A dynamic grouping charging and discharging scheduling method for cascade utilization of battery energy storage system

Abstract

The application discloses a kind of dynamic grouping charge-discharge scheduling methods of cascade utilization battery energy storage system, it is related to energy storage control technical field, including: obtaining initial characteristic parameter based on initial charge-discharge analysis;Grouping processing based on initial characteristic parameter;Based on the real-time charge-discharge parameters of all sets of retired batteries and grouping condition, dynamic scheduling is carried out between groups for retired batteries;The application is used to solve the problems in the prior art, such as lack of real-time feature checking and real-time grouping method based on the timing curve characteristics of retired batteries during charge-discharge in dynamic grouping charge-discharge scheduling of cascade utilization battery energy storage system, which causes poor adaptability and group solidification between groups during charge-discharge, resulting in the problem of declining consistency of batteries within the same group during operation.

Description

Technical Field

[0001] This invention relates to the field of energy storage control technology, specifically to a dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system. Background Technology

[0002] Second-life battery energy storage systems are recycling systems that utilize retired power batteries that have met automotive standards after testing, screening, and reorganization for use in the energy storage field. This is a mainstream solution for the high-value reuse of retired power batteries. The system typically uses retired lithium iron phosphate batteries, combined with containers and string energy storage converters to form a battery cabinet. Precise control is achieved through a battery management system and an energy management system to ensure the safe operation of the system.

[0003] Existing methods for dynamic grouping and charging / discharging scheduling in cascaded battery energy storage systems typically control the charging and discharging of battery packs based on their state of charge (SOC). When battery modules are connected in series, charging and discharging are usually controlled based on the SOC difference. While this improved method allows for dynamic management of battery energy in cascaded battery packs, it lacks a method for real-time feature verification and grouping based on the timing curves of retired batteries during charging and discharging. This results in fixed grouping and poor compatibility between groups during charging and discharging, leading to decreased consistency in battery operation within the same group and thus reducing the overall lifespan of the system. For example, patent application CN112134319A discloses an energy feedback cascaded battery charging / discharging... The discharge equalization system and its control method utilize the state of charge of the battery pack and the charge state difference between battery modules to control the bidirectional power conversion unit and the inverter group to charge or discharge the battery pack. Other improvements to the dynamic grouping charge and discharge scheduling method for cascaded battery energy storage systems are usually improvements in single parameter monitoring. In terms of dynamic grouping charge and discharge scheduling, there is still a lack of methods for real-time feature verification and real-time grouping based on the time-series curve characteristics of retired batteries during charge and discharge. This results in fixed grouping and poor adaptability between groups during charge and discharge, leading to decreased consistency of battery operation within the same group and reduced overall system lifespan. Therefore, it is necessary to improve the existing dynamic grouping charge and discharge scheduling method for cascaded battery energy storage systems. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by proposing a dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system. This method addresses the lack of a real-time feature verification and grouping method based on the time-series curve characteristics of retired batteries during charge and discharge in existing dynamic grouping charge and discharge scheduling methods for cascaded battery energy storage systems. This results in fixed grouping and poor adaptability between groups during charge and discharge, leading to decreased consistency of battery operation within the same group and thus reducing the overall service life of the system.

[0005] To achieve the above objectives, this application provides a dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system, comprising the following steps:

[0006] The initial charge-discharge analysis is performed on the retired batteries to be classified in the cascaded battery energy storage system, and the initial characteristic parameters of all retired batteries to be classified are obtained based on the results of the initial charge-discharge analysis.

[0007] Based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and a set containing retired batteries after grouping is obtained.

[0008] When dynamically scheduling retired batteries, dynamic scheduling between groups is performed based on the real-time charging and discharging parameters of retired batteries in all sets and the grouping conditions. The grouping conditions include conditions 1 to 8.

[0009] Furthermore, the initial charge-discharge analysis includes:

[0010] For any retired battery: After completely discharging the retired battery, charge the retired battery k times; during the charging process, collect the changes in SOC and operating current in the retired battery, and record them as charging SOC data and charging current data respectively.

[0011] After each retired battery is fully charged, it is discharged until all the charge inside is released. During the discharge process, the changes in the SOC and operating current of the retired battery are collected and recorded as discharge SOC data and discharge current data, respectively.

[0012] Furthermore, the initial charge-discharge analysis also includes:

[0013] A Cartesian coordinate system with the unit of min for the horizontal axis and the unit of % for the vertical axis is established and denoted as the SOC analysis coordinate system. Based on the charging SOC data during k charging processes, k SOC-time relationship curves are constructed in the SOC analysis coordinate system and denoted as charging SOC curves. The points with the largest and smallest slopes in the charging SOC curves are denoted as SOC charging peaks and SOC charging valleys, respectively. When there are multiple SOC charging peaks or multiple SOC charging valleys, only the SOC charging peak and SOC charging valley with the smallest horizontal axis are retained.

[0014] In the k charging SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging peaks is called the charging peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging valleys is called the charging valley interval.

[0015] Based on the charging SOC data during k discharge cycles, k SOC-time relationship curves are constructed in the SOC analysis coordinate system and denoted as discharge SOC curves. The points with the largest and smallest slopes in the discharge SOC curves are denoted as SOC discharge valleys and SOC discharge peaks, respectively. When there are multiple SOC discharge peaks or multiple SOC discharge valleys, only the SOC discharge peak and SOC discharge valley with the smallest abscissa are retained.

[0016] In the k discharge SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge peaks is denoted as the discharge peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge valleys is denoted as the discharge valley interval.

[0017] Furthermore, the initial charge-discharge analysis also includes:

[0018] Establish a Cartesian coordinate system with the horizontal axis in min and the vertical axis in A, and denote it as the current analysis coordinate system. Based on the charging current data during k charging processes, construct k current-time relationship curves in the current analysis coordinate system, and denote the curve obtained by fitting the k curves as the charging current curve. Based on the discharging current data during k discharging processes, construct k current-time relationship curves in the current analysis coordinate system, and denote the curve obtained by fitting the k curves as the discharging current curve.

[0019] For the charging current curve: the point corresponding to the peak and the point corresponding to the trough in the charging current curve are respectively recorded as the charging current peak point and the charging current trough point; the difference in the horizontal coordinate of adjacent charging current peak points is recorded as the peak point period, and the difference in the horizontal coordinate of adjacent charging current trough points is recorded as the trough point period; the interval formed by the minimum and maximum values ​​of the peak point periods obtained from all charging current peak points is recorded as the peak point period interval, and the interval formed by the minimum and maximum values ​​of the trough point periods obtained from all charging current trough points is recorded as the trough point period interval.

[0020] Furthermore, the initial charge-discharge analysis also includes:

[0021] For the discharge current curve: Based on the method of obtaining the peak point period interval and valley point period interval from the charging current curve, the peak point period interval and valley point period interval corresponding to the discharge current curve are obtained.

[0022] The peak charging interval, valley charging interval, peak discharging interval, valley discharging interval, peak period interval and valley period interval of the charging current curve, and peak period interval and valley period interval of the discharging current curve are recorded as the initial characteristic parameters of the retired battery.

[0023] Furthermore, based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, resulting in a set of retired batteries after grouping, including:

[0024] Construct T sets for placing retired batteries. Based on the initial characteristic parameters of all retired batteries, place all retired batteries into all sets. When all retired batteries have been placed into a set, delete the set that does not contain retired batteries.

[0025] For any set, all retired batteries in the set should simultaneously satisfy conditions 1, 2, 3, and 4, and satisfy any two of conditions 5, 6, 7, and 8.

[0026] Furthermore, based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and the resulting set containing retired batteries after grouping also includes:

[0027] For any two retired batteries α and β in the set, condition 1 is: the charging peak interval of retired battery α completely includes the charging peak interval of retired battery β, or the charging peak interval of retired battery β completely includes the charging peak interval of retired battery α.

[0028] Condition 2 is: the charging valley interval of retired battery α completely includes the charging valley interval of retired battery β, or the charging valley interval of retired battery β completely includes the charging valley interval of retired battery α.

[0029] Condition 3 is: the discharge peak interval of retired battery α completely includes the discharge peak interval of retired battery β, or the discharge peak interval of retired battery β completely includes the discharge peak interval of retired battery α.

[0030] Condition 4 is: the discharge valley interval of retired battery α completely includes the discharge valley interval of retired battery β, or the discharge valley interval of retired battery β completely includes the discharge valley interval of retired battery α.

[0031] Furthermore, based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and the resulting set containing retired batteries after grouping also includes:

[0032] Condition 5 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the charging current curve of retired battery β.

[0033] Condition 6 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the charging current curve of the retired battery α.

[0034] Condition 7 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the discharge current curve of retired battery β.

[0035] Condition 8 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the discharge current curve of the retired battery α.

[0036] Furthermore, when dynamically scheduling retired batteries, the dynamic scheduling between groups of retired batteries is performed based on the real-time charge and discharge parameters of retired batteries in all sets and the grouping conditions, including:

[0037] When all retired batteries are in a schedulable state, for any retired battery: the most recent charging data and discharging data of the retired battery are acquired in real time and recorded as real-time charging data and real-time discharging data, respectively.

[0038] Initial charge-discharge analysis was used to analyze real-time charging and discharging data. Based on the analysis results, the peak and valley ranges of charging, discharging, charging, and discharging, as well as the peak and valley period ranges of the charging current curve and the discharging current curve of the retired battery, were updated.

[0039] Furthermore, when dynamically scheduling retired batteries, the dynamic scheduling between groups of retired batteries, based on the real-time charge and discharge parameters and grouping conditions of retired batteries in all sets, also includes:

[0040] The latest charging peak point range, charging valley point range, discharging peak point range, discharging valley point range, peak point period range and valley point period range of the charging current curve, and peak point period range and valley point period range of the discharging current curve of the retired battery are recorded as the real-time characteristic parameters of the retired battery.

[0041] Based on the real-time characteristic parameters and grouping conditions of all retired batteries, all sets containing retired batteries are updated. When updating sets, it is allowed to add sets or delete sets that do not contain retired batteries.

[0042] The beneficial effects of this invention are as follows: This application first performs initial charge-discharge analysis on the retired batteries to be classified in the cascaded battery energy storage system. Based on the results of the initial charge-discharge analysis, the initial characteristic parameters of all retired batteries to be classified are obtained. The advantage of this is that by obtaining the initial characteristic parameters of all retired batteries through the initial charge-discharge analysis, the characteristics of the time-series curves of all retired batteries during charge and discharge can be analyzed, thereby obtaining the periodicity of each point in the time-series curve. This allows the retired batteries to be grouped based on the initial characteristic parameters in subsequent analysis, and the method of obtaining the initial characteristic parameters can be used to schedule the retired batteries in each group in real time, so as to avoid the problems of fixed grouping and poor adaptability between groups.

[0043] This application also groups all retired batteries to be classified based on the initial characteristic parameters of all retired batteries, and obtains a set containing retired batteries after grouping; finally, when dynamically scheduling retired batteries, dynamic scheduling between groups is performed based on the real-time charging and discharging parameters of retired batteries in all sets and grouping conditions. The advantage of this is that by performing dynamic scheduling between groups based on the real-time charging and discharging parameters of retired batteries in all sets and grouping conditions, it can be ensured that the real-time charging and discharging parameters of retired batteries in the same group are within the same range, so that they can operate at a nearly the same frequency and rate in all time periods during charging and discharging, thereby avoiding the problem of reduced overall system lifespan caused by inconsistent operation of batteries in the same group. Attached Figure Description

[0044] Figure 1 This is a flowchart of the steps of the method of the present invention;

[0045] Figure 2 This is a schematic diagram of the current analysis coordinate system of the present invention;

[0046] Figure 3 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1, please refer to Figure 1 As shown, this application provides a dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system, including the following steps:

[0049] Step S1: Perform initial charge-discharge analysis on the retired batteries to be classified in the cascaded battery energy storage system, and obtain the initial characteristic parameters of all retired batteries to be classified based on the results of the initial charge-discharge analysis.

[0050] The initial charge-discharge analysis includes: Step S101, for any retired battery: after completely discharging the battery, charge the battery k times; during the charging process, collect the changes in SOC and operating current in the retired battery, and record them as charging SOC data and charging current data respectively.

[0051] In the specific implementation process, in order to ensure that the initial characteristic parameters obtained after data analysis are more consistent with the parameter characteristics of SOC and charging current corresponding to the retired battery during charging and discharging, and to avoid the randomness of a single charge and discharge, k charging processes and k discharging processes are used to obtain the initial characteristic parameters in this embodiment. The value of k can be determined according to the analysis capability during actual data analysis. In this embodiment, the value of k is set to 5. That is, for the same retired battery, 5 charging processes are performed respectively, and a discharging process is performed after each charging process, so as to obtain 5 sets of charging SOC data, charging current data, discharging SOC data and discharging current data.

[0052] Step S102: After each time the retired battery is fully charged by the charging process, the retired battery is discharged until the power in the retired battery is completely discharged; during the discharge process, the changes in the SOC and operating current in the retired battery are collected and recorded as discharge SOC data and discharge current data, respectively.

[0053] The initial charge-discharge analysis also includes: step S103, establishing a Cartesian coordinate system with the unit of min on the horizontal axis and the unit of % on the vertical axis, and denoting it as the SOC analysis coordinate system; based on the charging SOC data during k charging processes, constructing k SOC-time relationship curves in the SOC analysis coordinate system, and denoting them as charging SOC curves; and denoting the points with the largest and smallest slopes in the charging SOC curves as SOC charging peaks and SOC charging valleys, respectively. When there are multiple SOC charging peaks or multiple SOC charging valleys, only the SOC charging peak and SOC charging valley with the smallest horizontal axis are retained.

[0054] In the data analysis of this embodiment, for example, in the process of analyzing a charging SOC curve, the SOC charging peak point and SOC charging valley point obtained are (12%, 15min) and (98%, 115min), respectively; in addition, by analyzing 5 charging SOC curves corresponding to the same retired battery, the charging peak point interval and charging valley point interval obtained are [5%, 20%] and [90%, 98%], respectively.

[0055] Step S104: In the k charging SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging peaks is recorded as the charging peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging valleys is recorded as the charging valley interval.

[0056] Step S105: Based on the charging SOC data during k discharge processes, construct k SOC-time relationship curves in the SOC analysis coordinate system, and record them as discharge SOC curves; record the points with the largest and smallest slopes in the discharge SOC curves as SOC discharge valleys and SOC discharge peaks, respectively. When there are multiple SOC discharge peaks or multiple SOC discharge valleys, only the SOC discharge peak and SOC discharge valley with the smallest abscissa are retained.

[0057] Step S106: In the k discharge SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge peaks is recorded as the discharge peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge valleys is recorded as the discharge valley interval.

[0058] In the data analysis of this embodiment, the analysis method of the discharge SOC curve is similar to that of the charging SOC curve. By analyzing the five discharge SOC curves corresponding to the same retired battery, the discharge peak point interval and discharge valley point interval are [10%, 20%] and [80%, 95%], respectively.

[0059] The initial charge-discharge analysis also includes: step S107, establishing a Cartesian coordinate system with the horizontal axis in min and the vertical axis in A, and denoting it as the current analysis coordinate system; based on the charging current data during k charging processes, constructing k current-time relationship curves in the current analysis coordinate system, and denoting the curve obtained by fitting the k curves as the charging current curve; based on the discharging current data during k discharging processes, constructing k current-time relationship curves in the current analysis coordinate system, and denoting the curve obtained by fitting the k curves as the discharging current curve;

[0060] In practical implementation, % represents percentage, A represents current, "unit is %" means the unit of the coordinate axis is percentage, "unit is A" means the unit of the coordinate axis is current; SOC = State of Charge, which refers to the battery's state of charge, indicating the percentage of remaining battery capacity;

[0061] Step S108: For the charging current curve: the points corresponding to the peaks and the points corresponding to the troughs in the charging current curve are respectively recorded as the charging current peak point and the charging current valley point; the difference in the abscissa of adjacent charging current peak points is recorded as the peak point period, and the difference in the abscissa of adjacent charging current valley points is recorded as the valley point period; the interval formed by the minimum and maximum values ​​of the peak point periods obtained from all charging current peak points is recorded as the peak point period interval, and the interval formed by the minimum and maximum values ​​of the valley point periods obtained from all charging current valley points is recorded as the valley point period interval.

[0062] In the data analysis of this embodiment, for example, after fitting five current-time relationship curves constructed based on charging current data, a portion of the resulting charging current curve is as follows: Figure 2 The curve CL in the figure is shown; Figure 2 This is a schematic diagram of the current analysis coordinate system of the present invention. The horizontal axis (X-axis) of the current analysis coordinate system has a unit of min, and the vertical axis (Y-axis) has a unit of A. Through the analysis of... Figure 2 Analysis of the CL curve shows that the maximum and minimum values ​​of the abscissa difference between adjacent charging current peaks are 0.47 and 0.35, respectively, and the maximum and minimum values ​​of the abscissa difference between adjacent charging current valleys are 0.43 and 0.32, respectively. Therefore, the peak period interval and valley period interval obtained from the CL curve are [0.35, 0.47] and [0.32, 0.43], respectively.

[0063] The initial charge and discharge analysis also includes: step S109, for the discharge current curve: based on the method of obtaining the peak period interval and valley period interval from the charging current curve, obtain the peak period interval and valley period interval corresponding to the discharge current curve.

[0064] Step S110: The charging peak interval, charging valley interval, discharging peak interval, discharging valley interval, peak period interval and valley period interval of the charging current curve, and peak period interval and valley period interval of the discharging current curve are recorded as the initial characteristic parameters of the retired battery.

[0065] In the specific implementation process, by acquiring the charging peak point interval, charging valley point interval, discharging peak point interval, discharging valley point interval, peak point period interval and valley point period interval of the charging current curve, and the discharging current curve of all retired batteries, and using them as initial characteristic parameters, it can be ensured that after all batteries are grouped in the subsequent process, all retired batteries in the same set can operate at a more consistent charging and discharging rate at the same charging and discharging time. This ensures that the real-time charging and discharging parameters of retired batteries in the same group are within the same range, and that they can operate at a nearly identical frequency and rate in all time periods during charging and discharging, so as to achieve synchronous operation of all batteries in the same group during charging and discharging.

[0066] Step S2: Based on the initial feature parameters of all retired batteries, group all retired batteries to be classified into groups, and obtain a set containing retired batteries after grouping.

[0067] Step S2 includes: Step S201, constructing T sets for placing retired batteries, and placing all retired batteries into all sets based on the initial characteristic parameters of all retired batteries; when all retired batteries have been placed into a set, the set that does not contain retired batteries is deleted;

[0068] In the actual implementation process, since it is impossible to predict how many types of sets all retired batteries can form, the value of T can be set before grouping retired batteries, and additional sets can be added as needed; in the data analysis of this embodiment, the value of T is set to 20;

[0069] Step S202: For any set, all retired batteries in the set should simultaneously satisfy conditions 1, 2, 3 and 4, and satisfy any two of conditions 5, 6, 7 and 8.

[0070] Step S2 also includes: Step S203, for any two retired batteries α and retired batteries β in the set, condition 1 is: the charging peak point interval of retired battery α completely includes the charging peak point interval of retired battery β, or the charging peak point interval of retired battery β completely includes the charging peak point interval of retired battery α.

[0071] Condition 2 is: the charging valley interval of retired battery α completely includes the charging valley interval of retired battery β, or the charging valley interval of retired battery β completely includes the charging valley interval of retired battery α.

[0072] Condition 3 is: the discharge peak interval of retired battery α completely includes the discharge peak interval of retired battery β, or the discharge peak interval of retired battery β completely includes the discharge peak interval of retired battery α.

[0073] Condition 4 is: the discharge valley interval of retired battery α completely includes the discharge valley interval of retired battery β, or the discharge valley interval of retired battery β completely includes the discharge valley interval of retired battery α.

[0074] Condition 5 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the charging current curve of retired battery β.

[0075] Condition 6 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the charging current curve of the retired battery α.

[0076] Condition 7 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the discharge current curve of retired battery β.

[0077] Condition 8 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the discharge current curve of the retired battery α.

[0078] In the data analysis of this embodiment, for example, the two retired batteries α and β obtained through the above analysis, wherein the charging peak point interval and charging valley point interval of retired battery α are [5%, 20%] and [90%, 98%], respectively, and the discharging peak point interval and discharging valley point interval are [10%, 20%] and [80%, 95%], respectively; the charging peak point interval and charging valley point interval of retired battery β are [10%, 18%] and [92%, 95%], respectively, and the discharging peak point interval and discharging valley point interval are [12%, 16%] and [85%, 95%], respectively; through analysis, it can be found that retired batteries α and β simultaneously satisfy conditions 1, 2, 3, and 4; in addition, the peak point period interval and valley point period interval of the charging current curve corresponding to retired battery α are also consistent. The period intervals are [0.35, 0.47] and [0.32, 0.43], respectively. The peak period interval and valley period interval of the charging current curve corresponding to retired battery β are [0.33, 0.48] and [0.35, 0.4], respectively. Through analysis, it can be found that the interval lengths corresponding to the peak period interval and valley period interval of retired battery α are 0.12 and 0.11, respectively, and the interval lengths corresponding to the peak period interval and valley period interval of retired battery β are 0.15 and 0.05, respectively. Through calculation, it can be found that the average value of the interval length of the peak period interval and valley period interval corresponding to retired battery β is 0.1, and it is within the peak period interval length and valley period interval length of retired battery α. Therefore, retired batteries α and β satisfy condition 6.

[0079] In the specific implementation process, conditions 1 to 4 can be used to judge the similarity of the changes in SOC during charging and discharging between retired batteries. If two retired batteries can simultaneously meet conditions 1 to 4, it means that the two retired batteries are roughly the same in terms of the rate of change during charging and discharging. Conditions 6 to 8 can be used to judge the similarity of the changes in charging current during charging and discharging between retired batteries. If two retired batteries can simultaneously meet at least two of conditions 6 to 8, it means that the changes in the charging current used by the two retired batteries during charging and discharging are roughly the same.

[0080] Step S3: When dynamically scheduling retired batteries, dynamic scheduling between groups is performed based on the real-time charging and discharging parameters of retired batteries in all sets and the grouping conditions. The grouping conditions include conditions 1 to 8.

[0081] Step S3 includes: Step S301, when all retired batteries are in a schedulable state, for any retired battery: obtain the most recent charging data and discharging data of the retired battery in real time, and record them as real-time charging data and real-time discharging data respectively;

[0082] Step S302: Use initial charge and discharge analysis to analyze real-time charging data and real-time discharge data, and update the charging peak interval, charging valley interval, discharging peak interval, discharging valley interval, peak period interval and valley period interval of charging current curve and peak period interval and valley period interval of discharging current curve of retired battery based on the analysis results.

[0083] Step S3 also includes: Step S303, recording the latest charging peak interval, charging valley interval, discharging peak interval, discharging valley interval, peak period interval and valley period interval of the charging current curve and peak period interval and valley period interval of the discharging current curve as the real-time characteristic parameters of the retired battery.

[0084] Step S304: Based on the real-time characteristic parameters and grouping conditions of all retired batteries, update all sets containing retired batteries. When updating the sets, it is allowed to add sets or delete sets that do not contain retired batteries.

[0085] Example 2, please refer to Figure 3 As shown, Figure 3 A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps as described in a dynamic grouping charge-discharge scheduling method for a cascaded battery energy storage system to achieve the following functions: First, an initial charge-discharge analysis is performed on the retired batteries to be classified in the cascaded battery energy storage system. Based on the results of the initial charge-discharge analysis, initial characteristic parameters of all retired batteries to be classified are obtained. Then, based on the initial characteristic parameters of all retired batteries, all retired batteries to be classified are grouped to obtain a set containing retired batteries after grouping. Finally, when dynamically scheduling the retired batteries, dynamic scheduling between groups is performed based on the real-time charge-discharge parameters of the retired batteries in all sets and the grouping conditions.

[0086] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a dynamic grouping charge-discharge scheduling method for a cascaded battery energy storage system provided by the above methods. The method includes: firstly, performing an initial charge-discharge analysis on the retired batteries to be classified in the cascaded battery energy storage system, and obtaining initial characteristic parameters of all retired batteries to be classified based on the results of the initial charge-discharge analysis; then, grouping all retired batteries to be classified based on the initial characteristic parameters of all retired batteries, and obtaining a set containing retired batteries after grouping; finally, when dynamically scheduling retired batteries, performing dynamic scheduling between groups of retired batteries based on the real-time charge-discharge parameters of retired batteries in all sets and grouping conditions.

[0088] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of the above-described dynamic grouping charge-discharge scheduling method for a cascaded battery energy storage system to achieve the following functions: First, it performs an initial charge-discharge analysis on the retired batteries to be classified in the cascaded battery energy storage system, and obtains the initial characteristic parameters of all retired batteries to be classified based on the results of the initial charge-discharge analysis; then, it groups all retired batteries to be classified based on the initial characteristic parameters of all retired batteries, and obtains a set containing retired batteries after grouping; finally, when dynamically scheduling retired batteries, it performs dynamic scheduling between groups based on the real-time charge-discharge parameters of retired batteries in all sets and the grouping conditions.

[0089] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0090] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system, characterized in that, Includes the following steps: The initial charge-discharge analysis is performed on the retired batteries to be classified in the cascaded battery energy storage system, and the initial characteristic parameters of all retired batteries to be classified are obtained based on the results of the initial charge-discharge analysis. Based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and a set containing retired batteries after grouping is obtained. When dynamically scheduling retired batteries, dynamic scheduling between groups is performed based on the real-time charging and discharging parameters of retired batteries in all sets and the grouping conditions. The grouping conditions include conditions 1 to 8. The initial charge-discharge analysis includes: For any retired battery: After completely discharging the battery, charge it k times; during charging, collect data on the changes in SOC and operating current, recording them as charging SOC data and charging current data, respectively; after each full charge, discharge the battery until it is completely depleted; during discharging, collect data on the changes in SOC and operating current, recording them as discharging SOC data and discharging current data, respectively; analyze the charging SOC data, charging current data, discharging SOC data, and discharging current data. When dynamically scheduling retired batteries, the dynamic scheduling between groups of retired batteries is based on the real-time charging and discharging parameters and grouping conditions of retired batteries in all sets. This includes: when all retired batteries are in a schedulable state, for any retired battery: the most recent charging and discharging data of the retired battery are acquired in real time and recorded as real-time charging data and real-time discharging data, respectively; the real-time charging data and real-time discharging data are analyzed using initial charge and discharge analysis, and the peak point interval, valley point interval, peak point interval, valley point interval, peak point period interval, and valley point period interval of the charging current curve and the peak point period interval and valley point period interval of the discharging current curve of the retired battery are updated based on the analysis results.

2. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 1, characterized in that, The initial charge-discharge analysis also includes: establishing a Cartesian coordinate system with the unit of min on the horizontal axis and the unit of % on the vertical axis, and denoting it as the SOC analysis coordinate system; based on the charging SOC data during k charging processes, constructing k SOC-time relationship curves in the SOC analysis coordinate system, and denoting them as charging SOC curves; and denoting the points with the largest and smallest slopes in the charging SOC curves as SOC charging peaks and SOC charging valleys, respectively. When there are multiple SOC charging peaks or multiple SOC charging valleys, only the SOC charging peak and SOC charging valley with the smallest horizontal axis are retained. In the k charging SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging peaks is called the charging peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC charging valleys is called the charging valley interval. Based on the charging SOC data during k discharge cycles, k SOC-time relationship curves are constructed in the SOC analysis coordinate system and denoted as discharge SOC curves. The points with the largest and smallest slopes in the discharge SOC curves are denoted as SOC discharge valleys and SOC discharge peaks, respectively. When there are multiple SOC discharge peaks or multiple SOC discharge valleys, only the SOC discharge peak and SOC discharge valley with the smallest abscissa are retained. In the k discharge SOC curves, the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge peaks is denoted as the discharge peak interval, and the closed interval formed by the minimum and maximum values ​​of the ordinates of all SOC discharge valleys is denoted as the discharge valley interval.

3. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 2, characterized in that, The initial charge-discharge analysis also includes: establishing a Cartesian coordinate system with the horizontal axis in min and the vertical axis in A, denoted as the current analysis coordinate system; based on the charging current data during k charging cycles, constructing k current-time relationship curves within the current analysis coordinate system, and recording the curve obtained by fitting the k curves as the charging current curve; based on the discharging current data during k discharging cycles, constructing k current-time relationship curves within the current analysis coordinate system, and recording the curve obtained by fitting the k curves as the discharging current curve; For the charging current curve: the point corresponding to the peak and the point corresponding to the trough in the charging current curve are respectively recorded as the charging current peak point and the charging current trough point; the difference in the horizontal coordinate of adjacent charging current peak points is recorded as the peak point period, and the difference in the horizontal coordinate of adjacent charging current trough points is recorded as the trough point period; the interval formed by the minimum and maximum values ​​of the peak point periods obtained from all charging current peak points is recorded as the peak point period interval, and the interval formed by the minimum and maximum values ​​of the trough point periods obtained from all charging current trough points is recorded as the trough point period interval.

4. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 3, characterized in that, The initial charge-discharge analysis also includes: for the discharge current curve: based on the method of obtaining the peak period interval and valley period interval from the charging current curve, the peak period interval and valley period interval corresponding to the discharge current curve are obtained; The peak charging interval, valley charging interval, peak discharging interval, valley discharging interval, peak period interval and valley period interval of the charging current curve, and peak period interval and valley period interval of the discharging current curve are recorded as the initial characteristic parameters of the retired battery.

5. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 4, characterized in that, Based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and the resulting set containing retired batteries includes: Construct T sets for placing retired batteries. Based on the initial characteristic parameters of all retired batteries, place all retired batteries into all sets. When all retired batteries have been placed into a set, delete the set that does not contain retired batteries. For any set, all retired batteries in the set should simultaneously satisfy conditions 1, 2, 3, and 4, and satisfy any two of conditions 5, 6, 7, and 8.

6. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 5, characterized in that, Based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and the resulting set containing retired batteries after grouping also includes: For any two retired batteries α and β in the set, condition 1 is: the charging peak interval of retired battery α completely includes the charging peak interval of retired battery β, or the charging peak interval of retired battery β completely includes the charging peak interval of retired battery α. Condition 2 is: the charging valley interval of retired battery α completely includes the charging valley interval of retired battery β, or the charging valley interval of retired battery β completely includes the charging valley interval of retired battery α. Condition 3 is: the discharge peak interval of retired battery α completely includes the discharge peak interval of retired battery β, or the discharge peak interval of retired battery β completely includes the discharge peak interval of retired battery α. Condition 4 is: the discharge valley interval of retired battery α completely includes the discharge valley interval of retired battery β, or the discharge valley interval of retired battery β completely includes the discharge valley interval of retired battery α.

7. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 6, characterized in that, Based on the initial feature parameters of all retired batteries, all retired batteries to be classified are grouped, and the resulting set containing retired batteries after grouping also includes: Condition 5 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the charging current curve of retired battery β. Condition 6 is: the average length of the peak period interval and the valley period interval of the charging current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the charging current curve of the retired battery α. Condition 7 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to retired battery α is simultaneously within the peak period interval and the valley period interval of the discharge current curve of retired battery β. Condition 8 is: the average length of the peak period interval and the valley period interval of the discharge current curve corresponding to the retired battery β is simultaneously within the peak period interval and the valley period interval of the discharge current curve of the retired battery α.

8. The dynamic grouping charge and discharge scheduling method for a cascaded battery energy storage system according to claim 7, characterized in that, When dynamically scheduling retired batteries, the dynamic scheduling between groups of retired batteries also includes recording the latest charging peak interval, charging valley interval, discharging peak interval, discharging valley interval, peak period interval and valley period interval of the charging current curve and the peak period interval and valley period interval of the discharging current curve as the real-time characteristic parameters of the retired batteries. Based on the real-time characteristic parameters and grouping conditions of all retired batteries, all sets containing retired batteries are updated. When updating sets, it is allowed to add sets or delete sets that do not contain retired batteries.

Images