline rate .

[0261] Economic boundary conditions: Set economic parameters such as on-grid electricity price, steel unit price, and operation and maintenance cost rate, where the financial discount rate is taken as... .

[0262] Photovoltaic module layout paradigm: according to the appendix Figure 2 In this context, as the basic paradigm of photovoltaic modules, specific parameters such as row spacing and tilt angle are derived from corresponding calculation results.

[0263] Figure 2 This demonstrates how photovoltaic (PV) modules are supported at a specific angle by a steel frame and ultimately anchored to the foundation. The tilt angle is the angle between the inclined plane where the PV module is located and the horizontal plane. The PV steel purlin LT-1 is a transverse member arranged perpendicular to the main inclined beam. It directly supports the PV modules (PV panels), which are typically bolted to these purlins. The purlins are responsible for transferring the self-weight of the PV panels, wind loads, and snow loads borne on their surfaces, to the steel beams below. The steel beam GL-1 is the main diagonal load-bearing member supporting the purlins, running through the entire inclined plane of the PV panels. It fixes and supports all transverse purlins, maintains the set tilt angle, and transfers all static loads (self-weight) and dynamic loads (wind, snow) collected by the superstructure to the front foundation and rear columns. The strut CG-1 is a diagonal member connecting the lower part of the main steel beam (GL-1) to the lower part of the rear column (GZ-1), forming a triangular truss load-bearing system together with the steel beam and column. The struts effectively resist upward or downward deformation caused by wind, enhancing the longitudinal stiffness and wind and earthquake resistance of the entire support system. The GZ-1 column, located at the rear of the support, is a vertically erected load-bearing component that elevates the rear of the main steel beam to achieve the required design angle. It bears the pressure and tension transmitted from the steel beam and struts, ultimately transferring these forces to the concrete foundation below. The concrete foundation forms the base of the entire photovoltaic system; the bottom ends of the front main beam and the rear column are fixed to it. Relying on its own weight and ground grip, the foundation resists overturning moments generated under extreme weather conditions, ensuring structural safety.

[0264] 2. Specific implementation steps of the optimized design method

[0265] This embodiment performs closed-loop calculation and optimization based on the following steps S1 to S5:

[0266] S1 to S2: Multiphysics Coupling Modeling

[0267] First, a project database including latitude, longitude, altitude, and surface reflectivity was established. Based on the physical characteristics of the N-type BC module, bounded least squares method was used to extract single-diode model parameters, constructing a high-precision photoelectric conversion model. When calculating the tilted plane (POA) irradiance, the Perez anisotropic scattering model was adopted, combined with the DeSoto model to perform real-time corrections to the module's operating temperature and electrical parameters under different meteorological conditions, thereby accurately simulating the module's theoretical power generation throughout its entire lifespan.

[0268] S3: Dynamic geometric arrangement based on true solar time

[0269] exist to Within the tilt angle iteration space, for each candidate tilt angle, the method calculates the shadow length using astronomical algorithms based on the unobstructed requirement of true solar time (09:00-15:00) on the winter solstice, and then determines the minimum line spacing. Combined with... Given the limited space on the roof, an integer programming algorithm was used to arrange the components and calculate the maximum installed capacity that the roof could accommodate at that tilt angle.

[0270] S4: Tilt-Driven Structural Loads and Cost Response

[0271] For each iteration tilt angle, this method is based on The standard wind pressure is used to dynamically calculate the corresponding wind load shape coefficient. As the tilt angle changes, the wind pressure / suction force borne by the component changes nonlinearly. Based on this, the controlling bending moment is calculated, and the cross-section model that meets the strength requirements and uses the least amount of steel is automatically matched from the standard steel library, thus obtaining the dynamic support cost (yuan / W) at that tilt angle.

[0272] S5: Life Cycle Economic Accounting and Optimization

[0273] Based on the power generation, installed capacity, and dynamic costs obtained from the above steps, a cash flow model is constructed that includes initial investment (CAPEX) and operating expenses (OPEX). With the objectives of minimizing the levelized cost of electricity (LCOE) and maximizing the net present value (NPV), the optimal design scheme is calculated and output.

[0274] 3. Results and Beneficial Effects Analysis of the Examples

[0275] Through full-parameter iterative optimization, the method of this invention screens out... The optimal tilt angle is determined. To verify the technical advantages of this invention, it is compared with the "optimal radial tilt angle" (quick lookup table scheme, approximately) commonly used in local conventional designs. A deep benchmarking was conducted, and the specific comparison data is shown in the table below:

[0276]

[0277] Technical Achievements:

[0278] Significantly improves land utilization and installed capacity. As shown in the table above, traditional solutions simply pursue maximizing power generation per watt, and adopt... The high tilt angle results in a large array row spacing, limiting the installation to only 191kW on a confined 40m*50m roof. The method recommended in this invention... The proposed solution, while sacrificing approximately 8.03% of the power generation per watt (from 1.611 to 1.481), significantly shortens the shadow length, resulting in a substantial reduction in row spacing, thereby increasing the total installed capacity to 300kW, an increase of 57.1%.

[0279] A dual optimization of structural costs and rent amortization. Adopting... The low tilt angle significantly reduces the wind load shape coefficient, allowing for the use of lighter support structures under wind pressure conditions of 0.5 kN / m², thus lowering the construction cost per watt. Simultaneously, the significantly increased installed capacity effectively reduces the fixed roof rental fee and grid connection costs per unit of electricity.

[0280] Maximizing economic benefits. Considering the above factors, although the physical power generation efficiency per watt of the proposed solution is slightly reduced, its LCOE is decreased by 4.9% (down to 0.1338 yuan / kWh), and the net present value (NPV) over its entire life cycle is increased by 48.3% (from 1.07 million yuan to 1.59 million yuan). This fully demonstrates that the proposed method can break through the limitations of traditional design thinking in solving the multi-objective game of "limited space, wind load, and economic benefits," and uncover significant hidden gains for investors.

[0281] Example 2

[0282] Please see Figure 3 This invention provides a device for coordinating and optimizing the optimal tilt angle of a building rooftop photovoltaic array, comprising:

[0283] The acquisition module 301 is used to acquire solar irradiance data of the area where the photovoltaic array is located, the electrical parameters and geometric dimensions of the individual photovoltaic modules of the photovoltaic array, and the cost parameters and site dimensions for constructing the photovoltaic array.

[0284] The power generation calculation module 302 is used to obtain the total life cycle power generation of a single photovoltaic module at the preset tilt angle based on the solar irradiance data, the electrical parameters of the module, and the preset tilt angle.

[0285] The arrangement module 303 is used to arrange the photovoltaic modules according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints, so as to obtain the maximum installed capacity and the total number of modules under the preset tilt angle.

[0286] The cost calculation module 304 is used to calculate the levelized cost of electricity (LCOE) at the preset tilt angle based on the total life-cycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters.

[0287] The tilt angle determination module 305 is used to determine the optimal tilt angle based on the levelized cost of electricity corresponding to each preset tilt angle in the preset tilt angle range.

[0288] It should be noted that each module and unit in the optimal tilt angle co-optimization device for building roof photovoltaic arrays in this embodiment corresponds one-to-one with each step in the optimal tilt angle co-optimization method for building roof photovoltaic arrays in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned optimal tilt angle co-optimization method for building roof photovoltaic arrays, and will not be repeated here.

[0289] Example 3

[0290] Please see Figure 4 This embodiment provides an electronic device, including at least one processor 401 and a memory 402. Optionally, the device further includes a communication component 403. The processor 401, memory 402, and communication component 403 are connected via a bus 404.

[0291] In a specific implementation, at least one processor 401 executes computer execution instructions stored in memory 402, causing at least one processor 401 to perform the above-described method.

[0292] The specific implementation process of processor 401 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0293] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0294] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0295] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0296] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0297] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0298] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0299] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0300] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0301] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0302] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0303] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0304] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0305] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for collaborative optimization of the optimal tilt angle of a building rooftop photovoltaic array, characterized in that, include: Acquire solar irradiance data for the region where the photovoltaic array is located, electrical parameters and geometric dimensions of individual photovoltaic modules in the photovoltaic array, cost parameters and site dimensions for constructing the photovoltaic array, wherein the site dimensions are the site dimensions within the building roof area; Based on the solar irradiance data, the electrical parameters of the components, and the preset tilt angle, the total life-cycle power generation of the single photovoltaic module at the preset tilt angle is obtained; The maximum installed capacity and the total number of modules are obtained by arranging them according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints. Based on the total life-cycle power generation of a single photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters, the levelized cost per kilowatt-hour at the preset tilt angle is calculated. Based on the levelized cost of electricity corresponding to each preset tilt angle within the preset tilt angle range, the preset tilt angle with the lowest levelized cost of electricity is determined as the optimal tilt angle; The step of calculating the levelized cost of electricity (LCOE) at the preset tilt angle based on the total lifecycle power generation of a single photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters includes: The initial investment and operating expenses are calculated based on the cost parameters to obtain the total life cycle cost. The initial investment includes the cost of the support structure, the cost of the components, the cost of the inverter and the balancing system, and the installation cost. The cost of the support structure is obtained through the following methods: The wind load shape coefficient is determined based on the preset tilt angle and the standard wind pressure at the location of the photovoltaic array; The standard value of wind load is calculated based on the wind load shape coefficient, the standard wind pressure, the preset wind pressure height variation coefficient, and the wind vibration coefficient. The design surface load is obtained by combining the load effects based on the standard value of wind load and the preset component dead load. The design surface load is converted into a line load acting on the purlins according to the preset purlin spacing, and the purlins are used to support the photovoltaic array; Based on the line load, the controlling design bending moment of the purlin is calculated according to the preset structural mechanics model; Based on the aforementioned controlling design bending moment, select the steel profile that meets the strength requirements and has the smallest mass per unit length from the pre-set standard steel profile library; Calculate the total steel consumption based on the selected steel profiles, total purlin length, number of support sets, and rear column length; Calculate the cost of the support structure based on the total amount of steel used and the unit price of steel.

2. The method for co-optimizing the optimal tilt angle of a building rooftop photovoltaic array according to claim 1, characterized in that, The step of obtaining the total life-cycle power generation of a single photovoltaic module at the preset tilt angle based on the solar irradiance data, the module's electrical parameters, and the preset tilt angle includes: Based on the characteristic point data under standard test conditions provided in the specification sheet of the single photovoltaic module, a nonlinear least squares optimization model is constructed. The objective function of the nonlinear least squares optimization model is defined as the sum of squared residuals at the characteristic points, including open circuit points, short circuit points, and maximum power points. The parameters of the single diode model are obtained by iteratively solving for the parameter combination that minimizes the objective function. Based on the effective total irradiance of the photovoltaic module, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters. The effective total irradiance is obtained based on the solar irradiance data and the preset tilt angle. The real-time maximum output power of the single photovoltaic module at each moment in a typical meteorological year is calculated based on the corrected photoelectric conversion model parameters. Based on the preset system efficiency, component degradation rate, and all real-time maximum output power, the total life-cycle power generation of the single photovoltaic module is calculated.

3. The method for co-optimizing the optimal tilt angle of a building rooftop photovoltaic array according to claim 2, characterized in that, The step of correcting the photoelectric conversion model parameters of the photovoltaic module based on the effective total irradiance of the photovoltaic module to obtain the corrected photoelectric conversion model parameters includes: Based on the total horizontal radiation, horizontal scattered radiation, and normal direct radiation in the solar irradiance data, combined with the solar zenith angle and the preset tilt angle, the frontal irradiance is calculated using the Perez anisotropic scattering model. Based on the geometric arrangement of the photovoltaic array determined by the preset tilt angle, the ground coverage rate is calculated, wherein the ground coverage rate is used to characterize the proportion of the photovoltaic array projection area to the total site area; Based on the ground coverage, surface reflectivity, and component bifaciality, the back irradiance is calculated using an infinitely long array window factor model. The effective total irradiance of the photovoltaic module is calculated based on the front irradiance and the back irradiance. Based on the effective total irradiance and ambient temperature, the operating temperature of the photovoltaic module is calculated using a photovoltaic module thermal model. Based on the effective total irradiance and the operating temperature, the photoelectric conversion model parameters of the photovoltaic module are corrected to obtain the corrected photoelectric conversion model parameters.

4. The method for co-optimizing the optimal tilt angle of a building rooftop photovoltaic array according to claim 3, characterized in that, The step of correcting the photoelectric conversion model parameters of the photovoltaic module based on the effective total irradiance and the operating temperature to obtain the corrected photoelectric conversion model parameters includes: Based on the effective total irradiance, the photocurrent is corrected according to a linear relationship; Based on the effective total irradiance, the parallel resistance is corrected according to an inverse proportional relationship; Based on the operating temperature, an exponential model including the cubic term of bandgap energy and temperature is used to correct the reverse saturation current. Keep the series resistance constant; Based on the corrected photocurrent, parallel resistance, and reverse saturation current, the corrected photoelectric conversion model parameters are obtained.

5. The method for co-optimizing the optimal tilt angle of a building rooftop photovoltaic array according to claim 1, characterized in that, The arrangement of photovoltaic modules based on the preset tilt angle, the geometric dimensions of individual photovoltaic modules, the site dimensions, and true solar time shading constraints to obtain the maximum installed capacity and total number of modules at the preset tilt angle includes: Based on the target observation time on the winter solstice, convert the local time to true solar time; Calculate the solar altitude angle and solar azimuth angle based on the true solar time; Based on the solar altitude angle, solar azimuth angle, preset tilt angle, and component inclined surface length, calculate the projection length of the shadow cast by the front array on the rear array in the north-south direction; Calculate the minimum row spacing based on the projection length; Based on the geometric dimensions, the minimum row spacing, the site dimensions, and the component installation gap, the maximum number of installable rows and columns are calculated using an integer programming algorithm to obtain the maximum installed capacity and the total number of components. The calculation of the number of columns satisfies the even number constraint to adapt to the support structure.

6. The method for collaborative optimization of the optimal tilt angle of a building rooftop photovoltaic array according to claim 1, characterized in that, The step of calculating the levelized cost of electricity (LCOE) at the preset tilt angle based on the total lifecycle power generation of a single photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters includes: The total power generation of the photovoltaic array over its entire life cycle is calculated based on the total power generation of each individual photovoltaic module and the total number of modules. Calculate the fixed rental cost allocated per unit of electricity generation based on the maximum installed capacity and the land rent in the cost parameters. The initial investment and operating expenses are calculated based on the cost parameters to obtain the total life cycle cost. The initial investment includes the cost of the support structure, the cost of the components, the cost of the inverter and the balancing system, and the installation cost. The operating expenses include the operation and maintenance costs and the fixed rental costs. Based on the total life-cycle cost and total life-cycle power generation, the levelized cost per kilowatt-hour at the preset tilt angle is calculated using the net present value method.

7. A device for coordinating and optimizing the tilt angle of a building rooftop photovoltaic array, characterized in that, include: The acquisition module is used to acquire solar irradiance data of the area where the photovoltaic array is located, the electrical parameters and geometric dimensions of individual photovoltaic modules of the photovoltaic array, and the cost parameters and site dimensions for constructing the photovoltaic array. The power generation calculation module is used to obtain the total life cycle power generation of a single photovoltaic module at the preset tilt angle based on the solar irradiance data, the electrical parameters of the module, and the preset tilt angle. The arrangement module is used to arrange the photovoltaic modules according to the preset tilt angle, the geometric dimensions of the individual photovoltaic modules, the site dimensions, and the true solar time shading constraints, so as to obtain the maximum installed capacity and the total number of modules under the preset tilt angle. The cost calculation module is used to calculate the levelized cost of electricity (LCOE) at the preset tilt angle based on the total life-cycle power generation of the individual photovoltaic module, the total number of modules, the maximum installed capacity, and the cost parameters. The tilt angle determination module is used to determine the optimal tilt angle based on the levelized cost of electricity corresponding to each preset tilt angle within the preset tilt angle range, with the preset tilt angle having the lowest levelized cost of electricity. The cost calculation module is also used for: The initial investment and operating expenses are calculated based on the cost parameters to obtain the total life cycle cost. The initial investment includes the cost of the support structure, the cost of the components, the cost of the inverter and the balancing system, and the installation cost. The cost of the support structure is obtained through the following methods: The wind load shape coefficient is determined based on the preset tilt angle and the standard wind pressure at the location of the photovoltaic array; The standard value of wind load is calculated based on the wind load shape coefficient, the standard wind pressure, the preset wind pressure height variation coefficient, and the wind vibration coefficient. The design surface load is obtained by combining the load effects based on the standard value of wind load and the preset component dead load. The design surface load is converted into a line load acting on the purlins according to the preset purlin spacing, and the purlins are used to support the photovoltaic array; Based on the line load, the controlling design bending moment of the purlin is calculated according to the preset structural mechanics model; Based on the aforementioned controlling design bending moment, select the steel profile that meets the strength requirements and has the smallest mass per unit length from the pre-set standard steel profile library; Calculate the total steel consumption based on the selected steel profiles, total purlin length, number of support sets, and rear column length; Calculate the cost of the support structure based on the total amount of steel used and the unit price of steel.

8. An electronic device, characterized in that, include: At least one processor, at least one memory, and computer program instructions stored in the memory, which, when executed by the processor, implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, The method as described in any one of claims 1-6 is implemented when the computer program instructions are executed by the processor.

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