An energy storage state of charge dynamic optimization control method, device, medium and product

Abstract

The application discloses a kind of energy storage state of charge dynamic optimization control method, device, medium and product, it is related to energy storage state of charge control field, the method includes: obtaining the real-time state of charge of energy storage system;Determine the difference of AGC power instruction value of power grid and the real-time power generation power of unit in power grid, obtain power instruction deviation value;If the absolute value of power instruction deviation value is less than or equal to the rated power of energy storage system, then determine the charge-discharge power of energy storage system according to power instruction deviation value;If the absolute value of power instruction deviation value is greater than the rated power of energy storage system, then determine the charge-discharge power ratio parameter of energy storage system according to real-time state of charge, and determine the charge-discharge power of energy storage system according to charge-discharge power ratio parameter and the rated power of energy storage system.The application can realize the optimization control to energy storage system SOC, improve the sustainable performance of energy storage system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy storage state of charge control, in particular to an energy storage state of charge dynamic optimization control method and device, medium and product. BACKGROUND

[0002] Under the background of global energy structure transformation and climate change response, energy strategy is also constantly adjusted and optimized to achieve safe, clean and efficient use of energy. As the world's largest energy producer and consumer, the adjustment of China's energy strategy has a profound impact on the global energy pattern. In the past ten years, the scale of new energy power generation in China has continued to grow rapidly. With the rapid growth of new energy, its own intermittent, random and volatile characteristics make the power balance protection contradiction more prominent, and the demand for energy storage on the source and network side arises accordingly. In order to ensure the smooth grid connection of new energy and the stable operation of the power grid, the power grid urgently needs to improve the regulation capacity of the system. The generation side + energy storage joint unit participating in the power spot market is born in such a strategic background.

[0003] New energy storage technologies are emerging, and lithium-ion battery energy storage still occupies an absolute dominant position. However, the life characteristics of lithium batteries are affected by many factors such as working temperature, discharge depth, working voltage, cycle number and charge-discharge rate, resulting in capacity loss and internal resistance increase, and the capacity of the battery is less than 80%, which needs to be replaced regularly. Among them, temperature has a significant impact on battery life performance, including the strength of polarization effect and side reaction, internal resistance and capacity size, etc. These performance changes further manifest as changes in battery coulomb efficiency and terminal voltage, thereby affecting the temperature difference of the entire battery pack, limiting the full power output of lithium batteries. In actual field operation, more attention is paid to the large temperature difference between lithium battery monomers, and in order to reduce temperature rise, the power state is operated, which cannot meet the power requirements of the power grid, and the lithium battery is operated in the 40%-70% interval, and the temperature difference between the battery packs of the lithium battery charge-discharge is less than the temperature difference in the high state of charge (State of Charge, SOC) and low SOC area. On the other hand, 1C lithium iron phosphate batteries are used, and the cycle life is 3500-5000 times, while the fire-storage combined frequency modulation is a frequent fluctuation working condition, and the power output of the lithium battery is controlled to ensure the performance of the fire-storage combined frequency modulation while reducing the cycle number of the lithium battery.

[0004] At present, although some control strategies forcibly reposition the SOC when the SOC exceeds the normal charge-discharge range, they do not fully realize the optimization control of the energy storage system SOC, resulting in poor sustainability of the energy storage system. SUMMARY

[0005] The application aims to provide a storage energy state of charge dynamic optimization control method, device, medium and product to realize the optimization control of the storage energy system SOC and improve the sustainable performance of the storage energy system.

[0006] To achieve the above-mentioned purpose, the application provides the following solutions.

[0007] A storage energy state of charge dynamic optimization control method comprises the following steps.

[0008] Obtaining the real-time state of charge of the storage energy system;

[0009] Determining the difference between the AGC power instruction value of the power grid and the real-time power generation of the unit in the power grid to obtain a power instruction deviation value;

[0010] If the absolute value of the power instruction deviation value is less than or equal to the rated power of the storage energy system, the charging and discharging power of the storage energy system is determined according to the power instruction deviation value;

[0011] If the absolute value of the power instruction deviation value is greater than the rated power of the storage energy system, the charging and discharging power ratio parameter of the storage energy system is determined according to the real-time state of charge, and the charging and discharging power of the storage energy system is determined according to the charging and discharging power ratio parameter and the rated power of the storage energy system.

[0012] Optionally, if the absolute value of the power instruction deviation value is less than or equal to the rated power of the storage energy system, the charging and discharging power of the storage energy system is determined according to the power instruction deviation value, specifically comprising:

[0013] If the absolute value of the power instruction deviation value is less than or equal to the rated power of the storage energy system, it is determined that the current working condition is a small power instruction working condition;

[0014] If the power instruction deviation value is greater than zero in the small power instruction working condition, it is determined that the frequency modulation instruction of the storage energy system is a discharging instruction, at this time, the discharging power of the storage energy system in the small power instruction working condition is equal to the power instruction deviation value;

[0015] If the power instruction deviation value is less than zero in the small power instruction working condition, it is determined that the frequency modulation instruction of the storage energy system is a charging instruction, at this time, the charging power of the storage energy system in the small power instruction working condition is equal to the absolute value of the power instruction deviation value.

[0016] Optionally, if the absolute value of the power instruction deviation value is greater than the rated power of the storage energy system, the charging and discharging power ratio parameter of the storage energy system is determined according to the real-time state of charge, specifically comprising:

[0017] If the absolute value of the power instruction deviation value is greater than the rated power of the storage energy system, it is determined that the current working condition is a large power instruction working condition;

[0018] If the power instruction deviation value is greater than zero in the high-power instruction working condition, it is determined that the frequency modulation instruction of the energy storage system is a discharge instruction, at this time, the calculation formula of the discharge power multiple parameter of the energy storage system in the high-power instruction working condition is:

[0019] ;

[0020] wherein, discharge power multiple parameter is represented; real-time state of charge is represented;

[0021] If the power instruction deviation value is less than zero in the high-power instruction working condition, it is determined that the frequency modulation instruction of the energy storage system is a charging instruction, at this time, the calculation formula of the charging power multiple parameter of the energy storage system in the high-power instruction working condition is:

[0022] ;

[0023] wherein, charging power multiple parameter is represented.

[0024] Optionally, the charging and discharging power of the energy storage system is determined according to the charging and discharging power multiple parameter and the rated power of the energy storage system, specifically including:

[0025] the discharge power of the energy storage system in the high-power instruction working condition is determined according to the discharge power multiple parameter and the rated power of the energy storage system;

[0026] the charging power of the energy storage system in the high-power instruction working condition is determined according to the charging power multiple parameter and the rated power of the energy storage system;

[0027] wherein, the calculation formula of the discharge power of the energy storage system in the high-power instruction working condition is:

[0028] ;

[0029] the calculation formula of the charging power of the energy storage system in the high-power instruction working condition is:

[0030] ;

[0031] discharge power of the energy storage system in the high-power instruction working condition is represented; charging power of the energy storage system in the high-power instruction working condition is represented; rated power of the energy storage system is represented.

[0032] Optionally, the calculation formula of the power instruction deviation value is:

[0033] ;

[0034] wherein, denotes the power instruction deviation value at time t; denotes the AGC power instruction value of the power grid at time t; denotes the real-time power generation of the unit in the power grid at time t.

[0035] Optionally, the energy storage system comprises a lithium ion battery.

[0036] The application further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the energy storage state of charge dynamic optimization control method.

[0037] The application further provides a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement the energy storage state of charge dynamic optimization control method.

[0038] The application further provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the energy storage state of charge dynamic optimization control method.

[0039] According to the specific embodiments of the application, the following technical effects are achieved:

[0040] According to the embodiments of the application, the charging and discharging power ratio parameters of the energy storage system are adjusted according to the real-time state of charge (SOC), and the charging and discharging power of the energy storage system is adjusted according to the real-time dynamic charging and discharging power ratio parameters and the rated power of the energy storage system, so that the SOC of the energy storage system is maintained in a suitable range as much as possible, the voltage of the energy storage system is stabilized, and the optimization control of the SOC of the energy storage system is achieved, thereby improving the sustainable performance of the energy storage system. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0042] Figure 1 A flowchart of the energy storage state of charge dynamic optimization control method provided for the embodiment 1 of the application is shown in the figure.

[0043] Figure 2 A specific flowchart of the frequency modulation control strategy implemented by the energy storage state of charge dynamic optimization control method provided for the embodiment 1 of the application is shown in the figure.

[0044] Figure 3 A schematic diagram of the SOC region distribution of the energy storage battery provided for embodiment 1 of the present application is shown in the figure.

[0045] Figure 4 A lithium battery auxiliary frequency modulation response curve of a thermal power generating unit under a small power instruction condition (taking energy storage discharge as an example) provided for embodiment 1 of the present application is shown in the figure.

[0046] Figure 5 A lithium battery auxiliary frequency modulation response curve of a thermal power generating unit under a large power instruction condition (taking energy storage discharge as an example) provided for embodiment 1 of the present application is shown in the figure.

[0047] Figure 6 An internal structure diagram of the computer device. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0049] The purpose of the present application is to provide a kind of energy storage state of charge dynamic optimization control method, device, medium and product, to realize the optimization control of energy storage system SOC, improve the sustainable performance of energy storage system.

[0050] In order to make the above-mentioned purposes, characteristics and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0051] Embodiment 1

[0052] As shown in the figure, the energy storage state of charge dynamic optimization control method in the present embodiment comprises: Figure 1

[0053] Step 101: obtaining the real-time state of charge of the energy storage system. Wherein, the energy storage system comprises lithium ion battery.

[0054] Step 102: determining the difference between the AGC power instruction value of the power grid and the real-time power generation power of the unit in the power grid, to obtain the power instruction deviation value.

[0055] Step 103: judging whether the absolute value of the power instruction deviation value is less than or equal to the rated power of the energy storage system.

[0056] ​If the absolute value of the power instruction deviation value is less than or equal to the rated power of the energy storage system, step 104 is performed; if the absolute value of the power instruction deviation value is greater than the rated power of the energy storage system, steps 105 and 106 are performed.

[0057] Step 104: determining the charge-discharge power of the energy storage system according to the power instruction deviation value.

[0058] Step 105: determining the charge-discharge power multiple parameter of the energy storage system according to the real-time state of charge.

[0059] Step 106: determining the charge-discharge power of the energy storage system according to the charge-discharge power multiple parameter and the rated power of the energy storage system.

[0060] In an exemplary embodiment, when the AGC power instruction value changes in steps, it is considered as a power instruction switching, at which time the above steps 101-106 are started to be performed. Whether the AGC power instruction value changes in steps is determined according to formula (1).

[0061] (1)

[0062] denotes the AGC power instruction value at the current time t1; t 1; denotes the AGC power instruction value at the previous time t0 of the current time t1; t 0; t denotes the change value of the AGC power instruction, if , the above steps 101-106 are started to be performed, and is considered as the updated value of the energy storage system frequency modulation instruction.

[0063] In an exemplary embodiment, in the above step 101, after the real-time state of charge of the energy storage system is obtained, it is further determined whether the obtained real-time state of charge satisfies the basic condition shown in formula (2). If yes, steps 102-106 are performed; otherwise, the energy storage system does not respond (prohibiting charging and discharging), and the energy storage system does not participate in frequency modulation.

[0064] (2)

[0065] In an exemplary embodiment, in the above step 102, the calculation formula of the power instruction deviation value is:

[0066] (3)

[0067] wherein, ​a power instruction deviation value at time t, which is an input of the frequency regulation instruction of the energy storage system; an AGC power instruction value of the power grid at time t, considering the continuous change of the AGC power instruction; a real-time power generation of the unit in the power grid at time t.

[0068] In an exemplary embodiment, the step 104 specifically comprises:

[0069] If the absolute value of the power instruction deviation value is less than or equal to the rated power of the energy storage system, it is determined that the current working condition is a small power instruction working condition.

[0070] If the power instruction deviation value is greater than zero in the small power instruction working condition, it is determined that the frequency regulation instruction of the energy storage system is a discharge instruction, and at this time, the discharge power of the energy storage system in the small power instruction working condition is equal to the power instruction deviation value.

[0071] If the power instruction deviation value is less than zero in the small power instruction working condition, it is determined that the frequency regulation instruction of the energy storage system is a charge instruction, and at this time, the charge power of the energy storage system in the small power instruction working condition is equal to the absolute value of the power instruction deviation value.

[0072] In an exemplary embodiment, the step 105 specifically comprises:

[0073] If the absolute value of the power instruction deviation value is greater than the rated power of the energy storage system, it is determined that the current working condition is a large power instruction working condition.

[0074] If the power instruction deviation value is greater than zero in the large power instruction working condition, it is determined that the frequency regulation instruction of the energy storage system is a discharge instruction, and at this time, the calculation formula of the discharge power multiple parameter of the energy storage system in the large power instruction working condition is:

[0075] (4)

[0076] wherein, discharge power multiple parameter; real-time state of charge.

[0077] If the power instruction deviation value is less than zero in the large power instruction working condition, it is determined that the frequency regulation instruction of the energy storage system is a charge instruction, and at this time, the calculation formula of the charge power multiple parameter of the energy storage system in the large power instruction working condition is:

[0078] (5)

[0079] wherein, charge power multiple parameter.

[0080] In one exemplary embodiment, the above step 106 specifically includes:

[0081] determining the discharge power of the energy storage system under the large-power instruction condition according to the discharge power multiple parameter and the rated power of the energy storage system , the calculation formula is:

[0082] (6)

[0083] represents the rated power of the energy storage system.

[0084] determining the charge power of the energy storage system under the large-power instruction condition according to the charge power multiple parameter and the rated power of the energy storage system , the calculation formula is:

[0085] (7)

[0086] Next, taking lithium batteries as an energy storage system as an example, combined with Figure 2 , a more specific implementation process of the above energy storage state of charge dynamic optimization control method in actual application is introduced.

[0087] This embodiment aims at the design deficiency of the protection strategy of lithium battery cycle life, which does not fully consider the main role that lithium batteries should play in the frequency modulation process, and does not focus on the problem of long-term operation of the energy storage SOC state in the boundary state. Considering the life of lithium batteries, a control strategy of dynamically adjusting the output power of lithium batteries is proposed. The large capacity and long time power output characteristics of lithium batteries are used to assist the unit to focus on improving the regulation rate of the unit, which can also reduce the number of lithium battery charging and discharging, improve the service life of lithium batteries, provide all-weather frequency modulation service within the limited energy, improve the utilization rate of energy storage resources, and then apply the wide area dynamic interval management strategy of the energy storage system to the frequency modulation control strategy, so as to keep the SOC of the energy storage system in a suitable range as much as possible, and ensure the voltage stability of the battery.

[0088] The control strategy realized by the above energy storage state of charge dynamic optimization control method includes the following steps:

[0089] Step 1: Obtain the real-time state of charge of lithium battery energy storage.

[0090] The state of charge SOC of the current lithium battery is obtained by the energy storage management system, which represents the size of the current energy storage capacity of the energy storage system, and the value range is 0~1, The closer to 1, the stronger the discharge capacity; the closer to 0, the stronger the charging capacity.

[0091] Step 2: Real-time state of charge monitoring of lithium battery energy storage.

[0092] Judge whether the real-time state of charge of lithium battery energy storage meets formula (2). If not, the energy storage system does not respond, and the lithium battery is forbidden to charge and discharge. If the condition is met, go to step 3.

[0093] Step 3: Lithium battery energy storage real-time state of charge region division.

[0094] According to the concept of life protection, as shown in Figure 3 , control the charging and discharging depth of lithium battery, the voltage stability of lithium battery, and divide the lithium battery energy storage system into 6 regions according to SOC, which are the best SOC interval (0.40, 0.70), the interval has the largest charging and discharging margin, and has a long charging and discharging capacity for various power commands; good SOC interval is (0.25, 0.40) and (0.70, 0.85); charging recovery SOC interval is (0.20, 0.25); discharging recovery SOC interval is (0.85, 0.9); limit discharging interval is (0.0, 0.20); limit charging interval is (0.9, 1.0).

[0095] Step 4: Get the AGC power command value of the power grid and the real-time power generation of the unit in the power grid, and calculate the power command deviation value according to formula (3) , which is the input value of lithium battery energy storage frequency modulation command.

[0096] Step 5: Power command discrimination.

[0097] When the AGC power command step changes, , it is considered as a large power command condition, , it is considered as a small power command condition. Under large power command, the rated power of lithium battery cannot meet the power command deviation value , and the lithium battery energy storage auxiliary thermal power unit steps into the response stage. Small power command condition, the rated power of lithium battery can meet the power command deviation value , full power auxiliary thermal power unit to track AGC power command.

[0098] Step 6: Small power command condition.

[0099] Referring to Figure 4 , the AGC command step change occurs at t 1 moment, Figure 4 , the middle red line is the AGC command line, the black line is the actual power generation curve of thermal power unit, and the blue line is the lithium power curve, t3 The thermal power unit tracks the AGC command at time 3, and the lithium battery energy storage exits. The small-power instruction condition lithium battery response instruction deviation charge-discharge instruction adopts a small-power control strategy to achieve. The small-power control strategy is: if the power instruction deviation value is greater than zero in the small-power instruction condition, it is determined that the frequency modulation instruction of the energy storage system is the discharge instruction, at this time, the discharge power of the energy storage system in the small-power instruction condition is equal to the power instruction deviation value; if the power instruction deviation value is less than zero in the small-power instruction condition, it is determined that the frequency modulation instruction of the energy storage system is the charging instruction, at this time, the charging power of the energy storage system in the small-power instruction condition is equal to the absolute value of the power instruction deviation value.

[0100] Step 7: Large-power instruction condition, dynamic SOC interval management control strategy.

[0101] In the large-power instruction condition, referring to Figure 5 , the change value is greater than the rated power of the lithium battery , due to the insufficient variable load rate capability of the unit response stage to the dynamic adjustment stage, in t 1, the small-power auxiliary unit of the lithium battery exits the dead zone, only improves the response time of the grid frequency modulation performance index, the purple diagonal line part becomes the adjustable part, and the dynamic power adjustment process is realized.

[0102] The dynamic SOC value control of the lithium battery under the large-power instruction condition is set. t 1- t 2 is the response stage, the calculation formula of the charge-discharge power of the lithium battery under the large-power instruction condition is shown in formula (6) and formula (7), wherein the calculation formula of the charge-discharge power rate parameter is shown in formula (4) and formula (5). Wait t 2, the thermal power unit enters the adjustment stage, and the adjustment stage is t 2- t 3, the rated power of the lithium battery can meet the power instruction deviation value , the lithium battery response instruction deviation charge-discharge instruction adopts a small-power control strategy to achieve.

[0103] The above embodiment aims to improve the cycle life of the lithium battery, considers the main role that the lithium battery should play in the frequency modulation process, avoids the lithium battery energy storage SOC from running in the boundary state for a long time, proposes a dynamic adjustment lithium battery SOC management control strategy that takes into account the frequency modulation performance, specifically restricts the power of the lithium battery auxiliary unit to exit the response stage, reduces the lithium battery charge-discharge times, improves the all-weather frequency modulation service provided by the lithium battery energy storage within its limited energy, and improves the utilization rate of energy storage resources. The dynamic interval management strategy is applied to the frequency modulation control strategy to ensure that the energy storage system will try to keep the SOC in a suitable range and ensure the voltage stability of the lithium battery.

[0104] Embodiment 2

[0105] A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the computer program to implement the energy storage state of charge dynamic optimization control method in embodiment 1.

[0106] Embodiment 3

[0107] A computer readable storage medium having stored thereon a computer program, the computer program being executable by a processor to implement the energy storage state of charge dynamic optimization control method in embodiment 1.

[0108] Embodiment 4

[0109] A computer program product comprising a computer program, the computer program being executable by a processor to implement the energy storage state of charge dynamic optimization control method in embodiment 1.

[0110] Embodiment 5

[0111] A computer device, the internal structure diagram of which can be as shown in Figure 6 The computer device comprises a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is used to store transactions to be processed. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to implement the energy storage state of charge dynamic optimization control method in embodiment 1.

[0112] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the object or fully authorized by all parties.

[0113] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided by the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided by the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided by the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, etc., without being limited thereto.

[0114] Any combination of the technical features of the above embodiments can be made, and in order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0115] The principles and implementation modes of the present application are described by applying specific examples herein, and the above-mentioned embodiments are only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In view of the above, the content of the present application should not be understood as a limitation.

Claims

1. A method for dynamic optimization control of the state of charge of energy storage, characterized in that, include: Obtain the real-time state of charge of the energy storage system; The difference between the AGC power command value of the power grid and the real-time power generation of the generating units in the power grid is determined to obtain the power command deviation value; If the absolute value of the power command deviation is less than or equal to the rated power of the energy storage system, then the charging and discharging power of the energy storage system is determined based on the power command deviation. If the absolute value of the power command deviation is greater than the rated power of the energy storage system, then the charge / discharge power ratio parameter of the energy storage system is determined according to the real-time state of charge, and the charge / discharge power of the energy storage system is determined according to the charge / discharge power ratio parameter and the rated power of the energy storage system. If the absolute value of the power command deviation is greater than the rated power of the energy storage system, then the charge / discharge power ratio parameter of the energy storage system is determined based on the real-time state of charge, specifically including: If the absolute value of the power command deviation is greater than the rated power of the energy storage system, then the current operating condition is determined to be a high-power command operating condition. If the power command deviation is greater than zero under high-power command conditions, then the frequency regulation command of the energy storage system is determined to be a discharge command. In this case, the calculation formula for the discharge power ratio parameter of the energy storage system under high-power command conditions is: ； in, This represents the discharge power rate parameter; Indicates the real-time state of charge; If the power command deviation is less than zero under high-power command conditions, then the frequency regulation command of the energy storage system is determined to be a charging command. In this case, the calculation formula for the charging power rate parameter of the energy storage system under high-power command conditions is: ； in, This indicates the charging power rate parameter.

2. The dynamic optimization control method for energy storage state of charge according to claim 1, characterized in that, If the absolute value of the power command deviation is less than or equal to the rated power of the energy storage system, then the charging and discharging power of the energy storage system is determined based on the power command deviation, specifically including: If the absolute value of the power command deviation is less than or equal to the rated power of the energy storage system, then the current operating condition is determined to be a low power command operating condition. If the power command deviation value is greater than zero under the low power command condition, then the frequency regulation command of the energy storage system is determined to be a discharge command. At this time, the discharge power of the energy storage system under the low power command condition is equal to the power command deviation value. If the power command deviation value is less than zero under the low power command condition, then the frequency regulation command of the energy storage system is determined to be a charging command. In this case, the charging power of the energy storage system under the low power command condition is equal to the absolute value of the power command deviation value.

3. The dynamic optimization control method for energy storage state of charge according to claim 1, characterized in that, The charging and discharging power of the energy storage system is determined based on the charging and discharging power ratio parameter and the rated power of the energy storage system, specifically including: The discharge power of the energy storage system under high power command conditions is determined based on the discharge power ratio parameter and the rated power of the energy storage system. The charging power of the energy storage system under high power command conditions is determined based on the charging power rate parameter and the rated power of the energy storage system. The formula for calculating the discharge power of the energy storage system under high-power command conditions is as follows: ； The formula for calculating the charging power of the energy storage system under high-power command conditions is as follows: ； This indicates the discharge power of the energy storage system under high-power command conditions; This indicates the charging power of the energy storage system under high-power command conditions; This indicates the rated power of the energy storage system.

4. The method for dynamic optimization control of energy storage state of charge according to claim 1, characterized in that, The formula for calculating the power command deviation is: ； in, This represents the power command deviation at time t; This represents the AGC power command value of the power grid at time t; This represents the real-time power generation of the generating units in the power grid at time t.

5. The method for dynamic optimization control of energy storage state of charge according to claim 1, characterized in that, The energy storage system includes lithium-ion batteries.

6. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the dynamic optimization control method for the state of charge of energy storage as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the dynamic optimization control method for the state of charge of energy storage as described in any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic optimization control method for the state of charge of energy storage as described in any one of claims 1-5.

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