Photovoltaic array reconstruction method, device, equipment, medium and product

Abstract

The invention relates to the technical field of photovoltaic arrays, in particular to a photovoltaic array reconstruction method, device, equipment, medium and product, and the method comprises the steps: determining a circuit connection relation between photovoltaic units in a photovoltaic array through the irradiance distribution of the photovoltaic array and an initial matrix generation strategy determined according to the current irradiation condition of the photovoltaic array; the matrix is an initial matrix. And carrying out iterative optimization on the initial matrix through a preset matrix optimization strategy until the initial matrix satisfies a preset irradiation difference condition, outputting a target matrix, and carrying out structure reconstruction on the photovoltaic array according to the target matrix so that the photovoltaic array accords with a corresponding circuit connection relationship of the target matrix. Therefore, the reconstruction efficiency and the reconstruction accuracy of the photovoltaic array are improved, and the output power of the photovoltaic array is improved.

Description

Technical Field

[0001] This application relates to the field of photovoltaic array technology, and in particular to a photovoltaic array reconfiguration method, apparatus, equipment, medium and product. Background Technology

[0002] Laser wireless power transfer technology, as an emerging method of wireless energy transmission, uses high-energy laser beams to transfer energy over long distances in space. It features high transmission efficiency, good directionality, and strong anti-interference capabilities, and has broad application prospects in areas such as space communication, drone endurance, and mobile device charging, providing crucial technical support for the development of future wireless energy networks. However, during laser wireless power transfer, factors such as clouds, turbulence, and thermal corona can alter the shape of the received laser spot, leading to power mismatch in the photovoltaic array, reducing its output power, and significantly limiting the efficiency of the photovoltaic system.

[0003] In related technologies, a single algorithm is typically used to calculate the appropriate photovoltaic array, thereby increasing the output power of the photovoltaic array by modifying its circuit structure. However, in actual laser wireless energy transmission, the irradiation conditions faced by the photovoltaic array are often complex, diverse, and dynamically changing. It is difficult to adapt to these conditions using a single, pre-fixed algorithm, making it impossible to determine a suitable photovoltaic array, resulting in a persistently low output power for the photovoltaic array.

[0004] Therefore, there is an urgent need for a photovoltaic array reconfiguration method to improve the reconfiguration efficiency and accuracy of photovoltaic arrays, thereby increasing the output power of photovoltaic arrays. Summary of the Invention

[0005] In view of the above problems, the present invention provides a photovoltaic array reconfiguration method, apparatus, device, medium and product to improve the reconfiguration efficiency and accuracy of photovoltaic arrays, thereby increasing the output power of photovoltaic arrays.

[0006] In a first aspect, this application provides a photovoltaic array reconfiguration method, the method comprising:

[0007] Based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy, the initial matrix corresponding to the photovoltaic array is determined; the initial matrix generation strategy is determined based on the current irradiance conditions of the photovoltaic array, and the initial matrix represents the circuit connection relationship between each photovoltaic unit in the photovoltaic array;

[0008] The initial matrix is ​​iteratively optimized based on a preset matrix optimization strategy until the initial matrix meets a preset irradiance difference condition, and the target matrix is ​​output; the irradiance difference condition indicates that the difference between the irradiance and the irradiance of every two elements in the corresponding matrix is ​​less than a preset threshold.

[0009] Secondly, this application provides a photovoltaic array reconfiguration device, the device comprising:

[0010] A photovoltaic array, including the circuit connection structure corresponding to each photovoltaic unit;

[0011] A matrix determination unit is used to determine the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy; the initial matrix generation strategy is determined based on the current irradiance conditions of the photovoltaic array, and the initial matrix represents the circuit connection relationship between each photovoltaic unit in the photovoltaic array;

[0012] The initial matrix is ​​iteratively optimized based on a preset matrix optimization strategy until the initial matrix meets a preset irradiance difference condition, and the target matrix is ​​output; the irradiance difference condition indicates that the difference between the irradiance and the irradiance of every two elements in the corresponding matrix is ​​less than a preset threshold.

[0013] An array reconstruction unit is used to reconstruct the structure of the photovoltaic array based on the target matrix, so that the photovoltaic array conforms to the corresponding circuit connection relationship of the target matrix.

[0014] Optionally, the array reconfiguration unit is further configured to determine the irradiance distribution based on the power value of each photovoltaic unit in the photovoltaic array; the irradiance distribution includes the irradiance of each photovoltaic unit in the photovoltaic array.

[0015] The matrix determination unit is further configured to determine the initial matrix generation strategy from a preset strategy set based on the current irradiation conditions, wherein the current irradiation conditions characterize the uniformity of the light spot energy received by the photovoltaic array.

[0016] Optionally, when the initial matrix generation strategy is the first matrix generation strategy, the matrix determination unit is specifically used for:

[0017] The elements in the irradiance distribution are arranged in descending order to obtain an element sequence; and the total number of element groups is determined based on the total number of elements corresponding to each element, wherein the total number of groups is determined based on a factor of the total number of elements.

[0018] Based on a preset first allocation strategy, each element is assigned to a corresponding element group to obtain the initial matrix; the first allocation strategy is characterized by: assigning the element to the element group with the smallest sum of irradiance among the current element groups, and when the sum of irradiance of multiple element groups is the same, assigning the element to the element group with the smallest number.

[0019] Optionally, when the initial matrix generation strategy is the second matrix generation strategy, the matrix determination unit is specifically used for:

[0020] The elements in the irradiance distribution are sorted in descending order to obtain an element sequence; and the irradiance threshold is determined based on the median of the element sequence.

[0021] The element sequence is divided into abnormal groups based on the irradiance threshold to determine abnormal element groups; the irradiance of each abnormal element in the abnormal element group is less than the irradiance threshold.

[0022] Based on the abnormal irradiance and value of the abnormal element group and the ratio between the total irradiance and value of the element sequence, the number of remaining groups corresponding to each element group is determined.

[0023] Based on the preset second allocation strategy and the remaining number of groups, each element is allocated to the corresponding element group to obtain the initial matrix; the second allocation strategy is characterized by: based on the sorting of the element sequence and the numbering order of each element group, the elements are sequentially allocated to the current group until the irradiance and value of the current group exceed the abnormal irradiance and value, and then the corresponding elements are allocated to the next element group corresponding to the next number.

[0024] Optionally, when the initial matrix generation strategy is the third matrix generation strategy, the matrix determination unit is specifically used for:

[0025] The elements in the irradiance distribution are sorted in descending order to obtain an element sequence; and the irradiance threshold is determined based on the median of the element sequence.

[0026] The element sequence is divided into abnormal groups based on the irradiance threshold to determine abnormal element groups; the irradiance of each abnormal element in the abnormal element group is less than the irradiance threshold.

[0027] Based on the sum of the abnormal irradiance and values ​​of the abnormal element group and the sum of the total irradiance and values ​​of the element sequence, determine the number of remaining groups corresponding to the element group;

[0028] Based on a preset third allocation strategy, each element is assigned to a corresponding element group to obtain the initial matrix; the third allocation strategy is characterized by: assigning the element to the element group with the smallest sum of irradiance among the current element groups, and when the sum of irradiance of multiple element groups is the same, assigning the element to the element group with the smallest number.

[0029] Optionally, the initial matrix generation strategy includes a first matrix generation strategy, a second matrix generation strategy, and a third matrix generation strategy, wherein the first matrix generation strategy corresponds to the energy uniformity of a first light spot, the second matrix generation strategy corresponds to the energy uniformity of a second light spot, and the third matrix generation strategy corresponds to the energy uniformity of a third light spot, and the energy uniformity of the first light spot, the energy uniformity of the second light spot, and the energy uniformity of the third light spot show a decreasing trend.

[0030] Optionally, the matrix determining unit is specifically used for:

[0031] Element swaps are performed on the two groups of elements in the initial matrix to obtain candidate comparison groups;

[0032] When the exchange difference value of the candidate comparison group meets the preset difference reduction condition, the two element groups are exchanged to obtain the optimized element group; the exchange difference value represents the change in irradiance and value of the corresponding two element groups before and after the element exchange.

[0033] Thirdly, this application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the photovoltaic array reconfiguration methods described in the first aspect above.

[0034] Fourthly, this application provides a computer storage medium storing computer program instructions, which are executed by a processor using any of the photovoltaic array reconfiguration methods described in the first aspect above.

[0035] Fifthly, an embodiment of this application provides a computer program product including computer program instructions, which, when executed by a processor, implement any one of the photovoltaic array reconfiguration methods described in the first aspect above.

[0036] The beneficial effects of this invention are as follows:

[0037] This application provides a photovoltaic array reconfiguration method. This method determines the circuit connection relationships (i.e., the initial matrix) between photovoltaic units in the photovoltaic array based on the irradiance distribution of the array and an initial matrix generation strategy determined according to the current irradiance conditions of the array. The initial matrix is ​​then iteratively optimized using a preset matrix optimization strategy until it meets preset irradiance difference conditions, outputting a target matrix. The photovoltaic array is then structurally reconfigured based on the target matrix to ensure that the array conforms to the corresponding circuit connection relationships of the target matrix. This improves the reconfiguration efficiency and accuracy of the photovoltaic array, thereby increasing its output power. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0039] Figure 1A schematic flowchart illustrating a photovoltaic array reconfiguration method provided in an embodiment of this application;

[0040] Figure 2 A schematic diagram illustrating an initial matrix generation process provided in an embodiment of this application;

[0041] Figure 3 A schematic diagram illustrating another initial matrix generation process provided in an embodiment of this application;

[0042] Figure 4 A schematic diagram illustrating another initial matrix generation process provided in an embodiment of this application;

[0043] Figure 5 A schematic diagram illustrating an iterative optimization process for an initial matrix provided in an embodiment of this application;

[0044] Figure 6 This is a schematic diagram of a photovoltaic array reconfiguration device provided in an embodiment of this application;

[0045] Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0047] The terms "first" and "second" in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the term "comprising" and any variations thereof are intended to cover non-exclusive protection. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. The term "multiple" in this application can mean at least two, for example, two, three, or more, and this application does not impose limitations.

[0048] The term "and / or" in the embodiments of this application is merely a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0049] The design concept of the embodiments of this application will be briefly introduced below.

[0050] Laser wireless power transmission (LWPT), as an emerging wireless power transfer method, uses high-energy laser beams to transfer energy over long distances in space. It features high transmission efficiency, good directionality, and strong anti-interference capabilities, making it promising for applications in space communication, drone endurance, and mobile device charging. It provides crucial technical support for the development of future wireless power networks. Furthermore, LWPT boasts advantages such as good directionality, high energy density, and long transmission distance, enabling non-contact continuous power supply to devices even in extreme environments.

[0051] However, during laser wireless energy transmission, factors such as clouds, turbulence, and thermal corona can alter the shape of the received light spot, leading to power mismatch in the photovoltaic array and reducing its output power, thus significantly limiting the efficiency of the photovoltaic system. Related technologies typically employ a single algorithm to calculate a suitable photovoltaic array, thereby modifying the array's circuit structure and increasing its output power. However, in actual laser wireless energy transmission, the irradiation conditions faced by the photovoltaic array are complex, diverse, and dynamically changing. A single, pre-fixed algorithm is insufficient for successful adaptation, failing to determine a suitable photovoltaic array and resulting in persistently low output power.

[0052] To address the aforementioned issues, this application provides a photovoltaic array reconfiguration method. This method determines the circuit connection relationships (i.e., the initial matrix) between photovoltaic units in the photovoltaic array based on the irradiance distribution of the array and an initial matrix generation strategy determined according to the current irradiance conditions of the array. The initial matrix is ​​then iteratively optimized using a preset matrix optimization strategy until it meets preset irradiance difference conditions, outputting a target matrix. The photovoltaic array is then structurally reconfigured based on the target matrix to ensure that the array conforms to the corresponding circuit connection relationships of the target matrix. This improves the reconfiguration efficiency and accuracy of the photovoltaic array, thereby increasing its output power.

[0053] The method provided by exemplary embodiments of this application will now be described with reference to the accompanying drawings, such as... Figure 1 As shown in the figure, this application provides a photovoltaic array reconfiguration method, the specific process of which is as follows:

[0054] Step 101: Determine the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy.

[0055] In this embodiment, the irradiance distribution includes the irradiance of each photovoltaic unit in the photovoltaic array. The initial matrix generation strategy is determined based on the current irradiance conditions of the photovoltaic array. In this way, the initial circuit connection relationship between each photovoltaic unit can be determined according to different irradiance conditions of the photovoltaic array, ensuring the output efficiency of the photovoltaic array under different irradiance conditions.

[0056] In one possible implementation, before determining the initial matrix, the irradiance distribution of the photovoltaic array is determined by the power value of each photovoltaic unit in the photovoltaic array. Based on the uniformity of the light spot energy currently received by the photovoltaic matrix, i.e., the current irradiance condition, a corresponding initial matrix generation strategy is selected from a preset strategy set to achieve subsequent initial matrix generation and target matrix optimization. In this way, by using initial matrix generation strategies corresponding to different light spot energy uniformity, the initial matrix generated by this application can be adapted to any irradiance condition, thereby improving the output efficiency of the photovoltaic array reconstructed by this application under various irradiance conditions.

[0057] Specifically, this application can obtain the power distribution of the photovoltaic array by measuring the power at both ends of each cell in the photovoltaic array and then normalizing it. Since irradiance and power are positively correlated, the power distribution obtained by the process can be equivalent to the irradiance distribution in this application, so as to collect the irradiance distribution information received by the photovoltaic array.

[0058] In one possible implementation, this application can measure the power at both ends of each solar cell using a sampling module, and ensure that the distance between each solar cell and the sampling module is equal during sampling. For example, each solar cell of the photovoltaic array can be connected to the sampling module using wires of the same length, so that the equivalent impedance of the sampling channel of each solar cell is the same, thus ensuring the accuracy and stability of the sampling.

[0059] In one possible implementation, the initial matrix production strategy in the preset strategy set of this application embodiment includes at least: a first matrix generation strategy, a second matrix generation strategy, and a third matrix generation strategy corresponding to different irradiation conditions, wherein the first matrix generation strategy corresponds to the first spot energy uniformity, the second matrix generation strategy corresponds to the second spot energy uniformity, and the third matrix generation strategy corresponds to the third spot energy uniformity, and the energy uniformity of the first, second, and third spots exhibits a decreasing trend. Thus, based on different irradiation conditions where the spot energy uniformity is uniform, slightly non-uniform, or severely non-uniform, corresponding first, second, and third matrix generation strategies are designed respectively, making the initial matrix adaptable to different irradiation conditions of uniform, slightly non-uniform, and severely non-uniform spot energy, thereby improving the output efficiency of the photovoltaic matrix under various irradiation conditions.

[0060] In one possible implementation, embodiments of this application can utilize the variance σ of the irradiance distribution. 2 Choose the appropriate matrix generation strategy.

[0061] Specifically, this application pre-normalizes the irradiance data of the photovoltaic array, thus allowing the calculation of the variance σ of the irradiance distribution. 2 Matching is performed based on a preset variance threshold, for example, if σ 2 If σ < 0.015, the first matrix generation strategy is preferred; if 0.015 ≤ σ 2 If ≤0.03, the second matrix generation strategy is preferred; if σ 2 If the value is greater than 0.03, the third matrix generation strategy should be preferred.

[0062] In one possible implementation, when selecting a first matrix generation strategy as the initial matrix generation strategy, this application sorts each element in descending order according to the relative irradiance of each element in the irradiance distribution to obtain an element sequence. The total number of element groups is determined based on the total number of elements in the irradiance distribution, which is determined by a factor of the total number of elements. Thus, after obtaining the element sequence and the required number of element groups, each element in the element sequence is sequentially assigned to the element group with the smallest sum of irradiance values ​​in the current element group according to a preset first allocation strategy. If multiple element groups have the same sum of irradiance values, the element is assigned to the element group with the smallest number, thereby obtaining the initial matrix.

[0063] For details, please refer to Figure 2The diagram illustrates the initial matrix generation process of the first matrix generation strategy provided in this application embodiment. This application inputs the irradiance distribution of the photovoltaic array into the target algorithm (i.e., the first matrix generation strategy), and arranges the irradiance of each photovoltaic unit in descending order, assigning numbers sequentially (e.g., a1, a2, ..., an). Then, using a greedy algorithm, they are evenly divided into appropriate groups (e.g., P1, P2, ..., Pm). The specific grouping process includes: determining the total number of groups required based on the total number of photovoltaic units in the photovoltaic array. After determining the total number of groups, subsequent elements are allocated according to the sum of the current elements (i.e., the irradiance of each photovoltaic unit) in each group, prioritizing the allocation of subsequent elements to the group with the smallest sum of the current elements. If multiple groups have the same sum of elements, elements are prioritized for allocation to the group with the smaller number.

[0064] Specifically, this application arranges the irradiance of each photovoltaic unit in descending order and assigns numbers accordingly, resulting in multiple elements a1, a2, ..., an. These elements are then divided into an appropriate number of element groups using a greedy algorithm, resulting in multiple element groups P1, P2, ..., Pm, where n > m. For example, if the photovoltaic array is a 6x6 structure with 36 photovoltaic units, the corresponding irradiance distribution includes 36 elements. Based on the factor of 36, the total number of element groups required is 6, with each group containing 6 elements corresponding to 6 photovoltaic units. During the grouping process, a1 is placed in group P1, a2 in group P2, and so on, until each group contains one element. For am+1, it will enter group Pm following the above process. For am+2, the sum of elements within each group is compared. If several groups have the same sum, the element is assigned to the group with the smaller number. For example, if Pm and P1 have the same sum, the element is assigned to P1. For example, after sorting the irradiance in descending order, the first 6 elements are placed into 6 element groups, with one element in each group. The 7th element (a7) will be assigned to the element group with the smallest sum of current irradiance. If the sums of irradiance in all element groups are the same at this point, the elements are assigned sequentially according to their group numbers. This ensures that high-irradiance units are evenly distributed, preventing some groups from saturating prematurely and reducing the number of iterations required for subsequent optimization. This process is repeated until all elements have been assigned.

[0065] In one possible implementation, when selecting the second matrix generation strategy as the initial matrix generation strategy, this application sorts the elements in descending order according to the relative irradiance of each element in the irradiance distribution to obtain an element sequence. Then, based on the median of the element sequence, an irradiance threshold is determined. This threshold is used to divide the element sequence into aberration groups, identifying aberration element groups where the irradiance of each aberration element is less than the threshold. Next, the ratio between the aberration sum of the aberration element groups and the total irradiance sum of the element sequence is used to determine the remaining number of groups corresponding to the required element group division. After determining the remaining number of groups, elements are sequentially assigned to the current group according to the preset second allocation strategy, following the order of the element sequence and the numbering order of each element group. This continues until the irradiance sum of the current group exceeds the aberration sum of the element group, at which point the corresponding element is assigned to the next element group. This process is repeated until all elements are assigned, resulting in the initial matrix.

[0066] For details, please refer to Figure 3 The diagram illustrates the initial matrix generation process of the second matrix generation strategy provided in this application embodiment. This application inputs the irradiance distribution of the photovoltaic array into the target algorithm (i.e., the second matrix generation strategy), and arranges the irradiance of each photovoltaic unit in descending order (e.g., denoted as a1, a2, ..., an multiple elements). The median element is denoted as amed, and the irradiance amed-w (algorithm preset value) corresponding to this element is used as a threshold. Elements smaller than this threshold are placed into a group (i.e., an abnormal group), and the number of elements in the group is recorded. The number of remaining groups is determined by calculating the sum of abnormal elements corresponding to the abnormal group and the total sum of all elements, and dividing the two (e.g., denoted as P1, P2, ..., Pm). After determining the number of remaining groups, each element can be placed into its respective group according to the element sequence order until the current group is saturated, i.e., the sum of elements within the abnormal group is reached. For example, element a1 is placed in group P1. For element a2, if the sum of elements in group P1 is less than the sum of elements in the abnormal group, it is placed in group P1; otherwise, it is placed in the next group. This process is repeated until all elements are assigned. In this way, photovoltaic units with abnormally low irradiance (such as cloud-shaded areas) are identified by the median threshold and processed in independent groups. This avoids inefficient units interfering with the balance of the main group. The number of groups is determined based on the ratio of irradiance of the abnormal group to that of all photovoltaic units. Compared to traditional fixed grouping (e.g., 6 fixed groups), this method more precisely matches the current irradiance distribution characteristics, ensuring that the power capacity of each group matches the actual available energy. Furthermore, using the sum of irradiance of the abnormal group as the upper limit for element grouping ensures that the sum of irradiance of each element group does not exceed the abnormal baseline, further improving the output power of the photovoltaic array.

[0067] In one possible implementation, when selecting a third matrix generation strategy as the initial matrix generation strategy, this application sorts each element in descending order based on the relative irradiance of each element in the irradiance distribution to obtain an element sequence. Then, based on the median of the element sequence, an irradiance threshold is determined. This threshold is used to divide the element sequence into aberration groups, identifying aberration element groups where the irradiance of each aberration element is less than the threshold. Next, the ratio between the sum of the aberration irradiance of the aberration element group and the sum of the total irradiance of the element sequence is used to determine the remaining number of groups corresponding to the required element group division. Thus, after determining the remaining number of groups, each element in the element sequence is sequentially assigned to the element group with the smallest sum of irradiance among the current element groups according to a preset third allocation strategy. If multiple element groups have the same sum of irradiance, the element is assigned to the element group with the smallest number, thereby obtaining the initial matrix.

[0068] For details, please refer to Figure 4 The diagram illustrates the initial matrix generation process of the third matrix generation strategy provided in this application embodiment. This application inputs the irradiance distribution into the target algorithm (third matrix generation strategy) and arranges the irradiance of each photovoltaic unit in descending order (denoted as a1, a2, ..., an). The median element is denoted as amed, and the corresponding irradiance amed-w (algorithm preset value) is used as a threshold. Elements smaller than this threshold are placed into a group (i.e., anomaly group), and the number of elements in the group is recorded. The number of remaining groups is determined by calculating the sum of the anomalous elements corresponding to the anomaly group and the total sum of all elements, and dividing the two (e.g., denoted as P1, P2, ..., Pm). After confirming the number of remaining groups, this application allocates subsequent elements according to the size of the sum of the current elements in each group, prioritizing the allocation of elements to the element group with the smallest sum in the current group. If there are several element groups with the same sum in the current group, elements are prioritized for allocation to the element group with the smaller number.

[0069] Specifically, this application arranges the irradiance of each photovoltaic unit in descending order and assigns numbers sequentially, resulting in multiple elements a1, a2, ..., an. a1 is placed in group P1, a2 in group P2, and so on, until each element group contains one element. For am+1, following the above process, it will enter group Pm. For am+2, the sum of elements within each element group is compared. If several groups have the same sum, the element is assigned to the group with the smaller number. For example, if Pm and P1 have the same sum, the element is assigned to P1. This process is repeated until all elements are assigned. Thus, the third matrix generation strategy employs a dual rule of prioritizing the minimum element sum and prioritizing the number, preferentially assigning high-irradiance units to the element group with the smallest current irradiance sum, ensuring initial load balance among element groups. Furthermore, by consistently selecting lower-numbered groups, randomness is eliminated, guaranteeing the determinism of the algorithm output.

[0070] Step 102: Iteratively optimize the initial matrix based on the preset matrix optimization strategy until the initial matrix meets the preset irradiance difference condition, and output the target matrix.

[0071] In this embodiment of the application, the irradiance difference condition means that the difference between the irradiance and the irradiance of each two element groups is less than a preset threshold. In this way, the initial matrix is ​​iteratively optimized through this optimization condition, so as to ensure that the irradiance distribution among the element groups in the target matrix is ​​balanced, reduce the mismatch loss of the photovoltaic array, and improve the overall power generation efficiency.

[0072] In one possible implementation, during each iteration of optimization, this application can perform element-wise swaps on two groups of elements in the initial matrix to obtain candidate comparison groups. When the changes in irradiance and values ​​before and after the element swap satisfy a preset difference descent condition, the corresponding two groups of elements are swapped to obtain the optimized target matrix. Thus, by employing a pairwise comparison group traversal strategy, the instability of traditional stochastic optimization algorithms is eliminated, ensuring unique output results under the same input conditions. It also ensures that effective element adjustments are performed in each iteration, avoiding invalid computations, and enabling the optimization process to quickly converge to the global optimum within a finite number of iterations.

[0073] Specifically, to ensure that the sum of irradiance within a group is equal or as similar as possible, this application compares each element group with any other element group in each iteration of optimization, calculating whether the exchange effectively reduces the difference in the sum of irradiance. Thus, by using a pairwise comparison and exchange strategy, the change in power difference between groups before and after the exchange is calculated, thereby minimizing the difference in irradiance values ​​between any two element groups.

[0074] Specifically, in this embodiment, for group P1, it is first compared with group P2 to calculate whether there are any elements that, when swapped, would decrease the difference in the sum of elements within the two groups. If so, the elements are swapped. Next, group P1 is compared with groups P3, ..., Pm, and the same calculation is performed in the previous step. This process is repeated for groups P2, ..., Pm. This process is continued until no elements can be swapped, or a preset number of iterations k is reached, at which point a target matrix that meets the irradiation difference condition is output.

[0075] In one possible implementation, refer to Figure 5 The diagram illustrates an iterative optimization process for an initial matrix according to an embodiment of this application. First, the initial matrix is ​​grouped into m groups, from P1 to Pm. The loop count is set to k, and the current loop count is initialized to 0. The outer loop iterates through each group Pi (i from 1 to m-1), and the inner loop iterates through each group Pj (j from i+1 to m). For each element in Pi, it attempts to swap it with each element in Pj, calculating the difference between the sums of the elements in the two groups after the swap. If the difference in the sums decreases after the swap, the swap operation is performed and the loop count is incremented by 1. If the difference in the sums does not decrease after the swap, the swap operation is not performed. This process of iterating through all pairs of groups and performing element swap checks using the inner and outer loops gradually optimizes the matrix until the preset loop count k is reached or the difference in the sums of the elements meets the convergence condition.

[0076] In one possible implementation, the embodiments of this application can simultaneously run three strategies—a first matrix generation strategy, a second matrix generation strategy, and a third matrix generation strategy—for iterative optimization to obtain the corresponding target matrix, perform simulated power calculation, and select the target matrix that can achieve the maximum simulated power.

[0077] Specifically, this application can simultaneously run three matrix generation strategies and perform power simulation calculations on the target matrices obtained after optimization for each strategy. For example, based on the element with the minimum irradiance in each group of photovoltaic units in the target matrix, the short-circuit current of that group of series branches is determined. The power of each group of photovoltaic units is equal to the short-circuit current multiplied by the total number of elements in the group. The sum of the power of each group in the target matrix is ​​the simulated power corresponding to that target matrix. Thus, by comparing the simulated power values ​​of the three matrices, the target matrix corresponding to the maximum power value can be selected for subsequent photovoltaic array reconstruction.

[0078] Step 103: Reconstruct the structure of the photovoltaic array based on the target matrix so that the photovoltaic array conforms to the corresponding circuit connection relationship of the target matrix.

[0079] In this embodiment of the application, after determining the initial matrix and the matrix iterative optimization process described above, the circuit structure of the photovoltaic array can be changed by obtaining the target matrix, so that the series and parallel connection relationship of each photovoltaic unit in the photovoltaic array corresponds to the target matrix, thereby realizing the reconstruction of the photovoltaic matrix.

[0080] In one possible implementation, after obtaining the target matrix, this application can change the original series-parallel structure of the photovoltaic array circuit to connect the photovoltaic units of the corresponding group in the target matrix in series within the same group and connect different groups in parallel, thereby increasing the final output power of the photovoltaic array.

[0081] Specifically, the target matrix in this application embodiment may include irradiance and spatial location information of multiple groups of photovoltaic units in the photovoltaic array. For example, a 6×6 photovoltaic array is divided into 6 groups, each group containing 6 photovoltaic units at different locations and their irradiance values. The positive and negative terminals of each photovoltaic unit in the photovoltaic array can be connected by independent switches. When it is necessary to change the circuit structure, this application can disconnect the original connection through the controller and, according to the target matrix, sequentially close the series switches of the units in each group. For example, the 6 specified photovoltaic units in group P1 can be connected in series to form a branch through switches, and the photovoltaic units of different groups can be connected in parallel through switches, thereby increasing the final output power of the photovoltaic array.

[0082] Based on the same inventive concept, this application also provides a photovoltaic array reconfiguration device, which includes:

[0083] A photovoltaic array includes the circuit connection structure corresponding to each photovoltaic unit.

[0084] The matrix determination unit is used to determine the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy. The initial matrix generation strategy is determined based on the current irradiance conditions of the photovoltaic array, and the initial matrix represents the circuit connection relationship between each photovoltaic unit in the photovoltaic array.

[0085] The initial matrix is ​​iteratively optimized based on a preset matrix optimization strategy until the initial matrix meets the preset irradiance difference condition, and the target matrix is ​​output. The irradiance difference condition indicates that the difference between the irradiance and the sum of every two elements in the corresponding matrix is ​​less than a preset threshold.

[0086] The array reconstruction unit is used to reconstruct the structure of the photovoltaic array based on the target matrix so that the photovoltaic array conforms to the corresponding circuit connection relationship of the target matrix.

[0087] In one possible implementation, such as Figure 6The illustration shows a photovoltaic array reconfiguration device 60 provided in an embodiment of this application. The photovoltaic array can be in the form of a photovoltaic matrix 601. The matrix determination unit can use a Total-Cross-Tied (TCT) circuit board 602 to collect matrix information such as the irradiance distribution of the photovoltaic matrix, communicate with a host computer (or embedded system) 603, and send the aforementioned matrix information to it. It then receives the target matrix information fed back by the host computer, which is used to change the circuit structure of the photovoltaic matrix to achieve photovoltaic matrix reconfiguration. The host computer (or embedded system), as the matrix determination unit, calculates the initial matrix and the target matrix based on the matrix information, and then feeds back the calculated structure to the TCT circuit board.

[0088] For ease of description, the above sections are divided into functional units (or modules) and described separately. Of course, in implementing this application, the functions of each unit (or module) can be implemented in one or more software or hardware components. Those skilled in the art will understand that various aspects of this application can be implemented as systems, methods, or program products. Therefore, various aspects of this application can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, collectively referred to herein as "circuit," "module," or "system."

[0089] This device can be used to execute the methods shown in the various embodiments of this application. Therefore, the functions that each functional module of this device can achieve can be referred to the description of the foregoing embodiments, and will not be repeated here.

[0090] Please see Figure 7 As shown, based on the same technical concept, this application embodiment also provides a computer device 70, which can be used for... Figure 5 The photovoltaic array reconfiguration device shown includes a computer device such as... Figure 7 As shown, it includes a memory 701, a communication module 703, and one or more processors 702.

[0091] The memory 701 is used to store computer programs executed by the processor 702. The memory 701 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and programs required to run instant messaging functions, etc.; the data storage area may store various instant messaging information and operation instruction sets, etc.

[0092] Memory 701 may be volatile memory, such as random-access memory (RAM); memory 701 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or memory 701 may be any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. Memory 701 may be a combination of the above-described memories.

[0093] The processor 702 may include one or more central processing units (CPUs) or digital processing units, etc. The processor 702 is used to implement the aforementioned photovoltaic array reconfiguration method when it calls the computer program stored in the memory 701.

[0094] The communication module 703 is used to communicate with terminal devices or other servers.

[0095] This application embodiment does not limit the specific connection medium between the memory 701, communication module 703, and processor 702 described above. This application embodiment... Figure 7 The memory 701 and the processor 702 are connected via a bus 704, and the bus 704 is in Figure 7 The diagram uses thick lines to describe the connections between other components; these are for illustrative purposes only and should not be considered limiting. The 704 bus can be divided into address bus, data bus, control bus, etc. For ease of description, Figure 7 It is described using only a thick line, but does not indicate that there is only one bus or one type of bus.

[0096] The memory 701 stores a computer storage medium, which stores computer-executable instructions. The computer-executable instructions are used to implement the photovoltaic array reconfiguration method of the embodiments of this application, and the processor 702 is used to execute the photovoltaic array reconfiguration method of the above embodiments.

[0097] Based on the same inventive concept, embodiments of this application also provide a storage medium storing a computer program that, when run on a computer, causes the computer to perform the steps in the photovoltaic array reconfiguration method according to various exemplary embodiments of this application described above.

[0098] In some possible implementations, various aspects of the photovoltaic array reconfiguration method provided in this application can also be implemented in the form of a computer program product, which includes a computer program that, when run on a computer device, causes the computer device to perform the steps in the photovoltaic array reconfiguration method according to various exemplary embodiments of this application described above. For example, the computer device can perform the steps of the various embodiments.

[0099] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0100] The program product of the embodiments of this application may employ a portable compact disc read-only memory (CD-ROM) and include a computer program, and may run on a computer device. However, the program product of this application is not limited thereto. In this application, the readable storage medium may be any tangible medium that contains or stores a program, and the computer program included therein may be used by or in conjunction with a command execution system, apparatus, or device.

[0101] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a readable computer program. This propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with a command execution system, apparatus, or device.

[0102] Computer programs contained on readable media may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0103] Computer programs for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages.

[0104] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0105] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0106] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0108] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method of photovoltaic array reconfiguration, the method comprising: The method comprises: determining an initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and an initial matrix generation strategy; the initial matrix generation strategy is determined based on the current irradiation condition of the photovoltaic array, and the initial matrix represents the circuit connection relationship between each photovoltaic unit in the photovoltaic array; iteratively optimizing the initial matrix based on a preset matrix optimization strategy until the initial matrix meets a preset irradiation difference condition, and outputting a target matrix; the irradiation difference condition represents that the difference value between the irradiance sum values of each two element groups in the corresponding matrix is less than a preset threshold value; based on the target matrix, reconstructing the structure of the photovoltaic array to make the photovoltaic array meet the corresponding circuit connection relationship of the target matrix.

2. The method of claim 1, wherein, Before determining the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy, the method further comprises: determining the irradiance distribution based on the power value of each photovoltaic unit in the photovoltaic array; the irradiance distribution includes the irradiance of each photovoltaic unit in the photovoltaic array, determining the initial matrix generation strategy from a preset strategy set based on the current irradiation condition, and the current irradiation condition represents the uniformity of the spot energy received by the photovoltaic array.

3. The method of claim 1, wherein, When the initial matrix generation strategy is a first matrix generation strategy, the determination of the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy comprises: arranging each element in the irradiance distribution in descending order to obtain an element sequence, and determining the total number of element groups based on the total number of elements corresponding to each element; the total number of groups is determined based on the factor of the total number of elements; distributing each element into the corresponding element group based on a preset first distribution strategy to obtain the initial matrix; the first distribution strategy represents that the element is distributed into the element group with the minimum irradiance sum value in the current element group, and when the irradiance sum values of multiple element groups are the same, the element is distributed into the element group with the smallest number.

4. The method of claim 1, wherein, When the initial matrix generation strategy is a second matrix generation strategy, the determination of the initial matrix corresponding to the photovoltaic array based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy comprises: arranging each element in the irradiance distribution in descending order to obtain an element sequence, and determining an irradiance threshold value based on the median of the element sequence; dividing the element sequence into an abnormal element group based on the irradiance threshold value; the irradiance of each abnormal element in the abnormal element group is less than the irradiance threshold value; determining the remaining group number corresponding to each element group based on the ratio between the abnormal irradiance sum value of the abnormal element group and the total irradiance sum value of the element sequence. The elements are allocated into corresponding element groups based on a preset second allocation strategy and the remaining group number, to obtain the initial matrix; the second allocation strategy represents that elements are sequentially allocated into a current group based on the order of the element sequence and the numbering order of element groups, until the irradiance sum and value of the current group exceeds the abnormal irradiance sum and value, and the corresponding element is allocated into an element group corresponding to a next number.

5. The method of claim 1, wherein, When the initial matrix generation strategy is a third matrix generation strategy, the initial matrix corresponding to the photovoltaic array is determined based on the irradiance distribution of the photovoltaic array and the initial matrix generation strategy, including: The elements in the irradiance distribution are arranged in descending order to obtain an element sequence; and based on the median of the element sequence, an irradiance threshold is determined; Based on the irradiance threshold, the element sequence is divided into abnormal groups to determine an abnormal element group; the irradiance of each abnormal element in the abnormal element group is less than the irradiance threshold; Based on the sum value between the abnormal irradiance sum value of the abnormal element group and the total irradiance sum value of the element sequence, a remaining group number corresponding to the element group is determined; Based on a preset third allocation strategy, each element is allocated into a corresponding element group to obtain the initial matrix; the third allocation strategy represents that elements are allocated into an element group with the minimum irradiance sum and value in each current element group, and when the irradiance sum and values of multiple element groups are the same, the elements are allocated into an element group with the minimum number.

6. The method of any one of claims 1-5, wherein, The initial matrix generation strategy includes a first matrix generation strategy, a second matrix generation strategy and a third matrix generation strategy, wherein the first matrix generation strategy corresponds to a first light spot energy uniformity, the second matrix generation strategy corresponds to a second light spot energy uniformity, the third matrix generation strategy corresponds to a third light spot energy uniformity, and the first light spot energy uniformity, the second light spot energy uniformity and the third light spot energy uniformity show a downward trend.

7. The method of claim 1, wherein, Each iteration optimization includes: Element quasi-exchange is performed on two element groups in the initial matrix to obtain a candidate comparison group; When the exchange difference value of the candidate comparison group meets a preset difference drop condition, element exchange is performed on the two element groups to obtain an optimized element group; the exchange difference value represents the change amount of the irradiance sum and value of the corresponding two element groups before and after element exchange.

8. A photovoltaic array reconfiguration device, characterized by, The device includes: A photovoltaic array including a circuit connection structure corresponding to each photovoltaic unit; A matrix determination unit configured to determine an initial matrix corresponding to the photovoltaic array based on an irradiance distribution of the photovoltaic array and an initial matrix generation strategy; the initial matrix generation strategy is determined based on a current irradiation condition of the photovoltaic array, and the initial matrix represents a circuit connection relationship between the photovoltaic units in the photovoltaic array; The initial matrix is iteratively optimized based on a preset matrix optimization strategy until the initial matrix meets a preset irradiation difference condition, and a target matrix is output; the irradiation difference condition represents that the difference value between the irradiance sum and value of each two element groups in the corresponding matrix is less than a preset threshold. An array reconstruction unit is configured to reconstruct the photovoltaic array based on the target matrix, so that the photovoltaic array meets the corresponding circuit connection relationship of the target matrix. 9.A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, The processor executes the computer program to implement the steps of the method in any one of claims 1 to 7. 10.A computer storage medium having computer program instructions stored thereon, wherein, The computer program instructions are executed by the processor to implement the steps of the method in any one of claims 1 to 7. 11.A computer program product, comprising computer program instructions, wherein, The computer program instructions are executed by the processor to implement the steps of the method in any one of claims 1 to 7.

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