Battery charging and discharging control method, system and equipment of energy storage system and medium

Abstract

The invention belongs to the field of energy storage, and particularly provides a battery charging and discharging control method, system and equipment for an energy storage system and a medium, and the method comprises the following steps: 1, obtaining energy storage battery data and power grid data of a target energy storage system; step 2, inputting the obtained energy storage battery data and power grid data into a preset battery charging and discharging control model; 3, calculating an optimal charging and discharging control strategy at the current moment by adopting an optimization algorithm; and step 4, controlling the energy storage system to charge and discharge based on the obtained optimal charge and discharge control strategy. Wherein the battery charging and discharging control model is constructed by taking cost minimization and battery life maximization as optimization targets; the operation cost of the energy storage system is reduced, the service life of the energy storage battery is prolonged, meanwhile, the phenomena of over-charging, over-discharging and frequent charging and discharging of the battery are effectively reduced, and the charging and discharging requirements of the energy storage system under different working conditions can be met.

Description

Technical Field

[0001] The present invention belongs to the field of direct-mounted energy storage systems, and in particular relates to a battery charging and discharging control method, system, equipment and medium of an energy storage system. Background Art

[0002] In the context of the rapid development of new energy, energy storage systems are an indispensable part of the power system, and their performance and efficiency are directly related to the stable operation of the power grid and the efficient use of renewable energy. However, the current battery charging and discharging control strategy has exposed many problems in practical applications, especially the control strategy design is too simple and cannot fully meet the complex needs of energy storage systems.

[0003] Existing battery charge and discharge control strategies for energy storage systems often perform simple charge and discharge scheduling based on the immediate power demand of the power grid or the current power level of the energy storage battery, ignoring the long-term optimization of the operating cost of the energy storage system and the maintenance of the battery life. This simplified control method is incapable of coping with complex working conditions such as large grid load fluctuations and unstable renewable energy output, which can easily lead to frequent charge and discharge of the energy storage system, increase operating costs, and accelerate battery aging and shorten service life.

[0004] In view of this, the art needs a battery charging and discharging control method and system for an energy storage system to solve the above problems. Summary of the invention

[0005] The object of the present invention is to provide a battery charge and discharge control method, system, device and medium for an energy storage system, so as to solve the defects of the existing battery charge and discharge control of the energy storage system, such as frequent charge and discharge of the energy storage system and increased operating costs.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: The present invention provides a battery charging and discharging control method for an energy storage system, comprising the following steps: Step 1, obtaining energy storage battery data and power grid data of the target energy storage system; Step 2: input the obtained energy storage battery data and power grid data into a preset battery charge and discharge control model, wherein: the expression of the battery charge and discharge control model is:

[0007] in, It is a function of the battery charge and discharge control model; , are the weight coefficients respectively; is the total cost function; is the battery life loss function; Step 3, using an optimization algorithm to optimize the output of the preset battery charge and discharge control model to obtain the optimal charge and discharge control strategy at the current moment; Step 4, controlling the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy; The battery charge and discharge control model is constructed with cost minimization and battery life maximization as optimization objectives; the constraints of the battery charge and discharge control model are constructed with battery charge and discharge power, battery operating temperature, battery internal resistance, battery cycle number, environmental cost, income obtained through grid auxiliary services, total cost and battery life loss.

[0008] Preferably, the total cost function for:

[0009] in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services.

[0010] Preferably, the battery life loss function for:

[0011] in, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the impact of battery charging and discharging power on battery life.

[0012] Preferably, in step 2, the constraints of the battery charge and discharge control model are:

[0013] in, and are the minimum and maximum values ​​of battery charge and discharge power respectively; and are the minimum and maximum temperatures for battery operation, respectively; and are the minimum and maximum values ​​of the battery internal resistance respectively; and are the minimum and maximum values ​​of the battery cycle times; and are the minimum and maximum values ​​of environmental costs, respectively; and are the minimum and maximum values ​​of grid ancillary service revenue, respectively; and are the minimum and maximum values ​​of the total cost respectively; and are the minimum and maximum values ​​of battery life loss; For the moment The battery charge and discharge power; For the moment Battery temperature; For the moment The internal resistance of the battery; For the moment The number of battery cycles; For the moment electricity price; For the moment Revenue from providing grid ancillary services; is the total cost function; is the battery life loss function.

[0014] Preferably, the total cost function for:

[0015] in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services; The battery life loss function for:

[0016] in, is the total time period, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the effect of battery charging and discharging power on battery life; In step 2, the constraints of the battery charge and discharge control model are:

[0017] in, and are the minimum and maximum values ​​of battery charge and discharge power respectively; and are the minimum and maximum temperatures for battery operation, respectively; and are the minimum and maximum values ​​of the battery internal resistance respectively; and are the minimum and maximum values ​​of the battery cycle times; and are the minimum and maximum values ​​of environmental costs, respectively; and are the minimum and maximum values ​​of grid ancillary service revenue, respectively; and are the minimum and maximum values ​​of the total cost respectively; and are the minimum and maximum values ​​of battery life loss; For the moment The battery charge and discharge power; For the moment Battery temperature; For the moment The internal resistance of the battery; For the moment The number of battery cycles; For the moment electricity price; For the moment Revenue from providing grid ancillary services; is the total cost function; is the battery life loss function.

[0018] Preferably, in step 3, a genetic algorithm is used to calculate the optimal charge and discharge control strategy at the current moment.

[0019] A battery charging and discharging control system for an energy storage system, comprising: An acquisition module, used to acquire energy storage battery data and power grid data of a target energy storage system; An input module is used to input the obtained energy storage battery data and power grid data into a preset battery charge and discharge control model, wherein the battery charge and discharge control model is constructed with cost minimization and battery life maximization as optimization goals; and the constraints of the battery charge and discharge control model are constructed with battery charge and discharge power, battery operating temperature, battery internal resistance, battery cycle number, environmental cost, income obtained through power grid auxiliary services, total cost and battery life loss; A calculation module is used to optimize the output of a preset battery charge and discharge control model using an optimization algorithm to obtain the optimal charge and discharge control strategy at the current moment; A control module is used to control the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy.

[0020] A computer device comprising: a processor suitable for executing a computer program; A computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method described is performed.

[0021] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0022] A computer program product comprises a computer program, wherein the computer program implements the method when executed by a processor.

[0023] Compared with the prior art, the present invention has the following beneficial technical effects: The present invention provides a battery charge and discharge control method for an energy storage system. By constructing a battery charge and discharge control model based on cost minimization and battery life maximization, and using an optimization algorithm to calculate the optimal charge and discharge control strategy in real time, the method can significantly reduce the operating cost of the energy storage system and improve the overall economic benefits. At the same time, it can effectively reduce the overcharge, over-discharge and frequent charge and discharge of the battery, and extend the service life of the energy storage battery. In addition, the method can also obtain power grid data in real time, more accurately judge the real-time demand of the power grid, and adjust the charge and discharge strategy of the energy storage system accordingly, which helps to enhance the stability and reliability of the power grid. At the same time, the use of advanced optimization algorithms and sophisticated control models improves the intelligence level and automation level of the system, making the method highly adaptable and robust, and able to adapt to the charge and discharge needs of the energy storage system under different working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of the present invention; Figure 2 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0025] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0026] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0027] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0028] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0029] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0030] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0031] In order to solve the above technical problems, that is, to solve the problem that the existing battery charge and discharge control strategy of the energy storage system is too simple, which easily leads to frequent charging and discharging of the energy storage system, increases the operating cost, and accelerates battery aging and shortens the service life, the present application provides a battery charge and discharge control method and system for an energy storage system, which aims to reduce the operating cost of the energy storage system, extend the service life of the energy storage battery, and effectively reduce the overcharging, over-discharging and frequent charging and discharging of the battery, and can adapt to the charging and discharging needs of the energy storage system under different working conditions.

[0032] Example 1 like Figure 1 As shown, this embodiment provides a battery charging and discharging control method for an energy storage system, and the control method includes the following steps: Step 1, obtaining energy storage battery data and power grid data of the energy storage system; Step 2, inputting the energy storage battery data and the power grid data into a preset battery charge and discharge control model; Step 3, using an optimization algorithm to optimize the output of the preset battery charge and discharge control model to obtain the optimal charge and discharge control strategy at the current moment; Step 4, controlling the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy; The battery charge and discharge control model is constructed based on minimizing cost and maximizing battery life as optimization objectives.

[0033] Example 2 On the basis of Example 1, this embodiment provides a battery charge and discharge control method for an energy storage system. In step 2, the battery charge and discharge control model expression is:

[0034] in, is a function of the battery charge and discharge control model, , are the weight coefficients respectively; is the total cost function; is the battery life loss function.

[0035] The total cost function for:

[0036] in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services.

[0037] The battery maintenance cost The formula is:

[0038] in, , , , and are the coefficients, is a constant, It's time The battery temperature, It's time The battery's state of charge, It's time The battery charge and discharge rate.

[0039] The battery life loss function for:

[0040] in, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the impact of battery charging and discharging power on battery life.

[0041] The constraints of the battery charge and discharge control model are:

[0042] in, and are the minimum and maximum values ​​of battery charge and discharge power, respectively. and are the minimum and maximum temperatures for battery operation, and are the minimum and maximum values ​​of the battery internal resistance, and are the minimum and maximum battery cycle times, and are the minimum and maximum values ​​of environmental costs, and are the minimum and maximum values ​​of grid ancillary service revenue, and are the minimum and maximum values ​​of the total cost, respectively. and are the minimum and maximum values ​​of battery life loss.

[0043] Example 3 On the basis of Example 1, this embodiment provides a battery charge and discharge control method for an energy storage system, in step 3, the optimization algorithm is a genetic algorithm; the optimization algorithm is used to calculate the optimal charge and discharge control strategy at the current moment, including: Code the variables, determine the number of individuals in the population, and randomly generate the initial population; According to the function of the battery charge and discharge control model Define the fitness function and perform constraint processing; Determine the individuals that will participate in the next generation of reproduction based on their fitness; Select two parent individuals, exchange some genes using uniform crossover to generate new offspring individuals; Set the probability of crossover operation and perform mutation operation on selected individuals with preset probability; Set the probability of mutation operation and iterate; After the iteration, the individual with the highest fitness is selected as the optimal solution; The optimal individual code is decoded into the actual decision variable value to obtain the optimal charging and discharging control strategy.

[0044] The encoding of the variables includes: Determine the type of variable. For continuous variables, use real number coding, and for discrete variables, use binary coding; The constraint processing comprises: For individuals that do not meet the constraints, the penalty function method is used to reduce the fitness of the individuals to meet the constraints.

[0045] The formula of the penalty function method is:

[0046] in, is the fitness value after constraint penalty, is the fitness value of the individual, is the number of constraints, It is Constraints, It is with The penalty coefficient associated with each constraint.

[0047] Example 4 This embodiment provides a battery charging and discharging control system for an energy storage system, the control system comprising: An acquisition module 100 is used to acquire energy storage battery data and grid data of a target energy storage system; The input module 200 is used to input the obtained energy storage battery data and power grid data into a preset battery charge and discharge control model, wherein the battery charge and discharge control model is constructed with cost minimization and battery life maximization as optimization objectives; the constraints of the battery charge and discharge control model are constructed with battery charge and discharge power, battery operating temperature, battery internal resistance, battery cycle number, environmental cost, income obtained through power grid auxiliary services, total cost and battery life loss, specifically: The battery charge and discharge control model expression is:

[0048] in, is a function of the battery charge and discharge control model, , are the weight coefficients respectively; is the total cost function; is the battery life loss function.

[0049] The total cost function for:

[0050] in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services.

[0051] The battery maintenance cost The formula is:

[0052] in, , , , and are the coefficients, is a constant, It's time The battery temperature, It's time The state of charge of the battery, It's time The battery charge and discharge rate.

[0053] The battery life loss function for:

[0054] in, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the impact of battery charging and discharging power on battery life.

[0055] The constraints of the battery charge and discharge control model are:

[0056] in, and are the minimum and maximum values ​​of battery charge and discharge power, respectively. and are the minimum and maximum temperatures for battery operation, and are the minimum and maximum values ​​of the battery internal resistance, and are the minimum and maximum battery cycle times, and are the minimum and maximum values ​​of environmental costs, and are the minimum and maximum values ​​of grid ancillary service revenue, and are the minimum and maximum values ​​of the total cost, respectively. and are the minimum and maximum values ​​of battery life loss.

[0057] The calculation module 300 is used to calculate the optimal charge and discharge control strategy at the current moment using an optimization algorithm, specifically: Genetic algorithm is used to calculate the optimal charge and discharge control strategy at the current moment; The control module 400 is used to control the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy.

[0058] This application constructs a battery charge and discharge control model based on cost minimization and battery life maximization, and uses an optimization algorithm to calculate the optimal charge and discharge control strategy in real time. This method can significantly reduce the operating cost of the energy storage system and improve the overall economic benefits. At the same time, it can effectively reduce the overcharge, over-discharge and frequent charge and discharge of the battery, and extend the service life of the energy storage battery. In addition, the method can also obtain power grid data in real time, more accurately judge the real-time needs of the power grid, and adjust the charge and discharge strategy of the energy storage system accordingly, which helps to enhance the stability and reliability of the power grid. At the same time, the use of advanced optimization algorithms and sophisticated control models improves the intelligence level and automation level of the system, making the method highly adaptable and robust, and able to adapt to the charge and discharge needs of the energy storage system under different working conditions.

[0059] Example 5 This embodiment 5 provides a computer device, including: a memory for storing a computer program; and a processor for implementing the steps of a computer method when executing the computer program.

[0060] When the processor executes the computer program, the steps of the above computer method are implemented.

[0061] Alternatively, when the processor executes the computer program, the functions of each module in the above system are realized. The computer device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The computer device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above are examples of computer devices and do not constitute a limitation on computer devices. The computer device may include more components than the above, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0062] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer device, and uses various interfaces and lines to connect various parts of the entire computer device.

[0063] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0064] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0065] Example 6 This embodiment 6 also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method described are implemented.

[0066] If the module / unit integrated in the computer system is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0067] Based on such understanding, the present invention implements all or part of the processes in the above method, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above computer method can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0068] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0069] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0070] Example 7 This embodiment 7 provides a computer product, which includes a computer program, and the computer program is stored in a computer-readable storage medium; the processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device can execute the method in embodiment 1, which will not be repeated here.

[0071] It should be noted that a person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods.

[0072] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A battery charging and discharging control method for an energy storage system, characterized in that: The following steps are involved: Step 1, obtaining energy storage battery data and power grid data of the target energy storage system; Step 2: input the obtained energy storage battery data and power grid data into a preset battery charge and discharge control model, wherein the expression of the battery charge and discharge control model is: in, It is a function of the battery charge and discharge control model; , are the weight coefficients respectively; is the total cost function; is the battery life loss function; Step 3, using an optimization algorithm to optimize the output of the preset battery charge and discharge control model to obtain the optimal charge and discharge control strategy at the current moment; Step 4, controlling the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy; The battery charge and discharge control model is constructed with cost minimization and battery life maximization as optimization objectives; the constraints of the battery charge and discharge control model are constructed with battery charge and discharge power, battery operating temperature, battery internal resistance, battery cycle number, environmental cost, income obtained through grid auxiliary services, total cost and battery life loss.

2. The battery charging and discharging control method of an energy storage system according to claim 1, characterized in that: The total cost function for: in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services.

3. The battery charging and discharging control method of an energy storage system according to claim 1, characterized in that: The battery life loss function for: in, is the total time period, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the impact of battery charging and discharging power on battery life.

4. The battery charging and discharging control method of an energy storage system according to claim 1, characterized in that: In step 2, the constraints of the battery charge and discharge control model are: in, and are the minimum and maximum values ​​of battery charge and discharge power respectively; and are the minimum and maximum temperatures for battery operation, respectively; and are the minimum and maximum values ​​of the battery internal resistance respectively; and are the minimum and maximum values ​​of the battery cycle times; and are the minimum and maximum values ​​of environmental costs, respectively; and are the minimum and maximum values ​​of grid ancillary service revenue, respectively; and are the minimum and maximum values ​​of the total cost respectively; and are the minimum and maximum values ​​of battery life loss; For the moment The battery charge and discharge power; For the moment Battery temperature; For the moment The internal resistance of the battery; For the moment Number of battery cycles; For the moment electricity price; For the moment Revenue from providing grid ancillary services; is the total cost function; is the battery life loss function.

5. The battery charging and discharging control method of an energy storage system according to claim 1, characterized in that: The total cost function for: in, is the total time period, It's time The electricity price, It's time The power purchased from or sold to the grid, It's time Battery maintenance costs, It's time The battery replacement cost, It's time environmental costs, It's time Revenue from providing grid ancillary services; The battery life loss function for: in, is the total time period, is the rated number of cycles of the battery, It's time The depth of discharge, is the exponential coefficient of the effect of discharge depth on battery life. It's time The battery temperature, is the reference temperature, It's time The internal resistance of the battery, is the initial internal resistance of the battery, is the exponential coefficient of the effect of battery internal resistance on battery life. It's time The battery charge and discharge power, It is the exponential coefficient of the effect of battery charging and discharging power on battery life; In step 2, the constraints of the battery charge and discharge control model are: in, and are the minimum and maximum values ​​of battery charge and discharge power respectively; and are the minimum and maximum temperatures for battery operation, respectively; and are the minimum and maximum values ​​of the battery internal resistance respectively; and are the minimum and maximum values ​​of the battery cycle times; and are the minimum and maximum values ​​of environmental costs, respectively; and are the minimum and maximum values ​​of grid ancillary service revenue, respectively; and are the minimum and maximum values ​​of the total cost respectively; and are the minimum and maximum values ​​of battery life loss; For the moment The battery charge and discharge power; For the moment Battery temperature; For the moment The internal resistance of the battery; For the moment Number of battery cycles; For the moment electricity price; For the moment Revenue from providing grid ancillary services; is the total cost function; is the battery life loss function.

6. The battery charging and discharging control method of an energy storage system according to claim 1, characterized in that: In step 3, a genetic algorithm is used to calculate the optimal charge and discharge control strategy at the current moment.

7. A battery charging and discharging control system for an energy storage system, characterized in that: include: An acquisition module, used to acquire energy storage battery data and power grid data of a target energy storage system; An input module is used to input the obtained energy storage battery data and power grid data into a preset battery charge and discharge control model, wherein the battery charge and discharge control model is constructed with cost minimization and battery life maximization as optimization goals; and the constraints of the battery charge and discharge control model are constructed with battery charge and discharge power, battery operating temperature, battery internal resistance, battery cycle number, environmental cost, income obtained through power grid auxiliary services, total cost and battery life loss; A calculation module is used to optimize the output of a preset battery charge and discharge control model using an optimization algorithm to obtain the optimal charge and discharge control strategy at the current moment; A control module is used to control the charging and discharging of the energy storage system based on the obtained optimal charging and discharging control strategy.

8. A computer device, characterized in that: include: a processor suitable for executing a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the method according to any one of claims 1 to 6 is performed.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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