Power tracking method and device, equipment, storage medium and program product

Abstract

The invention discloses a power tracking method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring an irradiation measured value, an environment temperature measured value and component operation information of a to-be-detected photovoltaic component in a current state; determining an operation temperature evaluation value and an attenuation evaluation value of the photovoltaic module to be detected according to the irradiation measured value, the environment temperature measured value and the module operation information; according to a preset mapping relation between the input parameters and the maximum power data, determining corresponding target maximum power data under the irradiation measured value, the operation temperature evaluation value and the attenuation evaluation value; wherein the input parameters comprise an irradiation parameter, an operation temperature parameter and an attenuation parameter; and performing power adjustment on the to-be-detected photovoltaic module according to the target maximum power data so as to realize maximum power tracking of the to-be-detected photovoltaic module. Therefore, not only can the maximum power point tracking of the photovoltaic module with the delay effect be realized, but also the tracking precision and tracking efficiency of the maximum power are improved.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a power tracking method, apparatus, device, storage medium, and program product. Background Technology

[0002] Solar energy, as a clean energy source, is widely used due to its high stability, long service life, and simple maintenance. In photovoltaic power generation systems, to improve the working efficiency of photovoltaic modules, it is necessary to control the output power of the photovoltaic modules to approach the maximum value when the external environment changes, based on the Maximum Power Point Tracking (MPPT) algorithm.

[0003] The MPPT algorithm in related technologies is adapted to crystalline silicon modules, assuming that current and power changes instantaneously with voltage changes. However, it cannot be adapted to photovoltaic modules with hysteresis effects, making it difficult to accurately track the maximum power point of this type of photovoltaic module. Summary of the Invention

[0004] This application proposes a power point tracking method, apparatus, device, storage medium, and program product that not only enables maximum power point tracking for photovoltaic modules with delay effects, but also improves the tracking accuracy and efficiency of maximum power.

[0005] The technical solution of this application is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a power tracking method, the method comprising:

[0007] Obtain the measured values ​​of irradiance, ambient temperature, and module operation information of the photovoltaic module under test in its current state;

[0008] Based on the measured values ​​of irradiation, ambient temperature, and module operation information, the operating temperature assessment value and degradation assessment value of the photovoltaic module under test are determined.

[0009] Based on the preset mapping relationship between input parameters and maximum power data, the target maximum power data corresponding to the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value are determined; where the input parameters include: irradiation parameters, operating temperature parameters, and attenuation parameters;

[0010] The power of the photovoltaic module under test is adjusted based on the target maximum power data in order to achieve maximum power tracking of the photovoltaic module under test.

[0011] Using the aforementioned technical methods, based on the measured irradiance, measured ambient temperature, and module operating information of the photovoltaic module under test (PV module) in its current state, the operating temperature assessment value and degradation assessment value of the PV module under test are determined. Then, based on the preset mapping relationship between irradiance parameters, operating temperature parameters, degradation parameters, and maximum power data, the target maximum power data corresponding to the measured irradiance, operating temperature assessment value, and degradation assessment value are determined. Finally, the power of the PV module under test is adjusted according to the target maximum power data. In this way, the maximum power point of PV modules under test with hysteresis (such as perovskite modules) can be accurately tracked, improving the maximum power tracking accuracy; and it eliminates the need to wait for the hysteresis-affected PV module to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0012] In some embodiments, the method further includes: acquiring multiple sets of test data corresponding to the input parameters of the photovoltaic module under test; determining the maximum power data corresponding to each of the multiple sets of test data when the photovoltaic module under test is in a steady state; and establishing a preset mapping relationship between the input parameters and the maximum power data based on the multiple sets of test data and the maximum power data corresponding to each of the multiple sets of test data.

[0013] By employing the aforementioned technical methods, when the photovoltaic module under test (PVD) is in a steady state, the maximum power data corresponding to each of the multiple sets of test data is determined. Then, based on the multiple sets of test data and their respective maximum power data, a preset mapping relationship between the input parameters and the maximum power data is established. In this way, by acquiring the maximum power data corresponding to each of the multiple sets of test data when the PVD is in a steady state, the target maximum power data of the PVD with a delay effect in the current state can be accurately determined through the preset mapping relationship, thereby improving the maximum power tracking accuracy.

[0014] In some embodiments, the method further includes: determining the minimum power and maximum power of the photovoltaic module under test within a preset time period; determining the power change range of the photovoltaic module under test within the preset time period based on the minimum power and maximum power; and determining that the photovoltaic module under test is in a steady state when the power change range meets a preset range.

[0015] By using the above-mentioned technical means, the power change range is determined based on the maximum and minimum power values ​​of the photovoltaic module under test within a preset time. Then, it is determined whether the power change range meets the preset range to determine whether the photovoltaic module under test is in a steady state. This can improve the accuracy of the preset mapping relationship and thus improve the tracking accuracy of the maximum power.

[0016] In some embodiments, based on multiple sets of test data and the maximum power data corresponding to each set of test data, a preset mapping relationship between input parameters and maximum power data is established, including: determining a training sample set; wherein the training sample set includes multiple sets of test data and the maximum power data corresponding to each set of test data; training a preset model according to the training sample set, and determining the trained preset model as a mapping model when the model training meets a preset stopping condition; wherein the mapping model is used to indicate the preset mapping relationship between input parameters and maximum power data.

[0017] Using the above-mentioned technical means, the preset model is trained based on multiple sets of test data and the maximum power data corresponding to each set of test data. When the model training meets the preset stopping condition, the trained preset model is determined as the mapping model. In this way, the target maximum power data of the photovoltaic module under test with delay effect in any state can be accurately obtained based on the mapping model, thereby improving the tracking accuracy of maximum power.

[0018] In some embodiments, the target maximum power data corresponding to the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value is determined according to the preset mapping relationship between the input parameters and the maximum power data. This includes: inputting the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value into the mapping model, and outputting the target maximum power data through the mapping model.

[0019] By using the above-mentioned technical means, the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value are input into the mapping model to obtain the target maximum power data of the photovoltaic module under test in the current state. This avoids the problem that the photovoltaic module under test with the delay effect needs to wait for a long time to reach a steady state. It can determine the target maximum power data more quickly and accurately, and improve the tracking efficiency and accuracy of maximum power.

[0020] In some embodiments, based on multiple sets of test data and the maximum power data corresponding to each set of test data, a preset mapping relationship between input parameters and maximum power data is established, including: establishing a mapping relationship table according to multiple sets of test data and the maximum power data corresponding to each set of test data; wherein, the mapping relationship table is used to indicate the preset mapping relationship between input parameters and maximum power data.

[0021] By employing the aforementioned technical means, a mapping table is established between irradiation parameters, operating temperature parameters, attenuation parameters, and maximum power data based on multiple sets of test data and their corresponding maximum power data. In this way, the target maximum power data of the photovoltaic module under test with a delay effect can be accurately determined under any state, thereby improving the tracking accuracy of maximum power.

[0022] In some embodiments, determining the target maximum power data corresponding to the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value based on a preset mapping relationship between input parameters and maximum power data includes: matching the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value with the input parameters in the mapping relationship table; determining the target maximum power data based on the mapping relationship table when the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value match the input parameters in the mapping relationship table; and determining the target maximum power data by interpolating the maximum power data in the mapping relationship table based on the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value when the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value do not match the input parameters in the mapping relationship table.

[0023] Using the above-mentioned technical means, if the measured irradiation value, the assessed operating temperature value, and the assessed attenuation value match the input parameters in the mapping table, the target maximum power data can be directly determined through the mapping table. If the measured irradiation value, the assessed operating temperature value, and the assessed attenuation value do not match the input parameters in the mapping table, the target maximum power data can be determined based on the mapping table and interpolation. This avoids the problem that photovoltaic modules under test with delay effects need to wait a long time to reach a steady state, and can determine the target maximum power data more quickly and accurately, thus improving tracking efficiency and accuracy.

[0024] In some embodiments, determining the degradation assessment value of the photovoltaic module under test based on measured irradiance, measured ambient temperature, and module operating information includes: obtaining a preset output power value corresponding to standard test conditions; determining the measured output power value of the photovoltaic module under test based on module operating information; converting the measured output power value based on standard test conditions, measured irradiance, and measured ambient temperature to determine a calculated output power value under standard test conditions; and performing a degradation assessment based on the calculated output power value and the preset output power value to determine the degradation assessment value of the photovoltaic module under test.

[0025] Using the above-mentioned technical means, the measured output power value is converted based on standard test conditions, measured irradiance value, and measured ambient temperature value to obtain the calculated output power value under standard test conditions. Then, the attenuation assessment is performed based on the calculated output power value and the preset output power value to obtain the attenuation assessment value. In this way, the measured output power value is converted into the calculated output power value under standard test conditions, so that the calculated output power value and the preset output power value are used to assess the attenuation of the photovoltaic module under test under the same conditions, thereby accurately obtaining the attenuation assessment value of the photovoltaic module under test.

[0026] Secondly, embodiments of this application provide a power tracking device, which includes an acquisition unit, a determination unit, and an adjustment unit; wherein...

[0027] The acquisition unit is configured to acquire the measured values ​​of irradiance, ambient temperature, and module operation information of the photovoltaic module under test in its current state.

[0028] The determination unit is configured to determine the operating temperature assessment value and degradation assessment value of the photovoltaic module under test based on the measured irradiance value, the measured ambient temperature value, and the module operating information.

[0029] The determining unit is further configured to determine the target maximum power data corresponding to the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value based on a preset mapping relationship between the input parameters and the maximum power data; wherein the input parameters include: irradiation parameters, operating temperature parameters, and attenuation parameters;

[0030] The adjustment unit is configured to adjust the power of the photovoltaic module under test according to the target maximum power data in order to achieve maximum power tracking of the photovoltaic module under test.

[0031] Using the aforementioned technical means, the acquisition unit obtains the measured irradiance, measured ambient temperature, and module operating information of the photovoltaic module under test (PV module) in its current state. Then, based on these measurements, the determination unit determines the operating temperature assessment value and degradation assessment value of the PV module under test. Next, according to the preset mapping relationship between input parameters and maximum power data, the determination unit determines the target maximum power data corresponding to the measured irradiance, operating temperature assessment value, and degradation assessment value. The input parameters include irradiance parameters, operating temperature parameters, and degradation parameters. Finally, the adjustment unit adjusts the power of the PV module under test based on the target maximum power data. This allows for accurate tracking of the maximum power point of PV modules with hysteresis (e.g., perovskite modules), improving maximum power tracking accuracy. Furthermore, it eliminates the need to wait for the hysteresis-affected PV module to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0032] Thirdly, embodiments of this application provide an electronic device, which includes a memory and a processor; wherein,

[0033] Memory is used to store computer programs that can run on a processor;

[0034] A processor for executing the method as described in any one of the first aspects when running a computer program.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by at least one processor, implements the method as described in any one of the first aspects.

[0036] This application proposes a power point tracking (PPT) method, apparatus, device, storage medium, and program product. The method acquires the measured irradiance, ambient temperature, and module operating information of a photovoltaic (PV) module under test (PVMT) in its current state. Based on these parameters, it determines the module's operating temperature and degradation assessment values. Then, according to a preset mapping relationship between irradiance, operating temperature, degradation parameters, and maximum power data, it determines the target maximum power data corresponding to the measured irradiance, operating temperature, and degradation assessment values. Finally, it adjusts the PVMT's power output based on the target maximum power data to achieve PPT. This power PPT method can accurately track the maximum power point of PV modules with hysteresis (e.g., perovskite modules), improving PPT tracking accuracy. Furthermore, it eliminates the need to wait for the hysteresis-affected PV module to reach a steady state before acquiring maximum power data, reducing waiting time and improving PPT tracking efficiency. Attached Figure Description

[0037] Figure 1 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 1 ;

[0038] Figure 2 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 2 ;

[0039] Figure 3 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 3 ;

[0040] Figure 4 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 4 ;

[0041] Figure 5 A detailed flowchart illustrating a power tracking method provided in this application embodiment;

[0042] Figure 6 A schematic diagram of the power variation curve of a photovoltaic module under test provided in an embodiment of this application;

[0043] Figure 7 This is a schematic diagram of the composition structure of a preset model provided in an embodiment of this application;

[0044] Figure 8 This is a schematic diagram of the composition structure of a power tracking device provided in an embodiment of this application;

[0045] Figure 9This is a schematic diagram of the specific hardware structure of an electronic device provided in an embodiment of this application;

[0046] Figure 10 This is a schematic diagram of the composition structure of a photovoltaic power generation system provided in an embodiment of this application. Detailed Implementation

[0047] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit the scope of this application.

[0049] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0050] It should also be noted that the terms "first, second, and third" used in the embodiments of this application are only used to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, and third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0051] Furthermore, the reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0052] The following is a description of the relevant technologies used in this application.

[0053] New energy batteries are being used more and more widely in daily life and industry. For example, new energy vehicles equipped with batteries are already widely used. In addition, batteries are being used more and more in the field of energy storage.

[0054] Currently, new energy batteries are being used more and more widely in daily life and industry. They are not only used in energy storage systems for hydropower, thermal power, wind power, and solar power plants, but also extensively in electric vehicles such as electric bicycles, electric motorcycles, and electric cars, as well as in aerospace and other fields. With the continuous expansion of the application areas of power batteries, the market demand is also constantly increasing.

[0055] In this embodiment, the battery can be a single battery cell. A single battery cell refers to a basic unit capable of converting chemical energy into electrical energy, and can be used to manufacture battery modules or battery packs to supply power to electrical devices. A single battery cell can be a rechargeable battery, which is a battery cell that can be recharged after discharge to reactivate its active materials and continue to be used. A single battery cell can be a lithium-ion battery, sodium-ion battery, sodium-lithium-ion battery, lithium metal battery, sodium metal battery, lithium-sulfur battery, magnesium-ion battery, nickel-metal hydride battery, nickel-cadmium battery, lead-acid battery, etc., and this embodiment is not limited to these types.

[0056] In this embodiment, the battery may also be a single physical module comprising one or more battery cells to provide higher voltage and capacity. When there are multiple battery cells, the multiple battery cells are connected in series, parallel, or mixed via a busbar.

[0057] Solar energy is a renewable and clean energy source, but natural environmental factors such as sunlight and temperature are constantly changing, making it impossible for photovoltaic (PV) modules in a photovoltaic (PV) power generation system to output power stably. To ensure the efficiency of PV modules, it is necessary to use the MPPT algorithm to ensure that the PV modules eventually reach their maximum power value during operation, so that the output power of the PV modules approaches the highest value.

[0058] Photovoltaic modules can be composed of materials with different light-absorbing band gaps. For example, solar cells using perovskite organometal halide semiconductors as light-absorbing materials are called perovskite photovoltaic modules, or simply perovskite modules; solar cells using crystalline silicon as light-absorbing materials are called crystalline silicon photovoltaic modules, or simply crystalline silicon modules. Because crystalline silicon photovoltaic modules have a stable structure, high material purity, and excellent current transport performance, they can more efficiently convert light energy into electrical energy under illumination, reducing the time it takes for charges to move within the material. Therefore, when the voltage changes, the changes in current and power are instantaneous, without hysteresis. However, due to interface defects, ion migration, and interface capacitance, perovskite photovoltaic modules exhibit a different hysteresis effect than crystalline silicon photovoltaic modules. This means that after a voltage change, the current and power in a perovskite photovoltaic module may take several seconds or tens of seconds to reach a new steady state. Moreover, the current-voltage (IV) curves of the same perovskite photovoltaic module after voltage disturbance are different under different scanning speed, scanning direction, scanning step size, waiting time after scanning, induction voltage, light intensity, source-source impedance, and other conditions. Among them, the relationship between the scanning direction and the current-voltage (IV) curves of the perovskite photovoltaic module is the most closely related.

[0059] MPPT algorithms in related technologies, such as Perturb and Observe (P&O) algorithms, optimized P&O algorithms, Incremental Conductance (INC) algorithms, and some power prediction algorithms, are all adapted for crystalline silicon photovoltaic (PV) modules and do not consider the hysteresis effect of perovskite PV modules. This leads to their inability to track the maximum power point (MPP) of perovskite PV modules, or in certain scenarios, they cannot track the MPP of perovskite PV modules, or even if they do track the MPP, the tracking accuracy is significantly different compared to when applied to crystalline silicon PV modules. The basic idea of ​​the P&O algorithm is to first perturb the output voltage or current of the PV module, then observe the changes in the output power of the PV module, and continuously change the perturbation direction of the output voltage or current according to the trend of power change, so that the PV module eventually operates at its maximum power point.

[0060] In related technologies, the Power Point and Current (P&O) algorithm can be applied to crystalline silicon photovoltaic (PV) modules, reaching a steady state relatively quickly after a disturbance. It then collects the power or current of the crystalline silicon PV module in the steady state to determine the direction of the disturbance. However, when the P&O algorithm is applied to perovskite PV modules, the voltage and current do not change immediately after a disturbance, requiring a longer time to reach a new steady state. In laboratory testing environments, where irradiance is constant or nearly constant, the waiting time after each disturbance can be extended indefinitely until the perovskite module reaches a new steady state. However, in real-world environments, factors such as irradiance and temperature vary, causing power to fluctuate. This makes it difficult to wait for a long time, and the collected data is not the steady-state current data of the perovskite module, resulting in a deviation from the true steady-state current data. Consequently, the power determined based on this current data also has errors, leading to repeated disturbances. This makes the P&O algorithm unable to accurately determine the maximum power point of the perovskite PV module, and its tracking accuracy is low. In addition, although some MPPT control methods already exist in related technologies, these methods are only applicable to crystalline silicon modules and do not take into account the hysteresis effect of perovskite modules. Therefore, they cannot achieve MPPT for perovskite modules or may cause large tracking errors in MPPT.

[0061] Based on this, embodiments of this application provide a power point tracking method, apparatus, device, storage medium, and program product. The method acquires the measured irradiance, measured ambient temperature, and module operating information of a photovoltaic (PV) module under test (TPS) in its current state. Based on these parameters, the method determines the operating temperature assessment value and degradation assessment value of the TPS. Then, according to a preset mapping relationship between irradiance parameters, operating temperature parameters, degradation parameters, and maximum power data, the method determines the target maximum power data corresponding to the measured irradiance, operating temperature assessment value, and degradation assessment value. Finally, the method adjusts the power of the TPS based on the target maximum power data. This allows for accurate tracking of the maximum power point of the TPS, even with hysteresis, improving maximum power tracking accuracy. Furthermore, it eliminates the need to wait for the TPS to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0062] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0063] In one embodiment of this application, Figure 1 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 1 .like Figure 1 As shown, the method may include steps S101 to S104, as detailed below:

[0064] S101, obtain the measured irradiance value, measured ambient temperature value, and module operation information of the photovoltaic module under test in the current state.

[0065] In this embodiment of the application, the photovoltaic module under test can be a single photovoltaic module or a photovoltaic string formed by connecting multiple photovoltaic modules in series. Specifically, this embodiment of the application can obtain the measured values ​​of irradiance and ambient temperature of the photovoltaic power generation system where the photovoltaic module or photovoltaic string is located, as the measured values ​​of irradiance and ambient temperature of the photovoltaic module under test in the current state.

[0066] In this embodiment, the component operation information can refer to actual operating data, such as the operating current, operating voltage, and operating time of the photovoltaic module under test (PVMT) in its current state, collected by an inverter or combiner box. Alternatively, it can be described as the IV curve and operating time of the PVMT in its current state obtained through IV scanning, i.e., the actual operating data of the PVMT under test. Thus, the degradation assessment of the PVMT under test can be performed using measured irradiance values, measured ambient temperature values, and component operation information to determine the degradation assessment value of the PVMT under test.

[0067] In this embodiment, the photovoltaic module under test can refer to a photovoltaic module with hysteresis, such as a perovskite module. The actual operating condition of a perovskite module is alternating light and dark conditions; in the light state, the photovoltaic module operates at its maximum power point, meaning it can achieve maximum power output under various conditions, while in the dark state, the perovskite module stops generating electricity. However, due to the hysteresis effect of the perovskite module, MPPT (Multi-Level Testing) of the perovskite module cannot be achieved, or the MPPT tracking error is large. The main reason for the hysteresis effect of the perovskite module is that, due to interface defects, ion migration, interface capacitance, etc., different scanning speeds, scanning directions, scanning step sizes, post-scan waiting times, induction voltages, light intensity, and source-to-surface impedances result in different IV curves for the perovskite module. In other words, the IV curve of the perovskite module is closely related to the scanning conditions, which causes the forward and reverse scanning IV curves to not completely overlap during MPPT due to the hysteresis effect. This reduces the accuracy and reliability of the MPPT results and also affects the performance of the perovskite module.

[0068] In this embodiment, irradiance can refer to either photovoltaic slope irradiance or photovoltaic horizontal irradiance. Correspondingly, the measured irradiance value can be either the measured value of photovoltaic slope irradiance or the measured value of photovoltaic horizontal irradiance. Here, if the actual measured value is the measured value of photovoltaic horizontal irradiance, it can be converted to the measured value of photovoltaic slope irradiance using some algorithms.

[0069] In this embodiment, the measured irradiance value can be obtained by combining the direct irradiance value and the diffuse irradiance value. That is, the measured irradiance value is the total radiation value, which is the sum of the direct radiation value and the diffuse radiation value. Here, the measured direct irradiance value can refer to the radiation value of sunlight directly hitting the photovoltaic module under test, and the diffuse irradiance value can refer to the radiation value of sunlight after being scattered in the atmosphere before reaching the photovoltaic module under test.

[0070] S102. Based on the measured irradiance value, measured ambient temperature value, and component operation information, determine the operating temperature assessment value and degradation assessment value of the photovoltaic module under test.

[0071] In this embodiment, the operating temperature assessment value of the photovoltaic module under test can be obtained by converting measured irradiance values ​​and measured ambient temperature values. For example, the operating temperature assessment value can be obtained by using measured irradiance values, measured ambient temperature values, and measured wind speed values ​​to evaluate the operating temperature of the photovoltaic module under test.

[0072] In this embodiment, the attenuation irradiance value of the photovoltaic module under test can be obtained by converting the measured irradiance value, the measured ambient temperature value, and the module's operating information. For example, the measured output power of the photovoltaic module under test can be determined using the module's operating information. Then, the measured output power value is converted using the measured irradiance temperature value and the measured ambient temperature value to obtain the calculated output power value under standard test conditions. Finally, the attenuation of the photovoltaic module under test is evaluated based on the calculated output power value and a preset output power value to obtain the attenuation evaluation value.

[0073] S103, based on the preset mapping relationship between the input parameters and the maximum power data, determines the target maximum power data corresponding to the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value; wherein, the input parameters include: irradiation parameters, operating temperature parameters, and attenuation parameters.

[0074] In this embodiment, a preset mapping relationship can be established in advance based on multiple sets of test data corresponding to input parameters, namely irradiation parameters, operating temperature parameters, and attenuation parameters, as well as the maximum power data corresponding to each of the multiple sets of test data. The maximum power data can be the operating voltage and operating current corresponding to the maximum power point. Thus, after obtaining the measured irradiation value, operating temperature assessment value, and attenuation assessment value of the photovoltaic module under test, the target maximum power data corresponding to the measured irradiation value, operating temperature assessment value, and attenuation assessment value can be determined by combining the preset mapping relationship; the target maximum power data can be the operating voltage and operating current corresponding to the target maximum power point. Here, the operating voltage can also be referred to as the output voltage, and the operating current can also be referred to as the output current.

[0075] In this embodiment, due to the inherent fragility of perovskite materials, such as poor resistance to high temperatures, light exposure, and hydrolysis, perovskite modules exhibit rapid degradation, and their overall degradation rate remains higher than that of crystalline silicon modules. Therefore, in this embodiment, in addition to considering the influence of irradiation parameters and operating temperature parameters on the maximum power point tracking (MPPT) of the photovoltaic module under test, the influence of degradation parameters on the MPPT is also considered. A preset mapping relationship is then established between irradiation parameters, operating temperature parameters, degradation parameters, and maximum power data, thereby enabling accurate determination of the target maximum power data corresponding to the photovoltaic module under test in its current state. Furthermore, the input parameters are not limited to temperature parameters, irradiation parameters, and degradation parameters; other parameters affecting the maximum power data can also be used. No specific limitations are imposed on the specific parameters among the input parameters.

[0076] S104, adjust the power of the photovoltaic module under test according to the target maximum power data.

[0077] In this embodiment of the application, after obtaining the target maximum power data of the photovoltaic module under test, the power of the photovoltaic module under test can be adjusted according to the target maximum power data to achieve maximum power point tracking of the photovoltaic module under test, thereby enabling the photovoltaic module under test to work at maximum power. This achieves maximum power point tracking of the photovoltaic module under test and improves the tracking accuracy of maximum power.

[0078] In some embodiments, obtaining the operating temperature assessment value of the photovoltaic module under test may include: obtaining the measured wind speed value of the photovoltaic module under test in the current state; and determining the operating temperature assessment value of the photovoltaic module under test in the current state based on the measured irradiance value, the measured ambient temperature value, and the measured wind speed value.

[0079] In this embodiment of the application, since it is difficult to obtain the measured operating temperature of the photovoltaic module under test during actual operation, the measured ambient temperature, measured irradiance and measured wind speed of the photovoltaic module under test in the current state can be used to estimate the operating temperature of the photovoltaic module under test, thereby obtaining the operating temperature evaluation value of the photovoltaic module under test.

[0080] In some embodiments, the operating temperature assessment value of the photovoltaic module under test is calculated as shown in the following formula:

[0081] T m =T a +EPOA×e b+c×WS (1)

[0082] Among them, T m T is the operating temperature assessment value. aThe values ​​represent: ambient temperature (measured), EPOA (measured), WS (measured), and b and c (coefficients). It's important to note that b and c are related to the combination of glass and encapsulating film used in the photovoltaic module under test; different glass and encapsulating film combinations correspond to different b and c values. Here, we can conduct prior experiments to obtain the different b and c values ​​corresponding to different glass and encapsulating film combinations; no limitations are imposed on this.

[0083] Thus, in this embodiment of the application, the operating temperature of the photovoltaic module under test is calculated by converting the measured wind speed, measured irradiance, and measured ambient temperature, thereby obtaining the operating temperature assessment value of the photovoltaic module under test, avoiding the problem of difficulty in directly obtaining the measured operating temperature value of the photovoltaic module under test.

[0084] In some embodiments, the acquisition of the degradation assessment value of the photovoltaic module under test, such as Figure 2 As shown, the method may include steps S201 to S204, as detailed below:

[0085] S201, Obtain the preset output power value corresponding to the standard test conditions.

[0086] In the embodiments of this application, the preset output power value can be obtained by the photovoltaic module working normally under standard test conditions, or it can be preset when the photovoltaic module leaves the factory.

[0087] S202, Based on the component operation information, determine the measured value of the output power of the photovoltaic module under test.

[0088] In this embodiment of the application, the IV curve of the photovoltaic module under test in the current state can be obtained through the component operation information, and then the measured output power of the photovoltaic module under test in the current state can be obtained based on the IV curve.

[0089] S203 converts the measured output power value based on standard test conditions, measured irradiation value, and measured ambient temperature value to determine the calculated output power value under standard test conditions.

[0090] In this embodiment, after obtaining the measured output power of the photovoltaic module under test in the current state, the measured output power is then converted based on the standard test conditions, the measured irradiance value, and the measured ambient temperature value to obtain the calculated output power value under the standard test conditions (STC). This allows the calculated output power value to be evaluated under the same conditions as the preset output power value, thereby accurately obtaining the degradation evaluation value of the photovoltaic module under test.

[0091] S204. Based on the calculated output power value and the preset output power value, the attenuation assessment is performed to determine the attenuation assessment value of the photovoltaic module under test.

[0092] In this embodiment, the calculated output power value and the preset output power value are used to assess the attenuation, thereby obtaining the attenuation assessment value of the photovoltaic module under test. For example, if the calculated output power value is P_act and the preset output power value is P_nom, then the attenuation assessment value = (P_nom - P_act) / P_nom.

[0093] In this embodiment, an IV scan can be performed on the photovoltaic module under test in an illuminated state to obtain a measured IV curve. Then, based on the measured irradiance and ambient temperature values, the measured IV curve is converted to a STC (Simultaneous Temperature Coefficient) curve to obtain a converted IV curve. The converted IV curve is then compared with a pre-stored initial curve under STC, and the deviation between the converted IV curve and the initial curve is used to determine the attenuation, thereby obtaining an attenuation assessment value. The measured IV curve is used to obtain the measured output power value, while the initial curve is used to obtain a preset output power value.

[0094] Thus, in this embodiment of the application, the measured output power value is converted into the calculated output power value under standard test conditions, so that the calculated output power value and the preset output power value are used to evaluate the degradation of the photovoltaic module under test under the same conditions, thereby accurately obtaining the degradation evaluation value of the photovoltaic module under test.

[0095] In some embodiments, obtaining the degradation assessment value of the photovoltaic module under test may further include: determining the operating time of the photovoltaic module under test; and performing a degradation assessment based on the operating time and the rated degradation value to determine the degradation assessment value of the photovoltaic module under test.

[0096] In this embodiment, the current operating time and rated degradation value of the photovoltaic module under test can be obtained first. For example, the operating time can be the number of years 'y', and the rated degradation value can be the calibrated annual degradation value 'deg'. Then, the degradation assessment value of the photovoltaic module under test can be the product of the number of years 'y' and the calibrated annual degradation value 'deg', i.e., degradation assessment value = y × 'deg'. Here, the calibrated annual degradation value can be a fixed value set at the factory when the photovoltaic module under test leaves the factory.

[0097] It should be noted that if the smallest measurement unit is a photovoltaic string, that is, the photovoltaic module under test is a photovoltaic module, and the inverter uses the photovoltaic string as the smallest power point tracking unit, the annual degradation value of different photovoltaic modules in the photovoltaic string is different, which makes the degradation of each module in the photovoltaic string different, resulting in a relatively low accuracy of the degradation assessment value calculated by this method.

[0098] This application provides a power point tracking (PPT) method. The method acquires the measured irradiance, ambient temperature, and module operating information of a photovoltaic (PV) module under test (PVMT) in its current state. Based on these parameters, it determines the module's operating temperature and degradation assessment values. Then, according to a preset mapping relationship between irradiance, operating temperature, degradation parameters, and maximum power data, it determines the target maximum power data corresponding to the measured irradiance, operating temperature, and degradation assessment values. Finally, it adjusts the PVMT's power output based on the target maximum power data. This method accurately tracks the maximum power point of PV modules with hysteresis (e.g., perovskite modules), improving PPT tracking accuracy. Furthermore, it eliminates the need to wait for the hysteresis-affected PV module to reach a steady state before collecting maximum power data, reducing waiting time and improving PPT tracking efficiency.

[0099] In another embodiment of this application, Figure 3 A flowchart illustrating a power point tracking method provided in this application embodiment. Figure 3 .like Figure 3 As shown, the method may include steps S301 to S303, as detailed below:

[0100] S301, acquire multiple sets of test data corresponding to the input parameters of the photovoltaic module under test.

[0101] In this embodiment, the photovoltaic module under test can be a perovskite module. Perovskite modules can be tested in a laboratory environment. Since different perovskite module systems exhibit different performance characteristics, it is necessary to test each system separately. Generally, perovskite modules are connected to inverters or combiner boxes in photovoltaic power generation systems as photovoltaic strings; therefore, perovskite modules can be tested as photovoltaic strings.

[0102] In this embodiment, the maximum power data corresponding to at least one test value for each of the irradiation parameter, operating temperature parameter, and attenuation parameter can be tested, that is, the operating voltage and operating current corresponding to the maximum power point can be obtained, and then a test data table can be drawn. The data in a single row of the test data table can include data information such as irradiation, operating temperature, attenuation, operating voltage, and operating current.

[0103] For example, taking a set of test data as an example, when the operating temperature test value of the photovoltaic module under test is 45 degrees Celsius (°C), the irradiance test value is 800 watts per square meter (W / ㎡), and the degradation test value is 0.2%, the photovoltaic module under test is tested to obtain the operating current and operating voltage corresponding to the maximum power point.

[0104] In this embodiment of the application, to determine multiple sets of test data for the photovoltaic module under test, the attenuation test value of the photovoltaic module under test can be fixed first, the irradiation test range and operating temperature test range of the photovoltaic module under test can be obtained, the irradiation test value and the operating temperature test value can be determined according to the irradiation test range and the operating temperature test range, and the electrical parameters corresponding to the maximum power point of the photovoltaic module under test under different combinations of irradiation test value and operating temperature test value, namely the operating voltage and operating current, can be obtained; then the operating voltage and operating current corresponding to the maximum power point under different attenuation test values ​​can be tested.

[0105] In this embodiment, the upper and lower limits of the irradiation test range and operating temperature test range used in the testing process can be determined based on the equipment measurement range, the performance of the photovoltaic module under test, and the application scenario. When performing combined tests on irradiation test values ​​and operating temperature test values, the irradiation test range and operating temperature test range can be divided into intervals to obtain multiple irradiation test values ​​and operating temperature test values. The intervals used when dividing the irradiation test range and operating temperature test range can be determined based on the photovoltaic module system under test, system design, test quantity, and accuracy requirements; no limitations are imposed here.

[0106] For example, the irradiation test range [100, 1600] can be divided into irradiation test values ​​at intervals of 20, i.e., [100, 120, 140, ..., 1000, 1020, ..., 1600]; the operating temperature test range can be [10, 80], which can be divided into operating temperature test values ​​at intervals of 2, i.e., [10, 12, 14, 16, ..., 70, 72, ..., 80]. It should be noted that, in this embodiment, it is necessary to test under the same attenuation test value, under the same irradiation test value but different operating temperature test values, and under the same operating temperature test value but different irradiation test values. That is, if there are m irradiation test values ​​and n operating temperature test values, a total of (m×n) tests are required.

[0107] It is important to note that the smaller the interval used when dividing the irradiation test range and the operating temperature test range, the larger the number of tests required. The interval used for division can be determined based on the actual operating conditions. Data not tested between two intervals can be calculated later using interpolation or other methods. Furthermore, if the photovoltaic module under test is a perovskite module, since the temperature coefficient of some perovskite modules can be as low as -0.001% / ℃, indicating that their efficiency is very little affected by temperature changes, this value range is relatively low compared to other types of modules (such as crystalline silicon modules). Therefore, when dividing the operating temperature test range for perovskite modules, the interval can be appropriately increased to reduce the number of tests required.

[0108] In this embodiment, the testing of the maximum power data of the photovoltaic module under different degradation test values ​​can be achieved by simulating the performance after degradation corresponding to different service years through accelerated aging experiments. Then, cross-experiments are conducted on different irradiation test values ​​and operating temperature test values ​​to obtain the maximum power data corresponding to different operating temperature test values ​​and irradiation test values ​​for the corresponding service years. If there are a total of k degradation test values, and m irradiation test values ​​and n operating temperature test values, then a total of (k×m×n) tests are required.

[0109] In the embodiments of this application, for determining multiple sets of test data for the photovoltaic module under test, the attenuation test value of the photovoltaic module under test can be fixed, and the irradiation test value and operating temperature test value can be determined by random method. The operating voltage and operating current corresponding to the maximum power point under different combinations of irradiation test value and operating temperature test value can be obtained; and the operating voltage and operating current corresponding to the maximum power point under different attenuation test values ​​can be tested.

[0110] It is understandable that by obtaining multiple sets of test data through random methods and adjusting the operating temperature and irradiation parameters in the form of random variables, the amount of testing can be reduced and the testing cycle can be shortened.

[0111] S302, when the photovoltaic module under test is in a steady state, determine the maximum power data corresponding to each of the photovoltaic module under test under multiple sets of test data.

[0112] In the embodiments of this application, the maximum power data of the perovskite module can be measured using MPPT testing in an IV test instrument or MPPT testing in a steady-state illumination chamber. There are no restrictions on the specific MPPT tracking method, but it needs to be optimized according to the hysteresis effect of the perovskite module, that is, it is necessary to measure the maximum power data of the perovskite module under steady state.

[0113] For example, taking the perturbation observation method, due to the hysteresis effect of perovskite modules, a certain amount of time is required for the modules to reach a new steady state after each perturbation. During laboratory testing, it is ensured that the temperature, irradiation, and degradation parameters remain constant during each perturbation and the testing process. After the perovskite module reaches a new steady state, the operating voltage and current corresponding to the maximum power point are recorded, thus obtaining the maximum power data of the photovoltaic module under test in steady state.

[0114] S303 establishes a preset mapping relationship between input parameters and maximum power data based on multiple sets of test data and the maximum power data corresponding to each set of test data.

[0115] In this embodiment, after obtaining multiple sets of test data and their corresponding maximum power data, a series of discontinuous irradiation parameters, operating temperature parameters, and attenuation parameters, along with their corresponding maximum power data, can be obtained. Then, using the irradiation parameters, operating temperature parameters, and attenuation parameters as input parameters, and the maximum power data under any operating condition as output data, a preset mapping relationship is established. Here, obtaining the preset mapping relationship through the input parameters and output data can be confirmed using various methods, such as the listing method or deep learning models, and is not specifically limited to any particular method.

[0116] In some embodiments, determining whether the photovoltaic module under test is in a steady state may include: determining the minimum power and maximum power of the photovoltaic module under test within a preset time period; determining the power change range of the photovoltaic module under test within the preset time period based on the minimum power and maximum power; and determining that the photovoltaic module under test is in a steady state when the power change range meets a preset range.

[0117] In this embodiment of the application, the power change range of the photovoltaic module under test can be determined by the maximum and minimum power values ​​of the photovoltaic module under test within a preset time. Then, it is determined whether the power change range meets the preset range, thereby determining whether the photovoltaic module under test is in a steady state.

[0118] In this embodiment, if the power change amplitude meets the preset range, it indicates that the photovoltaic module under test is in a steady state; if the power change amplitude does not meet the preset range, it indicates that the photovoltaic module under test is not in a steady state. Furthermore, the preset time and preset range can be fixed, or they can be determined based on the performance of the photovoltaic module under test. Here, no limitation is made on the determination of the preset time and preset range.

[0119] For example, within a time period t, the range of power variation is used as the criterion for determining whether the photovoltaic module under test is in a steady state. For example, |p max -p min |≤σ p , where p max and p min σ represents the maximum and minimum power values ​​within time period t. p This is a preset threshold, and the preset range can be [-σ]. p ,σ p ].

[0120] Thus, in this embodiment of the application, the power change range to be measured is determined based on the maximum and minimum power values ​​of the photovoltaic module under test within a preset time. Then, it is determined whether the power change range meets the preset range to determine whether the photovoltaic module under test is in a steady state. This can improve the accuracy of the preset mapping relationship and thus improve the tracking accuracy of the maximum power.

[0121] In some embodiments, determining that the photovoltaic module under test is in a steady state may further include: determining the power change rate of the photovoltaic module under test within a preset time period; and determining that the photovoltaic module under test is in a steady state when the power change rate of the photovoltaic module under test meets the change range.

[0122] In this embodiment, if the power change rate meets the specified range, it indicates that the photovoltaic module under test is in a steady state; if the power change rate does not meet the specified range, it indicates that the photovoltaic module under test is not in a steady state. Furthermore, the range can be fixed or determined based on the performance of the photovoltaic module under test; therefore, no limitation is placed on the range here.

[0123] Thus, in this embodiment of the application, by determining the power change rate of the photovoltaic module under test within a preset time, and then judging whether the power change rate meets the change range, it is determined whether the photovoltaic module under test is in a steady state, thereby improving the accuracy of the preset mapping relationship and thus improving the tracking accuracy of the maximum power.

[0124] In some embodiments, the determination of the preset mapping relationship, such as Figure 4 The method may include steps S401 to S402, as follows:

[0125] S401, Determine the training sample set; wherein, the training sample set includes multiple sets of test data and the maximum power data corresponding to each set of test data.

[0126] In this embodiment, multiple sets of test data of the photovoltaic module under test and the maximum power data corresponding to the multiple sets of test data are divided into a training set and a validation set, and a preset model is trained and tested based on the training set and validation set.

[0127] In this embodiment, machine learning can be used to obtain a preset mapping relationship. That is, it is not necessary to explicitly define the correspondence between input parameters (i.e., irradiation parameters, operating temperature parameters, and decay parameters) and maximum power data. By using machine learning to input and learn from a large amount of data, a relatively accurate preset mapping relationship can be obtained. In some embodiments, the preset model is a multi-layer perceptron (MLP).

[0128] For example, using MLP, a large amount of regular or irregular test data is used as input data. There is no need to specify a complete conversion method. Through the input of a large amount of data and machine learning, the output data rules (i.e., the preset mapping relationship) are obtained.

[0129] In this embodiment, the dataset of the preset model can be a 5D dataset, specifically including operating temperature parameters, irradiation parameters, attenuation parameters, and the operating voltage and current corresponding to the maximum power point. The inputs to the preset model are: operating temperature parameters, irradiation parameters, and attenuation parameters; the output of the preset model is the operating voltage and current corresponding to the maximum power point.

[0130] In this embodiment, the preset model may include an input layer, a hidden layer, and an output layer. The input layer uses three neurons (corresponding to the three features of the three-dimensional data, namely the operating temperature parameter, the irradiation parameter, and the attenuation parameter); the output layer uses two neurons (corresponding to the operating voltage and operating current at the maximum power point); the hidden layer can be a single layer or multiple layers, which is not specifically limited here.

[0131] S402, train the preset model according to the training sample set, and when the model training meets the preset stopping condition, determine the trained preset model as the mapping model; wherein, the mapping model is used to indicate the preset mapping relationship between the input parameters and the maximum power data.

[0132] In this embodiment, the preset stopping condition can be the maximum number of iterations or the convergence of the loss function; no specific limitation is made here. For example, if the number of iterations during model training exceeds the maximum number of iterations, model training is stopped, and the trained preset model is used as the mapping model; if the loss function during model training converges, model training is stopped, and the trained preset model is used as the mapping model.

[0133] In this embodiment of the application, after obtaining the trained preset model, the trained preset model can be determined as a mapping model. Here, the mapping model is used to indicate the preset mapping relationship between the input parameters (i.e., irradiation parameters, operating temperature parameters, and decay parameters) and the maximum power data.

[0134] In one specific embodiment, after obtaining the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value, the method may include: inputting the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value into a mapping model, and outputting the target maximum power data through the mapping model.

[0135] In this embodiment, the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value are input into the mapping model to obtain the target maximum power data of the photovoltaic module under test in the current state. This avoids the problem that the photovoltaic module under test with the delay effect needs to wait for a long time to reach a steady state. It can determine the target maximum power data more quickly and accurately, and improve the tracking efficiency and accuracy of the maximum power.

[0136] Thus, in this embodiment of the application, a preset model is trained based on multiple sets of test data and the maximum power data corresponding to each set of test data. When the model training meets the preset stopping condition, the trained preset model is determined as a mapping model. In this way, the target maximum power data of the photovoltaic module under test with delay effect under any operating condition can be accurately obtained based on the mapping model, thereby improving the tracking accuracy of the maximum power.

[0137] In some embodiments, determining the preset mapping relationship may further include: establishing a preset mapping relationship between the input parameter and the maximum power data based on multiple sets of test data and the maximum power data corresponding to each set of test data, including: establishing a mapping relationship table according to multiple sets of test data and the maximum power data corresponding to each set of test data; wherein the mapping relationship table is used to indicate the preset mapping relationship between the input parameter and the maximum power data.

[0138] In this embodiment, a mapping table between irradiation parameters, operating temperature parameters, attenuation parameters, and maximum power data is established based on multiple sets of test data and the maximum power data corresponding to each set of test data. In this way, the maximum power data of the photovoltaic module under test with delay effect can be accurately obtained under any operating condition according to the mapping table, thereby improving the tracking accuracy of maximum power.

[0139] In one specific embodiment, after obtaining the measured irradiance value, the estimated operating temperature value, and the estimated attenuation value, the method may include: matching the measured irradiance value, the estimated operating temperature value, and the estimated attenuation value with the input parameters in the mapping table; when the measured irradiance value, the estimated operating temperature value, and the estimated attenuation value match the input parameters in the mapping table, determining the target maximum power data based on the mapping table; when the measured irradiance value, the estimated operating temperature value, and the estimated attenuation value do not match the input parameters in the mapping table, performing interpolation calculations on the maximum power data in the mapping table based on the measured irradiance value, the estimated operating temperature value, and the estimated attenuation value to determine the target maximum power data.

[0140] Thus, in this embodiment, if the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value match the input parameters in the mapping table, the target maximum power data is directly determined through the mapping table; if the measured irradiance value, the assessed operating temperature value, and the assessed attenuation value do not match the input parameters in the mapping table, the target maximum power data is determined based on the mapping table and interpolation. This avoids the problem that photovoltaic modules under test with delay effects need to wait a long time to reach a steady state, and can determine the target maximum power data more quickly and accurately, improving tracking efficiency and accuracy.

[0141] This application provides a power point tracking (PPT) method. When the photovoltaic (PV) module under test (PPT) is in a steady state, the method determines the maximum power data corresponding to each of multiple sets of test data. Based on these multiple sets of test data and their respective maximum power data, a preset mapping relationship is established between input parameters and the maximum power data. Thus, when the PPT is in a steady state, by acquiring the maximum power data corresponding to each of the multiple sets of test data, the target maximum power data of the PPT with a delay effect in the current state can be accurately determined through the preset mapping relationship, thereby improving the maximum power tracking accuracy.

[0142] In another embodiment of this application, the power tracking method based on the foregoing embodiments, Figure 5 This is a detailed flowchart illustrating a power point tracking method provided in an embodiment of this application. Figure 5 As shown, the detailed process may include steps S501 to S505, as follows:

[0143] S501 tests the maximum power data of the photovoltaic module under test under different irradiation test values, different operating temperature test values, and different degradation test values.

[0144] In the embodiments of this application, the photovoltaic module under test can be a perovskite module, and the irradiation parameters, operating temperature parameters, and attenuation parameters corresponding to multiple operating conditions can be discrete values, and the maximum power data of the corresponding multiple operating conditions can be obtained.

[0145] S502 establishes a preset mapping relationship between irradiation parameters, operating temperature parameters, attenuation parameters, and maximum power data of the photovoltaic module under test by acquiring the maximum power data of the photovoltaic module under different irradiation test values, operating temperature test values, and attenuation test values.

[0146] In the embodiments of this application, the preset mapping relationship can be called the correspondence relationship, which can be obtained by interpolation methods or other algorithms. Then, the maximum power data under any operating condition can be obtained through the correspondence relationship.

[0147] S503, obtain the measured values ​​of irradiance and ambient temperature of the photovoltaic module under test in the current state; based on the measured values ​​of irradiance and ambient temperature, obtain the evaluation values ​​of operating temperature and degradation of the photovoltaic module under test.

[0148] In this embodiment of the application, the photovoltaic module under test can be connected to an inverter, and the inverter can be connected to an environmental monitoring instrument for communication, thereby enabling the acquisition of the measured irradiance value and the measured ambient temperature value of the photovoltaic module under test in the current state.

[0149] S504 determines the target maximum power data of the photovoltaic module under test through the MPPT control module in the inverter.

[0150] In this embodiment of the application, the inverter may include an MPPT control module, which is used to acquire target maximum power data of the photovoltaic module under test and adjust the photovoltaic module under test according to the target maximum power data so that the photovoltaic module under test operates at the maximum power point.

[0151] The S505 collects real-time measured values ​​of irradiance and ambient temperature, determines the target maximum power data corresponding to the measured values ​​of irradiance and ambient temperature, and adjusts the maximum power of the photovoltaic module under test.

[0152] In this embodiment, by acquiring real-time measured values ​​of irradiance and ambient temperature, and determining the operating temperature assessment value and degradation assessment value of the photovoltaic module under test based on the measured values ​​of irradiance and ambient temperature, the target maximum power data corresponding to the measured values ​​of irradiance, operating temperature assessment value, and degradation assessment value under the current state can be determined through a preset mapping relationship. Then, the maximum power point of the photovoltaic module under test is adjusted so that the photovoltaic module under test operates at the maximum power point, thereby improving the efficiency of the photovoltaic power generation system.

[0153] In the embodiments of this application, the MPPT method commonly used in inverters is applied to crystalline silicon modules, without considering the hysteresis effect of perovskite modules. As a result, the maximum power point of perovskite modules cannot be tracked, or the maximum power point of perovskite modules cannot be tracked in certain scenarios, resulting in a significant difference in tracking accuracy between perovskite modules and crystalline silicon modules.

[0154] For example, the commonly used MPPT method, taking the P&O algorithm as an example, has the following basic idea: first, the output voltage or output current of the photovoltaic cell is perturbed; then, the change in the output power of the photovoltaic cell is observed; and the direction of the perturbed output voltage or output current is continuously changed according to the trend of power change, so that the photovoltaic cell eventually operates at its maximum power point. However, when this method is applied to perovskite modules, it cannot track the maximum power point, or the tracking accuracy of MPPT is low. The main reason is that after the perturbation of the perovskite module occurs, the output voltage of the perovskite module cannot change immediately, and the time required for the output voltage of different perovskite module systems to reach steady state is different, that is, the time required for different perovskite module systems to reach the maximum power point is different, thus resulting in low tracking accuracy of MPPT.

[0155] It is understandable that if the conventional MPPT method (collecting component power or current in a short time to determine the direction of disturbance) is used, the maximum power data collected for perovskite modules is not steady-state data, leading to a deviation between the collected data and the actual data. This results in repeated left and right disturbances, making it impossible to find the maximum power point of the perovskite module. Furthermore, if the perovskite module reaches a new stable state after each disturbance, the waiting time may be several seconds or tens of seconds. Therefore, in this embodiment, in an ideal state test system (i.e., constant or approximately constant irradiation parameters), the waiting time after each disturbance can be infinitely extended until the perovskite module reaches a new steady state to acquire the collected data. However, in a real environment, irradiation changes constantly, causing the power of the perovskite module to change accordingly. It is difficult to wait such a long time, making it impossible for the conventional P&O algorithm to accurately track the maximum power point of the perovskite module. Therefore, in this embodiment, by establishing a preset mapping relationship between irradiation parameters, operating temperature parameters, attenuation parameters, and maximum power data, the maximum power data corresponding to the perovskite module in the real environment, i.e., the output voltage and output current corresponding to the maximum power point, can be obtained.

[0156] In the embodiments of this application, Figure 6 This is a schematic diagram of the power variation curve of a photovoltaic module under test, provided as an embodiment of this application. Figure 6 As shown, the horizontal axis represents time in seconds (s), and the vertical axis represents photovoltaic cell efficiency (power conversion efficiency, PCE) in percentage. The abrupt peak in PCE corresponds to the moment the perturbation is applied, and the subsequent sloping curve indicates the time required for the tested photovoltaic module to reach a stable state after the perturbation. For example... Figure 6 The peak appears the instant the perturbation is applied at 100s, and it reaches a steady state at around 130s.

[0157] In this embodiment of the application, the photovoltaic module under test is a perovskite module, combined with Figure 5 The power tracking method provided in this application specifically includes the following steps:

[0158] Step 1: Conduct laboratory tests on the maximum power point of the perovskite module under different operating conditions.

[0159] In this embodiment, perovskite modules are tested in a laboratory environment, i.e., an ideal testing environment. Since perovskite modules of different systems exhibit different performance characteristics, they must be tested separately. Furthermore, perovskite modules in photovoltaic power generation systems are often connected to inverters or combiner boxes in the form of photovoltaic strings; therefore, perovskite modules can be tested in the form of photovoltaic strings. Additionally, for the same type (system) of perovskite modules, their electrical parameters are determined by the conventional photovoltaic system voltage level (e.g., 1000V or 1500V) and the number of photovoltaic modules connected in a single string. Since each photovoltaic module has a certain voltage and current output, the number of photovoltaic modules connected in series affects the voltage and current of the entire photovoltaic string.

[0160] In this embodiment of the application, the power generation performance of the perovskite module is tested under different irradiation test values, different operating temperature test values, and different attenuation test values. That is, the operating voltage (Vmppt) and operating current (Imppt) corresponding to the maximum power point of the perovskite module are tested under different conditions. Then, an original test data table can be established. Each row of data contains the following information: irradiation, operating temperature, attenuation, and operating voltage and operating current corresponding to the maximum power point.

[0161] In the embodiments of this application, the measurement of the maximum power point electrical parameters (i.e., the output voltage and output current corresponding to the maximum power point) of the perovskite module can be performed using MPPT testing in an IV test instrument or MPPT testing in a steady-state illumination box. The specific MPPT tracking method is not limited, but it needs to be optimized according to the hysteresis effect of the perovskite module, that is, the maximum power point needs to be measured when the perovskite is in a steady state.

[0162] For example, taking P&O as an example, since perovskite modules have a hysteresis effect, a certain amount of time is required to reach a new steady state after each disturbance. Therefore, during laboratory environment testing, it is necessary to ensure that the operating temperature test value and irradiation test value remain unchanged during each disturbance and test. After reaching a new steady state, the Vmppt and Imppt corresponding to the maximum power point are recorded.

[0163] In the embodiments of this application, the criteria for determining whether a perovskite module is in a steady state are not unique. For example, taking interpolation as an example: within a time period t, the range of power variation is used as the criterion for determining steady state. If |p max -p min |≤σ p , where p max and p min σ represents the maximum and minimum power values ​​within time period t. p This is a preset threshold. Other methods can also be used as the basis for judging steady state; no specific restrictions are imposed here.

[0164] In this embodiment, an exhaustive method can be used to test the maximum power point electrical parameters of the perovskite module under multiple test values ​​corresponding to the irradiation parameters and operating temperature parameters, respectively. Here, the irradiation test range can be [100, 120, 140, ..., 1000, 1020, ..., 1600], and the unit of irradiation value is W / m³. 2 The upper and lower limits of the irradiation test range can be determined based on factors such as equipment measurement range, component performance, and application scenario. The operating temperature test range can be [10, 12, 14, 16, ..., 70, 72, ..., 80], with temperature values ​​in °C. The upper and lower limits of the operating temperature test range can also be determined based on factors such as equipment measurement range, component performance, and application scenario. The irradiation test range and operating temperature test range have already been divided using their respective intervals, which are only used as examples here. In this embodiment, the intervals used to divide the irradiation test range and operating temperature test range can be determined based on the perovskite component system, system design, test quantity, accuracy requirements, etc., and are not specifically limited here, as long as suitable test data for the perovskite component can be obtained. For example, taking a perovskite component as an example, the temperature coefficient of a perovskite component is extremely low, so the interval for dividing the operating temperature test range can be appropriately increased to reduce the test quantity.

[0165] In this embodiment, under the same attenuation test value of the perovskite module, maximum power point (MPP) tests need to be performed under the same irradiation test value and different operating temperature test values, as well as under the same operating temperature test value and different irradiation test values. That is, if there are m irradiation test values ​​and n operating temperature test values, a total of (m×n) tests are required. Here, the smaller the test data interval, the larger the number of tests. If the test data interval is smaller, the actual operating condition MPP can be calculated later through interpolation or other methods.

[0166] In addition, it is necessary to measure the change in the maximum power point of the perovskite module under different test values ​​of the degradation parameters. This can be achieved through accelerated aging tests to simulate the performance after degradation at different service lifespans. Then, cross-testing can be performed on different irradiation test values ​​and operating temperature test values ​​to obtain the maximum power data corresponding to the operating temperature test value and irradiation test value at the corresponding service life. Alternatively, the degradation test value can be estimated using a prediction algorithm. If there are a total of k degradation test values, with m irradiation test values ​​and n operating temperature test values, then a total of (k×m×n) tests are required.

[0167] In this embodiment, the maximum power point electrical parameters of perovskite modules under different combinations of irradiation test values ​​and operating temperature test values ​​can also be tested using a random method. Since the exhaustive method involves a large number of tests and a long testing cycle, a random method can be used to reduce the number of tests and thus the testing cycle. Here, the testing conditions for the random method are the same as those for the exhaustive method, but the operating temperature test value and irradiation test value are used as random variables for random adjustment. Furthermore, the testing of the attenuation parameter remains consistent with the exhaustive method.

[0168] In this embodiment, after acquiring all test data, a series of discontinuous irradiation test values, operating temperature test values, and attenuation test values, as well as the corresponding maximum power data, can be obtained. The irradiation test values, operating temperature test values, attenuation test values, and the corresponding maximum power data are used as input data, and the maximum power data under any operating condition is used as output data. The correspondence between the input data and the output data (i.e., a preset mapping relationship) is obtained. This correspondence can be confirmed through various methods and is not specifically limited.

[0169] Step 2: Obtain the maximum power data of the perovskite module under actual operating conditions.

[0170] In this embodiment, an exhaustive method can be used to obtain different irradiation test values, different operating temperature test values, and different attenuation test values, as well as the corresponding maximum power data, thereby obtaining a preset mapping relationship between the input parameters, attenuation parameters, and maximum power data. Here, the maximum power data corresponding to the untested operating conditions can be obtained using linear interpolation. For example, the maximum power data under the same temperature test value and attenuation test value but different irradiation test values ​​are [Vmppt_1, Imppt_1], [Vmppt_2, Imppt_2], [Vmppt_3, Imppt_3], ... Because the irradiation test values ​​are discontinuous, the maximum power data [Vmppt_int, Imppt_int] corresponding to the discontinuous irradiation test values ​​is obtained by linear interpolation. Similarly, the interpolated data of different operating temperature test values ​​under the same irradiation test value and attenuation test value, as well as the interpolated data of different attenuation test values ​​under the same temperature test value and irradiation test value, are obtained using the same method.

[0171] Table 1 in this application embodiment is a test data table provided by this application embodiment. As shown in Table 1, the test data is obtained by testing different irradiance test values ​​under the same operating temperature test value and attenuation test value; wherein, Temp represents the operating temperature of the photovoltaic module under test, in °C, Deg represents the attenuation of the photovoltaic module under test, and Radiation represents the irradiance of the photovoltaic module under test, in W / m². 2Vmppt represents the output voltage at the maximum power point, in volts (V), and Imppt represents the output current at the maximum power point, in amperes (A). Taking one row of data from Table 1 as an example, the test photovoltaic module operates at a temperature of 45℃, a degradation rate of 0.20%, and an irradiance of 800W / m². 2 The output voltage is u1 and the output current is i1.

[0172] Table 1

[0173] Temp (°C) Deg(%) <![CDATA[Radiation(W / m 2 )]]> Vmppt(V) Imppt(A) … … … … … 45 0.20％ 800 u1 i1 45 0.20％ 820 u2 i2 45 0.20％ 840 u3 i3 45 0.20％ 860 u4 i4 45 0.20％ 880 u5 i5 45 0.20％ 900 u6 i6 45 0.20％ 920 u7 i7 45 0.20％ 940 u8 i8 45 0.20％ 960 u9 i9 45 0.20％ 980 u10 i10 45 0.20％ 1000 u11 i11 45 0.20％ 1020 u12 i12 45 0.20％ 1040 u13 i13 45 0.20％ 1400 u14 i14 … … … … …

[0174] In this embodiment of the application, if the attenuation assessment value is 0.2%, the operating temperature assessment value is 45°C, and the measured irradiation value is 930 W / m², then... 2 After matching the attenuation assessment value, operating temperature assessment value, and measured irradiation value with Table 1, the output voltage Vmppt_int and output current Imppt_int corresponding to the maximum power point of the perovskite module under this operating condition can be obtained by linear interpolation. The calculation formula is shown below:

[0175]

[0176] In addition, in this embodiment of the application, the maximum power data corresponding to the actual operating condition can be determined by machine learning. That is, it is not necessary to explicitly define the correspondence between the input operating condition and the output data, i.e. the maximum power point. By learning through the input of a large amount of data, a more accurate correspondence can be obtained. For example, the machine learning method of neural network can be used to take a large amount of regular or irregular test data as input data. Through the input of a large amount of data and machine learning, the output data rules (i.e., the preset mapping relationship) can be obtained.

[0177] In the embodiments of this application, Figure 7 This is a schematic diagram illustrating the composition of a preset model provided in an embodiment of this application. The preset model 70 can be an MLP, such as... Figure 7 As shown, the MLP includes an input layer 701, a hidden layer 702, and an output layer 703. The input layer 701 represents irradiance, operating temperature, and attenuation, while the output layer 703 represents the output voltage and output current corresponding to the maximum power point.

[0178] In this embodiment, the preset model 70 is initialized, specifically by initializing the weights and biases of each layer of the preset model 70 (except for the input layer 701). The weights and biases can be randomly initialized. Forward propagation of the preset model 70 is performed, specifically by directly passing the input data to the next layer (hidden layer 702) through the input layer 701. For each hidden layer 702, each neuron receives the weighted input from all neurons in the previous layer (i.e., the output of the previous layer's neurons multiplied by the corresponding weight plus the bias). The weighted input is then processed through an activation function (e.g., sigmoid) to obtain the output of the current neuron, which is then used as the input to the next layer's neuron (i.e., the output layer 703). The output layer 703 then receives the weighted input from the previous layer and... The activation function yields the final output. Then, the output of the preset model 70 and the true labels (i.e., the maximum power data corresponding to the input data) are compared. Backpropagation is performed on the preset model 70, specifically by calculating the gradient of the loss function with respect to the network parameters using the chain rule and gradient descent. The calculated gradient is then used to update the weights and biases of the preset model 70 to minimize the loss function. Iterative optimization of the preset model 70 is performed, specifically by repeating the forward propagation, loss calculation, and backpropagation process until the preset stopping conditions are met (e.g., reaching the maximum number of iterations, loss function convergence, etc.). Finally, the trained preset model 70 is obtained, which can be used to predict new input data. At this point, only forward propagation is needed, and backpropagation and parameter updates are not required.

[0179] In this embodiment, a preset mapping relationship allows for the acquisition of maximum power data corresponding to the measured irradiance, assessed operating temperature, and assessed attenuation values ​​under any operating condition (current state). This preset mapping relationship can be used as the basis for MPPT (Maximum Power Point Tracking). Specifically, by using the tested maximum power data and a conversion method, the maximum power data under the measured meteorological conditions (i.e., actual operating conditions) is calculated. The inverter is then used to adjust the perovskite module to operate at its maximum power point. Furthermore, as the measured meteorological conditions change, the position of the perovskite module's maximum power point can be dynamically adjusted to ensure the perovskite module's output power. Additionally, this power point tracking method can be configured into the MPPT control module. This means that the MPPT control module can ensure the perovskite module operates at its maximum power point. Alternatively, existing inverters or MPPT equipment can be imported to achieve MPPT for the perovskite module, providing MPPT tracking accuracy.

[0180] Step 3: Obtain information about the perovskite components during actual operation.

[0181] In this embodiment of the application, since the inverter usually cannot directly collect the operating temperature of the perovskite module, the inverter equipment is connected to the environmental monitoring equipment to collect data such as the measured ambient temperature, measured irradiance, and measured wind speed of the perovskite module in real time. Then, the operating temperature evaluation value is obtained by using the measured ambient temperature, measured irradiance, and measured wind speed. The calculation formula is as shown in the above formula (1).

[0182] In this embodiment, the measured attenuation value of the perovskite module can be obtained in two ways: Method 1, calculated by the current number of years y of the perovskite module and the calibrated annual attenuation value deg. For example, the attenuation in year y is y*deg. However, since the inverter uses the photovoltaic string as the minimum power tracking unit, the attenuation of each photovoltaic module in the photovoltaic string varies due to the different annual attenuation performance of different photovoltaic modules. Therefore, the accuracy of this calculation method is relatively low. Method 2, the inverter performs IV scanning on the string. Specifically, the light state performs IV scanning on the perovskite module. Based on the measured IV curve, the measured irradiance value, and the measured ambient temperature value, the measured IV curve is converted to STC conditions and compared with the initial curve under the pre-stored STC conditions. The curve deviation is used to judge the attenuation. For example, if the output power under the pre-stored STC conditions is P_nom and the output power converted from the measured IV curve is P_act, then the measured attenuation value is (P_nom-P_act) / P_nom. The measured attenuation value can be the amplitude, and there is no limitation on the specific conversion method.

[0183] In this embodiment, after obtaining the operating temperature assessment value, measured amplitude value, and attenuation assessment value of the perovskite module, the maximum power point [Vmppt, Imppt] of the perovskite module in the current state is obtained through a preset mapping relationship between the input data (operating temperature parameters, irradiation parameters, and attenuation parameters) and the output data (maximum power data). The output voltage and output current of the perovskite module are adjusted by the MPPT control module to make the perovskite module work at the maximum power point, thereby ensuring that the output power of the perovskite module is at the maximum level. In other words, by obtaining data such as the measured irradiation value and the measured ambient temperature value of the perovskite module, the maximum power point of the perovskite module is dynamically adjusted to ensure that the output power of the perovskite module is at the maximum level.

[0184] This application provides a power point tracking (MPPT) method, specifically an MPPT method applicable to perovskite modules. The specific implementation of the aforementioned embodiments has been described in detail through the above embodiments. It can be seen that by establishing a preset mapping relationship, maximum power point tracking can be achieved for perovskite modules with hysteresis or significant hysteresis, thus improving the MPPT accuracy of perovskite modules. Furthermore, it eliminates the need to wait for perovskite modules with hysteresis to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0185] Based on the same inventive concept as the foregoing embodiments. Figure 8 This is a schematic diagram illustrating the structural composition of a power tracking device provided in an embodiment of this application. Figure 8 As shown, the power point tracking device 80 may include an acquisition unit 801, a determination unit 802, and an adjustment unit 803, wherein:

[0186] The acquisition unit 801 is configured to acquire the measured values ​​of irradiance and ambient temperature of the photovoltaic module under test in the current state.

[0187] Unit 802 is configured to determine the operating temperature assessment value and degradation assessment value of the photovoltaic module under test based on the measured irradiance value and the measured ambient temperature value.

[0188] The determining unit 802 is further configured to determine the target maximum power data corresponding to the measured irradiation value, the operating temperature evaluation value, and the attenuation evaluation value based on the preset mapping relationship between the input parameters and the maximum power data; wherein the input parameters include: irradiation parameters, operating temperature parameters, and attenuation parameters;

[0189] The adjustment unit 803 is configured to adjust the power of the photovoltaic module under test according to the target maximum power data in order to achieve maximum power tracking of the photovoltaic module under test.

[0190] In some embodiments, see Figure 8 The power tracking device 80 may further include an establishment unit 804; an acquisition unit 801, further configured to acquire multiple sets of test data corresponding to the input parameters of the photovoltaic module under test; a determination unit 802, further configured to determine the maximum power data corresponding to each of the multiple sets of test data when the photovoltaic module under test is in a steady state; and an establishment unit 804, configured to establish a preset mapping relationship between the input parameters and the maximum power data based on the multiple sets of test data and the maximum power data corresponding to each of the multiple sets of test data.

[0191] In some embodiments, the determining unit 802 is further configured to determine the minimum power and maximum power of the photovoltaic module under test within a preset time period; determine the power change range of the photovoltaic module under test within the preset time period based on the minimum power and maximum power; and determine that the photovoltaic module under test is in a steady state when the power change range meets a preset range.

[0192] In some embodiments, the determining unit 802 is further configured to determine a training sample set; wherein the training sample set includes multiple sets of test data and maximum power data corresponding to each of the multiple sets of test data; and to train a preset model according to the training sample set, and when the model training meets a preset stopping condition, determine the trained preset model as a mapping model; wherein the mapping model is used to indicate a preset mapping relationship between input parameters and maximum power data.

[0193] In some embodiments, the determining unit 802 is further configured to input the measured irradiation value, the operating temperature assessment value, and the attenuation assessment value into the mapping model, and output the target maximum power data through the mapping model.

[0194] In some embodiments, the establishing unit 802 is further configured to establish a mapping table based on multiple sets of test data and the maximum power data corresponding to each set of test data; wherein the mapping table is used to indicate a preset mapping relationship between input parameters and maximum power data.

[0195] In some embodiments, the determining unit 802 is further configured to match the measured irradiance value, the operating temperature assessment value, and the attenuation assessment value with the input parameters in the mapping table; when the measured irradiance value, the operating temperature assessment value, and the attenuation assessment value match the input parameters in the mapping table, determine the target maximum power data based on the mapping table; when the measured irradiance value, the operating temperature assessment value, and the attenuation assessment value do not match the input parameters in the mapping table, perform interpolation calculations on the maximum power data in the mapping table based on the measured irradiance value, the operating temperature assessment value, and the attenuation assessment value to determine the target maximum power data.

[0196] In some embodiments, the acquisition unit 801 is further configured to acquire a preset value of output power corresponding to standard test conditions; the determination unit 802 is further configured to determine the measured value of output power of the photovoltaic module under test based on the module operation information; convert the measured value of output power based on standard test conditions, measured value of irradiation and measured value of ambient temperature to determine the calculated value of output power under standard test conditions; and perform attenuation assessment based on the calculated value of output power and the preset value of output power to determine the attenuation assessment value of the photovoltaic module under test.

[0197] This application provides a power tracking device, which may include an acquisition unit, a determination unit, and an adjustment unit. This not only enables accurate tracking of the maximum power point of a photovoltaic module under test exhibiting hysteresis, improving maximum power tracking accuracy, but also eliminates the need to wait for the hysteresis-affected photovoltaic module to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0198] In yet another embodiment of this application, Figure 9 This is a schematic diagram of the specific hardware structure of an electronic device provided in an embodiment of this application. For example... Figure 9 As shown, electronic device 90 may include: a communication interface 901, a memory 902, and a processor 903; the various components are coupled together via a bus system 904. It is understood that the bus system 904 is used to implement communication between these components. In addition to a data bus, the bus system 904 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 9 The various buses are all labeled as bus system 904. Among them, the communication interface 901 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

[0199] Memory 902 is used to store computer programs that can run on processor 903;

[0200] Processor 903, when running the computer program, performs the following:

[0201] The system acquires the measured irradiance and ambient temperature values ​​of the photovoltaic module under test (PV module) in its current state. Based on these values, it determines the estimated operating temperature and degradation values ​​of the PV module. According to a pre-defined mapping relationship between input parameters and maximum power data, it determines the target maximum power data corresponding to the measured irradiance, estimated operating temperature, and degradation values. The input parameters include irradiance parameters, operating temperature parameters, and degradation parameters. Based on the target maximum power data, the system adjusts the power of the PV module under test to achieve maximum power tracking.

[0202] It is understood that the memory 902 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 902 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0203] The processor 903 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 903 or by software instructions. The processor 903 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 902, and the processor 903 reads the information in memory 902 and, in conjunction with its hardware, completes the steps of the above method.

[0204] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0205] For software implementation, the techniques described herein can be achieved through modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented within the processor or externally.

[0206] Alternatively, as another embodiment, the processor 903 is further configured to perform the steps of any of the methods described in the foregoing embodiments when running the computer program.

[0207] In some embodiments, this application also provides an electronic device 90, which may include at least the power tracking device 80 described in any of the foregoing embodiments.

[0208] This application provides an electronic device that can not only accurately track the maximum power point of a photovoltaic module under test with hysteresis, thus improving the maximum power tracking accuracy, but also eliminates the need to wait for the photovoltaic module under test with hysteresis to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency.

[0209] Understandably, in this embodiment, a "unit" can be a portion of a circuit, a portion of a processor, a portion of a program or software, etc., and can also be a module or a non-modular component. Furthermore, the components in this embodiment can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module.

[0210] In this embodiment, if the integrated unit is implemented as a software functional module and not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0211] This application provides a computer-readable storage medium storing a computer program that, when executed by at least one processor, implements the steps of any of the methods described in the foregoing embodiments.

[0212] This application also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the method as described in any of the foregoing embodiments.

[0213] In yet another embodiment of this application, Figure 10 This is a schematic diagram illustrating the structural composition of a photovoltaic power generation system provided in an embodiment of this application. See also... Figure 10 The photovoltaic power generation system 100 may include a photovoltaic module 1001 and an electronic device 90, wherein the electronic device 90 includes the power tracking device 80 as described in any of the foregoing embodiments.

[0214] The power tracking device 80 is used to acquire the measured irradiance and ambient temperature of the photovoltaic module under test in its current state; determine the operating temperature assessment value and degradation assessment value of the photovoltaic module under test based on the measured irradiance and ambient temperature; and determine the target maximum power data corresponding to the measured irradiance, operating temperature assessment value, and degradation assessment value based on the preset mapping relationship between the input parameters and the maximum power data. The input parameters include irradiance parameters, operating temperature parameters, and degradation parameters. The device adjusts the power of the photovoltaic module under test according to the target maximum power data to achieve maximum power tracking of the photovoltaic module under test.

[0215] In this embodiment, the electronic device 90 can be an MPPT device or an inverter. The power point tracking device 80 can be directly integrated into the inverter. Figure 10 As shown in the diagram. If the inverter includes an MPPT control module, the power point tracking device 80 can also be located within the MPPT control module; the location of the power point tracking device 80 is not specifically limited here.

[0216] This application provides a photovoltaic power generation system, which includes photovoltaic modules, a power point tracking device, and an inverter. This not only enables accurate tracking of the maximum power point of a photovoltaic module with hysteresis (such as a perovskite module), improving maximum power tracking accuracy, but also eliminates the need to wait for the hysteresis-affected photovoltaic module to reach a steady state before collecting maximum power data, reducing waiting time and improving maximum power tracking efficiency, thereby increasing the efficiency of the photovoltaic power generation system.

[0217] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, devices, or computer program products. Therefore, this application can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage) containing computer-usable program code.

[0218] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0219] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0220] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0221] It should be noted that, in this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes that element.

[0222] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0223] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0224] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0225] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0226] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A power tracking method, characterized by, The method comprises: acquiring irradiation measured value, environment temperature measured value and component operation information of the photovoltaic component to be tested in current state; determining operation temperature evaluation value and attenuation evaluation value of the photovoltaic component to be tested according to the irradiation measured value, the environment temperature measured value and the component operation information; determining corresponding target maximum power data under the irradiation measured value, the operation temperature evaluation value and the attenuation evaluation value according to preset mapping relationship between input parameters and maximum power data; wherein, the input parameters comprise irradiation parameter, operation temperature parameter and attenuation parameter; adjusting power of the photovoltaic component to be tested according to the target maximum power data, so as to realize maximum power tracking of the photovoltaic component to be tested.

2. The method of claim 1, wherein, The method further comprises: acquiring multiple sets of test data corresponding to input parameters of the photovoltaic component to be tested; determining respective maximum power data of the photovoltaic component to be tested under the multiple sets of test data when the photovoltaic component to be tested is in steady state; establishing preset mapping relationship between the input parameters and maximum power data based on the multiple sets of test data and the respective maximum power data of the multiple sets of test data.

3. The method of claim 2, wherein, The method further comprises: determining power minimum value and power maximum value of the photovoltaic component to be tested within preset time; determining power variation amplitude of the photovoltaic component to be tested within preset time according to the power minimum value and the power maximum value; determining that the photovoltaic component to be tested is in steady state when the power variation amplitude meets preset range.

4. The method of claim 2, wherein, The establishing of preset mapping relationship between the input parameters and maximum power data based on the multiple sets of test data and the respective maximum power data of the multiple sets of test data comprises: determining training sample set; wherein, the training sample set comprises the multiple sets of test data and the respective maximum power data of the multiple sets of test data; performing model training on preset model according to the training sample set, and determining trained preset model as mapping model when the model training meets preset stop condition; wherein, the mapping model is used to indicate preset mapping relationship between the input parameters and maximum power data.

5. The method of claim 4, wherein, The determining of corresponding target maximum power data under the irradiation measured value, the operation temperature evaluation value and the attenuation evaluation value according to preset mapping relationship between input parameters and maximum power data comprises: inputting the irradiation measured value, the operation temperature evaluation value and the attenuation evaluation value into the mapping model, and outputting the target maximum power data through the mapping model.

6. The method of claim 2, wherein, The establishing of preset mapping relationship between the input parameters and maximum power data based on the multiple sets of test data and the respective maximum power data of the multiple sets of test data comprises: establishing mapping relationship table according to the multiple sets of test data and the respective maximum power data of the multiple sets of test data; wherein, the mapping relationship table is used to indicate preset mapping relationship between the input parameters and maximum power data.

7. The method of claim 6, wherein, The step of determining the target maximum power data corresponding to the measured irradiation value, the evaluated operating temperature value, and the evaluated attenuation value based on the preset mapping relationship between the input parameters and the maximum power data includes: The measured irradiation value, the estimated operating temperature value, and the estimated attenuation value are matched with the input parameters in the mapping table; When the measured irradiation value, the estimated operating temperature value, and the estimated attenuation value match the input parameters in the mapping table, the target maximum power data is determined based on the mapping table. When the measured irradiation value, the evaluated operating temperature value, and the evaluated attenuation value do not match the input parameters in the mapping table, the maximum power data in the mapping table is interpolated based on the measured irradiation value, the evaluated operating temperature value, and the evaluated attenuation value to determine the target maximum power data.

8. The method according to any one of claims 1 to 7, characterized in that, The step of determining the degradation assessment value of the photovoltaic module under test based on the measured irradiance value, the measured ambient temperature value, and the module operating information includes: Obtain the preset output power value corresponding to the standard test conditions; Based on the component operation information, determine the measured output power of the photovoltaic module under test; Based on the standard test conditions, the measured irradiation value, and the measured ambient temperature value, the measured output power value is converted to determine the calculated output power value under the standard test conditions. The degradation assessment value of the photovoltaic module under test is determined by performing a degradation assessment based on the calculated output power value and the preset output power value.

9. A power tracking device, characterized by, The power tracking device includes an acquisition unit, a determination unit, and an adjustment unit, wherein: The acquisition unit is configured to acquire the measured irradiance value, measured ambient temperature value, and module operation information of the photovoltaic module under test in the current state. The determining unit is configured to determine the operating temperature assessment value and the degradation assessment value of the photovoltaic module under test based on the measured irradiation value, the measured ambient temperature value, and the module operating information. The determining unit is further configured to determine the target maximum power data corresponding to the measured irradiation value, the operating temperature evaluation value, and the attenuation evaluation value based on a preset mapping relationship between the input parameters and the maximum power data; wherein the input parameters include: irradiation parameters, operating temperature parameters, and attenuation parameters; The adjustment unit is configured to adjust the power of the photovoltaic module under test according to the target maximum power data in order to achieve maximum power tracking of the photovoltaic module under test.

10. An electronic device, comprising: The electronic device includes a memory and a processor; wherein... The memory is used to store computer programs that can run on the processor; The processor is configured to perform the method as described in any one of claims 1 to 8 when running the computer program.

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

12. A computer program product comprising computer programs or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method of any one of claims 1 to 8.

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