A photovoltaic module string line arrangement determination method, device and electronic equipment

Abstract

Embodiments of the present application provide a photovoltaic module string arrangement determination method, device and electronic equipment, the method comprising: constructing a network node graph and an adjacency matrix of the photovoltaic module according to the arrangement of the photovoltaic module and the inverter in the installation area; determining the shortest string path of the photovoltaic module in series according to the network node graph and the adjacency matrix, combined with a preset path search algorithm; dividing the shortest string path according to the target component number contained in each photovoltaic module string to determine the string arrangement mode of the photovoltaic module and the inverter. By using the method, the arrangement of the photovoltaic module and the inverter is comprehensively considered, the photovoltaic module square matrix is converted into a network node graph and an adjacency matrix for graph theory research, the shortest string path is determined based on the minimum spanning tree principle of the graph in graph theory, and then it is divided, thereby realizing the optimal string effect of the photovoltaic module and the inverter, which is not affected by obstacles and saves the cable cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic modules, in particular to a photovoltaic module string arrangement determination method and device and electronic equipment. BACKGROUND

[0002] The basic power generation unit of a photovoltaic power station is a photovoltaic module. When a photovoltaic power station is constructed, the photovoltaic modules need to be connected into strings, and then connected with inverters. With the development of photovoltaic power station business, intelligent photovoltaic module string arrangement design is needed to meet different photovoltaic power station scenarios. Existing photovoltaic module string optimization methods include C string priority algorithm and irregular string optimization algorithm based on certain four-neighbor rules.

[0003] However, the number of module strings is a multi-objective optimization problem, and the current algorithm still has some problems in application: the current algorithm takes the module as the starting point, and after all the modules are connected into strings, the starting point of each string is connected to the inverter. The connection line from each string starting point to the inverter accounts for about 80% of the total cable consumption of the power station. This stringing mode that does not consider the inverter and then calculates the cable to the inverter is obviously unreasonable. In addition, when there are multiple obstacles, there may be no path result, and the entire power station scenario cannot be covered. Moreover, the stringing path given by the current algorithm cannot guarantee to be the optimal stringing path due to the rule limitation. SUMMARY

[0004] The embodiments of the present application provide a photovoltaic module string arrangement determination method and device and electronic equipment to realize unified processing of installation areas of different area types and obtain the optimal solution of stringing in a complex installation area in a short time.

[0005] In a first aspect, the embodiments of the present application provide a photovoltaic module string arrangement determination method, which includes:

[0006] According to the arrangement of the photovoltaic modules and the inverters in the installation area, a network node graph and an adjacency matrix of the photovoltaic modules are constructed;

[0007] According to the network node graph and the adjacency matrix, a preset path search algorithm is combined to determine the shortest stringing path of the photovoltaic modules.

[0008] According to the number of target modules contained in each photovoltaic module string, the shortest stringing path is divided to determine the stringing arrangement mode of the photovoltaic modules and the inverters.

[0009] In a second aspect, the embodiments of the present application provide a photovoltaic module string arrangement determination device, which includes:

[0010] The constructing module is configured to construct a network node graph and an adjacency matrix of the photovoltaic components according to arrangement of the photovoltaic components and the inverters in the installation area;

[0011] The path determining module is configured to determine a shortest string line path of the photovoltaic components in series according to the adjacency matrix and a preset path search algorithm.

[0012] The arrangement determining module is configured to divide the shortest string line path according to a target component number contained in each photovoltaic component string, and determine a string line arrangement mode of the photovoltaic components and the inverters.

[0013] In a third aspect, the present embodiment provides an electronic device, which comprises:

[0014] at least one processor; and

[0015] a memory in communication with the at least one processor; wherein

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the photovoltaic component string line arrangement determination method according to any one of the embodiments of the present application.

[0017] The present embodiment provides a photovoltaic component string line arrangement determination method, device and electronic device. The method comprises: constructing a network node graph and an adjacency matrix of the photovoltaic components according to arrangement of the photovoltaic components and the inverters in the installation area; determining a shortest string line path of the photovoltaic components in series according to the network node graph and the adjacency matrix and a preset path search algorithm; and dividing the shortest string line path according to a target component number contained in each photovoltaic component string, and determining a string line arrangement mode of the photovoltaic components and the inverters. The above technical solution comprehensively considers the arrangement of the photovoltaic components and the inverters, converts the photovoltaic component square matrix into a network node graph and an adjacency matrix for graph theory research, determines the shortest string line path based on the minimum spanning tree principle of the graph in graph theory, and divides the shortest string line path to obtain the string line arrangement mode of the photovoltaic components. Compared with the prior art, the present technical solution considers the connecting cable of the inverters and the photovoltaic components, and is not affected by obstacles in the installation area and is not limited by string line rules, thereby achieving optimal string line effect of the photovoltaic components and the inverters and saving cable cost.

[0018] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiments description. Obviously, the drawings described in the following are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0020] Figure 1 A flowchart of a method for determining string line arrangement of a photovoltaic module provided in Embodiment One of the present application is shown in the figure.

[0021] Figure 2 An eight-neighbor structure example of a photovoltaic module provided in Embodiment One of the present application is shown in the figure.

[0022] Figure 3 An eight-neighbor structure construction example of a certain photovoltaic module provided in Embodiment One of the present application is shown in the figure.

[0023] Figure 4 A flowchart of another method for determining string line arrangement of a photovoltaic module provided in Embodiment Two of the present application is shown in the figure.

[0024] Figure 5 A conversion example from a square matrix of a photovoltaic module to a network node graph provided in Embodiment Two of the present application is shown in the figure.

[0025] Figure 6 A conversion example from a network node graph to a neighborhood matrix provided in Embodiment Two of the present application is shown in the figure.

[0026] Figure 7 A path example generated based on an algorithm provided in Embodiment Two of the present application is shown in the figure.

[0027] Figure 8 A structure schematic diagram of a device for determining string line arrangement of a photovoltaic module provided in Embodiment Three of the present application is shown in the figure.

[0028] Figure 9 A structure schematic diagram of an electronic device provided in Embodiment Four of the present application is shown in the figure. DETAILED DESCRIPTION

[0029] In order to make the person skilled in the art better understand the present application, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort should belong to the protection scope of the present application.

[0030] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting, unless the contrary is indicated. For example, the description and drawings are not meant to restrict the position of the elements presented therein to the precise relationships and relative arrangements shown and described. Furthermore, examples of the processes and methods described herein can include more, fewer, or other steps. For brevity, common data manipulation techniques, such as buffering, caching, etc., can not be shown in the figures. It will be appreciated that data used in the description and figures is for illustrative purposes only and is not intended to limit the scope of the application. It is to be understood that the use of certain terms include some flexibility and that not all embodiments utilize all the recited features. For example, the term "comprising" is used herein to mean including the elements following the term, but not to the exclusion of additional elements. Further, the term "comprising" is used to include some embodiments and not to exclude others. For example, a process, method, system, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but can include other elements not expressly listed or inherent to such process, method, system, article, or apparatus. Further, unless otherwise specified, terms of approximation, such as "substantially", "approximately", and the like, include that a description is within a reasonable range of values.

[0031] In the prior art, the string line optimization mode of the photovoltaic module has a C string priority algorithm, a rule-based exhaustive optimization string line algorithm, and a string line algorithm based on mapping of a photovoltaic module square matrix to a digital square matrix. Considering that the number of module strings is a multi-objective optimization problem, the current string line optimization mode still has certain problems in application: the current string line mode is to take the photovoltaic module as a starting point, and after all the photovoltaic modules are connected, the starting point of each string is connected to the inverter. The connection line from each string starting point to the inverter accounts for about 80% of the total cable consumption of the power station. This string line mode does not consider the inverter, and finally calculates the cable to the inverter, which is obviously unreasonable. The current string line mode is to take a fixed number of strings, such as {14, 15, 16} in a fixed order. The first string must be 14 modules. Moving the position of a module in the string line will affect the result of the entire string line. This order limits the selection of the optimal solution. Due to the limitation of multiple rules (such as two modules with an obstacle in between, the two photovoltaic modules cannot be connected, and the rules of non-continuous line change), when there are multiple obstacles in the installation area, there will be no result. Due to too many rule limitations, the optimal path may be missed, so the result cannot be guaranteed to be optimal. The current string line mode is limited to a single square matrix for processing of horizontal row modules. When multiple roof square matrices have horizontal rows, the existing algorithm cannot handle it. In addition, the string line mode based on the mapping of the module to the digital square matrix completely depends on the mapping of the module to the digital square matrix, and has poor flexibility and is not easy to expand.

[0032] In view of the above problems, the embodiment provides a photovoltaic module string line arrangement determination method.

[0033] Embodiment one

[0034] Figure 1A flowchart of a photovoltaic module string line arrangement determination method provided by Embodiment One of the present application is shown in the figure. The method can be applied to the arrangement of photovoltaic modules in strings. The method can be executed by a photovoltaic module string line arrangement determination device, which can be realized in the form of hardware and / or software and is generally integrated in an electronic device.

[0035] As shown in Figure 1 , the photovoltaic module string line arrangement determination method provided by Embodiment One can specifically include the following steps:

[0036] S101. Construct a network node graph and an adjacency matrix of the photovoltaic modules according to the arrangement of the photovoltaic modules and the inverters in the installation area.

[0037] In this embodiment, the arrangement of the photovoltaic modules and the inverters is converted into a network node graph based on the principles of graph theory, with the network node graph as the research object. The network node graph can be understood as a weighted undirected graph, in which each photovoltaic module is a node of the graph, each photovoltaic module that can be directly connected to the current node is a connected node of the current node, and the distance between the current node and the connected node can be used as the weight. Preferably, the components in the eight-neighborhood of the photovoltaic module are used as the components directly connected to the photovoltaic module. In this step, the position coordinates of the photovoltaic module arrangement and the position coordinates of the inverters can be obtained, and the eight-neighborhood connection point structure of the component coordinates can be constructed according to the position coordinates of the photovoltaic modules and the position coordinates of the inverters. Further, the network node graph of the photovoltaic modules can be constructed according to the eight-neighborhood connection point structure of the components.

[0038] It can be understood that, in this embodiment, the arrangement type of the components or the type of the roof in the household power station is not dependent, and whether it is a household roof photovoltaic power station or a large-scale photovoltaic power station, only the coordinates of each component and the placement position coordinates of the inverters are needed to determine the network node graph of the photovoltaic modules. Specifically, each photovoltaic module is sequentially taken as the current photovoltaic module, and the connectable points from the current component to the next component are found in eight directions according to the position coordinates of the photovoltaic modules. The connectivity between the nodes in the graph is constructed through the eight-neighborhood connection points of each component. Among them, the nodes within the neighborhood of the node indicate that the node can be connected to the current node, that is, in the graph, it can be represented as two nodes that can be connected; the nodes not within the neighborhood of the node indicate that the node cannot be directly connected to the current node, that is, in the graph, it can be represented as two nodes that cannot be connected. The weight between two nodes represents the actual distance between each two connected components.

[0039] In order to more clearly describe the eight-neighborhood structure of the photovoltaic modules, an exemplary Figure 2 eight-neighborhood structure of the photovoltaic modules provided by Embodiment One of the present application is shown in the figure. As shown in Figure 2As shown, assuming P is the current photovoltaic module, P(x, y) represents the coordinates of the current photovoltaic module, P1-P8 represents the eight neighborhood structure of the current photovoltaic module P, and L1-L8 represents the actual distance from the center point of each module in the eight neighborhood structure to the center point of the current module. It can be clearly seen that P1-P8 represents the possible situation of the current photovoltaic module connected to the next module, and the module in the neighborhood indicates that it can be connected, and the point not in the neighborhood indicates that it cannot be connected.

[0040] In order to better explain the construction rule of the eight neighborhood, taking the construction of the eight neighborhood of a certain photovoltaic module as an example for illustration. Exemplarily, Figure 3 The eight neighborhood construction example of a certain photovoltaic module provided by the embodiment one of the present application is shown in the figure. It can be understood that when actually constructing the eight neighborhood of the photovoltaic module square, the position coordinates of the photovoltaic module can be judged, and numbering is not required. In this example, each photovoltaic module is numbered for more convenient expression. In this example, each photovoltaic module is numbered to represent each photovoltaic module. The module square in the figure includes photovoltaic modules P1-P45, and the inverter connected in parallel with the photovoltaic module is numbered 0. In this example, the construction rule is illustrated by taking the neighborhood situation of different photovoltaic modules as an example, and the different photovoltaic module situations include: no obstacle in eight directions, obstacle in the lower left corner, obstacle in the front, obstacle in the lower right, obstacle in the left, obstacle in the right, obstacle in the upper left corner, obstacle in the front, and obstacle in the upper right.

[0041] Continuing to refer to Figure 3 As shown in the figure, the hatched part indicates that there is an obstacle, and the overall construction rule of the photovoltaic module can be expressed as:

[0042] 1) If there is no obstacle in eight directions, such as Figure 3 the module numbered 23 in the middle, the modules in the eight neighborhood are all available, which can be represented as {P1, P2, P3, P4, P5, P6, P7, P8} = {13, 14, 15, 22, 24, 33, 34, 35};

[0043] 2) If the lower left corner P1 is an obstacle, then search to the left along the row where P1 is located until a module is found or the edge of the square is reached, such as Figure 3 the neighborhood P1 of module 26 in the middle is module number 15, and the neighborhood P1 of module 10 does not exist;

[0044] 3) If the front P2 is an obstacle, then continue to search downward along the vertical direction until a module is found or the edge of the square is reached. For example, Figure 3 the neighborhood P2 of module 31 in the middle is module 11, and by analogy, the neighborhood P2 of module 13 does not exist;

[0045] 4) If the lower right P3 is an obstacle, search right along the row of P3 until a component is found or the edge of the square is reached. As shown in Figure 3 The neighborhood P3 of component 16 is component 8, and the neighborhood P3 of component 43 does not exist;

[0046] 5) If the left P4 is an obstacle, search left along the row of P3 until a component is found or the edge of the square is reached. As shown in Figure 3 The neighborhood P4 of component 21 is component 20, and the neighborhood P4 of component 38 does not exist;

[0047] 6) If the right P5 is an obstacle, search right along the row of P5 until a component is found or the edge of the square is reached. As shown in Figure 3 The neighborhood P5 of component 20 is component 21, and the neighborhood P5 of component 37 does not exist;

[0048] 7) If the upper left corner P6 is an obstacle, search left along the row of P6 until a component is found or the edge of the square is reached. As shown in Figure 3 The neighborhood P6 of component 33 is component 39, and the neighborhood P6 of component 30 does not exist;

[0049] 8) If the directly above P7 is an obstacle, continue to search upward along the vertical direction until a component is found or the edge of the square is reached, as shown in Figure 3 The neighborhood P7 of component 11 is component 31, and the neighborhood P7 of component 35 does not exist;

[0050] 9) If the upper right P8 is an obstacle, search right along the row of P8 until a component is found or the edge of the square is reached. As shown in Figure 3 The neighborhood P8 of component number 34 is component 42, and the neighborhood P8 of component 26 does not exist.

[0051] In this embodiment, the eight-neighborhood structure of the inverter is specially processed. Considering that the position of the inverter is often outside the edge of the component arrangement square, unlike the component square, a connection relationship with other components can be established from eight directions; from a practical point of view, every photovoltaic component string, regardless of the position of the first and last component, will eventually be connected in parallel to the inverter. Therefore, in this embodiment, the inverter is taken as the starting point of the algorithm. It is stipulated that the components that can be directly connected to the inverter in the square are taken as the neighborhood points of the inverter. As shown in Figure 3 The inverter is on the right side, and the photovoltaic component numbers that can be directly connected to the inverter are 8, 18, 28, 37, and 45, that is, the neighborhood components of the inverter are components {8, 18, 28, 37, 45}.

[0052] It can be understood that after the neighborhood component graph of the photovoltaic component square array is constructed, each photovoltaic component can be taken as a node of the network node graph. The connection between each component and the components in the eight neighborhood is taken as an edge of the network node graph. According to the coordinates of the photovoltaic components, the distance between each component and the components in the eight neighborhood can be determined as the weight of the edge.

[0053] wherein the adjacency matrix represents the matrix of the adjacent relationship between the vertices, and is a conversion form of the graph to the matrix, facilitating the storage of the graph. It is assumed that the network node graph is represented by G=(V, E), V represents the set of all vertices of the graph, E represents the set of all edges of the graph, (u, v) represents the edge connecting the vertex u and the vertex v, and w(u, v) represents the weight of the edge. The weight of the edge between the nodes is stored in a two-dimensional array, which is called the adjacency matrix.

[0054] S102, according to the network node graph and the adjacency matrix, and in combination with a preset path search algorithm, the shortest string path of the series photovoltaic components is determined.

[0055] In the embodiment, the path search algorithm can be understood as a minimum spanning tree algorithm based on the rule restriction, which is designed based on the minimum spanning tree principle of the graph in the graph theory and in the background of the photovoltaic component string rule. The minimum spanning tree is the shortest string path required to connect all nodes. The purpose of this step is to specify a starting point, and the sum of the weights of the edges connecting all nodes from the starting point is the minimum. It can be understood that the weight of the edge of the node represents the distance between the two nodes, so the shortest string path of the series photovoltaic components can be determined when the sum of the weights of the edges is determined. It needs to be clear that the shortest string path should include all photovoltaic components. In the embodiment, the minimum spanning tree generated by the graph determines the minimum sum of the weights of the edges connecting all nodes, that is, the least cable generated by connecting all components, and determines the globally optimal solution.

[0056] wherein the minimum spanning tree algorithm can be expressed as: 10) input: the weighted undirected graph is represented by G=(V, E), V represents the set of all vertices of the graph, and E represents the set of all edges of the graph; 20) initialization: set a vertex set S and an edge set TE, and the initial states of S and TE are both empty sets; 30) repeat the following operations until the vertex set S is equal to V, and the repeating operations include 31) selecting the edge with the minimum weight in the set E, wherein u is an element in the vertex set S, and v is not in the set S, and v∈V; 32) adding v to the set S and adding the edge to the set TE; 40) output: the minimum spanning tree, that is, the shortest string path, is described by using the vertex set S and the edge set TE.

[0057] In the present embodiment, when selecting the minimum edge with weight in step 33), the rules that the photovoltaic module arrangement must follow, such as the positive and negative connections of the photovoltaic modules, need to be considered. It is necessary to know that, since each photovoltaic string needs to be connected in parallel to the inverter, in the present embodiment, the connection cable between the inverter and the photovoltaic modules is calculated from the node corresponding to the inverter as the starting point.

[0058] S103, according to the target number of modules contained in each photovoltaic string, the shortest string line path is divided to determine the string line arrangement mode of the photovoltaic modules and the inverter.

[0059] In the photovoltaic module string line, it is often composed of multiple strings, and each photovoltaic string contains a set number of modules, which is referred to as the target number of modules in the present embodiment. For example, the target number of modules of three photovoltaic strings can be represented as route = {14, 15, 16}. It can be understood that not all photovoltaic modules are connected by a path, but each photovoltaic string is continuous. It can be understood that each photovoltaic string is connected in parallel to the inverter. That is, the starting point (or tail point) of the previous string is in the neighborhood of the starting point (or tail point) of the next string, that is, we can divide the large path into small paths of a specified length by cutting the minimum string line path.

[0060] In the present embodiment, the neighborhood point of the inverter is preferred as the cutting point in the module cutting. The reason is that each cutting point will generate a string starting point and a tail point, and both points will eventually be connected in parallel to the inverter. The neighborhood point of the inverter is the node closest to the inverter, which ensures the shortest parallel distance. And under the premise that the neighborhood point of the inverter does not meet the conditions, the trial-and-error method is used to ensure that each cutting point is as close to the inverter as possible to reduce the cable cost generated by parallel connection to the inverter. Taking the inverter as the reference point, the trial-and-error method is used to preferentially select the cutting point from the module close to the inverter to realize the cutting of the generated tree to the string line path. It is ensured that each path cut is in line with the string line rules, and the starting point formed by the cutting point is as close to the inverter as possible to save the cable.

[0061] The embodiment of the present application provides a kind of photovoltaic module string line arrangement determination method, this method includes: according to the arrangement of photovoltaic module and inverter in installation area, the network node graph and adjacency matrix of the photovoltaic module are constructed;According to the network node graph and the adjacency matrix, the shortest string line path of the photovoltaic module in series is determined in combination with preset path search algorithm;According to the target component number contained by each photovoltaic module string, the shortest string line path is divided, and the string line arrangement mode of the photovoltaic module and the inverter is determined.Utilize this method, the arrangement of photovoltaic module and inverter is considered comprehensively, photovoltaic module square matrix is converted into network node graph and adjacency matrix of graph theory research, based on the minimum spanning tree principle of graph in graph theory, the shortest string line path is determined, and then it is divided to obtain photovoltaic module string line arrangement mode.Compared with the process of determining string line mode in prior art, inverter is not considered, and finally calculated to inverter cable leads to that string line effect is not necessarily optimal.The technical scheme considers the connecting cable of inverter and photovoltaic module, and is not affected by obstacle in installation area and limited by stringing rule, realizes the optimal stringing effect of photovoltaic module and inverter, and saves cable cost.

[0062] Embodiment two

[0063] Figure 4 The flowchart of another photovoltaic module string line arrangement determination method provided by the second embodiment of the present application is based on the above-mentioned embodiment, in this embodiment, according to the arrangement of photovoltaic module and inverter in installation area, the network node graph and adjacency matrix of the photovoltaic module can be constructed, which can be specifically expressed as: according to the arrangement of the photovoltaic module and the inverter in the installation area, the neighborhood components in the eight neighborhoods of each photovoltaic module and the inverter are determined respectively; according to the neighborhood components, the network node graph of the photovoltaic module is constructed; the network node graph is converted into the adjacency matrix of the photovoltaic module.

[0064] Meanwhile, the embodiment can also be specifically expressed as: the shortest string line path of the photovoltaic module in series is determined in combination with preset path search algorithm according to the network node graph and the adjacency matrix, which can be specifically expressed as: the node corresponding to the inverter in the network node graph is taken as the starting point of the shortest string line path, and is added to the vertex set; the node corresponding to each photovoltaic module in the network node graph is sequentially obtained as the current node; the target node connected to the current node is determined according to the adjacency matrix; the target node is added to the vertex set and the edge between the current node and the target node is added to the edge set; the shortest string line path of the photovoltaic module in series is determined according to the addition order of the target node.

[0065] And, the embodiment can also divide the shortest string line path according to the target component number contained in each photovoltaic string, to determine the string line arrangement mode of the photovoltaic component and the inverter, which is specifically expressed as: determining a target segmentation point of the shortest string line path according to the neighborhood nodes of the inverter corresponding node; cutting the shortest string line path according to the target segmentation point to obtain a target string line path cut off; taking the shortest string line path remaining after cutting as a new shortest string line path, and returning to continue the determination step of the target segmentation point until the shortest string line path is cut into a mode matching the photovoltaic string; and obtaining the string line arrangement mode of the photovoltaic component and the inverter according to each target string line path.

[0066] As shown in Figure 4 The embodiment two of the present application provides a photovoltaic component string line arrangement determination method, which specifically includes the following steps:

[0067] S201, according to the arrangement of the photovoltaic component and the inverter in the installation area, the neighborhood components in the eight neighborhoods of each photovoltaic component and the inverter are determined respectively.

[0068] Among them, the neighborhood components in the eight neighborhoods of the photovoltaic component refer to the eight components on the upper, lower, left, right and two diagonal lines of the current photovoltaic component. According to the photovoltaic component coordinates, the connecting point from the current component to the next component is found from eight directions of each component. It can be understood that this step does not depend on the component arrangement type or the roof type in the household power station. Whether it is a household roof photovoltaic power station or a large photovoltaic power station, only the coordinates of each component and the placement position coordinates of the inverter are needed.

[0069] In this embodiment, the photovoltaic component and the inverter can be represented by the center point position coordinates, and each photovoltaic component corresponds to a unique position coordinate. For the photovoltaic component, it can be determined whether there is a component in the eight neighborhoods of the current photovoltaic component from eight directions, and if there is, it is determined that the component is the neighborhood component of the current photovoltaic component. In turn, each photovoltaic component in the photovoltaic component square matrix is taken as the current photovoltaic component, and the components in the eight neighborhoods of each current photovoltaic component are determined, and finally the neighborhood components in the eight neighborhoods of each photovoltaic component in the photovoltaic component square matrix are determined. For the inverter, considering that the position of the inverter is often outside the edge of the component arrangement square matrix, which is different from the component square matrix, the connection relationship with other components can be established from eight directions; from the actual point of view, each string group, regardless of the position of the first and last component, will finally be connected in parallel to the inverter. Therefore, in this embodiment, the inverter is taken as the starting point of the algorithm. Therefore, the photovoltaic components that can be directly connected to the inverter in the photovoltaic component square matrix are defined as the neighborhood components of the inverter.

[0070] S202, according to the neighborhood components, a network node graph of the photovoltaic component is constructed.

[0071] In this step, each photovoltaic module in the photovoltaic module square array is taken as a node of a network node graph. According to the neighborhood modules determined in the above step, if each photovoltaic module is taken as a current photovoltaic module, the connection relationship and distance between the current photovoltaic module and the neighborhood modules of the current photovoltaic module can be determined. It can be understood that the eight neighborhood modules of a photovoltaic module represent the possible connection of the current photovoltaic module to the next module. The photovoltaic module can be directly connected to the neighborhood modules of the photovoltaic module, and the photovoltaic module cannot be directly connected to the modules other than the eight neighborhood modules of the photovoltaic module.

[0072] Specifically, each photovoltaic module is taken as a node of a network node graph, and a network node graph of the photovoltaic module is constructed according to the connection relationship and distance between the photovoltaic modules.

[0073] Further, the network node graph of the photovoltaic module is constructed according to the neighborhood modules, comprising:

[0074] a1) determining the distance from each photovoltaic module and the inverter to the corresponding neighborhood modules.

[0075] Specifically, according to the position coordinates of the photovoltaic modules and the position coordinates of the inverter, the distance between the photovoltaic modules and the neighborhood modules of the photovoltaic modules, and the distance between the inverter and the corresponding neighborhood modules can be determined.

[0076] For example, continuing to refer to Figure 3 , the inverter is on the right side, and the modules directly connected to the inverter are numbered 8, 18, 28, 37, and 45, that is, the neighborhood modules of the inverter are {8, 18, 28, 37, 45}, and the distance from the position of the inverter to the neighborhood modules is calculated. The distance from the center point of each module to the center point of each module in the eight neighborhood structure is calculated, such as the module numbered 23, the eight neighborhood structure is {P1, P2, P3, P4, P5, P6, P7, P8} = {13, 14, 15, 22, 24, 33, 34, 35}, and L1-L8 represents the actual distance from module 23 to modules 13, 14, 15, 22, 24, 33, 34, and 35, respectively. The eight neighborhood of the module numbered 18 is only five, which is represented as {P1, P2, P4, P6, P7} = {7, 8, 17, 27, 28}, and L1, L2, L4, L6, and L7 represent the actual distance from module 18 to modules 7, 8, 17, 27, and 28, respectively.

[0077] b1) constructing a network node graph of the photovoltaic module by taking each photovoltaic module as a node, taking the connection between each photovoltaic module and the corresponding neighborhood modules of the inverter as an edge, and taking each distance as the weight of each edge.

[0078] Specifically, the photovoltaic components and the adjacent components of the photovoltaic components can be directly connected, and the inverters and the adjacent components of the inverters can be directly connected. Therefore, the connection relationship between the photovoltaic components and the inverters can be determined. The photovoltaic components are taken as nodes of a network node graph, the connection lines between the photovoltaic components and the adjacent components of the photovoltaic components and the inverters are taken as edges of the network node graph, and the distances between the photovoltaic components and the adjacent components of the photovoltaic components and the inverters are taken as weights of the corresponding edges in the network node graph.

[0079] The graph converted from the component square matrix is a weighted undirected graph, and the neighborhood of the component is represented as the connectivity between the nodes in the graph. The nodes that are not connected cannot be directly connected, that is, the components that are not in the neighborhood of the component cannot be directly connected. Exemplarily, Figure 5 The conversion example of the photovoltaic component square matrix to the network node graph is provided for the second embodiment of the present application. The inverters are on the left side of the photovoltaic component square matrix, in which the inverters are numbered as 0, and the photovoltaic components are sequentially numbered as 1, 2, 3, 4, 5 and 6. The distance between the components is represented by Lij in the graph, and i and j represent the node numbers, such as L54, which represents the distance between the center point of the component numbered as 5 (or 4) and the center point of the component numbered as 4 (or 5) in the component square matrix. L54 represents the weight of the node 5 (or 4) to the node 4 (or 5) in the graph;

[0080] It can be seen that the inverter 0 can be directly connected with the photovoltaic components 1 and 4, and the weights of the edges of the two nodes are represented as L10 and L40, respectively. The photovoltaic component 1 can be directly connected with the photovoltaic components 2, 4 and 5, and the weights of the edges of each two nodes are represented as L21, L41 and L51, respectively. The photovoltaic component 2 can be directly connected with the photovoltaic components 1, 3, 4, 5 and 6, and the weights of the edges of each two nodes are represented as L21, L32, L42, L52 and L62, respectively. The connection and the weight of the remaining components are not listed one by one.

[0081] S203, converting the network node graph into an adjacency matrix of the photovoltaic components.

[0082] The adjacency matrix represents the adjacent relationship between the nodes, and is a conversion form of the graph to the matrix, which is convenient for the storage of the graph. It is assumed that the network node graph is represented by G=(V, E), V represents the set of all vertices of the graph, E represents the set of all edges of the graph, (u, v) represents the edge connecting the vertex u and the vertex v, and w(u, v) represents the weight of the edge. The weight of the edge between the nodes is stored in a two-dimensional array, which is called an adjacency matrix.

[0083] Further, the conversion of the network node graph into the adjacency matrix of the photovoltaic components comprises:

[0084] a2) constructing an initial two-dimensional array according to the nodes contained in the network node graph.

[0085] Specifically, according to the nodes contained in the network node graph, an initial two-dimensional array is constructed, and each element in the initial two-dimensional array can be set as "inf" representing infinity, that is, two nodes are not connected.

[0086] b2) adding the weight in the network node graph as a matrix element to the corresponding position of the initial two-dimensional array to determine the adjacency matrix of the photovoltaic module.

[0087] In this step, the value in the adjacency matrix represents the weight between each two nodes. The weight in the network node graph is added as a matrix element to the corresponding position of the initial two-dimensional array to determine the adjacency matrix of the photovoltaic module, wherein "0" represents the distance of a node to itself, and "inf" represents infinity, that is, two nodes are not connected. The weight in the network node graph is added as a matrix element to the corresponding position of the initial two-dimensional array to determine the adjacency matrix of the photovoltaic module. Exemplarily, Figure 6 The conversion example diagram of the network node graph to the neighborhood matrix provided in the second embodiment of the present application is shown in the figure. The first column (row) represents that the neighborhood components corresponding to the component number 1 are numbered as {0, 2, 4, 5}, and the distances to each component node are represented as {L10, L21, L41, L51}, and the distances to each component node are represented as {L10, L21, L41, L51}. For other components, they are not listed one by one here.

[0088] S204, the inverter corresponding node in the network node graph is taken as the starting point of the shortest string line path, and is added to the vertex set.

[0089] The vertex set is used to store the connection nodes determined in sequence. Considering that the photovoltaic strings need to be connected in parallel to the inverters, the cable between the photovoltaic components and the inverters is calculated into the bus cable in this embodiment. Specifically, a vertex set S and an edge set TE are set, and the initial states of S and TE are empty sets. The inverter position node "0" is selected as the starting point, and "0" is added to the set S. That is, the inverter corresponding node in the network node graph is taken as the starting point of the shortest string line path, and is added to the vertex set. It can be understood that the position of the inverter is added as the starting point of the graph search, and the component nodes connected with the inverter nodes are specially processed to ensure the rationality.

[0090] S205, the photovoltaic component corresponding node in the network node graph is taken as the current node.

[0091] Specifically, the photovoltaic component corresponding node in the network node graph is taken as the current node, that is, the network node is taken as the current node from all vertex sets V of the graph in sequence.

[0092] S206, the target node connected with the current node is determined according to the adjacency matrix.

[0093] The embodiment defines a starting point, and the sum of the weights of the edges connecting all nodes from the starting point is the minimum to determine the shortest string path. The target node can be understood as the next node that the current node should be connected to with the minimum weight. Specifically, according to the elements in the adjacency matrix and the rules of the photovoltaic module string itself, the target node connected by the current node is determined. It can be understood that when all the nodes in the network node graph are sequentially added to the vertex set, the process ends.

[0094] Further, according to the adjacency matrix, the target node connected by the current node is determined, including:

[0095] a3) arranging the neighborhood nodes of the current node in ascending order of weight to obtain a neighborhood node sequence of the current node.

[0096] Specifically, each node in the neighborhood of the current node is sorted in ascending order of weight to obtain a neighborhood node sequence of the current node.

[0097] b3) taking the neighborhood node with the minimum weight in the neighborhood node sequence as the current neighborhood node.

[0098] For example, assuming that the current node is represented as A, and X represents the neighborhood node with the minimum weight, starting from the first edge (A, X) in the sorting, the node X is taken as the current neighborhood node.

[0099] c3) judging whether the current neighborhood node satisfies the set node connection condition according to the adjacency matrix.

[0100] The node connection condition in this step can be represented as:

[0101] c31) requiring A to be an element of the vertex set S, and X not to be an element of the vertex set S;

[0102] c32) if the current node A is the first element of a certain row appearing in the vertex set S, and there are more than two nodes in the same row before the node A, assuming that the two nodes are B and C, then:

[0103] If the connection mode of B and C is B→C, i.e., to the right, and the node A and the nodes B and C differ by an even number of rows, then it is required that X is a node other than the neighborhood node P5 of A, i.e., X∈{P1, P2, P3, P4, P6, P7, P8}; if the node A and the nodes B and C differ by an odd number of rows, then it is required that X is a node other than the neighborhood node P4 of A, i.e., X∈{P1, P2, P3, P5, P6, P7, P8}.

[0104] If the connection of B and C is B←C, i.e. to the left, if node A and node BC are different by even rows, it is required that X is a node other than the adjacent node P4 of A, i.e. X∈{P1, P2, P3, P5, P6, P7, P8}, if node A and node BC are different by odd rows, it is required that X is a node other than the adjacent node P5 of A, i.e. X∈{P1, P2, P3, P4, P6, P7, P8}.

[0105] It should be noted that the connection of the photovoltaic module in this step needs to consider the positive and negative poles of the photovoltaic module itself, for example, the positive and negative poles of the adjacent two rows of photovoltaic modules are arranged in opposite directions.

[0106] d3) If yes, the current adjacent node is determined as the target node connected by the current node.

[0107] Specifically, if the current adjacent node meets the set node connection condition, the current adjacent node is determined as the target node connected by the current node.

[0108] e3) Otherwise, the next adjacent node of the current adjacent node is obtained from the adjacent node sequence as a new current adjacent node, and the judgment step of whether the set node connection condition is met is returned to continue execution until the adjacent nodes in the adjacent node sequence are all traversed.

[0109] Specifically, if the current adjacent node does not meet the set node connection condition, the next adjacent node of the current adjacent node is obtained from the adjacent node sequence as a new current adjacent node, and the step c3) is returned to continue execution of the judgment of whether the current adjacent node meets the set node connection condition, until the adjacent nodes in the adjacent node sequence are all traversed. For example, if the edge (A, X) does not meet the above condition, it is continued to judge whether the next edge in the sequence meets the condition.

[0110] Optionally, the method further comprises: if the current node has no target node to be connected, obtaining the previous node of the current node from the node set as a new current node, and re-determining the target node connected by the current node. Specifically, if the current node cannot determine the next target node to be connected, the previous node of the current node is obtained from the node set as a new current node, and the target node connected by the current node is re-determined based on the above determination method of the target node.

[0111] For example, continuing the above example, if none of the nodes in the neighborhood of A satisfy the above conditions, then back off the A node to the last node in the set S. Assume that the last node of A in the path in the set S is N, then the A node is a neighborhood node of the N node. The current node is reselected as N, the next node of N is rejudged, N is updated as the current neighborhood node, and the execution of the judgment of whether the current neighborhood node A satisfies the set node connection condition is returned. It can be understood that the next node of N in the set S is A, but when A finds the next node, there is no node satisfying the condition, which means that this path is not available, i.e., the next connection point of N is reselected.

[0112] S207, adding the target node to the vertex set and adding the edge between the current node and the target node to the edge set.

[0113] Specifically, each time a target node is determined, the target node can be added to the vertex set, and the edge between the current node and the target node is added to the edge set. For example, if the target node is determined to be X, the node X is added to the vertex set S, and the edge (A, X) is added to the set TE. When the last target node is determined, the edge from the last node to the corresponding node of the inverter is added to the edge set.

[0114] S208, determining the shortest string line path of the photovoltaic module according to the addition order of the target node.

[0115] Specifically, according to the determined target string line path, the connection relationship of each node in the target string line path can be obtained. The addition order of all target nodes in the vertex set is the connection order of the nodes, and the sum of all weights in the edge set is the minimum spanning tree of the graph generated within the algorithm rule range, i.e., the shortest string line path. For example, Figure 7 The shortest string line path of the path example graph generated based on the algorithm provided in the second embodiment of the present application is 0→1→2→3→4→5→6→0.

[0116] S209, determining the target segmentation point of the shortest string line path according to the neighborhood node of the corresponding node of the inverter.

[0117] The target segmentation point refers to the segmentation point of the shortest string line path to segment the photovoltaic string meeting the requirements.

[0118] In this embodiment, an entire path is obtained by the above steps, that is, a path in which all nodes are connected in series. However, in the component string, it is often composed of multiple groups, such as route={14, 15, 16}, which is not a path connecting all components, but each group string is continuous, that is, the starting point (or tail point) of the previous group string is in the neighborhood of the starting point (or tail point) of the next group string, that is, we can divide the large path into small paths of a specified length by cutting the shortest string path. Assume that the generated shortest string path is path, and path contains all components.

[0119] Considering the cable connected between the inverter and the starting point or terminal point of the photovoltaic group string, in order to make the cable as short as possible, the target segmentation point of the shortest string path is preferably determined according to the neighborhood node of the inverter corresponding node. For example, whether the neighborhood node meets the photovoltaic group string condition is judged as the segmentation point, or the node near the neighborhood node of the inverter corresponding node is taken as the segmentation point of the photovoltaic group string.

[0120] Further, the target segmentation point of the shortest string path is determined according to the neighborhood node of the inverter corresponding node, including:

[0121] a4) Taking the neighborhood node of the inverter corresponding node as the segmentation point.

[0122] Specifically, the neighborhood node of the inverter corresponding node is preferably taken as the segmentation point. The neighborhood node of the inverter is preferred in the component segmentation, because each segmentation point will generate a group string starting point and tail point, and the two points will be finally connected in parallel to the inverter, and the neighborhood node of the inverter is the node closest to the inverter, which ensures the shortest parallel distance.

[0123] b4) Judging whether the segmentation point is the target segmentation point of the shortest string path.

[0124] Specifically, whether the number of nodes contained in the string path determined according to the segmentation point meets the target component number contained in the set group string, that is, whether the segmentation point is the target segmentation point of the shortest string path can be judged.

[0125] Further, judging whether the segmentation point is the target segmentation point of the shortest string path, including:

[0126] b41) Taking the first segmentation point reached along the shortest string path from the starting point or terminal point of the shortest string path as the current segmentation point.

[0127] Specifically, the first segmentation point reached from the starting point (tail point) of the shortest string path is determined as the current segmentation point in this embodiment, which is not counted as the inverter corresponding node.

[0128] b42) determining the number of nodes contained in the string path from the start point or the end point to the current split point.

[0129] Specifically, the number of nodes contained in the string path from the start point or the end point to the current split point is calculated. It is assumed that the number of components in the path from the start point to the first split point is startNum, and the number of components determined by the end point is endNum.

[0130] b43) if the number of nodes is the target number of components, determining that the current split point is the target split point.

[0131] Specifically, if startNum or endNum is in the target number of components, the number of nodes is the target number of components, and the split point is determined as the target split point. Preferably, when startNum and endNum both belong to the target number of components, the split point determined by the start point is preferably the target split point.

[0132] b44) if the number of nodes is not the target number of components, determining that the current split point is not the target split point, and taking the next split point of the current split point as a new current split point, and continuing to execute the step of determining the number of nodes until each split point is traversed.

[0133] Specifically, if startNum or endNum is not in the target number of components, the number of nodes is not the target number of components, and the next split point of the current split point is taken as a new current split point, and the step of determining the number of nodes is continued until each split point is traversed. The target number of components is added to the number of nodes from the current split point to the next split point, and it is returned to step b42) to determine whether the number of nodes of the next split point meets the requirements. If it meets the requirements, the next split point is determined as the target split point. If it does not meet the requirements, the next split point is continued to be taken for judgment until each split point is traversed.

[0134] c4) if yes, obtaining the target split point.

[0135] Specifically, if the split point is the target split point of the shortest string path, the target split point is obtained.

[0136] d4) otherwise, determining the target split point of the shortest string path according to the minimum difference error method.

[0137] Specifically, if the split point is not the target split point of the shortest string path, the target split point of the shortest string path is determined according to the minimum difference error method, and the split point closest to the inverter is determined as the target split point of the shortest string path.

[0138] Further, the target split point of the shortest string path is determined according to the minimum difference error method, comprising:

[0139] d41) respectively determining the first number of nodes contained in the string path from the start point to the first split point and the second number of nodes contained in the string path from the end point to the first split point.

[0140] Specifically, the first node number represents the node number from the starting point to the first split point, that is, the number of components contained, and the second node number represents the node number from the ending point to the first split point, that is, the number of components contained.

[0141] d42) determining the minimum value of the difference between the first node number and the second node number and the node number contained in the string path corresponding to the minimum value.

[0142] Specifically, the first node number and the second node number are respectively subtracted from the target component number to obtain absolute values, the minimum value of the two absolute values is determined, and it is determined whether the minimum value corresponds to the starting point or the ending point. Assuming that the minimum value corresponds to the starting point, the first node number is used as the basis to perform the following steps. It can be understood that since there are multiple groups of strings, each group of strings corresponds to a target component number, and there are multiple target component numbers, any target component number can be selected to be subtracted from the first node number and the second node number.

[0143] d43) If the node number is greater than the target component number, the first initial split point is rolled back to the minimum number of nodes, and the rolled-back node is used as the target split point.

[0144] Specifically, if the node number is greater than the target component number, the minimum number of components is rolled back at the current split point as a cut point of a string path, and the node advanced to is used as the target split point.

[0145] d44) If the node number is less than the target component number, the first initial split point is advanced to the minimum number of nodes, and the node advanced to is used as the target split point.

[0146] Specifically, if the node number is less than the target component number, the minimum number of components is advanced at the current split point as a cut point of a string path, and the node advanced to is used as the target split point.

[0147] Under the premise that there is no point in the inverter neighborhood that meets the condition, the trial-and-error method is used to ensure that each cut point is as close to the inverter as possible to reduce the cable cost generated by the parallel inverters.

[0148] S210, cutting the shortest string path according to the target split point to obtain a target string path cut off.

[0149] Specifically, according to the target split point, the string path meeting the target number of strings is cut off, and the cut-off string path is used as the target string path.

[0150] S211, taking the remaining shortest string path after cutting as a new shortest string path, returning to continue the determination step of the target split point until the shortest string path is cut to match each photovoltaic string.

[0151] Specifically, when the target string line path is cut off, and the shortest string line path remaining after cutting is updated as a new shortest string line path, the step S209 is returned to continue the determination of the target segmentation point until the shortest string line path is cut into a target group string.

[0152] S212, according to each target string line path, obtaining the string line arrangement mode of the photovoltaic module and the inverter.

[0153] Specifically, according to the target string line path, the starting point, the ending point and the connection relationship of each node in the target string line path can be determined. The photovoltaic module corresponding to the starting point and the ending point is connected, and the corresponding photovoltaic module is connected according to the connection relationship of each node in the target string line path, and finally the string line arrangement mode of the photovoltaic module and the inverter is obtained.

[0154] In this embodiment, the eight-neighbor structure based on the position and distance of the photovoltaic module is refined, the relationship between each component is fully constructed, and the path output of the string line algorithm is ensured. The photovoltaic module arrangement square is converted into a network node graph, and the component square is stored in the adjacency matrix of the graph, without distinguishing the type of square, and the influence of the algorithm on the arrangement of the special-shaped roof component in the on-site roof is eliminated. In addition, in graph theory, there is no longer the concept of obstacle, and the influence of the obstacle or the special-shaped area on the algorithm is eliminated; at the same time, based on the minimum spanning tree algorithm, the overall string line optimization is ensured, and the preferred segmentation point is selected, and the algorithm is no longer affected by the order of the string, and the determination of the optimal string line path is realized.

[0155] Embodiment three

[0156] Figure 8 A structure diagram of a photovoltaic module string line arrangement determination device provided in the third embodiment of the present application can be applied to the string line arrangement of the photovoltaic module. The device can be realized in the form of hardware and / or software. As shown in the figure, the device comprises a construction module 31, a path determination module 32 and an arrangement determination module 33, wherein, Figure 8

[0157] The construction module 31 is used for constructing the network node graph and the adjacency matrix of the photovoltaic module according to the arrangement of the photovoltaic module and the inverter in the installation area.

[0158] The path determination module 32 is used for determining the shortest string line path of the series photovoltaic module according to the adjacency matrix and combining the preset path search algorithm.

[0159] The arrangement determination module 33 is used for dividing the shortest string line path according to the number of target components contained in each photovoltaic string, and determining the string line arrangement mode of the photovoltaic module and the inverter.

[0160] ​Optionally, the constructing module 31 can comprise:

[0161] a neighborhood component determining unit configured to determine neighborhood components in eight neighborhoods of each photovoltaic component and the inverter according to arrangement of the photovoltaic components and the inverter in the installation area;

[0162] a node graph determining unit configured to construct a network node graph of the photovoltaic components according to the neighborhood components;

[0163] a matrix determining unit configured to convert the network node graph into an adjacency matrix of the photovoltaic components.

[0164] Further, the node graph determining unit is specifically configured to:

[0165] determine distances from each photovoltaic component and the inverter to corresponding neighborhood components;

[0166] construct the network node graph of the photovoltaic components by taking each photovoltaic component as a node, a connection line from each photovoltaic component and the inverter to corresponding neighborhood components as an edge, and each distance as a weight of each edge.

[0167] Further, the matrix determining unit is specifically configured to:

[0168] construct an initial two-dimensional array according to nodes contained in the network node graph;

[0169] add weights in the network node graph to corresponding positions of the initial two-dimensional array as matrix elements to determine the adjacency matrix of the photovoltaic components.

[0170] Optionally, the path determining module 32 comprises:

[0171] a start point determining unit configured to take a node corresponding to the inverter in the network node graph as a start point of a shortest series path and add the start point to a vertex set;

[0172] a current node obtaining unit configured to sequentially obtain nodes corresponding to each photovoltaic component in the network node graph as a current node;

[0173] a target node determining unit configured to determine a target node connected to the current node according to the adjacency matrix;

[0174] a node adding unit configured to add the target node to the vertex set and add an edge between the current node and the target node to an edge set;

[0175] a path determining unit configured to determine the shortest series path of the photovoltaic components according to an adding sequence of the target node.

[0176] Optionally, the path determining module 32 further comprises a node re-determining unit, which is specifically configured to:

[0177] If the current node has no connected target node, the last node of the current node is obtained from the node set as a new current node, and the target node connected by the current node is re-determined.

[0178] Further, the target node determination unit is specifically configured to:

[0179] arranging the neighbor nodes of the current node in ascending order of weight to obtain a neighbor node sequence of the current node;

[0180] taking the neighbor node with the minimum weight in the neighbor node sequence as a current neighbor node;

[0181] determining whether the current neighbor node meets the set node connection condition according to the adjacency matrix;

[0182] If yes, the current neighbor node is determined as the target node connected by the current node.

[0183] Otherwise, the next neighbor node of the current neighbor node is obtained from the neighbor node sequence as a new current neighbor node, and the step of determining whether the current neighbor node meets the set node connection condition is returned to continue to be executed until all the neighbor nodes in the neighbor node sequence are traversed.

[0184] Optionally, the arrangement determination module 33 comprises:

[0185] The split point determination unit is configured to determine a target split point of the shortest string connection path according to the neighbor nodes of the inverter corresponding node.

[0186] The target path determination unit is configured to cut the shortest string connection path according to the target split point to obtain a target string connection path cut off.

[0187] The return unit is configured to return the remaining shortest string connection path after cutting as a new shortest string connection path, and return to continue to execute the step of determining the target split point until the shortest string connection path is cut into a string connection mode matching the photovoltaic string.

[0188] The string connection arrangement unit is configured to obtain the string connection arrangement mode of the photovoltaic module and the inverter according to the target string connection paths.

[0189] Further, the split point determination unit comprises:

[0190] The neighbor nodes of the inverter corresponding node are taken as the split points.

[0191] determining whether the split point is the target split point of the shortest string connection path;

[0192] If yes, the target split point is obtained.

[0193] Otherwise, the target split point of the shortest string connection path is determined according to the minimum difference error method.

[0194] Further, the split point determination unit is configured to determine whether the split point is a target split point of the shortest string line path, comprising:

[0195] taking the first split point reached along the shortest string line path from the start point or the end point as a current split point;

[0196] determining the number of nodes contained in the string line path from the start point or the end point to the current split point;

[0197] if the number of nodes is the target component number, determining that the current split point is the target split point;

[0198] if the number of nodes is not the target component number, determining that the current split point is not the target split point, taking the next split point of the current split point as a new current split point, and continuing to determine the number of nodes until all split points are traversed.

[0199] Further, the split point determination unit is configured to determine the target split point of the shortest string line path according to the minimum difference error method, which can comprise:

[0200] respectively determining a first number of nodes contained in the string line path from the start point to the first split point and a second number of nodes contained in the string line path from the end point to the first split point;

[0201] determining the minimum value of the difference between the first number of nodes and the second number of nodes and the number of nodes contained in the string line path corresponding to the minimum value;

[0202] if the number of nodes is greater than the target component number, backtracking the first initial split point to the minimum number of nodes, and taking the backtracked node as the target split point;

[0203] if the number of nodes is less than the target component number, advancing the first initial split point to the minimum number of nodes, and taking the advanced node as the target split point.

[0204] The photovoltaic module string line arrangement determination device provided by the embodiment of the application can execute the photovoltaic module string line arrangement determination method provided by any embodiment of the application, and has the corresponding function modules and beneficial effects of the execution method.

[0205] Embodiment four

[0206] Figure 9A structural diagram of an electronic device is provided for Embodiment Four of the present application. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application as described and / or claimed in this document.

[0207] As shown in Figure 9 The electronic device 40 includes at least one processor 41, and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., connected to the at least one processor 41 in communication, where the memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 42 or loaded into the random access memory (RAM) 43 from the storage unit 48. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0208] A plurality of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a magnetic disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0209] The processor 41 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs various methods and processes described above, such as the photovoltaic module string line arrangement determination method.

[0210] In some embodiments, the photovoltaic module string layout determination method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 48. In some embodiments, portions of the computer program, or all of the computer program, can be loaded onto the electronic device 40 via, e.g., ROM 42 and / or communication unit 49. When a computer program is loaded onto the RAM 43 and executed by the processor 41, one or more of the steps of the photovoltaic module string layout determination method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured, by software means (e.g., firmware), to perform the photovoltaic module string layout determination method.

[0211] It should be understood that the steps illustrated in the figures, and / or other steps, can be re-ordered, added, or removed, and that the steps need not be performed in the illustrated order. For example, the steps recited in the present disclosure can be performed in parallel, in series, or in a different order, as long as the desired results of the present technology are achieved. This disclosure is not limited in this regard.

[0212] The specific embodiments described above have been disclosed by way of example only. Persons skilled in the art will appreciate that various modifications, combinations, sub-combinations, and alternatives of the specific embodiments described above can be made without departing from the spirit and scope of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A method for determining the string arrangement of photovoltaic modules, characterized in that, The method comprises the following steps: According to the arrangement of photovoltaic modules and inverters in the installation area, a network node graph and an adjacency matrix of the photovoltaic modules are constructed; According to the network node graph and the adjacency matrix, and in combination with a preset path search algorithm, a shortest string line path of the photovoltaic modules in series is determined; According to the target component number contained in each photovoltaic module string, the shortest string line path is divided to determine the string line arrangement mode of the photovoltaic modules and the inverters, and the target component number is a set number of components contained in each photovoltaic module string; Wherein, according to the target component number contained in each photovoltaic module string, the shortest string line path is divided to determine the string line arrangement mode of the photovoltaic modules and the inverters, comprising: According to the neighborhood nodes of the corresponding nodes of the inverters, the target division points of the shortest string line path are determined; According to the target division points, the shortest string line path is cut to obtain the target string line path cut off; The remaining shortest string line path after cutting is taken as a new shortest string line path, and the determination step of the target division point is returned to continue to be executed until the shortest string line path is cut into each photovoltaic module string matching; According to each target string line path, the string line arrangement mode of the photovoltaic modules and the inverters is obtained.

2. The method of claim 1, wherein, According to the arrangement of photovoltaic modules and inverters in the installation area, a network node graph and an adjacency matrix of the photovoltaic modules are constructed, comprising: According to the arrangement of the photovoltaic modules and the inverters in the installation area, the neighborhood components in the eight neighborhoods of each photovoltaic module and the inverters are determined respectively; According to the neighborhood components, a network node graph of the photovoltaic modules is constructed; The network node graph is converted into an adjacency matrix of the photovoltaic modules.

3. The method of claim 2, wherein, According to the neighborhood components, a network node graph of the photovoltaic modules is constructed, comprising: The distances from each photovoltaic module and the inverters to the corresponding neighborhood components are determined; Each photovoltaic module is taken as a node, the connection lines from each photovoltaic module and the inverters to the corresponding neighborhood components are taken as edges, and each distance is taken as the weight of each edge, so that the network node graph of the photovoltaic modules is constructed.

4. The method of claim 2, wherein, The network node graph is converted into an adjacency matrix of the photovoltaic modules, comprising: An initial two-dimensional array is constructed according to the nodes contained in the network node graph; The weights in the network node graph are added to the corresponding positions of the initial two-dimensional array as matrix elements to determine the adjacency matrix of the photovoltaic modules.

5. The method of claim 1, wherein, According to the network node graph and the adjacency matrix, and in combination with a preset path search algorithm, a shortest string line path of the photovoltaic modules in series is determined, comprising: The corresponding node of the inverter in the network node graph is taken as the starting point of the shortest string line path and is added to the vertex set; The corresponding nodes of each photovoltaic module in the network node graph are sequentially obtained as current nodes; According to the adjacency matrix, the target node connected with the current node is determined; The target node is added to the vertex set and the edge between the current node and the target node is added to the edge set; According to each target string line path, the string line arrangement mode of the photovoltaic modules and the inverters is obtained. Determine a shortest string line path of the photovoltaic components according to an adding order of the target nodes.

6. The method of claim 5, wherein, Further comprising: If there is no target node connected to the current node, obtain a last node of the current node from the vertex set as a new current node, and re-determine the target node connected to the current node.

7. The method of claim 5, wherein, The determining the target node connected to the current node according to the adjacency matrix comprises: Arrange the adjacent nodes of the current node in ascending order of weights to obtain a sequence of the adjacent nodes of the current node; Take the adjacent node with the minimum weight in the sequence of the adjacent nodes as a current adjacent node; Determine whether the current adjacent node meets a set node connection condition according to the adjacency matrix; If yes, determine the current adjacent node as the target node connected to the current node; Otherwise, obtain a next adjacent node of the current adjacent node from the sequence of the adjacent nodes as a new current adjacent node, and continue to execute the step of determining whether the current adjacent node meets the set node connection condition until all the adjacent nodes in the sequence of the adjacent nodes are traversed.

8. The method of claim 1, wherein, The determining the target split point of the shortest string line path according to the adjacent node of the inverter corresponding node comprises: Take the adjacent node of the inverter corresponding node as a split point; Determine whether the split point is the target split point of the shortest string line path; If yes, obtain the target split point; Otherwise, determine the target split point of the shortest string line path according to a minimum difference error method.

9. The method of claim 8, wherein, The determining whether the split point is the target split point of the shortest string line path comprises: Take the first split point reached along the shortest string line path from the start point or the end point of the shortest string line path as a current split point; Determine a number of nodes contained in a string line path from the start point or the end point to the current split point; If the number of nodes is the target component number, determine that the current split point is the target split point; If the number of nodes is not the target component number, determine that the current split point is not the target split point, take a next split point of the current split point as a new current split point, and continue to execute the step of determining the number of nodes until all the split points are traversed.

10. The method of claim 9, wherein, The determining the target split point of the shortest string line path according to the minimum difference error method comprises: Determine a first number of nodes contained in a string line path from the start point to the first split point and a second number of nodes contained in a string line path from the end point to the first split point, respectively; Determine a minimum value of the first number of nodes and the second number of nodes from the target component number and a number of nodes contained in a string line path corresponding to the minimum value; If the number of nodes is greater than the target component number, back off the first initial split point to the minimum number of nodes, and take the node after the back off as the target split point; If the number of nodes is less than the target component number, advance the first initial split point to the minimum number of nodes, and take the node after the advance as the target split point.

11. A photovoltaic module string layout determination device, characterized by, Comprise: The constructing module is configured to construct a network node graph and an adjacency matrix of the photovoltaic modules according to arrangement of the photovoltaic modules and the inverter in an installation area; The path determining module is configured to determine a shortest string path of the photovoltaic modules in series according to the adjacency matrix and in combination with a preset path search algorithm; The arrangement determining module is configured to divide the shortest string path according to a target module number contained in each photovoltaic module string, and determine a string arrangement mode of the photovoltaic modules and the inverter, the target module number being a set number of module numbers contained in each photovoltaic module string; The arrangement determining module comprises: A split point determining unit configured to determine a target split point of the shortest string path according to a neighborhood node of a corresponding node of the inverter; A target path determining unit configured to cut the shortest string path according to the target split point, and obtain a target string path cut off; A returning unit configured to return the shortest string path remaining after cutting as a new shortest string path, and continue to perform the determining step of the target split point until the shortest string path is cut into each photovoltaic module string; A string arrangement unit configured to obtain the string arrangement mode of the photovoltaic modules and the inverter according to each target string path.

12. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the photovoltaic module string arrangement determination method in any one of claims 1-10.

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