Energy storage system efficiency optimization calculation method and device

Abstract

The invention discloses an energy storage system efficiency optimization calculation method and device. The method comprises the steps of obtaining a current operation strategy and a historical charging and discharging data set of an energy storage system; determining a plurality of charging and discharging data matrixes according to the current operation strategy and the historical charging and discharging data set; and determining the efficiency of the energy storage system according to the plurality of charging and discharging data matrixes and the target charging and discharging data. According to the current operation strategy of the energy storage system and the historical charging and discharging data set, the plurality of charging and discharging data matrixes representing the influence of the current operation strategy on the plurality of efficiency indexes of the energy storage battery are determined, so that the efficiency of the energy storage system is determined according to the plurality of charging and discharging data matrixes and the current charging and discharging data. The method fully considers the influence of the working condition caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, can adapt to the change of the operation strategy, and improves the flexibility and accuracy of calculating the efficiency of the energy storage system.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage systems, and in particular to a method and device for calculating energy storage system efficiency optimization. Background Art

[0002] The efficiency of energy storage systems is an important indicator for evaluating the performance and economic benefits of energy storage systems. Since the working conditions of energy storage systems in different energy storage states are different, the efficiency of energy storage systems is also different. In the existing technology, calculations are usually performed based on the non-operating state of the energy storage system, without considering the working conditions of the actual operation strategy of the energy storage system, resulting in poor flexibility and low accuracy in calculating the efficiency of the energy storage system. Therefore, how to improve the flexibility and accuracy of calculating the efficiency of energy storage systems has become a technical problem that needs to be further solved. Summary of the invention

[0003] The present application proposes a method and device for optimizing the calculation of energy storage system efficiency, so as to solve the problems of poor flexibility and low accuracy in calculating the efficiency of energy storage systems, and to improve the flexibility and accuracy of calculating the efficiency of energy storage systems.

[0004] In a first aspect, an embodiment of the present application provides an energy storage system efficiency optimization calculation method, which is applied to a server of an energy storage system, wherein the energy storage system includes the server and an energy storage battery, and the method includes:

[0005] Acquire a current operation strategy and a historical charge and discharge data set of the energy storage system, wherein the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals;

[0006] Determining a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, wherein the plurality of charge and discharge data matrices are used to characterize the influence of the current operation strategy on a plurality of efficiency indicators of the energy storage battery;

[0007] The efficiency of the energy storage system is determined according to the multiple charge and discharge data matrices and the target charge and discharge data, wherein the target charge and discharge data is used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0008] In a second aspect, an embodiment of the present application provides an energy storage system efficiency optimization calculation device, which is applied to a server of an energy storage system, wherein the energy storage system includes the server and an energy storage battery, and the device includes:

[0009] A first receiving unit is used to obtain a current operation strategy and a historical charge and discharge data set of the energy storage system, wherein the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals;

[0010] The first processing unit is used to determine a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, wherein the plurality of charge and discharge data matrices are used to characterize the influence of the current operation strategy on a plurality of efficiency indicators of the energy storage battery; and determine the efficiency of the energy storage system according to the plurality of charge and discharge data matrices and target charge and discharge data, wherein the target charge and discharge data are used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0011] In a third aspect, an embodiment of the present application provides a server, comprising a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the method described in any one of the first aspects.

[0012] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program / instruction stored thereon, wherein the computer program / instruction, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0013] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements part or all of the steps of the method described in any one of the first aspects of the embodiments of the present application.

[0014] It can be seen that in this application, the server obtains the current operating strategy and historical charge and discharge data set of the energy storage system, the current operating strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; multiple charge and discharge data matrices are determined according to the current operating strategy and the historical charge and discharge data set, and the multiple charge and discharge data matrices are used to characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery; the efficiency of the energy storage system is determined according to multiple charge and discharge data matrices and target charge and discharge data, and the target charge and discharge data are used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval. Since multiple charge and discharge data matrices that characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery are determined according to the current operating strategy and the historical charge and discharge data set of the energy storage system, the efficiency of the energy storage system is determined according to multiple charge and discharge data matrices and the current charge and discharge data. Compared with the prior art, it not only fully considers the impact of the working conditions caused by the actual operating strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to changes in the operating strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 is a structural schematic diagram of an energy storage system provided in an embodiment of the present application;

[0017] Figure 2 It is a structural diagram of a server in an energy storage system provided in an embodiment of the present application;

[0018] Figure 3 It is a flow chart of a method for optimizing the efficiency of an energy storage system provided in an embodiment of the present application;

[0019] Figure 4 It is a flowchart of another energy storage system efficiency optimization calculation method provided in an embodiment of the present application;

[0020] Figure 5 It is a block diagram of the functional units of an energy storage system efficiency optimization calculation device provided in an embodiment of the present application;

[0021] Figure 6 It is a block diagram of the functional units of another energy storage system efficiency optimization calculation device provided in an embodiment of the present application;

[0022] Figure 7 It is a structural block diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0024] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0025] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0026] In the embodiments of the present application, "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist at the same time; B exists alone. Among them, A and B can be singular or plural.

[0027] In the embodiment of the present application, the symbol " / " can indicate that the objects associated with each other are in an "or" relationship. In addition, the symbol " / " can also indicate a division sign, that is, performing a division operation. For example, A / B can indicate A divided by B.

[0028] In the embodiments of the present application, "at least one item" or similar expressions refer to any combination of these items, including any combination of single items or plural items, and refer to one or more, and multiple refers to two or more. For example, at least one item of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0029] In the embodiments of the present application, "equal to" can be used in conjunction with greater than, and is applicable to the technical solution adopted when greater than, and can also be used in conjunction with less than, and is applicable to the technical solution adopted when less than. When equal to is used in conjunction with greater than, it is not used in conjunction with less than; when equal to is used in conjunction with less than, it is not used in conjunction with greater than.

[0030] In order to better understand the solutions of the embodiments of the present application, the terminal devices, related concepts and backgrounds that may be involved in the embodiments of the present application are first introduced below.

[0031] The efficiency of energy storage systems is an important indicator for evaluating the performance and economic benefits of energy storage systems. Since the working conditions of energy storage systems in different energy storage states are different, the efficiency of energy storage systems is also different. In the existing technology, calculations are usually performed based on the non-operating state of the energy storage system, without considering the working conditions of the actual operation strategy of the energy storage system, resulting in poor flexibility and low accuracy in calculating the efficiency of the energy storage system. Therefore, how to improve the flexibility and accuracy of calculating the efficiency of energy storage systems has become a technical problem that needs to be further solved.

[0032] To solve the above problems, an embodiment of the present application provides a method and device for calculating the efficiency optimization of an energy storage system. The method determines multiple charge and discharge data matrices that characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery according to the current operating strategy of the energy storage system and historical charge and discharge data sets, thereby determining the efficiency of the energy storage system according to the multiple charge and discharge data matrices and the current charge and discharge data. Compared with the prior art, the method not only fully considers the impact of the operating conditions caused by the actual operating strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to changes in the operating strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0033] See also Figure 1 , Figure 1 Schematic diagram of the structure of an energy storage system provided in an embodiment of the present application. Figure 1As shown, the energy storage system 100 includes an energy storage battery 110, the server 120 and a terminal device 130. The energy storage battery 110 is communicatively connected to the server 120, and the server 120 is communicatively connected to the terminal device 130. The energy storage battery 110 can be an energy storage battery group, or an energy storage battery group group composed of multiple energy storage battery groups. The server 120 can be a server, or a server group composed of multiple servers. The terminal device 130 can be a mobile terminal, a computer, a tablet computer, etc.

[0034] In daily use of the energy storage system 100, the server 120 obtains the current operating strategy and historical charge and discharge data sets of the energy storage system, where the current operating strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data sets are used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; multiple charge and discharge data matrices are determined based on the current operating strategy and the historical charge and discharge data sets, and the multiple charge and discharge data matrices are used to characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery; the energy storage system efficiency is determined based on the multiple charge and discharge data matrices and the target charge and discharge data, and the target charge and discharge data are used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0035] See also Figure 2 , Figure 2 Schematic diagram of the structure of a server in an energy storage system provided in an embodiment of the present application. Figure 2 As shown, the server 120 includes a processor 210 and a memory 220, and the processor 210 is communicatively connected to the memory 220. Among them, one or more programs are stored in the memory 220, and the one or more programs are configured to be executed by the processor 210. The function of the one or more programs is to obtain the current operation strategy and historical charge and discharge data set of the energy storage system, the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; determine multiple charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, and the multiple charge and discharge data matrices are used to characterize the impact of the current operation strategy on multiple efficiency indicators of the energy storage battery; determine the efficiency of the energy storage system according to the multiple charge and discharge data matrices and the target charge and discharge data, and the target charge and discharge data is used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0036] A method for calculating energy storage system efficiency optimization provided by an embodiment of the present application is described below.

[0037] See also Figure 3 , Figure 3 is a flow chart of a method for calculating energy storage system efficiency optimization provided by an embodiment of the present application, which is applied to Figure 1The server 120 in the energy storage system 100 shown in the figure comprises an energy storage battery 110, the server 120 and a terminal device 130. The energy storage battery 110 is in communication connection with the server 120, and the server 120 is in communication connection with the terminal device 130. The energy storage battery 110 may be an energy storage battery pack, or an energy storage battery pack group composed of multiple energy storage battery packs. The server 120 may be a server, or a server group composed of multiple servers. The terminal device 130 may be a mobile terminal, a computer, a tablet computer, etc. Figure 3 As shown, the method comprises the following steps:

[0038] Step S301, obtaining the current operation strategy and historical charge and discharge data set of the energy storage system.

[0039] The current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals.

[0040] The current operation strategy may be, for example, a constant current charge and discharge control strategy, a constant voltage charge and discharge control strategy, a staged charge and discharge control strategy, etc., which are configured by relevant staff according to the actual state and usage of the energy storage system.

[0041] The constant current charge and discharge control strategy is to keep the charging current constant during charging and the discharging current constant during discharging. The constant current charge and discharge control strategy is simple to control and easy to implement, but it does not take into account the change of the internal resistance and voltage fluctuation of the energy storage battery, so it may be overcharged or over-discharged when the battery ages or the temperature changes.

[0042] The constant voltage charge and discharge control strategy refers to keeping the voltage at both ends of the energy storage battery constant during charging and keeping the voltage at both ends of the energy storage battery constant during discharging. The constant voltage charge and discharge control strategy can prevent the energy storage battery from overcharging and protect the energy storage battery, but it is difficult to achieve constant voltage charge and discharge due to factors such as the internal resistance of the energy storage battery and load changes.

[0043] The staged charge and discharge control strategy refers to dividing the charging and / or discharging process into multiple stages, performing constant current charging and discharging in some stages, and constant voltage charging and discharging in some stages. The staged charge and discharge control strategy can avoid overcharging and discharging and protect the energy storage battery, but the control is complex and has high performance requirements for the energy storage battery.

[0044] Among them, the historical charge and discharge data set can be obtained through the energy storage system edge controller or cloud platform.

[0045] The number of the multiple historical charge and discharge intervals is n, where n≥100, and the historical charge and discharge data set is the charge and discharge data of the energy storage battery in the latest 1st to nth historical charge and discharge intervals.

[0046] Step S302: determining a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set.

[0047] The multiple charge and discharge data matrices are used to characterize the impact of the current operation strategy on multiple efficiency indicators of the energy storage battery.

[0048] The multiple efficiency indicators may specifically include battery efficiency, power conversion system efficiency, power line efficiency and transformer efficiency.

[0049] In a possible embodiment, determining a plurality of charge and discharge data matrices according to the current operating strategy and the historical charge and discharge data set includes: determining a plurality of influencing factors according to the current operating strategy, the plurality of influencing factors corresponding one-to-one to the plurality of efficiency indicators; and determining the plurality of charge and discharge data matrices according to the plurality of influencing factors and the historical charge and discharge data set.

[0050] Each of the multiple influencing factors has a major impact on the corresponding efficiency index.

[0051] Among them, determining multiple influencing factors according to the current operating strategy may specifically be: determining the degree of influence of each of the multiple strategy settings in the current operating strategy on each of the multiple efficiency indicators, and obtaining multiple groups of influence degrees, wherein the multiple groups of influence degrees correspond one-to-one to the multiple strategy settings; and determining the multiple influencing factors according to the multiple groups of influence degrees.

[0052] Among them, the determining of the influence degree of each of the multiple strategy settings in the current operating strategy on each of the multiple efficiency indicators to obtain multiple groups of influence degrees can specifically be: determining the multiple groups of influence degrees through a principal component analysis algorithm or a grey correlation analysis algorithm.

[0053] The determining of the multiple impact factors according to the multiple groups of impact degrees may specifically be: determining the policy setting corresponding to the impact degree greater than the corresponding preset threshold in each group of impact degrees as the impact factor to obtain the multiple impact factors.

[0054] The multiple influencing factors may specifically include charge and discharge depth, system standby time, system charge and discharge times and charge and discharge power.

[0055] It can be seen that in this example, multiple influencing factors are determined according to the current operating strategy, and then multiple charging and discharging data matrices are determined according to the multiple influencing factors and historical charging and discharging data sets, so that the efficiency of the energy storage system is determined according to the multiple charging and discharging data matrices and the current charging and discharging data. Compared with the existing technology, it not only fully considers the impact of the working conditions caused by the actual operating strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to changes in the operating strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0056] In a possible embodiment, determining the multiple charge and discharge data matrices according to the multiple influencing factors and the historical charge and discharge data sets includes: determining multiple historical operation data sets according to the multiple influencing factors and the historical charge and discharge data sets; determining multiple historical efficiency indicator sets according to the multiple efficiency indicators and the historical charge and discharge data sets; determining the multiple charge and discharge data matrices according to the historical operation data sets and the historical efficiency indicator sets.

[0057] The charging and discharging data include operation data and efficiency data.

[0058] Among them, the multiple historical operation data sets correspond to the multiple influencing factors one by one, and each of the multiple historical operation data sets includes the charge and discharge data corresponding to the corresponding influencing factor in the historical charge and discharge data set. For example: the operation data includes charge and discharge depth data, and the multiple historical operation data sets include a charge and discharge depth data set, the influencing factor corresponding to the charge and discharge depth data set is the charge and discharge depth, and the data in the charge and discharge depth data set is the charge and discharge depth data of the energy storage battery in the multiple historical charge and discharge intervals.

[0059] Among them, the multiple historical efficiency indicator sets correspond one-to-one to the multiple efficiency indicators, and each historical efficiency indicator set in the multiple historical efficiency indicator sets includes the charging and discharging data corresponding to the corresponding efficiency indicator in the historical charging and discharging data set. For example: the efficiency data includes battery efficiency data. The multiple historical efficiency indicator sets include a battery efficiency set, the efficiency indicator corresponding to the battery efficiency set is battery efficiency, and the data in the battery efficiency set is the battery efficiency data of the energy storage battery in the multiple historical charging and discharging intervals.

[0060] It can be seen that in this example, multiple historical operation data sets are determined based on multiple influencing factors and historical charge and discharge data sets, multiple historical efficiency indicator sets are determined based on multiple efficiency indicators and historical charge and discharge data sets, and then multiple charge and discharge data matrices are determined based on the historical operation data sets and the historical efficiency indicator sets. Thus, the efficiency of the energy storage system is determined based on the multiple charge and discharge data matrices and the current charge and discharge data. Compared with the prior art, it not only fully considers the impact of the operating conditions caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, but can also adapt to changes in the operation strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0061] In a possible embodiment, determining the multiple charge and discharge data matrices based on the historical operation data set and the historical efficiency index set includes: mapping the multiple historical operation data sets to the multiple historical efficiency index sets to obtain multiple charge and discharge mapping functions; and determining the multiple charge and discharge data matrices based on the multiple charge and discharge mapping functions.

[0062] Among them, mapping the multiple historical operation data sets to the multiple historical efficiency index sets to obtain multiple charge and discharge mapping functions can specifically be: establishing a functional relationship between the multiple historical operation data sets and the multiple historical efficiency index sets based on linear mapping or nonlinear mapping to obtain the multiple charge and discharge mapping functions.

[0063] The determining of the plurality of charge-discharge data matrices according to the plurality of charge-discharge mapping functions may specifically be: converting the plurality of charge-discharge mapping functions into a matrix form to obtain the plurality of charge-discharge data matrices.

[0064] It can be seen that in this example, multiple historical operating data sets are mapped to the multiple historical efficiency indicator sets to obtain multiple charge and discharge mapping functions, and then multiple charge and discharge data matrices are determined based on the multiple charge and discharge mapping functions, so that the efficiency of the energy storage system is determined based on the multiple charge and discharge data matrices and the current charge and discharge data. Compared with the existing technology, it not only fully considers the impact of the working conditions caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to changes in the operation strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0065] In a possible embodiment, the multiple efficiency indicator sets include a battery efficiency set, a power conversion system efficiency set, a power line efficiency set and a transformer efficiency set; the multiple historical operation data sets include a charge and discharge depth data set, a system standby time data set, a charge and discharge frequency data set and a charge and discharge power data set; the multiple charge and discharge mapping functions include a first mapping function, a second mapping function, a third mapping function and a fourth mapping function; and mapping the multiple historical operation data sets to the multiple historical efficiency indicator sets to obtain multiple charge and discharge mapping functions includes: mapping the charge and discharge depth data set to the battery efficiency set to obtain the first mapping function; mapping the system standby time data set to the power conversion system efficiency set to obtain the second mapping function; mapping the charge and discharge frequency data set to the power line efficiency set to obtain the third mapping function; and mapping the charge and discharge power data set to the transformer efficiency set to obtain the fourth mapping function.

[0066] Among them, the charge and discharge depth data set is {X1}, the system standby time data set is {X2}, the charge and discharge number data set is {X3}, the charge and discharge power data set is {X4}, the battery efficiency set is {Φ1}, the power conversion system efficiency set is {Φ2}, the power line efficiency set is {Φ3}, and the transformer efficiency set is {Φ4}. The first mapping function obtained is {a}=f({X1},{Φ1}), the second mapping function is {b}=f({X2},{Φ2}), the third mapping function is {c}=f({X3},{Φ3}), and the fourth mapping function is {d}=f({X4},{Φ4}).

[0067] It can be seen that in this example, the charge and discharge depth data set, the system standby time data set, the charge and discharge number data set, and the charge and discharge power data set are respectively mapped to the battery efficiency set, the power conversion system efficiency set, the power line efficiency set, and the transformer efficiency set to obtain the first mapping function, the second mapping function, the third mapping function, and the fourth mapping function, thereby obtaining multiple charge and discharge data matrices, so as to determine the efficiency of the energy storage system according to the multiple charge and discharge data matrices and the current charge and discharge data. Compared with the prior art, it not only fully considers the impact of the working conditions caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to the changes in the operation strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0068] Step S303: determining the efficiency of the energy storage system according to the plurality of charge and discharge data matrices and the target charge and discharge data.

[0069] The target charge and discharge data is used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0070] Among them, the target charging and discharging data can be obtained through the edge controller or cloud platform of the energy storage system.

[0071] In a possible embodiment, determining the efficiency of the energy storage system according to the multiple charge and discharge data matrices and the target charge and discharge data includes: determining multiple parameter correction coefficients according to the multiple influencing factors and the multiple charge and discharge data matrices; determining an energy storage system efficiency calculation model according to the multiple parameter correction coefficients and the multiple charge and discharge data matrices; and determining the energy storage system efficiency according to the target charge and discharge data and the energy storage system efficiency calculation model.

[0072] The plurality of correction coefficients correspond one-to-one to the plurality of charge and discharge data matrices.

[0073] Among them, the multiple correction coefficients include a first coefficient, a second coefficient, a third coefficient and a fourth coefficient, the first coefficient corresponds to the charge and discharge data matrix determined according to the first mapping function, the second coefficient corresponds to the charge and discharge data matrix determined according to the second mapping function, the third coefficient corresponds to the charge and discharge data matrix determined according to the third mapping function, and the fourth coefficient corresponds to the charge and discharge data matrix determined according to the fourth mapping function.

[0074] Among them, determining the energy storage system efficiency calculation model according to the multiple parameter correction coefficients and the multiple charge and discharge data matrices may specifically be: determining an initial energy storage system efficiency calculation model according to the multiple charge and discharge data matrices; and correcting the initial energy storage system efficiency calculation model according to the multiple parameter correction coefficients to obtain the energy storage system efficiency calculation model.

[0075] The initial energy storage system efficiency calculation model may be, for example: Φ=Φ1×Φ2×Φ3×Φ4.

[0076] The determining of the energy storage system efficiency according to the target charge and discharge data and the energy storage system efficiency calculation model may specifically be: inputting the target charge and discharge data into the energy storage system efficiency calculation model to obtain the energy storage system efficiency.

[0077] It can be seen that in this example, multiple parameter correction coefficients are determined according to multiple influencing factors and multiple charging and discharging data matrices, and then the energy storage system efficiency calculation model is determined according to the multiple parameter correction coefficients and multiple charging and discharging data matrices, so as to determine the efficiency of the energy storage system according to the current charging and discharging data and the energy storage system efficiency calculation model. Compared with the existing technology, it not only fully considers the impact of the operating conditions caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, but also considers the cross-influence between the operating conditions, can adapt to changes in the operation strategy, and improves the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0078] In a possible embodiment, determining multiple parameter correction coefficients according to the multiple influencing factors and the multiple charge and discharge data matrices includes: determining at least one target charge and discharge data matrix corresponding to each of the multiple influencing factors, the at least one target charge and discharge data matrix being a charge and discharge data matrix among the multiple charge and discharge data matrices except for the charge and discharge data matrix corresponding to the corresponding influencing factor; determining the parameter correction coefficient corresponding to each influencing factor according to the at least one target charge and discharge data matrix corresponding to each influencing factor, to obtain the multiple parameter correction coefficients.

[0079] The plurality of charge-discharge data matrices include a first charge-discharge data matrix (a1, a2, ..., a n ), the second charge-discharge data matrix (b1, b2, ..., b n ), the third charge-discharge data matrix (c1, c2, ..., c n ), the fourth charge-discharge data matrix (d1, d2, ..., d n ).

[0080] Among them, see Figure 4 , Figure 4 FIG. 1 is a flow chart of another method for calculating the efficiency optimization of an energy storage system provided in an embodiment of the present application. Figure 4 As shown, the method includes the following steps:

[0081] Step S401, obtaining the current operation strategy and historical charge and discharge data set of the energy storage system.

[0082] Step S402: determining a plurality of influencing factors according to the current operation strategy.

[0083] Step S403: determining a plurality of historical operation data sets according to the plurality of influencing factors and the historical charge and discharge data sets.

[0084] Step S404: determining a plurality of historical efficiency indicator sets according to the plurality of efficiency indicators and the historical charge and discharge data set.

[0085] Step S405 : Mapping the multiple historical operation data sets to the multiple historical efficiency indicator sets to obtain multiple charge-discharge mapping functions.

[0086] Step S406: determining the plurality of charge-discharge data matrices according to the plurality of charge-discharge mapping functions.

[0087] Step S407: determining at least one target charge-discharge data matrix corresponding to each of the multiple influencing factors.

[0088] Step S408: determining a parameter correction coefficient corresponding to each influencing factor according to the at least one target charge-discharge data matrix corresponding to each influencing factor, to obtain the plurality of parameter correction coefficients.

[0089] Step S409: determining an energy storage system efficiency calculation model according to the multiple parameter correction coefficients and the multiple charge and discharge data matrices.

[0090] Step S410: determining the efficiency of the energy storage system according to the target charge and discharge data and the energy storage system efficiency calculation model.

[0091] Among them, the at least one target charge and discharge data matrix corresponding to each of the multiple influencing factors is determined, for example, can be: the at least one target charge and discharge data matrix corresponding to the charge and discharge depth includes the second charge and discharge data matrix, the third charge and discharge data matrix and the fourth charge and discharge data matrix; the at least one target charge and discharge data matrix corresponding to the system standby time includes the first charge and discharge data matrix, the third charge and discharge data matrix and the fourth charge and discharge data matrix; the at least one target charge and discharge data matrix corresponding to the system charge and discharge times includes the first charge and discharge data matrix, the second charge and discharge data matrix and the fourth charge and discharge data matrix; the at least one target charge and discharge data matrix corresponding to the charge and discharge power includes the first charge and discharge data matrix, the second charge and discharge data matrix and the third charge and discharge data matrix.

[0092] Wherein, the parameter correction coefficient corresponding to each influencing factor is determined according to the at least one target charge and discharge data matrix corresponding to each influencing factor to obtain the multiple parameter correction coefficients, for example, it can be: for the charge and discharge depth of the influencing factor, f(∑ ij biaj) is the correction coefficient of the influencing factor system standby time on the influencing factor charge and discharge depth, f(∑ ij ciaj) is the correction coefficient of the charge and discharge times of the influencing factor to the charge and discharge depth of the influencing factor, f(∑ ij diaj) is the correction coefficient of the influencing factor charging and discharging power to the influencing factor charging and discharging depth, then the correction coefficient corresponding to the influencing factor charging and discharging depth is f(∑ ij aibj)*f(∑ ij aicj)*f(∑ ij aidj).

[0093] It can be seen that in this example, at least one target charge and discharge data matrix corresponding to each influencing factor is determined, and then the parameter correction coefficient corresponding to each influencing factor is determined according to the at least one target charge and discharge data matrix corresponding to each influencing factor, and then the energy storage system efficiency calculation model is determined according to multiple parameter correction coefficients and multiple charge and discharge data matrices, so as to determine the efficiency of the energy storage system according to the current charge and discharge data and the energy storage system efficiency calculation model. Compared with the prior art, it not only fully considers the impact of the operating conditions caused by the actual operation strategy of the energy storage system on the efficiency of the energy storage system, but also considers the cross-influence between the operating conditions, can adapt to changes in the operation strategy, and improves the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0094] It can be seen that in this application, the server obtains the current operating strategy and historical charge and discharge data set of the energy storage system, the current operating strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; multiple charge and discharge data matrices are determined according to the current operating strategy and the historical charge and discharge data set, and the multiple charge and discharge data matrices are used to characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery; the efficiency of the energy storage system is determined according to multiple charge and discharge data matrices and target charge and discharge data, and the target charge and discharge data are used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval. Since multiple charge and discharge data matrices that characterize the impact of the current operating strategy on multiple efficiency indicators of the energy storage battery are determined according to the current operating strategy and the historical charge and discharge data set of the energy storage system, the efficiency of the energy storage system is determined according to multiple charge and discharge data matrices and the current charge and discharge data. Compared with the prior art, it not only fully considers the impact of the working conditions caused by the actual operating strategy of the energy storage system on the efficiency of the energy storage system, but also can adapt to changes in the operating strategy, thereby improving the flexibility and accuracy of calculating the efficiency of the energy storage system.

[0095] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the controller includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0096] In accordance with the above-mentioned embodiments, please refer to Figure 5 , Figure 5is a functional unit block diagram of an energy storage system efficiency optimization calculation device provided by an embodiment of the present application, such as Figure 5 As shown, the energy storage system efficiency optimization calculation device 500 includes: a first receiving unit 501, used to obtain the current operation strategy and historical charge and discharge data set of the energy storage system, the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; a first processing unit 502, used to determine multiple charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, and the multiple charge and discharge data matrices are used to characterize the impact of the current operation strategy on multiple efficiency indicators of the energy storage battery; determine the energy storage system efficiency according to the multiple charge and discharge data matrices and target charge and discharge data, and the target charge and discharge data is used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

[0097] In a possible embodiment, in terms of determining a plurality of charge and discharge data matrices according to the current operating strategy and the historical charge and discharge data set, the first processing unit 502 is specifically used to: determine a plurality of influencing factors according to the current operating strategy, the plurality of influencing factors corresponding one-to-one to the plurality of efficiency indicators; and determine the plurality of charge and discharge data matrices according to the plurality of influencing factors and the historical charge and discharge data set.

[0098] In a possible embodiment, in terms of determining the multiple charge and discharge data matrices based on the multiple influencing factors and the historical charge and discharge data sets, the first processing unit 502 is specifically used to: determine multiple historical operation data sets based on the multiple influencing factors and the historical charge and discharge data sets; determine multiple historical efficiency indicator sets based on the multiple efficiency indicators and the historical charge and discharge data sets; determine the multiple charge and discharge data matrices based on the historical operation data sets and the historical efficiency indicator sets.

[0099] In a possible embodiment, in terms of determining the multiple charge and discharge data matrices based on the historical operation data set and the historical efficiency index set, the first processing unit 502 is specifically used to: map the multiple historical operation data sets to the multiple historical efficiency index sets to obtain multiple charge and discharge mapping functions; and determine the multiple charge and discharge data matrices based on the multiple charge and discharge mapping functions.

[0100] In a possible embodiment, the multiple efficiency indicator sets include a battery efficiency set, a power conversion system efficiency set, a power line efficiency set and a transformer efficiency set; the multiple historical operation data sets include a charge and discharge depth data set, a system standby time data set, a charge and discharge frequency data set and a charge and discharge power data set; the multiple charge and discharge mapping functions include a first mapping function, a second mapping function, a third mapping function and a fourth mapping function; in terms of mapping the multiple historical operation data sets to the multiple historical efficiency indicator sets to obtain multiple charge and discharge mapping functions, the first processing unit 502 is specifically used to: map the charge and discharge depth data set to the battery efficiency set to obtain the first mapping function; map the system standby time data set to the power conversion system efficiency set to obtain the second mapping function; map the charge and discharge frequency data set to the power line efficiency set to obtain the third mapping function; map the charge and discharge power data set to the transformer efficiency set to obtain the fourth mapping function.

[0101] In a possible embodiment, in terms of determining the efficiency of the energy storage system according to the multiple charge and discharge data matrices and the target charge and discharge data, the first processing unit 502 is specifically used to: determine multiple parameter correction coefficients according to the multiple influencing factors and the multiple charge and discharge data matrices; determine an energy storage system efficiency calculation model according to the multiple parameter correction coefficients and the multiple charge and discharge data matrices; determine the energy storage system efficiency according to the target charge and discharge data and the energy storage system efficiency calculation model.

[0102] In a possible embodiment, in terms of determining multiple parameter correction coefficients based on the multiple influencing factors and the multiple charge and discharge data matrices, the first processing unit 502 is specifically used to: determine at least one target charge and discharge data matrix corresponding to each of the multiple influencing factors, the at least one target charge and discharge data matrix being a charge and discharge data matrix other than the charge and discharge data matrix corresponding to the corresponding influencing factor in the multiple charge and discharge data matrices; determine the parameter correction coefficient corresponding to each influencing factor based on the at least one target charge and discharge data matrix corresponding to each influencing factor, to obtain the multiple parameter correction coefficients.

[0103] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part and will not be repeated here.

[0104] In the case of an integrated unit, such as Figure 6 As shown, Figure 6 This is a functional unit block diagram of another energy storage system efficiency optimization calculation device provided by an embodiment of the present application. Figure 6In the embodiment, the energy storage system efficiency optimization calculation device 500 includes: a processing module 612 and a communication module 611. The processing module 612 is used to control and manage the actions of the energy storage system efficiency optimization calculation device 500, for example, to execute the steps of the first receiving unit 501 and the first processing unit 502, and / or other processes for executing the technology described in this article. The communication module 611 is used to support the interaction between the energy storage system efficiency optimization calculation device 500 and other devices. Figure 6 As shown, the energy storage system efficiency optimization computing device 500 may further include a storage module 613 , and the storage module 613 is used to store program codes and data of the energy storage system efficiency optimization computing device 500 .

[0105] Among them, the processing module 612 can be a processor or a controller, for example, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements a computing function, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication module 611 can be a transceiver, an RF circuit or a communication interface, and the like. The storage module 613 can be a memory.

[0106] Among them, all relevant contents of each scenario involved in the above method embodiment can be referred to the functional description of the corresponding functional module, and will not be repeated here. The above energy storage system efficiency optimization calculation device 500 can execute the above Figure 3 The energy storage system efficiency optimization calculation method shown.

[0107] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0108] Figure 7 is a structural block diagram of a server provided in an embodiment of the present application. Figure 7 As shown, the server 120 may include one or more of the following components: a processor 210, and a memory 220 coupled to the processor 210, wherein the memory 220 may store one or more computer programs 221, and the one or more computer programs 221 may be configured to implement the methods described in the above embodiments when executed by one or more processors 210.

[0109] The processor 210 may include one or more processing cores. The processor 210 uses various interfaces and lines to connect the various parts of the entire server 120, and executes various functions and processes data of the server 120 by running or executing instructions, programs, code sets or instruction sets stored in the memory 220, and calling data stored in the memory 220. Optionally, the processor 210 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 210 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 210, but may be implemented separately through a communication chip.

[0110] The memory 220 may include a random access memory (RAM) or a read-only memory (ROM). The memory 220 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 220 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. The data storage area may also store data created by the server 120 during use, etc.

[0111] It is understandable that the server 120 may include more or fewer structural elements than those in the above structural block diagram, which is not limited here. The present application embodiment provides a computer-readable storage medium on which a computer program / instruction is stored, and when the computer program / instruction is executed by a processor, the steps of the method described in any possible embodiment are implemented.

[0112] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0113] In the several embodiments provided in the present application, it should be understood that the disclosed methods, devices and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the unit is only a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0114] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0115] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be physically included separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0116] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a volatile memory or a non-volatile memory. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM) and direct RAM bus random access memory (DR RAM), among other media that can store program code.

[0117] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including the combination of the above-mentioned different functions and implementation steps, including software and hardware implementation methods, all of which are within the scope of protection of the present invention.

Claims

1. A method for calculating energy storage system efficiency optimization, characterized in that: A server applied to an energy storage system, wherein the energy storage system comprises the server and an energy storage battery, and the method comprises: Acquire a current operation strategy and a historical charge and discharge data set of the energy storage system, wherein the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; Determining a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, wherein the plurality of charge and discharge data matrices are used to characterize the influence of the current operation strategy on a plurality of efficiency indicators of the energy storage battery; The efficiency of the energy storage system is determined according to the multiple charge and discharge data matrices and the target charge and discharge data, wherein the target charge and discharge data is used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

2. The method according to claim 1, characterized in that The determining of a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set includes: Determine a plurality of influencing factors according to the current operation strategy, wherein the plurality of influencing factors correspond one to one to the plurality of efficiency indicators; The plurality of charge and discharge data matrices are determined according to the plurality of influencing factors and the historical charge and discharge data set.

3. The method according to claim 2, characterized in that The determining the plurality of charge-discharge data matrices according to the plurality of influencing factors and the historical charge-discharge data set comprises: Determine a plurality of historical operation data sets according to the plurality of influencing factors and the historical charge and discharge data sets; Determine a plurality of historical efficiency index sets according to the plurality of efficiency indexes and the historical charge and discharge data set; The plurality of charge and discharge data matrices are determined according to the historical operation data set and the historical efficiency index set.

4. The method according to claim 3, characterized in that The determining the plurality of charge and discharge data matrices according to the historical operation data set and the historical efficiency index set comprises: Mapping the multiple historical operation data sets to the multiple historical efficiency indicator sets to obtain multiple charge-discharge mapping functions; The plurality of charge-discharge data matrices are determined according to the plurality of charge-discharge mapping functions.

5. The method according to claim 4, characterized in that The multiple efficiency indicator sets include a battery efficiency set, a power conversion system efficiency set, a power line efficiency set, and a transformer efficiency set; the multiple historical operation data sets include a charge and discharge depth data set, a system standby time data set, a charge and discharge number data set, and a charge and discharge power data set; the multiple charge and discharge mapping functions include a first mapping function, a second mapping function, a third mapping function, and a fourth mapping function; the multiple historical operation data sets are mapped to the multiple historical efficiency indicator sets to obtain multiple charge and discharge mapping functions, including: Mapping the charge and discharge depth data set to the battery efficiency set to obtain the first mapping function; Mapping the system standby time data set to the power conversion system efficiency set to obtain the second mapping function; Mapping the charge and discharge times data set to the power line efficiency set to obtain the third mapping function; The charging and discharging power data set is mapped to the transformer efficiency set to obtain the fourth mapping function.

6. The method according to claim 5, characterized in that The determining the efficiency of the energy storage system according to the plurality of charge and discharge data matrices and the target charge and discharge data comprises: Determine a plurality of parameter correction coefficients according to the plurality of influencing factors and the plurality of charge and discharge data matrices; Determine an energy storage system efficiency calculation model according to the multiple parameter correction coefficients and the multiple charge and discharge data matrices; The energy storage system efficiency is determined according to the target charge and discharge data and the energy storage system efficiency calculation model.

7. The method according to claim 6, characterized in that The determining of a plurality of parameter correction coefficients according to the plurality of influencing factors and the plurality of charge and discharge data matrices comprises: Determine at least one target charge-discharge data matrix corresponding to each of the multiple influencing factors, wherein the at least one target charge-discharge data matrix is ​​a charge-discharge data matrix other than a charge-discharge data matrix corresponding to a corresponding influencing factor among the multiple charge-discharge data matrices; The parameter correction coefficient corresponding to each influencing factor is determined according to the at least one target charge and discharge data matrix corresponding to each influencing factor to obtain the multiple parameter correction coefficients.

8. An energy storage system efficiency optimization calculation device, characterized in that: A server applied to an energy storage system, wherein the energy storage system comprises the server and an energy storage battery, and the device comprises: A first receiving unit is used to obtain a current operation strategy and a historical charge and discharge data set of the energy storage system, wherein the current operation strategy is used to characterize the charge and discharge control strategy currently adopted by the energy storage system, and the historical charge and discharge data set is used to characterize the charge and discharge data of the energy storage battery in multiple historical charge and discharge intervals; The first processing unit is used to determine a plurality of charge and discharge data matrices according to the current operation strategy and the historical charge and discharge data set, wherein the plurality of charge and discharge data matrices are used to characterize the influence of the current operation strategy on a plurality of efficiency indicators of the energy storage battery; and determine the efficiency of the energy storage system according to the plurality of charge and discharge data matrices and target charge and discharge data, wherein the target charge and discharge data are used to characterize the charge and discharge data of the energy storage battery in the current charge and discharge interval.

9. A server, characterized in that: The method comprises a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program / instruction is stored thereon, and when the computer program / instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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