Operation state monitoring method of energy storage energy management system

Abstract

The invention relates to the technical field of energy storage state monitoring, in particular to an operation state monitoring method for an energy storage energy management system, and the method comprises the steps: obtaining voltage sequences and internal resistance sequences of each single energy storage battery and an energy storage battery pack; according to the voltage data fluctuation characteristics of each single energy storage battery, the voltage change rate difference and the voltage range difference between each single energy storage battery and all other single energy storage batteries, obtaining the voltage abnormal weight of each single energy storage battery, and combining the trend term data of the internal resistance data of each single energy storage battery to obtain the voltage abnormal weight of each single energy storage battery. And according to the fluctuation characteristic and the nonlinear characteristic of the internal resistance sequence of each single energy storage battery and the internal resistance data similarity between the single energy storage batteries and all other single energy storage batteries, obtaining an operation abnormality factor of each single energy storage battery, and further judging whether the energy storage battery pack operates abnormally or not. According to the invention, the monitoring accuracy of the running state of the energy storage battery pack is improved by more accurately analyzing the abnormal characteristics of each single energy storage battery.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage status monitoring, and in particular to a method for monitoring the operating status of an energy storage energy management system. Background Art

[0002] The operating status monitoring of the energy storage management system refers to the real-time and accurate acquisition of key parameters and equipment operating information in the energy storage system through a variety of sensors, monitoring equipment, the Internet of Things, or data acquisition and processing technologies. The data analysis technology is used to achieve a comprehensive understanding and effective monitoring of the operating status of the energy storage system, and to promptly detect potential faults and anomalies.

[0003] As a crucial component of the energy storage and energy management system (EMS), BMS (Battery Management System) operating status monitoring is crucial for ensuring stable EMS operation and improving efficiency. Existing technologies for monitoring the operating status of energy storage battery packs fail to account for differences in capacity decay rates between different batches of cells. Cluster-level battery monitoring can mask abnormalities in individual cells, leading to errors in the monitoring results of the battery pack's operating status. Furthermore, in parallel configurations of energy storage battery packs, the nonlinear irrelevance of the internal resistance data of energy storage batteries due to temperature, as well as abnormalities in the internal resistance of individual energy storage cells caused by extreme temperatures, can also lead to monitoring errors in the internal resistance of the battery pack, resulting in low accuracy in the monitoring results of the battery pack's operating status. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an operating status monitoring method of an energy storage energy management system to solve the existing problems.

[0005] The present invention provides a method for monitoring the operating status of an energy storage and energy management system using the following technical solutions: An embodiment of the present application provides a method for monitoring the operating status of an energy storage and energy management system, the method comprising the following steps: Obtain the voltage sequence and internal resistance sequence of each single energy storage battery; obtain the voltage sequence and internal resistance sequence of the energy storage battery group; The voltage change rate sequence of each single energy storage battery is obtained based on the voltage change rate within the neighborhood of each mutation point in the voltage sequence of each single energy storage battery; the response rate consistency of each single energy storage battery is obtained based on the similarity between the mutation point sequence in the voltage sequence of each single energy storage battery and the mutation point sequence in the voltage sequence of the energy storage battery group, and the distance between the voltage change rate sequence of each single energy storage battery and all other single energy storage batteries. In addition, the voltage anomaly weight of each single energy storage battery is obtained by combining the difference in the degree of discreteness of the voltage sequence of each single energy storage battery and the energy storage battery group, as well as the difference in the voltage range of each single energy storage battery and all other single energy storage batteries; The internal resistance trend sequence of each single energy storage battery and energy storage battery group is obtained based on the trend item strength of each internal resistance data in the internal resistance sequence of each single energy storage battery and energy storage battery group. The trend fluctuation strength of each single energy storage battery is obtained based on the autocorrelation degree of the internal resistance trend sequence corresponding to each single energy storage battery and energy storage battery group and the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each single energy storage battery. The internal resistance abnormality factor of each single energy storage battery is obtained by combining the distance between all data in the internal resistance sequence of each single energy storage battery and its fitting straight line, as well as the similarity of the internal resistance sequence between each single energy storage battery and all other single energy storage batteries. The operation abnormality factor of each single energy storage battery is obtained by combining the voltage abnormality weight of each single energy storage battery, and then judging whether the energy storage battery group is operating abnormally.

[0006] Preferably, the process of obtaining the voltage change rate sequence of each single energy storage battery is as follows: obtaining all mutation points in the voltage sequence of each single energy storage battery; recording a sequence consisting of all voltage data between each mutation point and the previous mutation point in the voltage sequence in chronological order as the instantaneous voltage sequence of each mutation point; recording the ratio of the absolute value of the difference between the first and last voltage data of each instantaneous voltage sequence and its duration as the instantaneous voltage change rate of each instantaneous voltage sequence; and recording a sequence consisting of the instantaneous voltage change rates of all instantaneous voltage sequences corresponding to each single energy storage battery as the voltage change rate sequence of each single energy storage battery.

[0007] Preferably, the process of obtaining the consistency of the response rates of the individual energy storage batteries is as follows: Obtaining a mutation sequence for each voltage sequence according to the position order of all mutation points in each voltage sequence; Calculate the response rate consistency of each single energy storage battery: Where, is the response rate consistency of the i-th single energy storage battery, is the cosine similarity between the mutation sequence of the voltage sequence of the energy storage battery group and the mutation sequence of the voltage sequence of the i-th single energy storage battery, It is the cumulative result of the DTW distance between the voltage change rate sequence corresponding to the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group.

[0008] Preferably, the mutation sequence of each voltage sequence refers to a sequence composed of the position sequences of all mutation points in each voltage sequence.

[0009] Preferably, the calculation formula for the voltage abnormality weight of each single energy storage battery is: Where, is the voltage abnormality weight of the i-th single energy storage battery, is the ratio between the variance of the voltage sequence of the i-th single energy storage battery and the corresponding voltage sequence of the energy storage battery group, The cumulative result of the absolute value of the difference between the voltage range of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group; is the response rate consistency of the i-th single energy storage battery, and norm() is the normalization function.

[0010] Preferably, the internal resistance trend sequence of each single energy storage battery or energy storage battery pack refers to a sequence composed of the trend item strengths of all internal resistance data in the internal resistance sequence of each single energy storage battery or energy storage battery pack in a chronological order.

[0011] Preferably, the calculation formula for the trend fluctuation intensity of each single energy storage battery is: Where, is the trend fluctuation intensity of the i-th single energy storage battery, 、 are the Hurst exponents of the internal resistance trend series of the i-th single energy storage battery and the energy storage battery group, is the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of the i-th single energy storage battery.

[0012] Preferably, the calculation formula for the abnormal internal resistance factor of each single energy storage battery is: Where, is the abnormal internal resistance factor of the i-th single energy storage battery; is the trend fluctuation intensity of the i-th single energy storage battery, is the cumulative result of the shortest distance between all data in the internal resistance series of the i-th single energy storage battery and its fitting straight line, It is the cumulative result of the Pearson similarity coefficient between the internal resistance series of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group.

[0013] Preferably, the calculation formula for the abnormal operation factor of each single energy storage battery is: Where, is the abnormal operation factor of the i-th single energy storage battery; is the voltage anomaly weight of the i-th single energy storage battery in the energy storage battery group; is the internal resistance shielding abnormality of the i-th single energy storage battery in the energy storage battery pack; norm( ) is the normalization function.

[0014] Preferably, the specific process of determining whether the energy storage battery pack is operating abnormally is as follows: when the number of single energy storage batteries in the energy storage battery pack whose operating abnormality factor is greater than or equal to a preset abnormality threshold exceeds a preset proportion, the energy storage battery pack is determined to be in an operating abnormal state; otherwise, the energy storage battery pack is determined not to be in an operating abnormal state.

[0015] This application has at least the following beneficial effects: 1. This application addresses the problem that in the battery management unit under the energy storage energy management system, the energy storage battery group has a serious shielding effect on the voltage and internal resistance monitoring of the single energy storage battery, making it impossible to accurately evaluate the operating status of the energy storage battery group. The voltage abnormality weight and internal resistance abnormality factor of the single energy storage battery are constructed to more accurately reflect the voltage discreteness of the single energy storage battery and the consistency with the response change rate of the energy storage battery group, as well as the nonlinear and unrelated change trend of the single energy storage battery caused by extreme temperature and temperature conduction, so that the abnormal status assessment results of each single energy storage battery are more accurate.

[0016] 2. The operation abnormality factor is obtained through the voltage abnormality weight and the internal resistance abnormality factor, and is used as a basis for evaluating the operation status of the energy storage battery group. This effectively avoids the situation where the cluster-level energy storage unit masks the abnormal conditions of the voltage and internal resistance of the single energy storage battery during the operation of the energy storage energy management system. It can effectively characterize the overall operation status of the energy storage battery group and more accurately judge whether the energy storage battery group in the energy storage energy management system is in an abnormal operation state. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A flowchart of the steps of a method for monitoring the operating status of an energy storage energy management system provided in this application; Figure 2 This is a process for obtaining the operating abnormality factor of each single energy storage battery provided in this application. DETAILED DESCRIPTION

[0019] In order to further illustrate the technical means and effects adopted by this application to achieve the predetermined invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the operation status monitoring method of an energy storage energy management system proposed in this application, its specific implementation method, structure, features and effects. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics of one or more embodiments may be combined in any suitable form.

[0020] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0021] The following describes in detail a method for monitoring the operating status of an energy storage and energy management system provided by the present application with reference to the accompanying drawings.

[0022] An embodiment of the present application provides a method for monitoring the operating status of an energy storage energy management system. Specifically, the following method for monitoring the operating status of an energy storage energy management system is provided. Figure 1 , the method comprises the following steps: Step 1: Obtain the voltage sequence and internal resistance sequence of each single energy storage battery; obtain the voltage sequence and internal resistance sequence of the energy storage battery group.

[0023] This application deploys sensors in the BMS (Battery Management System) within the energy storage energy management system to obtain relevant data during the operation of the energy storage batteries. Specifically, voltage and current sensors are deployed on each single energy storage battery in the BMS. The voltage and current data of each single energy storage battery at each moment are collected through the voltage and current sensors, respectively. The voltage and current data sampling frequency is set to 8 kHz. At the same time, the voltage and current of the energy storage battery pack composed of all single energy storage batteries are collected at each moment. The open circuit voltage of the energy storage battery pack is obtained through the BMS battery management system.

[0024] The acquired data for individual energy storage cells and battery packs is synchronized across the entire site using the PTP protocol to ensure data timestamp alignment. A sliding window filtering algorithm is then used to filter the voltage and current data for each individual energy storage cell and the battery pack. The filter window width is set to 5ms to eliminate interference from sudden voltage and current fluctuations. Since the sliding window filtering algorithm is well known, the specific acquisition process will not be elaborated on.

[0025] The ratio of the voltage to the current of each single energy storage battery at each moment is used as the internal resistance of each single energy storage battery at that moment; the ratio of the voltage to the current of the energy storage battery pack at each moment is used as the internal resistance of the energy storage battery pack at that moment. The sequence of the voltage data and internal resistance data of each single energy storage battery in a time sequence is recorded as the voltage sequence and internal resistance sequence of each single energy storage battery; the sequence of the voltage data and internal resistance data of the energy storage battery pack in a time sequence is recorded as the voltage sequence and internal resistance sequence of the energy storage battery pack.

[0026] At this point, the voltage sequence and internal resistance sequence of each single energy storage battery and energy storage battery group in the energy storage energy management system can be obtained through the above method.

[0027] Step 2: Obtain the voltage change rate sequence of each single energy storage battery based on the voltage change rate within the neighborhood of each mutation point in the voltage sequence of each single energy storage battery; obtain the response rate consistency of each single energy storage battery based on the similarity between the mutation point sequence in the voltage sequence of each single energy storage battery and the mutation point sequence in the voltage sequence of the energy storage battery group, and the distance between the voltage change rate sequence of each single energy storage battery and all other single energy storage batteries. In addition, the voltage anomaly weight of each single energy storage battery is obtained by combining the difference in the degree of dispersion of the voltage sequence of each single energy storage battery and the energy storage battery group, as well as the difference in the voltage range of each single energy storage battery and all other single energy storage batteries.

[0028] In energy storage and energy management systems, overcharging and over-discharging of energy storage batteries are the fundamental solution to the problem of battery pack consistency. However, due to differences in the capacity decay rates of different batches of battery cells, and the energy storage battery pack contains a large number of single energy storage batteries, the abnormality of single batteries may be masked by the operating status of the cluster-level energy storage unit. As a result, the single battery may have reached the overcharge or over-discharge state, while the cluster-level energy storage unit is in good monitoring status. This will aggravate the battery imbalance phenomenon in the energy storage battery pack and the aging process of the single energy storage battery, shorten the service life of the energy storage unit, and seriously affect the stable operation and overall performance of the energy storage and energy management system.

[0029] Specifically, in an energy storage battery pack, the more seriously the abnormality of a single energy storage battery is masked by the operating status of a cluster-level energy storage unit, the more stable the voltage of the energy storage battery pack is. However, the dispersion between the energy storage voltages of each single energy storage battery increases due to the forced voltage balance of the circulating current of the parallel battery structure, and the greater the voltage range difference between the single energy storage batteries due to the difference in battery capacity; at the same time, the greater the difference in voltage change rate between the single energy storage batteries that make up the energy storage battery pack due to different capacity attenuation rates, the stronger the inconsistency in voltage change response between the energy storage battery pack and the single energy storage batteries.

[0030] Based on the above analysis, this application constructs voltage anomaly weights to characterize the degree to which cluster-level voltage in the battery management system masks anomalies in individual energy storage batteries. The difference between the maximum and minimum values ​​in the voltage sequence corresponding to each individual energy storage battery is recorded as the voltage range of each individual energy storage battery. The voltage sequence of each individual energy storage battery is used as input, and the Bayesian Online Changepoint Detection algorithm is used to obtain all mutation points in the voltage sequence of each individual energy storage battery; similarly, all mutation points in the voltage sequence of the energy storage battery group are obtained.

[0031] The sequence of all voltage data between each mutation point and the previous mutation point in the voltage sequence of a single energy storage battery, in chronological order, is recorded as the instantaneous voltage sequence of each mutation point. (It should be noted that when there is no mutation point before a mutation point, that is, when the mutation point is the first mutation point, the sequence of all data between the first voltage data and the first mutation point in the voltage sequence, in chronological order, is recorded as the instantaneous voltage sequence of the first mutation point.) The ratio of the absolute value of the difference between the first and last voltage data of each instantaneous voltage sequence and its duration is recorded as the instantaneous voltage change rate of each instantaneous voltage sequence. The sequence of the instantaneous voltage change rates of all instantaneous voltage sequences corresponding to each single energy storage battery is recorded as the voltage change rate sequence of each single energy storage battery. The sequence of the positional order of all mutation points in each voltage sequence is recorded as the mutation sequence of each voltage sequence.

[0032] In this embodiment, the response rate consistency of the i-th single energy storage battery is recorded as , whose expression is: Where, is the response rate consistency of the i-th single energy storage battery, is the cosine similarity between the mutation sequence of the voltage sequence of the energy storage battery group and the mutation sequence of the voltage sequence of the i-th single energy storage battery, The cumulative DTW distance between the voltage rate of change sequences of the i-th individual energy storage battery and all other individual energy storage batteries in the energy storage battery pack. Response rate consistency characterizes the difference in instantaneous voltage change rates between individual energy storage batteries and the consistency of voltage change responses between the energy storage battery pack and individual energy storage batteries.

[0033] As a preferred implementation, based on the consistency of the response rate of each single energy storage battery, the difference in the discrete degree of the voltage series of each single energy storage battery and the energy storage battery group, and the difference in the voltage range of each single energy storage battery and all other single energy storage batteries, the voltage anomaly weight of each single energy storage battery is obtained to characterize the degree of abnormality of the voltage data of each single energy storage battery.

[0034] In this embodiment, the voltage abnormality weight of the i-th single energy storage battery is recorded as , its specific expression is: Where, is the voltage abnormality weight of the i-th single energy storage battery, is the ratio between the variance of the voltage sequence of the i-th single energy storage battery and the corresponding voltage sequence of the energy storage battery group, The cumulative result of the absolute value of the difference between the voltage range of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group; is the response rate consistency of the i-th single energy storage battery, norm() is the normalization function, so that The value range of is in the range of [0,1].

[0035] The voltage anomaly weight reflects the degree of discrete difference in voltage of individual energy storage batteries caused by the masking effect of cluster-level voltage on the anomaly of individual energy storage batteries and the inconsistency of the voltage response change rate of individual energy storage batteries. It reflects the discrete voltage of single energy storage battery on the basis of the stable voltage of energy storage battery group; It reflects the degree of difference in voltage range between each single energy storage battery. During the operation of the EMS battery management system, when the abnormal condition of the i-th single energy storage battery is more serious, the voltage dispersion of the i-th single energy storage battery is greater on the basis of the stable voltage of the energy storage battery group, and the greater the difference in voltage range between the single energy storage batteries that make up the energy storage battery group, that is, the calculated index The larger the value, the lower the consistency of the voltage response change between the energy storage battery group and the single energy storage battery caused by the different cell capacity attenuation rates, and the greater the difference in the voltage change rate between the single energy storage batteries that make up the energy storage battery group, that is, the calculated index The smaller.

[0036] At this point, the voltage anomaly weight of any single energy storage battery in the energy storage battery group can be obtained through the above method.

[0037] Step 3: Obtain the internal resistance trend sequence of each single energy storage battery and energy storage battery pack based on the trend item strength of each internal resistance data in the internal resistance sequence of each single energy storage battery and energy storage battery pack; obtain the trend fluctuation strength of each single energy storage battery based on the degree of autocorrelation of the internal resistance trend sequence corresponding to each single energy storage battery and energy storage battery pack and the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each single energy storage battery, and obtain the internal resistance abnormality factor of each single energy storage battery based on the distance between all data in the internal resistance sequence of each single energy storage battery and its fitting line, as well as the degree of similarity between the internal resistance sequences of each single energy storage battery and all other single energy storage batteries. Furthermore, obtain the operation abnormality factor of each single energy storage battery based on the voltage abnormality weight of each single energy storage battery, and then determine whether the energy storage battery pack is operating abnormally.

[0038] In an energy storage battery pack composed of a parallel structure of single energy storage batteries, the influence of temperature conduction will cause a dynamic coupling effect of temperature and internal resistance between the single energy storage batteries. Evaluating the operating status of the energy storage batteries in the energy storage energy management system only by the voltage anomaly weight of the single energy storage batteries still has certain disadvantages. It does not consider that the temperature difference of the energy storage batteries will cause changes in internal resistance. There is a lack of analysis of the nonlinear negative correlation between internal resistance and temperature during the charging and discharging behavior of the energy storage batteries, resulting in the inability to accurately assess the risk of overcharging and over-discharging of the energy storage batteries, which affects the operating status monitoring results of the energy storage energy management system.

[0039] Specifically, during the operation of the energy storage battery pack, when the abnormal internal resistance of the single energy storage battery caused by extreme temperature is more serious and the shielding effect of the cluster-level internal resistance monitoring is more serious, the intensity of the internal resistance change trend of the energy storage battery pack is more vague, but the internal resistance change trend of the single energy storage battery is more obvious, and the internal resistance fluctuation frequency of the single energy storage battery is higher; at the same time, the nonlinear correlation caused by the influence of extreme temperature and temperature conduction on the energy storage battery pack is more significant.

[0040] Based on the above analysis, this application constructs an internal resistance anomaly factor to characterize the severity of the internal resistance anomaly of a single energy storage battery in a battery management system due to the masking effect of cluster-level internal resistance. The internal resistance series of each single energy storage battery and energy storage battery group are used as input, and the STL (Seasonal and Trend decomposition using Loess) sequence decomposition algorithm is used as input to obtain the trend item strength of each internal resistance data in the internal resistance series of the single energy storage battery and the energy storage battery group. The trend item strength of all internal resistance data in the internal resistance series of each single energy storage battery is recorded as the internal resistance trend series of each single energy storage battery, and the trend item strength of all internal resistance data in the internal resistance series of the energy storage battery group is recorded as the internal resistance trend series of the energy storage battery group. The first-order difference series of the internal resistance series corresponding to the single energy storage battery is obtained, and the zero-crossing rate of the first-order difference series is calculated. The internal resistance series of each single energy storage battery is used as input, and the least squares method is used to obtain the fitting straight line of the internal resistance series of each single energy storage battery.

[0041] In this embodiment, the trend fluctuation intensity of the i-th single energy storage battery is recorded as , its specific expression is: Where, is the trend fluctuation intensity of the i-th single energy storage battery, 、 are the Hurst exponents of the internal resistance trend sequence of the i-th single energy storage battery and the energy storage battery group, respectively. When the Hurst exponent is closer to 0.5, it means that the random walk of the data sequence is stronger. When the Hurst exponent is less close to 0.5, it means that the internal resistance trend sequence is more correlated, and the internal resistance data has a more obvious trend. is the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of the i-th single energy storage battery.

[0042] The degree of trend fluctuation reflects the trend strength and the frequency intensity of internal resistance fluctuation of the single energy storage battery based on the fact that there is no obvious change trend in the internal resistance of the energy storage battery pack.

[0043] As a preferred embodiment, the internal resistance abnormality factor of each single energy storage battery is obtained based on the trend fluctuation intensity of each single energy storage battery, the distance between all data in the internal resistance series of each single energy storage battery and its fitting straight line, and the similarity between the internal resistance series of each single energy storage battery and all other single energy storage batteries. The internal resistance abnormality factor is used to characterize the abnormality of the internal resistance data of each single energy storage battery.

[0044] In this embodiment, the abnormal internal resistance factor of the i-th single energy storage battery in the energy storage battery pack is recorded as , its specific expression is: Where, is the abnormal internal resistance factor of the i-th single energy storage battery; is the trend fluctuation intensity of the i-th single energy storage battery, is the cumulative result of the shortest distance between all data in the internal resistance series of the i-th single energy storage battery and its fitting straight line, It is the cumulative result of the Pearson similarity coefficient between the internal resistance series of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group.

[0045] The internal resistance anomaly factor reflects the intensity of energy storage battery trend fluctuations and the correlation of nonlinear changes in internal resistance caused by extreme temperature and cluster-level resistance monitoring shielding effects in the battery management system; It represents the nonlinear change trend of internal resistance data caused by extreme temperature and temperature conduction. Characterizes the degree of correlation between the internal resistance data of the i-th single energy storage battery and other single energy storage batteries. The larger the value, the more obvious the trend of the internal resistance change of the single energy storage battery, the higher the zero-crossing rate of the internal resistance data of the single energy storage battery, and at the same time, the more nonlinear the internal resistance data of the single energy storage battery shows, and the stronger the correlation between the internal resistance data of the other single energy storage batteries in the energy storage battery group, then during the operation of the EMS battery management system, the more serious the impact of extreme external temperature on the energy storage battery group, and the more obvious the shielding effect of the internal resistance of the energy storage battery group on the abnormality of the single energy storage battery.

[0046] Furthermore, during the operation of the energy storage battery pack, when the voltage anomaly weight of the energy storage battery is more serious and the internal resistance anomaly factor is more obvious, it means that the mean smoothing in the monitoring process of the energy storage battery pack has a more serious abnormal shielding effect on the single energy storage battery, and the consistent operation state of the energy storage battery pack is worse.

[0047] As a preferred embodiment, the operation abnormality factor of each single energy storage battery is obtained based on the internal resistance abnormality factor and voltage abnormality weight of each single energy storage battery, which is used to characterize the degree of operation abnormality of each single energy storage battery. The process of obtaining the operation abnormality factor of each single energy storage battery is as follows: Figure 2 shown.

[0048] In this embodiment, the abnormal operation factor of the i-th single energy storage battery is recorded as , whose expression is: Where, is the abnormal operation factor of the i-th single energy storage battery; is the voltage anomaly weight of the i-th single energy storage battery in the energy storage battery group; is the internal resistance shielding abnormality of the i-th single energy storage battery in the energy storage battery pack; norm( ) is the normalization function, so that The value range of is in the range of [0,1].

[0049] When the operating abnormality factor of a single energy storage battery is higher, it means that the voltage discreteness of the single energy storage battery is more obvious and the response rate consistency with the energy storage battery group is worse; at the same time, the internal resistance fluctuation trend of the single energy storage battery is stronger and the nonlinear correlation transformation is more obvious. At this time, the battery capacity loss and the risk of overcharge and over-discharge are greater, and the accelerated aging process is more serious.

[0050] Furthermore, a preset abnormality threshold is set. When the number of single energy storage batteries in the energy storage battery group whose operation abnormality factor is greater than or equal to the preset abnormality threshold exceeds a preset ratio, it is considered that the operation balance consistency of each single energy storage battery in the energy storage battery group is poor, the capacity decay and aging process risk of the single energy storage battery is high, the shielding effect of the energy storage battery group on the single energy storage battery is more serious, the energy storage battery group is in an abnormal operation state, and the energy storage energy management system is in a poor operation state; conversely, it is considered that the operation balance consistency of each single energy storage battery in the energy storage battery group is good, the capacity decay and aging process risk of the single energy storage battery is low, the energy storage battery group is not in an abnormal operation state, and the operation state is good. In this embodiment, the preset abnormality threshold value is 0.6, and the preset ratio is .

[0051] At this point, the operating status evaluation result of the battery management system in the energy storage energy management system can be obtained through the above method, thereby realizing an operating status monitoring method of the energy storage energy management system.

[0052] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0054] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them. Modifications to the technical solutions described in the aforementioned embodiments, or equivalent replacements of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for monitoring the operating status of an energy storage energy management system, characterized in that: The method comprises the following steps: Obtain the voltage sequence and internal resistance sequence of each single energy storage battery; obtain the voltage sequence and internal resistance sequence of the energy storage battery group; The voltage change rate sequence of each single energy storage battery is obtained based on the voltage change rate within the neighborhood of each mutation point in the voltage sequence of each single energy storage battery; the response rate consistency of each single energy storage battery is obtained based on the similarity between the mutation point sequence in the voltage sequence of each single energy storage battery and the mutation point sequence in the voltage sequence of the energy storage battery group, and the distance between the voltage change rate sequence of each single energy storage battery and all other single energy storage batteries. In addition, the voltage anomaly weight of each single energy storage battery is obtained by combining the difference in the degree of discreteness of the voltage sequence of each single energy storage battery and the energy storage battery group, as well as the difference in the voltage range of each single energy storage battery and all other single energy storage batteries; The internal resistance trend sequence of each single energy storage battery and energy storage battery group is obtained based on the trend item strength of each internal resistance data in the internal resistance sequence of each single energy storage battery and energy storage battery group. The trend fluctuation strength of each single energy storage battery is obtained based on the autocorrelation degree of the internal resistance trend sequence corresponding to each single energy storage battery and energy storage battery group and the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each single energy storage battery. The internal resistance abnormality factor of each single energy storage battery is obtained by combining the distance between all data in the internal resistance sequence of each single energy storage battery and its fitting straight line, as well as the similarity of the internal resistance sequence between each single energy storage battery and all other single energy storage batteries. The operation abnormality factor of each single energy storage battery is obtained by combining the voltage abnormality weight of each single energy storage battery, and then judging whether the energy storage battery group is operating abnormally.

2. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The process of obtaining the voltage change rate sequence of each single energy storage battery is as follows: obtaining all mutation points in the voltage sequence of each single energy storage battery; recording a sequence consisting of all voltage data between each mutation point and the previous mutation point in the voltage sequence in chronological order as the instantaneous voltage sequence of each mutation point; recording the ratio of the absolute value of the difference between the first and last voltage data of each instantaneous voltage sequence and its duration as the instantaneous voltage change rate of each instantaneous voltage sequence; and recording a sequence consisting of the instantaneous voltage change rates of all instantaneous voltage sequences corresponding to each single energy storage battery as the voltage change rate sequence of each single energy storage battery.

3. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The process of obtaining the consistency of the response rates of the individual energy storage batteries is as follows: Obtaining a mutation sequence for each voltage sequence according to the position order of all mutation points in each voltage sequence; Calculate the response rate consistency of each single energy storage battery: Where, is the response rate consistency of the i-th single energy storage battery, is the cosine similarity between the mutation sequence of the voltage sequence of the energy storage battery group and the mutation sequence of the voltage sequence of the i-th single energy storage battery, It is the cumulative result of the DTW distance between the voltage change rate sequence corresponding to the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group.

4. The method for monitoring the operating status of an energy storage and energy management system according to claim 3, wherein: The mutation sequence of each voltage sequence refers to a sequence composed of the position sequences of all mutation points in each voltage sequence.

5. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The calculation formula for the voltage abnormality weight of each single energy storage battery is: Where, is the voltage abnormality weight of the i-th single energy storage battery, is the ratio between the variance of the voltage sequence of the i-th single energy storage battery and the corresponding voltage sequence of the energy storage battery group, The cumulative result of the absolute value of the difference between the voltage range of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group; is the response rate consistency of the i-th single energy storage battery, and norm() is the normalization function.

6. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The internal resistance trend sequence of each single energy storage battery or energy storage battery pack refers to a sequence composed of the trend item strengths of all internal resistance data in the internal resistance sequence of each single energy storage battery or energy storage battery pack in a chronological order.

7. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The calculation formula for the trend fluctuation intensity of each single energy storage battery is: Where, is the trend fluctuation intensity of the i-th single energy storage battery, 、 are the Hurst exponents of the internal resistance trend series of the i-th single energy storage battery and the energy storage battery group, is the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of the i-th single energy storage battery.

8. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The calculation formula of the abnormal internal resistance factor of each single energy storage battery is: Where, is the abnormal internal resistance factor of the i-th single energy storage battery; is the trend fluctuation intensity of the i-th single energy storage battery, is the cumulative result of the shortest distance between all data in the internal resistance series of the i-th single energy storage battery and its fitting straight line, It is the cumulative result of the Pearson similarity coefficient between the internal resistance series of the i-th single energy storage battery and all other single energy storage batteries in the energy storage battery group.

9. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The calculation formula for the abnormal operation factor of each single energy storage battery is: Where, is the abnormal operation factor of the i-th single energy storage battery; is the voltage anomaly weight of the i-th single energy storage battery in the energy storage battery group; is the internal resistance shielding abnormality of the i-th single energy storage battery in the energy storage battery pack; norm( ) is the normalization function.

10. The method for monitoring the operating status of an energy storage and energy management system according to claim 1, wherein: The specific process of determining whether the energy storage battery pack is operating abnormally is as follows: when the number of single energy storage batteries in the energy storage battery pack whose operating abnormality factor is greater than or equal to a preset abnormality threshold exceeds a preset ratio, the energy storage battery pack is determined to be in an abnormal operating state; Otherwise, it is determined that the energy storage battery pack is not in an abnormal operating state.

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