An internal structure optimization method and system for reducing loss capacity of an energy storage power station

Abstract

The application relates to an internal structure optimization method and system for reducing loss capacity of an energy storage power station, the method comprising the following steps: obtaining an optimal arrangement scheme of storage batteries in the energy storage power station with the minimum loss capacity of the energy storage power station as a target; and arranging the storage batteries in the energy storage power station by using the optimal arrangement scheme of the storage batteries. The technical scheme provided by the application can consider the fault probability model of each unit of the energy storage power station, optimize the arrangement structure of each element in the energy storage power station, achieve the purpose of minimizing the overall loss capacity of the energy storage power station, and greatly reduce the problems of other system faults caused by the loss capacity of the energy storage power station.

Description

Technical Field

[0001] This invention relates to the field of internal structure layout of energy storage power stations, and specifically to a method and system for optimizing the internal structure of energy storage power stations to reduce capacity loss. Background Technology

[0002] With the continuous development of energy storage technology, the advantages of energy storage power stations—such as flexible output adjustment, controllable response speed, and bidirectional charging and discharging—are becoming increasingly apparent. As the grid-connected capacity of various types of energy storage power stations gradually increases, they are playing a crucial role on the power supply side. However, as an emerging technology, energy storage, especially energy storage power stations that use batteries as their primary power source, carries the risk of uncertain failure rates. The inherent failure rates of the batteries, converters, and cable connections within the power station pose a significant challenge to the reliability of the power supply. This can lead to unreliable power supply capacity and other system failures.

[0003] Currently, research on the structural optimization of energy storage power stations, both domestically and internationally, often focuses on optimizing the overall capacity and site selection of energy storage power stations. However, there is limited understanding of the failure rate of the energy storage power stations themselves. This research is limited to modeling and identifying the failure rates of individual components such as batteries or cables within the energy storage power station, lacking modeling and analysis of the overall failure rate of the energy storage power station. Furthermore, no effective technical improvement or optimization schemes have been proposed to reduce the overall capacity loss of energy storage power stations in order to control the overall failure rate. The arrangement of internal components of an energy storage power station has a significant impact on its capacity loss, and there is currently a lack of detailed requirements for the arrangement of internal components. In other words, no consideration has been given to how to reduce capacity loss by optimizing the structure of the energy storage power station itself. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide an internal structure optimization method for reducing capacity loss in energy storage power stations. This method optimizes the arrangement of components within the energy storage power station, taking into account the failure probability model of each unit, thereby minimizing the overall capacity loss of the energy storage power station and significantly mitigating other system failures caused by capacity loss.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] The purpose of this invention is to provide a method for optimizing the internal structure of an energy storage power station to reduce capacity loss. The improvement lies in that the method includes:

[0007] The goal is to obtain the optimal battery layout scheme in the energy storage power station with the objective of minimizing the loss capacity of the energy storage power station.

[0008] The optimal arrangement scheme of the batteries in the energy storage power station is used to arrange the batteries in the energy storage power station.

[0009] The arrangement scheme includes: the number of rows and columns of battery units, and the number of batteries in each battery unit.

[0010] Preferably, the step of obtaining the optimal battery layout scheme in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station includes:

[0011] An optimization model for the arrangement of batteries in an energy storage power station is established with the goal of minimizing the loss capacity of the energy storage power station.

[0012] Solve the optimization model of the battery layout scheme in the energy storage power station to obtain the optimal battery layout scheme in the energy storage power station.

[0013] Furthermore, the objective function in the optimization model for the battery layout scheme in the energy storage power station is determined by the following formula:

[0014]

[0015] In the above formula, B represents the energy storage power station's loss capacity. The failure rate of battery system components, For the failure rate of cable components, For the failure rate of transformer components, The preset total capacity of the energy storage power station, This refers to the total capacity of the battery system components.

[0016] Furthermore, the failure rate of battery system components is determined by the following formula. :

[0017]

[0018] In the above formula, The failure rate of a single battery. It is the fault time interval of a single battery, e is a natural constant, a is the number of rows of battery cells, and b is the number of columns of battery cells.

[0019] Furthermore, the failure rate of the cable components is determined by the following formula. :

[0020]

[0021] In the above formula, The number of cable failures. The exposure time of the faulty line. This represents the length of the cable.

[0022] Furthermore, the failure rate of transformer components is determined by the following formula. :

[0023]

[0024] In the above formula, Let be the number of transformer failures during time period t. For transformers in Number of failures during a given period The time interval between adjacent time periods. T The total number of time periods. .

[0025] Furthermore, the constraints in the internal structure optimization model of the energy storage power station include:

[0026] The capacity constraints of an energy storage power station are determined by the following formula:

[0027]

[0028] In the above formula, The preset total capacity of the energy storage power station, Let be the capacity of the i-th battery in the battery system, 'a' be the number of rows of battery cells, 'b' be the number of columns of battery cells, and 'k' be the number of batteries in each battery cell. ;

[0029] The output constraints of battery system components are determined by the following formula:

[0030]

[0031] In the above formula, The lower limit of the output of battery system components. This is the upper limit of the battery's output. For the output of battery system components;

[0032] The cable transmission power constraint condition is determined by the following formula:

[0033]

[0034] In the above formula, This represents the lower limit of the cable's transmission power. This is the upper limit of the cable's transmission power. The power transmitted by the cable.

[0035] Preferably, the step of arranging the batteries in the energy storage power station using the optimal battery layout scheme includes:

[0036] Each The end of the feeder cable in each battery unit branch is connected to the grid connection point of the energy storage power station.

[0037] Among them, the battery unit branch is Each battery unit is connected to a feeder cable;

[0038] The battery unit includes: One storage battery and its corresponding AC / DC converter and isolation transformer;

[0039] The Each battery is connected to the low-voltage AC terminal of the isolation transformer via its corresponding AC / DC converter, and the medium-voltage AC terminal of the isolation transformer is connected to the feeder cable.

[0040] This represents the number of rows of battery cells in the optimal layout. This represents the number of columns for the battery cells in the optimal layout. This represents the number of batteries in each battery unit in the optimal battery layout.

[0041] Based on the same inventive concept, the present invention also provides an internal structure optimization system for reducing capacity loss in an energy storage power station, wherein the improvement is that the system includes:

[0042] Acquisition module: Used to obtain the optimal battery layout scheme in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station;

[0043] Arrangement module: used to arrange the batteries in the energy storage power station using the optimal arrangement scheme of the batteries in the energy storage power station;

[0044] The arrangement scheme includes: the number of rows and columns of battery units, and the number of batteries in each battery unit.

[0045] Preferably, the acquisition module is specifically used for:

[0046] An optimization model for the arrangement of batteries in an energy storage power station is established with the goal of minimizing the loss capacity of the energy storage power station.

[0047] Solve the optimization model of the battery layout scheme in the energy storage power station to obtain the optimal battery layout scheme in the energy storage power station.

[0048] Compared with the closest existing technology, the present invention has the following advantages:

[0049] The technical solution provided by this invention proposes a method and system for optimizing the internal structure of an energy storage power station to reduce capacity loss. First, the optimal arrangement of batteries in the energy storage power station is obtained with the goal of minimizing capacity loss. Then, the batteries in the energy storage power station are arranged using the optimal arrangement. This solution can minimize the overall capacity loss of the energy storage power station by optimizing the arrangement of each component, taking into account the failure probability model of each unit in the energy storage power station. This greatly reduces the problems of other system failures caused by capacity loss in the energy storage power station. Attached Figure Description

[0050] Figure 1 This is a flowchart of an energy storage power station internal structure optimization method to reduce capacity loss provided by the present invention;

[0051] Figure 2 This is a topological diagram of the internal structure of the energy storage power station in an embodiment of the present invention;

[0052] Figure 3 This is a Venn diagram of the objective function for the loss capacity of the energy storage power station in this embodiment of the invention;

[0053] Figure 4 This is a schematic diagram illustrating the variation of energy storage power station loss capacity with parameters and time in an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of an internal structure optimization system for energy storage power stations that reduces capacity loss, provided by the present invention. Detailed Implementation

[0055] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] To address the shortcomings of existing fault rate modeling and fault identification methods, such as the inability to guarantee the lost capacity of energy storage power stations and high failure rates, this invention provides a method for optimizing the internal structure of energy storage power stations to reduce lost capacity. First, the internal structure of the energy storage power station and the components to be optimized are established sequentially. a , b , kAfter selecting the parameters and model numbers of each component, an independent failure rate model for each component of the energy storage power station can be obtained. With the goal of minimizing the energy storage power station's capacity loss, a model is established based on the approach of calculating the area of ​​a Venn diagram. a , b , k The objective function for the energy storage power station's loss capacity is defined by parameters, and with reference to constraints, an optimization model for the internal structure of the energy storage power station is completed. Finally, the optimization model is solved using the MATLAB / fmincon function to obtain the final optimal solution. a , b , k Based on the parameter results, the optimization design is completed, as follows: Figure 1 As shown, the method includes:

[0058] Step (1) Obtain the optimal battery layout scheme in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station;

[0059] Step (2) Arrange the batteries in the energy storage power station using the optimal arrangement scheme of the batteries in the energy storage power station;

[0060] Specifically, in step (1), an optimization model for the arrangement of batteries in the energy storage power station is first established with the goal of minimizing the loss capacity of the energy storage power station.

[0061] In reality, when a single battery in the battery system of an energy storage power station fails, the total power output of the battery system will decrease. When a cable component fails, the battery connected to the cable will be disconnected, resulting in a decrease in the power output of the battery system. When the transformer component at the grid connection point of the energy storage power station fails, the power output of the battery system will be interrupted. It can be seen that the change in the loss capacity of an energy storage power station is related to the power output of the battery system components. Therefore, when each component of the energy storage power station fails, the failure rate of each component determines the size of the total loss capacity of the energy storage power station.

[0062] In the embodiments provided by the present invention, such as Figure 2 As shown, the loss capacity of an energy storage power station includes the failure rates of three components, each with an independent failure rate. Minimizing the total loss capacity of the energy storage power station is equivalent to minimizing the area of ​​the Venn diagram. Based on the Venn diagram, the overlapping areas of each component in the energy storage power station are first calculated using the principles of probability addition and multiplication on the basis of independent events. Then, these areas are multiplied by the preset total capacity of the energy storage power station and the total capacity of the battery system components, respectively. Finally, the results are summed to obtain the minimum loss capacity of the energy storage power station.

[0063] Because the failure rate of each component in an energy storage power station determines the total loss capacity of the energy storage power station, it is necessary to arrange the batteries in the energy storage power station according to the optimal a, b, k parameter arrangement scheme to minimize the failure rate of each component in the energy storage power station, thereby achieving the goal of minimizing the loss capacity of the energy storage power station.

[0064] Based on the above analysis, the objective function in the optimization model of battery layout scheme in energy storage power stations can be obtained.

[0065] In the embodiments provided by this invention, the objective function in the optimization model for the battery layout scheme in an energy storage power station can be determined by the following formula:

[0066]

[0067] In the above formula, B represents the energy storage power station's loss capacity. The failure rate of battery system components, For the failure rate of cable components, For the failure rate of transformer components, The preset total capacity of the energy storage power station, This refers to the total capacity of the battery system components.

[0068] In the embodiments provided by this invention, the objective function in the optimization model of the battery layout scheme in the above-mentioned energy storage power station is based on the addition and multiplication principles of probability theory. This only represents the capacity loss when the battery system components and the cable components connected to the battery system components of the energy storage power station fail. The above formula represents the capacity loss when the transformer, battery system components, and cable components connected to the battery system components at the grid connection point of the energy storage power station fail. The sum of the above formulas indicates that the total capacity loss of the energy storage power station will change with the failure rate of each of its internal components.

[0069] Furthermore, the failure rate of battery system components is determined by the following formula. :

[0070]

[0071] In the above formula, The failure rate of a single battery. It is the fault time interval of a single battery, e is a natural constant, a is the number of rows of battery cells, and b is the number of columns of battery cells.

[0072] The failure rate of cable components is determined by the following formula. :

[0073]

[0074] In the above formula, The number of cable failures. The exposure time of the faulty line. This represents the length of the cable.

[0075] The failure rate of transformer components is determined by the following formula. :

[0076]

[0077] In the above formula, Let be the number of transformer failures during time period t. For transformers in Number of failures during a given period The time interval between adjacent time periods. T The total number of time periods. .

[0078] In the embodiments provided by this invention, the constraints in the internal structure optimization model of the energy storage power station include:

[0079] The capacity constraints of an energy storage power station are determined by the following formula:

[0080]

[0081] In the above formula, The preset total capacity of the energy storage power station, Let be the capacity of the i-th battery in the battery system, 'a' be the number of rows of battery cells, 'b' be the number of columns of battery cells, and 'k' be the number of batteries in each battery cell. ;

[0082] In the embodiments provided by the present invention, for a specific energy storage power station, there is a capacity constraint, that is, the total capacity of the batteries contained inside should meet the total capacity requirement of the energy storage power station. Therefore, the above formula means that the total capacity of the batteries arranged in a×b×k must be equal to the set total capacity of the energy storage power station. The above constraint is an equality constraint.

[0083] The output constraints of battery system components are determined by the following formula:

[0084]

[0085] In the above formula, The lower limit of the output of battery system components. This is the upper limit of the battery's output. For the output of battery system components;

[0086] The cable transmission power constraint condition is determined by the following formula:

[0087]

[0088] In the above formula, This represents the lower limit of the cable's transmission power. This is the upper limit of the cable's transmission power. Power is transmitted through the cable.

[0089] In the embodiments provided by the present invention, the transmission power of each line of the energy storage power station is limited, and each battery itself has upper and lower limits of output. Therefore, the constraints of the upper and lower limits of battery output and the constraints of the upper and lower limits of cable transmission power can be derived.

[0090] Based on the above-mentioned optimization model of battery layout in the energy storage power station, the optimization model of battery layout in the energy storage power station is then solved to obtain the optimal layout scheme of batteries in the energy storage power station.

[0091] In the embodiments provided by this invention, the optimal battery layout scheme in the energy storage power station given in step (1) considers the failure probability of each unit in the energy storage power station and gives the optimal parameter selection for a, b, and k. In the technical solution provided by this invention, step (2) arranges the internal structure of the energy storage power station based on this, such as... Figure 3 As shown, firstly, the connection between k groups of batteries and the converter in each battery-converter unit is formed to realize the inverter output of electrical energy. Secondly, each battery-converter unit is arranged in a row and column form as a basic structure of a rows and b columns. Then, the inverter output side of the battery-converter unit in a row and b columns is stepped up by a transformer and then sent to the grid connection point of the energy storage power station through a feeder cable. Finally, after being stepped up by the transformer at the grid connection point of the energy storage power station, it is sent to the high-voltage AC transmission line to complete the power transmission. Specifically, step (2) may include:

[0092] Each The end of the feeder cable in each battery unit branch is connected to the grid connection point of the energy storage power station.

[0093] Among them, the battery unit branch is Each battery unit is connected to a feeder cable;

[0094] The battery unit includes: One storage battery and its corresponding AC / DC converter and isolation transformer;

[0095] The Each battery is connected to the low-voltage AC terminal of the isolation transformer via its corresponding AC / DC converter, and the medium-voltage AC terminal of the isolation transformer is connected to the feeder cable.

[0096] This represents the number of rows of battery cells in the optimal layout. This represents the number of columns for the battery cells in the optimal layout. This represents the number of batteries in each battery unit in the optimal battery layout.

[0097] In the embodiments provided by the present invention, it is possible to, for example Figure 4 The above solution is verified in the application scenario shown. k Taking 2 as an example, the loss capacity of an energy storage power station varies with parameters. a , b The advantages and significance of this invention are illustrated using a diagram showing the changes over time. Figure 4 The vertical axis represents the energy storage power station's failure loss capacity, which is proportional to the total failure rate of the energy storage power station, in order to optimize the results. a =50, b Taking the minimum failure loss capacity achieved when the value is 2 as an example, the optimal parameter combination can be obtained. The maximum percentage reduction in failure loss capacity in the first four years reaches 55.56%. Therefore, this invention optimizes the design structural parameters. a , b, k It can effectively reduce the capacity loss when the energy storage power station fails, and greatly alleviate other system failure problems caused by the capacity loss of the energy storage power station.

[0098] In summary, the internal structure optimization method for reducing capacity loss in an energy storage power station proposed in this invention can minimize the overall capacity loss of the energy storage power station by optimizing the arrangement of various components within the energy storage power station, taking into account the failure probability model of each unit. This greatly alleviates the problem of other system failures caused by the capacity loss of the energy storage power station.

[0099] Based on the same inventive concept, this invention also provides an internal structure optimization system for energy storage power stations to reduce capacity loss, such as... Figure 5 As shown, the system includes:

[0100] Acquisition module: Used to obtain the optimal battery layout scheme in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station;

[0101] Arrangement module: used to arrange the batteries in the energy storage power station using the optimal arrangement scheme of the batteries in the energy storage power station;

[0102] The arrangement scheme includes: the number of rows and columns of battery units, and the number of batteries in each battery unit.

[0103] Preferably, the acquisition module is specifically used for:

[0104] An optimization model for the arrangement of batteries in an energy storage power station is established with the goal of minimizing the loss capacity of the energy storage power station.

[0105] Solve the optimization model of the battery layout scheme in the energy storage power station to obtain the optimal battery layout scheme in the energy storage power station.

[0106] Furthermore, the objective function in the optimization model for the battery layout scheme in the energy storage power station is determined by the following formula:

[0107]

[0108] In the above formula, B represents the energy storage power station's loss capacity. The failure rate of battery system components, For the failure rate of cable components, For the failure rate of transformer components, The preset total capacity of the energy storage power station, This refers to the total capacity of the battery system components.

[0109] Furthermore, the failure rate of battery system components is determined by the following formula. :

[0110]

[0111] In the above formula, The failure rate of a single battery. It is the fault time interval of a single battery, e is a natural constant, a is the number of rows of battery cells, and b is the number of columns of battery cells.

[0112] Furthermore, the failure rate of the cable components is determined by the following formula. :

[0113]

[0114] In the above formula, The number of cable failures. The exposure time of the faulty line. This represents the length of the cable.

[0115] Furthermore, the failure rate of transformer components is determined by the following formula. :

[0116]

[0117] In the above formula, Let be the number of transformer failures during time period t. For transformers in Number of failures during a given period The time interval between adjacent time periods. T The total number of time periods. .

[0118] Furthermore, the constraints in the internal structure optimization model of the energy storage power station include:

[0119] The capacity constraints of an energy storage power station are determined by the following formula:

[0120]

[0121] In the above formula, The preset total capacity of the energy storage power station, Let be the capacity of the i-th battery in the battery system, 'a' be the number of rows of battery cells, 'b' be the number of columns of battery cells, and 'k' be the number of batteries in each battery cell. ;

[0122] The output constraints of battery system components are determined by the following formula:

[0123]

[0124] In the above formula, The lower limit of the output of battery system components. This is the upper limit of the battery's output. For the output of battery system components;

[0125] The cable transmission power constraint condition is determined by the following formula:

[0126]

[0127] In the above formula, This represents the lower limit of the cable's transmission power. This is the upper limit of the cable's transmission power. The power transmitted by the cable.

[0128] Preferably, the arrangement module is specifically used for:

[0129] Each The end of the feeder cable in each battery unit branch is connected to the grid connection point of the energy storage power station.

[0130] Among them, the battery unit branch is Each battery unit is connected to a feeder cable;

[0131] The battery unit includes: One storage battery and its corresponding AC / DC converter and isolation transformer;

[0132] The k batteries are connected to the low-voltage AC terminal of the isolation transformer via their respective AC / DC converters, and the medium-voltage AC terminal of the isolation transformer is connected to the feeder cable.

[0133] This represents the number of rows of battery cells in the optimal layout. This represents the number of columns for the battery cells in the optimal layout. This represents the number of batteries in each battery unit in the optimal battery layout.

[0134] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0136] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0137] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the internal structure of an energy storage power station to reduce capacity loss, characterized in that, The method includes: The goal is to obtain the optimal battery layout scheme in the energy storage power station with the objective of minimizing the loss capacity of the energy storage power station. The optimal arrangement scheme of the batteries in the energy storage power station is used to arrange the batteries in the energy storage power station. The arrangement scheme includes: the number of rows and columns of the battery cells, and the number of batteries in each battery cell; The method of obtaining the optimal battery layout scheme in an energy storage power station with the goal of minimizing the loss capacity of the energy storage power station includes: An optimization model for the arrangement of batteries in an energy storage power station is established with the goal of minimizing the loss capacity of the energy storage power station. Solve the optimization model of the battery layout scheme in the energy storage power station to obtain the optimal battery layout scheme in the energy storage power station; The objective function in the optimization model for the battery layout scheme in an energy storage power station is determined by the following formula: In the above formula, B represents the energy storage power station's loss capacity. The failure rate of battery system components, For the failure rate of cable components, For the failure rate of transformer components, The preset total capacity of the energy storage power station, This refers to the total capacity of the battery system components; The capacity constraints of an energy storage power station are determined by the following formula: In the above formula, Let be the capacity of the i-th battery in the battery system, 'a' be the number of rows of battery cells, 'b' be the number of columns of battery cells, and 'k' be the number of batteries in each battery cell. .

2. The method as described in claim 1, characterized in that, Determine the failure rate of battery system components using the following formula. : In the above formula, The failure rate of a single battery. It is the fault time interval of a single battery, e is a natural constant, a is the number of rows of battery cells, and b is the number of columns of battery cells.

3. The method as described in claim 1, characterized in that, The failure rate of cable components is determined by the following formula. : In the above formula, The number of cable failures. The exposure time of the faulty line. This represents the length of the cable.

4. The method as described in claim 1, characterized in that, The failure rate of transformer components is determined by the following formula. : In the above formula, Let be the number of transformer failures during time period t. For transformers in Number of failures during a given period The time interval between adjacent time periods. T The total number of time periods. .

5. The method as described in claim 1, characterized in that, The constraints in the optimization model for the internal structure of the energy storage power station include: The output constraints of battery system components are determined by the following formula: In the above formula, The lower limit of the output of battery system components. This is the upper limit of the battery's output. For the output of battery system components; The cable transmission power constraint condition is determined by the following formula: In the above formula, This represents the lower limit of the cable's transmission power. This is the upper limit of the cable's transmission power. The power transmitted by the cable.

6. The method as described in claim 1, characterized in that, The arrangement of batteries in the energy storage power station using the optimal battery layout scheme includes: Each The end of the feeder cable in each battery unit branch is connected to the grid connection point of the energy storage power station. Among them, the battery unit branch is Each battery unit is connected to a feeder cable; The battery unit includes: One storage battery and its corresponding AC / DC converter and isolation transformer; The Each battery is connected to the low-voltage AC terminal of the isolation transformer via its corresponding AC / DC converter, and the medium-voltage AC terminal of the isolation transformer is connected to the feeder cable. This represents the number of rows of battery cells in the optimal layout. This represents the number of columns for the battery cells in the optimal layout. This represents the number of batteries in each battery unit in the optimal battery layout.

7. An internal structure optimization system for energy storage power stations to reduce capacity loss, used to implement the method as described in claim 1, characterized in that, The system includes: Acquisition module: Used to obtain the optimal battery layout scheme in the energy storage power station with the goal of minimizing the loss capacity of the energy storage power station; Arrangement module: used to arrange the batteries in the energy storage power station using the optimal arrangement scheme of the batteries in the energy storage power station; The arrangement scheme includes: the number of rows and columns of battery units, and the number of batteries in each battery unit.

8. The system as described in claim 7, characterized in that, The acquisition module is specifically used for: An optimization model for the arrangement of batteries in an energy storage power station is established with the goal of minimizing the loss capacity of the energy storage power station. Solve the optimization model of the battery layout scheme in the energy storage power station to obtain the optimal battery layout scheme in the energy storage power station.

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