Energy storage system charging and discharging power hierarchical control method based on lithium ion characteristics

Abstract

The invention discloses an energy storage system charging and discharging power hierarchical control method based on lithium ion characteristics. The method comprises the steps that energy storage system power control is divided into a system monitoring layer, a state evaluation layer and a power regulation and control layer; the monitoring layer collects the charging and discharging power of each battery pack and stores into a database; the evaluation and judgment module judges whether the state of the battery pack needs to be evaluated or not by analyzing the correlation coefficient of the power curve and calculating a power deviation value P I; if evaluation is needed, the state evaluation layer constructs a state evaluation model by using a support vector machine algorithm, outputs an aging degree value and judges linear correlation in combination with a power deviation value, and if linear correlation exists, the power regulation and control layer enters regulation and control, constructs a battery aging sequence, calculates charging and discharging upper limit power and regulates and controls the charging and discharging upper limit power. The invention further relates to a related control system, computer equipment and a storage medium, the power of the energy storage system can be effectively managed, and the system performance and stability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power control, and in particular to a hierarchical control method for charging and discharging power of an energy storage system based on lithium ion characteristics. Background Art

[0002] In the modern energy field, energy storage systems play a vital role in ensuring the stability and reliability of power systems. However, there are some problems with lithium-ion batteries during the charging and discharging process. If they cannot be effectively controlled, they will have an adverse effect on the overall performance and life of the battery pack.

[0003] Existing technologies are not detailed and comprehensive enough in monitoring the charging and discharging power of battery packs, and lack systematic hierarchical management. For example, in terms of battery status assessment, there is a lack of accurate and effective models and methods. Many existing technologies only rely on a single indicator or a simple empirical formula to judge the health of the battery, which makes it difficult to fully and accurately reflect the actual degree of battery aging and performance changes. For example, some methods only consider the battery capacity attenuation, ignoring the impact of internal resistance changes on the battery status, resulting in large deviations in the evaluation results.

[0004] Existing technologies lack flexibility in power regulation. When the battery pack experiences power deviation changes, they cannot be precisely regulated according to the actual aging degree of the battery and the power deviation, and cannot effectively balance the relationship between the battery pack's efficiency and life extension. For example, some regulation strategies use fixed thresholds or simple rules, which cannot adapt to the diverse needs of different battery packs at different stages of use, and can easily cause overcharging, over-discharging or overuse of the battery, further accelerating battery aging and reducing the overall performance and reliability of the energy storage system.

[0005] To this end, the present invention provides a stratified control method for charging and discharging power of an energy storage system based on lithium ion characteristics. Summary of the invention

[0006] The object of the present invention is to provide a hierarchical control method for charge and discharge power of an energy storage system based on lithium ion characteristics, so as to solve at least one of the above-mentioned problems of the prior art.

[0007] In a first aspect, the present invention provides a method for controlling the charging and discharging power of an energy storage system based on the characteristics of lithium ions, comprising:

[0008] Based on the characteristics of lithium-ion energy storage systems, the power control of the energy storage system is divided into: system monitoring layer, state assessment layer, and power regulation layer. Based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is obtained, and the collected charging and discharging power data is stored in the database;

[0009] Obtain the charging and discharging power of each battery pack from the database, draw a curve for analysis, obtain the correlation coefficient of the curve, perform numerical calculation on the correlation coefficient of the charging and discharging power curve, obtain the power deviation value PI, and determine whether the battery pack status needs to be evaluated based on the power deviation value PI;

[0010] If the status of the battery pack needs to be evaluated, the energy storage system is in the status evaluation layer. The historical charging power and discharging power data of each battery pack in the energy storage system and the dynamic internal resistance of each battery pack are obtained to establish a status evaluation model, and the aging degree value of each battery pack is output. The power deviation value is combined for fitting analysis to obtain the fitting approximation ratio. Based on the fitting approximation ratio, it is determined whether the aging degree value - power deviation value presents a linear growth trend;

[0011] If the aging degree value - power deviation value shows a linear growth trend, the power control of the energy storage system enters the power regulation layer, and a battery aging sequence is constructed based on the aging degree value. The charging and discharging power of the battery pack in the battery aging sequence is numerically analyzed to obtain the upper limit charging power and the upper limit discharging power. Based on the upper limit charging power and the upper limit discharging power, the energy storage inverter is used to regulate the charging and discharging power of the battery pack.

[0012] In a second aspect, the present invention provides a hierarchical control system for charging and discharging power of an energy storage system based on the characteristics of lithium ions, including: a data acquisition module: based on the characteristics of the lithium ion energy storage system, the power control of the energy storage system is divided into a system monitoring layer, a state evaluation layer, and a power regulation layer; based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is obtained, and the collected charging and discharging power data is stored in a database;

[0013] Evaluation and judgment module: obtain the charging and discharging power of each battery pack from the database, draw a curve for analysis, obtain the correlation coefficient of the curve, perform numerical calculation on the correlation coefficient of the charging and discharging power curve, obtain the power deviation value PI, and judge whether the battery pack status needs to be evaluated based on the power deviation value PI;

[0014] Evaluation and analysis module: If the status of the battery pack needs to be evaluated, the energy storage system is in the status evaluation layer, and the historical charging power and discharging power data of each battery pack in the energy storage system and the dynamic internal resistance of each battery pack are obtained to establish a status evaluation model, and the aging degree value of each battery pack is output, and a fitting analysis is performed in combination with the power deviation value to obtain the fitting approximation ratio. Based on the fitting approximation ratio, it is determined whether the aging degree value - power deviation value shows a linear growth trend;

[0015] Power control module: If the aging degree value - power deviation value shows a linear growth trend, the power control of the energy storage system enters the power control layer, and a battery aging sequence is constructed based on the aging degree value. The charging and discharging power of the battery pack in the battery aging sequence is numerically analyzed to obtain the upper limit charging power and the upper limit discharging power. Based on the upper limit charging power and the upper limit discharging power, the energy storage inverter is used to control the charging and discharging power of the battery pack.

[0016] Beneficial effects of the present invention:

[0017] 1. The system monitoring layer accurately collects the charging and discharging power data of each battery pack, providing a rich and accurate information basis for subsequent analysis. The state assessment layer is based on the support vector machine algorithm, integrating historical charging power, discharging power data and dynamic internal resistance multi-dimensional information to build a state assessment model, so as to more comprehensively evaluate the aging value of the battery pack.

[0018] 2. Through the power control layer, according to the relationship between the aging degree value and the power deviation value, the battery packs with power deviation exceeding the threshold in the battery aging sequence are regulated, the upper limit power of charging and the upper limit power of discharging are calculated, and the upper limit power of battery packs with a larger degree of aging is reduced, thereby extending the overall service life of the battery pack as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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.

[0020] Figure 1 is a flow chart of a power acquisition and determination method provided in Embodiment 1 of the present invention;

[0021] Figure 2 is a flow chart of state assessment and function control provided by Embodiment 2 of the present invention;

[0022] Figure 3 is a schematic diagram of the structure of a computer device provided by Embodiment 4 of the present invention; DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0024] Embodiment 1

[0025] Figure 1 This is a flow chart of a method for obtaining charging and discharging power provided in Embodiment 1 of the present invention. The embodiment of the present invention can be applicable to the case of power stratification control of an energy storage system. The energy storage system power control method can be executed by a stratified charging and discharging power control system for an energy storage system based on lithium-ion characteristics. The stratified charging and discharging power control system for an energy storage system based on lithium-ion characteristics can be implemented by software or hardware. The stratified charging and discharging power control system for an energy storage system based on lithium-ion characteristics can be configured in a computer device.

[0026] Step 1: Based on the characteristics of the lithium-ion energy storage system, the power control of the energy storage system is divided into three levels: system monitoring layer, state assessment layer, and power regulation layer. Based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is obtained, and the collected charging and discharging power data is stored in the database;

[0027] Based on the characteristics of lithium-ion energy storage systems, the power control of energy storage systems is divided into multiple levels, including: system monitoring layer, state assessment layer, and power regulation layer;

[0028] It should be noted that during the charging and discharging process of lithium-ion batteries, if the power varies greatly from the target value, it will affect the overall performance and life of the battery pack. The system monitoring layer, state evaluation layer, and power control layer are divided into multiple levels to monitor, evaluate, and control the power of the energy storage battery; the system monitoring layer is used to collect the power changes of the energy storage system during charging and discharging, the state evaluation layer is used to evaluate the aging degree of each battery pack in the energy storage system, and the power control layer is used to adjust the power during charging and discharging;

[0029] Based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is acquired at fixed intervals, and the acquired charging and discharging power data is stored in the database;

[0030] In some embodiments, a multi-channel power quality analyzer is selected as a power meter, and the power meter can collect the voltage and current values ​​of multiple battery packs during charging and discharging, and obtain the charging and discharging power by multiplying the voltage and current;

[0031] Exemplarily, the power meter collects the charging power of the battery pack 1 every 5 minutes. For example, the charging power at 8:00 is 101.13 W, the charging power at 8:05 is 105.36 W, ..., the charging power at 8:45 is 0.81 W, until the power required to fully charge the battery is reached, and the charging power measurement is stopped;

[0032] Step 2: Obtain the charging and discharging power of each battery pack from the database, draw a curve for analysis, obtain the correlation coefficient of the curve, perform numerical calculation on the correlation coefficient of the charging and discharging power curve, obtain the power deviation value PI, and determine whether it is necessary to evaluate the status of the battery pack based on the power deviation value PI;

[0033] In some embodiments, a power meter is used to collect the charging power and discharging power of the energy storage system at fixed intervals, and the charging power collected by the power meter is input into MatLab software to draw a time-charging power change curve and a time-discharging power change curve;

[0034] Use the correlation coefficient function of MatLab to analyze the overlap between the time-charging power curve and the charging target curve, and get the curve correlation coefficient.

[0035] It should be noted that the correlation coefficient function of MatLab is used to determine the degree of overlap between the time-charging power change curve and the charging target curve. The correlation coefficient function will return a correlation coefficient matrix, in which the elements on the diagonal are the correlation coefficients of the two curves. The closer the correlation coefficient is to 1, the higher the degree of overlap; the closer it is to 0, the lower the degree of overlap.

[0036] The time-charging power variation curve and the charging target curve have the same other interfering factors, that is, the ambient temperature and grid input voltage are the same. The charging target curve is obtained by professional technicians in this field based on the historical charging data of the energy storage device;

[0037] Divide the time-charging power variation curve into multiple sub-segments, and obtain the correlation coefficient of each sub-segment;

[0038] The correlation coefficient is compared with a correlation coefficient threshold, and if the correlation coefficient is higher than the correlation coefficient threshold, the sub-segment is marked as a close segment;

[0039] If the correlation coefficient in the sub-segment of the acquisition time-charging power variation curve is lower than the correlation coefficient threshold, no processing is performed;

[0040] Obtain the number of all approach sections and the number of sub-sections, perform ratio processing on the number of approach sections and the number of sub-sections to obtain the approach section ratio of the charging curve, and mark the approach section ratio as Jq;

[0041] Perform difference processing on the correlation coefficient in the close section and the correlation coefficient threshold to obtain the correlation coefficient difference;

[0042] The correlation coefficient difference is processed by ratio with the correlation coefficient threshold to obtain the correlation proximity ratio;

[0043] Obtain the relevant proximity ratios of all the proximity sections, sum and average the relevant proximity ratios of all the proximity sections to obtain the correlation ratio mean, and mark the correlation ratio mean as Xg;

[0044] Based on the close section ratio Jq and the correlation ratio mean Xg, the curve matching degree Pd of the time-discharge power change curve is calculated;

[0045] The curve matching degree Pd is obtained by the formula: Pd = a*Jq + b*Xg, where a = 0.213, b = 0.787;

[0046] Based on the curve matching degree calculation method of the time-charging power change curve, the curve matching degree Pd of the time-discharging power change curve is obtained, and the curve matching degree of the time-discharging power change curve is marked as Fd;

[0047] Based on the curve matching degree Pd of the time-discharge power change curve and the curve matching degree Fd of the time-discharge power change curve, the power deviation value PI is calculated;

[0048] By formula: Obtain the power deviation value PI, where c=0.483, d=0.517;

[0049] Compare the power deviation value PI with the power deviation threshold to determine whether the state of the battery pack needs to be evaluated;

[0050] If the power deviation value PI ≥ the power deviation threshold, it indicates that the time-charging power variation curve and the time-discharging power variation curve of the battery pack deviate greatly from the corresponding target curve, and the battery pack status needs to be evaluated;

[0051] If the power deviation value PI is less than the power deviation threshold, it indicates that the deviation between the time-charging power variation curve and the time-discharging power variation curve of the battery pack and the corresponding target curve is within the expected range. It is not necessary to evaluate the status of the battery pack, but it is still necessary to continuously monitor the change of the power deviation value PI.

[0052] Exemplarily, the lithium-ion energy storage system includes three battery groups, which are marked as battery group 1, battery group 2, and battery group 3 respectively; taking the charging power of battery group 1 as an example, the charging power is collected every 5 minutes from 9:00 to 9:30, and the charging power data is [100.51, 103.36, 105.72, 108.48, 110.23, 113.15, 116.09], in watts (W). The input power curve is drawn by MatLab software, and the proximity section ratio Jq is calculated to be 0.50, the correlation ratio mean Xg is 0.213, and the curve matching degree Pd of the charging power is calculated to be 0.269. If the curve matching degree Fd of the discharge power is 0.201, the power deviation value PI is 0.945, and the power deviation threshold is 0.8. The power deviation value PI of battery group 1 is higher than the power deviation threshold, and the state of battery group 1 needs to be evaluated;

[0053] The technical solution of this embodiment is: based on the characteristics of the lithium-ion energy storage system, the power control of the energy storage system is divided into a system monitoring layer, a state evaluation layer, and a power regulation layer, the charging and discharging power of each battery pack in the energy storage system is obtained, the collected charging and discharging power data is stored in a database, the charging and discharging power of each battery pack is obtained from the database, and a curve is drawn for analysis to obtain the correlation coefficient of the curve, the correlation coefficient of the charging and discharging power curve is numerically calculated to obtain a power deviation value PI, and based on the power deviation value PI, it is determined whether it is necessary to evaluate the state of the battery pack;

[0054] Embodiment 2

[0055] Based on the first embodiment, the energy storage system charge and discharge power hierarchical control method based on the lithium ion characteristics of the present invention also includes:

[0056] Step 3: If the status of the battery pack needs to be evaluated, the energy storage system is in the status evaluation layer, and the historical charging power, discharging power data, and dynamic internal resistance of each battery pack in the energy storage system are obtained. A status evaluation model is established, and the aging degree value of each battery pack is output. A fitting analysis is performed in combination with the power deviation value to obtain a fitting approximation ratio. Based on the fitting approximation ratio, it is determined whether the aging degree value - power deviation value presents a linear growth trend.

[0057] The energy storage system is in the state assessment layer, obtaining the historical charging power, discharging power data, and dynamic internal resistance of each battery pack in the energy storage system;

[0058] The specific method of obtaining the internal resistance of the battery pack is:

[0059] Based on the voltage and current values ​​collected by the power meter, Ohm's law Obtain the dynamic internal resistance R of each battery pack, where U is the collected voltage value of the battery pack, and I is the collected current value of the battery pack;

[0060] It should be noted that, since the voltage and voltage value of the battery pack collected at fixed intervals have multiple data values, the internal resistance calculated by the Ohm's law formula also has multiple data values. Therefore, the internal resistance of each battery pack is dynamic;

[0061] Based on the historical charging power and discharging power data of each battery pack in the energy storage system and the dynamic internal resistance of each battery pack, a state assessment model of the battery pack in the energy storage system is constructed using the support vector machine algorithm. Based on the state assessment model, the aging degree value of each battery pack is output;

[0062] The specific construction method of the state assessment model is as follows:

[0063] S1. Take the historical charging power, discharging power data of each battery pack, and the dynamic internal resistance of each battery pack as a data set, and perform data preprocessing on the data set, including: removing outliers in the data set and filling in missing values;

[0064] It should be noted that the data in the dataset is divided into three columns according to the historical charging power, discharging power data, and the dynamic internal resistance of each battery pack. The mean and standard deviation of each column of data are calculated, and the data that deviates from the mean of each column of data by ±3 times the standard deviation is regarded as an outlier and the corresponding data is removed; the missing data in each column is filled according to the mean;

[0065] S2, divide the data set into a training set and a test set in a ratio of 8:2, use the training set to train using the linear support vector machine algorithm, and the test set to verify the training results of the model;

[0066] It should be noted that the support vector machine model is trained using the training set data, with the historical charging power, discharging power and dynamic internal resistance data in the training set as input features, and the corresponding battery pack aging degree values ​​as output labels. During the training process, the support vector machine algorithm will find an optimal hyperplane based on the input features and output labels, so that battery pack data with different aging degrees can be classified;

[0067] S3, the state assessment model outputs the aging degree value of each battery pack in the energy storage system;

[0068] Based on the aging degree value of the battery pack output by the state model and the power deviation value PI of each battery pack, a scatter plot of the aging degree value of the battery pack - the power deviation value is drawn in a two-dimensional rectangular coordinate system with the aging degree value on the horizontal axis and the power deviation value on the vertical axis;

[0069] Using Python's matplotlib library, use the polyfit function to fit the trend line of the scatter plot of aging degree value-power deviation value;

[0070] Specifically, the equation of the trend line is y=k*x+b, where k is the slope and b is the intercept;

[0071] If k>0, it means that the aging degree value-power deviation value shows a linear growth trend;

[0072] If k < 0, it means that the aging degree value - power deviation value shows a linear downward trend;

[0073] Calculate the goodness of fit R of the trend line 2 , judge the fitting effect of the fitting trend line equation;

[0074] Specifically, the fitting effect of the fitting trend line equation is judged as follows:

[0075] SS1. Calculate the total sum of squares Where n is the number of data points, y i is the power deviation value of the i-th battery pack, i=1, 2, 3, n;

[0076] SS2, calculate regression sum of squares pass Calculate the power deviation value of the aging degree value x corresponding to the fitting

[0077] SS3, calculate the residual sum of squares

[0078] SS4, through the formula: Get the goodness of fit R of the trend line 2 ;

[0079] The goodness of fit of the trend line R 2 Perform difference processing with the upper limit value of the goodness of fit to obtain the goodness of fit difference;

[0080] The goodness of fit difference is compared with the upper limit of the goodness of fit to obtain the close fitting ratio.

[0081] comparing the fitted closeness ratio to a fitted closeness ratio threshold;

[0082] If the fitting closeness ratio is higher than the fitting closeness ratio threshold, it indicates that the trend line has a good fitting degree, that is, the aging degree value - power deviation value presents a linear correlation trend. If k of the fitting trend line is greater than 0, it indicates that the aging degree value - power deviation value presents a linear growth correlation trend, that is, the higher the aging degree of the battery pack, the greater the power deviation value.

[0083] If the fitting closeness ratio is lower than the fitting closeness ratio threshold, it indicates that the fitting degree of the trend line is poor, that is, the aging degree value-power deviation value does not show a linear correlation trend;

[0084] For example, if there are three battery packs in the energy storage system, n=3, and the power deviation values ​​y1, y2, and y3 of battery packs 1, 2, and 3 are 0.25, 0.18, and 0.32 respectively, then SST=0.0098 is calculated, and the trend line equation is y=0.4*x+0.01. When the aging deviation values ​​x1, x2, and x3 of battery packs 1, 2, and 3 are 0.6, 0.4, and 0.8 respectively, the trend line formula is used to calculate The values ​​are 0.25, 0.17, and 0.33 respectively. Then the SSE is calculated as 0.002 by the formula. Finally, the goodness of fit R is calculated. 2 is 0.98, the upper limit of goodness of fit is 1, and the threshold of fitting closeness is 0.80.

[0085] Step 4: If the aging degree value - power deviation value shows a linear growth trend, the power control of the energy storage system enters the power regulation layer, and a battery aging sequence is constructed based on the aging degree value. The charging and discharging power of the battery pack in the battery aging sequence is numerically analyzed to obtain the upper limit charging power and the upper limit discharging power. The charging and discharging power of the battery pack is regulated based on the upper limit charging power and the upper limit discharging power.

[0086] If the fitting approximation ratio determines that the aging degree value - the power deviation value shows a linear growth trend, the aging degree value of each battery pack is obtained, and the battery aging sequence is constructed in descending order of the aging degree values;

[0087] If the power deviation value PI of the battery group is greater than or equal to the power deviation threshold value in the battery aging sequence, the battery group is marked as a power control group;

[0088] The battery groups in the power control group are regulated in sequence according to the battery aging sequence;

[0089] The specific battery pack control method of the power control group is:

[0090] Obtain a power deviation value PI of a battery group in a power control group, perform difference processing on the power deviation value PI and a power deviation threshold value, and obtain a power deviation difference;

[0091] The power deviation difference is processed by ratio with the power deviation threshold to obtain a power regulation ratio;

[0092] Obtain the maximum charging and discharging power of the battery group in the power control group, and multiply the maximum charging and discharging power of the battery group by the power control ratio to obtain the upper limit charging power and the upper limit discharging power;

[0093] Based on the upper limit of charging power and the upper limit of discharging power, the charging power and discharging power of each battery pack are regulated by using an energy storage converter;

[0094] It should be noted that the energy storage inverter is a device in the energy storage system that connects the battery energy storage system to the power grid. The core components of the energy storage inverter include the DC / DC converter, DC / AC inverter, AC / DC rectifier and its control unit. The core components of the energy storage inverter work together. When each battery pack in the energy storage system reaches the upper limit of charging power and the upper limit of discharging power, the energy storage inverter will control the power of the battery pack according to the upper limit of charging power and the upper limit of discharging power.

[0095] Embodiment 3

[0096] The energy storage system charging and discharging power hierarchical control system based on the characteristics of lithium ions includes:

[0097] Data acquisition module: Based on the characteristics of lithium-ion energy storage systems, the power control of the energy storage system is divided into system monitoring layer, state assessment layer, and power regulation layer. Based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is obtained, and the collected charging and discharging power data is stored in the database;

[0098] Evaluation and judgment module: obtain the charging and discharging power of each battery pack from the database, draw a curve for analysis, obtain the correlation coefficient of the curve, perform numerical calculation on the correlation coefficient of the charging and discharging power curve, obtain the power deviation value PI, and judge whether the battery pack status needs to be evaluated based on the power deviation value PI;

[0099] Evaluation and analysis module: If the status of the battery pack needs to be evaluated, the energy storage system is in the status evaluation layer, and the historical charging power and discharging power data of each battery pack in the energy storage system and the dynamic internal resistance of each battery pack are obtained to establish a status evaluation model, and the aging degree value of each battery pack is output, and a fitting analysis is performed in combination with the power deviation value to obtain the fitting approximation ratio. Based on the fitting approximation ratio, it is determined whether the aging degree value - power deviation value shows a linear growth trend;

[0100] Power control module: If the aging degree value - power deviation value shows a linear growth trend, the power control of the energy storage system enters the power control layer, and a battery aging sequence is constructed based on the aging degree value. The charging and discharging power of the battery pack in the battery aging sequence is numerically analyzed to obtain the upper limit charging power and the upper limit discharging power. Based on the upper limit charging power and the upper limit discharging power, the energy storage converter is used to control the charging and discharging power of the battery pack.

[0101] Embodiment 4

[0102] Reference Figure 3The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a stratified control method for charging and discharging power of an energy storage system based on lithium-ion characteristics as described in any one of the above methods is implemented.

[0103] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that

[0104] Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0105] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0106] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0107] Embodiment 5

[0108] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for controlling the charging and discharging power of an energy storage system based on lithium ion characteristics as described in any one of the above methods is implemented.

[0109] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0110] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0111] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0112] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0115] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A stratified control method for charging and discharging power of an energy storage system based on lithium-ion characteristics, characterized in that: The following steps are involved: Based on the characteristics of lithium-ion energy storage systems, the power control of the energy storage system is divided into three levels: system monitoring layer, state assessment layer, and power regulation layer. Based on the system monitoring layer, the charging and discharging power of each battery pack in the energy storage system is obtained, and the collected charging and discharging power data is stored in the database; Obtain the charging and discharging power of each battery pack from the database, draw a curve for analysis, obtain the correlation coefficient of the curve, perform numerical calculation on the correlation coefficient of the charging and discharging power curve, obtain the power deviation value PI, and determine whether the battery pack status needs to be evaluated based on the power deviation value PI; If the status of the battery pack needs to be evaluated, the energy storage system is in the status evaluation layer. The historical charging power and discharging power data of each battery pack in the energy storage system and the dynamic internal resistance of each battery pack are obtained to establish a status evaluation model, and the aging degree value of each battery pack is output. The power deviation value is combined for fitting analysis to obtain the fitting approximation ratio. Based on the fitting approximation ratio, it is determined whether the aging degree value - power deviation value presents a linear growth trend; If the aging degree value - power deviation value shows a linear growth trend, the power control of the energy storage system enters the power regulation layer, and a battery aging sequence is constructed based on the aging degree value. The charging and discharging power of the battery pack in the battery aging sequence is numerically analyzed to obtain the upper limit charging power and the upper limit discharging power. The energy storage inverter is used to regulate the charging and discharging power of the battery pack.

2. The method for controlling the charge and discharge power of an energy storage system based on the characteristics of lithium ions according to claim 1, characterized in that: The power deviation value PI is obtained in the following manner: Based on the curve matching degree Pd of the time-discharge power change curve and the curve matching degree Fd of the time-discharge power change curve, the power deviation value PI is calculated; By formula: Obtain the power deviation value PI, where c=0.483, d=0.517; The method for evaluating whether the battery pack status needs to be evaluated is: If the power deviation value PI ≥ the power deviation threshold, the state of the battery pack needs to be evaluated.

3. The method for controlling the charging and discharging power of an energy storage system based on the characteristics of lithium ions according to claim 2, characterized in that: The curve matching degree Pd of the time-discharge power variation curve is obtained as follows: Based on the close section ratio Jq and the correlation ratio mean Xg, the curve matching degree Pd of the time-discharge power change curve is calculated; The curve matching degree Pd is obtained by the formula: Pd = a*Jq + b*Xg, where a = 0.213, b = 0.787; The curve matching degree Fd of the time-discharge power variation curve is obtained as follows: Based on the curve matching degree calculation method of the time-charging power variation curve, the curve matching degree of the time-discharging power variation curve is marked as Fd.

4. The method for controlling the charge and discharge power of an energy storage system based on the characteristics of lithium ions according to claim 3, characterized in that: The acquisition method of the close section ratio Jq and the correlation ratio mean Xg is: Use a power meter to collect the charging power and discharging power of the energy storage system at fixed intervals. Input the charging power collected by the power meter into MatLab software to draw time-charging power change curves and time-discharging power change curves. Use the correlation coefficient function of MatLab to analyze the overlap between the time-charging power curve and the charging target curve, and obtain the curve correlation coefficient; Divide the time-charging power variation curve into multiple sub-segments, and obtain the correlation coefficient of each sub-segment; The correlation coefficient is compared with a correlation coefficient threshold, and if the correlation coefficient is higher than the correlation coefficient threshold, the sub-segment is marked as a close segment; Obtain the number of all close segments and the number of all sub-segments, perform ratio processing on the number of close segments and the number of sub-segments to obtain a close segment ratio, and mark the close segment ratio as Jq; Perform difference processing on the correlation coefficient in the close section and the correlation coefficient threshold to obtain the correlation coefficient difference; The correlation coefficient difference is processed by ratio with the correlation coefficient threshold to obtain the correlation proximity ratio; Obtain the relevant proximity ratios of all the proximity sections, sum and average the relevant proximity ratios of all the proximity sections to obtain the correlation ratio mean, and mark the correlation ratio mean as Xg.

5. The method for controlling the charging and discharging power of an energy storage system based on the characteristics of lithium ions according to claim 1, characterized in that: The state model is constructed as follows: The energy storage system is in the state assessment layer, obtaining the historical charging power, discharging power data, and dynamic internal resistance of each battery pack in the energy storage system; Based on the historical charging power, discharging power data of each battery pack in the energy storage system, and the dynamic internal resistance of each battery pack, a support vector machine algorithm is used to build a state assessment model for the battery pack in the energy storage system. Based on the state assessment model, the aging degree value of each battery pack is output; The specific construction method of the state assessment model is as follows: S1. The historical charging power, discharging power data of each battery pack and the dynamic internal resistance of each battery pack are taken as a data set, and the data set is preprocessed, including: removing outliers in the data set and filling in missing values; S2, divide the data set into a training set and a test set in a ratio of 8:2, use the training set to train the state assessment model, and use the test set to verify the training results of the model; S3. The state assessment model outputs the aging degree value of each battery pack in the energy storage system.

6. The method for controlling the charge and discharge power of an energy storage system based on lithium-ion characteristics according to claim 1, characterized in that: The method for judging whether the aging degree value-power deviation value presents a linear growth trend is: comparing the fitted closeness ratio to a fitted closeness ratio threshold; If the fitting closeness ratio is higher than the fitting closeness ratio threshold, and k of the fitting trend line is greater than 0, it indicates that the aging degree value - power deviation value presents a linear growth trend.

7. The method for controlling the charging and discharging power of the energy storage system based on the characteristics of lithium ions according to claim 6, characterized in that: The method for obtaining the fitting closeness ratio is as follows: the fitting goodness of the trend line R 2 Perform difference processing with the upper limit value of the goodness of fit to obtain the goodness of fit difference; The goodness of fit difference is compared with the upper limit of the goodness of fit to obtain the close fitting ratio.

8. The method for controlling the charging and discharging power of the energy storage system based on the characteristics of lithium ions according to claim 7, characterized in that: The goodness of fit R 2 The way to obtain is: Based on the aging degree value of the battery pack output by the state model and the power deviation value PI of each battery pack, a scatter plot of the aging degree value of the battery pack - the power deviation value is drawn in a two-dimensional rectangular coordinate system with the aging degree value on the horizontal axis and the power deviation value on the vertical axis; Using Python's matplotlib library, the polyfit function is used to fit the trend line of the scatter plot of aging degree value-power deviation value. The equation of the trend line is y=k*x+b, where k is the slope and b is the intercept. If k>0, it means that the aging degree value-power deviation value shows a linear growth trend; If k < 0, it means that the aging degree value - power deviation value shows a linear downward trend; Calculate the goodness of fit R of the trend line 2 , judge the fitting effect of the fitting trend line equation; The way to judge the fitting effect of the fitting trend line equation is as follows: SS1. Calculate the total sum of squares Where n is the number of data points, y i is the power deviation value of the i-th battery; SS2, calculate regression sum of squares pass Calculate the fitted power deviation value corresponding to the aging degree value x SS3, calculate the residual sum of squares SS4, through the formula: Get the goodness of fit R of the trend line 2 .

9. The method for controlling the charging and discharging power of an energy storage system based on lithium-ion characteristics according to claim 1, characterized in that: The charging and discharging power of the battery pack is regulated in the following manner: Obtain a power deviation value PI of a battery group in a power control group, perform difference processing on the power deviation value PI and a power deviation threshold value, and obtain a power deviation difference; The power deviation difference is processed by ratio with the power deviation threshold to obtain the power regulation ratio; Obtain the maximum charging and discharging power of the battery group in the power control group, and multiply the maximum charging and discharging power of the battery group by the power control ratio to obtain the upper limit charging power and the upper limit discharging power; Based on the upper limit of charging power and the upper limit of discharging power, the charging power and discharging power of each battery pack are regulated using an energy storage inverter.

10. The method for controlling the charging and discharging power of an energy storage system based on lithium-ion characteristics according to claim 1, characterized in that: The power control group is obtained in the following manner: If the fitting approximation ratio determines that the aging degree value - the power deviation value shows a linear growth trend, the aging degree value of each battery pack is obtained, and the battery aging sequence is constructed in descending order of the aging degree values; If the power deviation value PI of the battery group is greater than or equal to the power deviation threshold in the battery aging sequence, the battery group is marked as a power control group, and the battery groups in the power control group are regulated in sequence according to the order of the battery aging sequence.

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