A method, device, equipment and medium for evaluating the balance of energy storage system battery cells

Abstract

The present application discloses a method, device, equipment and medium for evaluating the cell balance of an energy storage system. The evaluation method includes: obtaining historical operation data of at least one energy storage system; generating a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data; predicting the improvable capacity of the energy storage system after cell balance within the operation day based on the voltage data of each cell in the energy storage system and the first and second relationship curves; and determining the cell balance priority levels of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system. Through the evaluation method of the present application, the improvable capacity and balance priority levels of the energy storage system can be quantitatively evaluated, thereby achieving the technical effects of assisting technical personnel to complete the operation and maintenance work of cell balance, reducing the equipment outage duration, improving the operation efficiency, and maximizing the available capacity of the energy storage system.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage system cell balancing, and particularly relates to a method, device, equipment and medium for evaluating energy storage system cell balancing. Background Art

[0002] Cell balancing refers to the process of using specific technical means to make the SOC (State of Charge) of all individual cells in a battery pack reach equilibrium. The efficiency of balancing is crucial for ensuring the stable operation of equipment, and thus has attracted much attention in the industry. As a key maintenance link of the energy storage system, cell balancing plays a decisive role in ensuring system performance and extending service life. Even for cells in the same production batch, there may be subtle differences in key parameters such as capacity, internal resistance, and self-discharge rate. These differences will gradually accumulate during the use of the battery pack, eventually leading to an imbalance in the working states of the cells. This imbalance not only reduces the overall efficiency of the energy storage system, but may also cause some cells to age or be damaged prematurely.

[0003] However, due to the relatively late start of the large-scale application of energy storage systems, most current energy storage systems have been in operation for a short time, and the cells are mostly in a healthy state. The imbalance problem has not been fully manifested, and the demand for evaluating energy storage system cell balancing has not been fully met. Existing balancing evaluation methods often lack in-depth analysis of the historical operation data of energy storage systems, resulting in the inability of maintenance personnel to quantitatively evaluate the increased capacity of the system after balancing when performing balancing, and thus unable to scientifically formulate the balancing order and plan arrangement. This makes the priority ranking of balancing operations inaccurate, affecting the overall performance and life of the energy storage system. Summary of the Invention

[0004] In view of the above problems, the present application is proposed to provide a method, device, equipment and medium for evaluating energy storage system cell balancing, so as to achieve the technical effects of quantitatively evaluating the increased capacity of the energy storage system, determining the balancing priorities of multiple energy storage systems, and then assisting technical personnel to complete the maintenance work of cell balancing, reducing the equipment outage time, improving the operation efficiency, and maximizing the available capacity of the energy storage system.

[0005] According to the first aspect of the present application, a method for evaluating energy storage system cell balancing is proposed, and the method includes:

[0006] Obtain historical operation data of at least one energy storage system;

[0007] Generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data;

[0008] Based on the voltage data of each battery cell in the energy storage system and based on the first relationship curve and the second relationship curve, the increased capacity of the energy storage system after cell balancing is predicted within the operating day;

[0009] According to the increased capacity and the cell distribution of the energy storage system, the cell balancing priorities of multiple energy storage systems are determined.

[0010] Optionally, the first relationship curve includes a mapping relationship curve between the charging voltage value and the SOC value of the energy storage system; the second relationship curve includes a mapping relationship curve between the discharging voltage value and the SOC value of the energy storage system.

[0011] Optionally, the historical operation data at least includes one of the following: the operation state, voltage value, and SOC value corresponding to the energy storage system at different sampling moments before the operation day;

[0012] The generating the first relationship curve in the charging state and the second relationship curve in the discharging state of the energy storage system according to the historical operation data includes:

[0013] Generating a multi-dimensional information matrix according to the historical operation data of at least one energy storage system;

[0014] Obtaining a charging information matrix in the charging state and a discharging information matrix in the discharging state respectively according to the multi-dimensional information matrix;

[0015] Fitting the charging information matrix and the discharging information matrix, and obtaining the first relationship curve and the second relationship curve respectively.

[0016] Optionally, the method further includes:

[0017] Responding to the preset operating conditions of the energy storage system within the operating day; wherein,

[0018] In the first operating condition, generating a first cell list according to the voltage data of each cell obtained in real time, and screening to obtain a first list of cells to be balanced whose actual voltage value at the instant of charging cut-off is higher than the preset voltage threshold;

[0019] In the second operating condition, generating a second cell list according to the voltage data of each cell obtained in real time, and screening to obtain a second list of cells to be balanced whose actual voltage value at the instant of discharging cut-off is lower than the preset voltage threshold.

[0020] Optionally, the predicting the increased capacity of the energy storage system after cell balancing within the operating day according to the voltage data of each cell of the energy storage system and based on the first relationship curve and the second relationship curve includes:

[0021] Under the first operating condition:

[0022] According to the first battery cell list, obtain the highest voltage value in each battery cell;

[0023] According to the first battery cell list and the first list of battery cells to be balanced, determine the first non-balanced battery cells, and obtain the highest voltage value of the first non-balanced battery cells;

[0024] Based on the first relationship curve, according to the highest voltage value in each battery cell and the highest voltage value of the first non-balanced battery cells, predict the improvable capacity of the energy storage system after battery cell balancing within the operating day;

[0025] Under the second operating condition:

[0026] According to the second battery cell list, obtain the lowest voltage value in each battery cell;

[0027] According to the second battery cell list and the second list of battery cells to be balanced, determine the second non-balanced battery cells, and obtain the lowest voltage value of the second non-balanced battery cells;

[0028] Based on the second relationship curve, according to the lowest voltage value in each battery cell and the lowest voltage value of the second non-balanced battery cells, predict the improvable capacity of the energy storage system after battery cell balancing within the operating day.

[0029] Optionally, the determining the cell balancing priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system includes:

[0030] Obtain the sum of the improvable capacities of each energy storage system according to the improvable capacity calculated at the moment of the most recent charging cut-off and the improvable capacity calculated at the moment of the most recent discharging cut-off;

[0031] According to the sum of the improvable capacities of each energy storage system and the number of battery packs corresponding to the battery cells to be balanced in the energy storage system, respectively obtain the balance score values of each energy storage system;

[0032] Sort the balance score values of multiple energy storage systems, and determine the cell balancing priorities of multiple energy storage systems.

[0033] Optionally, the method further includes:

[0034] Perform data preprocessing on the obtained historical operation data;

[0035] The data preprocessing includes at least one of the following operations: performing missing value processing, duplicate value processing, outlier processing, and filling point alignment processing on the historical operation data.

[0036] According to a second aspect of the present application, there is provided an energy storage system cell balance evaluation device, which includes:

[0037] An acquisition unit for acquiring historical operation data of at least one energy storage system;

[0038] A curve generation unit for generating a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data;

[0039] A capacity calculation unit for predicting the improvable capacity of the energy storage system after cell balance within an operating day based on the voltage data of each cell in the energy storage system and based on the first relationship curve and the second relationship curve;

[0040] A priority determination unit for determining the cell balance priorities of a plurality of the energy storage systems according to the improvable capacity and the cell distribution of the energy storage system.

[0041] According to a third aspect of the present application, there is provided an electronic device, which includes: a processor; and a memory arranged to store computer-executable instructions, and the executable instructions, when executed, cause the processor to execute the evaluation method according to any one of the above first aspects.

[0042] According to a fourth aspect of the present application, there is provided a computer-readable storage medium, which stores one or more programs, and when the one or more programs are executed by a processor, the evaluation method according to any one of the above first aspects is implemented.

[0043] As can be seen from the above, the above at least one technical solution adopted in the embodiments of the present application can achieve the following beneficial effects: A method, device, equipment and medium for evaluating the balance of energy storage system battery cells are provided. First, historical operation data of at least one energy storage system is obtained; secondly, according to the historical operation data, a first relationship curve in the charging state of the energy storage system and a second relationship curve in the discharging state are generated; thirdly, according to the voltage data of each battery cell in the energy storage system, and based on the first relationship curve and the second relationship curve, the improvable capacity of the energy storage system after battery cell balance is predicted within the operation day; finally, according to the improvable capacity and the battery cell distribution of the energy storage system, the battery cell balance priority of multiple energy storage systems is determined. Through the evaluation method of the embodiments of the present application, on the one hand, by using big data real-time calculation technology, without the need for the energy storage system equipment to be stationary, out of service, or opened, the screening of the balanced battery cell list and the quantitative evaluation of the improvable capacity of the energy storage system can be realized, providing an effective basis for the battery cell balance operation of the energy storage system; on the other hand, by using the historical operation data of the energy storage system, the mapping relationship between the voltage value - SOC value is dynamically updated, and the evaluation is carried out based on the latest mapping relationship to achieve a more accurate evaluation effect; on the third hand, the balance priority of multiple energy storage systems can be determined to assist relevant operators in battery cell balance, achieving the technical effect of reducing the equipment out-of-service duration and maximizing the available capacity of the energy storage system.

[0044] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present application. And throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0046] Figure 1 is a schematic flow chart of the method for evaluating the balance of energy storage system battery cells in an embodiment of the present application;

[0047] Figure 2 is a schematic diagram of the first relationship curve (mapping relationship curve of charging voltage value - SOC value) in the charging state in an embodiment of the present application;

[0048] Figure 3 is a schematic diagram of the second relationship curve (mapping relationship curve of discharging voltage value - SOC value) in the discharging state in an embodiment of the present application;

[0049] Figure 4 Schematic structural diagram of a cell equalization evaluation device for an energy storage system in an embodiment of the present application;

[0050] Figure 5 Schematic structural diagram of an electronic device in an embodiment of the present application. Detailed implementation manners

[0051] Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be fully conveyed to those skilled in the art.

[0052] In actual operation, cell equalization is divided into two strategies: passive equalization and active equalization. Whether passive equalization or active equalization is adopted, when performing large-scale or in-depth equalization adjustments, for safety considerations or to achieve the best equalization effect, it is usually necessary to suspend the operation of the energy storage system. Therefore, it has become the key to reducing the downtime to preferentially equalize the energy storage system with the greatest capacity improvement potential within the limited downtime.

[0053] Based on this, the technical concept of the present application is to utilize the advantages of the massive data of the energy storage cloud platform, form a comprehensive voltage-SOC curve of the energy storage system based on the second-level operation data of the cells, identify the list of cells to be equalized in the energy storage system, and quantify and evaluate the capacity that can be improved in the energy storage system after cell equalization based on the comprehensive voltage-SOC curve. Thus, according to the list of cells to be equalized and the capacity that can be improved, the equalization priority of each set of energy storage systems is calculated.

[0054] It should be noted that the embodiments of the present application are preferably applicable to the passive equalization scenario of cells, for example, the equalization operation is completed through devices such as intelligent equalization chargers. That is, the embodiments of the present application can predict the capacity that can be improved in the energy storage system after completing the corresponding cell equalization operation, and accordingly arrange relevant technicians to carry out the operation and maintenance work of cell equalization in the order of priority. Thus, within the limited downtime, the energy storage system with a greater capacity improvement potential can be preferentially equalized for cells, thereby improving the overall operation efficiency of the energy storage system.

[0055] The following will describe in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

[0056] In the embodiments of the present application, as Figure 1 shown, a flowchart of a method for evaluating cell equalization of an energy storage system is provided. The evaluation method of the embodiments of the present application at least includes the following steps S110 to step S140:

[0057] Step S110: Obtain the historical operation data of at least one energy storage system.

[0058] In the embodiments of the present application, the energy storage system refers to the smallest device combination that can independently achieve power storage, conversion, and release. The historical operation data refers to the operation data before the operation date of the energy storage system. Preferably, the historical operation data of the energy storage system in the most recent 30 days can be obtained, and the historical operation data includes, but is not limited to, the operation state, voltage value, SOC value, etc. of the energy storage system. Among them, the operation state includes charging, discharging, standby, etc., and the SOC value represents the remaining power of the energy storage system at the current moment, usually expressed as a percentage.

[0059] Step S120: Generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data.

[0060] In this embodiment, taking advantage of the massive data of the energy storage cloud platform, the operation states of the energy storage system are classified. For example, the energy storage system is divided into charging state, discharging state, standby state, etc., and a big data calculation method is adopted to form a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage based on the second-level operation data of the battery cells. For example, a comprehensive voltage-SOC curve of the energy storage system in different operation states is formed respectively.

[0061] Step S130: Based on the voltage data of each battery cell in the energy storage system and based on the first relationship curve and the second relationship curve, predict the improvable capacity of the energy storage system after the battery cells are balanced within the operation day.

[0062] After generating the first relationship curve and the second relationship curve, it is necessary to identify the voltage data of all battery cells in the energy storage system on the operation day and generate a list of battery cells to be balanced in the energy storage system, so that the improvable capacity of the energy storage system after the battery cells are balanced can be quantitatively evaluated within the operation day according to the relationship between the list of battery cells to be balanced and the first relationship curve and the second relationship curve respectively.

[0063] Step S140: Determine the cell balancing priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system.

[0064] The energy storage system can be a single set or multiple sets. When including a single energy storage system, the improvable capacity of the single energy storage system can be used as a reference index for the cell equalization operation and maintenance work, assisting relevant technical personnel to complete the operation and maintenance work of energy storage cell equalization; when including multiple energy storage systems, the equalization priority of multiple energy storage systems can be calculated by combining the list of cells to be equalized and the improvable capacity of each energy storage system. The higher the equalization priority, the more urgent the cell equalization requirement of the corresponding energy storage system. In this way, the operation and maintenance personnel can scientifically plan the priority order of cell equalization, thereby effectively reducing the equipment outage duration and maximizing the available capacity of the energy storage system. Of course, the embodiments of the present application do not limit the number of energy storage systems.

[0065] It can be seen that different from the prior art solutions that cannot quantitatively evaluate the available capacity of the energy storage system after cell equalization, through the energy storage system cell equalization evaluation method of the embodiments of the present application, on the one hand, using big data real-time calculation technology, without the need for the energy storage system equipment to be stationary, out of service, or opened, it is possible to screen the equalized cell list and quantitatively evaluate the improvable capacity of the energy storage system after equalization, providing an effective basis and guidance for the cell equalization operation of the energy storage system; on the other hand, using the historical operation data of the energy storage system, dynamically updating the mapping relationship between voltage and SOC, and performing evaluation based on the latest mapping relationship to achieve a more accurate evaluation effect; on the other hand, it is possible to determine the equalization priority of multiple energy storage systems, assisting relevant technical personnel in cell equalization operations, achieving the technical effects of reducing equipment outage duration, improving operation efficiency, and maximizing the available capacity of the energy storage system.

[0066] It should be understood that the energy storage system cell equalization evaluation method of the embodiments of the present application may include additional steps not shown and / or some shown steps may be omitted, and the scope of the present disclosure is not limited to this.

[0067] In some embodiments, the first relationship curve includes the mapping relationship curve between the charging voltage value and the SOC value of the energy storage system; the second relationship curve includes the mapping relationship curve between the discharging voltage value and the SOC value of the energy storage system.

[0068] In some preferred embodiments, the historical operation data at least includes one of the following: the operation state, voltage value, and SOC value corresponding to the energy storage system at different sampling moments before the operation date.

[0069] Preferably, the method further includes: performing data preprocessing on the obtained historical operation data; the data preprocessing at least includes one of the following operations: performing missing value processing, duplicate value processing, outlier processing, and filling point alignment processing on the historical operation data.

[0070] In one example, the format of each piece of data in the historical operation data includes the following form:

[0071] message=[pid,value,time];

[0072] Among them, message represents the information of a single piece of data; pid represents the point name, which can be used to represent the operating state (charging, discharging, standby), voltage, SOC, etc.; value represents the value corresponding to pid; time represents the sampling moment of this piece of data information.

[0073] For example, the processing of missing values in the historical operation data includes: when one of [pid, value, time] in the message data information is a null value, then discard this piece of message data information;

[0074] The processing of duplicate values in the historical operation data includes: when there are two or more pieces of message data information that are exactly the same, then only keep one of the message data information;

[0075] The processing of outlier values in the historical operation data includes: when one of [pid, value, time] in the message data information is abnormal, then discard this piece of message data;

[0076] The processing of filling points and aligning in the historical operation data includes: for a certain battery cell in the energy storage system, obtain all non-repeated time values with pid being the voltage value or SOC value in the message, and form a time series T = [time1, time2... time n , and according to each moment in the time series T, query the corresponding value of value when pid is the operating state, voltage, and SOC. If there is no data at this moment, then use the value of the previous data of the corresponding pid.

[0077] In some embodiments, generating the first relationship curve in the charging state and the second relationship curve in the discharging state of the energy storage system according to the historical operation data includes: generating a multi-dimensional information matrix according to the historical operation data of the at least one energy storage system; respectively obtaining a charging information matrix in the charging state and a discharging information matrix in the discharging state according to the multi-dimensional information matrix; fitting the charging information matrix and the discharging information matrix, and respectively obtaining the first relationship curve and the second relationship curve.

[0078] In one example, the multi-dimensional information matrix includes the following form:

[0079]

[0080] Among them, data represents the processed multi-dimensional information matrix, state represents the operating state of the energy storage system, and u represents the voltage value;

[0081] Fitting the charging information matrix and the discharging information matrix respectively to obtain the first relationship curve and the second relationship curve specifically includes the following process:

[0082] When the operating state is charging, extract the data with the state of charging from data to form the charging information matrix data 充 ;

[0083] When the operating state is discharging, extract the data with the state of discharging from data to form the discharging information matrix data 放 ;

[0084] For data 充 and data 放 , using the least squares method for fitting, the mapping relationship between the charging voltage value and the SOC value can be obtained respectively , that is, u = f 充 (soc); and the mapping relationship between the discharging voltage value and the SOC value , that is, u = f 放 (soc);

[0085] Thus, the comprehensive voltage - SOC curve of the energy storage system in the charging state, that is, the first relationship curve, and the comprehensive voltage - SOC curve in the discharging state, that is, the second relationship curve, are generated.

[0086] In some embodiments, the method further includes: responding to the preset operating conditions of the energy storage system within the operating day; wherein, in the first operating condition, generating a first cell list according to the voltage data of each cell obtained in real time, and screening to obtain a first list of cells to be balanced whose actual voltage value at the moment of charging cut-off is higher than the preset voltage threshold; in the second operating condition, generating a second cell list according to the voltage data of each cell obtained in real time, and screening to obtain a second list of cells to be balanced whose actual voltage value at the moment of discharging cut-off is lower than the preset voltage threshold.

[0087] In an example, the preset operating conditions of the energy storage system at least include a first operating condition and a second operating condition. The first operating condition includes: within the operating day, the energy storage system continuously operates in the charging condition (for example, for more than 10 minutes), and due to the excessive voltage of the single cell, the charging cut-off moment occurs; for the charging cut-off moment, select the cells whose cell voltage is higher than the average value (for example, a millivolts) as the first cells to be balanced and form a list of cells to be balanced.

[0088] The second operating condition includes: within an operating day, the energy storage system is continuously in a discharging condition (for more than 10 minutes), and at the moment of discharging cut-off due to the voltage of a single cell being too low; for the moment of discharging cut-off, cells with a voltage lower than the average value (such as a millivolts) are selected as the second cells to be balanced and a list of cells to be balanced is formed. Of course, the energy storage system also includes normal charging and discharging conditions, standby, shutdown conditions, etc., which will not be elaborated here.

[0089] It should be noted that when calculating the list of cells to be balanced in the energy storage system in this example, big data technology can be used to supplement the voltage data of all cells in the energy storage system at this time section (the moment of charging or discharging cut-off), and sort and calculate the average value thereof; it can be understood that the average value calculation means excluding 10% of the cells with the highest and lowest voltages of the cells, and then calculating the average value of the voltages of the remaining cells; taking a lithium-ion battery as an example, the value of a millivolts is 200, and for other batteries, the value of a can be determined according to the battery material characteristics.

[0090] In some embodiments, the method for predicting the capacity that can be improved by the energy storage system after cell balancing within an operating day according to the voltage data of each cell in the energy storage system and based on the first relationship curve and the second relationship curve includes: in the first operating condition: according to the first cell list, obtaining the highest voltage value among each cell; according to the first cell list and the first list of cells to be balanced, determining the first non-balanced cells and obtaining the highest voltage value of the first non-balanced cells; based on the first relationship curve, according to the highest voltage value among each cell and the highest voltage value of the first non-balanced cells, predicting the capacity that can be improved by the energy storage system after cell balancing within an operating day; in the second operating condition: according to the second cell list, obtaining the lowest voltage value among each cell; according to the second cell list and the second list of cells to be balanced, determining the second non-balanced cells and obtaining the lowest voltage value of the second non-balanced cells; based on the second relationship curve, according to the lowest voltage value among each cell and the lowest voltage value of the second non-balanced cells, predicting the capacity that can be improved by the energy storage system after cell balancing within an operating day.

[0091] In one example, in the first operating condition, for the moment of charging cut-off:

[0092] The highest voltage value of all cells in the energy storage system is denoted as u max ; the highest voltage value of the first non-balanced cells that are not in the first list of cells to be balanced is denoted as u max-无需均衡 ;

[0093] Under the charging condition, since the cells to be balanced need to be discharged when the cells are balanced, the increased capacity of the system after balancing is the difference between the highest cell voltage and the highest voltage of the non-cells to be balanced. The calculation formula for the increased SOC is as follows:

[0094] ;

[0095] where, is the inverse function of, represents the mapping function of the first relationship curve;

[0096] Therefore, the calculation formula for the increased capacity of the energy storage system is:

[0097] ;

[0098] Under the second operating condition, for the instant of discharge cut-off:

[0099] The lowest voltage of all cells in the energy storage system is denoted as u min ; The lowest voltage of the second unbalanced cells that are not in the second list of cells to be balanced is denoted as u min-无需均衡 ;

[0100] Under the discharge condition, since the cells to be balanced need to be charged when the cells are balanced, the increased capacity of the system after balancing is the difference between the lowest cell voltage and the lowest discharge voltage of the non-cells to be balanced. The calculation formula for the increased SOC is as follows:

[0101]

[0102] where, is the inverse function of f 放 (), f 放 () represents the mapping function of the second relationship curve; Therefore, the increased capacity of the energy storage system is:

[0103] ;

[0104] Thus, within the operating day, the increased capacity of the energy storage system in different operating states after cell balancing can be predicted, providing an effective basis for the cell balancing operation of the energy storage system.

[0105] In some embodiments, determining the cell balancing priorities of multiple energy storage systems according to the capacity that can be increased and the cell distribution of the energy storage system includes: obtaining the sum of the capacities that can be increased for each energy storage system based on the capacity that can be increased calculated at the moment of the most recent charging cut-off and the capacity that can be increased calculated at the moment of the most recent discharging cut-off; obtaining the balancing score value for each energy storage system respectively based on the sum of the capacities that can be increased for each energy storage system and the number of battery packs corresponding to the cells to be balanced in the energy storage system; sorting the balancing score values of the multiple energy storage systems, and determining the cell balancing priorities of the multiple energy storage systems.

[0106] In one example, for each set of energy storage systems: at the moment of the most recent charging cut-off (i.e., the most recent first operating condition) and the most recent discharging cut-off (i.e., the most recent second operating condition), the battery packs (i.e., energy storage battery packs) to which the corresponding cells in the list of cells to be balanced belong can be located according to the list of the first cells to be balanced and the list of the second cells to be balanced calculated according to the foregoing steps, and the number of battery packs distributed in each set of energy storage systems is respectively counted and denoted as n, such as n1, n2, n3; for example, in an energy storage system, there are 100 cells to be balanced in its list of cells to be balanced, and the above-mentioned cells to be balanced are distributed in 20 battery packs, then the number of battery packs corresponding to the cells to be balanced in this energy storage system n = 20, which will not be elaborated here.

[0107] At the moment of the most recent charging cut-off and the most recent discharging cut-off of each set of energy storage systems, the sum of the capacities that can be increased for each set of energy storage systems is respectively calculated based on the capacity that can be increased calculated at the moment of the most recent charging cut-off and the capacity that can be increased calculated at the moment of the most recent discharging cut-off, and is denoted as m, such as m1, m2, m3; therefore, the balancing cost performance score of each set of energy storage systems, that is, the balancing score value is denoted as score = m / n.

[0108] Further, when multiple sets of energy storage systems are included, the balancing score values score of each set of systems can be sorted. The higher the score, the higher the balancing priority. Furthermore, it can guide on-site operation and maintenance personnel to perform cell balancing operations on energy storage systems with higher priorities first, thereby improving the overall operating efficiency of the energy storage system and extending its service life.

[0109] To facilitate understanding of the technical solution of the present application, a specific application embodiment is provided below:

[0110] A 200MW / 400MWh independent energy storage power station consists of 10 sets of 20MW / 40MWh energy storage systems with 35kV, and each set of energy storage systems can be charged and discharged independently.

[0111] Taking the No. 1 energy storage system as an example, its operation data is used as the data of this embodiment. The No. 1 energy storage system uses the data from September 1, 2024 to September 30, 2024 as the historical operation data for the recent 30 days. After processing, the data can be formed in the following form:

[0112]

[0113] According to the above data, the mapping relationship f between the voltage value and the SOC value of the No. 1 energy storage system in the charge and discharge states is obtained by fitting 充 () and f 放 (), specifically referring to Figure 2 the first relationship curve shown and Figure 3 the second relationship curve shown.

[0114] On the operating day of October 1, 2024, under specific operating conditions, the list of cells to be balanced in the No. 1 energy storage system will be calculated and the improved capacity after balancing will be evaluated.

[0115] For example, at 11:38:12 on October 1, 2024, the energy storage system stopped charging due to the voltage of a single cell being too high and reaching the cut-off voltage. At this time, the highest voltage value of all cells in the energy storage system is recorded as u max = 3.6V, the average voltage is 3.35V, and the cells with a voltage between 3.45V and 3.6V are included in the list of cells to be balanced. Among the cells not in the list of cells to be balanced, the highest voltage value of the non-balanced cells is recorded as u max-无需均衡 = 3.34V. Referring to Figure 2 the curve, when charging is cut off, it can be obtained that:

[0116]

[0117] Therefore, after cell balancing, the improvement range of SOC is:

[0118] ;

[0119] The improved capacity of this energy storage system is:

[0120] ;

[0121] Similarly, when discharging is cut off, the cells with too low power can be balanced, and the improved capacity of this energy storage system can also be obtained.

[0122] By using big data technology to perform online real-time calculations on 10 energy storage systems in real time, it is possible to effectively screen out the number list of cells to be balanced, the battery packs to which they belong, and the sum of the improved capacities after balancing for each energy storage system when charging is cut off and discharging is cut off.

[0123] Finally, the equilibrium score values score of 10 sets of energy storage systems are calculated respectively, which are 0.9288, 0.9134, 0.6413, 0.7157, 0.4713, 0.2741, 0.4693, 0.4931, 0.4341, 0.8133 in sequence. Therefore, the equilibrium priorities are System No. 1, System No. 2, System No. 10, System No. 4, System No. 3, System No. 8, System No. 5, System No. 7, System No. 9, System No. 6. Thus, it can assist relevant technical personnel to perform cell balancing on each set of energy storage systems in the above equilibrium priority order, so that they can give priority to investing limited time and equipment resources in the battery pack with the highest cost performance, thereby reducing the outage time of the equipment and improving the available capacity of the energy storage system as much as possible.

[0124] In another embodiment of the present application, as Figure 4 shown, an energy storage system cell balancing evaluation device is provided. The energy storage system cell balancing evaluation device 400 includes:

[0125] An acquisition unit 410, configured to acquire historical operation data of at least one energy storage system;

[0126] A curve generation unit 420, configured to generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data;

[0127] A capacity calculation unit 430, configured to predict the improvable capacity of the energy storage system after cell balancing within an operating day based on the voltage data of each cell in the energy storage system and based on the first relationship curve and the second relationship curve;

[0128] A priority determination unit 440, configured to determine the cell balancing priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system.

[0129] It can be understood that each step of the foregoing energy storage system cell balancing evaluation method can be executed by the energy storage system cell balancing evaluation device provided in this embodiment. Therefore, the relevant explanations regarding the energy storage system cell balancing evaluation method are applicable to the energy storage system cell balancing evaluation device and will not be repeated here.

[0130] In summary, the present application has achieved at least the following technical effects: on the one hand, by using the big data real-time calculation technology, without the need to statically stop or open the energy storage system equipment, it is possible to realize the screening of the equalized cell list and quantitatively evaluate the improvable capacity of the energy storage system, providing an effective basis and guidance for the cell equalization operation of the energy storage system; on the other hand, by using the historical operation data of the energy storage system, the voltage-SOC mapping relationship is dynamically updated, and the evaluation is carried out based on the latest mapping relationship to achieve a more accurate evaluation effect; on the other hand, the equalization priority of multiple energy storage systems can be determined to assist relevant technical personnel in the operation and maintenance work of cell equalization, achieving the technical effect of reducing the equipment outage time and maximizing the available capacity of the energy storage system.

[0131] Figure 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Please refer to Figure 5 , at the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. Among them, the memory may include internal memory, such as high-speed random access memory (Random-Access Memory, RAM), and may also include non-volatile memory, such as at least one disk memory, etc. Of course, the electronic device may also include other hardware required for other services.

[0132] The processor, network interface, and memory can be interconnected through an internal bus, and the internal bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 5 only a bidirectional arrow is used in

[0133] Memory, used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory may include internal memory and non-volatile memory, and provide instructions and data to the processor.

[0134] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming an energy storage system cell equalization evaluation device at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0135] Obtain historical operation data of at least one energy storage system;

[0136] Generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data;

[0137] Based on the voltage data of each battery cell in the energy storage system and based on the first relationship curve and the second relationship curve, predict the improvable capacity of the energy storage system after the battery cells are balanced within the operating day;

[0138] Determine the cell balancing priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system.

[0139] The above energy storage system cell balance evaluation method disclosed in the embodiments of the present application Figure 1 can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor or by instructions in the form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0140] The embodiments of the present application also propose a computer program product. The computer program product stores one or more programs. The one or more programs include instructions that, when executed by an electronic device including multiple application programs, can enable the electronic device to execute Figure 1The energy storage system cell balancing evaluation method in the illustrated embodiment, and is specifically used to execute:

[0141] Obtain historical operation data of at least one energy storage system;

[0142] Generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data;

[0143] According to the voltage data of each cell in the energy storage system, and based on the first relationship curve and the second relationship curve, predict the improvable capacity of the energy storage system after cell balancing within the operation day;

[0144] Determine the cell balancing priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system.

[0145] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0147] These computer program instructions can 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 generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, causing a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process Figure 1 one process or a plurality of processes and / or boxes Figure 1 steps for implementing the functions specified in one box or a plurality of boxes.

[0149] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0150] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0151] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0152] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0153] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0154] The above are only the embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for evaluating the balance of energy storage system battery cells, characterized in that, The method includes: Obtaining historical operation data of at least one energy storage system; Generating a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data; Predicting the improvable capacity of the energy storage system after cell equalization within an operation day according to the voltage data of each cell in the energy storage system and based on the first relationship curve and the second relationship curve; Determining the cell equalization priorities of multiple energy storage systems according to the improvable capacity and the cell distribution of the energy storage system, including: Obtaining the sum of the improvable capacities of each energy storage system according to the improvable capacity calculated at the moment of the most recent charging cut-off and the improvable capacity calculated at the moment of the most recent discharging cut-off; Respectively obtaining the equalization score value of each energy storage system according to the sum of the improvable capacities of each energy storage system and the number of battery packs corresponding to the cells to be equalized in the energy storage system; Sorting the equalization score values of multiple energy storage systems and determining the cell equalization priorities of multiple energy storage systems.

2. The assessment method according to claim 1, wherein The first relationship curve includes a mapping relationship curve between the charging voltage value and the SOC value of the energy storage system; the second relationship curve includes a mapping relationship curve between the discharging voltage value and the SOC value of the energy storage system.

3. The evaluation method according to claim 1, wherein The historical operation data at least includes one of the following: the operation state, voltage value, and SOC value corresponding to the energy storage system at different sampling moments before the operation day; The generating a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operation data includes: Generating a multi-dimensional information matrix according to the historical operation data of the at least one energy storage system; Respectively obtaining a charging information matrix in the charging state and a discharging information matrix in the discharging state according to the multi-dimensional information matrix; Fitting the charging information matrix and the discharging information matrix and respectively obtaining the first relationship curve and the second relationship curve.

4. The evaluation method according to claim 1, characterized in that The method further includes: Responding to special operation conditions of the energy storage system within an operation day; wherein, In a first operation condition, generating a first cell list according to the voltage data of each cell obtained in real time, and screening to obtain a first list of cells to be equalized with the actual voltage value higher than the preset voltage threshold at the moment of charging cut-off; In a second operation condition, generating a second cell list according to the voltage data of each cell obtained in real time, and screening to obtain a second list of cells to be equalized with the actual voltage value lower than the preset voltage threshold at the moment of discharging cut-off.

5. The evaluation method according to claim 4, characterized in that The predicting the improvable capacity of the energy storage system after cell equalization within an operation day according to the voltage data of each cell in the energy storage system and based on the first relationship curve and the second relationship curve includes: In the first operation condition: Obtaining the highest voltage value among each cell according to the first cell list; Determining the first non-cell-to-be-equalized according to the first cell list and the first list of cells to be equalized, and obtaining the highest voltage value of the first non-cell-to-be-equalized; Based on the first relationship curve, according to the highest voltage value in each battery cell and the highest voltage value of the first non - to - be - balanced battery cell, the improvable capacity of the energy storage system after battery cell balancing is predicted within the operating day; Under the second operating condition: According to the second battery cell list, obtain the lowest voltage value in each battery cell; According to the second battery cell list and the second to - be - balanced battery cell list, determine the second non - to - be - balanced battery cell, and obtain the lowest voltage value of the second non - to - be - balanced battery cell; Based on the second relationship curve, according to the lowest voltage value in each battery cell and the lowest voltage value of the second non - to - be - balanced battery cell, the improvable capacity of the energy storage system after battery cell balancing is predicted within the operating day.

6. The evaluation method according to claim 1, characterized in that, The method further includes: Performing data pre - processing on the obtained historical operating data; The data pre - processing at least includes one of the following operations: performing missing value processing, duplicate value processing, outlier processing, and filling point alignment processing on the historical operating data.

7. An energy storage system cell balancing evaluation device, characterized in that, The device includes: An acquisition unit, configured to acquire historical operating data of at least one energy storage system; A curve generation unit, configured to generate a first relationship curve in the charging state and a second relationship curve in the discharging state of the energy storage system according to the historical operating data; A capacity calculation unit, configured to predict the improvable capacity of the energy storage system after battery cell balancing within the operating day according to the voltage data of each battery cell in the energy storage system and based on the first relationship curve and the second relationship curve; A priority determination unit, configured to determine the battery cell balancing priorities of multiple energy storage systems according to the improvable capacity and the battery cell distribution of the energy storage system, including: Obtaining the sum of the improvable capacities of each energy storage system according to the improvable capacity calculated at the moment of the most recent charging cut - off and the improvable capacity calculated at the moment of the most recent discharging cut - off; Respectively obtaining the balance score value of each energy storage system according to the sum of the improvable capacities of each energy storage system and the number of battery packs corresponding to the to - be - balanced battery cells in the energy storage system; Sorting the balance score values of multiple energy storage systems, and determining the battery cell balancing priorities of multiple energy storage systems.

8. An electronic device, wherein, The electronic device includes: a processor; and a memory arranged to store computer - executable instructions, the executable instructions when executed cause the processor to execute the evaluation method according to any one of claims 1 to 6.

9. A computer-readable storage medium, wherein, The computer - readable storage medium stores one or more programs, and the one or more programs when executed by a processor, implement the evaluation method according to any one of claims 1 to 6.

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