Adaptive fractional order MPPT control method and device for perovskite solar cell

Abstract

The application discloses a kind of self-adaptive fractional order MPPT control method and device for perovskite solar cell, comprising: obtaining the output current and output voltage of PSCs;Based on output current and output voltage, determine the target operating condition and corresponding fractional order parameter of PSCs belonging to;Based on target operating condition, determine the target perturbation step function and target perturbation switching frequency function corresponding to PSCs;Based on target perturbation step function, target perturbation switching frequency function and fractional order parameter, determine the adaptive adjustment strategy corresponding to PSCs, and adjust PSCs based on adaptive adjustment strategy.The application realizes the adaptive adjustment of PSC, improves the energy conversion efficiency of photovoltaic system, reduces the power oscillation and tracking error caused by hysteresis effect, without additional material cost, provides an effective technical scheme for low-cost, high-performance and large-scale industrial application of perovskite solar cell.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and in particular to an adaptive fractional-order MPPT control method and apparatus for perovskite solar cells. Background Technology

[0002] Perovskite solar cells (PSCs), as an emerging photovoltaic technology, have become one of the most promising materials for solar cells. However, perovskite solar cells exhibit anomalous hysteresis during testing, leading to a significant reduction in output efficiency when combined with power electronic converters and MPPT controllers to construct PSC photovoltaic systems.

[0003] In practical applications, the overall performance of a photovoltaic power generation system depends not only on the materials themselves but also on the control strategy. Furthermore, the hysteresis effect of the aforementioned PSCs can interfere with the maximum power point tracking of traditional MPPT algorithms (such as adaptive P&O algorithms, fuzzy logic control, neural networks, and machine learning), leading to misjudgments, interfering with the tracking accuracy, and causing power oscillations and tracking errors.

[0004] In existing technologies, the suppression of the hysteresis effect of perovskite solar cells mainly focuses on material-level optimization, such as interface passivation, material modification, and structural engineering. However, these methods are usually accompanied by problems such as increased manufacturing costs, increased process complexity, and insufficient environmental stability, and cannot provide an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells. Summary of the Invention

[0005] The present invention aims to at least partially solve one of the technical problems in the related art.

[0006] Therefore, one objective of this invention is to propose an adaptive fractional-order MPPT control method for perovskite solar cells. This method determines the adaptive adjustment strategy corresponding to the PSCs based on the target disturbance step size function, the target disturbance switching frequency function, and fractional-order parameters determined by the target operating conditions of the PSCs. The PSCs are then adjusted based on the adaptive adjustment strategy, thereby improving the energy conversion efficiency of the photovoltaic system, reducing power oscillations and tracking errors caused by hysteresis, and without increasing material costs. This provides an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells.

[0007] Another object of the present invention is to provide an adaptive fractional-order MPPT control device for perovskite solar cells.

[0008] To achieve the above objectives, one embodiment of the present invention proposes an adaptive fractional-order MPPT control method for perovskite solar cells, comprising:

[0009] Obtain the output current and output voltage of the perovskite solar cells (PSCs);

[0010] Based on the output current and the output voltage, determine the target operating condition and corresponding fractional-order parameters of the PSCs;

[0011] Based on the target operating conditions, determine the target disturbance step size function and the target disturbance switching frequency function corresponding to the PSCs;

[0012] Based on the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameter, an adaptive adjustment strategy corresponding to the PSCs is determined, and the PSCs are adjusted based on the adaptive adjustment strategy.

[0013] The adaptive fractional-order MPPT control method for perovskite solar cells according to embodiments of the present invention may also have the following additional technical features:

[0014] Further, based on the output current and the output voltage, the target operating condition and corresponding fractional-order parameters of the PSCs are determined, including:

[0015] Construct at least one reference curve for PSCs, and obtain the boundary curve based on the at least one reference curve;

[0016] Multiple sampling points corresponding to the PSCs are obtained, the boundary curve is used to verify the multiple sampling points, and a sampling vector is obtained based on the sampling points that pass the verification.

[0017] Based on the sampling vector and the at least one reference curve, the target reference curve is determined;

[0018] The current in the target reference curve corresponding to the output voltage is determined as the reference current;

[0019] Based on the output current and the reference current, the target operating condition to which the PSCs belong is determined.

[0020] Based on the target reference curve and the output current, the corresponding fractional-order parameters are determined.

[0021] Further, determining the target reference curve based on the sampling vector and the at least one reference curve includes:

[0022] Calculate the normalized root mean square error between the sampled current and each reference curve in the sampling vector;

[0023] The reference curve corresponding to the smallest normalized root mean square error is determined as the target reference curve.

[0024] Further, determining the corresponding fractional-order parameters based on the target reference curve and the output current includes:

[0025] Based on the output current and the target reference curve, the corresponding fractional-order parameters are determined using a parameter calculation formula, which is:

[0026]

[0027] Among them, I in For the output current, I ref As a reference, C represents the current value under the same voltage on the curve. α dV / dt is the fractional capacitance value, dV / dt is the voltage change rate, and α is the fractional parameter.

[0028] Further, determining the target operating condition of the PSCs based on the output current and the reference current includes:

[0029] The difference between the output current and the reference current is calculated to obtain the difference result.

[0030] If the difference result is greater than the preset value, then the target operating condition to which the PSCs belong is determined to be the first operating condition;

[0031] If the difference result is less than the preset value, then the target operating condition to which the PSCs belong is determined to be the second operating condition.

[0032] Further, determining the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameters includes:

[0033] Based on the target perturbation step size function and the fractional-order parameter, the target perturbation step size corresponding to the PSCs is determined;

[0034] Based on the target disturbance switching frequency function and the fractional-order parameter, the target disturbance switching frequency corresponding to the PSCs is determined;

[0035] Based on the target perturbation step size and the target perturbation switching frequency, the adaptive adjustment strategy corresponding to the PSCs is determined.

[0036] To achieve the above objectives, another embodiment of the present invention provides an adaptive fractional-order MPPT control device for perovskite solar cells, the device comprising:

[0037] The acquisition module is used to acquire the output current and output voltage of the perovskite solar cells (PSCs).

[0038] The first determining module is used to determine the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and the output voltage.

[0039] The second determining module is used to determine the target disturbance step size function and the target disturbance switching frequency function corresponding to the PSCs based on the target operating conditions.

[0040] The adjustment module is used to determine the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, the target perturbation switching frequency function and the fractional-order parameter, and to adjust the PSCs based on the adaptive adjustment strategy.

[0041] This invention proposes an adaptive fractional-order MPPT control method and apparatus for perovskite solar cells. The method includes: acquiring the output current and output voltage of the perovskite solar cell PSCs; determining the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and output voltage; determining the target perturbation step size function and target perturbation switching frequency function of the PSCs based on the target operating condition; determining the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters; and adjusting the PSCs based on the adaptive adjustment strategy. This invention determines the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters determined through the target operating condition of the PSCs, and adjusts the PSCs based on the adaptive adjustment strategy. This improves the energy conversion efficiency of the photovoltaic system, reduces power oscillations and tracking errors caused by hysteresis, and does not require additional material costs, providing an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells.

[0042] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0043] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 A flowchart of an adaptive fractional-order MPPT control method for perovskite solar cells according to an embodiment of the present invention;

[0045] Figure 2The upper and lower envelope curves are fitted to the endpoints of the average values ​​of the forward and reverse scan curves in the embodiments of the present invention.

[0046] Figure 3 This is a schematic diagram of the operating conditions of the PSC in an embodiment of the present invention;

[0047] Figure 4 This is a schematic diagram of the structure of a PSCs system according to an embodiment of the present invention;

[0048] Figure 5 This is a comparison chart of the results of an adaptive fractional MPPT control method proposed in an embodiment of the present invention;

[0049] Figure 6 The figure shows a comparison of the results of applying the adaptive fractional MPPT control method proposed in this invention and the traditional P&O algorithm to PSC photovoltaic systems with different hysteresis effects.

[0050] Figure 7 This is a schematic diagram of an adaptive fractional-order MPPT control device for perovskite solar cells according to an embodiment of the present invention. Detailed Implementation

[0051] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0052] Based on the above description, and with reference to the accompanying drawings, an adaptive fractional-order MPPT control method and apparatus for perovskite solar cells according to embodiments of the present invention are described.

[0053] First, an adaptive fractional-order MPPT control method for perovskite solar cells according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0054] Figure 1 This is a flowchart of an adaptive fractional-order MPPT control method for perovskite solar cells according to an embodiment of the present invention.

[0055] like Figure 1 As shown, the adaptive fractional-order MPPT control method for perovskite solar cells includes the following steps:

[0056] Step S1: Obtain the output current and output voltage of PSCs.

[0057] In one embodiment of the present invention, the real-time output current and output voltage of PSCs can be obtained.

[0058] Step S2: Based on the output current and output voltage, determine the target operating condition to which the PSCs belong.

[0059] In one embodiment of the present invention, after obtaining the output current and output voltage of PSCs through the above steps, the target operating condition of PSCs can be determined based on the output current and output voltage.

[0060] Specifically, in one embodiment of the present invention, the method for determining the target operating condition of PSCs based on output current and output voltage may include the following steps:

[0061] Step S21: Construct at least one reference curve for PSCs, and obtain the boundary curve based on at least one reference curve;

[0062] Step S22: Obtain multiple sampling points corresponding to PSCs, verify the multiple sampling points using boundary curves, and obtain the sampling vector based on the verified sampling points;

[0063] Step S23: Determine the target reference curve based on the sampling vector and at least one reference curve;

[0064] Step S24: Determine the current in the target reference curve corresponding to the output voltage as the reference current;

[0065] Step S25: Based on the output current and the reference current, determine the target operating condition to which the PSCs belong.

[0066] Step S26: Determine the corresponding fractional-order parameters based on the target reference curve and the output current.

[0067] In one embodiment of the present invention, JV curves of PSC forward and reverse scans can be obtained under different bias voltage scanning conditions, and linear interpolation is performed on each set of forward and reverse scan curves within their common voltage range, and the average is calculated point by point to construct at least one reference curve (e.g., 6 curves) under different bias voltages.

[0068] In one embodiment of the present invention, the endpoint coordinates of each reference curve can be extracted to form corresponding upper and lower endpoint envelope curves (e.g., ...) through interpolation. Figure 2 As shown in the figure, the boundary curve is determined based on the range to which all the upper and lower endpoint envelope curves belong. That is, the boundary curve is the minimum boundary that includes all the upper and lower endpoint envelope curves, so that the current output boundary of the PSC under the bias voltage condition can be effectively characterized.

[0069] Furthermore, in one embodiment of the present invention, sampling is performed on real-time running PSCs to obtain multiple sampling points corresponding to the PSCs, and the multiple sampling points are verified using a boundary curve. A sampling vector is obtained based on the verified sampling points, wherein each sampling point includes corresponding voltage and current. In one embodiment of the present invention, the method for verifying multiple sampling points using a boundary curve may include: if the coordinate points corresponding to the voltage and current of a sampling point are not within the boundary curve, it indicates that the sampling point is abnormal data, and the sampling point fails verification and can be discarded; if the coordinate points corresponding to the voltage and current of a sampling point are within the boundary curve, it indicates that the sampling point is normal data, and the sampling point passes verification.

[0070] For example, in one embodiment of the present invention, the above sampling vector may be:

[0071] J s,k =[J s,0 J s,1 J s,2 ,...,J s,9 ] T

[0072] Among them, J s,k For the k-th sampling point V k The current density measured at the location, and each term J in the sampling vector s,k The corresponding voltage corresponds to the voltage in the target reference curve, thus ensuring the alignment of the sampling vector and the reference curve on the voltage axis, so that the subsequent error calculation and matching of the target reference curve have a clear correspondence and comparability.

[0073] Furthermore, in one embodiment of the present invention, the method for determining a target reference curve based on a sampling vector and at least one reference curve may include: calculating the normalized root mean square error between the sampling current in the sampling vector and each reference curve, and determining the reference curve corresponding to the smallest normalized root mean square error as the target reference curve.

[0074] Furthermore, in one embodiment of the present invention, after determining the target reference curve through the above steps, the current of the output voltage in the target reference curve can be determined as the reference current.

[0075] Furthermore, in one embodiment of the present invention, the method for determining the target operating condition of PSCs based on the output current and the reference current may include: performing a difference operation on the output current and the reference current to obtain a difference result; if the difference result is greater than a preset value, then the target operating condition of PSCs is determined to be a first operating condition; if the difference result is less than the preset value, then the target operating condition of PSCs is determined to be a second operating condition. The preset value can be 0.

[0076] Figure 3 This is a schematic diagram of a reference curve and a target operating condition proposed in an embodiment of the present invention. Figure 3 As shown, ΔI c Let ΔI be the difference between the output current and the reference current. c If ΔI > 0, then the target operating condition to which PSCs belongs is determined to be the first operating condition; if ΔI c If <0, then the target operating condition to which PSCs belong is determined to be the second operating condition.

[0077] Furthermore, in one embodiment of the present invention, the method for determining the corresponding fractional-order parameters based on the target reference curve and the output current may include: determining the corresponding fractional-order parameters based on the output current and the target reference curve using a parameter calculation formula, wherein the parameter calculation formula is:

[0078]

[0079] Among them, I in For the output current, I ref C represents the current value at the same voltage on the target reference curve. α dV / dt is the fractional capacitance value, dV / dt is the voltage change rate, and α is the fractional parameter.

[0080] Step S3: Based on the target operating conditions, determine the target disturbance step size function and the target disturbance switching frequency function corresponding to PSCs.

[0081] In one embodiment of the present invention, after determining the target operating condition through the above steps, the target disturbance step size function and the target disturbance switching frequency function corresponding to PSCs can be determined based on the target operating condition.

[0082] In one embodiment of the present invention, different operating conditions correspond to different disturbance step size functions and disturbance switching frequency functions.

[0083] Specifically, in one embodiment of the present invention, if the target operating condition is the first operating condition, the target disturbance step size function corresponding to PSCs is determined to be: ΔV s-1 =ΔV init ·sgn(ΔI c The target disturbance switching frequency function is: Δf·(α-1); s-1 =sgn(ΔI) c )·(-α)·f s_min .

[0084] In one embodiment of the present invention, if the target operating condition is the second operating condition, the target disturbance step size function corresponding to PSCs is determined to be: ΔV s-2 =ΔV init·sgn(ΔI c The target disturbance switching frequency function is: Δf·(α-1); s-2 =sgn(ΔI) c )·(-α)·f s_min .

[0085] Where, ΔV init f represents the initial perturbation step size. s_min This indicates the minimum switching frequency.

[0086] Step S4: Based on the target disturbance step size function, the target disturbance switching frequency function, and the fractional-order parameters, determine the adaptive adjustment strategy corresponding to the PSCs, and adjust the PSCs based on the adaptive adjustment strategy.

[0087] In one embodiment of the present invention, after determining the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameter through the above steps, the adaptive adjustment strategy corresponding to the PSCs can be determined based on the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameter, and the PSCs can be adjusted based on the adaptive adjustment strategy.

[0088] Specifically, in one embodiment of the present invention, the method for determining the adaptive adjustment strategy corresponding to PSCs based on the target perturbation step size function, the target perturbation switching frequency function, and fractional-order parameters may include the following steps:

[0089] Step S41: Determine the target perturbation step size corresponding to PSCs based on the target perturbation step size function and fractional-order parameters;

[0090] Step S42: Determine the target disturbance switching frequency corresponding to PSCs based on the target switching frequency function and fractional-order parameters;

[0091] Step S43: Determine the adaptive adjustment strategy corresponding to PSCs based on the target perturbation step size and the target perturbation switching frequency.

[0092] In one embodiment of the present invention, fractional-order parameters can be substituted into the target perturbation step size function to determine the target perturbation step size corresponding to PSCs. Also, in one embodiment of the present invention, fractional-order parameters can be substituted into the target perturbation switching frequency function to determine the target perturbation switching frequency corresponding to PSCs.

[0093] Furthermore, in one embodiment of the present invention, the target perturbation step size ΔV is determined through the above steps. s and the target disturbance switching frequency Δf s Then, based on the target step size ΔV and the target switching frequency f s Determine the adaptive adjustment strategy corresponding to PSCs.

[0094] Specifically, in one embodiment of the present invention, the method for determining the adaptive adjustment strategy corresponding to PSCs based on the target perturbation step size and the target perturbation switching frequency may include: if the target operating condition is the first operating condition, then ΔI c A value greater than 0 indicates that the current PSC performance is better than the reference state. Therefore, the target step size ΔV and target switching frequency f need to be reduced synchronously according to the corresponding perturbation step size function and perturbation switching frequency function. s If the target operating condition is the first operating condition, then ΔI c A value less than 0 indicates poor PSC performance. In this case, the target step size ΔV and target switching frequency f should be increased synchronously according to the corresponding perturbation step size function and perturbation switching frequency function. s .

[0095] In one embodiment of the present invention, after determining the adaptive adjustment strategy through the above steps, the PSCs can be adjusted according to the adaptive adjustment strategy so that the photovoltaic system composed of PSCs is at the maximum power point.

[0096] In one embodiment of the present invention, Figure 4 This is a schematic diagram of the structure of a PSCs system proposed in an embodiment of the present invention. Figure 4 As shown, after determining the adaptive adjustment strategy corresponding to PSCs through the above steps, the Boost converter can be controlled by the controller to perform the adaptive adjustment strategy, so that the perovskite solar cell operates at the maximum power point.

[0097] Figure 5 This is a comparison chart showing the results of an adaptive fractional-order MPPT control method proposed in an embodiment of the present invention. The illumination intensity is 100 mW / cm². 2 Under the same conditions and with the same hysteresis factor, the adaptive fractional MPPT algorithm proposed in this invention improves the MPPT efficiency of the PSC photovoltaic system by 2.23% compared with the existing P&O algorithm, thereby effectively mitigating the adverse effects of hysteresis and verifying the effectiveness of the proposed method in suppressing hysteresis.

[0098] Figure 6 A comparison was made between a system using the traditional P&O algorithm (H = 3.72%) and a system using the Fo-ASF MPPT algorithm (H = 11.67%). The results show that the proposed algorithm achieves a performance improvement level similar to materials engineering optimization methods without changing the device materials or structure, thus providing an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells.

[0099] An adaptive fractional-order MPPT control method for perovskite solar cells, proposed according to embodiments of the present invention, includes: acquiring the output current and output voltage of the perovskite solar cell PSCs; determining the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and output voltage; determining the target perturbation step size function and target perturbation switching frequency function corresponding to the PSCs based on the target operating condition; determining the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters; and adjusting the PSCs based on the adaptive adjustment strategy. This invention determines the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters determined through the target operating condition of the PSCs, and adjusts the PSCs based on the adaptive adjustment strategy, thereby improving the energy conversion efficiency of the photovoltaic system, reducing power oscillations and tracking errors caused by hysteresis, and without increasing material costs, providing an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells.

[0100] Next, with reference to the accompanying drawings, an adaptive fractional-order MPPT control device for perovskite solar cells according to an embodiment of the present invention is described.

[0101] Figure 7 This is a schematic diagram of an adaptive fractional-order MPPT control device for perovskite solar cells according to an embodiment of the present invention.

[0102] like Figure 7 As shown, the adaptive fractional-order MPPT control device 10 for perovskite solar cells includes:

[0103] The acquisition module 701 is used to acquire the output current and output voltage of perovskite solar cells (PSCs).

[0104] The first determining module 702 is used to determine the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and output voltage.

[0105] The second determining module 703 is used to determine the target disturbance step size function and the target disturbance switching frequency function corresponding to the PSCs based on the target operating conditions.

[0106] The adjustment module 704 is used to determine the adaptive adjustment strategy corresponding to PSCs based on the target disturbance step size function, the target disturbance switching frequency function and the fractional-order parameters, and to adjust the PSCs based on the adaptive adjustment strategy.

[0107] Furthermore, the aforementioned first determining module 702 is specifically used for:

[0108] Construct at least one reference curve for PSCs, and obtain the boundary curve based on at least one reference curve;

[0109] Obtain multiple sampling points corresponding to PSCs, verify the multiple sampling points using boundary curves, and obtain the sampling vector based on the sampling points that pass the verification;

[0110] The target reference curve is determined based on the sampling vector and at least one reference curve;

[0111] The current corresponding to the output voltage in the target reference curve is determined as the reference current;

[0112] Based on the output current and the reference current, the target operating condition of the PSCs is determined.

[0113] Based on the target reference curve and the output current, the corresponding fractional-order parameters are determined.

[0114] Furthermore, the aforementioned first determining module 702 is also used for:

[0115] Calculate the normalized root mean square error between the sampled current and each reference curve in the sampling vector;

[0116] The reference curve corresponding to the smallest normalized root mean square error is determined as the target reference curve.

[0117] Furthermore, the aforementioned first determining module 702 is also used for:

[0118] Based on the output current and the target reference curve, the corresponding fractional-order parameters are determined using the parameter calculation formula, which is as follows:

[0119]

[0120] Among them, I in For the output current, I ref C represents the current value at the same voltage on the target reference curve. α dV / dt is the fractional capacitance value, dV / dt is the voltage change rate, and α is the fractional parameter.

[0121] Furthermore, the aforementioned first determining module 702 is also used for:

[0122] The difference between the output current and the reference current is calculated to obtain the difference result.

[0123] If the difference is greater than the preset value, the target operating condition to which the PSCs belong is determined to be the first operating condition.

[0124] If the difference is less than the preset value, the target operating condition to which the PSCs belong is determined to be the second operating condition.

[0125] Furthermore, the aforementioned adjustment module 704 is specifically used for:

[0126] Based on the target perturbation step size function and fractional-order parameters, determine the target perturbation step size corresponding to PSCs;

[0127] Based on the target disturbance switching frequency function and fractional-order parameters, the target disturbance switching frequency corresponding to PSCs is determined;

[0128] Based on the target disturbance step size and the target disturbance switching frequency, the adaptive adjustment strategy corresponding to PSCs is determined.

[0129] The adaptive fractional-order MPPT control device for perovskite solar cells proposed in this invention acquires the output current and output voltage of perovskite solar cell PSCs; based on the output current and output voltage, it determines the target operating condition and corresponding fractional-order parameters of the PSCs; based on the target operating condition, it determines the target perturbation step size function and target switching perturbation frequency function corresponding to the PSCs; based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters, it determines the adaptive adjustment strategy corresponding to the PSCs, and adjusts the PSCs based on the adaptive adjustment strategy. This invention determines the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, target perturbation switching frequency function, and fractional-order parameters determined through the target operating condition of the PSCs, and adjusts the PSCs based on the adaptive adjustment strategy, thereby improving the energy conversion efficiency of the photovoltaic system, reducing power oscillations and tracking errors caused by hysteresis, and without increasing material costs, providing an effective technical solution for the low-cost, high-performance, and large-scale industrial application of perovskite solar cells.

[0130] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0131] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0132] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. An adaptive fractional-order MPPT control method for perovskite solar cells, characterized in that, The method includes: Obtain the output current and output voltage of the perovskite solar cells (PSCs); Based on the output current and the output voltage, determine the target operating condition and corresponding fractional-order parameters of the PSCs; Based on the target operating conditions, determine the target disturbance step size function and the target disturbance switching frequency function corresponding to the PSCs; Based on the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameter, an adaptive adjustment strategy corresponding to the PSCs is determined, and the PSCs are adjusted based on the adaptive adjustment strategy. The process of determining the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and the output voltage includes: Construct at least one reference curve for PSCs, and obtain the boundary curve based on the at least one reference curve; Multiple sampling points corresponding to the PSCs are obtained, the boundary curve is used to verify the multiple sampling points, and a sampling vector is obtained based on the sampling points that pass the verification. Based on the sampling vector and the at least one reference curve, the target reference curve is determined; The current in the target reference curve corresponding to the output voltage is determined as the reference current; Based on the output current and the reference current, the target operating condition of the PSCs is determined; Based on the target reference curve and the output current, the corresponding fractional-order parameters are determined.

2. The method according to claim 1, characterized in that, Determining the target reference curve based on the sampling vector and the at least one reference curve includes: Calculate the normalized root mean square error between the sampled current and each reference curve in the sampling vector; The reference curve corresponding to the smallest normalized root mean square error is determined as the target reference curve.

3. The method according to claim 1, characterized in that, The step of determining the corresponding fractional-order parameters based on the target reference curve and the output current includes: Based on the output current and the target reference curve, the corresponding fractional-order parameters are determined using a parameter calculation formula, which is: in, I in For output current, I ref The current value at the same voltage on the target reference curve. C α The fractional capacitance value, d V / d t The rate of change of voltage. For fractional-order parameters.

4. The method according to claim 1, characterized in that, The step of determining the target operating condition of the PSCs based on the output current and the reference current includes: The difference between the output current and the reference current is calculated to obtain the difference result. If the difference result is greater than the preset value, then the target operating condition to which the PSCs belong is determined to be the first operating condition; If the difference result is less than the preset value, then the target operating condition to which the PSCs belong is determined to be the second operating condition.

5. The method according to claim 1, characterized in that, The step of determining the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, the target perturbation switching frequency function, and the fractional-order parameters includes: Based on the target perturbation step size function and the fractional-order parameter, the target perturbation step size corresponding to the PSCs is determined; Based on the target disturbance switching frequency function and the fractional-order parameter, the disturbance target switching frequency corresponding to the PSCs is determined; Based on the target perturbation step size and the target perturbation switching frequency, the adaptive adjustment strategy corresponding to the PSCs is determined.

6. An adaptive fractional-order MPPT control device for perovskite solar cells, characterized in that, The device includes: The acquisition module is used to acquire the output current and output voltage of the perovskite solar cells (PSCs). The first determining module is used to determine the target operating condition and corresponding fractional-order parameters of the PSCs based on the output current and the output voltage. The second determining module is used to determine the target disturbance step size function and the target disturbance switching frequency function corresponding to the PSCs based on the target operating conditions. The adjustment module is used to determine the adaptive adjustment strategy corresponding to the PSCs based on the target perturbation step size function, the target perturbation switching frequency function and the fractional-order parameter, and to adjust the PSCs based on the adaptive adjustment strategy. The first determining module is specifically used for: Construct at least one reference curve for PSCs, and obtain the boundary curve based on the at least one reference curve; Multiple sampling points corresponding to the PSCs are obtained, the boundary curve is used to verify the multiple sampling points, and a sampling vector is obtained based on the sampling points that pass the verification. Based on the sampling vector and the at least one reference curve, the target reference curve is determined; The current in the target reference curve corresponding to the output voltage is determined as the reference current; Based on the output current and the reference current, the target operating condition of the PSCs is determined; Based on the target reference curve and the output current, the corresponding fractional-order parameters are determined.

7. An electronic device, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

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