Construction Method of Optimization Configuration Model for Sodium-Ion Battery Energy Storage System

Abstract

The present disclosure provides a method for constructing an optimized configuration model of a sodium-ion battery energy storage system. The method includes: initializing model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection mode, charge and discharge strategy, and control logic; constructing a system cost function and a system energy efficiency function according to the model configuration parameters; constructing a system constraint function according to the model configuration parameters; and constructing an optimized configuration model of the sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function. By implementing the method of the present disclosure, the practicability and reliability of the obtained optimized configuration model of the sodium-ion battery energy storage system can be ensured by using the system cost function and the system energy efficiency function as objective functions and combining the system constraint function, thereby effectively improving the optimization effect of the obtained optimized configuration model of the sodium-ion battery energy storage system on the sodium-ion battery energy storage system.

Description

Technical Field

[0001] The present disclosure relates to the technical field of energy storage, and particularly to a method for constructing an optimized configuration model of a sodium-ion battery energy storage system. Background Art

[0002] Battery energy storage is an important part of new energy storage. Against the background of the skyrocketing price of lithium-ion batteries due to the shortage of lithium resources, the increasingly mature sodium-ion battery has come into people's sight. Sodium resources are abundant and inexpensive, and sodium-ion batteries have excellent low-temperature performance and rate performance, and are compatible with lithium-ion battery production lines, and can be used as an important strategic reserve technology for lithium-ion batteries.

[0003] At present, the commercialization level of sodium-ion batteries is relatively low, and the installed capacity of sodium-ion battery energy storage systems is only in the order of dozens of megawatt-hours. Sodium-ion batteries have excellent low-temperature performance and rate performance, but their battery life, system capacity, system efficiency, etc. are slightly inferior to those of lithium-ion batteries, and multiple indicators restrict each other, making it difficult to achieve the optimal goal of multiple targets simultaneously.

[0004] In related technologies, the parameter configuration of sodium-ion battery energy storage systems has poor effects, affecting the overall performance of sodium-ion battery energy storage systems. Summary of the Invention

[0005] The present disclosure aims to solve at least one of the technical problems in related technologies to some extent.

[0006] To this end, the purpose of the present disclosure is to propose a method, device, computer device and storage medium for constructing an optimized configuration model of a sodium-ion battery energy storage system, which can use the system cost function and the system energy efficiency function as objective functions and combine the system constraint function to ensure the practicability and reliability of the obtained optimized configuration model of the sodium-ion battery energy storage system, thereby effectively improving the optimization configuration effect of the obtained optimized configuration model of the sodium-ion battery energy storage system for the sodium-ion battery energy storage system.

[0007] To achieve the above object, the method for constructing an optimized configuration model of a sodium-ion battery energy storage system proposed in the first aspect embodiment of the present disclosure includes:

[0008] Initializing model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic;

[0009] Constructing a system cost function and a system energy efficiency function according to the model configuration parameters;

[0010] Constructing a system constraint function according to the model configuration parameters;

[0011] Based on the system cost function, the system energy efficiency function, and the system constraint function, an optimized configuration model of the sodium-ion battery energy storage system is constructed.

[0012] To achieve the above object, an apparatus for constructing an optimized configuration model of a sodium-ion battery energy storage system according to an embodiment of the second aspect of the present disclosure includes:

[0013] A processing module, configured to initialize model configuration parameters, where the model configuration parameters include: battery parameters, the number of module clusters, connection modes, charge and discharge strategies, and control logics;

[0014] A first construction module, configured to construct a system cost function and a system energy efficiency function according to the model configuration parameters;

[0015] A second construction module, configured to construct a system constraint function according to the model configuration parameters;

[0016] A third construction module, configured to construct an optimized configuration model of the sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function.

[0017] A computer device according to an embodiment of the third aspect of the present disclosure includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method for constructing an optimized configuration model of the sodium-ion battery energy storage system according to the embodiment of the first aspect of the present disclosure is implemented.

[0018] An embodiment of the fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method for constructing an optimized configuration model of the sodium-ion battery energy storage system according to the embodiment of the first aspect of the present disclosure is implemented.

[0019] An embodiment of the fifth aspect of the present disclosure provides a computer program product. When the instructions in the computer program product are executed by a processor, the method for constructing an optimized configuration model of the sodium-ion battery energy storage system according to the embodiment of the first aspect of the present disclosure is executed.

[0020] The method, device, computer equipment and storage medium for constructing an optimized configuration model of a sodium-ion battery energy storage system provided by the present disclosure initialize the model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge-discharge strategy and control logic; construct a system cost function and a system energy efficiency function according to the model configuration parameters; construct a system constraint function according to the model configuration parameters; and construct an optimized configuration model of a sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function and the system constraint function. Thus, the practicability and reliability of the obtained optimized configuration model of a sodium-ion battery energy storage system can be ensured by using the system cost function and the system energy efficiency function as objective functions and combining the system constraint function, thereby effectively improving the optimization effect of the obtained optimized configuration model of a sodium-ion battery energy storage system on the sodium-ion battery energy storage system.

[0021] Additional aspects and advantages of the present disclosure will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present disclosure will become apparent and be readily understood from the following description of the embodiments in conjunction with the accompanying drawings, where:

[0023] Figure 1 is a flowchart of a method for constructing an optimized configuration model of a sodium-ion battery energy storage system proposed in an embodiment of the present disclosure;

[0024] Figure 2 is a flowchart of a method for constructing an optimized configuration model of a sodium-ion battery energy storage system proposed in another embodiment of the present disclosure;

[0025] Figure 3 is a flowchart of a process for solving the Pareto optimal solution set using NSGA-II proposed according to the present disclosure;

[0026] Figure 4 is a structural diagram of a device for constructing an optimized configuration model of a sodium-ion battery energy storage system proposed in an embodiment of the present disclosure;

[0027] Figure 5 shows a block diagram of an exemplary computer equipment suitable for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Embodiments of the present disclosure will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary only for explaining the present disclosure and should not be construed as a limitation of the present disclosure. On the contrary, the embodiments of the present disclosure include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0029] Figure 1 is a schematic flowchart of a method for constructing an optimized configuration model of a sodium-ion battery energy storage system proposed in an embodiment of the present disclosure.

[0030] It should be noted that the execution subject of the method for constructing the optimized configuration model of the sodium-ion battery energy storage system in this embodiment is a device for constructing the optimized configuration model of the sodium-ion battery energy storage system. This device can be implemented in software and / or hardware and can be configured in a computer device. The computer device can include, but is not limited to, a terminal, a server, etc. For example, the terminal can be a mobile phone, a personal digital assistant, etc.

[0031] As Figure 1 shown, the method for constructing the optimized configuration model of the sodium-ion battery energy storage system includes:

[0032] S101: Initialize the model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic.

[0033] Among them, the model configuration parameters can refer to the relevant parameters of the performance prediction model of the sodium-ion battery energy storage system.

[0034] Among them, the battery parameters can refer to the relevant parameters of the batteries configured in the sodium-ion battery energy storage system. For example, they can include rated capacity, rated voltage, etc., and are not limited thereto.

[0035] In the embodiments of the present disclosure, multiple batteries can be combined and configured into battery modules, and multiple modules can be jointly configured into module clusters.

[0036] Among them, the connection method can refer to the connection method between different batteries in the sodium-ion battery energy storage system, such as series connection, parallel connection, etc., and is not limited thereto.

[0037] Among them, the charge and discharge strategy can be used to describe the control strategy of the sodium-ion battery energy storage system during the charge and discharge process, such as charging power, charging cut-off voltage, discharging power, discharging cut-off voltage, etc., and is not limited thereto.

[0038] Among them, the control logic can be used to describe the control strategy for the entire sodium-ion battery energy storage system, such as the temperature control strategy, continuous working duration, etc., without limitation thereto.

[0039] That is to say, in the embodiments of the present disclosure, before constructing the optimization configuration model of the sodium-ion battery energy storage system, the model configuration parameters can be initialized first, so as to provide a reliable parameter adjustment object for subsequent optimization configuration.

[0040] S102: Construct a system cost function and a system energy efficiency function according to the model configuration parameters.

[0041] Among them, the system cost function can be used to describe the change situation of the configuration cost of the sodium-ion battery energy storage system following one or more parameters in the model configuration parameters.

[0042] Among them, the system energy efficiency function can be used to indicate the change situation of the system energy efficiency function of the sodium-ion battery energy storage system following one or more parameters in the model configuration parameters.

[0043] That is to say, in the embodiments of the present disclosure, a system cost function and a system energy efficiency function can be constructed according to the model configuration parameters as the objective functions in the process of constructing the optimization configuration model of the sodium-ion battery energy storage system.

[0044] S103: Construct a system constraint function according to the model configuration parameters.

[0045] Among them, the system constraint function can be used to constrain the relevant parameters in the process of constructing the optimization configuration model of the sodium-ion battery energy storage system.

[0046] It can be understood that in the process of optimizing the configuration of the sodium-ion battery energy storage system, it is necessary to ensure that the values of the relevant system parameters conform to the normal value range. Therefore, it is necessary to construct a system constraint function according to the model configuration parameters to ensure the practicability and reliability of the obtained optimization configuration model of the sodium-ion battery energy storage system.

[0047] S104: Based on the system cost function, the system energy efficiency function and the system constraint function, construct an optimization configuration model of the sodium-ion battery energy storage system.

[0048] Among them, the optimization configuration model of the sodium-ion battery energy storage system refers to a model that adjusts parameters such as battery parameters, the number of module clusters, connection methods, charge and discharge strategies, and control logic to obtain the optimal configuration of the sodium-ion battery energy storage system.

[0049] In the embodiments of the present disclosure, when constructing an optimal configuration model for a sodium-ion battery energy storage system based on a system cost function, a system energy efficiency function, and a system constraint function, the fast elitist multi-objective genetic algorithm (NSGA-II) can be used to solve the Pareto optimal solution set, and according to the actual requirements of the project, an optimal control strategy can be obtained from the Pareto optimal solution set. The optimization objectives of the optimal configuration model for the sodium-ion battery energy storage system may include the lowest system cost and the maximum system energy efficiency.

[0050] In this embodiment, by initializing the model configuration parameters, where the model configuration parameters include: battery parameters, the number of module clusters, connection methods, charge and discharge strategies, and control logic; according to the model configuration parameters, a system cost function and a system energy efficiency function are constructed; according to the model configuration parameters, a system constraint function is constructed; based on the system cost function, the system energy efficiency function, and the system constraint function, an optimal configuration model for the sodium-ion battery energy storage system is constructed. Thus, the system cost function and the system energy efficiency function can be used as the objective functions and combined with the system constraint function to ensure the practicability and reliability of the obtained optimal configuration model for the sodium-ion battery energy storage system, thereby effectively improving the optimization effect of the obtained optimal configuration model for the sodium-ion battery energy storage system.

[0051] Figure 2 It is a schematic flowchart of a method for constructing an optimal configuration model for a sodium-ion battery energy storage system proposed in another embodiment of the present disclosure.

[0052] As Figure 2 shown, the method for constructing the optimal configuration model for the sodium-ion battery energy storage system includes:

[0053] S201: Initialize the model configuration parameters, where the model configuration parameters include: battery parameters, the number of module clusters, connection methods, charge and discharge strategies, and control logic.

[0054] For the description of S201, reference can be specifically made to the above embodiments and will not be elaborated here.

[0055] S202: Construct a battery cost function according to the battery parameters, charge and discharge strategies, and control logic.

[0056] Among them, the battery cost function can be used to describe the change of the battery configuration cost with the battery parameters, charge and discharge strategies, and control logic.

[0057] In the embodiments of the present disclosure, when constructing a battery cost function according to the battery parameters, charge and discharge strategies, and control logic, the association information between the battery parameters, charge and discharge strategies, and control logic and the battery cost can be determined respectively, and then the battery cost function can be constructed according to the association information.

[0058] S203: Construct an integrated cost function based on battery parameters, the number of module clusters, connection methods, charge-discharge strategies, and control logic.

[0059] Among them, the integration cost refers to the cost of integrating the sodium-ion battery energy storage system. The integrated cost function can be used to describe the correlation between battery parameters, the number of module clusters, connection methods, charge-discharge strategies, and control logic and the integration cost.

[0060] S204: Based on the battery cost function and the integrated cost function, construct a system cost function.

[0061] In the embodiments of the present disclosure, when constructing the system cost function based on the battery cost function and the integrated cost function, the battery cost function and the integrated cost function can be added together to obtain the system cost function.

[0062] That is to say, in the embodiments of the present disclosure, the battery cost function can be constructed according to battery parameters, charge-discharge strategies, and control logic; the integrated cost function can be constructed according to battery parameters, the number of module clusters, connection methods, charge-discharge strategies, and control logic; and the system cost function can be constructed based on the battery cost function and the integrated cost function. Thus, by combining the battery cost function and the integrated cost function, the indication accuracy of the obtained system cost function for the optimization configuration cost of the sodium-ion battery energy storage system can be effectively improved.

[0063] S205: According to the model configuration parameters, construct a battery unit energy efficiency function and a non-battery system integration efficiency function.

[0064] Among them, the battery unit energy efficiency refers to the energy conversion efficiency of a single battery unit or battery pack, that is, the energy ratio between input and output. It is usually expressed as a percentage or a decimal and is used to measure the loss of the battery during the process of storing and releasing energy.

[0065] Among them, the battery unit energy efficiency function can be used to describe the correlation between one or more parameters in the model configuration parameters and the battery unit energy efficiency.

[0066] Among them, the non-battery system integration efficiency can refer to the energy conversion and transmission efficiency of other components and devices (such as inverters, charge-discharge controllers, sensors, cooling systems, etc.) in the system except for the battery itself.

[0067] Among them, the non-battery system integration efficiency function can be used to describe the correlation between one or more parameters in the model configuration parameters and the non-battery system integration efficiency.

[0068] Optionally, in some embodiments, when constructing the energy efficiency function of the battery cell according to the model configuration parameters, it may be to determine the system material characteristics according to the model configuration parameters, and construct a first function based on the system material characteristics, where the first function is used to indicate the association information between the system material characteristics and the energy efficiency of the battery cell; determine the working voltage according to the model configuration parameters, and construct a second function based on the working voltage, where the second function is used to indicate the association information between the working voltage and the energy efficiency of the battery cell; construct the energy efficiency function of the battery cell based on the first function and the second function. Thus, the obtained energy efficiency function of the battery cell can accurately indicate the association information between the energy efficiency of the battery cell and the system material characteristics and the working voltage, thereby ensuring the practicality of the energy efficiency function of the battery cell in the subsequent model construction process.

[0069] Among them, the system material characteristics may be information used to describe the material characteristics of the sodium-ion battery energy storage system determined according to one or more parameters in the model configuration parameters in the embodiments of the present disclosure.

[0070] Among them, the working voltage may be the voltage of the sodium-ion battery energy storage system in the working state determined according to one or more parameters in the model configuration parameters in the embodiments of the present disclosure.

[0071] Optionally, in some embodiments, when constructing the integrated efficiency function of the non-battery system according to the model configuration parameters, it may be to determine the system energy storage conversion strategy according to the model configuration parameters, and construct a third function based on the system energy storage conversion strategy, where the third function is used to indicate the association information between the system energy storage conversion strategy and the integrated efficiency of the non-battery system; determine the system integration architecture according to the model configuration parameters, and construct a fourth function based on the system integration architecture, where the fourth function is used to indicate the association information between the system integration architecture and the integrated efficiency of the non-battery system, and construct the integrated efficiency function of the non-battery system based on the third function and the fourth function. Thus, the accuracy and reliability of the obtained integrated efficiency function of the non-battery system can be ensured by combining the system energy storage conversion strategy and the system integration architecture.

[0072] Among them, the system energy storage conversion strategy refers to how the battery energy storage system manages and schedules the charging and discharging processes of the battery to maximize the efficiency, life, and economy of the system. These strategies can be formulated according to factors such as energy demand, grid conditions, battery type, and technical characteristics.

[0073] Among them, the system integration architecture refers to the design framework and organizational structure of the entire system, including each subsystem, component, and their connection methods and interaction relationships.

[0074] In the embodiments of the present disclosure, when constructing the battery unit energy efficiency function and the non-battery system integration efficiency function according to the model configuration parameters, reliable reference information can be provided for the subsequent construction of the system energy efficiency function.

[0075] S206: Based on the battery unit energy efficiency function and the non-battery system integration efficiency function, construct the system energy efficiency function.

[0076] That is to say, in the embodiments of the present disclosure, the battery unit energy efficiency function and the non-battery system integration efficiency function can be constructed according to the model configuration parameters; based on the battery unit energy efficiency function and the non-battery system integration efficiency function, the system energy efficiency function is constructed. Thus, the comprehensiveness and accuracy of the indication of the obtained system energy efficiency function can be effectively improved.

[0077] S207: According to the model configuration parameters, construct the system constraint function.

[0078] S208: Based on the system cost function, the system energy efficiency function, and the system constraint function, construct the optimization configuration model of the sodium-ion battery energy storage system.

[0079] For the descriptions of S207 and S208, specific reference can be made to the above embodiments, which will not be elaborated here.

[0080] In this embodiment, by constructing the battery cost function according to the battery parameters, the charge and discharge strategy, and the control logic; constructing the integration cost function according to the battery parameters, the number of module clusters, the connection method, the charge and discharge strategy, and the control logic; and based on the battery cost function and the integration cost function, constructing the system cost function. Thus, the accuracy of the indication of the obtained system cost function for the optimization configuration cost of the sodium-ion battery energy storage system can be effectively improved by combining the battery cost function and the integration cost function. By constructing the battery unit energy efficiency function and the non-battery system integration efficiency function according to the model configuration parameters; based on the battery unit energy efficiency function and the non-battery system integration efficiency function, constructing the system energy efficiency function. Thus, the comprehensiveness and accuracy of the indication of the obtained system energy efficiency function can be effectively improved.

[0081] Optionally, the present disclosure also proposes a method for constructing an optimization configuration model of a sodium-ion battery energy storage system, wherein the system constraint function includes at least one of the following: the battery energy efficiency constraint function; the working voltage constraint function; the system energy efficiency constraint function. Thus, the practicability and applicability of the system constraint function can be effectively improved.

[0082] Among them, the battery energy efficiency constraint function is used to constrain the value range of the battery energy efficiency during the optimization configuration process of the sodium-ion battery energy storage system.

[0083] Among them, the working voltage constraint function is used to constrain the range of working voltage values ​​during the optimization configuration of the sodium-ion battery energy storage system.

[0084] Among them, the system energy efficiency constraint function is used to constrain the value range of the system energy efficiency during the optimization configuration of the sodium-ion battery energy storage system.

[0085] In summary, in order to achieve the goal of optimizing the performance of a sodium-ion battery energy storage system, the present disclosure proposes a sodium-ion battery energy storage system optimization configuration model based on CMOP. Based on the energy storage system equipment performance prediction model, the performance of the sodium-ion battery energy storage system is optimized by adjusting parameters such as battery parameters, number of module clusters, connection mode, charge and discharge strategy, and control logic.

[0086] The energy system of sodium-ion batteries is low, and because the energy density of sodium-ion battery monomers is low and the voltage range is wide, the system energy efficiency is also lower than that of lithium-ion batteries. In addition, sodium-ion batteries are currently rarely used commercially, and the scale effect of production capacity cannot amortize the cost of sodium-ion batteries, and the integration cost is higher. Therefore, compared with lithium-ion batteries, the cost of sodium-ion battery energy storage systems is higher. Therefore, the objective function is set to minimize system cost and maximize system energy efficiency. The objective function is as follows:

[0087] (1) Lowest system cost

[0088]

[0089] System cost includes two types of ASSEM(x): battery cost Cell(x) and integration cost. Ω is the system configuration optimization parameter set, including battery parameters, number of module clusters, connection method, charging and discharging strategy, control logic, etc.

[0090] (2) Maximum system energy efficiency

[0091]

[0092] System energy efficiency is the accumulation of battery unit energy efficiency and non-battery system integration efficiency.

[0093] The output capacity and energy efficiency of sodium-ion batteries are subject to the material system and operating voltage, etc. Therefore, the energy efficiency of the battery cell is subject to the function of the material and operating voltage, Ecell(x) = G(M(x), V(x)). M(x) is the material-efficiency function, and V(x) is the voltage-efficiency function.

[0094] The integration efficiency of the non-battery system is restricted by the conversion strategy of the energy storage converter and the system integration architecture. Therefore, the integration efficiency of the non-battery system is restricted by the function ESSEM(x) = T(ET(x), ST(x)) of the energy storage conversion strategy and the system integration architecture. ET(x) is the energy storage conversion strategy - efficiency function, and ST(x) is the system integration architecture - efficiency function.

[0095] The constraints are as follows:

[0096] 1) Define the battery unit as the basic unit containing battery monomers, that is, the battery cluster. Referring to the relevant standards of existing lithium-ion batteries, the battery energy efficiency should be not less than 95%. Therefore, the value range of ECell(x) should be 95% - 100%.

[0097] 2) Since the controllable voltage range of sodium-ion battery monomers is 1.5 - 4V, its output capacity and energy efficiency are restricted by the working voltage range. That is, 1.5 ≤ V(x) ≤ 4.

[0098] 3) The system efficiency is usually higher than 85%, but it is difficult to achieve 100%. Therefore, 85% ≤ E(x) ≤ 100%.

[0099] Therefore, this system model is optimized with the system cost and system energy efficiency as the objective functions. The multi-objective optimization configuration model of the sodium-ion battery energy storage system is:

[0100] minF(C(x), -E(x))

[0101]

[0102] x ∈ Ω

[0103] For the above multi-objective optimization problem, the fast elitist multi-objective genetic algorithm (NSGA-II) can be used to solve the Pareto optimal solution set. According to the actual requirements of the project, the optimal control strategy is obtained from the Pareto optimal solution set, that is, the optimal parameter set of x. As Figure 3 shown, Figure 3 is the schematic flow chart of solving the Pareto optimal solution set by using NSGA-II proposed in this disclosure.

[0104] Figure 4 is the schematic structural diagram of the device for constructing the optimization configuration model of the sodium-ion battery energy storage system proposed in an embodiment of this disclosure.

[0105] As Figure 4 shown, the device 40 for constructing the optimization configuration model of the sodium-ion battery energy storage system includes:

[0106] A processing module 401, configured to initialize the model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic;

[0107] The first construction module 402 is configured to construct a system cost function and a system energy efficiency function according to model configuration parameters;

[0108] The second construction module 403 is configured to construct a system constraint function according to model configuration parameters;

[0109] The third construction module 404 is configured to construct an optimized configuration model for a sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function.

[0110] It should be noted that the foregoing explanation of the construction method of the optimized configuration model for the sodium-ion battery energy storage system also applies to the construction device of the optimized configuration model for the sodium-ion battery energy storage system in this embodiment, and will not be elaborated here.

[0111] In this embodiment, by initializing model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic; constructing a system cost function and a system energy efficiency function according to the model configuration parameters; constructing a system constraint function according to the model configuration parameters; and constructing an optimized configuration model for a sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function. Thus, the practicability and reliability of the obtained optimized configuration model for the sodium-ion battery energy storage system can be ensured by using the system cost function and the system energy efficiency function as objective functions and combining the system constraint function, thereby effectively improving the optimization effect of the obtained optimized configuration model for the sodium-ion battery energy storage system on the sodium-ion battery energy storage system.

[0112] Figure 5 A block diagram of an exemplary computer device suitable for implementing the embodiments of the present disclosure is shown. Figure 5 The computer device 12 shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0113] As Figure 5 shown, the computer device 12 is presented in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0114] Bus 18 represents one or more of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, an Accelerated Graphics Port, a processor bus, or a local bus using any of the several bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnection (PCI) bus.

[0115] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and nonvolatile media, removable and non-removable media.

[0116] Memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / nonvolatile computer system storage media. By way of example only, storage system 34 can be used for reading and writing on non-removable, nonvolatile magnetic media ( Figure 5 not shown, typically referred to as a "hard disk drive").

[0117] Although Figure 5 not shown in the figure, a disk drive for reading and writing on a removable nonvolatile disk (such as a "floppy disk") and an optical disk drive for reading and writing on a removable nonvolatile optical disk (such as a Compact Disc Read Only Memory (CD-ROM), Digital Video Disc Read Only Memory (DVD-ROM), or other optical media) can be provided. In these cases, each drive can be connected to bus 18 via one or more data media interfaces. Memory 28 can include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0118] A program / utility 40 having a set (at least one) of program modules 42 can be stored, for example, in a memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules 42 generally execute the functions and / or methods in the embodiments described in this disclosure.

[0119] The computer device 12 can also communicate with one or more external devices 14 (such as a keyboard, a pointing device, a display 24, etc.), and can also communicate with one or more devices that enable a human body to interact with the computer device 12, and / or communicate with any device that enables the computer device 12 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through an input / output (I / O) interface 22. Moreover, the computer device 12 can also communicate with one or more networks (such as a Local Area Network (LAN), a Wide Area Network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As shown in the figure, the network adapter 20 communicates with other modules of the computer device 12 through a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in combination with the computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0120] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the construction method of the optimized configuration model of the sodium-ion battery energy storage system mentioned in the foregoing embodiments.

[0121] To implement the above embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the construction method of the optimized configuration model of the sodium-ion battery energy storage system proposed in the foregoing embodiments of the present disclosure.

[0122] To implement the above embodiments, the present disclosure also proposes a computer program product. When the instructions in the computer program product are executed by a processor, it executes the construction method of the optimized configuration model of the sodium-ion battery energy storage system proposed in the foregoing embodiments of the present disclosure.

[0123] Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and examples are only illustrative, and the true scope and spirit of the present disclosure are pointed out by the following claims.

[0124] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

[0125] It should be noted that in the description of the present disclosure, the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance. In addition, in the description of the present disclosure, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0126] Any process or method description in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present disclosure includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the technical field of the embodiments of the present disclosure.

[0127] It should be understood that the various parts of the present disclosure can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0128] Those of ordinary skill in the art of the present technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, includes one or a combination of the steps of the method embodiments.

[0129] In addition, in various embodiments of the present disclosure, each functional unit may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0130] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, or the like.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0132] Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for constructing an optimization configuration model of a sodium-ion battery energy storage system, characterized in that Including: Initializing model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic; Constructing a system cost function and a system energy efficiency function according to the model configuration parameters; among them, the system cost function is constructed based on a battery cost function and an integration cost function; determining a working voltage, a system energy storage conversion strategy, a system integration architecture, and a system material feature for describing the material characteristics of a sodium-ion battery energy storage system according to the model configuration parameters, constructing a first function for indicating the association information between the system material feature and the energy efficiency of the battery unit based on the system material feature, constructing a second function for indicating the association information between the working voltage and the energy efficiency of the battery unit based on the working voltage, constructing a third function for indicating the association information between the system energy storage conversion strategy and the integration efficiency of the non-battery system based on the system energy storage conversion strategy, constructing a fourth function for indicating the association information between the system integration architecture and the integration efficiency of the non-battery system based on the system integration architecture, constructing a battery unit energy efficiency function based on the first function and the second function, constructing a non-battery system integration efficiency function based on the third function and the fourth function, and constructing the system energy efficiency function based on the battery unit energy efficiency function and the non-battery system integration efficiency function; Constructing a system constraint function according to the model configuration parameters; Constructing an optimized configuration model for a sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function.

2. The method according to claim 1, wherein Constructing the battery cost function according to the battery parameters, the charge and discharge strategy, and the control logic; Constructing the integration cost function according to the battery parameters, the number of module clusters, the connection method, the charge and discharge strategy, and the control logic.

3. The method according to claim 1, wherein The system constraint function includes: Battery unit energy efficiency constraint function; Working voltage constraint function; System energy efficiency constraint function.

4. An apparatus for constructing an optimized configuration model of a sodium-ion battery energy storage system, characterized in that, Including: A processing module for initializing model configuration parameters, where the model configuration parameters include: battery parameters, number of module clusters, connection method, charge and discharge strategy, and control logic; A first construction module, configured to construct a system cost function and a system energy efficiency function according to the model configuration parameters; wherein, based on a battery cost function and an integration cost function, the system cost function is constructed; a working voltage, a system energy storage conversion strategy, a system integration architecture, and a system material feature for describing the material characteristics of a sodium-ion battery energy storage system are determined according to the model configuration parameters, and based on the system material feature, a first function for indicating the correlation information between the system material feature and the energy efficiency of a battery cell is constructed, based on the working voltage, a second function for indicating the correlation information between the working voltage and the energy efficiency of the battery cell is constructed, based on the system energy storage conversion strategy, a third function for indicating the correlation information between the system energy storage conversion strategy and the integration efficiency of a non-battery system is constructed, based on the system integration architecture, a fourth function for indicating the correlation information between the system integration architecture and the integration efficiency of a non-battery system is constructed, based on the first function and the second function, an energy efficiency function of the battery cell is constructed, based on the third function and the fourth function, an integration efficiency function of the non-battery system is constructed, and based on the energy efficiency function of the battery cell and the integration efficiency function of the non-battery system, the system energy efficiency function is constructed; A second construction module, configured to construct a system constraint function according to the model configuration parameters; A third construction module, configured to construct an optimization configuration model of a sodium-ion battery energy storage system based on the system cost function, the system energy efficiency function, and the system constraint function.

5. A computer device, characterized in that, Comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-3.

6. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, Wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-3.

7. A computer program product, characterized in that, Comprising a computer program, which when executed by a processor implements the steps of the method according to any one of claims 1-3.

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