CN114819302A - Photovoltaic module partitioning method, system, terminal device and medium - Google Patents
Photovoltaic module partitioning method, system, terminal device and medium Download PDFInfo
- Publication number
- CN114819302A CN114819302A CN202210379229.5A CN202210379229A CN114819302A CN 114819302 A CN114819302 A CN 114819302A CN 202210379229 A CN202210379229 A CN 202210379229A CN 114819302 A CN114819302 A CN 114819302A
- Authority
- CN
- China
- Prior art keywords
- photovoltaic module
- photovoltaic
- partitioning
- cable
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000638 solvent extraction Methods 0.000 title claims abstract description 87
- 238000000034 method Methods 0.000 title claims abstract description 58
- 230000006870 function Effects 0.000 claims abstract description 117
- 239000011159 matrix material Substances 0.000 claims abstract description 68
- 238000005192 partition Methods 0.000 claims abstract description 63
- 238000005457 optimization Methods 0.000 claims abstract description 34
- 230000002068 genetic effect Effects 0.000 claims description 12
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000004088 simulation Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013082 photovoltaic technology Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Photovoltaic Devices (AREA)
Abstract
The invention discloses a method, a system, terminal equipment and a computer readable storage medium for partitioning a photovoltaic module, wherein the method for partitioning the photovoltaic module comprises the following steps: based on position parameters of photovoltaic modules in a preset photovoltaic module square matrix, carrying out initial partitioning on the photovoltaic modules to obtain a photovoltaic module set; determining cable functions corresponding to the photovoltaic assembly sets, and determining target cable functions corresponding to the preset photovoltaic assembly square matrix based on the cable functions; and based on a cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module. The photovoltaic module can be partitioned based on the principle of minimizing the cost of the cable, so that the wiring cost of the cable is reduced.
Description
Technical Field
The present invention relates to the field of photovoltaic technologies, and in particular, to a method, a system, a terminal device, and a computer-readable storage medium for partitioning a photovoltaic module.
Background
With the rapid development of photovoltaic system technology, the cost of photovoltaic power stations is reduced year by year. In the existing photovoltaic power plant cost construction, the cable cost accounts for about 4% of the total cost. The arrangement of the current assembly is mainly performed through cable connection and laying in a manual mode or a third-party software mode.
However, the manual wiring mode is easily influenced by personal experience, automatic wiring cannot be realized, and a great optimization space also exists in the cable wiring mode; and the partition and cable connection of the photovoltaic assembly can be realized by a third-party software wiring mode, but the cost of the cable is not considered by the automatic wiring function, and a certain optimization space also exists.
Generally speaking, when photovoltaic modules in a photovoltaic system are partitioned, the photovoltaic modules cannot be reasonably partitioned according to the mode with the lowest cable laying cost, and the cost of a photovoltaic power station is increased.
Disclosure of Invention
The invention mainly aims to provide a photovoltaic module partitioning method, a photovoltaic module partitioning system, terminal equipment and a computer readable storage medium, and aims to partition a photovoltaic module based on a cable cost minimization principle so as to reduce the wiring cost of a cable.
In order to achieve the above object, the present invention provides a method for partitioning a photovoltaic module, where the partitioning of the photovoltaic module includes:
based on position parameters of photovoltaic modules in a preset photovoltaic module square matrix, carrying out initial partitioning on the photovoltaic modules to obtain a photovoltaic module set;
determining cable functions corresponding to the photovoltaic assembly sets, and determining target cable functions corresponding to the preset photovoltaic assembly square matrix based on the cable functions;
and based on a cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module.
Optionally, after the step of performing parameter optimization on the target cable function to obtain an optimal partition of the photovoltaic module, the method further includes:
according to the optimal partition, all the photovoltaic modules in the preset photovoltaic module square matrix are partitioned to obtain sub-areas;
and sequentially connecting the photovoltaic modules in the sub-areas through cables so as to reduce the cable laying cost.
Optionally, the step of initially partitioning the photovoltaic module to obtain a photovoltaic module set includes:
and partitioning the photovoltaic modules according to the capacity of a preset header box or a preset string inverter to obtain a photovoltaic module set.
Optionally, the step of determining a cable function corresponding to each of the photovoltaic module sets includes:
and determining the Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining the cable function corresponding to the photovoltaic module set according to the Manhattan distance.
Optionally, the step of determining a target cable function corresponding to the preset component square matrix based on each cable function includes:
and accumulating the cable functions to obtain a target cable function corresponding to the preset assembly square matrix.
Optionally, the step of performing parameter optimization on the target cable function to obtain an optimal partition of the photovoltaic module includes:
and based on a cable cost minimization principle, performing parameter optimization on the target cable function through a preset genetic algorithm to obtain the optimal partition of the photovoltaic module.
Optionally, before the step of initially partitioning the photovoltaic module based on the position parameter of the photovoltaic module in the preset photovoltaic module square matrix to obtain the photovoltaic module set, the method further includes:
and deriving the position parameters of all the photovoltaic modules in the preset module square matrix from preset drawing software.
In order to achieve the above object, the present invention further provides a partitioning system of a photovoltaic module, including:
the partitioning module is used for initially partitioning the photovoltaic modules based on position parameters of the photovoltaic modules in a preset photovoltaic module matrix to obtain a photovoltaic module set;
the determining module is used for determining cable functions corresponding to the photovoltaic assembly sets and determining target cable functions corresponding to the preset photovoltaic assembly square matrix based on the cable functions;
and the optimizing module is used for carrying out parameter optimizing on the target cable function based on a cable cost minimization principle to obtain the optimal partition of the photovoltaic module.
The method for partitioning the photovoltaic module comprises the steps of dividing the photovoltaic module into a plurality of functional modules, and dividing the functional modules into a plurality of functional modules.
In order to achieve the above object, the present invention further provides a terminal device, including: a memory, a processor and a partitioning program of a photovoltaic module stored on the memory and executable on the processor, the partitioning program of a photovoltaic module implementing the steps of the method of partitioning a photovoltaic module as described above when executed by the processor.
In addition, to achieve the above object, the present invention further provides a computer readable storage medium, on which a partition program of a photovoltaic module is stored, and when being executed by a processor, the partition program of the photovoltaic module implements the steps of the partition method of the photovoltaic module as described above.
Furthermore, to achieve the above object, the present invention also provides a computer program product comprising a computer program which, when being executed by a processor, realizes the steps of the method for partitioning a photovoltaic module as described above.
The invention provides a photovoltaic module partitioning method, a system, terminal equipment, a computer readable storage medium and a computer program product, wherein a photovoltaic module is initially partitioned to obtain a photovoltaic module set based on position parameters of the photovoltaic module in a preset photovoltaic module matrix; determining cable functions corresponding to the photovoltaic assembly sets, and determining target cable functions corresponding to the preset photovoltaic assembly square matrix based on the cable functions; and based on a cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module.
Compared with the photovoltaic module partitioning wiring mode in the prior art, in the invention, the target cable function of the photovoltaic module matrix is obtained according to the cable function of the photovoltaic module set obtained by initial partitioning, and the photovoltaic module partitioning mode with the lowest cable cost of the photovoltaic modules in the photovoltaic module matrix can be obtained by carrying out parameter optimization on the target cable function. Therefore, the photovoltaic module can be wired through the cable, and the photovoltaic module partition mode with the lowest cable wiring cost can be realized. On the basis, the photovoltaic power station can further reduce the cost of the photovoltaic power station.
Drawings
FIG. 1 is a schematic diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic view of a first process of an embodiment of a method for partitioning a photovoltaic module according to the present invention;
FIG. 3 is a second schematic flow chart of an embodiment of a method for partitioning a photovoltaic module according to the present invention;
fig. 4 is a schematic view of a photovoltaic module support point set according to an embodiment of the method for partitioning a photovoltaic module according to the present invention;
FIG. 5 is a schematic view of a bracket distribution simulation involved in an embodiment of a method for partitioning a photovoltaic module according to the present invention;
FIG. 6 is a first schematic diagram of a partitioning result according to an embodiment of the partitioning method for a photovoltaic module of the present invention;
FIG. 7 is a second schematic diagram of a partitioning result according to an embodiment of the partitioning method for a photovoltaic module of the present invention;
fig. 8 is a functional block diagram of a partitioning system of a photovoltaic module according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
It should be noted that the terminal device in the embodiment of the present invention may be a terminal device for implementing the partitioning of the photovoltaic module, and the terminal device may specifically be a smart phone, a personal computer, a server, and the like.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001 described previously.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a partition program of a photovoltaic module. The operating system is a program that manages and controls the hardware and software resources of the device, supporting the execution of the partition programs of the photovoltaic modules and other software or programs. In the device shown in fig. 1, the user interface 1003 is mainly used for data communication with a client; the network interface 1004 is mainly used for establishing communication connection with a server; and the processor 1001 may be configured to call a partition program of the photovoltaic module stored in the memory 1005, and perform the following operations:
based on position parameters of photovoltaic modules in a preset photovoltaic module square matrix, carrying out initial partitioning on the photovoltaic modules to obtain a photovoltaic module set;
determining cable functions corresponding to the photovoltaic assembly sets, and determining target cable functions corresponding to the preset photovoltaic assembly square matrix based on the cable functions;
and based on a cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module.
Further, after the step of performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
according to the optimal partition, all the photovoltaic modules in the preset photovoltaic module square matrix are partitioned to obtain sub-areas;
and sequentially connecting the photovoltaic modules in the sub-areas through cables so as to reduce the cable laying cost.
Further, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
and partitioning the photovoltaic modules according to the capacity of a preset header box or a preset string inverter to obtain a photovoltaic module set.
Further, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
and determining the Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining the cable function corresponding to the photovoltaic module set according to the Manhattan distance.
Further, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
and accumulating the cable functions to obtain a target cable function corresponding to the preset assembly square matrix.
Further, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
and based on a cable cost minimization principle, performing parameter optimization on the target cable function through a preset genetic algorithm to obtain the optimal partition of the photovoltaic module.
Further, before the step of initially partitioning the photovoltaic module based on the position parameter of the photovoltaic module in the preset photovoltaic module square matrix to obtain the photovoltaic module set, the processor 1001 may be further configured to call a partition program of the photovoltaic module stored in the memory 1005, and further perform the following operations:
and deriving the position parameters of all the photovoltaic modules in the preset module square matrix from preset drawing software.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a photovoltaic module partitioning method according to the present invention.
In the present embodiment, an embodiment of an interface switching method is provided, and it should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in an order different from that here.
In order to partition a plurality of photovoltaic modules in a photovoltaic system and connect each partitioned photovoltaic module through a cable, so that the laying cost of the cable is the lowest, in this embodiment, as shown in fig. 3, first, position information of the photovoltaic modules is read, then, a determined objective function is obtained based on the position information of each photovoltaic module, and then, the objective function is optimized through a genetic algorithm to obtain an optimal partition and an optimal connection mode of the photovoltaic modules.
Step S10, based on the position parameters of the photovoltaic modules in the preset module matrix, carrying out initial partitioning on the photovoltaic modules to obtain a photovoltaic module set;
it should be noted that, in the present embodiment, the layout positions of the photovoltaic modules in the photovoltaic system are predetermined, that is, the positions of the photovoltaic modules cannot be changed. On this basis, before the plurality of photovoltaic modules are partitioned on the basis of the cable laying cost minimization principle, initial partitioning needs to be performed on each photovoltaic module.
Specifically, for example, the position parameter of the photovoltaic module may be expressed as:
X＝{X 1 ,X 2 ,…,X i ,…,X n }
wherein n is a squareTotal number of components in array, X i Is the position coordinate (x) of the ith photovoltaic module Xi ,y Xi )。
It should be noted that, in this embodiment, the photovoltaic modules may be uniformly grouped or non-uniformly grouped, and this grouping manner is not specifically limited in this embodiment.
Step S20, determining cable functions corresponding to the photovoltaic module sets, and determining target cable functions corresponding to the preset photovoltaic module square matrix based on the cable functions;
the terminal equipment further determines cable functions corresponding to all the photovoltaic module sets after acquiring position parameters, namely position coordinates, of all the photovoltaic modules in the photovoltaic module array and initially partitioning the photovoltaic modules according to the position coordinates to obtain the photovoltaic module sets. On the basis, the cable functions are accumulated to obtain a target cable function corresponding to the photovoltaic module array.
And step S30, based on the cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module.
It should be noted that, in this embodiment, the principle of minimizing the cable cost is that, when all the photovoltaic modules in the photovoltaic module matrix are wired by cables, the cables are used for completing the wiring of all the photovoltaic modules, so that the cost of the bus cable for the wiring is the lowest.
Specifically, for example, after each photovoltaic module in the photovoltaic module matrix is initially partitioned to obtain a photovoltaic module set, and then a target cable function of the photovoltaic module matrix is determined based on a cable function of each photovoltaic module set, in order to minimize the wiring cost, the target cable function is optimized in parameters to obtain an optimal partition of each photovoltaic module in the photovoltaic module matrix, and the total cable cost for wiring is minimized according to the optimal partition.
In this embodiment, each photovoltaic module is initially partitioned based on the position parameter of the photovoltaic module to obtain a photovoltaic module set, a cable function of each photovoltaic module set to the photovoltaic module set is determined, and the cable functions are accumulated to obtain a function of a target cable corresponding to the photovoltaic module array. In order to minimize the wiring cost, the target cable function is optimized in parameters to obtain the optimal partition of each photovoltaic module in the photovoltaic module square matrix, and the total cable cost for wiring is minimized according to the optimal partition.
Compared with the photovoltaic module partitioning wiring mode in the prior art, in the invention, the target cable function of the photovoltaic module matrix is obtained according to the cable function of the photovoltaic module set obtained by initial partitioning, and the photovoltaic module partitioning mode with the lowest cable cost of the photovoltaic modules in the photovoltaic module matrix can be obtained by carrying out parameter optimization on the target cable function. Therefore, the photovoltaic module can be wired through the cable, and the photovoltaic module partition mode with the lowest cable wiring cost can be realized. On the basis, the photovoltaic power station can further reduce the cost of the photovoltaic power station.
Based on the first embodiment of the partitioning method of the photovoltaic module of the present invention, a second embodiment of the partitioning method of the photovoltaic module of the present invention is proposed.
Compared with the first embodiment, in this embodiment, after the step S30, "performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module," the method further includes:
step S40, according to the optimal partition, all the photovoltaic modules in the preset module square matrix are partitioned to obtain each sub-area;
and step S50, sequentially connecting the photovoltaic modules in the sub-areas through cables.
It should be noted that, in this embodiment, after parameter optimization is performed on a target cable function by the terminal device to obtain an optimal partition of the photovoltaic module, area division of the photovoltaic module and connection of the photovoltaic module in the area are further performed according to the optimal partition, so that the total cost of cables for wiring is the lowest.
Specifically, for example, the terminal device partitions all photovoltaic modules in a preset photovoltaic module matrix according to the optimal partition to obtain each sub-area, wherein each sub-area includes a plurality of photovoltaic modules, and on the basis, the terminal device partitions all photovoltaic modules in the preset photovoltaic module matrix to obtain each sub-areaAnd the photovoltaic modules are connected in sequence according to the subscripts of the photovoltaic modules, and the cable laying cost generated by the partition and connection mode of the photovoltaic modules is the lowest. For example, in sub-region D i Including a photovoltaic module d 1 、d 2 、…、d i All photovoltaic modules within that sub-zone will be connected sequentially in the order 1, 2, …, i.
Further, in step S10, the "obtaining a photovoltaic module set by initially partitioning the photovoltaic modules" may include:
and S101, partitioning the photovoltaic modules according to the capacity of a preset header box or a preset string inverter to obtain a photovoltaic module set.
It should be noted that, in the present embodiment, all the photovoltaic modules in the photovoltaic module matrix may be partitioned by using the capacity of the combiner box or the string inverter.
Specifically, for example, the photovoltaic module is divided into m sub-regions according to the capacity of the combiner box or the group string inverter, the size of each sub-region may be different or the same, and the set of sub-regions is denoted as D ═ { D ═ D 1 ,D 2 ,…,D i ,…,D m The number of components corresponding to each sub-area is { d } 1 ,d 2 ,…,d i ,…,d m In which D is i Is the ith photovoltaic module subregion, contains d i And the photovoltaic modules are connected according to the subscript sequence.
On the basis, the set of components corresponding to each photovoltaic subregion Di is S ═ S 1 ,S 2 ,…,S i ,…,S di And (4) wherein S is equal to X, and X is a position parameter of the photovoltaic module and can be expressed as: x ═ X 1 ,X 2 ,…,X i ,…,X n }。
Further, in step S20, the "determining a cable function corresponding to each of the photovoltaic module sets" may include:
step S201, determining a Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining a cable function corresponding to the photovoltaic module set according to the Manhattan distance.
The terminal equipment partitions the photovoltaic modules according to the position parameters of the photovoltaic modules, obtains a photovoltaic module set, and then connects the photovoltaic modules according to the subscripts of the modules according to the position parameters of the photovoltaic modules in the photovoltaic module set, so that the cable usage and the cable cost of the partitions can be determined.
In particular, for example, since the photovoltaic module is set to S ═ { S ═ S 1 ,S 2 ,…,S i ,…,S di At this time, the corresponding cable function is g i (S). Starting from S1 in the set S, the next connection point S is calculated respectively i And the last connection point S i-1 The Manhattan distance of, the target function of the connection mode of the components in the sub-area is
Wherein the content of the first and second substances,
further, in the step S20, the "determining the target cable function corresponding to the preset photovoltaic module square matrix based on each cable function" may include:
step S202, accumulating the cable functions of the photovoltaic modules to obtain a target cable function corresponding to the preset module matrix.
After the cable functions corresponding to the photovoltaic module sets are determined, in order to partition all photovoltaic modules of the photovoltaic module square matrix, the terminal equipment further determines target cable functions corresponding to the photovoltaic module square matrix according to the cable functions corresponding to the photovoltaic module sets.
Specifically, for example, the number of components per partition { d } 1 ,d 2 ,…,d i ,…,d m Sequentially acquiring support point sets of the sub-areas from the support point sets in a centralized manner, namely the photovoltaic assembly sets { D ] of the sub-areas 1 ,D 2 ,…,D i ,…,D m Due to the cables of each sub-areaObjective function g i (S) having determined above, based on the partitioned cable functions, a cable objective function f (x) for the photovoltaic module square matrix can be obtained as:
on the basis, f (X) is taken as an objective function of the system to be optimized and solved.
Further, in step S30, the "performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module" may include:
and S301, performing parameter optimization on the target cable function through a preset genetic algorithm based on a cable cost minimization principle to obtain an optimal partition of the photovoltaic module.
After the terminal equipment acquires the target cable function corresponding to the photovoltaic module matrix, in order to determine the partition result and the wiring sequence of the photovoltaic module corresponding to the condition that the total cost of the cable for wiring is the lowest, parameter optimization is carried out on the target cable function through a genetic algorithm on the basis of a cable cost minimization principle.
Specifically, for example, the input of the optimization objective function f (X) is the position parameter X ═ X of the photovoltaic module 1 ,X 2 ,…,X i ,…,X n And f, (X) obtaining the partitioning result of each partitioning point set and the wiring sequence of the photovoltaic module when the optimization target is f (X) is the minimum value.
From this, it can be seen that the TSP optimization problem of the Genetic Algorithm (GA) can be used to solve.
Specifically, for example, when solving using the GA _ TSP function, the parameters are set as follows:
the objective function is set as: f (X); the number of the populations is set to 100; the genetic iteration times are set to be 200, genetic algorithm solving is carried out based on the above settings, and finally the optimal result of the connection mode of the photovoltaic module partitions and the photovoltaic modules is obtained. The optimized minimum objective function is the minimum cable usage in the photovoltaic module matrix, and the corresponding partitioning result is as follows:
D best ＝{D 1 best ,D 2 best ,…,D i best ,…,D m best }
further, before the step S10, "obtaining a photovoltaic module set by initially partitioning the photovoltaic modules based on the position parameters of the photovoltaic modules in the preset photovoltaic module square matrix", the method further includes:
and step S40, deriving the position parameters of all the photovoltaic modules in the preset module square matrix from preset drawing software.
Before the terminal equipment partitions the photovoltaic module based on the position parameters of the photovoltaic module in the photovoltaic module matrix, the position parameters of the photovoltaic module in the photovoltaic module matrix are required to be obtained in advance from a CAD drawing or a data file derived from other software.
In this embodiment, after the terminal device performs parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module, the terminal device further performs area division of the photovoltaic module and connection of the photovoltaic module in the area according to the optimal partition, so that the total cost of cables for wiring is the lowest. Terminal equipment can adopt the capacity of collection flow box or group string dc-to-ac converter to carry out the subregion to all photovoltaic module in the photovoltaic module square matrix. And determining the Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining the cable function corresponding to the photovoltaic module set according to the Manhattan distance. In order to partition all photovoltaic modules of the photovoltaic module square matrix, accumulating the cable functions corresponding to all the photovoltaic module sets to obtain a target cable function corresponding to the photovoltaic module square matrix. After the terminal equipment acquires the target cable function corresponding to the photovoltaic module matrix, in order to determine the partition result and the wiring sequence of the photovoltaic module corresponding to the condition that the total cost of the cable for wiring is the lowest, parameter optimization is carried out on the target cable function through a genetic algorithm on the basis of a cable cost minimization principle.
In the invention, after each photovoltaic module in the photovoltaic module matrix is initially partitioned to obtain a photovoltaic module set, and further, cable functions of each photovoltaic module set are subjected to target cable functions of the photovoltaic module matrix, in order to minimize the wiring cost, the target cable functions are subjected to parameter optimization through a genetic algorithm to obtain the optimal partition of each photovoltaic module in the photovoltaic module matrix, and the photovoltaic modules of each sub-area are sequentially connected according to the optimal partition, so that the purpose of minimizing the consumption of the whole simulation cable and reducing the cable cost of a station is achieved.
Based on the first and second embodiments of the partitioning method of the photovoltaic module of the present invention, a third embodiment of the partitioning method of the photovoltaic module of the present invention is proposed.
In this embodiment, the partitioning method of the photovoltaic module is applied to a photovoltaic module partitioning scene.
The method includes the steps that a support point set X of 100 photovoltaic modules of a photovoltaic square matrix is obtained from a data file, as shown in fig. 4, and the distribution situation of the support point sets of the 100 photovoltaic modules in simulation is shown in fig. 5, the support is divided into 10 confluence areas, and each area is divided into 10 supports. The number of components in each partition is distributed as {10,10,10,10,10,10,10,10,10,10 }. And the optimization objective function at this time is:
solving by taking minf (X) as an optimization target, wherein the optimization result of the partition method adopting the photovoltaic module is as follows:
min f(X)＝295.68
the photovoltaic module partition result and the connection result of the photovoltaic modules in each sub-area are shown in fig. 7, at this time, 100 photovoltaic modules in the photovoltaic module square matrix are divided into 4 sub-areas, each sub-area has 25 photovoltaic modules, the 25 photovoltaic modules in each sub-area are sequentially connected, and the total cost of the used cable is the lowest.
In addition, an embodiment of the present invention further provides a partitioning system for a photovoltaic module, and referring to fig. 8, fig. 8 is a schematic functional module diagram of an embodiment of the partitioning of the photovoltaic module according to the present invention. As shown in fig. 8, the partitioning system of the photovoltaic module of the present invention includes:
the partitioning module 10 is configured to perform initial partitioning on the photovoltaic modules based on position parameters of the photovoltaic modules in a preset photovoltaic module matrix to obtain a photovoltaic module set;
a determining module 20, configured to determine a cable function corresponding to each photovoltaic module set, and determine a target cable function corresponding to the preset photovoltaic module matrix based on each cable function;
and the optimizing module 30 is configured to perform parameter optimization on the target cable function based on a cable cost minimization principle to obtain an optimal partition of the photovoltaic module.
Further, the partition system of the photovoltaic module further comprises:
the subarea acquisition module is used for partitioning all the photovoltaic assemblies in the preset photovoltaic assembly square matrix according to the optimal subarea to obtain each subarea;
and the sequential connection module is used for sequentially connecting the photovoltaic modules in the sub-areas through cables.
Further, the partition module 10 includes:
and the partitioning unit is used for partitioning the photovoltaic assembly according to the capacity of a preset header box or a preset string inverter to obtain a photovoltaic assembly set.
Further, the determining module 20 includes:
and the distance determination parameter is used for determining the Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining the cable function corresponding to the photovoltaic module set according to the Manhattan distance.
Further, the determining module 20 further includes:
and the accumulation module is used for accumulating the cable functions to obtain a target cable function corresponding to the preset assembly square matrix.
Further, the optimizing module 30 includes:
and the optimizing unit is used for carrying out parameter optimization on the target cable function through a preset genetic algorithm based on a cable cost minimization principle to obtain the optimal partition of the photovoltaic module.
Further, the partition system of the photovoltaic module further comprises:
and the position parameter derivation module is used for deriving the position parameters of all the photovoltaic modules in the preset module square matrix from preset drawing software.
The specific implementation of each functional module of the partitioning system of the photovoltaic module is basically the same as that of each embodiment of the partitioning method of the photovoltaic module, and is not described herein again.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, where a partition program of a photovoltaic module is stored on the computer-readable storage medium, and when executed by a processor, the partition program of the photovoltaic module implements the steps of the partition method of the photovoltaic module described above.
The embodiments of the partitioning system and the computer-readable storage medium of the photovoltaic module of the present invention can refer to the embodiments of the partitioning method of the photovoltaic module of the present invention, and are not described herein again.
Furthermore, an embodiment of the present invention also provides a computer program product, which includes a computer program that, when being executed by a processor, implements the steps of the method for partitioning a photovoltaic module according to any one of the above embodiments of the method for partitioning a photovoltaic module.
The specific embodiment of the computer program product of the present invention is substantially the same as the embodiments of the partitioning method for a photovoltaic module described above, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method for partitioning a photovoltaic module, the method comprising:
based on position parameters of photovoltaic modules in a preset photovoltaic module square matrix, carrying out initial partitioning on the photovoltaic modules to obtain a photovoltaic module set;
determining a cable function corresponding to the photovoltaic component set, and determining a target cable function corresponding to the preset photovoltaic component square matrix based on the cable function;
and based on a cable cost minimization principle, performing parameter optimization on the target cable function to obtain the optimal partition of the photovoltaic module.
2. The method for partitioning a photovoltaic module according to claim 1, wherein after said step of performing parameter optimization with respect to said target cable function to obtain an optimal partition of said photovoltaic module, further comprising:
according to the optimal partition, all the photovoltaic modules in the preset photovoltaic module square matrix are partitioned to obtain sub-areas;
and sequentially connecting the photovoltaic modules in the sub-areas through cables.
3. The method for partitioning a photovoltaic module according to claim 1, wherein the step of initially partitioning the photovoltaic module to obtain a set of photovoltaic modules comprises:
and partitioning the photovoltaic modules according to the capacity of a preset header box or the capacity of a preset string inverter to obtain a photovoltaic module set.
4. The method for partitioning photovoltaic modules according to claim 1, wherein said step of determining a cable function corresponding to said set of photovoltaic modules comprises:
and determining the Manhattan distance between adjacent photovoltaic modules according to the position parameters of each photovoltaic module in the photovoltaic module set, and determining the cable function corresponding to the photovoltaic module set according to the Manhattan distance.
5. The method for partitioning a photovoltaic module according to claim 1, wherein the step of determining a target cable function corresponding to the preset module matrix based on the cable function comprises:
and accumulating the cable functions to obtain a target cable function corresponding to the preset assembly square matrix.
6. The method for partitioning a photovoltaic module according to claim 1, wherein said step of performing parameter optimization with respect to said target cable function to obtain an optimal partition of said photovoltaic module comprises:
and based on a cable cost minimization principle, performing parameter optimization on the target cable function through a preset genetic algorithm to obtain the optimal partition of the photovoltaic module.
7. The method for partitioning a photovoltaic module according to claim 1, wherein before the step of initially partitioning the photovoltaic module based on the position parameter of the photovoltaic module in the preset photovoltaic module matrix to obtain the photovoltaic module set, the method further comprises:
and deriving the position parameters of all the photovoltaic modules in the preset module square matrix from preset drawing software.
8. A partitioning system for a photovoltaic module, comprising:
the partitioning module is used for initially partitioning the photovoltaic modules based on position parameters of the photovoltaic modules in a preset photovoltaic module matrix to obtain a photovoltaic module set;
the determining module is used for determining a cable function corresponding to the photovoltaic assembly set and determining a target cable function corresponding to the preset photovoltaic assembly square matrix based on the cable function;
and the optimizing module is used for carrying out parameter optimizing on the target cable function based on a cable cost minimization principle to obtain the optimal partition of the photovoltaic module.
9. A terminal device, characterized in that it comprises a memory, a processor and a partitioning program of photovoltaic modules stored on said memory and executable on said processor, said partitioning program of photovoltaic modules implementing, when executed by said processor, the steps of the method of partitioning of photovoltaic modules according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a partitioning program of a photovoltaic module, which when executed by a processor implements the steps of the method of partitioning a photovoltaic module according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210379229.5A CN114819302A (en) | 2022-04-12 | 2022-04-12 | Photovoltaic module partitioning method, system, terminal device and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210379229.5A CN114819302A (en) | 2022-04-12 | 2022-04-12 | Photovoltaic module partitioning method, system, terminal device and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114819302A true CN114819302A (en) | 2022-07-29 |
Family
ID=82534518
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210379229.5A Pending CN114819302A (en) | 2022-04-12 | 2022-04-12 | Photovoltaic module partitioning method, system, terminal device and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114819302A (en) |
-
2022
- 2022-04-12 CN CN202210379229.5A patent/CN114819302A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10652360B2 (en) | Access scheduling method and apparatus for terminal, and computer storage medium | |
| CN106919449B (en) | Scheduling control method of computing task and electronic equipment | |
| CN101604264B (en) | Task scheduling method and system for supercomputer | |
| CN110675471B (en) | Node connection line generation method, device, equipment and storage medium | |
| CN108304256B (en) | Task scheduling method and device with low overhead in edge computing | |
| CN103873534A (en) | Method and device for application cluster migration | |
| CN111064666B (en) | Networking method and device | |
| CN114819302A (en) | Photovoltaic module partitioning method, system, terminal device and medium | |
| CN107634978B (en) | Resource scheduling method and device | |
| CN107491352B (en) | Resource scheduling method and device | |
| CN105207216A (en) | Implementing method and system of service expansion scheme based on of power supply network | |
| CN102186182A (en) | Comprehensive network plan management system and method | |
| CN104360909A (en) | Method and device for processing videos | |
| CN109064382B (en) | Image information processing method and server | |
| CN103501509A (en) | Method and device for balancing loads of radio network controller | |
| CN113626472B (en) | Method and device for processing order data | |
| CN112132271A (en) | Neural network accelerator operation method, architecture and related device | |
| CN113378069B (en) | Main and distribution network automatic drawing method based on intelligent recommendation algorithm | |
| CN112749822B (en) | Method and device for generating route | |
| US9507635B2 (en) | Assigning speculative processes to plurality of CPUs based on calculated maximum number of speculative processes capable of being assigned and other processes assigned to each CPU | |
| CN114172817A (en) | Virtual network function deployment method and system for edge computing | |
| CN103796226A (en) | Network optimizing method and apparatus | |
| CN108683185B (en) | Disconnection impedance calculation apparatus, disconnection impedance calculation system, disconnection impedance calculation method, computer device, and storage medium | |
| CN112183799A (en) | Task allocation method and device for synthesizing task list | |
| CN103117917A (en) | Automatic operating parameter configuration method and system using the same |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |