Method, device and computer equipment for determining discharge depth of electrochemical energy storage system

Abstract

The embodiments of this specification disclose a method, device and computer equipment for determining the discharge depth of an electrochemical energy storage system. The method comprises: obtaining parameter data of the electrochemical energy storage system, the parameter data comprising the discharge depth of a historical optimization cycle; constructing an objective function based on the parameter data, the objective function being used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system over the remaining life cycle, wherein the remaining life cycle at least includes the current optimization cycle; optimizing the objective function to obtain the discharge depth of the current optimization cycle. The embodiments of this specification can effectively improve the benefits of the electrochemical energy storage system and maximize the benefits of the electrochemical energy storage system.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of computer technology, and in particular to a method, device and computer equipment for determining the discharge depth of an electrochemical energy storage system. Background Art

[0002] The electrochemical energy storage system is an energy storage system that uses batteries as core energy storage elements and whose input and output energy types are both electrical energy. The electrochemical energy storage system has the advantages of short construction period, fast response speed, and high energy density. In addition, the electrochemical energy storage system has less site restrictions and is a powerful supplement to mechanical energy storage technologies represented by pumped storage. It can promote the balance of supply and demand of the power grid and ensure the safety of the power grid. It is an important means for the strong development of the power grid and the efficient use of renewable energy.

[0003] The discharge depth of an electrochemical energy storage system affects the change in the internal resistance of the battery, thereby determining the cycle life of the system. In related technologies, a fixed discharge depth is often set. However, the selection of a fixed discharge depth depends more on engineering experience. Moreover, the selected fixed discharge depth is unlikely to maximize the benefits of an electrochemical energy storage system. Summary of the invention

[0004] The embodiments of this specification provide a method, device and computer equipment for determining the discharge depth of an electrochemical energy storage system to determine the discharge depth of the electrochemical energy storage system and maximize the benefits of the electrochemical energy storage system.

[0005] In a first aspect of the embodiments of this specification, a method for determining a discharge depth of an electrochemical energy storage system is provided, comprising:

[0006] Acquiring parameter data of the electrochemical energy storage system, wherein the parameter data includes a discharge depth of a historical optimization cycle;

[0007] Constructing an objective function according to the parameter data, the objective function being used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system over the remaining life cycle, wherein the remaining life cycle at least includes the current optimization cycle;

[0008] The objective function is optimized to obtain the discharge depth of the current optimization cycle.

[0009] A second aspect of the embodiments of this specification provides a device for determining a discharge depth of an electrochemical energy storage system, comprising:

[0010] An acquisition unit, used to acquire parameter data of the electrochemical energy storage system, wherein the parameter data includes a discharge depth of a historical optimization cycle;

[0011] A construction unit, used to construct an objective function according to the parameter data, wherein the objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system in the remaining life cycle, wherein the remaining life cycle at least includes the current optimization cycle;

[0012] The optimization unit is used to optimize the objective function and obtain the discharge depth of the electrochemical energy storage system in the current optimization cycle.

[0013] A third aspect of the embodiments of this specification provides a computer device, including:

[0014] at least one processor;

[0015] A memory storing program instructions, wherein the program instructions are configured to be suitable for being executed by the at least one processor, and the program instructions include instructions for executing the method as described in the first aspect.

[0016] The technical solution provided in the embodiments of this specification can obtain parameter data of the electrochemical energy storage system; can construct an objective function based on the parameter data; can optimize the objective function to obtain the discharge depth of the current optimization cycle. The objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system over the remaining life cycle. Therefore, the method of the embodiments of this specification can effectively improve the income of the electrochemical energy storage system and maximize the income of the electrochemical energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0018] Figure 1 Schematic diagram of a method for determining a discharge depth of an electrochemical energy storage system in an embodiment of this specification;

[0019] Figure 2 Schematic diagram of a method for determining a discharge depth of an electrochemical energy storage system in an embodiment of this specification;

[0020] Figure 3 This is a schematic diagram of the structure of a device for determining the discharge depth of an electrochemical energy storage system in an embodiment of this specification;

[0021] Figure 4 Schematic diagram of the structure of a computer device in an embodiment of this specification. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of this specification to clearly and completely describe the technical solutions in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0023] The embodiments of this specification provide a method for determining the discharge depth of an electrochemical energy storage system.

[0024] In some embodiments, the electrochemical energy storage system may include a battery system, a power electronic interface device (PCS (Power Converter System, energy storage converter) or a bidirectional DC / DC converter, etc.), a BMS (Battery Management System, battery management system), an EMS (Energy Management System, energy management system), a transformer, a container, a fire protection system, a temperature control system, supporting power distribution facilities, etc. The life cycle of the electrochemical energy storage system can be divided into multiple optimization cycles in advance. The optimization cycle is a time period for optimizing the depth of discharge. The duration of the optimization cycle can be flexibly set according to actual needs. In practical applications, the duration of the optimization cycle can be determined according to the number of charge and discharge cycles of the electrochemical energy storage system. For example, the duration of the optimization cycle needs to meet the following requirements: the number of charge and discharge cycles of the electrochemical energy storage system within the optimization cycle is 500 to 600 times. The duration of the optimization cycle can be 6 months, 12 months, etc. The durations of the multiple optimization cycles may be the same or different. Within the optimization cycle, the depth of discharge may remain unchanged. Between the multiple optimization cycles, the depth of discharge may be the same or different. The depth of discharge is used to represent the percentage of the battery discharge amount to the rated capacity of the battery.

[0025] See also Figure 1 and Figure 2 , the method for determining the discharge depth of the electrochemical energy storage system may include the following steps.

[0026] Step S11: Acquire parameter data of the electrochemical energy storage system.

[0027] In some embodiments, parameter data of the electrochemical energy storage system can be obtained after the trigger condition is met. The trigger condition may include: entering a new optimization cycle. In practical applications, it can be determined whether the operating time of the electrochemical energy storage system in the optimization cycle reaches the duration of the optimization cycle. If reached, it means that the optimization cycle is over and the electrochemical energy storage system enters a new optimization cycle; if not reached, it means that the optimization cycle is not over and a new optimization cycle has not been entered.

[0028] In some embodiments, the parameter data may include the discharge depth of the electrochemical energy storage system in a historical optimization cycle. The historical optimization cycle is the optimization cycle before the current moment. The number of the historical optimization cycles may be 0, one, or more. It is worth noting that if the number of historical optimization cycles is 0, the discharge depth of the historical optimization cycle may be considered to be a preset discharge depth. The preset discharge depth may be the initial discharge depth of the electrochemical energy storage system.

[0029] In some embodiments, the parameter data may also include at least one of the following: installed parameters, historical charge and discharge data, EMS operation strategy, etc. Among them, the installed parameters may include at least one of the following: rated parameters of the battery, rated parameters of the PCS, rated parameters of the BMS, test curves, project taxes, loans, electricity prices, land occupation information, etc. The historical charge and discharge data may include the power curve and start and end SOC status of the historical operation day. The EMS operation strategy may include the operation mode and number of cycles per operation day. In different application scenarios, the electrochemical energy storage system can be configured with different EMS operation strategies. The application scenarios of the electrochemical energy storage system may include the power generation side, the grid side and the load side. On the power generation side, the electrochemical energy storage system is mainly based on auxiliary services, such as assisting new energy grid connection, providing peak and frequency regulation resources, etc., and its power instructions must meet the requirements of the declared value and duration. According to the operating point characteristics of the power grid in the area where the electrochemical energy storage system is located, and the preset control strategy of the electrochemical energy storage system, the number of charge and discharge times within the optimization cycle can be estimated. On the grid side, the electrochemical energy storage system is mainly based on large-scale energy storage to alleviate the weak points of the grid and provide support capabilities. Conventional dispatching is mainly to reduce peak loads and fill valleys. Emergency support may occur in a few cases, but it will not change the number of charge and discharge times per day. On the load side, unmanned operation and remote operation and maintenance are mostly adopted. Therefore, electrochemical energy storage systems are usually charged and discharged once or twice a day according to the preset time. If a demand-side response occurs, the preset time can be changed according to the bidding situation, which will have no effect on the number of charge and discharge times.

[0030] In some embodiments, parameter data input by an engineer may be received. Alternatively, the electrochemical energy storage system may record and store parameter data during operation. Thus, the stored parameter data may be read.

[0031] Step S13: construct an objective function according to the parameter data.

[0032] In some embodiments, the parameter data can be used as a coefficient in the objective function, so as to construct an objective function based on the parameter data. The objective function can be used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system in the remaining life cycle. Through the objective function, the cash flow depreciation caused by taking the cycle life as the optimization target can be avoided, so that the entire electrochemical energy storage system life cycle has the best economy. Among them, the remaining life cycle includes at least the current optimization cycle. Specifically, the remaining life cycle may only include the current optimization cycle. Or, the remaining life cycle may include the current optimization cycle and at least one future optimization cycle. The current optimization cycle is the optimization cycle at the current moment, and the future optimization cycle is the optimization cycle after the current moment. For example, the number of the multiple optimization cycles is N, the current optimization cycle is T, and the remaining life cycle may include optimization cycles such as T, T+1, ..., N. The cumulative discounted value of net profit may refer to the sum of the discounted values ​​of the net profits of each optimization cycle in the remaining life cycle. The discounted value of net profit may refer to the net profit converted into a present value according to a certain discount factor.

[0033] In some embodiments, the objective function can be expressed as W(T)=I(T)-Q(T). Wherein, T represents the current optimization cycle. W(T) represents the cumulative discounted value of the net profit of the electrochemical energy storage system during the remaining life cycle. I(T) represents the cumulative discounted value of the actual income of the electrochemical energy storage system during the remaining life cycle. The cumulative discounted value of actual income may refer to the sum of the discounted values ​​of actual income of each optimization cycle during the remaining life cycle. The discounted value of actual income may refer to the actual income converted into present value according to a certain discount factor. Q(T) represents the cumulative operating cost of the electrochemical energy storage system during the remaining life cycle. The cumulative operating cost may refer to the sum of the operating costs of each optimization cycle during the remaining life cycle.

[0034] In some embodiments, the

[0035] N represents the number of optimization cycles of the electrochemical energy storage system.

[0036] a(i) represents the available energy storage capacity in the i-th optimization cycle. Specifically, The a(i) described above takes into account the number of failure cycles and the number of battery factory cycles for conversion, and corrects the conversion result by adjusting the capacitance attenuation at the time of scrapping and environmental changes, so that it has the advantages of being testable, correctable, simple and reliable. Wherein, S represents the rated energy storage capacity of the electrochemical energy storage system. b1 represents the available capacity attenuation rate of the electrochemical energy storage system when it is no longer used. b2 represents a preset correction factor. b2 can be set according to changes in the operating environment of the electrochemical energy storage system. The size of b2 can be, for example, 0.8-1.2. A represents the number of charge and discharge cycles of the electrochemical energy storage system. C(DOD(j)) represents the number of charge and discharge cycles that lead to failure within the jth optimization cycle. C(DOD(j)) can be obtained by fitting the curve formed by the number of charge and discharge cycles and the depth of discharge. For example, n(j) represents the number of charge and discharge cycles of the jth optimization period. e is a natural constant. α1, α2, α3, α4, and α5 are fitting parameters.

[0037] DOD(i) represents the discharge depth of the i-th optimization cycle.

[0038] η represents the charge and discharge efficiency.

[0039] n(i) represents the number of charge and discharge cycles in the i-th optimization period.

[0040] y(i) represents the benefit of a single charge and discharge cycle in the i-th optimization period.

[0041] R(i) represents the discount factor of the i-th optimization period. Specifically, Where r represents the inflation rate and t represents the duration of the optimization cycle.

[0042] In some embodiments, q(i) represents the operating cost of the i-th optimization cycle. The operating cost may include personnel expenses, periodic payment fees, depreciation, material costs, etc. The operating cost may be obtained by estimation.

[0043] Step S15: Optimize the objective function to obtain the discharge depth of the electrochemical energy storage system in the current optimization cycle.

[0044] In some embodiments, the objective function can be optimized with the goal of maximizing the value of the objective function, and the maximum discharge depth and the minimum discharge depth can be used as constraints to obtain the optimal discharge depth as the discharge depth of the electrochemical energy storage system in the current optimization cycle; the electrochemical energy storage system can be operated according to the discharge depth.

[0045] The discharge depth of the electrochemical energy storage system in each optimization cycle is between the maximum discharge depth and the minimum discharge depth. The maximum discharge depth and the minimum discharge depth can be pre-set. For example, the maximum discharge depth can be 1, and the minimum discharge depth can be 0. It is worth noting that when optimizing the objective function, it can be assumed that the discharge depth of each optimization cycle in the remaining life cycle is the same, that is, DOD(T)=DOD(T+1)=…=DOD(N); it can be assumed that the number of charge and discharge cycles in each optimization cycle in the remaining life cycle is n(T-1)=n(T)=n(T+1)=…=n(N). On this basis, the objective function W(T)=I(T)-Q(T) is optimized to obtain DOD(T).

[0046] In some embodiments, multiple discharge depths can be selected between the maximum discharge depth and the minimum discharge depth; each discharge depth can be substituted into the objective function to obtain the objective function value corresponding to the discharge depth; the discharge depth corresponding to the maximum objective function value can be selected from the multiple discharge depths as the target discharge depth; the target discharge depth can be used as the discharge depth in the current optimization cycle. Of course, the objective function can also be optimized using a function optimization algorithm. For example, the objective function can also be optimized using algorithms such as the gradient descent method and the Newton method.

[0047] In some embodiments, it can be determined whether the current optimization cycle is the last optimization cycle of the multiple optimization cycles. If not, after entering the next optimization cycle, steps S11 to S15 can be iteratively executed. If so, the method flow can be terminated. In other words, steps S11 to S15 can be iteratively executed until the current optimization cycle is the last optimization cycle.

[0048] The method of the embodiment of this specification can obtain parameter data of the electrochemical energy storage system; can construct an objective function based on the parameter data; can optimize the objective function to obtain the discharge depth of the current optimization cycle. The objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system over the remaining life cycle. Therefore, the method of the embodiment of this specification can effectively improve the income of the electrochemical energy storage system and maximize the income of the electrochemical energy storage system.

[0049] The method of the embodiment of this specification reduces the uncertainty of charge and discharge times caused by the application of electrochemical energy storage systems in scenarios with greater uncertainty such as new energy by setting an optimization cycle. A longer optimization cycle can improve the accuracy of battery attenuation assessment, while avoiding frequent optimization, greatly improving engineering feasibility.

[0050] The embodiments of this specification also provide a device for determining the discharge depth of an electrochemical energy storage system.

[0051] See also Figure 3 The discharge depth determination device of the electrochemical energy storage system may include the following units.

[0052] An acquisition unit 31 is used to acquire parameter data of the electrochemical energy storage system, wherein the parameter data includes a discharge depth of a historical optimization cycle;

[0053] A construction unit 33 is used to construct an objective function according to the parameter data, wherein the objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system in the remaining life cycle, wherein the remaining life cycle at least includes the current optimization cycle;

[0054] The optimization unit 35 is used to optimize the objective function to obtain the discharge depth of the electrochemical energy storage system in the current optimization cycle.

[0055] An embodiment of the computer device of the present specification is introduced below. Figure 4 Schematic diagram of the hardware structure of the computer device in this embodiment. Figure 4 As shown, the computer device may include one or more (only one is shown in the figure) processors, memory and transmission modules. Of course, it can be understood by those skilled in the art that Figure 4 The hardware structure shown is only for illustration and does not limit the hardware structure of the above-mentioned computer device. In practice, the computer device may also include Figure 4 More or fewer component units as shown; or, Figure 4 Different configurations are shown.

[0056] The memory may include a high-speed random access memory; or, it may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory or other non-volatile solid-state memory. Of course, the memory may also include a remotely set network memory. The memory may be used to store program instructions or modules of application software, such as the instructions in this manual. Figure 1 The program instructions or modules of the corresponding embodiment.

[0057] The processor may be implemented in any suitable manner. For example, the processor may take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, etc. The processor may read and execute program instructions or modules in the memory.

[0058] The transmission module can be used for transmitting data via a network, for example, via a network such as the Internet, an intranet, a local area network, a mobile communication network, etc.

[0059] This specification also provides an embodiment of a computer storage medium. The computer storage medium includes but is not limited to a random access memory (RAM), a read-only memory (ROM), a cache, a hard disk (HDD), a memory card, etc. The computer storage medium stores computer program instructions. When the computer program instructions are executed, the following are achieved: Figure 1 The program instructions or modules of the corresponding embodiment.

[0060] It should be noted that each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, computer equipment embodiment, and computer storage medium embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. In addition, it is understandable that after reading this specification document, those skilled in the art can think of any combination of some or all of the embodiments listed in this specification without creative work, and these combinations are also within the scope of disclosure and protection of this specification.

[0061] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0062] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0063] It can be known from the above description of the implementation mode that the technicians in this field can clearly understand that the present specification can be implemented by means of software plus the necessary general hardware platform. Based on such an understanding, the technical solution of the present specification can be essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present specification or some parts of the embodiments.

[0064] This specification can be used in many general or special computer system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0065] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0066] Although the present specification is described through embodiments, those skilled in the art will appreciate that there are many modifications and changes to the present specification without departing from the spirit of the present specification, and it is intended that the appended claims include these modifications and changes without departing from the spirit of the present specification.

Claims

1. A method for determining a discharge depth of an electrochemical energy storage system, comprising: Dividing the life cycle of the electrochemical energy storage system into a plurality of optimization cycles in advance, wherein the optimization cycle is a time period for optimizing the discharge depth, and the discharge depth of the electrochemical energy storage system remains unchanged during the optimization cycle; Determining whether the operation time of the electrochemical energy storage system in the optimization cycle reaches the time of the optimization cycle; If yes, enter a new optimization cycle and obtain parameter data of the electrochemical energy storage system, wherein the parameter data includes the discharge depth of the historical optimization cycle, and the historical optimization cycle is the optimization cycle before the current moment; Constructing an objective function according to the parameter data, wherein the objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system in the remaining life cycle, wherein the remaining life cycle includes the remaining optimization cycles in the multiple optimization cycles except the historical optimization cycles; Optimize the objective function to obtain the discharge depth of the current optimization cycle; In the current optimization cycle, the electrochemical energy storage system is operated according to the discharge depth.

2. The method according to claim 1, wherein the objective function comprises W(T)=I(T)-Q(T); The T represents the current optimization cycle; W(T) represents the cumulative discounted value of the net profit of the electrochemical energy storage system during its remaining life cycle; I(T) represents the actual cumulative discounted value of the income of the electrochemical energy storage system during the remaining life cycle; The Q(T) represents the cumulative operating cost of the electrochemical energy storage system during its remaining life cycle.

3. The method according to claim 2, N represents the number of optimization cycles of the electrochemical energy storage system; a(i) represents the available capacity of energy storage in the i-th optimization cycle; DOD(i) represents the discharge depth of the i-th optimization cycle; η represents the charge and discharge efficiency; n(i) represents the number of charge and discharge cycles in the i-th optimization period; y(i) represents the benefit of a single charge-discharge cycle in the i-th optimization period; R(i) represents the discount factor of the i-th optimization period.

4. The method according to claim 3, S represents the rated energy storage capacity of the electrochemical energy storage system; b1 represents the available capacity attenuation rate of the electrochemical energy storage system when it is no longer in use; b2 represents the preset correction coefficient; A represents the number of charge and discharge cycles of the electrochemical energy storage system; C(DOD(j) represents the number of charge-discharge cycles to failure within the jth optimization period.

5. The method according to claim 3, r represents the inflation rate; t represents the duration of the optimization cycle.

6. The method according to claim 1, wherein optimizing the objective function comprises: The objective function is optimized with the maximum discharge depth and the minimum discharge depth as constraints.

7. The method according to claim 1, further comprising: The above steps are iterated until the current optimization cycle is the last optimization cycle.

8. A discharge depth determination device for an electrochemical energy storage system, comprising: A division unit, used to divide the life cycle of the electrochemical energy storage system into a plurality of optimization cycles in advance, wherein the optimization cycle is a time period for optimizing the discharge depth, and the discharge depth of the electrochemical energy storage system remains unchanged during the optimization cycle; A judgment unit, used to judge whether the operation time of the electrochemical energy storage system in the optimization cycle reaches the time of the optimization cycle; An acquisition unit is used to, if yes, enter a new optimization cycle and acquire parameter data of the electrochemical energy storage system, wherein the parameter data includes a discharge depth of a historical optimization cycle, wherein the historical optimization cycle is an optimization cycle before the current moment; A construction unit, configured to construct an objective function according to the parameter data, wherein the objective function is used to represent the cumulative discounted value of the net profit of the electrochemical energy storage system in the remaining life cycle, wherein the remaining life cycle includes the remaining optimization cycles in the plurality of optimization cycles except the historical optimization cycles; An optimization unit, used to optimize the objective function and obtain the discharge depth of the electrochemical energy storage system in the current optimization cycle; An operating unit is used to operate the electrochemical energy storage system according to the discharge depth in a current optimization cycle.

9. A computer device comprising: at least one processor; A memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing the method according to any one of claims 1 to 7.

Images