A method, system, terminal and medium for balancing the health status of multiple battery clusters

Abstract

The present invention discloses a method, system, terminal, and medium for balancing the health status of multiple battery clusters. The method first sets a grid-connected power reference value for the energy storage system and upper and lower limits for the transmission power of the energy storage converter, determines the number of energy storage converters involved in the operation of the energy storage system, and obtains the health status of each battery cluster at a preset period. The method then uses the analytic hierarchy process to evaluate the health status of each battery cluster and construct a target layer and indicator judgment layer matrix to determine the weight coefficient of the grid-connected power borne by each energy storage converter. It then determines whether the power of each energy storage converter is within the upper and lower limits. If not, the number of converters involved and the corresponding transmission power are adjusted until the power of each energy storage converter is within the range. The method can effectively extend the overall service life of the energy storage system and improve the safety and economy of the energy storage system.

Description

Technical Field

[0001] The present invention relates to the technical field of grid-connected multi-energy storage converters in energy storage power stations, and in particular to a method, system, terminal, and medium for balancing the health status of multiple battery clusters. Background Art

[0002] With the rapid development of new energy, electrochemical energy storage has become an indispensable key factor in promoting the development of new energy due to its flexible resource control. Renewable energy is weather-dependent, and its output power is intermittent and volatile. It requires many energy storage systems to support grid operation to maintain power stability. During the operation of large-scale energy storage, internal and external factors can easily lead to inconsistent degradation rates between energy storage units. Therefore, when the energy storage system and the grid perform power conversion, how to reasonably allocate the power of multiple energy storage converters (PCS) to balance the health status of the battery cluster is a problem that the present invention needs to solve.

[0003] In response to the inconsistency of battery clusters in energy storage systems, existing power allocation algorithms can be roughly divided into two types: one focuses on achieving battery state balance, and the other focuses on optimizing battery degradation. Optimization algorithms aimed at balancing battery states include power-based algorithms and battery state of charge (SOC)-based algorithms. Existing battery state-based sharing algorithms ignore the degradation characteristic effects, which may lead to a higher degradation rate for the entire energy storage system. Sharing algorithms that optimize battery degradation usually take degradation characteristic effects into account. When there are differences in battery life or degradation rates between energy storage units, the focus should be shifted to balancing battery health status to extend the service life of the entire energy storage system. Therefore, the power allocation strategy for balancing the health status of battery clusters designed in the present invention is to improve the safety and stability of the energy storage system under the premise of grid safety. Summary of the Invention

[0004] The present invention aims to provide a method, system, terminal, and medium for balancing the health status of multiple battery clusters. When an energy storage system participates in grid power conversion, the method uses the analytic hierarchy process to evaluate the health status of each battery cluster and rationally allocate the power of multiple PCSs, thereby balancing the health status of each battery cluster and extending the overall service life and safety of the energy storage system.

[0005] In a first aspect, a method for balancing the health status of multiple battery clusters is provided, comprising:

[0006] Set the grid-connected power reference value P of the energy storage system ref And the upper and lower limits of the energy storage system PCS transmission power, the upper and lower limits of which are shown as follows.

[0007] P min <·P batt_1 ,P batt_2 ,…,P batt_n ≤Pbatt_N

[0008] Where, P min The lower limit of PCS power transmission is to prevent the harmonic content of PCS grid connection from being lower than 5%; P batt_n P is the power of the nth PCS; batt_N This is the rated operating power of the PCS and also the upper limit of the PCS transmission power.

[0009] Determine the number of PCS units n involved in the operation of the energy storage system, which is obtained by the following formula:

[0010]

[0011] Wherein, the number of PCS units involved in the operation, n, is an integer rounded down.

[0012] Collect the health status SOH of each battery cluster involved in the operation of the energy storage system and record them as SOH1, SOH2, ..., SOH n , SOH n The health status of the nth battery cluster;

[0013] Combined with the hierarchical analysis method, the health status of each battery cluster involved in the operation is evaluated and quantified. The higher the health status SOH of the battery cluster, the higher the score. Based on the score, the target layer and indicator layer judgment matrix are constructed, as shown in the following table, where Z represents the target layer, a 1n =1 / a n1 ;

[0014] Z <![CDATA[SOH1]]> <![CDATA[SOH2]]> … <![CDATA[SOH n ]]> <![CDATA[SOH1]]> 1 <![CDATA[a 12 ]]> … <![CDATA[a 1n ]]> <![CDATA[SOH2]]> <![CDATA[a 21 ]]> 1 … <![CDATA[a 2n ]]> … … … … … <![CDATA[SOH n ]]> <![CDATA[a n1 ]]> <![CDATA[a n2 ]]> … 1

[0015] The judgment matrix is ​​normalized by column, and the weight ratio of each battery cluster is obtained by arithmetic mean method. The weight ratio of each battery cluster is named w1, w2, ..., w n ;

[0016] To obtain the output power of each PCS, the calculation process is as follows:

[0017]

[0018] Determine whether the transmission power of each PCS is within the set power upper and lower limits. If the power allocated to a PCS is less than the transmission power lower limit, the operation of the PCS is cancelled, and the number of PCSs participating in the system becomes n-1. Similarly, the weight coefficient of the grid-connected power borne by n-1 PCSs and the corresponding power size are obtained according to the above method; further, if the power allocated to n-1 PCSs exceeds the transmission power upper limit, the transmission power size of the PCS is output according to the upper limit, and the remaining grid-connected power P ref -P batt_nThe same method is used to obtain the grid-connected power weight coefficients and corresponding power levels for n-2 PCSs. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is considered complete.

[0019] To prevent over-discharge and over-charge of the battery cluster, the SOC discharge lower limit of each battery cluster in the energy storage system is set to 20%, and the charge upper limit is set to 95%.

[0020] In a second aspect, a system for balancing the health status of multiple battery clusters is provided, comprising:

[0021] Parameter setting module, used to set the energy storage system grid-connected power reference value and the energy storage system PCS transmission power upper and lower limits;

[0022] A data acquisition module is used to obtain the health status of each battery cluster participating in the operation of the energy storage system at a preset period;

[0023] The power distribution module is used to optimize the grid-connected power distribution of each converter in the energy storage system in combination with the health status of each battery cluster in the energy storage system. It evaluates the health status of each battery cluster in the energy storage system based on the hierarchical analysis method and obtains the weight coefficient of the power distribution of each battery cluster. It then determines whether the transmission power of each PCS is within the set upper and lower limits of power. If the power allocated to a PCS is less than the lower limit of the transmission power, the operation of the PCS is cancelled, and the number of PCSs participating in the operation of the system becomes n-1. The same method is used to obtain the weight coefficient of the grid-connected power borne by n-1 PCSs and the corresponding power size; further, if the power size allocated to n-1 PCSs exceeds the upper limit of the transmission power, the transmission power size of the PCS is output according to the upper limit, and the remaining grid-connected power P ref -P batt_n The same method is used to obtain the grid-connected power weight coefficients and corresponding power levels for n-2 PCSs. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is considered complete.

[0024] In a third aspect, an electronic terminal is provided, comprising:

[0025] a memory having a computer program stored thereon;

[0026] A processor is configured to load and execute the computer program to implement any one of the above methods for balancing the health status of multiple battery clusters.

[0027] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for balancing the health status of multiple battery clusters as described above is implemented.

[0028] Beneficial effects

[0029] The present invention proposes a method, system, terminal and medium for balancing the health status of multiple battery clusters. When multiple PCSs in an energy storage system bear grid-connected power instructions, the health status of each battery cluster is evaluated in combination with the hierarchical analysis method and a target layer and indicator judgment layer matrix is ​​constructed to obtain the weight coefficient of the grid-connected power borne by each energy storage converter. The transmission power of each PCS is reasonably allocated on the basis of grid-connected safety. The present invention can effectively increase the overall service life of the energy storage system and improve the safety and economy of the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 is a flow chart of a method for balancing the health status of multiple battery clusters provided by an embodiment of the present invention;

[0032] Figure 2 This is a graph of grid-connected harmonic content at different PCS output powers provided by an embodiment of the present invention;

[0033] Figure 3 Schematic diagram of the grid-connected topology of the energy storage system provided by an embodiment of the present invention;

[0034] Figure 4 This is a diagram showing changes in the health status of each battery cluster using the method of the present invention provided in an embodiment of the present invention;

[0035] Figure 5 This is a diagram showing changes in the health status of each battery cluster under power sharing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] To make the objectives, technical solutions, and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other implementations obtained by those of ordinary skill in the art without inventive effort are within the scope of protection of the present invention.

[0037] like Figure 1 As shown, an embodiment of the present invention provides a method for balancing the health status of multiple battery clusters, including the following steps:

[0038] S1: Set the grid-connected power reference value P of the energy storage system refThe upper and lower limits of PCS transmission power are 15kW and 6kW respectively.

[0039] In this embodiment, the grid-connected power reference value P is set ref The sum of the rated output power of all participating battery clusters. The upper limit of PCS transmission power is the rated power of PCS. In order to ensure that the harmonic content of energy storage grid connection is within 5%, combined with Figure 2 The lower limit of PCS transmission power is set to 40% of the rated power, that is, 6kW.

[0040] S2: Determine the number of PCSs put into operation. According to the calculation formula of the invention, the number n of PCSs involved in the operation is 4 (24 / 6=4).

[0041] For the sake of convenience, in this embodiment, Figure 3 A topology including four battery clusters and four PCSs is provided as an example for explanation.

[0042] S3: The health status of each battery cluster participating in the operation of the energy storage system is obtained at a preset period, and the health status of each battery cluster is recorded as SOH1, SOH2, SOH3 and SOH4 respectively.

[0043] In this embodiment, it is assumed that the health status of each battery cluster is: SOH1 = 98%, SOH2 = 94%, SOH3 = 92% and SOH4 = 90%.

[0044] S4: Evaluate the health status of each battery cluster and quantify the value by combining the hierarchical analysis method. The scores of battery clusters in different health states refer to Table 1:

[0045] Table 1 Scoring reference table

[0046] Factor i vs. factor j Equally important Slightly important Strong and important Strongly important Extremely important The middle value of two adjacent judgments Quantized value 1 3 5 7 9 2，4，6，8

[0047] Furthermore, based on Table 1, output scores are assigned to battery clusters at different health states, with a score range of 1-9, with higher SOH scores corresponding to higher scores. The initial battery SOH is 100%, resulting in a score of 9. When the battery's current SOH is 80%, it is typically retired. Therefore, in this embodiment, a battery cluster with a health state of 80% is assigned a score of 1.

[0048] The scoring in this embodiment adopts linear scoring, and the health status value SOH of any battery cluster is x The resulting score y is calculated as follows:

[0049] y=9-8(100-SOH x ) / 20

[0050] Therefore, the initial scores of the battery clusters SOH1, SOH2, SOH3 and SOH4 in this embodiment are y1=8.2, y2=6.6, y3=5.8, and y4=5, respectively. Based on the corresponding scores, a judgment matrix of the target layer and the indicator layer can be constructed. The resulting matrix is ​​shown in Table 2 below:

[0051] Table 2 Judgment matrix of target layer and indicator layer

[0052] Z <![CDATA[SOH1]]> <![CDATA[SOH2]]> <![CDATA[SOH3]]> <![CDATA[SOH4]]> <![CDATA[SOH1]]> 1 1.242424 1.413793 1.64 <![CDATA[SOH2]]> 0.804878 1 1.137931 1.32 <![CDATA[SOH3]]> 0.707317 0.878788 1 1.16 <![CDATA[SOH4]]> 0.609756 0.757576 0.862069 1

[0053] Furthermore, the above matrix is ​​normalized by columns, and the resulting matrix is ​​shown in Table 3 below:

[0054] Table 3 The target layer and indicator layer judgment matrix are normalized matrices

[0055] Z <![CDATA[SOH1]]> <![CDATA[SOH2]]> <![CDATA[SOH3]]> <![CDATA[SOH4]]> <![CDATA[SOH1]]> 0.3203 0.3203 0.3203 0.3203 <![CDATA[SOH2]]> 0.2578 0.2578 0.2578 0.2578 <![CDATA[SOH3]]> 0.2266 0.2266 0.2266 0.2266 <![CDATA[SOH4]]> 0.1953 0.1953 0.1953 0.1953

[0056] Furthermore, the arithmetic mean method is used to obtain the weights of the indicators in each row in Table 3, and the weight coefficients corresponding to the battery clusters SOH1, SOH2, SOH3 and SOH4 are w1=0.3203, w2=0.2578, w3=0.2266 and w4=0.1953.

[0057] Furthermore, the power of each PCS transmission is obtained according to the above weight coefficients as follows:

[0058]

[0059] Since the power of the fourth PCS is less than the PCS transmission power lower limit of 6kW, according to the method of the present invention, the operation of the fourth PCS is canceled at this time, n becomes 3, and the judgment matrix of the target layer and the indicator layer becomes as shown in Table 4:

[0060] Table 4 New target layer and indicator layer judgment matrix

[0061] Z <![CDATA[SOH1]]> <![CDATA[SOH2]]> <![CDATA[SOH3]]> <![CDATA[SOH1]]> 1 1.242424 1.413793 <![CDATA[SOH2]]> 0.804878 1 1.137931 <![CDATA[SOH3]]> 0.707317 0.878788 1

[0062] Furthermore, the matrix in Table 4 is normalized by columns. The subsequent method is similar to that used to obtain the transmission power of the three PCSs as follows:

[0063]

[0064] As can be seen from the above formula, the power allocation of these three PCSs is within the constraint range. At this time, the system will complete the grid-connected power transmission according to the above power allocation.

[0065] In this embodiment, in order to prevent the battery cluster from being over-discharged and over-charged, the lower discharge limit of each battery cluster in the energy storage system is set to 20%, and the upper charge limit is set to 95%.

[0066] The power is allocated according to the above steps in each operation. The aging of the four battery clusters after 5000 hours of operation is as follows: Figure 4 As shown in the figure, the health status of each battery cluster gradually becomes balanced, which effectively improves the service life of the entire energy storage system. If these four battery clusters are directly operated at the average power, the battery with the highest health status will exit the operation early, such as Figure 5 As shown in the figure, after 3556 hours of system operation, the health status of the battery cluster dropped to 80%, thereby reducing the capacity of the entire energy storage system. Compared with this, the proposed method of the present invention can extend the service life of the energy storage station as a whole by 40.6% ((5000-3556) / 3556≈0.406), which fully demonstrates the effectiveness of the present invention.

[0067] This embodiment provides a method for balancing the health status of multiple battery clusters. When allocating grid-connected power to each PCS in an energy storage system, the method uses the analytic hierarchy process to score the health status of each battery cluster and construct a target layer and indicator layer judgment matrix. Based on the health status of each battery cluster and the upper and lower limits of the PCS operating power, the power of each PCS is rationally allocated. This effectively extends the overall service life of the energy storage power station while ensuring grid connection safety, improving system safety and economy.

[0068] An embodiment of the present invention further provides a system for balancing the health status of multiple battery clusters, including:

[0069] Parameter setting module, used to set the energy storage system grid-connected power reference value and the energy storage system PCS transmission power upper and lower limits;

[0070] A data acquisition module is used to obtain the health status of each battery cluster in the energy storage system at a preset period;

[0071] The power distribution module is used to optimize the grid-connected power distribution of each converter in the energy storage system in combination with the health status of each battery cluster in the energy storage system. It evaluates the health status of each battery cluster in the energy storage system based on the hierarchical analysis method and obtains the weight coefficient of the power distribution of each battery cluster. It then determines whether the transmission power of each PCS is within the set upper and lower limits of power. If the power allocated to a PCS is less than the lower limit of the transmission power, the operation of the PCS is cancelled, and the number of PCSs participating in the operation of the system becomes n-1. The same method is used to obtain the weight coefficient of the grid-connected power borne by n-1 PCSs and the corresponding power size; further, if the power size allocated to n-1 PCSs exceeds the upper limit of the transmission power, the transmission power size of the PCS is output according to the upper limit, and the remaining grid-connected power P ref -P batt_nThe same method is used to determine the grid-connected power weights and corresponding power levels for n-2 PCSs. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is complete, and the system can transmit at the calculated power level.

[0072] When the power distribution module performs power distribution, the power transmitted by each PCS is calculated using the following formula:

[0073]

[0074] Where, P batt_n w is the power of the nth PCS; n P is the weight coefficient of the grid-connected power borne by the nth PCS; ref is the grid-connected power instruction size of the energy storage system.

[0075] The transmission power of each PCS must be within the set upper and lower power limits, as shown below.

[0076] P min <·P batt_1 ,P batt_2 ,…,P batt_n ≤P batt_N

[0077] Where, P min The lower limit of PCS power transmission, which prevents the harmonic content of PCS grid connection from being lower than 5%; P batt_N This is the rated operating power of the PCS and also the upper limit of the PCS transmission power.

[0078] The number of PCS units involved in the operation, n, is obtained by the following formula:

[0079]

[0080] In the formula, the number of units involved in the operation, n, is an integer rounded down.

[0081] The weight coefficient of the grid-connected power borne by each PCS is obtained by the hierarchical analysis method. First, the health status of each battery cluster is evaluated, and the target layer and indicator judgment layer matrices are constructed. Then, the matrix is ​​normalized by column, and the arithmetic average method is used to obtain the weight coefficient of the grid-connected power borne by each PCS.

[0082] It should be understood that the functional unit modules in various embodiments of the present invention can be concentrated in one processing unit, or each unit module can exist physically separately, or two or more unit modules can be integrated into one unit module, and can be implemented in the form of hardware or software.

[0083] An embodiment of the present invention further provides an electronic terminal, including:

[0084] a memory having a computer program stored thereon;

[0085] A processor is configured to load and execute the computer program to implement any one of the above methods for balancing the health status of multiple battery clusters.

[0086] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program implements any of the above methods for balancing the health status of multiple battery clusters.

[0087] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0088] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0089] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0092] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for balancing the health status of multiple battery clusters, characterized in that: include: Set the energy storage system grid-connected power reference value and the energy storage system PCS transmission power upper and lower limits; Determine the number of energy storage converters involved in the operation of the energy storage system; Obtain the health status of each battery cluster involved in the energy storage system at a preset period; The analytic hierarchy process is used to evaluate the health status of each battery cluster and construct a target layer and indicator judgment layer matrix. This is used to determine the weight coefficient of each energy storage inverter's grid-connected power. This determines whether the power of each energy storage inverter is within the upper and lower power limits. If not, the number of participating units and the corresponding transmission power are adjusted until the power of each energy storage inverter is within the range, and the system can then operate again. The weight coefficient of the grid-connected power borne by each PCS is obtained by the following method: Obtain the health status SOH of each battery cluster involved in the energy storage system and record them as SOH1, SOH2, ..., SOH n , SOH n The health status of the nth battery cluster; The health status of each battery cluster is evaluated by combining the hierarchical analysis method. The larger the health status SOH of the battery cluster, the higher the score. Based on the score of each battery cluster, the target layer and indicator layer judgment matrix are constructed. The resulting matrix is ​​shown in the following table: Where Z represents the target layer, a 1n =1 / a n1 ; The judgment matrix is ​​normalized by column, and the weight coefficients w1, w2, ..., w of each PCS grid-connected power are obtained by arithmetic mean method. n ; When the power allocated by the PCS is not within the set range, the number of units participating in the operation and the corresponding transmission power are adjusted as follows: When the power allocated to a PCS is less than the lower limit of the transmission power, the operation of the PCS is cancelled, and the number of PCSs participating in the system becomes n-1. The weight coefficient of the grid-connected power borne by n-1 PCSs is obtained, and the power allocated to n-1 PCSs is calculated; further, if the power allocated to n-1 PCSs exceeds the upper limit of the transmission power, the transmission power of the PCS is output according to the upper limit, that is, the rated power is output, and the remaining grid-connected power P ref -P batt_n Similarly, the weight coefficients of the grid-connected power shared by n-2 PCSs are obtained using the above method, and the power allocated to n-2 PCSs is calculated. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is considered complete. Where, P batt_n is the power of the nth PCS, P ref is the grid-connected power instruction size of the energy storage system.

2. The method for balancing the health status of multiple battery clusters according to claim 1, characterized in that: The upper and lower limits of the PCS transmission power of the energy storage system are set as follows: P min <·P batt_1 ,P batt_2 ,…,P batt_n ≤P batt_N Where n is the number of PCS units involved in the energy storage system operation; P min The lower limit of PCS power transmission, which prevents the harmonic content of PCS grid connection from being lower than 5%; P batt_n P is the power of the nth PCS; batt_N This is the rated operating power of the PCS and also the upper limit of the PCS transmission power.

3. The method for balancing the health status of multiple battery clusters according to claim 2, characterized in that: The number of PCS units n involved in the operation of the energy storage system is obtained by the following formula: Wherein, the number of PCS units involved in the operation, n, is an integer rounded down.

4. The method for balancing the health status of multiple battery clusters according to claim 1, characterized in that: The power of each PCS participating in the grid connection is calculated by the following formula: Where w n is the weight coefficient of the grid-connected power borne by the nth PCS, where w1+w2+…+w n =1;P ref is the grid-connected power instruction size of the energy storage system.

5. The method for balancing the health status of multiple battery clusters according to claim 1, characterized in that: The lower discharge limit of each battery cluster in the energy storage system is set to 20%, and the upper charge limit is set to 95%.

6. A system for balancing the health status of multiple battery clusters, characterized in that: include: Parameter setting module, used to set the energy storage system grid-connected power reference value and the energy storage system PCS transmission power upper and lower limits; A data acquisition module is used to obtain the health status of each battery cluster in the energy storage system at a preset period; The power allocation module is used to optimize the grid-connected power allocation of each converter in the energy storage system based on the health status of each battery cluster in the energy storage system. It evaluates the health status of each battery cluster in the energy storage system based on the analytic hierarchy process and calculates the power allocation weight coefficient of each battery cluster. It then determines whether the transmission power of each PCS is within the set upper and lower power limits. If the power allocated to a PCS is less than the lower limit of the transmission power, the operation of the PCS is cancelled, and the number of PCSs participating in the system becomes n-1. The same method is used to obtain the weight coefficient of the grid-connected power borne by n-1 PCSs and the corresponding power size; further, if the power allocated to n-1 PCSs exceeds the upper limit of the transmission power, the transmission power size of the PCS is output according to the upper limit, and the remaining grid-connected power P ref -P batt_n The same method is used to obtain the weight coefficients and corresponding power sizes of the grid-connected power borne by n-2 PCSs. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is considered complete. The weight coefficient of the grid-connected power borne by each PCS is obtained by the following method: Obtain the health status SOH of each battery cluster involved in the energy storage system and record them as SOH1, SOH2, ..., SOH n , SOH n The health status of the nth battery cluster; The health status of each battery cluster is evaluated by combining the hierarchical analysis method. The larger the health status SOH of the battery cluster, the higher the score. Based on the score of each battery cluster, the target layer and indicator layer judgment matrix are constructed. The resulting matrix is ​​shown in the following table: Where Z represents the target layer, a 1n =1 / a n1 ; The judgment matrix is ​​normalized by column, and the weight coefficients w1, w2, ..., w of each PCS grid-connected power are obtained by arithmetic mean method. n ; When the power allocated by the PCS is not within the set range, the number of units participating in the operation and the corresponding transmission power are adjusted as follows: When the power allocated to a PCS is less than the lower limit of the transmission power, the operation of the PCS is cancelled, and the number of PCSs participating in the system becomes n-1. The weight coefficient of the grid-connected power borne by n-1 PCSs is obtained, and the power allocated to n-1 PCSs is calculated; further, if the power allocated to n-1 PCSs exceeds the upper limit of the transmission power, the transmission power of the PCS is output according to the upper limit, that is, the rated power is output, and the remaining grid-connected power P ref -P batt_n Similarly, the weight coefficients of the grid-connected power shared by n-2 PCSs are obtained using the above method, and the power allocated to n-2 PCSs is calculated. Similarly, when the transmission power of all participating PCSs is within the set upper and lower limits, the energy storage system power allocation is considered complete. Where, P batt_n is the power of the nth PCS, P ref is the grid-connected power instruction size of the energy storage system.

7. An electronic terminal, characterized in that: include: a memory having a computer program stored thereon; A processor is configured to load and execute the computer program to implement the method for balancing the health status of multiple battery clusters according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for balancing the health status of multiple battery clusters according to any one of claims 1 to 5 is implemented.

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