Balancing control method and system for lithium battery energy storage system

Abstract

The invention provides an equalization control method and system of a lithium battery energy storage system, and relates to the technical field of equalization control of energy storage systems. The method comprises the following steps: acquiring environmental parameters of the current environment of the lithium battery, respectively inputting the battery model of the lithium battery and the environmental parameters of the environment into a first charging and discharging analysis model, and determining predicted temperatures of the lithium battery in different charging and discharging modes; inputting the predicted temperatures in different charging and discharging modes into a second charging and discharging analysis model to obtain a charging and discharging strategy of the lithium battery; and controlling the lithium battery energy storage system to perform charging and discharging operation according to the charging and discharging strategy of each lithium battery. According to the method, the optimal charging and discharging strategy of each lithium battery in the lithium battery energy storage system at different environment temperatures is determined by analyzing the use data of the lithium batteries of different models, the charging and discharging power of the lithium battery energy storage system is improved while the performance stability of the lithium batteries is ensured, the service life of the lithium batteries is prolonged, and the cost is reduced. And the utilization rate of the lithium battery is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage system balancing control, and particularly to a balancing control method and system for a lithium battery energy storage system. Background Art

[0002] An energy storage system is an important part of a power system. At present, battery energy storage has the advantages of mature technology, safety and reliability, and easy installation. The battery-type energy storage system is one of the commonly used energy storage system types. Due to its high energy, long service life, and environmental friendliness, lithium batteries are widely used as an excellent energy storage product in the energy storage field.

[0003] Although lithium batteries have various advantages, they are greatly affected by temperature during actual use. The change of ambient temperature is one of the factors affecting the performance of lithium batteries, and heat is also generated during the charging and discharging process of lithium batteries. Excessive temperature will have a great impact on the performance of lithium batteries. Different from ordinary battery packs, a large number of batteries are integrated in an energy storage system, and it is very difficult to make the specification parameters of each battery completely uniform. Controlling each battery to work with the same charging and discharging method can reduce the management difficulty of the energy storage system, but it is difficult for the same charging and discharging method to suit all batteries, resulting in insufficient stability of the energy storage system and low utilization rate of each battery. Summary of the Invention

[0004] The present application provides a balancing control method and system for a lithium battery energy storage system, aiming to solve at least one of the technical problems existing in the above background art.

[0005] As an aspect of the present application, a balancing control method for a lithium battery energy storage system is provided, including: Obtaining the usage sample data and specification parameter data of lithium batteries of various models in the lithium battery energy storage system. The lithium battery energy storage system includes a plurality of lithium batteries for energy storage, and the plurality of lithium batteries include at least one battery model. The sample usage data includes at least one of a charging and discharging method, battery temperature, and environmental parameters, and the specification parameter data includes at least one of a maximum number of charge and discharge cycles, a maximum charge and discharge voltage, a maximum charge and discharge current, a rated temperature, a rated input power, and a rated output power; Constructing a training data set based on the usage sample data of lithium batteries of various models, and training a pre-constructed first charge and discharge analysis model through the training data set. The first charge and discharge analysis model is a neural network model, and the first charge and discharge analysis model is used to analyze the predicted temperature of different models of lithium batteries under different charging and discharging methods; Obtain the environmental parameters of the current environment where the lithium batteries in the lithium battery energy storage system are located, and input the battery model to which each lithium battery in the lithium battery energy storage system belongs and the environmental parameters of the environment where it is located into the first charge-discharge analysis model respectively. Determine the predicted temperature of each lithium battery under different charge-discharge modes through the first charge-discharge analysis model; Input the predicted temperature of each lithium battery under different charge-discharge modes into the second charge-discharge analysis model to obtain the charge-discharge strategy of each lithium battery; Control the charge-discharge operation of the lithium battery energy storage system according to the charge-discharge strategy of each lithium battery.

[0006] Further, the step of inputting the predicted temperature of each lithium battery under different charge-discharge modes into the second charge-discharge analysis model to obtain the charge-discharge strategy of each lithium battery includes: The second charge-discharge analysis model stores the specification parameter data of each model of lithium battery; After receiving the predicted temperature of each lithium battery under different charge-discharge modes, the second charge-discharge analysis model obtains the working state of the lithium battery energy storage system; the working state includes a charging state and a discharging state; For any lithium battery, the second charge-discharge analysis model determines the corresponding specification parameter data according to the working state and the battery model of the lithium battery, determines the first power of the lithium battery according to the rule parameter data, the first power is less than the rated input power or the rated output power in the rule parameter data, and the predicted temperature under the corresponding charge-discharge mode of the first power is less than the rated temperature in the rule parameter data; Determine the first power of each lithium battery, thereby obtaining the charge-discharge strategy of each lithium battery.

[0007] Further, a training data set is constructed based on the usage sample data of each model of lithium battery, and the first charge-discharge analysis model constructed in advance is trained through the training data set, including: At least one data set centered on each battery model is constructed according to the battery signal. For each data set, a plurality of sub-data sets are constructed respectively with the environmental temperature and the charge-discharge mode as single variables. Each sub-data set records the usage sample data of different charge-discharge modes at the same environmental temperature, or the usage sample data of different environmental temperatures under the same charge / discharge mode. A training data set is composed of a plurality of sub-data sets for model training of the first charge-discharge analysis model.

[0008] Further, after obtaining the charge-discharge strategy of each lithium battery, it further includes: Obtain the working state of the lithium battery energy storage system and the current stored power of each lithium battery, input the working state of the lithium battery energy storage system, the current stored power of each lithium battery, and the charge and discharge strategy into the third charge and discharge analysis model, adjust the charge and discharge strategy of each lithium battery through the third charge and discharge analysis model, and control the lithium battery energy storage system to perform charge and discharge operations according to the adjusted charge and discharge strategy of each lithium battery.

[0009] Further, the adjusting the charge and discharge strategy of each lithium battery through the third charge and discharge analysis model includes: If the working state of the lithium battery energy storage system is the charging state, screen out the lithium batteries with the current stored power lower than the first preset power threshold, and adjust the charging strategy of the lithium batteries with the current stored power lower than the first preset power threshold according to the battery protection scheme stored in the third charge and discharge analysis model; The battery protection scheme records the charging protection strategy of each model of lithium battery, and the charging strategy includes the charging strategy that needs to be adopted after the battery stored power is lower than the first preset power threshold.

[0010] Further, in the process of controlling the lithium battery energy storage system to perform charge and discharge operations according to the charge and discharge strategy of each lithium battery, it further includes: If the stored power of any lithium battery is lower than the first preset power threshold, stop the discharge operation of the lithium battery; If the stored power of any lithium battery is higher than the second preset power threshold, stop the charging operation of the lithium battery.

[0011] As another aspect of the present application, a balancing control system for a lithium battery energy storage system is provided, including: A data acquisition module, configured to acquire the usage sample data and specification parameter data of each model of lithium battery in the lithium battery energy storage system; A sample preparation module, configured to construct a training data set based on the usage sample data of each model of lithium battery; A model training module, configured to train a pre-constructed first charge and discharge analysis model through the training data set; A strategy generation module, configured to determine the predicted temperature of each lithium battery under different charge and discharge modes through the first charge and discharge analysis model, input the predicted temperature of each lithium battery under different charge and discharge modes into the second charge and discharge analysis model, and generate the charge and discharge strategy of each lithium battery; A balancing control module, configured to control the lithium battery energy storage system to perform charge and discharge operations according to the charge and discharge strategy of each lithium battery.

[0012] Further, the system further includes: A strategy adjustment module is used to adjust the charge and discharge strategies of each lithium battery through a third charge and discharge analysis model.

[0013] The present invention has the following advantages: 1. By analyzing the usage data of lithium batteries of different models, the present invention determines the optimal charge and discharge strategies of each lithium battery in a lithium battery energy storage system at different ambient temperatures, improves the charge and discharge power of the lithium battery energy storage system while ensuring the performance stability of the lithium batteries, prolongs the service life of the lithium batteries, and enhances the utilization rate of the lithium batteries.

[0014] 2. By combining the stored electricity data of the lithium batteries, the present invention intelligently adjusts the charge and discharge strategies of the lithium batteries when the stored electricity is too high or too low, further reducing the impact of improper charge and discharge methods on the service life of the lithium batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the structures shown in these drawings without creative efforts.

[0016] Figure 1 It is a schematic flow chart of an equalization control method for a lithium battery energy storage system provided in an embodiment of the present invention.

[0017] Figure 2 It is a schematic structural diagram of an equalization control system for a lithium battery energy storage system provided in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to make the objectives, technical solutions and advantages of the present application clearer, the following further details some embodiments of the present application in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. However, those of ordinary skill in the art can understand that in each embodiment of the present application, many technical details are provided to help readers better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions required to be protected by the present application can still be implemented.

[0019] Figure 1 It is a schematic flow chart of an equalization control method for a lithium battery energy storage system provided in an embodiment of the present invention. As one aspect of the embodiment of the present invention, see Figure 1 , an equalization control method for a lithium battery energy storage system, includes: S10. Obtain the usage sample data and specification parameter data of lithium batteries of various models in the lithium battery energy storage system; It should be noted that a lithium battery energy storage system generally includes multiple lithium batteries for energy storage. Among them, multiple lithium batteries form a single battery pack, and multiple battery packs constitute the energy storage module in the lithium battery energy storage system. To ensure the stability of the energy storage system, the battery models of the lithium batteries used in a single battery pack are mostly the same. However, considering the assembly cost of the energy storage system, there may be differences in the lithium battery models between each battery pack. For example, the lithium batteries produced by a manufacturer may include multiple series, and the differences between each series are not significant, so they can be used together to assemble a lithium battery energy storage system. This application is applicable to lithium battery energy storage systems composed of single and multiple battery models. In this embodiment, a lithium battery energy storage system containing multiple battery models is taken as an example. The information carried by the collected sample usage data includes but is not limited to charge and discharge methods, battery temperature, and environmental parameters. The specification parameter data includes but is not limited to the maximum number of charge and discharge cycles, maximum charge and discharge voltage, maximum charge and discharge current, rated temperature, rated input power, and rated output power.

[0020] S20. Construct a training data set based on the usage sample data of lithium batteries of various models, and train the pre-constructed first charge and discharge analysis model through the training data set; It should be noted that the first charge and discharge analysis model is specifically a pre-constructed neural network model. The role of the trained first charge and discharge analysis model is to analyze the predicted temperature of lithium batteries of different models under different charge and discharge methods; S30. Obtain the environmental parameters of the current environment where the lithium batteries in the lithium battery energy storage system are located, input the battery model to which the lithium battery belongs and the environmental parameters of the current environment into the first charge and discharge analysis model, and output the predicted temperature of each lithium battery under different charge and discharge methods; It should be noted that after training the first charge and discharge analysis model, for the lithium battery energy storage system to be analyzed, obtain the battery model information of each lithium battery in the lithium battery energy storage system, and collect the environmental parameters of the current environment where each lithium battery is located. Specifically, the environmental parameters can be collected through various sensors arranged in the lithium battery energy storage system. The collected parameters include but are not limited to environmental temperature, humidity, and atmospheric pressure. After inputting the obtained information into the first charge and discharge analysis model, data analysis is performed through the first charge and discharge analysis model, and finally, under the current environmental parameters, the predicted temperature of each lithium battery in the lithium battery energy storage system under different charge and discharge methods is obtained. Among them, the charge and discharge method is specifically a combination of charge and discharge voltage, current, etc. Generally, each lithium battery can be charged and discharged under different charging methods. The higher the power corresponding to the charging method, the faster the charge and discharge speed, but the resulting temperature of the lithium battery will be higher.

[0021] S40. Input the predicted temperature of each lithium battery under different charge and discharge modes into the second charge and discharge analysis model to obtain the charge and discharge strategy for each lithium battery; It should be noted that when the charging method remains unchanged, the temperature of the lithium battery will be affected by the change of the ambient temperature. For example, in winter when the temperature is below zero, the lithium battery operates in a certain charge and discharge mode, and during this process, the temperature of the lithium battery will not reach its corresponding rated temperature. While in summer, when it operates in the same charge and discharge mode, the temperature of the lithium battery during operation may be too high. If the lithium battery is continuously controlled to operate in this charge and discharge mode, it will affect the performance of the lithium battery and reduce its service life. During the process of controlling the lithium battery, in order to improve the convenience of control, a unified control method can be adopted, that is, controlling each lithium battery to operate in the same charge and discharge mode. However, due to the differences in the models of lithium batteries, if the power corresponding to the charge and discharge mode is too high, it may cause the temperature of some lithium batteries to be too high. And if a charge and discharge mode with a lower power is selected, although the impact on the performance of the battery is smaller, the overall power of the energy storage system does not reach the maximum, and the working efficiency is not high.

[0022] In this case, when determining the predicted temperature of each lithium battery under different charge and discharge modes, the second charge and discharge analysis model is used to analyze each lithium battery separately to obtain the charge and discharge strategy for each lithium battery. Among them, the obtained charge and discharge strategy for each lithium battery records the optimal charge and discharge mode suitable for the lithium battery, which can ensure that the temperature of the lithium battery will not be too high while maximizing the power as much as possible.

[0023] S50. Control the lithium battery energy storage system to perform charge and discharge operations according to the charge and discharge strategy of each lithium battery.

[0024] As an exemplary implementation, for step S20, a training data set is constructed based on the usage sample data of lithium batteries of various models, and the pre-constructed first charge and discharge analysis model is trained through the training data set. Specifically, it includes: Construct at least one data set centered on each battery model according to the battery signal, where the number of data sets specifically depends on the number of battery models of the lithium batteries collected; For each data set, multiple sub-data sets are constructed by taking the ambient temperature and the charge and discharge mode as single variables respectively. Each sub-data set records the usage sample data of different charge and discharge modes at the same ambient temperature, or the usage sample data of different ambient temperatures under the same charge / discharge mode; Exemplarily, taking the ambient temperature as a single variable, the ambient temperature can be -1°C, 15°C, 23°C, 38°C, etc. The usage sample data recorded in each data set corresponds to the same battery model. The usage sample data recorded in the sub-data set with the ambient temperature as a single variable further corresponds to the same ambient temperature and the same charging method or discharging method, that is, multiple usage sample data under different charging methods or discharging methods at the same ambient temperature; taking the charge-discharge method as an example, the usage sample data recorded in each sub-data set with the charge-discharge method as a single variable corresponds to the same charging method or discharging method, that is, multiple usage sample data at different ambient temperatures under the same charging method or discharging method. A training data set is composed of multiple sub-data sets and is used for model training of the first charge-discharge analysis model.

[0025] As an exemplary implementation, for step S40, inputting the predicted temperature of each lithium battery under different charge-discharge methods into the second charge-discharge analysis model to obtain the charge-discharge strategy of each lithium battery specifically includes: The second charge-discharge analysis model stores the specification parameter data of each model of lithium battery. Among them, the specification parameter data of each model of lithium battery can be extracted from the lithium battery description information provided by the manufacturer; After receiving the predicted temperature of each lithium battery under different charge-discharge methods, the second charge-discharge analysis model obtains the working state of the lithium battery energy storage system; the working state includes the charging state and the discharging state. Among them, the working state of the lithium battery energy storage system is not limited to the current working state, and can also be the working state about to change; For any lithium battery, the second charge-discharge analysis model determines the corresponding specification parameter data according to the working state and the battery model of the lithium battery, and determines the first power of the lithium battery according to the rule parameter data; It should be noted that here taking the charging state as an example, the principle of determining the first power is that the predicted temperature under the charging method corresponding to the first power cannot be too high, and the larger the first power, the better, so as to improve the overall working efficiency of the energy storage system. That is, the first power is less than the rated input power in the rule parameter data, the predicted temperature under the charge-discharge method corresponding to the first power is less than the rated temperature in the rule parameter data, and under the premise of satisfying the above two conditions, the larger the first power, the better.

[0026] The first power of each lithium battery is determined through the above method, thereby obtaining the charge-discharge strategy of each lithium battery.

[0027] As an exemplary implementation, for step S40, after obtaining the charge-discharge strategy of each lithium battery, it further includes: Obtain the working state of the lithium battery energy storage system and the current stored power of each lithium battery, and input the working state of the lithium battery energy storage system, the current stored power of each lithium battery, and the charge and discharge strategy into the third charge and discharge analysis model; It should be noted that the role of the third charge and discharge analysis model is to adjust the charge and discharge strategy to reduce the impact on the lithium battery during the charge and discharge process. Specifically, when the power of the lithium battery is too low, if it is directly charged in a high-power charging mode, the service life of the battery will be affected to a certain extent. Therefore, it can be charged in a lower-power charging mode to improve the service life of the lithium battery.

[0028] Among them, adjusting the charge and discharge strategy of each lithium battery through the third charge and discharge analysis model specifically includes: If the working state of the lithium battery energy storage system is the charging state, screen out the lithium batteries with the current stored power lower than the first preset power threshold. For the screened lithium batteries, adjust the charging strategy of the lithium batteries with the stored power lower than the first preset power threshold according to the battery protection scheme stored in the third charge and discharge analysis model; It should be noted that the battery protection scheme records the charging protection strategy of each type of lithium battery. The charging strategy specifically includes the charging strategy that needs to be adopted when the battery stored power is lower than the first preset power threshold, that is, the specific charging method. After adjusting the charge and discharge strategy of each lithium battery through the third charge and discharge analysis model, control the lithium battery energy storage system to perform charge and discharge operations according to the adjusted charge and discharge strategy of each lithium battery.

[0029] When the stored power of the lithium battery is charged to not less than the first preset power threshold using the charging strategy that needs to be adopted after using less than the first preset power threshold, the charging strategy output by the second charge and discharge analysis model can be used for charging.

[0030] As an exemplary implementation, during the process of controlling the lithium battery energy storage system to perform charge and discharge operations according to the charge and discharge strategy of each lithium battery, it further includes: If the stored power of any lithium battery is lower than the first preset power threshold, stop the discharge operation of the lithium battery; If the stored power of any lithium battery is higher than the second preset power threshold, stop the charging operation of the lithium battery.

[0031] It should be noted that during the charging and discharging process, too high or too low stored power of the lithium battery will have a certain impact on the service life of the lithium battery. Therefore, during actual use, for example, during the power storage process, when a certain lithium battery is charged to a stored power higher than the second preset power threshold, the charging of this lithium battery is stopped, and the remaining lithium batteries with stored power lower than the second preset power threshold are used to store electrical energy. During the discharging process, when a certain lithium battery is discharged to a stored power reduced to the first preset power threshold, the discharging of this lithium battery is stopped, and the remaining lithium batteries with stored power higher than the first preset power threshold are used to release electrical energy.

[0032] An equalization control method for a lithium battery energy storage system provided by the present application determines the optimal charging and discharging strategies of each lithium battery in the lithium battery energy storage system at different ambient temperatures by analyzing the usage data of different models of lithium batteries, improves the charging and discharging power of the lithium battery energy storage system while ensuring the performance stability of the lithium battery, extends the service life of the lithium battery, and improves the utilization rate of the lithium battery.

[0033] An equalization control method for a lithium battery energy storage system provided by the present application also combines the stored power data of the lithium battery and intelligently adjusts the charging and discharging strategies of the lithium battery when the stored power is too high or too low, further reducing the impact of improper charging and discharging methods on the service life of the lithium battery.

[0034] As another aspect of the embodiment of the present invention, based on an equalization control method for a lithium battery energy storage system provided by the embodiment of the present invention, refer to Figure 2 , an equalization control system for a lithium battery energy storage system, including: A data acquisition module for acquiring the usage sample data and specification parameter data of each model of lithium battery in the lithium battery energy storage system; Among them, the sample usage data includes at least one of the charging and discharging methods, battery temperature, and environmental parameters, and the specification parameter data includes at least one of the maximum number of charging and discharging times, maximum charging and discharging voltage, maximum charging and discharging current, rated temperature, rated input power, and rated output power; A sample preparation module for constructing a training data set based on the usage sample data of each model of lithium battery; A model training module for training a pre-constructed first charging and discharging analysis model through the training data set, where the first charging and discharging analysis model is a neural network model, and the first charging and discharging analysis model is used to analyze the predicted temperature of different models of lithium batteries under different charging and discharging methods; A strategy generation module for determining the predicted temperature of each lithium battery under different charging and discharging methods through the first charging and discharging analysis model, and inputting the predicted temperature of each lithium battery under different charging and discharging methods into the second charging and discharging analysis model to generate the charging and discharging strategy of each lithium battery; The balancing control module is used to control the charge and discharge operations of the lithium battery energy storage system according to the charge and discharge strategies of each lithium battery.

[0035] As an exemplary embodiment, the system further includes: The strategy adjustment module is used to adjust the charge and discharge strategies of each lithium battery through the third charge and discharge analysis model.

[0036] It should be understood that those of ordinary skill in the art can make improvements or transformations according to the above description, and all such improvements and transformations should fall within the protection scope of the appended claims of the present invention. The parts not described in detail in this specification belong to the prior art well known to those of ordinary skill in the art.

Claims

1. A balanced control method for a lithium battery energy storage system, characterized in that: include: Obtaining usage sample data and specification parameter data of each model of lithium batteries in a lithium battery energy storage system, wherein the lithium battery energy storage system includes a plurality of lithium batteries for energy storage, wherein the plurality of lithium batteries include at least one battery model, wherein the sample usage data includes at least one of a charge and discharge mode, a battery temperature, and an environmental parameter, and wherein the specification parameter data includes at least one of a maximum number of charge and discharge times, a maximum charge and discharge voltage, a maximum charge and discharge current, a rated temperature, a rated input power, and a rated output power; A training data set is constructed based on usage sample data of lithium batteries of various models, and a first charge and discharge analysis model constructed in advance is trained by the training data set, wherein the first charge and discharge analysis model is a neural network model, and the first charge and discharge analysis model is used to analyze the predicted temperature of lithium batteries of different models under different charge and discharge modes; Obtaining environmental parameters of the environment in which the lithium batteries in the lithium battery energy storage system are currently located, inputting the battery model and environmental parameters of the environment in which each lithium battery in the lithium battery energy storage system is located into the first charge and discharge analysis model, and determining the predicted temperature of each lithium battery under different charge and discharge modes through the first charge and discharge analysis model; Inputting the predicted temperature of each lithium battery under different charging and discharging modes into the second charging and discharging analysis model to obtain the charging and discharging strategy of each lithium battery; The lithium battery energy storage system is controlled to perform charging and discharging operations according to the charging and discharging strategy of each lithium battery.

2. A balanced control method for a lithium battery energy storage system as claimed in claim 1, characterized in that: The predicted temperature of each lithium battery under different charging and discharging modes is input into the second charging and discharging analysis model to obtain the charging and discharging strategy of each lithium battery, including: The second charge and discharge analysis model stores the specification parameter data of each model of lithium battery; After receiving the predicted temperature of each lithium battery under different charging and discharging modes, the second charging and discharging analysis model obtains the working state of the lithium battery energy storage system; the working state includes a charging state and a discharging state; For any lithium battery, the second charge and discharge analysis model determines the corresponding specification parameter data according to the working state and the battery model of the lithium battery, and determines the first power of the lithium battery according to the rule parameter data, the first power is less than the rated input power or the rated output power in the rule parameter data, and the predicted temperature under the charge and discharge mode corresponding to the first power is less than the rated temperature in the rule parameter data; The first power of each lithium battery is determined, thereby obtaining a charge and discharge strategy for each lithium battery.

3. A balanced control method for a lithium battery energy storage system as claimed in claim 1, characterized in that: A training data set is constructed based on usage sample data of lithium batteries of various models, and a pre-constructed first charge and discharge analysis model is trained by the training data set, including: At least one data set centered on each battery model is constructed according to the battery signal. For each data set, multiple sub-data sets are constructed with ambient temperature and charge and discharge mode as single variables. Each sub-data set records usage sample data of different charge and discharge modes at the same ambient temperature, or usage sample data of different ambient temperatures under the same charge / discharge mode. Multiple sub-data sets form a training data set for model training of the first charge and discharge analysis model.

4. A balanced control method for a lithium battery energy storage system as claimed in claim 1, characterized in that: After obtaining the charging and discharging strategy for each lithium battery, it also includes: The working state of the lithium battery energy storage system and the current storage capacity of each lithium battery are obtained, and the working state of the lithium battery energy storage system, the current storage capacity of each lithium battery and the charge and discharge strategy are input into a third charge and discharge analysis model, and the charge and discharge strategy of each lithium battery is adjusted through the third charge and discharge analysis model, and the lithium battery energy storage system is controlled to perform charge and discharge operations according to the adjusted charge and discharge strategy of each lithium battery.

5. A balanced control method for a lithium battery energy storage system as claimed in claim 4, characterized in that: The step of adjusting the charge and discharge strategy of each lithium battery by using the third charge and discharge analysis model includes: If the working state of the lithium battery energy storage system is a charging state, screen out lithium batteries whose current storage capacity is lower than a first preset power threshold, and adjust the charging strategy of the lithium batteries whose storage capacity is lower than the first preset power threshold according to the battery protection scheme stored in the third charge and discharge analysis model; The battery protection scheme records the charging protection strategy for each type of lithium battery, and the charging strategy includes a charging strategy to be adopted when the battery storage capacity is lower than a first preset capacity threshold.

6. A balanced control method for a lithium battery energy storage system as claimed in claim 5, characterized in that: In the process of controlling the lithium battery energy storage system to perform charging and discharging operations according to the charging and discharging strategy of each lithium battery, it also includes: If the storage capacity of any lithium battery is lower than the first preset capacity threshold, the discharge operation of the lithium battery is stopped; If the storage capacity of any lithium battery is higher than the second preset capacity threshold, the charging operation of the lithium battery is stopped.

7. A balancing control system for a lithium battery energy storage system, characterized in that: The system is used to implement a balanced control method for a lithium battery energy storage system according to any one of claims 1 to 6, comprising: A data acquisition module is used to obtain usage sample data and specification parameter data of various types of lithium batteries in the lithium battery energy storage system; A sample preparation module is used to construct a training data set based on usage sample data of various types of lithium batteries; A model training module, used for training a pre-built first charge-discharge analysis model using the training data set; A strategy generation module, used to determine the predicted temperature of each lithium battery under different charge and discharge modes through the first charge and discharge analysis model, input the predicted temperature of each lithium battery under different charge and discharge modes into the second charge and discharge analysis model, and generate a charge and discharge strategy for each lithium battery; The balancing control module is used to control the lithium battery energy storage system to perform charging and discharging operations according to the charging and discharging strategy of each lithium battery.

8. The system according to claim 7, characterized in that The system further comprises: The strategy adjustment module is used to adjust the charge and discharge strategy of each lithium battery through the third charge and discharge analysis model.

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