Real environment-oriented laminated solar cell efficiency optimization method

Abstract

The application discloses a real environment-oriented stacked solar cell efficiency optimization method, and belongs to the field of solar cell performance optimization and new energy technology. The method comprises the following steps: obtaining annual environmental parameters of a target area and discretizing the annual environmental parameters, establishing a stacked cell structure model and a light, electricity and heat multi-physical field coupling model, solving instantaneous output power hour by hour in the annual time scale and integrating the instantaneous output power to obtain annual energy output, and optimizing device parameters such as band gap with the maximum output as the target. The application overcomes the limitations of traditional static optimization based on standard test conditions, realizes multi-physical field coupling optimization based on the annual operation cycle by introducing real environment time sequence data and an environment-driven temperature model, and thus provides a theoretical basis for efficiency evaluation, band gap parameter selection and regional design of the stacked solar cell in a real operation environment.

Description

Technical Field

[0001] This invention relates to the fields of solar cell performance optimization and new energy technology, specifically to a method for optimizing the efficiency of tandem solar cells in real-world environments. Background Technology

[0002] Currently, most performance design and optimization methods for tandem solar cells are based on standard test conditions (STC) for parameter calculation and device matching, typically using the AM1.5G standard solar spectrum and a fixed operating temperature as boundary conditions. While these methods are suitable for performance analysis under laboratory conditions, they fail to reflect the actual operating conditions of solar cells in real outdoor environments.

[0003] In actual operation, environmental parameters such as ambient temperature, solar photon flux density, and wind speed vary with time and location, further affecting the light absorption, current matching, device temperature rise, and output performance of tandem solar cells. However, most existing technologies still use fixed spectral and temperature conditions for device optimization, lacking consideration of the characteristics of real-world environmental changes, leading to discrepancies between optimization results and actual operating conditions.

[0004] Furthermore, existing optimization methods typically analyze only single physical processes such as optical absorption or current matching, lacking a systematic study of the coupling effects of multiple physical fields including light, electricity, and heat. Changes in device operating temperature further affect key parameters such as semiconductor material bandgap, current output, and device voltage, but current technologies do not adequately consider the impact of temperature, making it difficult to accurately reflect device performance under long-term operating conditions.

[0005] Meanwhile, most existing technologies use instantaneous energy conversion efficiency as the optimization target, lacking an energy output evaluation mechanism based on the entire annual operating cycle. Due to differences in solar spectral distribution and climate conditions in different regions, the optimized parameters obtained based on standard test conditions may not necessarily correspond to the optimal power generation performance under actual operating conditions.

[0006] In addition, existing methods typically build models for specific device structures or material systems, lacking a unified optimization framework applicable to different regional environmental conditions and different stacked structures, resulting in limited model versatility and scalability.

[0007] Therefore, the existing technology still has the following problems: (1) Static optimization based on standard test conditions lacks adaptability to real operating environments; (2) The coupling of multiple physical fields such as light, electricity, and heat, as well as the influence of temperature, were not fully considered; (3) Lack of an energy output optimization mechanism based on the annual operating cycle; (4) There is a lack of universal optimization methods applicable to different regions and different stacked structures.

[0008] Therefore, there is an urgent need to propose a method for optimizing the efficiency of tandem solar cells in real-world environments, so as to improve the accuracy of calculating the limiting efficiency, selecting bandgap parameters, and designing regionalized tandem solar cells under real-world operating conditions. Summary of the Invention

[0009] The purpose of this invention is to provide a method for optimizing the efficiency of tandem solar cells under real-world conditions. By introducing regional environmental time-series data, multi-physics coupling models, and an annual energy output evaluation mechanism, the theoretical upper limit assessment and bandgap parameter optimization of tandem solar cells under real-world operating conditions can be achieved.

[0010] This invention provides a method for optimizing the efficiency of tandem solar cells in real-world environments, comprising the following steps: S1. Obtain environmental parameters of the target area during the annual operating cycle; the environmental parameters include solar photon flux density, ambient temperature and wind speed; and discretize the environmental parameters according to the time dimension to form a time series of the environmental parameters. S2. Establish a structural model of a tandem solar cell; the structural model is used to describe the absorption band, bandgap parameter, electrical output characteristics, thermal parameters, and connection constraints between sub-cells of each junction. S3. Establish a multi-physics coupling model of light, electricity, and heat; the multi-physics coupling model includes an optical model, an electrical model, and a thermal model; the optical model calculates the photocurrent density of each junction cell based on the effective absorption probability and solar photon flux density; the electrical model calculates the radiative recombination dark current density of each junction cell based on the blackbody radiation law with chemical potential, and introduces the non-radiative recombination current density; the thermal model introduces an environment-driven temperature model, dynamically calculates the operating temperature of the solar cell based on the ambient temperature, incident light power density, and wind speed, and uses the calculated solar cell operating temperature to update the parameters related to the solar cell operating temperature in the optical model and the electrical model; S4. Perform hourly solution over the entire year timescale, taking the annual time series of the environmental parameters as input, calculate the instantaneous output power at each time node through the multiphysics coupling model, and perform integral calculation on the instantaneous output power over the entire year operating cycle to obtain the annual energy output. S5. Using the annual energy output as the optimization target, optimize the device parameters of the tandem solar cell, including the band gap of each junction cell, to obtain the parameter combination that maximizes the annual energy output under real operating conditions.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention incorporates parameters such as solar photon flux density, ambient temperature, and wind speed from the real environment into the solar cell performance calculation process, enabling the optimization process to reflect the actual operating characteristics under different regions and climatic conditions, thereby improving the consistency between the solar cell optimization results and the actual operating conditions.

[0012] 2. This invention establishes a multi-physics coupling model of light, electricity, and heat, and introduces an environment-driven temperature model in the solution process, which can dynamically describe the influence of solar cell operating temperature changes on parameters such as bandgap, current output, and device voltage, thereby improving the accuracy and reliability of solar cell performance analysis.

[0013] 3. This invention uses annual energy output as the optimization objective. By solving and integrating the annual time-series environmental data, it achieves device parameter optimization based on the entire operating cycle. Compared to traditional optimization methods based on instantaneous efficiency, this invention can provide a theoretical upper limit reference for bandgap selection and structural design of tandem solar cells under real operating conditions.

[0014] 4. In the optimization process, the present invention introduces a dynamic current matching mechanism to enable each junction cell to maintain a better output matching relationship under time-varying conditions, thereby improving the overall energy conversion capability of the stacked structure under complex environmental conditions.

[0015] 5. The optimization framework established in this invention is applicable to different regional environmental conditions, different stacked structures, and different material systems. It has good versatility and scalability and can be used for the engineering design and regional application of stacked solar cells.

[0016] In summary, this invention achieves a technological shift in tandem solar cells from optimization under standard test conditions to optimization under real operating environments through real-world environment-driven, photoelectric-thermal coupling modeling, and year-round performance optimization. This provides a basis for efficiency evaluation, bandgap selection, and environmental adaptability design of tandem solar cells under practical application conditions. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a method for optimizing the efficiency of tandem solar cells in a real-world environment, according to an embodiment of the present invention. Figure 2This is a schematic diagram of the structure of a multiphysics coupling model that incorporates an environment-driven temperature model according to an embodiment of the present invention. Figure 3 This is an overall logical framework diagram of an embodiment of the present invention; Figure 4 The graph shows the calculated results of the theoretical limiting energy conversion efficiency throughout the year and the theoretical limiting benchmark efficiency under standard test conditions as a function of band gap in three typical real-world operating regions: Munich, Golmud, and West Texas, according to embodiments of the present invention. Figure 5 This is a comparative analysis chart of the theoretical limit energy conversion efficiency and the theoretical limit benchmark efficiency under standard test conditions for different real operating areas throughout the year, according to an embodiment of the present invention. Figure 6 The graph shows the calculated results of the theoretical limit energy conversion efficiency and the theoretical limit benchmark efficiency under standard test conditions throughout the year in three typical real-world operating areas of Munich, Golmud, and West Texas, as a function of the bandgap of the top cell in this embodiment of the invention. Figure 7 This is a graph showing the relationship between the bandgap of the top cell and the bandgap of the bottom cell of a two-terminal tandem solar cell on the theoretical limiting efficiency under the standard test conditions (STC, AM1.5G, 25℃) of an embodiment of the present invention. Figure 8 This is a graph showing the influence of the annual theoretical limit energy conversion efficiency in Golmud, Qinghai Province on the band gap of the top cell and the band gap of the bottom cell of a two-terminal tandem solar cell according to an embodiment of the present invention. Figure 9 This is a graph showing the relationship between the theoretical limiting energy conversion efficiency in West Texas (USA) region throughout the year and the band gap of the top and bottom cells of a two-terminal tandem solar cell, according to an embodiment of the present invention. Figure 10 This is a graph showing the relationship between the annual theoretical limit energy conversion efficiency in the Munich (Germany) region and the band gap of the top and bottom cells of a two-terminal tandem solar cell, according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] To address the issue that existing optimization methods for tandem solar cells primarily rely on static parameter design based on Standard Test Conditions (STC), which fails to reflect real-world outdoor operating environments, such as... Figure 1As shown, this invention provides a method for optimizing the efficiency of tandem solar cells in real-world environments, comprising the following steps: Step S1: Obtain the environmental parameters of the target area during the annual operating cycle; the environmental parameters include solar photon flux density, ambient temperature and wind speed; and discretize the environmental parameters according to the time dimension to form a time series of environmental parameters.

[0021] Specifically, this invention first constructs a real-world time-resolved input model. By acquiring the solar photon flux density, ambient temperature, and wind speed of the target area throughout the year, and then discretizing them according to the time dimension, a year-round time-series environmental input system is formed. .

[0022] Among them, in the first k Time nodes t k Under these conditions, environmental parameters can be expressed as: (1) in, ,, T This represents the sum of all time points throughout the year. The energy of the photon is E The solar photon flux density incident on the solar cell's light-receiving surface; T amb ( t k ( ) represents the ambient temperature; v wind ( t k ) represents wind speed, used to characterize the convective heat dissipation conditions on the surface of a device.

[0023] The aforementioned year-round time-series environmental input system serves as the external condition in the process of solving the performance of tandem solar cells, enabling device optimization to be extended from traditional standard test conditions to real outdoor operating environments.

[0024] Step S2: Establish a tandem solar cell structure model; the structure model is used to describe the absorption band, bandgap parameters, electrical output characteristics, thermal parameters, and connection constraints between sub-cells of each junction.

[0025] Specifically, taking a perovskite / silicon tandem solar cell as an example, this device includes a wide-bandgap perovskite top cell and a silicon bottom cell. The bandgap of the top cell can be set to... E g,top =1.62eV The bandgap of silicon-based solar cells can be set to... E g,bottom =1.12 eV. For the first... i Individual cells, whose spectral absorption range can be determined by band gapE g,i Or the corresponding cutoff wavelength λ g,i = hc / E g,i Determine, and combine with the first i Junction cell at photon energy of E Effective absorption probability at time α i ( E The following corrections are made: For a two-terminal series stacked structure, each junction cell satisfies a unified operating current condition (i.e., current matching condition), and the total output voltage is the sum of the operating voltages of each junction cell (i.e., total voltage superposition condition); for a stacked structure with independent output, the maximum output power of each junction cell is calculated separately and the power is superimposed; for a multi-junction series structure with three or more junctions, each junction cell is solved junction by junction and coupled through the series current matching condition and the total voltage superposition condition, rather than simplifying the entire stacked device into a single equivalent cell.

[0026] Step S3: Establish a multi-physics coupling model of light, electricity, and heat; the coupling model includes an optical model, an electrical model, and a thermal model, such as... Figure 2 As shown in the figure, the optical model calculates the photocurrent density of each junction cell based on the effective absorption probability and solar photon flux density; the electrical model calculates the radiative recombination dark current density of each junction cell based on the blackbody radiation law with chemical potential, and introduces the non-radiative recombination current density; the thermal model introduces an environment-driven temperature model, dynamically calculates the operating temperature of the solar cell based on the ambient temperature, incident light power density, and wind speed, and uses the calculated solar cell operating temperature to update the parameters related to the solar cell operating temperature in the optical and electrical models. In an alternative implementation, in the optical model, for the first junction cell in the stacked structure, its spectral absorption range is determined by the band gap of the first junction cell. E g,1 The decision is made. Specifically, in the energy domain, the first junction cell primarily absorbs photon energy. E ≥ E g,1 The incident light; in the wavelength domain, the corresponding absorption wavelength. λ The range is λ ≤ λ g,1 Among them, the cutoff wavelength corresponding to the bandgap of the first junction cell. λ g,1 = hc / E g,1 , h Let be Planck's constant. c It is the speed of light in a vacuum.

[0027] Therefore, the first junction cell at time node t k Photocurrent density at the following levels It can be represented as: (2) in, q It is the elementary charge; E g,1 This refers to the band gap of the first junction cell; α 1( E The first junction cell has a photon energy of... E Effective absorption probability at time; Φ sun ( E , t k (Time node) t k Below, photon energy is E The solar photon flux density incident on the solar cell's light-receiving surface.

[0028] For the first in the stacked structure i Junction cell, Assuming the band gap of each sub-cell in the tandem battery satisfies E g,1 > E g,2 >⋯> E g,N After the upper sub-cell absorbs high-energy photons, the first... i Junction cell's main energy absorption range E exist E g,i ≤ E < E g,i-1 Photons within the wavelength range; in the wavelength domain, the corresponding absorption wavelength. λ The range is λ g,i-1 < λ ≤ λ g,i Among them, the first i Cutoff wavelength corresponding to the band gap of a junction cell λ g,i = hc / E g,i , No. i -1 Cutoff wavelength corresponding to the bandgap of a junction cell λ g,i-1 = hc / E g,i-1 .

[0029] Therefore, the first i Junction cell at time nodet k Photocurrent density at the following levels It can be represented as: (3) in, E g,i-1 For the first i -1 band gap of junction cell; E g,i For the first i The band gap of a junction cell; α i ( E ) is the first i Junction cell at photon energy of E The effective absorption probability at any given time can include factors such as material absorption, absorption layer thickness, optical reflection, transmission loss, and parasitic absorption loss.

[0030] In one alternative implementation, in the electrical model, under bias voltage V i Next, the i In a junction cell, radiative recombination occurs, spontaneously emitting photons. According to the law of blackbody radiation with chemical potential, the radiative recombination dark current density can be given by the principle of fine equilibrium.

[0031] Specifically, for the first junction cell in a stacked structure, its radiative recombination dark current density It can be represented as: (4) in, q It is the elementary charge; E g,1 This refers to the band gap of the first junction cell; To ensure the device operates at a temperature of 0°C under zero bias conditions. Photon energy is E Blackbody radiation photon flux density at time; Boltzmann's constant; V 1 represents the operating voltage of the first junction cell; α 1( E The first junction cell has a photon energy of... E The effective absorption probability at that time; For the first in the stacked structure i Junction cell, its radiative recombination dark current density It can be represented as: (5) in, , E g,i For the first i The band gap of a junction cell; Eg,i-1 For the first i -1 band gap of junction cell; V i For the first i Operating voltage of a junction cell; α i ( E ) is the first i Junction cell at photon energy of E The effective absorption probability at that time.

[0032] In one alternative implementation, for a tandem solar cell with two ends connected in series, each junction cell satisfies a uniform operating current condition (i.e., current matching condition): (6) in, J op ( t k (Time node) t k Below, the uniform operating current density of the tandem solar cells at both ends connected in series; For the first i Junction cell at time node t k and pressure divider The net current density below; Furthermore, the total operating voltage satisfies (i.e., the total voltage superposition condition): (7) in, V op ( t k (Time node) t k The total operating voltage of the lower tandem solar cells, V i ( t k ) is the first i The operating voltage of a junction cell when it meets the uniform operating current condition.

[0033] It should be noted that in the electrical solution process, this invention treats each junction subcell in the tandem solar cell in a junction-by-junction manner, rather than equating the tandem device to a single solar cell. For the first... i The output current of a sub-cell is determined by the photogenerated current and the recombination current at the corresponding time point. The photogenerated current is determined by the real environmental spectrum and the spectral absorption characteristics of the sub-cell, while the recombination current is related to the sub-cell's operating voltage, device temperature, and material parameters.

[0034] Therefore, in one alternative implementation, the firsti Junction cell at time node and pressure divider The formula for calculating the net current density is: (8) in, Time node The photocurrent density generated by the real solar spectrum is shown below. The recombination current density includes both radiative and non-radiative recombination. Time node The operating temperature of the solar cell (calculated from a thermal model).

[0035] Composite current density For radiation composite current density Non-radiative composite current density The sum, its calculation expression is: (9); Among them, radiation recombination current density It can be calculated from the photon flux emitted by a blackbody with chemical potential. The nonradiative recombination current density can be expressed in diode form as follows: (10) in, For the first i Junction cell at solar cell operating temperature The nonradiative dark saturation current density is used to characterize the dark current intensity generated by the nonradiative recombination mechanism of the junction cell. For the first i The diode ideality factor of a junction cell is used to characterize the effect of nonradiative recombination current on the operating voltage division. The degree of sensitivity.

[0036] In one implementation, parameters related to the operating temperature of a solar cell can be categorized into optical parameters, electrical parameters, thermal parameters, and structural parameters. Optical parameters include sub-cell bandgap, effective absorption probability, or external quantum efficiency; electrical parameters include photogenerated current density, non-radiative dark saturation current density, recombination current density, diode ideality factor, and current-voltage characteristics; thermal parameters include ambient temperature, solar cell operating temperature, temperature coefficient, equivalent heat dissipation coefficient, and wind speed-related heat dissipation parameters; structural parameters include the number of sub-cells, the arrangement order of sub-cells in each junction, and whether the cells are connected in series or independently. These parameters are collectively used to establish a predictive model for the coupled optical, electrical, and thermal efficiency of tandem solar cells under real-world environmental input conditions.

[0037] In one optional embodiment, the present invention uses an environment-driven temperature model to calculate the operating temperature of the solar cell, the general form of which can be expressed as: (11) in, Time node The operating temperature of the solar cell is shown in units of ; Time node The ambient temperature is expressed in units of... ; Time node The incident light power density is expressed in W / m². 2 ; Time node The wind speed is measured in m / s. f T (·) is the function for calculating device temperature; θ T This is a set of temperature model parameters, which can be calibrated based on meteorological data of the target area, measured temperature data of solar cells or modules, empirical thermal models, thermal balance models, or thermal simulation results. The temperature model is used to establish the correspondence between real environmental inputs and device operating temperatures, enabling the device operating temperature to be dynamically updated with changes in ambient temperature, incident irradiance, and wind speed, and further used in the calculation of bandgap, current, voltage, and output power.

[0038] Specifically, this invention introduces an empirical device temperature model into the photoelectric-thermal coupling calculation process to characterize the changes in the operating temperature of solar cells under actual operating conditions. This model does not directly solve the strict thermal balance equation, but instead uses ambient temperature, incident light power density, and wind speed as input variables to calculate the actual operating temperature of the solar cell, thereby establishing a quantitative relationship between environmental conditions and device temperature rise.

[0039] This thermal model shows that the operating temperature of a solar cell is simultaneously affected by ambient temperature, incident light power density, and wind speed. Specifically, increased ambient temperature and incident light power density raise the cell's operating temperature, while increased wind speed enhances convective heat dissipation, thus lowering the solar cell's operating temperature. Using this thermal model, this invention can dynamically calculate the solar cell's operating temperature at each time point based on real-world environmental inputs, and further use this temperature in calculations of bandgap, voltage, current, and efficiency.

[0040] The thermal model of this invention constitutes the thermal input link in the opto-thermal coupling computational framework, thus freeing bandgap optimization from being limited to a fixed 25°. The standard test conditions can reflect temperature changes in real outdoor operating environments and their impact on the performance of tandem solar cells.

[0041] Step S4: Perform hourly solutions over the entire year timescale. Using the annual time series of environmental parameters as input, calculate the instantaneous output power at each time point through a multiphysics coupling model, and integrate the instantaneous output power over the entire year's operating cycle to obtain the annual energy output.

[0042] In one optional implementation, for a tandem solar cell with two ends connected in series, at a given time point, by adjusting the voltage division of each junction cell, the current matching condition of each junction cell is met, and the series operating current density and output voltage at that time point are obtained. The corresponding instantaneous output power can be expressed as: (12) in, Time node t k Instantaneous output power; J op ( t k (Time node) t k Below, the uniform operating current density of the tandem solar cells at both ends connected in series; V op ( t k (Time node) t k The total operating voltage of the lower tandem solar cells; For independently outputting tandem solar cells, the instantaneous output power calculation expression for each time point is: (13) in, Time node t k Instantaneous output power; Time node t k Next, the i The net current density of a junction cell; Time node t k Next, the i The working voltage of a junction cell.

[0043] In an alternative implementation, in step S4, annual energy production... AEPThe result is obtained by integrating the instantaneous output power over the entire year's time series, and is expressed as: (14) in, AEP For the annual energy output, Time node t k Instantaneous output power, T This represents the sum of all time points throughout the year.

[0044] Step S5: Using the annual energy output as the optimization objective, optimize the device parameters of the tandem solar cell, including the band gap of each junction cell, to obtain the optimal parameter combination that maximizes the annual energy output under real operating conditions (i.e., obtain the optimal device parameter combination that satisfies material physical constraints and structural constraints).

[0045] In one alternative implementation, the optimization objective in step S5 is to maximize annual energy output.

[0046] Specifically, such as Figure 3 As shown, this invention uses annual energy output as an optimization evaluation index. Under the conditions of satisfying sub-cell current matching, total voltage superposition, solar cell structural parameters and material physical constraints, it optimizes relevant parameters such as band gap of tandem solar cells, thereby obtaining annual energy output evaluation results based on theoretical efficiency calculation under real operating conditions.

[0047] In one optional embodiment, the method of the present invention further includes: Step S6: Calculate the total amount of incident solar energy in the target area over the entire year, and use the ratio of annual energy output to total incident solar energy as the theoretical limit energy conversion efficiency of the target area for the whole year. The theoretical limit of annual energy conversion efficiency is used to evaluate the upper limit of the theoretical power generation performance of tandem solar cells in the actual annual operating cycle under different target regions and / or different combinations of device parameters, and serves as an evaluation index for judging the quality of bandgap parameter combinations during the optimization process in step S5.

[0048] For the target area r The total amount of solar energy incident throughout the year is expressed as: (15) in, For target area r At the time point t k The incident light power density; Δ t k Time node t kThe corresponding discrete time step, in hours (h); Therefore, target area r The theoretical limit of energy conversion efficiency for the whole year is expressed as: (16) in, Let be the theoretical limit energy conversion efficiency for the target region r throughout the year. For target area r The total amount of incident solar energy over the entire year. For target area r Annual energy output.

[0049] The annual theoretical limit energy conversion efficiency represents the ratio of the annual theoretical limit output electrical energy of the target area to the annual incident solar energy. The same energy ratio definition is used for calculation and comparison in all actual operating areas.

[0050] For the standard test condition STC, since it uses a fixed AM1.5G solar spectrum, a fixed incident power density, and an operating temperature of 25°C, it does not use the annual time-series integration aperture of the real region, but uses the ratio of output power to incident power under fixed STC boundary conditions as the reference energy conversion efficiency. : (17) in, This represents the theoretical limiting output power density at the maximum power point of the device under fixed STC boundary conditions. The total incident power density corresponding to the AM1.5G reference spectrum is taken as 1000 W·m-2; both are calculated based on the unit light-receiving area.

[0051] Therefore, the efficiency in the actual operating area represents the theoretical limit energy conversion efficiency for the whole year, and STC represents the theoretical limit benchmark efficiency under fixed standard test conditions.

[0052] In summary, as Figure 3 As shown, this invention performs time-coupled solutions for tandem solar cells over a yearly timescale. At each time point, the solar photon flux density, ambient temperature, and wind speed parameters are input, and the instantaneous output power of the tandem solar cell is calculated using a joint optical, electrical, and thermal model. Subsequently, the instantaneous output power at each time point within the year is integrated to obtain the annual energy output of the tandem solar cell. This invention uses the annual energy output as the device optimization target. Under the conditions of satisfying device structural constraints, current matching constraints, and parameter range limitations, the parameters of the tandem solar cell are regionally optimized to obtain an optimized parameter combination suitable for the target real-world operating environment.

[0053] Unlike existing methods that rely on static optimization based on standard test conditions, this invention extends the performance analysis of tandem solar cells from single spectral conditions to year-round time-series environmental conditions, and expands current matching constraints from local instantaneous matching to dynamic matching throughout the entire operating cycle. Furthermore, by introducing an environment-driven temperature model, this invention allows the bandgap, output current, and operating voltage of the tandem solar cells to dynamically change with the actual operating environment. This establishes a photoelectric-thermal coupling relationship between environmental parameters, device temperature rise, and output performance, improving the physical consistency and practical engineering applicability of the device optimization results.

[0054] Therefore, the working principle of this invention can be summarized as follows: under real operating conditions, through regional environmental time-series data-driven, multi-physics field coupling solution and annual energy integral calculation, the theoretical efficiency assessment and bandgap parameter optimization of tandem solar cells are realized within the annual operating cycle. This transforms the device design from static optimal bandgap selection under traditional standard test conditions to regional optimization under real operating conditions, thereby providing theoretical reference for material selection, structural design and environmental adaptability assessment of solar cells in practical application scenarios.

[0055] like Figure 4 As shown, the red dashed line represents the standard test condition STC, and the theoretical limiting baseline efficiency is obtained based on an extended detailed equilibrium model under AM1.5G spectral and 25℃ conditions; the colored solid lines represent the annual theoretical limiting energy conversion efficiencies calculated based on the annual time series in Munich, Germany, Golmud, China, and West Texas, USA, respectively. Figure 4 The calculations show that under standard test conditions (AM1.5G, 25℃), the optimal bandgap of a single-junction solar cell is approximately 1.34 eV, corresponding to a theoretical limiting efficiency of approximately 33.76%. In contrast, under the actual annual solar spectrum time series, the annual theoretical limiting energy conversion efficiency-bandgap relationship curves show significant changes in different regions. Specifically, the optimal bandgap in Golmud remains close to 1.34 eV, while the optimal bandgap in West Texas and Munich shifts towards a higher bandgap of approximately 1.39 eV. The significant differences in the peak annual theoretical limiting energy conversion efficiency and curve trends across different regions indicate that the actual solar spectrum distribution alters the optimal absorption window and optimal parameter combination for single-junction solar cells.

[0056] Furthermore, in the higher bandgap region, the annual theoretical limit energy conversion efficiency (EPE) degradation trend also shows significant differences across different regions. The Munich region maintains a relatively high annual theoretical EPE within the high bandgap range, while the annual theoretical EPE decline is more pronounced in Golmud and West Texas. This indicates that the regional solar spectral composition not only affects the peak annual theoretical EPE of the device but also the applicability of wide bandgap absorbing materials. Therefore, determining device parameters solely using standard test conditions is insufficient to accurately reflect the performance of solar cells in real-world operating environments; device parameter optimization must be conducted in conjunction with regional solar spectral characteristics.

[0057] like Figure 5 As shown, this figure illustrates the relationship between the optimal bandgap and the theoretical limit of energy conversion efficiency (EPE) of solar cells under the actual annual solar spectrum time series conditions in different regions. The horizontal axis represents different geographical regions, including Golmud (China), West Texas (USA), and Munich (Germany); the left vertical axis represents the theoretical limit of energy conversion efficiency (%); and the right vertical axis represents the optimal bandgap (eV) for the corresponding region. Light blue bars represent the theoretical limit of efficiency under standard test conditions, dark blue bars represent the theoretical limit of energy conversion efficiency obtained from the actual operating region based on the annual time series and regional bandgap optimization, and green dashed lines represent the trend of optimal bandgap changes for different regions. Figure 5 It can be seen that the optimal bandgap of the device exhibits a significant regional dependence due to differences in solar spectral composition, atmospheric transmittance, and solar irradiance distribution across different regions. Specifically, the optimal bandgap in Golmud is approximately 1.34 eV, while the optimal bandgap in West Texas and Munich increases to approximately 1.39 eV. Furthermore, after regional environmental optimization under the conditions of a real annual solar spectrum time series, the annual theoretical limiting energy conversion efficiency in each actual operating region is improved compared to the results calculated using fixed standard bandgap parameters. For example, the annual theoretical limiting energy conversion efficiency in West Texas increased from 32.99% to 33.30%, and in Munich from 32.98% to 33.47%.

[0058] The above results show that traditional fixed-parameter designs based on standard test conditions are difficult to apply to the actual operating environments in different regions. By optimizing the device parameters in combination with regional solar spectral characteristics, a basis can be provided for the theoretical efficiency evaluation, bandgap selection, and environmental adaptability design of solar cells in real application scenarios.

[0059] like Figure 6As shown, in a perovskite / crystalline silicon tandem solar cell, keeping the parameters of the silicon bottom cell constant, the bandgap parameters of the perovskite top cell were calculated. The results show that under the real solar spectrum conditions throughout the year in different regions, the theoretical limiting energy conversion efficiency (EPE) of the device exhibits a trend of first increasing and then decreasing with the change in the top cell bandgap, and there is a clear optimal parameter range. Compared with the STC theoretical limiting benchmark efficiency, the peak value of the theoretical limiting EEP in the actual operating region decreases overall. Furthermore, there are significant differences in the annual theoretical limiting EEP curves between different regions, indicating that regional spectral characteristics affect the optimal bandgap matching relationship and the achievable annual theoretical limiting EEP of the perovskite / crystalline silicon tandem solar cell.

[0060] like Figure 7 As shown, the horizontal axis represents the band gap of the top cell. E g,top The vertical axis represents the band gap of the bottom cell. E g,bottom The color represents the theoretical limiting efficiency (STC) for the corresponding bandgap combination, and the black dot represents the optimal bandgap combination. Figure 7 It can be seen that, under standard test conditions, by jointly scanning the bandgap parameters of the top and bottom cells of the tandem solar cell, the device achieves the highest STC theoretical limit efficiency of approximately 45.57% near the bandgap of the top cell (approximately 1.59 eV) and the bandgap of the bottom cell (approximately 0.94 eV). The STC theoretical limit efficiency distribution results indicate that the spectral distribution relationship in the tandem structure and the current matching state between the sub-cells significantly affect the overall performance of the device.

[0061] like Figure 8 As shown, the horizontal axis represents the band gap of the top cell. E g,top The vertical axis represents the band gap of the bottom cell. E g,bottom The color represents the theoretical limit of energy conversion efficiency for the entire year under the corresponding bandgap combination, and the black dot represents the position of the optimal bandgap combination. Figure 8 It can be seen that under the actual annual solar spectrum time series conditions in the Golmud area, the optimal bandgap combination of the device shifts significantly, with the optimal bandgap of the top cell increasing to approximately 1.65 eV and the optimal bandgap of the bottom cell increasing to approximately 0.97 eV, corresponding to a maximum annual theoretical limit energy conversion efficiency of approximately 42.57%. Compared to standard test conditions, the stronger shortwave radiation and higher solar irradiance in high-altitude areas alter the optimal spectral distribution of the tandem cells, making a relatively wide bandgap structure more suitable for the top cell.

[0062] like Figure 9 As shown, the horizontal axis represents the band gap of the top cell. E g,top The vertical axis represents the band gap of the bottom cell.E g,bottom The color represents the theoretical limit of energy conversion efficiency for the entire year under the corresponding bandgap combination, and the black dot represents the position of the optimal bandgap combination. Figure 9 It can be seen that under the true solar spectrum throughout the year in West Texas, the optimal top cell bandgap of the device is approximately 1.65 eV, and the optimal bottom cell bandgap is approximately 0.95 eV, corresponding to a maximum theoretical annual limit energy conversion efficiency of approximately 43.06%. Compared to standard test conditions, the optimal top cell bandgap also shifts towards a higher bandgap, while the bottom cell parameters change less. This indicates that under high direct irradiance conditions, the device's ability to utilize high-energy photons is enhanced, leading to a change in the optimal bandgap combination.

[0063] like Figure 10 As shown, the horizontal axis represents the band gap of the top cell. E g,top The vertical axis represents the band gap of the bottom cell. E g,bottom The color represents the theoretical limit of energy conversion efficiency for the entire year under the corresponding bandgap combination, and the black dot represents the position of the optimal bandgap combination. Figure 10 It can be seen that under the true solar spectrum throughout the year in the Munich region, the optimal bandgap combination of the devices further shifts towards the higher bandgap region. Specifically, the optimal bandgap of the top cell increases to approximately 1.81 eV, and the optimal bandgap of the bottom cell increases to approximately 1.13 eV, corresponding to a maximum theoretical annual limit energy conversion efficiency of approximately 41.75%. Compared with standard test conditions, the changes in optimal parameters in this region are more significant, indicating that the higher proportion of scattered light in high-latitude regions leads to changes in the optimal absorption window of the tandem solar cells, thereby affecting the optimal bandgap matching relationship of the devices.

[0064] comprehensive Figures 7 to 10 It can be seen that there are significant differences in the theoretical limit of energy conversion efficiency and the optimal bandgap combination throughout the year in different real-world operating regions. Traditional fixed-parameter designs based on standard test conditions are difficult to apply to the actual operating environments of different regions. This invention, by combining regional environmental spectral characteristics, photoelectric-thermal coupling solutions, and year-round operating cycle optimization, achieves regional parameter optimization of tandem solar cells in real outdoor environments, providing a basis for evaluating the theoretical upper limit of device energy conversion performance and for regional environmental adaptability design.

[0065] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for optimizing the efficiency of tandem solar cells in real-world environments, characterized in that, Includes the following steps: S1. Obtain environmental parameters of the target area during the annual operating cycle; the environmental parameters include solar photon flux density, ambient temperature and wind speed; and discretize the environmental parameters according to the time dimension to form a time series of the environmental parameters. S2. Establish a structural model of a tandem solar cell; the structural model is used to describe the absorption band, bandgap parameter, electrical output characteristics, thermal parameters, and connection constraints between sub-cells of each junction. S3. Establish a multi-physics coupling model of light, electricity, and heat; the multi-physics coupling model includes an optical model, an electrical model, and a thermal model; the optical model calculates the photocurrent density of each junction cell based on the effective absorption probability and solar photon flux density; the electrical model calculates the radiative recombination dark current density of each junction cell based on the blackbody radiation law with chemical potential, and introduces the non-radiative recombination current density; the thermal model introduces an environment-driven temperature model, dynamically calculates the operating temperature of the solar cell based on the ambient temperature, incident light power density, and wind speed, and uses the calculated solar cell operating temperature to update the parameters related to the solar cell operating temperature in the optical model and the electrical model; S4. Perform hourly solution over the entire year timescale, taking the annual time series of the environmental parameters as input, calculate the instantaneous output power at each time node through the multiphysics coupling model, and perform integral calculation on the instantaneous output power over the entire year operating cycle to obtain the annual energy output. S5. Using the annual energy output as the optimization target, optimize the device parameters of the tandem solar cell, including the band gap of each junction cell, to obtain the parameter combination that maximizes the annual energy output under real operating conditions.

2. The method according to claim 1, characterized in that, In the optical model, the photogenerated current density of the first junction cell in the stacked structure is calculated using the following formula: （2） in, q It is the elementary charge; E g,1 This refers to the band gap of the first junction cell; α 1( E The first junction cell has a photon energy of... E Effective absorption probability at time; Φ sun ( E , t k (Time node) t k Below, photon energy is E The solar photon flux density incident on the solar cell's light-receiving surface; For the first in the stacked structure i The photocurrent density of a junction cell is calculated using the following formula: （3） in, , E g,i-1 For the first i -1 band gap of junction cell; E g,i For the first i The band gap of a junction cell; α i ( E ) is the first i Junction cell at photon energy of E The effective absorption probability at that time.

3. The method according to claim 1, characterized in that, In the electrical model, for the first junction cell in the stacked structure, its radiative recombination dark current density is... It can be represented as: （4） in, q It is the elementary charge; E g,1 This refers to the band gap of the first junction cell; To ensure the device operates at a temperature of 0°C under zero bias conditions. Photon energy is E Blackbody radiation photon flux density at time; Boltzmann's constant; V 1 represents the operating voltage of the first junction cell; α 1( E The first junction cell has a photon energy of... E The effective absorption probability at that time; For the first in the stacked structure i Junction cell, its radiative recombination dark current density It can be represented as: （5） in, , E g,i For the first i The band gap of a junction cell; E g,i-1 For the first i -1 band gap of junction cell; V i For the first i Operating voltage of a junction cell; α i ( E ) is the first i Junction cell at photon energy of E The effective absorption probability at that time.

4. The method according to claim 3, characterized in that, For a tandem solar cell with two ends connected in series, all subcells must meet the same operating current condition: （6） in, J op ( t k (Time node) t k Below, the uniform operating current density of the tandem solar cells at both ends connected in series; For the first i Junction cell at time node and pressure divider The net current density below; Furthermore, the total operating voltage satisfies: （7） in, V op ( t k (Time node) t k The total operating voltage of the lower tandem solar cells, V i ( t k ) is the first i The operating voltage of a junction cell when it meets the uniform operating current condition.

5. The method according to claim 4, characterized in that, The first i Junction cell at time node and pressure divider The expression for calculating the net current density is: （8） in, Time node The photocurrent density generated by the real solar spectrum is shown below. For composite current density, Time node Lower solar cell operating temperature; Composite current density For radiation composite current density Non-radiative composite current density The sum, its calculation expression is: （9）； Nonradiative composite current density The calculation expression is: （10） in, For the first i Junction cell at solar cell operating temperature The nonradiative dark saturation current density is as follows; For the first i The diode ideality factor of a junction cell.

6. The method according to claim 1, characterized in that, The operating temperature of the solar cell is calculated using the following environmentally driven temperature model: （11） in, Time node The operating temperature of the solar cell is shown in units of ; Time node The ambient temperature is expressed in units of... ; Time node The incident light power density is expressed in W / m². 2 ; Time node The wind speed below, in m / s; f T (·) is the function for calculating device temperature; θ T This is the set of parameters for the temperature model.

7. The method according to claim 1, characterized in that, In S4, for a tandem solar cell with two ends connected in series, the instantaneous output power calculation expression at each time point is: （12） in, Time node t k Instantaneous output power; J op ( t k (Time node) t k Below, the uniform operating current density of the tandem solar cells at both ends connected in series; V op ( t k (Time node) t k The total operating voltage of the lower tandem solar cells; For independently outputting tandem solar cells, the instantaneous output power calculation expression for each time point is: （13） in, Time node t k Instantaneous output power; Time node t k Next, the i The net current density of a junction cell; Time node t k Next, the i The working voltage of a junction cell.

8. The method according to claim 7, characterized in that, In S4, the annual energy output is obtained by integrating the instantaneous output power over the entire year's time series over time, expressed as: （14） in, AEP For the annual energy output, Time node t k Instantaneous output power, T This represents the sum of all time points throughout the year. The method further includes: S6. Calculate the total amount of incident solar energy in the target area over the entire year, and use the ratio of the annual energy output to the total amount of incident solar energy as the annual theoretical limit energy conversion efficiency of the target area. The theoretical limit energy conversion efficiency for the whole year is used to evaluate the upper limit of the theoretical power generation performance of tandem solar cells in the actual annual operating cycle under different target regions and / or different combinations of device parameters, and serves as an evaluation index for judging the quality of the bandgap parameter combination in the S5 optimization solution process.

9. The method according to claim 8, characterized in that, The optimization objective in S5 is to maximize the annual energy output. The formula for calculating the total amount of incident solar energy in the target area over the entire year is as follows: （15） in, For target area r At the time point t k The incident light power density, Δ t k Time node t k The corresponding discrete time step, in hours (h); The formula for calculating the annual theoretical limit energy conversion efficiency of the target region is as follows: （16） in, Let be the theoretical limit energy conversion efficiency for the target region r throughout the year. For target area r The total amount of incident solar energy over the entire year. For target area r Annual energy output.

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