Photovoltaic confluence unit division method and device, electronic equipment and readable storage medium

Abstract

The invention discloses a photovoltaic confluence unit division method and device, electronic equipment and a readable storage medium, and relates to the technical field of photovoltaic confluence unit division, and the method comprises the steps: obtaining the photovoltaic equipment information of a to-be-divided photovoltaic power generation unit: determining the preliminary planning information used for limiting the equipment planning position according to the photovoltaic equipment information; according to the preliminary planning information, a first division result is generated by using a preset division algorithm, and the first division result comprises equipment position information and convergence unit division information; on the basis of the first division result, cable path information is generated by using a preset path algorithm, and the preset path algorithm comprises an algorithm which is transformed by integrating engineering requirements; and combining the cable path information with the first division result to obtain a convergence unit division result. The method has the effects of reducing the dispersion degree of the confluence unit and improving the economic benefit.

Description

Technical Field

[0001] This application relates to the field of photovoltaic combiner unit partitioning technology, and in particular to a photovoltaic combiner unit partitioning method, apparatus, electronic device and readable storage medium. Background Technology

[0002] The rational planning of photovoltaic (PV) power generation units is crucial for improving land use efficiency. Among these, the optimized design of the combiner units directly impacts cable investment costs and system power generation efficiency. In practical engineering, the prefabricated substations for PV arrays are typically located at the center of the array. Current mainstream combiner unit optimization methods mainly include two technical approaches: one is to adopt a non-return cable scheme to reduce AC cable usage, and the other is to implement the shortest DC cable scheme to reduce DC cable losses. However, the combiner unit partitioning results from these two methods are discrete, and the increased cable usage leads to lower economic efficiency. Summary of the Invention

[0003] The purpose of this application is to at least solve one of the technical problems existing in the prior art, and to provide a photovoltaic combiner unit partitioning method, device, electronic device and readable storage medium, which aims to reduce the dispersion of combiner units and improve economic efficiency.

[0004] In a first aspect, embodiments of this application provide a method for partitioning photovoltaic combiner units, including: Obtain photovoltaic equipment information for the photovoltaic power generation units to be divided: Based on the photovoltaic equipment information, preliminary planning information for limiting the planned location of the equipment is determined; Based on the preliminary planning information, a first partitioning result is generated using a preset partitioning algorithm. The first partitioning result includes equipment location information and busbar partitioning information. Based on the first division result, cable path information is generated using a preset path algorithm, which includes an algorithm modified to incorporate engineering requirements. The cable path information and the first division result are combined to obtain the bus unit division result.

[0005] According to the technical solution of the embodiments of this application, at least the following beneficial effects are achieved: In addition to dividing multiple photovoltaic modules, the division of photovoltaic combiner units also includes setting the positions of equipment such as inverters and combiner boxes, as well as cable planning. Therefore, preliminary planning information for limiting the planning positions of equipment is determined based on photovoltaic equipment information. The positions of equipment in the photovoltaic combiner unit are standardized and limited by the preliminary planning information, so that the combiner units of the corresponding photovoltaic equipment are standardized and limited, thereby reducing the dispersion of combiner units. After completing the division of multiple photovoltaic modules and setting the positions of equipment such as inverters and combiner boxes, the cable path is planned by using a preset path algorithm that incorporates engineering requirements, so that the cable path is more standardized and meets engineering requirements, thereby improving economic efficiency.

[0006] According to some embodiments of this application, determining preliminary planning information for limiting the planned location of the photovoltaic equipment based on the photovoltaic equipment information includes: Based on the photovoltaic equipment information, the photovoltaic power generation unit is converted into a power generation point model; Based on the preset equipment location requirements, preliminary planning information for limiting the planned location of the equipment is determined through the power generation point model.

[0007] According to some embodiments of this application, determining preliminary planning information for limiting the planned location of equipment based on preset equipment location requirements using the power generation point model includes: Based on the power generation point model, multiple power generation unit centroids are obtained using a preset clustering algorithm; Based on the preset equipment location requirements, preliminary planning information is determined using the centroid of the power generation unit as a reference to restrict the planned location of the equipment.

[0008] According to some embodiments of this application, generating a first partitioning result using a preset partitioning algorithm based on the preliminary planning information includes: Based on the preliminary planning information, an equipment data model is established, which is used to characterize the subordinate relationships between different devices in the photovoltaic power generation unit. The device data model is processed using a preset partitioning algorithm to generate a first partitioning result.

[0009] According to some embodiments of this application, the preset path algorithm includes at least one path optimization algorithm for generating cable paths, wherein the path optimization algorithm includes at least one algorithm that is modified to incorporate engineering requirements.

[0010] According to some embodiments of this application, the preset path algorithm includes an algorithm that modifies the evaluation function in the pathfinding process based on engineering requirements.

[0011] According to some embodiments of this application, before generating cable path information using a preset path algorithm based on the first partitioning result, the photovoltaic combiner unit partitioning method further includes: Based on the merge unit division information, different photovoltaic devices are numbered; each photovoltaic device has a different number.

[0012] Secondly, embodiments of this application provide an operation control device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the photovoltaic combiner unit partitioning method described in the first aspect above.

[0013] Thirdly, embodiments of this application provide an electronic device including the operation control device described in the second aspect above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which are used to cause a computer to execute the photovoltaic combiner unit partitioning method as described in the first aspect above.

[0015] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] The present application will be further described below with reference to the accompanying drawings and embodiments; Figure 1 This is a flowchart of a photovoltaic combiner unit partitioning method provided in one embodiment of this application; Figure 2 This is a schematic diagram of a photovoltaic power generation unit to be divided according to an embodiment of this application; Figure 3 This is a schematic diagram of the combiner unit division result of a photovoltaic power generation unit provided in one embodiment of this application; Figure 4 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; Figure 5 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; Figure 6This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; Figure 7 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; Figure 8 This is a schematic diagram of an operation control device for performing a photovoltaic combiner unit partitioning method according to an embodiment of this application. Detailed Implementation

[0018] This section will describe in detail the specific embodiments of this application. Preferred embodiments of this application are shown in the accompanying drawings. The purpose of the drawings is to supplement the textual description with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of this application, but they should not be construed as limiting the scope of protection of this application.

[0019] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0020] In the description of this application, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] The various embodiments of the photovoltaic combiner unit partitioning method of this application will be further described below with reference to the accompanying drawings.

[0023] like Figure 1 As shown, Figure 1 This is a flowchart of a photovoltaic combiner unit partitioning method provided in one embodiment of this application. The photovoltaic combiner unit partitioning method may include, but is not limited to, steps S110, S120, S130 and S140.

[0024] Step S110: Obtain photovoltaic equipment information for the photovoltaic power generation units to be divided: Step S120: Based on the photovoltaic equipment information, determine the preliminary planning information used to restrict the planned location of the equipment; Step S130: Based on the preliminary planning information, generate the first division result using a preset division algorithm. The first division result includes equipment location information and busbar division information. Step S140: Based on the first division result, generate cable path information using a preset path algorithm. The preset path algorithm includes an algorithm that incorporates engineering requirements for modification. Step S150: Combine the cable path information with the first division result to obtain the bus unit division result.

[0025] It is understandable that photovoltaic combiner unit division refers to combining a certain number of photovoltaic modules into a relatively independent power generation unit according to their electrical connection relationship. The modules in the combiner unit are connected to the same combiner channel through series or parallel connection. By dividing the combiner unit, the system structure can be effectively optimized. By rationally planning the number of modules and the connection method, the amount of DC side cable and line loss can be significantly reduced, while improving economic efficiency.

[0026] In this embodiment, a photovoltaic (PV) power generation unit refers to an independent power generation module in a photovoltaic power station, consisting of a certain number of PV modules, support systems, DC combiner devices, and related electrical equipment. It is typically designed, installed, and managed as a basic power generation unit. The PV equipment information of a PV power generation unit may include the model and specifications, power parameters and quantity of PV modules and other equipment, the type and installation method of the support structure for the PV modules, the configuration of the DC combiner box or junction box for current collection, the specifications of the DC cables connecting the modules and the inverter, and the corresponding lightning protection and grounding devices.

[0027] In one embodiment, the photovoltaic equipment information of the photovoltaic power generation unit can be determined comprehensively based on equipment technical specifications, system operation requirements, and environmental conditions. For example, the operating voltage range of the photovoltaic modules should be limited between the manufacturer's nominal maximum system voltage and the inverter's MPPT voltage window. For instance, a 550W module with an open-circuit voltage of 49.6V needs to have its operating voltage controlled between 40 and 46V to ensure matching with the inverter. The AC output power of the inverter must not exceed its rated capacity and must meet the voltage fluctuation range of the grid connection. The tilt angle design of the support system needs to be structurally verified in conjunction with the local latitude, wind load, and snow load. The current carrying capacity of the DC cable must consider the temperature rise effect, and the cross-sectional area needs to be one size larger than the theoretically calculated value at an ambient temperature of 40°C.

[0028] Understandably, in the division of combiner units, the regional restrictions on equipment location need to comprehensively consider factors such as equipment performance parameters, environmental adaptability, ease of operation and maintenance, and safety regulations. Specifically, the photovoltaic module placement area must first avoid building shadows, tree obstructions, and dust pollution sources, ensuring unobstructed sunlight throughout the year, generally requiring no shadows between 9:00 AM and 3:00 PM true solar time on the winter solstice. Inverter locations should be close to the center of the module array to reduce line losses, while avoiding low-lying, waterlogged areas and maintaining adequate ventilation and heat dissipation space; the distance from the modules is typically controlled within 100 meters. The transformer substation should be located in the center of the array group and close to the road, ensuring the shortest possible high-voltage cable length while meeting fire and explosion safety distance requirements. The support foundation layout must avoid areas with poor geological conditions; when installing on slopes, the slope should not exceed 15 degrees, and anti-slip calculations must be performed. Based on this, the preliminary planned location range of the photovoltaic equipment can be determined according to the parameter information of each photovoltaic device in the photovoltaic equipment information, i.e., preliminary planning information, which can be used to restrict the planned location of the equipment.

[0029] In one embodiment, determining the area for equipment placement requires matching and analyzing the parameter information of the photovoltaic equipment with the array drawings of the photovoltaic power generation units. For example, based on the dimensions, weight, and electrical parameters specified in the photovoltaic module specifications, a reasonable installation spacing can be accurately calculated on the array drawings to meet both the requirement of unobstructed sunlight and the load-bearing limitations of the support system. The inverter placement must be combined with key parameters such as its rated input voltage range and MPPT operating window, and the reasonable connection distance to the module strings must be marked on the drawings to ensure that DC-side line losses are controlled within allowable limits. At the same time, sufficient ventilation space should be reserved on the drawings according to the inverter's heat dissipation requirements; for the location selection of the combiner equipment, the installation area on the array drawings should be planned according to its rated current and protection level to meet both the shortest path for electrical connection and the requirements for dust and water resistance; the location of the transformer substation should take into account the high-voltage side access point and the low-voltage side distribution distance, and find the most economical center point for electrical connection on the drawings; in addition, the layout of all equipment must strictly follow the information such as terrain elevation, geological conditions and obstacle distribution marked on the drawings, and avoid unfavorable areas such as gullies and soft foundations marked on the drawings.

[0030] Furthermore, it is understandable that during the initial determination of the planned location range for photovoltaic equipment, preliminary division of combiner units can also be carried out simultaneously. For example, based on the limitations of the module placement area, modules with the same installation parameters can be grouped into one combiner unit according to the consistency of string orientation and tilt angle; or, based on the optimal access capacity of the inverter, a certain number of module strings can be assigned to the same combiner unit according to the principle of proximity; or, based on terrain conditions and obstacle distribution, naturally separated photovoltaic sub-arrays can be treated as independent combiner units. In addition, in flat sites, a regular rectangular division method is usually adopted to ensure that the capacity of each combiner unit is balanced and the cable path is neat; while in complex terrain conditions, flexible division is required according to the terrain, which may result in irregularly shaped combiner units.

[0031] Therefore, in addition to the preliminary planned location range of photovoltaic equipment, the preliminary planning information can also include various preliminary merge unit division information.

[0032] In one embodiment, an intelligent algorithm can be used to filter out the bus unit partitioning information from various preliminary planning information that reduces unit dispersion and improves economic efficiency. Specifically, a multi-objective optimization model including equipment parameter constraints, array layout characteristics, and economic indicators can be established to transform various preliminary bus unit partitioning information into quantifiable evaluation parameters. The multi-objective optimization model is then processed by an algorithm aimed at reducing bus unit dispersion and improving economic efficiency to complete the screening. In terms of electrical performance, the dispersion of string parameters within each bus unit is mainly considered, including factors affecting power generation consistency such as string orientation deviation, tilt angle difference, and shading loss. The dispersion is quantified by calculating the standard deviation of the parameters for each unit. In terms of economic efficiency, cable investment costs, civil engineering costs, and expected power generation revenue are comprehensively evaluated, and factors such as DC cable length, AC cable routing, and transformer substation location are converted into costs. For example, a three-dimensional simulation can be performed on each preliminary partitioning scheme to simulate the power generation performance of each bus unit in different seasons and time periods. Schemes that do not meet technical specifications are automatically filtered out based on equipment layout constraints. Then, a multi-criteria decision-making method is used to rank and compare the remaining schemes.

[0033] In other words, the preliminary planning information can include not only the preliminary planned location range of photovoltaic equipment, but also the corresponding preliminary merge unit division information. When generating the first division result, a preset division algorithm can be used to optimize the preliminary merge unit division information and determine the final planned location of the photovoltaic equipment, thereby obtaining the first division result.

[0034] In this embodiment, the preset partitioning algorithm can be an algorithm that minimizes the sum of the distances from the string to the inverter plus the sum of the distances from the inverter to the transformer substation. In other words, the preset partitioning algorithm needs to minimize the sum of the DC cable distances from the string to the inverter and the AC cable distances from the inverter to the transformer substation. Therefore, the limitations on the arrangement of photovoltaic equipment need to be transformed into constraints in the algorithm. For example, firstly, based on component parameters and array layout, the optional connection range and electrical characteristics of each photovoltaic string need to be determined, and this information is quantified into algorithm input data. Simultaneously, the inverter's technical specifications, such as maximum number of input channels and rated capacity, are used as hard constraints. Then, a two-dimensional coordinate system is established to perform grid-based modeling of the photovoltaic field area. The transformer substation location is set as a known fixed point, the inverter location is set as a variable to be solved, and the connection relationship from each string to the inverter is used as a decision variable. An objective function is then constructed to minimize the sum of all cable lengths. For DC cables, a many-to-one connection from the string to the inverter is considered, while for AC cables, it is a one-to-one connection from the inverter to the transformer substation. During the solution process, the total cable length under different inverter locations and combiner unit partitioning combinations can be iteratively calculated, while simultaneously verifying in real time whether various equipment constraints are met, including inverter capacity limits, allowable voltage drop ranges, and maximum cable length requirements. Based on this, according to the preliminary planning information, the first partitioning result generated using the preset partitioning algorithm includes determined equipment location information and combiner unit partitioning information.

[0035] For complex large-scale photovoltaic arrays, a zonal optimization strategy can be adopted. First, the entire field area is divided into several relatively independent optimization regions based on the terrain and array distribution characteristics. Then, the optimal inverter location and combiner unit division are solved in each region, and the region boundaries are coordinated and optimized.

[0036] In one embodiment, the preset partitioning algorithm may employ algorithms such as genetic algorithms or particle swarm optimization.

[0037] In one embodiment, the path algorithm is modified by incorporating engineering requirements, which can include two implementation methods: partial integration and full integration. When engineering requirements are partially integrated, key constraints are mainly considered, such as fixing the transformer substation location at the coordinate point determined by the actual project and adhering to hard technical parameters such as the inverter's maximum capacity limit, while retaining the simplification assumptions in the theoretical algorithm. In the case of full integration of engineering requirements, all actual engineering constraints need to be integrated, including detailed topographic data, the distribution of weak soil layers in the geological survey report, the location of on-site obstacles, flood control and drainage requirements, and the reservation of operation and maintenance access channels, etc. At the same time, all equipment technical specifications and safety distance standards are strictly implemented so that the resulting solution fully meets the engineering implementation requirements and can be directly used for construction drawing design.

[0038] Therefore, by incorporating a pre-defined path algorithm that incorporates engineering requirements, cable path planning is performed based on the equipment location information and busbar division information represented by the first partitioning result, thus obtaining cable path information. For example, the structured data of the first division result, such as the inverter coordinates, transformer substation location, and combiner unit boundary, can be imported into the algorithm model first. At the same time, spatial information such as the site digital elevation model, geological layer, and obstacle distribution can be loaded to establish a three-dimensional planning environment containing all constraints. Then, based on cable laying specifications and economic principles, candidate paths can be automatically generated on the DC side from the string to the inverter using a star or tree topology. By calculating comprehensive indicators such as cable cost, voltage loss, and construction difficulty of each path, a feasible route scheme that meets the maximum voltage drop requirement can be selected. For the AC cable route from the inverter to the transformer substation, special requirements such as the turning radius and burial depth of the high-voltage cable are considered. The optimal laying route is planned along the preset maintenance passage or site road. In complex terrain areas, steep slopes and geological disaster areas are automatically avoided by combining slope analysis. When encountering insurmountable obstacles, the bypass logic is activated to recalculate the alternative route. In addition, electrical parameters such as cable current carrying capacity and thermal stability coefficient can be checked in real time during the planning process to ensure that all routes meet the equipment safety operation standards. For crossing areas, the elevation difference can be automatically adjusted or protective sleeves can be added to meet the safety distance requirements.

[0039] After obtaining the cable path information and the first division result, the cable path information and the first division result can be combined to obtain the bus unit division result. In this embodiment, a spatial topology network can be established based on the equipment location coordinates and electrical parameters. The rationality of the bus unit division can be verified by reverse verification through the actual direction and length data of the cable path. When it is found that the cable cost of some units is abnormally high due to path detours, the unit boundary or equipment position can be dynamically adjusted for re-optimization. At the same time, the bus unit capacity is checked by using the cable current carrying capacity and voltage drop calculation results to ensure that the electrical parameters of each unit are balanced and meet the equipment operation requirements. In addition, an iterative optimization method can be used to first optimize the cable path while keeping the bus unit division unchanged, and then fix the optimized path to adjust the unit division. This process is repeated until the overall system cost converges to the optimal value. In addition, the cable path information and the first division result can be integrated into the geographic information system platform. Spatial analysis tools can be used to automatically identify the conflict points between equipment layout and cable path, and the bus unit affiliation can be redistributed to simplify the wiring.

[0040] refer to Figure 2 and Figure 3 , Figure 2 This is a schematic diagram of a photovoltaic power generation unit to be divided according to an embodiment of this application. Figure 3 This is a schematic diagram of the combiner unit division result of a photovoltaic power generation unit provided in one embodiment of this application.

[0041] like Figure 4 As shown, Figure 4 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; regarding the above step S120, it may include, but is not limited to, steps S220 and S320.

[0042] Step S220: Based on the photovoltaic equipment information, convert the photovoltaic power generation unit into a power generation point model; Step S320: Based on the preset equipment location requirements, determine the preliminary planning information used to restrict the planned location of the equipment through the power generation point model.

[0043] It is understandable that abstracting a photovoltaic array into a power generation point model means simplifying the actual photovoltaic array into one or more mathematical points. In this way, the detailed arrangement, geometry, shading and other details of the internal components of the photovoltaic array can be ignored, and only the key electrical or spatial attributes are retained to facilitate calculation.

[0044] In this embodiment, the photovoltaic power generation unit is converted into a power generation point model. First, the basic technical parameters of the photovoltaic modules in the photovoltaic power generation unit are analyzed, including the physical dimensions, rated power, and electrical characteristics of the modules. Based on these data, the representative scale of the abstract point is determined, using a single string or standard photovoltaic array as the basic point element. The coordinate position of this point is calculated according to the module arrangement. For fixed support systems, the planar coordinates of the string center point can be taken, while for tracking support systems, the vertical coordinates of the rotation center also need to be considered. Furthermore, each point element needs to carry key attributes including its associated combiner unit number, connected inverter identifier, total installed capacity, rated output voltage, and other electrical parameters, as well as environmental parameters such as terrain elevation and sunshine conditions. Additionally, when establishing the point model, irregularly arranged array areas need to be meshed, discretizing the continuously distributed photovoltaic modules into a set of points with clear topological relationships, while preserving the electrical connection logic between strings.

[0045] After generating the power generation point model, preliminary planning information for restricting equipment location can be determined by combining spatial analysis with electrical parameters. Specifically, the coordinates of key equipment such as inverters and transformer substations can be used as fixed anchor points in the input point model system. Connectivity in all directions is calculated radiating outwards from these anchor points. Preliminary planning information is dynamically generated by combining the electrical attributes of the photovoltaic elements. For inverters, the limiting range mainly depends on the total power of the connected photovoltaic elements not exceeding the rated capacity. By traversing the power attributes of surrounding elements, the maximum coverage area meeting capacity requirements is divided in the point model using a density clustering algorithm. Simultaneously, DC voltage drop constraints are considered, and a voltage compliance region is formed with the electrical distance between elements as the radius. The limiting range of transformer substations requires a comprehensive assessment of the layout density of the inverter group under its jurisdiction. The Thiessen polygon algorithm can be used to divide the natural power supply zones of each transformer substation in the point model, and constraints such as cable current carrying capacity and short-circuit capacity are superimposed for boundary correction. Furthermore, terrain data can be incorporated when determining the limiting range to perform gradient analysis on the elevation attributes in the point model, automatically avoiding dangerous areas with slopes exceeding equipment installation requirements.

[0046] like Figure 5 As shown, Figure 5 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; regarding the above step S320, it may include, but is not limited to, steps S420 and S520.

[0047] Step S420: Based on the power generation point model, obtain the centroids of multiple power generation units using a preset clustering algorithm; Step S520: Based on the preset equipment location requirements, determine the preliminary planning information for limiting the planned location of the equipment, using the centroid of the power generation unit as a reference.

[0048] In this embodiment, after generating the power generation point model, multiple power generation unit centroids can be obtained based on the model using a preset clustering algorithm. Specifically, each point element is assigned a multi-dimensional feature vector of spatial coordinates and electrical parameters. Then, a preset clustering algorithm, such as Kmedoids, K-means, or DBSCAN, is used for automatic grouping. For the K-means algorithm, the number of clusters, K, needs to be preset. The value of K can be determined according to the number of inverters or site zoning requirements. Subsequently, the algorithm randomly initializes K centroid positions and then iteratively performs two steps: assigning each photovoltaic point element to the nearest centroid to form a temporary cluster, and then recalculating the average value of the coordinates of all points in each cluster to update the centroid position. This process is repeated until the centroid coordinates tend to stabilize. Here, the power generation unit centroid physically represents the geometric center of each cluster, and its coordinates are determined by the positions of all points within the cluster. It can be understood as the equilibrium center point of the photovoltaic zone, which often corresponds to the optimal installation position of the inverter in actual engineering. For the Kmedoids algorithm, the number of clusters K also needs to be set in advance. That is, K photovoltaic point elements are randomly selected as initial medoids (cluster representative points) and then the remaining point elements are assigned to the nearest medoid to form a temporary cluster. Then, within each cluster, the actual point element that minimizes the sum of the distances from all point elements in the cluster to it is selected as the new medoid. Through this iterative optimization, a stable clustering result is finally obtained, thus obtaining multiple power generation unit centroids. For the DBSCAN algorithm, there is no need to preset the number of clusters. Instead, it automatically identifies the cluster structure based on the spatial density of the point elements. The centroid obtained in this case is determined by subsequently calculating the mean of the point elements within the cluster.

[0049] Understandably, regardless of the algorithm used, the centroid of the power generation unit has clear engineering significance. In the spatial dimension, the centroid of the power generation unit represents the center of the photovoltaic equipment layout and is the starting point of the cable path radiation. In the electrical dimension, the centroid of the power generation unit represents the optimal access point for connecting photovoltaic points, which minimizes the total cable length.

[0050] In one embodiment, the number of main paths of the photovoltaic power generation unit can also be determined by the number of strings that the inverter can accommodate. That is, by using the Kmedoids clustering algorithm, multiple centroids of the photovoltaic power generation unit are calculated, and a suitable main path is found near the centroid. The main path, which is also the preliminary planning information, is used to limit the location of the inverter.

[0051] Specifically, the maximum number of strings that the inverter can accommodate can be used as the input value of the cluster number K in the K-medoids algorithm. Then, all strings in the photovoltaic array are abstracted into spatial objects with point element coordinates and electrical attributes. Through iterative calculation, K actual string positions are found as medoids. These medoids need to satisfy the condition that the number of strings contained in each cluster does not exceed the inverter capacity, while minimizing the total cable length from the strings in the cluster to the medoid. When the algorithm converges, each medoid represents the core access point of a photovoltaic power generation unit. Main path planning is carried out around these points within their surrounding radius. The direction of the main path needs to take into account engineering factors such as terrain slope, existing roads and cable trench layout. Specific coordinates with stable geological conditions and convenient construction and maintenance are selected near the medoid position as the initial installation range of the inverter, that is, the initial planning information.

[0052] In addition, other engineering constraints can be superimposed for fine-tuning. For example, when a medoid location is in a low-lying waterlogged area, a more suitable installation point needs to be selected within the allowable offset range of the main path, but the inverter must still be able to cover all strings within the original cluster.

[0053] like Figure 6 As shown, Figure 6 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; regarding the above step S130, it may include, but is not limited to, steps S230 and S330.

[0054] Step S230: Based on the preliminary planning information, establish an equipment data model. The equipment data model is used to characterize the subordinate relationships between different devices in the photovoltaic power generation unit. Step S330: Process the device data model using a preset partitioning algorithm to generate the first partitioning result.

[0055] In this embodiment, preliminary planning information is used to limit the planned location of equipment, for example, to limit the planned location of inverter equipment. Thus, after obtaining the preliminary planning information, an equipment data model can be established based on the preliminary planning information through mathematical modeling. The equipment data model is used to represent the subordinate relationship between different equipment in the photovoltaic power generation unit, that is, the equipment data model is used to represent the inverter location and the situation where photovoltaic strings belong to inverters. Subsequently, the equipment data model is processed using a preset partitioning algorithm. In this embodiment, the preset partitioning algorithm can be an algorithm that aims to minimize the sum of the distances from the strings to the inverter plus the sum of the distances from the inverter to the transformer. By solving the preset partitioning algorithm, the location of the inverter and the partitioning of the combiner unit can be obtained, that is, the first partitioning result.

[0056] Specifically, the preliminary planning information may include spatial constraints such as the allowed installation area boundary and minimum equipment spacing. These constraints are used as hard constraints to input into the preset partitioning algorithm. In this embodiment, the preset partitioning algorithm may be a mixed integer linear programming algorithm. Through the mixed integer linear programming algorithm, a device data model containing continuous variables and integer variables is constructed. The continuous variables represent the planar coordinate position of the inverter, and the integer variables are used to characterize the subordinate relationship between each photovoltaic string and the inverter. The value is 0 or 1 to indicate whether it is connected. During the model solution process, the mixed-integer linear programming algorithm simultaneously optimizes two types of variables. It ensures that the number of strings connected to each inverter does not exceed its rated capacity, and that the sum of the cable distance from the string to its inverter and the cable distance from the inverter to the designated transformer substation is minimized globally. Furthermore, the preset partitioning algorithm dynamically adjusts the inverter positions and string allocation scheme in each iteration, and processes integer variables through techniques such as linear relaxation and branch and bound to gradually approach the optimal solution. When the algorithm converges, the output inverter coordinates will automatically satisfy the spatial constraints of the initial plan, and the generated bus unit partitioning scheme can guarantee the optimal topology from the strings to the inverter within each unit.

[0057] In another embodiment of the photovoltaic combiner unit partitioning method provided in this application, the preset path algorithm includes at least one path optimization algorithm for generating cable paths, and the path optimization algorithm includes at least one algorithm that is modified to meet engineering requirements.

[0058] In this embodiment, the preset path algorithm may include one or more different path algorithms, which are path optimization algorithms used to generate cable paths. The path optimization algorithms used to generate cable paths include at least one algorithm that has been modified to meet engineering requirements. For example, the preset path algorithm includes two path optimization algorithms for generating cable paths: the A* algorithm and the Prim algorithm. The A* algorithm is an algorithm that has been modified to meet engineering requirements.

[0059] In another embodiment of the photovoltaic combiner unit partitioning method provided in this application, the preset path algorithm includes an algorithm that modifies the evaluation function in the pathfinding process according to engineering requirements.

[0060] In this embodiment, the preset path algorithm includes an algorithm modified to incorporate engineering requirements. These engineering requirements may include path reuse, single starting point to multiple endpoints, priority to areas near multiple inverters / strings, priority to main paths, and reduction of inflection points. Correspondingly, the algorithm is modified to incorporate these engineering requirements by altering the evaluation function in the pathfinding process, i.e., penalizing and weighting the engineering requirements. It is understood that the path reuse condition requires sharing existing cable paths to reduce the cost of redundant wiring; the single starting point to multiple endpoints condition is used for global optimization from one transformer substation to multiple inverters / strings; the priority to areas near multiple inverters / strings condition ensures that cable paths pass through densely populated areas of multiple inverters to reduce branch line length; the priority to main paths condition prioritizes main paths (such as cable trenches) over temporary paths; and the reduction of inflection points condition increases the weight of straight paths over curved paths.

[0061] In one embodiment, the preset path algorithm includes the A* algorithm, which can be modified to incorporate engineering requirements. For example, the evaluation function of the A* algorithm is as follows: dist_to_farthest=abs(current[0]--farthest[0])*10+ abs(current[1]-farthest[1]) dist_to_supply = abs(current[0]-supply[0])*10 + abs(current[1]-supply[1]) Based on the original Manhattan distance calculation, five key correction factors are introduced: path reuse rate penalty (controlled by coefficient a), multi-endpoint distribution adjustment (adjusted by coefficient b), cluster region proximity reward (adjusted by coefficient c), main path priority coefficient (controlled by weight d), and inflection point number penalty (adjusted by coefficient e). Subsequently, by dynamically tracking the heat map of planned paths, the cost calculation for reused path segments is given with decreasing coefficient a; considering the characteristic of a single starting point to multiple endpoints, the search priority of different endpoint directions is adjusted by coefficient b; when the path is close to a high-density cluster region, a distance decay function with coefficient c is introduced to give a reward; the main path priority is strengthened by coefficient d in the evaluation function to enhance the attraction of the main road; finally, coefficient e is used to incrementally penalize the direction change points in the path, effectively reducing unnecessary turns.

[0062] like Figure 7 As shown, Figure 7 This is a flowchart of a photovoltaic combiner unit partitioning method provided in another embodiment of this application; regarding the above photovoltaic combiner unit partitioning method, before step S140, there may be steps including but not limited to step S160.

[0063] Step S160: Number the different photovoltaic devices according to the combiner unit division information.

[0064] Each photovoltaic device has a unique serial number.

[0065] Understandably, before generating cable paths using a preset path algorithm, the photovoltaic devices in the already divided combiner units can be numbered. Each photovoltaic device has a unique number, which facilitates subsequent cable path planning.

[0066] Based on the photovoltaic combiner unit partitioning methods of the above embodiments, the following presents various embodiments of the operation control device, electronic device, computer-readable storage medium, and computer program product of this application.

[0067] like Figure 8 As shown, Figure 8 This is a schematic diagram of an operation control device for executing a photovoltaic combiner unit partitioning method according to an embodiment of this application. The operation control device 800 implemented in this application includes: a processor 820, a memory 810, and a computer program stored in the memory 810 and executable on the processor 820, wherein... Figure 8 The example uses a processor 820 and a memory 810.

[0068] The processor 820 and the memory 810 can be connected via a bus or other means. Figure 8 Taking the example of a connection between China and Israel via a bus.

[0069] Memory 810, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 810 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 810 may optionally include remotely located memories 810 relative to processor 820, which can be connected to the operation control device 800 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0070] Those skilled in the art will understand that Figure 8 The device structure shown does not constitute a limitation on the operation control device 800, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0071] exist Figure 8 In the operation control device 800 shown, the processor 820 can be used to call the control program stored in the memory 810, thereby implementing the photovoltaic combiner unit partitioning method described above. Specifically, the non-transitory software program and instructions required to implement the photovoltaic combiner unit partitioning method of the above embodiment are stored in the memory 810. When executed by the processor 820, the photovoltaic combiner unit partitioning method of the above embodiment is executed.

[0072] It is worth noting that, since the operation control device 800 of this application embodiment can execute the photovoltaic combiner unit partitioning method of any of the above embodiments, the specific implementation method and technical effects of the operation control device 800 of this application embodiment can refer to the specific implementation method and technical effects of the photovoltaic combiner unit partitioning method of any of the above embodiments.

[0073] Furthermore, one embodiment of this application also provides an electronic device that includes the operation control device described in the above embodiment.

[0074] It is worth noting that, since the electronic device of this application embodiment includes the operation control device of the above embodiment, and the operation control device of the above embodiment can execute the photovoltaic combiner unit partitioning method of any of the above embodiments, the specific implementation method and technical effect of the electronic device of this application embodiment can refer to the specific implementation method and technical effect of the photovoltaic combiner unit partitioning method of any of the above embodiments.

[0075] Furthermore, one embodiment of this application provides a computer-readable storage medium storing computer-executable instructions for performing the photovoltaic combiner unit partitioning method described above. Exemplarily, the above-described method is executed... Figure 1 , Figure 4 The steps are shown in the diagram.

[0076] It is worth noting that, since the computer-readable storage medium of this application embodiment can execute the photovoltaic combiner unit partitioning method of any of the above embodiments, the specific implementation method and technical effects of the computer-readable storage medium of this application embodiment can be referred to the specific implementation method and technical effects of the photovoltaic combiner unit partitioning method of any of the above embodiments.

[0077] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which may include computer storage media or non-transitory media and communication media or transient media. As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc DVD or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0078] In the several embodiments provided in this application, it should be understood that the disclosed systems, instruments, and methods can be implemented in other ways. For example, the instrument embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between instruments or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0079] It should also be understood that the various implementation methods provided in this application can be combined arbitrarily to achieve different technical effects.

[0080] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A method for dividing photovoltaic combiner units, characterized in that, include: Obtain photovoltaic equipment information for the photovoltaic power generation units to be divided: Based on the photovoltaic equipment information, preliminary planning information for limiting the planned location of the equipment is determined; Based on the preliminary planning information, a first partitioning result is generated using a preset partitioning algorithm. The first partitioning result includes equipment location information and busbar partitioning information. Based on the first division result, cable path information is generated using a preset path algorithm, which includes an algorithm modified to incorporate engineering requirements. The cable path information and the first division result are combined to obtain the bus unit division result.

2. The photovoltaic combiner unit partitioning method according to claim 1, characterized in that, The step of determining preliminary planning information for limiting the planned location of the photovoltaic equipment based on the photovoltaic equipment information includes: Based on the photovoltaic equipment information, the photovoltaic power generation unit is converted into a power generation point model; Based on the preset equipment location requirements, preliminary planning information for limiting the planned location of the equipment is determined through the power generation point model.

3. The photovoltaic combiner unit partitioning method according to claim 2, characterized in that, The step of determining preliminary planning information to restrict the planned location of equipment based on preset equipment location requirements and the power generation point model includes: Based on the power generation point model, multiple power generation unit centroids are obtained using a preset clustering algorithm; Based on the preset equipment location requirements, preliminary planning information is determined using the centroid of the power generation unit as a reference to restrict the planned location of the equipment.

4. The photovoltaic combiner unit partitioning method according to claim 1, characterized in that, The step of generating a first partitioning result using a preset partitioning algorithm based on the preliminary planning information includes: Based on the preliminary planning information, an equipment data model is established, which is used to characterize the subordinate relationships between different devices in the photovoltaic power generation unit. The device data model is processed using a preset partitioning algorithm to generate a first partitioning result.

5. The photovoltaic combiner unit partitioning method according to claim 1, characterized in that, The preset path algorithm includes at least one path optimization algorithm for generating cable paths, and the path optimization algorithm includes at least one algorithm that is modified to meet engineering requirements.

6. The photovoltaic combiner unit partitioning method according to claim 1, characterized in that, The preset path algorithm includes an algorithm that modifies the evaluation function in the pathfinding process according to engineering requirements.

7. The photovoltaic combiner unit partitioning method according to claim 1, characterized in that, Before generating cable path information using a preset path algorithm based on the first partitioning result, the photovoltaic combiner unit partitioning method further includes: Based on the merge unit division information, different photovoltaic devices are numbered; each photovoltaic device has a different number.

8. An operation control device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the photovoltaic combiner unit partitioning method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, Includes the operation control device as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the photovoltaic combiner unit partitioning method as described in any one of claims 1 to 7.

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