Energy storage system operation and maintenance method, device, equipment and medium

Abstract

The invention discloses an energy storage system operation and maintenance method and device, equipment and a medium. The method comprises the following steps: acquiring a battery health state value of each battery cell monomer in the energy storage system, and further evaluating a battery state of each battery cell monomer in the energy storage system; calculating data dispersion according to the battery health state value of each battery cell monomer in the energy storage system; and when the data dispersion exceeds the preset dispersion range, executing a battery replacement operation and maintenance strategy, thereby ensuring normal operation of the energy storage system, prolonging the service life of the energy storage system, and solving the problems of difficult evaluation and difficult determination of a reasonable battery replacement operation and maintenance period due to battery attenuation in a traditional energy storage system. Therefore, the operation and maintenance efficiency and economy of the whole operation and maintenance system are improved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage system operation and maintenance technology, and in particular to an energy storage system operation and maintenance method, device, equipment and medium. Background Art

[0002] Battery State of Health (SOH) is a key indicator used in the Battery Management System (BMS) to characterize the degradation of battery cells in energy storage systems.

[0003] In the current SOH estimation method for energy storage systems, the SOH of each single battery is directly tested separately, and then the SOH values of all single batteries are arithmetic averaged to obtain the SOH of the entire energy storage battery pack.

[0004] However, existing technologies fail to consider the actual performance weight of individual cells in a battery pack. When the SOH of individual cells varies significantly, this cannot accurately reflect the overall health of the battery pack, making it difficult to determine a reasonable battery replacement and maintenance cycle. For example, if the SOH of most individual cells in a battery pack is high, but a few are extremely low, a direct averaging method will overestimate the actual usable health of the battery pack. Summary of the Invention

[0005] The present invention provides an energy storage system operation and maintenance method, device, equipment and medium, which solves the problem in traditional energy storage systems that it is difficult to evaluate and determine a reasonable battery replacement operation and maintenance cycle due to battery degradation.

[0006] According to one aspect of the present invention, there is provided an energy storage system operation and maintenance method, comprising:

[0007] Obtain the battery health status value of each battery cell in the energy storage system;

[0008] Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system;

[0009] When the data discreteness exceeds the preset discrete range, the battery replacement operation and maintenance strategy is executed.

[0010] Optionally, obtain the battery health status of each cell in the energy storage system, including:

[0011] Obtain the battery health status value of each battery cell in the energy storage system when it is in the same battery loss state.

[0012] Optionally, the data dispersion is calculated based on the battery health status value of each battery cell in the energy storage system, including:

[0013] Determine the upper quartile Q1 and lower quartile Q3 of the battery health status values of all battery cells;

[0014] Based on the upper quartile Q1 and the lower quartile Q3, the interquartile range IQR is calculated as the data dispersion.

[0015] Optionally, after calculating the data dispersion based on the battery health status value of each battery cell in the energy storage system, the following is also included:

[0016] When the data discreteness is within a preset discrete range, the median M of the battery health status values of all battery cells is determined, and the median M is used as the battery health status value of the energy storage system.

[0017] Optionally, when the data discreteness is within a preset discrete range, after determining the median M of the battery health status values of all battery cells and using the median M as the battery health status value of the energy storage system, the method further includes:

[0018] When the data dispersion is within the preset discrete range and the median M value is within the preset healthy value range, the operation continues;

[0019] When the data discreteness is within the preset discrete range and the value of the median M exceeds the preset range of the health value, the battery replacement operation and maintenance strategy is executed.

[0020] Optionally, before calculating the data dispersion based on the battery health status value of each battery cell in the energy storage system, the following steps may also be performed:

[0021] Determine whether there are abnormal values in the battery health status value of each battery cell in the energy storage system;

[0022] When there are abnormal values in the battery health status value of each battery cell in the energy storage system and the abnormal values are accidental abnormal values, the abnormal values are eliminated.

[0023] Optionally, determining whether there are any abnormal values in the battery health status value of each battery cell in the energy storage system includes:

[0024] When the battery health status value of any battery cell is outside the normal value judgment range, the battery health status value of the battery cell is determined to be an abnormal value; wherein the normal value judgment range is (Q1-k*IQR, Q3+k*IQR), where k is a preset constant;

[0025] When the battery health status values of all battery cells are within the normal value judgment range, it is determined that no abnormal value exists in the battery health status value of each battery cell in the energy storage system.

[0026] Optionally, after determining whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system, the method further includes:

[0027] When an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determine whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value;

[0028] When the abnormal value is non-accidental, the battery replacement operation and maintenance strategy is executed.

[0029] Optionally, when an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determining whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value includes:

[0030] Obtain the "battery health status value-cycle number" curve of the battery cell corresponding to the abnormal value;

[0031] When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all within the normal value judgment range, the abnormal value is determined to be an accidental abnormal value;

[0032] When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all outside the normal value judgment range, the abnormal value is determined to be a non-accidental abnormal value.

[0033] According to another aspect of the present invention, there is provided an energy storage system operation and maintenance device, comprising:

[0034] An information acquisition module is used to obtain and record the battery health status value of each battery cell in the energy storage system;

[0035] The dispersion calculation module is used to calculate the data dispersion based on the battery health status value of each battery cell in the energy storage system;

[0036] The battery swap operation and maintenance module is used to execute the battery swap operation and maintenance strategy when the data discreteness is not within the preset range.

[0037] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0038] at least one processor;

[0039] and a memory communicatively coupled to the at least one processor;

[0040] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute any energy storage system operation and maintenance method according to any embodiment of the present invention.

[0041] According to another aspect of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores computer instructions for causing a processor to execute any energy storage system operation and maintenance method according to any embodiment of the present invention.

[0042] The technical solution of the embodiment of the present invention obtains the battery health status value of each battery cell in the energy storage system, and then evaluates the battery status of each battery cell in the energy storage system. According to the battery health status value of each battery cell in the energy storage system, the data discreteness is calculated, and then the consistency of the battery cells in the energy storage system is quantitatively evaluated to judge the stability of the energy storage system. When the data discreteness exceeds the preset discrete range, the battery replacement operation and maintenance strategy is executed to replace the battery cells with large differences in aging degree, so that the health status of the battery cells in the energy storage system can reach a more consistent level again, thereby ensuring the normal operation of the energy storage system and extending the service life of the energy storage system. It solves the problem that it is difficult to evaluate and determine a reasonable battery replacement operation and maintenance cycle due to battery attenuation in traditional energy storage systems, thereby improving the operation and maintenance efficiency and economy of the entire operation and maintenance system.

[0043] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 This is a flow chart of an energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0046] Figure 2 is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0047] Figure 3 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0048] Figure 4 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0049] Figure 5 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0050] Figure 6This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0051] Figure 7 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0052] Figure 8 Schematic diagram of a SOH-cycle number curve of a single cell provided by an embodiment of the present invention;

[0053] Figure 9 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention;

[0054] Figure 10 This is a structural block diagram of an energy storage system operation and maintenance device provided by an embodiment of the present invention;

[0055] Figure 11 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0057] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. 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 necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0058] Figure 1 This is a flow chart of an energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is applicable to evaluating the overall health of a battery energy storage system. The method can be executed by an energy storage system operation and maintenance device, which can be implemented in the form of hardware and / or software. Figure 1 As shown, the method includes:

[0059] S110: Obtain the battery health status value of each battery cell in the energy storage system.

[0060] Among them, the energy storage system can be understood as a device or system that can store electrical energy and release the stored electrical energy when needed. In this scenario, it specifically refers to a battery pack composed of multiple battery cells connected in series, parallel, etc. to form a battery pack with certain voltage, capacity and power characteristics; the battery cell can be understood as the most basic energy storage unit in the energy storage system; the battery health status value can be understood as an indicator for quantitatively evaluating the health of the battery cell, which reflects the degree of performance degradation of the battery cell in its current state relative to its initial state (brand new state). For example, the battery health status value can represent the ratio of the actual available capacity of the current battery cell to the initial capacity.

[0061] Specifically, the energy storage system calculates the actual available capacity of each cell in each cycle by recording parameters such as the voltage, current, and time of each cell during each charge and discharge process. Based on the ratio of the actual available capacity to the initial capacity, the system then obtains and records the battery health status of each cell. The initial capacity can be obtained from the cell's operation log, or it can be manually set using the capacity marked on the cell.

[0062] S120: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0063] Specifically, the battery management system consists of multiple battery cells. After obtaining the battery health status value of each battery cell, it is first necessary to determine the battery health mean of the battery cell based on the battery health status value of each battery cell, and calculate the specific dispersion based on dispersion indicators (such as range, variance, standard deviation, interquartile range, etc.), and then quantitatively evaluate the consistency of the battery cells in the energy storage system and judge the stability of the energy storage system.

[0064] S130. When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0065] Among them, the preset discrete range can be understood as a pre-set minimum battery health level range required for the energy storage system to operate normally and efficiently based on multiple factors such as the design specifications, expected performance and safe operation standards of the energy storage system; the battery replacement operation and maintenance strategy can be understood as a series of maintenance and repair measures taken when the health status of the battery cells in the energy storage system is poor and the degree of discreteness is large, such as replacing battery cells with performance differences that are significantly different from other battery cells.

[0066] Specifically, after confirming that the dispersion index exceeds the preset discrete range, it can be understood that based on multiple factors such as the design standards of the energy storage system, historical operating data, and industry experience, it can be determined that the current energy storage system is not suitable for continued operation. The energy storage system needs to be adjusted through a pre-set battery replacement operation and maintenance strategy until the energy storage system performance meets the requirements.

[0067] The technical solution of the embodiment of the present invention obtains the battery health status value of each battery cell in the energy storage system, and then evaluates the battery status of each battery cell in the energy storage system. According to the battery health status value of each battery cell in the energy storage system, the data discreteness is calculated, and then the consistency of the battery cells in the energy storage system is quantitatively evaluated to judge the stability of the energy storage system. When the data discreteness exceeds the preset discrete range, the battery replacement operation and maintenance strategy is executed to replace the battery cells with large differences in aging degree, so that the health status of the battery cells in the energy storage system can reach a more consistent level again, thereby ensuring the normal operation of the energy storage system and extending the service life of the energy storage system. It solves the problem that it is difficult to evaluate and determine a reasonable battery replacement operation and maintenance cycle due to battery attenuation in traditional energy storage systems, thereby improving the operation and maintenance efficiency and economy of the entire operation and maintenance system.

[0068] Optionally, after “S120, calculating data dispersion according to the battery health status value of each battery cell in the energy storage system,” the following steps may be added:

[0069] S121. When the data discreteness is within a preset discrete range, determine a median M of the battery health status values of all battery cells, and use the median M as the battery health status value of the energy storage system.

[0070] The median M can be understood as the battery health status values of all battery cells sorted from small to large. If the number of battery cells is odd, the median M is the value in the middle position; if it is an even number, the median M is the average of the two middle values. The battery health status value of the energy storage system can be understood as a quantitative indicator representing the overall health of the entire energy storage system.

[0071] Specifically, when the data dispersion falls within the preset discrete range, it indicates that the health status of each battery cell in the energy storage system varies little and exhibits good consistency. At this point, the system first reads the battery health status values of all battery cells from the storage device and determines the median M. The system then records and stores this median M as the battery health status value of the energy storage system. This provides a representative quantitative indicator for subsequent analysis of the energy storage system's overall performance and prediction of remaining service life, improving the convenience and scientific nature of operation and maintenance work and optimizing the energy storage system's operation and maintenance process.

[0072] Based on the above S121, further optionally, after “S121, when the data discreteness is within the preset discrete range, determining the median M of the battery health status values of all battery cells, and using the median M as the battery health status value of the energy storage system”, the following steps may be added:

[0073] S1221. When the data dispersion is within the preset dispersion range and the median M value is within the preset health value range, continue running;

[0074] S1222. When the data discreteness is within the preset discrete range and the value of the median M exceeds the preset range of the health value, the battery replacement operation and maintenance strategy is executed.

[0075] The preset range of health values can be understood as a pre-set range of battery health levels required for the energy storage system to operate normally and efficiently, based on multiple factors such as the design specifications, expected performance, and safe operation standards of the energy storage system.

[0076] Specifically, after confirming that the interquartile range IQR is less than or equal to the preset IQR threshold, the system also needs to determine whether the value of the median M exceeds the preset range of the health value. If the median M exceeds the preset range of the health value, it means that the overall health of the energy storage system is not good, which may affect its normal operation. At this time, the system will trigger the battery replacement operation and maintenance strategy. On the contrary, if the value of the median M is within the preset range of the health value, it means that the overall health of the system is good and it can continue to operate normally. The technical solution of the embodiment of the present invention effectively avoids system failures caused by overall battery loss, and thus solves the problem that it is difficult to evaluate and determine a reasonable battery replacement operation and maintenance cycle due to battery attenuation in traditional energy storage systems, thereby improving the operation and maintenance efficiency and economy of the entire operation and maintenance system.

[0077] For example, assuming the maximum battery health value is 100% (usually set based on the health status of a brand new battery cell), the preset health value range can be 80% × maximum battery health value - 100% × maximum battery health value, that is, 80% - 100%. When the median M is greater than 80% × maximum battery health value, the system determines that the overall health is good and allows the energy storage system to continue normal operation and provide stable power to related equipment or systems without the need for battery replacement and maintenance. Otherwise, it means that the battery has reached its expected lifespan and requires battery replacement and maintenance.

[0078] Figure 2 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is a refinement of the previous embodiment. Specifically, "S110, obtaining the battery health status value of each battery cell in the energy storage system." can be refined as follows:

[0079] Obtain the battery health status value of each battery cell in the energy storage system when it is in the same battery loss state.

[0080] like Figure 2 As shown, the method includes:

[0081] S210: Obtain the battery health status value of each battery cell in the energy storage system when it is in the same battery loss state.

[0082] The battery health status value when in the same battery loss state can be understood as the battery health status value corresponding to battery cells with approximately the same cumulative charge and discharge capacity (approximately the same loss over the service life). For example, the battery health status value of each battery cell in the energy storage system at the last cycle, or the battery health status value at the second to last cycle, can be considered to be in the same battery loss state.

[0083] Specifically, to ensure that the obtained battery health status values are in the same battery loss state, so as to more accurately evaluate the health of the battery cells and the consistency of the energy storage system, the energy storage system will obtain and record the battery health status value of each battery cell when it is in the same battery loss state according to the preset selection logic. For example, the ratio of the actual available capacity to the initial capacity of each battery cell in the energy storage system at the time of the last cycle is selected as the battery health status value of the battery cell when it is in the same battery loss state and recorded. At this point, the degree of battery loss experienced by each battery cell is similar, and the health of each battery cell can be compared on the same dimension, avoiding evaluation deviations caused by different loss stages.

[0084] S220: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0085] S230. When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0086] The embodiment of the present invention, based on the above embodiment, obtains the battery health status value of each battery cell in the energy storage system when it is in the same battery loss state, ensuring that the battery loss degree experienced by each battery cell is similar. The health status of each battery cell can be compared on the same dimension, avoiding assessment deviations caused by different loss stages, and further improving the accuracy and reliability of the energy storage system health status assessment.

[0087] Figure 3 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is refined based on the above embodiments. Specifically, "S120, calculate the data dispersion according to the battery health status value of each battery cell in the energy storage system, which can be refined as follows:

[0088] Determine the upper quartile Q1 and lower quartile Q3 of the battery health status values of all battery cells;

[0089] Based on the upper quartile Q1 and the lower quartile Q3, the interquartile range IQR is calculated as the data dispersion.

[0090] like Figure 3 As shown, the method includes:

[0091] S310: Obtain the battery health status value of each battery cell in the energy storage system.

[0092] S320 : Determine the upper quartile Q1 and the lower quartile Q3 of the battery health status values of all battery cells.

[0093] Among them, the upper quartile Q1 can be understood as sorting the battery health status values of all battery cells from small to large, dividing the data into four equal parts, and the value at the 75% position is the upper quartile; the lower quartile Q3 can be understood as the value at the 25% position.

[0094] Specifically, the system first reads the battery health status value data of each battery cell from a storage device, such as a database or file system. It then sorts the battery health status values and uses the sorted data as a basis to calculate the upper quartile Q1 and lower quartile Q3. The upper quartile Q1 reflects the middle position of the higher part of the data distribution, while the lower quartile Q3 reflects the middle level of battery cells with relatively poor health. By calculating these statistical values, a data foundation is provided for subsequent analysis of the discrete degree of battery cell health status.

[0095] S330. Based on the upper quartile Q1 and the lower quartile Q3, calculate the interquartile range IQR as the data dispersion.

[0096] Among them, the interquartile range IQR can be understood as the difference between the upper quartile Q1 and the lower quartile Q3.

[0097] Specifically, the system calculates the interquartile range (IQR) by taking the difference between the upper quartile Q1 and the lower quartile Q3 through the preset second calculation module. The interquartile range (IQR) is used to measure the degree of dispersion of the data. Compared with the range (the difference between the maximum and minimum values), the interquartile range is less susceptible to extreme values and can better reflect the fluctuations in the middle 50% of the data.

[0098] S340. When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0099] For example, when the dispersion index is IQR, after a large number of experiments and actual operation data statistics, it is found that when the IQR is greater than 5% × the maximum battery health value, the stability and reliability of the system will be significantly affected, then 5% × the maximum battery health value can be set as the preset IQR threshold of the energy storage system. When the interquartile range IQR calculated by the system is greater than 5% × the maximum battery health value, the system generates a battery replacement operation and maintenance task list, including the battery cell number that needs to be inspected, the expected number of battery cells to be replaced, the required new battery cell model and other information. Then, the operation and maintenance personnel will inspect, replace and adjust the battery cells according to the task list until the performance of the energy storage system meets the requirements.

[0100] In this embodiment of the present invention, based on the above embodiment, the interquartile range (IQR) is used as the data dispersion, which can effectively avoid the interference of extreme values on the results, more accurately reflect the degree of dispersion of the health status of battery cells in the energy storage system, and provide a more reliable data basis for subsequent evaluation and decision-making.

[0101] Figure 4 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is optimized based on the above embodiments. Specifically, before "S120, calculating data dispersion based on the battery health status value of each battery cell in the energy storage system", it also includes:

[0102] Determine whether there are abnormal values in the battery health status value of each battery cell in the energy storage system;

[0103] When there are abnormal values in the battery health status value of each battery cell in the energy storage system and the abnormal values are accidental abnormal values, the abnormal values are eliminated.

[0104] like Figure 4 As shown, the method includes:

[0105] S410: Obtain the battery health status value of each battery cell in the energy storage system.

[0106] S420: Determine whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system.

[0107] An outlier is defined as a situation in which the BHS of a single cell in an energy storage system differs significantly from that of the majority of other cells. This deviation from the normal range is considered an outlier, and includes both accidental and non-accidental values. For example, if the BHS of a cell in a given cycle suddenly drops to 60% (while the other cells are all above 80%), significantly deviating from the group distribution, it is considered an outlier.

[0108] Specifically, the interquartile range (IQR) of the battery health status data can be calculated to determine the normal range, and then the presence of outliers can be determined based on this range. Alternatively, a distribution curve of the battery health status values in the energy storage system can be fitted, and the residuals between the fitted curve and the actual data points can be calculated. The normal range can then be determined based on the distribution of the residuals to determine the presence of outliers.

[0109] S430: When there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, eliminate the abnormal value.

[0110] Among them, accidental outliers can be understood as outliers caused by temporary interference (sensor failure, communication interference, measurement error, instantaneous environmental fluctuation, etc.).

[0111] Specifically, since occasional outliers have no abnormalities in other related indicators (such as temperature, voltage, etc.) and are difficult to re-test and reproduce, they cannot reflect the actual performance degradation of the battery cell. Therefore, the battery health status value record of this cycle is directly deleted and supplemented by interpolation of adjacent data.

[0112] S440: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0113] S450: When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0114] The embodiment of the present invention, based on the above embodiment, determines whether there are abnormal values in the battery health status value of each battery cell in the energy storage system, significantly improving the reliability of the discreteness indicator; by eliminating accidental abnormal values, the credibility of the data is improved, and invalid battery replacement operations caused by misjudgment are reduced.

[0115] Figure 5 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is a refinement of the above embodiments. Specifically, "S420, determining whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system" can be refined as follows:

[0116] When the battery health status value of any battery cell is outside the normal value judgment range, the battery health status value of the battery cell is determined to be an abnormal value; wherein the normal value judgment range is (Q1-k*IQR, Q3+k*IQR), where k is a preset constant;

[0117] When the battery health status values of all battery cells are within the normal value judgment range, it is determined that no abnormal value exists in the battery health status value of each battery cell in the energy storage system.

[0118] like Figure 5As shown, the method includes:

[0119] S510: Obtain the battery health status value of each battery cell in the energy storage system.

[0120] S520 : When the battery health status value of any battery cell is outside the normal value judgment range, determine that the battery health status value of the battery cell is an abnormal value.

[0121] The normal value judgment range is (Q1-k*IQR, Q3+k*IQR), where k is a preset constant.

[0122] Specifically, by calculating the upper quartile Q1, the lower quartile Q3 and the interquartile range IQR, a normal value judgment range is constructed. When a battery health status value is outside the normal value judgment range, the battery health status value of the battery cell is determined to be an abnormal value and recorded.

[0123] S530: When the battery health status values of all battery cells are within the normal value judgment range, determine that no abnormal value exists in the battery health status value of each battery cell in the energy storage system.

[0124] Specifically, after sequentially determining the relationship between the battery health status values of all battery cells and the normal value judgment range, if the battery health status values of all battery cells are within the normal value judgment range, it is determined that there are no abnormal values in the battery health status values, thereby ensuring the accuracy of the battery health status assessment of the energy storage system and providing a reliable basis for subsequent operation and maintenance decisions.

[0125] S540: When there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, eliminate the abnormal value.

[0126] S550: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0127] S560: When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0128] The embodiment of the present invention, based on the above embodiment, refines the step of determining whether there are abnormal values in the battery health status values of the battery cells in the energy storage system. It determines whether the battery health status value of the battery cell is an abnormal value through the normal value judgment range, and identifies the battery cell with possible problems. By judging all battery cells in sequence, the accuracy of the health status assessment of the battery cells of the energy storage system is ensured, providing a reliable basis for subsequent operation and maintenance decisions.

[0129] Figure 6This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is optimized based on the above embodiments. Specifically, after "S430, when an abnormal value exists in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, the abnormal value is eliminated", it also includes:

[0130] When an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determine whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value;

[0131] When the abnormal value is non-accidental, the battery replacement operation and maintenance strategy is executed.

[0132] like Figure 6 As shown, the method includes:

[0133] S610: Obtain the battery health status value of each battery cell in the energy storage system.

[0134] S620: Determine whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system.

[0135] S630: When an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determine whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value.

[0136] Among them, non-accidental outliers can be understood as anomalies that reflect the actual performance degradation of the battery cell, which is a permanent decrease in capacity due to various reasons such as aging.

[0137] Specifically, the battery health status value of the battery cell can be continuously monitored, and when an abnormal value is detected, the battery health status value of the abnormal value battery cell in the adjacent charge and discharge cycle can be detected. If the battery health status value of the same battery cell is abnormal in multiple consecutive charge and discharge cycles (deviation > 15%), it is determined to be a non-accidental abnormal value; if the abnormal value is isolated and the historical data volatility is <5%, it is determined to be an accidental abnormal value.

[0138] For example, if the battery health value of a cell suddenly drops to 75% at the 150th cycle (the historical average is 85%), but recovers to 84.5% at the 151st cycle, then the 150th data is an accidental outlier. Conversely, if the battery health value of a cell drops continuously from 85% to 70% over five consecutive cycles and the internal resistance increases by 20%, then the battery health value data of this cell is a non-accidental outlier.

[0139] S640: When the abnormal value is a non-accidental abnormal value, execute the battery replacement operation and maintenance strategy.

[0140] Specifically, when the abnormal value is determined by the system to be a non-accidental abnormality, the system executes the pre-set battery replacement operation and maintenance strategy and generates operation and maintenance tasks based on the fluctuation amplitude of the non-accidental abnormal value.

[0141] For example, the operation and maintenance tasks generated based on non-accidental abnormal values may include: limiting the charge and discharge rate, determining whether it is under warranty, calling inventory information, generating purchase work orders, capacity testing after battery replacement, etc.

[0142] S650: When there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, eliminate the abnormal value.

[0143] S660: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0144] S670: When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0145] The embodiment of the present invention introduces the judgment of accidental outliers or non-accidental outliers on the basis of the above embodiment. When the outlier value is a non-accidental outlier value, the battery replacement operation and maintenance strategy is executed, which solves the problems of high misjudgment rate and delayed response in traditional methods.

[0146] Figure 7 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. This embodiment is a refinement of the previous embodiment. Specifically, "S630, when an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determine whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value." can be refined as follows:

[0147] Obtain the "battery health status value-cycle number" curve of the battery cell corresponding to the abnormal value;

[0148] When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all within the normal value judgment range, the abnormal value is determined to be an accidental abnormal value;

[0149] When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all outside the normal value judgment range, the abnormal value is determined to be a non-accidental abnormal value.

[0150] like Figure 7 As shown, the method includes:

[0151] S710: Obtain the battery health status value of each battery cell in the energy storage system.

[0152] S720: Determine whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system.

[0153] S730: Obtain a “battery health status value-cycle number” curve of the battery cell corresponding to the abnormal value.

[0154] Among them, the "battery health status value-cycle number" curve can be understood as a curve that records the changing trend of the battery health status value of a single battery cell under different cycle numbers, reflecting the long-term attenuation characteristics of the battery cell.

[0155] Specifically, Figure 8 Schematic diagram of the SOH-cycle number curve of a single cell provided by an embodiment of the present invention, such as Figure 8 As shown, the system continuously records the battery health status value after each charge and discharge cycle, and draws a line graph with the number of cycles as the horizontal axis and the battery health status value as the vertical axis.

[0156] S740: When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all within the normal value judgment range, determine that the abnormal value is an accidental abnormal value.

[0157] Among them, the preset number of battery health status values can be understood as the range of adjacent cycle times that need to be checked. For example, the preset number can be the 3 times before and 2 times after the abnormal value (a total of 5 data points).

[0158] Specifically, when a sudden drop / sudden rise in the battery health status value of a certain battery cell is determined to be an abnormal value, the "battery health status value-number of cycles" curve of the battery cell is called and the battery health status values of adjacent cycles near the abnormal value are detected. If the battery health status values of adjacent cycles are all within the normal value judgment range and there are no other related parameter abnormalities (such as temperature and internal resistance are normal), then the abnormal value is judged to be an accidental abnormal value.

[0159] S750: When a preset number of battery health status values near the abnormal value in the “battery health status value-cycle number” curve are all outside the normal value judgment range, determine that the abnormal value is a non-accidental abnormal value.

[0160] Specifically, when a sudden drop / sudden rise in the battery health status value of a certain battery cell is determined to be an abnormal value, the "battery health status value-number of cycles" curve of the battery cell is called and the battery health status values of adjacent cycles near the abnormal value are detected. If the battery health status values of adjacent cycles show an accelerated decay trend for multiple consecutive times, and are accompanied by related indicators such as increased internal resistance and abnormal temperature rise, then the abnormal value is judged to be a non-accidental abnormal value.

[0161] For example, starting from the 200th cycle, the SOH value of a certain battery cell decreases for five consecutive cycles: 78% → 75% → 72% → 68% → 65% (the normal value judgment range is greater than 80%). At the same time, it is detected that the internal resistance of the battery cell increases by 30% and the temperature rise is 5°C higher than that of other battery cells. In this case, the abnormal value is judged to be a non-accidental abnormal value.

[0162] S760: When the abnormal value is a non-accidental abnormal value, execute the battery replacement operation and maintenance strategy.

[0163] S770: When there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, eliminate the abnormal value.

[0164] S780: Calculate data dispersion based on the battery health status value of each battery cell in the energy storage system.

[0165] S790: When the data discreteness exceeds the preset discrete range, execute the battery replacement operation and maintenance strategy.

[0166] This embodiment of the present invention, building on the previous example, refines the method of distinguishing accidental and non-accidental outliers using the "battery health status value - cycle count" curve. This transforms outlier determination from a single-point judgment into trend analysis, resolving the problem of traditional O&M methods being unable to distinguish between temporary anomalies and permanent faults. This effectively avoids unnecessary O&M operations caused by misjudgments, while promptly identifying and addressing problematic cells. This improves the efficiency and safety of the energy storage system and reduces O&M costs and the risk of failure.

[0167] For the operation and maintenance methods of the above embodiments, the present invention also provides a specific implementation process. Figure 9 This is a flow chart of another energy storage system operation and maintenance method provided by an embodiment of the present invention. Figure 9 The actual operation and maintenance process is introduced as follows:

[0168] S810: Calculate the SOH of all battery cells in the energy storage system and draw a "SOH-cycle number" curve.

[0169] After this step is completed, S820 is executed.

[0170] S820: Take the SOH values of all monomers at a certain moment and sort them in descending order.

[0171] After this step is completed, S830 is executed.

[0172] S830. Based on the box plot theory, look up the table to calculate the median M, upper quartile Q1, lower quartile Q3, maximum value Q2, minimum value Q4, and outlier O of all monomer SOH values at this moment.

[0173] After this step is completed, S840 is executed.

[0174] S840. Eliminate outliers O, calculate the interquartile range (IQR), and determine the data dispersion.

[0175] After this step is completed, S850 is executed.

[0176] S850. Determine whether IQR is ≤5%?

[0177] If so, execute S860; if not, execute S890.

[0178] S860. Take the M value as the SOH value of the energy storage system.

[0179] After this step is completed, S870 is executed.

[0180] S870. Determine whether M is ≥ 70%?

[0181] If so, execute S880; if not, execute S890.

[0182] S880, continue running.

[0183] S890, battery swap operation and maintenance.

[0184] The energy storage system operation and maintenance method provided by the embodiment of the present invention first calculates the SOH of all battery cells in the energy storage system, draws a "SOH-cycle number" curve, and obtains the battery health of each battery cell and its corresponding change curve; secondly, takes the SOH values of all cells at a certain moment, sorts them in order from large to small, and sorts the battery cell data for easy analysis; then, based on the box plot theory, calculates the median M, upper quartile Q1, lower quartile Q3, maximum value Q2, minimum value Q4, and outlier O of the SOH values of all cells at this moment, and evaluates the overall state of the entire energy storage system; then, eliminates the outlier O, calculates the interquartile range IQR, and judges the data dispersion, thereby reducing the judgment errors caused by errors. Accurate, on this basis, calculate the dispersion that can be used to evaluate whether there are any abnormal cells in the entire system; further, determine whether the IQR is ≤5%. If the dispersion of the energy storage system is higher than the preset threshold, it means that the energy storage system cannot evaluate the overall health of the energy storage system through the median, and battery replacement and maintenance are required; correspondingly, if the dispersion of the energy storage system is lower than the preset threshold, it means that the energy storage system does not have the problem of inconsistent battery cells, and the overall health of the energy storage system can be evaluated through the median, and the M value is taken as the SOH value of the energy storage system; on this basis, the system still needs to determine whether M is ≥70% to determine whether the consistent energy storage system is aged as a whole, the energy storage efficiency is reduced, and battery replacement and maintenance are required. If M is less than 70%, battery replacement and maintenance are still required. The embodiment of the present invention realizes the overall evaluation of the health of the energy storage system through the above-mentioned energy storage system operation and maintenance method, and avoids the problem of inaccurate overall evaluation of the health of the energy storage system due to the problem of inconsistent battery cells.

[0185] Figure 10 This is a structural block diagram of an energy storage system operation and maintenance device provided by an embodiment of the present invention. Figure 10 As shown, the device includes:

[0186] The information acquisition module 21 is used to obtain and record the battery health status value of each battery cell in the energy storage system;

[0187] The dispersion calculation module 22 is used to calculate the data dispersion according to the battery health status value of each battery cell in the energy storage system;

[0188] The battery swap operation and maintenance module 23 is used to execute the battery swap operation and maintenance strategy when the data discreteness is not within a preset range.

[0189] Optionally, the information acquisition module 21 is specifically configured to obtain a battery health status value when each battery cell in the energy storage system is in the same battery loss state.

[0190] Optionally, the dispersion calculation module 22 is specifically used to determine the upper quartile Q1 and lower quartile Q3 of the battery health status values of all battery cells; and based on the upper quartile Q1 and lower quartile Q3, calculate the interquartile range IQR as the data dispersion.

[0191] Optionally, the dispersion calculation module 22 is further configured to determine a median M of the battery health status values of all battery cells when the data dispersion is within a preset discrete range, and use the median M as the battery health status value of the energy storage system.

[0192] Optionally, the battery swap operation and maintenance module 23 is specifically used to execute the battery swap operation and maintenance strategy when the data discreteness is within a preset discrete range and the value of the median M exceeds the preset range of the health value.

[0193] Optionally, the energy storage system operation and maintenance device also includes: an abnormal value processing module, wherein: the abnormal value processing module is used to determine whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system; and when there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, the abnormal value is eliminated.

[0194] Optionally, an abnormal value processing module is specifically used to determine that the battery health status value of any battery cell is an abnormal value when the battery health status value of the battery cell is outside the normal value judgment range; wherein the normal value judgment range is (Q1-k*IQR, Q3+k*IQR), and k is a preset constant; when the battery health status values of all battery cells are within the normal value judgment range, it is determined that there are no abnormal values in the battery health status values of each battery cell in the energy storage system.

[0195] Optionally, the abnormal value processing module is also used to determine whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value when there is an abnormal value in the battery health status value of each battery cell in the energy storage system; and when the abnormal value is a non-accidental abnormal value, call the battery replacement operation and maintenance module 23 to execute the battery replacement operation and maintenance strategy.

[0196] Optionally, the abnormal value processing module is further specifically used to obtain the "battery health status value-cycle number" curve of the battery cell corresponding to the abnormal value; when a preset number of battery health status values near the abnormal value in the "battery health status value-cycle number" curve are all within the normal value judgment range, the abnormal value is determined to be an accidental abnormal value; when a preset number of battery health status values near the abnormal value in the "battery health status value-cycle number" curve are all outside the normal value judgment range, the abnormal value is determined to be a non-accidental abnormal value.

[0197] The energy storage system operation and maintenance device provided in the embodiment of the present invention can execute the energy storage system operation and maintenance method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0198] Figure 11 is a structural diagram of an electronic device provided by an embodiment of the present invention, such as Figure 11 As shown, the electronic device includes:

[0199] at least one processor; and

[0200] a memory communicatively connected to at least one processor; wherein,

[0201] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the energy storage system operation and maintenance method of any embodiment of the present invention.

[0202] Figure 11 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0203] like Figure 11 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0204] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0205] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the energy storage system operation and maintenance method.

[0206] An embodiment of the present invention further provides a computer-readable storage medium storing computer instructions, which are used to enable a processor to implement the energy storage system operation and maintenance method of any embodiment of the present invention when executed.

[0207] In some embodiments, the energy storage system operation and maintenance method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the energy storage system operation and maintenance method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the energy storage system operation and maintenance method in any other appropriate manner (for example, by means of firmware).

[0208] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0209] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0210] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0211] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0212] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0213] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs that run on corresponding computers and have a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in a cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services. It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit them here.

[0214] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for operating and maintaining an energy storage system, characterized in that: include: Obtain the battery health status value of each battery cell in the energy storage system; Calculating data dispersion based on the battery health status value of each battery cell in the energy storage system; When the data discreteness exceeds the preset discrete range, the battery replacement operation and maintenance strategy is executed.

2. The energy storage system operation and maintenance method according to claim 1, characterized in that: The step of obtaining the battery health status value of each battery cell in the energy storage system includes: Obtaining a battery health status value when each of the battery cells in the energy storage system is in the same battery loss state.

3. The energy storage system operation and maintenance method according to claim 1, characterized in that: The step of calculating data dispersion according to the battery health status value of each battery cell in the energy storage system includes: Determine the upper quartile Q1 and lower quartile Q3 of the battery health status values of all battery cells; Based on the upper quartile Q1 and the lower quartile Q3, the interquartile range IQR is calculated as the data dispersion.

4. The energy storage system operation and maintenance method according to claim 1, characterized in that: After calculating the data dispersion based on the battery health status value of each battery cell in the energy storage system, the following steps are also included: When the data discreteness is within the preset discrete range, a median M of the battery health status values of all the battery cells is determined, and the median M is used as the battery health status value of the energy storage system.

5. The energy storage system operation and maintenance method according to claim 4, characterized in that: When the data discreteness is within the preset discrete range, determining a median M of the battery health status values of all battery cells, and using the median M as the battery health status value of the energy storage system, further comprising: When the data dispersion is within the preset dispersion range and the value of the median M is within the preset range of health values, the operation continues; When the data discreteness is within the preset discrete range and the value of the median M exceeds the preset range of the health value, the battery replacement operation and maintenance strategy is executed.

6. The energy storage system operation and maintenance method according to claim 3, characterized in that: Before calculating the data dispersion based on the battery health status value of each battery cell in the energy storage system, the following steps are also included: Determining whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system; When there is an abnormal value in the battery health status value of each battery cell in the energy storage system and the abnormal value is an accidental abnormal value, the abnormal value is eliminated.

7. The energy storage system operation and maintenance method according to claim 6, characterized in that: The determining whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system includes: When the battery health status value of any of the battery cells is outside the normal value judgment range, the battery health status value of the battery cell is determined to be an abnormal value; wherein the normal value judgment range is (Q1-k*IQR, Q3+k*IQR), where k is a preset constant; When the battery health status values of all the battery cells are within the normal value judgment range, it is determined that no abnormal value exists in the battery health status value of each battery cell in the energy storage system.

8. The energy storage system operation and maintenance method according to claim 7, characterized in that: After determining whether there is an abnormal value in the battery health status value of each battery cell in the energy storage system, the method further includes: When an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determining whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value; When the abnormal value is a non-accidental abnormal value, the battery replacement operation and maintenance strategy is executed.

9. The energy storage system operation and maintenance method according to claim 8, characterized in that: When an abnormal value exists in the battery health status value of each battery cell in the energy storage system, determining whether the abnormal value is an accidental abnormal value or a non-accidental abnormal value includes: Obtaining a "battery health status value-cycle number" curve of the battery cell corresponding to the abnormal value; When a preset number of battery health status values near the abnormal value in the "battery health status value-cycle number" curve are all within the normal value judgment range, determining that the abnormal value is an accidental abnormal value; When a preset number of battery health status values near the abnormal value in the "battery health status value-cycle number" curve are all outside the normal value judgment range, the abnormal value is determined to be a non-accidental abnormal value.

10. An energy storage system operation and maintenance device, characterized in that: include: An information acquisition module is used to obtain and record the battery health status value of each battery cell in the energy storage system; The dispersion calculation module is used to calculate the data dispersion based on the battery health status value of each battery cell in the energy storage system; The battery swap operation and maintenance module is used to execute the battery swap operation and maintenance strategy when the data discreteness is not within the preset range.

11. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the energy storage system operation and maintenance method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the energy storage system operation and maintenance method according to any one of claims 1 to 9 when executed.

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