Energy storage power station safety monitoring and data storage method and system

Abstract

The present invention relates to the field of battery detection technology, and specifically to a method and system for safety monitoring and data storage of energy storage power stations. The method obtains voltage data and power data of a battery cell at each moment; obtains the charging instability of the battery cell according to the change of power data of the battery cell in the charging stage in the current time period, and the difference in the change of power data of the battery cell and other battery cells in the same battery module; obtains the degree of abnormality according to the voltage data and charging instability of the battery cell; obtains the comprehensive abnormality index of the battery module according to the relationship between the abnormality, temperature data and humidity data and the voltage data, judges whether the battery module is safe, and obtains abnormal data and normal data for storage. The present invention accurately obtains the comprehensive abnormality index, and then accurately and timely judges the battery module with safety problems, which is conducive to timely repairing safety problems in energy storage power stations.

Description

Technical Field

[0001] The present invention relates to the field of battery detection technology, and in particular to a method and system for safety monitoring and data storage of an energy storage power station. Background Art

[0002] As battery energy storage systems are increasingly used in power systems, how to accurately analyze the safety of battery modules has become an important issue.

[0003] In the existing method, the voltage of each battery cell in the battery module is monitored in real time through the battery management system (BMS). When the voltage exceeds the standard voltage range of the battery cell, it indicates that there is a problem with the safety of the battery module. However, in actual situations, there may be errors in the process of obtaining the voltage of the battery cell, which may lead to the situation that it is mistaken for an abnormality. At the same time, environmental factors will affect the performance of the battery cell, resulting in abnormal voltage. Therefore, it is impossible to accurately judge whether the battery module in the energy storage power station is safe based only on the voltage of the battery cell obtained in real time. Summary of the invention

[0004] In order to solve the technical problem that the voltage of the battery cell obtained in real time cannot accurately determine whether the battery module in the energy storage power station is safe, the purpose of the present invention is to provide a method and system for safety monitoring and data storage of an energy storage power station. The technical solution adopted is as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for safety monitoring and data storage of an energy storage power station, the method comprising the following steps:

[0006] Obtain the voltage data and power data of each battery cell in the energy storage power station at each moment, as well as the temperature data and humidity data of the energy storage power station at each moment;

[0007] According to the change of the power data of each battery cell in each charging stage in the current time period, and the difference in the change of the power data of each battery cell in the charging stage between the battery cell and other battery cells in the same battery module, the charging instability degree of each battery cell is obtained;

[0008] According to the distribution of voltage data of each battery cell and the degree of charging instability in the current time period, the abnormality degree of each battery cell is obtained;

[0009] Obtaining a comprehensive abnormality index of each battery module according to the abnormality degree of the battery cells in each battery module and the relationship between the temperature data and the humidity data and the voltage data of each battery cell in each battery module in the current time period;

[0010] The safety of the battery module is determined based on the comprehensive abnormality index, and abnormal data and normal data are obtained and stored.

[0011] Furthermore, the method for obtaining the degree of charging instability is:

[0012] According to the change of the power data of each battery cell in each charging stage in the current time period, the charging fluctuation degree of each battery cell is obtained;

[0013] Obtaining the degree of deviation of each battery cell according to the difference in the change of the power data of each battery cell and other battery cells in the same battery module during the charging stage;

[0014] The charging instability of each battery cell is obtained according to the charging fluctuation degree and the deviation degree of each battery cell; wherein the charging fluctuation degree and the deviation degree are both positively correlated with the charging instability degree.

[0015] Furthermore, the method for obtaining the charging fluctuation degree is:

[0016] For any battery cell, each charging stage of the battery cell in the current time period is obtained as a reference charging stage; wherein each charging stage is a complete charging process and each charging stage corresponds to a power data segment;

[0017] Obtain the difference between the maximum power data and the minimum power data in each reference charging stage as the reference power change value of the corresponding reference charging stage;

[0018] The variance of all reference power change values ​​is obtained as the charging fluctuation degree of the battery cell.

[0019] Furthermore, the method for obtaining the degree of deviation is:

[0020] For any battery cell, a DTW value of the power data segments of any two reference charging stages of the battery cell is obtained by a dynamic time warping algorithm as a first eigenvalue;

[0021] Obtaining the average of all first characteristic values ​​as the health state value of the battery cell;

[0022] The average of the health status values ​​of all battery cells in the battery module to which the battery cell belongs is used as the target characteristic value;

[0023] The difference between the health status value of the battery cell and the target characteristic value is obtained as the deviation degree of the battery cell.

[0024] Furthermore, the method for obtaining the abnormality degree is:

[0025] According to the distribution of the voltage data of each battery cell in the current time period, the voltage abnormality degree of each battery cell is obtained;

[0026] The abnormality degree of each battery cell is obtained according to the abnormality degree of voltage and the unstable degree of charging of each battery cell; wherein the abnormality degree of voltage and the unstable degree of charging are both positively correlated with the abnormality degree.

[0027] Furthermore, the method for obtaining the voltage abnormality degree is:

[0028] For any battery cell, the standard voltage data range of the battery cell is taken as the target range, and the voltage data of the battery cell in the current time period that exceeds the target range is taken as abnormal voltage data;

[0029] Acquire the quantity of abnormal voltage data as a first quantity;

[0030] Obtaining a standard deviation of the voltage data of the battery cell within a specified time period as a first fluctuation value;

[0031] The product of the first quantity and the first fluctuation value is used as the voltage abnormality degree of the battery cell.

[0032] Furthermore, the method for obtaining the comprehensive abnormality index is:

[0033] For any battery module, the overall abnormality degree of the battery module is obtained according to the abnormality degree of the battery cells in the battery module;

[0034] For any battery cell in the battery module, each voltage data of the battery cell in the current time period and the temperature data at the same time are constructed as a coordinate point, mapped to a two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitting line is used as the first relationship value of the battery cell; wherein the voltage data is used as the horizontal axis and the temperature data is used as the vertical axis;

[0035] taking the average of the first relationship values ​​of all battery cells in the battery module as the temperature influence value of the battery module;

[0036] Each voltage data of the battery cell in the current time period and the humidity data at the same time are constructed as a coordinate point, mapped to a two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitting line is used as the second relationship value of the battery cell; wherein the voltage data is used as the horizontal axis and the humidity data is used as the vertical axis;

[0037] taking the average of the second relationship values ​​of all battery cells in the battery module as the humidity influence value of the battery module;

[0038] The overall abnormality degree, temperature impact value and humidity impact value of the battery module are multiplied and normalized to obtain a comprehensive abnormality index.

[0039] Furthermore, the method for obtaining the overall abnormality degree is:

[0040] For any battery module, obtain the average abnormality level of all battery cells in the battery module as the reference abnormality level of the battery module;

[0041] Acquire the number of battery cells in the battery module whose abnormality degree is greater than a reference abnormality degree as a second number;

[0042] The result of normalizing the product of the reference abnormality level and the second quantity is taken as the overall abnormality level of the battery module.

[0043] Furthermore, the method for judging whether the battery module is safe according to the comprehensive abnormality index and obtaining abnormal data and normal data for storage is:

[0044] When the comprehensive abnormality index is greater than the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be unsafe;

[0045] When the comprehensive abnormality index is less than or equal to the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be safe;

[0046] When the battery module is unsafe, the data in the corresponding battery module are regarded as abnormal data;

[0047] When the battery module is safe, the data in the corresponding battery module are regarded as normal data;

[0048] During the storage process, normal data is directly stored in the database, and abnormal data is marked and then stored in the specified location.

[0049] In a second aspect, another embodiment of the present invention provides a safety monitoring and data storage system for an energy storage power station, the system comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of any one of the above methods are implemented.

[0050] The present invention has the following beneficial effects:

[0051] The present invention first obtains the charging instability degree of each battery cell according to the change of the power data of each battery cell in each charging stage in the current time period, and the change difference of the power data of each battery cell in the charging stage between the battery cell and other battery cells in the same battery module, accurately reflects the change of the power data of each battery cell in the charging stage in the current time period, and indirectly judges the existence of abnormality of each battery cell; in order to more accurately analyze the abnormality of each battery cell in the energy storage power station, further according to the distribution of the voltage data of each battery cell in the current time period and the charging instability degree, obtains the abnormality degree of each battery cell, accurately reflects the abnormality of each battery cell, which is conducive to the subsequent accurate analysis of the abnormality of each battery module; considering that temperature and humidity will affect the battery cell The performance of the battery body is affected, resulting in more obvious abnormal conditions of the battery module. In order to accurately obtain the abnormal conditions of the battery module, the comprehensive abnormal index of each battery module is accurately obtained according to the abnormal degree of the battery cell in each battery module, and the relationship between the temperature data and humidity data and the voltage data of each battery cell in each battery module in the current time period. The battery module with problems can be accurately and timely judged through the comprehensive abnormal index, and the safety problems in the energy storage power station can be discovered in time, which is conducive to the staff to carry out maintenance in time and ensure the safe and stable operation of the energy storage power station. At the same time, the abnormal data and normal data in the energy storage power station can be accurately obtained through the comprehensive abnormal index, which is conducive to accurate analysis of the situation in the energy storage power station, and then targeted maintenance plans for the energy storage power station can be formulated to reduce unnecessary maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. 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 paying creative work.

[0053] Figure 1 A schematic flow chart of a method for safety monitoring and data storage of an energy storage power station provided by an embodiment of the present invention;

[0054] Figure 2 A flow chart of a method for obtaining charging instability provided by an embodiment of the present invention;

[0055] Figure 3 A flow chart of a method for obtaining an abnormality degree provided by an embodiment of the present invention;

[0056] Figure 4 A structural diagram of a safety monitoring and data storage system for an energy storage power station provided by an embodiment of the present invention;

[0057] Figure 5 A schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the energy storage power station safety monitoring and data storage method and system proposed by the present invention, its specific implementation method, structure, characteristics and effects in combination with the accompanying drawings and preferred embodiments. 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 in one or more embodiments may be combined in any suitable form.

[0059] 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 invention belongs.

[0060] The following describes in detail a specific scheme of a method and system for safety monitoring and data storage of an energy storage power station provided by the present invention in conjunction with the accompanying drawings.

[0061] Embodiment 1:

[0062] The specific scenario of this embodiment is: in order to ensure the safe and stable operation of the energy storage power station in real time, this embodiment analyzes the voltage data and power data of each battery cell in each battery module in the energy storage power station in the current time period to determine whether each battery module has an abnormality. Considering that temperature and humidity will affect the performance of the battery cell, which will lead to abnormal voltage data, this embodiment analyzes the impact of temperature data and humidity data on voltage data respectively, and more accurately analyzes the degree of abnormality of each battery module, and then accurately determines whether the battery module is safe. At the same time, the abnormal data and normal data in the energy storage power station are accurately obtained and stored separately, so that the unsafe problems in the energy storage power station can be analyzed more deeply and efficiently later.

[0063] The present invention proposes a method for safety monitoring and data storage of energy storage power stations. Figure 1 , which shows a schematic flow chart of a method for safety monitoring and data storage of an energy storage power station provided by an embodiment of the present invention, the method comprising the following steps:

[0064] Step S1: Obtain voltage data and power data of each battery cell in the energy storage power station at each moment, and temperature data and humidity data of the energy storage power station at each moment.

[0065] Specifically, there are usually one or more battery modules in the energy storage power station, each of which contains multiple battery cells. In order to ensure the safe and stable operation of the energy storage power station, it is necessary to analyze the safety of the battery modules in the energy storage power station in real time. In actual situations, by analyzing the abnormal conditions of each battery cell in the battery module, the health status and potential risks of the battery module can be fully reflected, thereby providing an important basis for the operation decision of the energy storage power station. For example, if multiple battery cells in a battery module are abnormal, the comprehensive abnormality index of the battery module will increase significantly. In order to facilitate the management and operation of the energy storage power station, the battery modules can be divided into normal and abnormal categories according to the abnormal conditions of the battery cells in each battery module. Among them, the comprehensive abnormality index of the normal battery module is low, indicating that it is in good operating condition; the comprehensive abnormality index of the abnormal battery module is high, indicating that it may have potential faults or safety hazards. In this way, the battery modules that need to be focused on and maintained can be quickly identified to improve the safety and reliability of the energy storage power station. Therefore, this embodiment indirectly reflects the abnormality of the battery module by analyzing the abnormality of the battery cell in real time.

[0066] It is known that voltage data is an important indicator reflecting the working state of a battery cell. Too high or too low voltage data may affect the performance and life of the battery cell. At the same time, the change in the power data of the battery cell during different charging processes can also reflect the performance of the battery cell. Therefore, in order to promptly discover abnormal conditions in the battery cell and thus promptly discover whether there are safety problems with the battery module, this embodiment uses the battery management system to obtain the voltage data and power data of each battery cell in the energy storage power station at each moment in real time.

[0067] In actual situations, a high temperature and high humidity environment may cause chemical reactions inside the battery, accelerating the aging of the battery cells; a low temperature and dry environment may affect the charging and discharging efficiency of the battery, affecting the battery performance; and when analyzing the abnormality of the battery module, it is necessary to consider the impact of temperature data and humidity data. In this embodiment, a temperature and humidity sensor is set at any location around the energy storage power station to obtain the temperature data and humidity data of the energy storage power station at every moment in real time.

[0068] It should be noted that the voltage data, power data, temperature data and humidity data are all collected synchronously at the same time. In this embodiment, the time interval between two adjacent times of collecting data is set to 0.1 seconds. The implementer can set the time interval between two adjacent times of collecting data according to actual conditions, and it is not limited here.

[0069] Step S2: Obtain the charging instability of each battery cell according to the change of the power data of each battery cell in each charging stage in the current time period and the difference in the change of the power data of each battery cell and other battery cells in the same battery module.

[0070] Specifically, in the energy storage power station, the charging and discharging processes of the battery cells are carried out separately, because the charging and discharging processes of the battery cells are two opposite electrochemical processes, which require different electrochemical reaction conditions and control strategies. The power data of the battery cells will change during the charging stage. When the degree of change of the power data of a battery cell in different charging stages is more different, it means that the power data change of the battery cell during the charging stage is more unstable, which indirectly indicates that the performance of the battery cell is more abnormal. The change of the power data of different battery cells in the same battery module should be similar. When the difference in the change of the power data of the charging stage between a battery cell and other battery cells in the same battery module is greater, it means that the change of the power data of the battery cell during the charging stage deviates more from the whole, which indirectly indicates that the performance of the battery cell is more abnormal. In order to accurately analyze the possibility of abnormal performance of each battery cell at the current moment, this embodiment obtains the degree of charging instability of each battery cell according to the change of the power data of each battery cell in each charging stage in the current time period, and the difference in the change of the power data of each battery cell in the charging stage between each battery cell and other battery cells in the same battery module. Among them, the greater the degree of charging instability, the more abnormal the performance of the corresponding battery cell. This embodiment sets the current time period to 48 hours, where the end time of the current time period must be the current time. The implementer can set the size of the current time period according to the actual situation, and it is not limited here. In the current time period, each battery cell must have multiple charging stages and each charging stage is a complete charging stage, where the charging stage of each battery cell can be directly determined by the battery management system. It should be noted that this embodiment limits the energy storage power station to have been running for at least 48 hours.

[0071] Preferably, in one possible implementation of this embodiment, the method for obtaining the degree of charging instability can refer to Figure 2 , which shows a flow chart of a method for obtaining charging instability provided by this embodiment, the method comprising the following steps:

[0072] Step S201: acquiring the charging fluctuation degree of each battery cell according to the change of the power data of each battery cell in each charging stage in the current time period.

[0073] Under normal circumstances, the changes in the power data of battery cells during the charging stage are similar. Therefore, this embodiment obtains the charging fluctuation degree of each battery cell by analyzing the changes in the power data of each battery cell in each charging stage within the current time period. The greater the charging fluctuation degree, the more likely it is that the corresponding battery cell is abnormal.

[0074] Preferably, in a method that can be implemented in this embodiment, the method for obtaining the degree of charging fluctuation is: for any battery cell, each charging stage of the battery cell in the current time period is obtained, and each charging stage is used as a reference charging stage; wherein each charging stage is a complete charging process and each charging stage corresponds to a power data segment; the difference between the maximum power data and the minimum power data in each reference charging stage is obtained as the reference power change value of the corresponding reference charging stage, reflecting the degree of change of the power data in each reference charging stage; the less similar the reference power change value is, the more likely the battery cell is abnormal, and then this embodiment obtains the variance of all reference power change values ​​as the charging fluctuation degree of the battery cell, which preliminarily reflects the possibility of abnormality of the battery cell.

[0075] At this point, the charging fluctuation degree of each battery cell is obtained.

[0076] Step S202: Obtain the deviation degree of each battery cell according to the difference in the change of the power data during the charging phase between each battery cell and other battery cells in the same battery module.

[0077] If the change of the power data of a battery cell during the charging stage is significantly different from the change of the power data of other battery cells in the same battery module during the charging stage in the current time period, it means that the change of the power data of the battery cell during the charging stage is significantly deviated from the overall data, which indirectly indicates that the battery cell is more likely to be abnormal. Furthermore, this embodiment obtains the degree of deviation of each battery cell based on the difference in the change of the power data during the charging stage between each battery cell and other battery cells in the same battery module. The greater the degree of deviation, the more abnormal the corresponding battery cell is.

[0078] Preferably, in a method that can be implemented in this embodiment, the method for obtaining the degree of deviation is: for any battery cell, the DTW value of the power data segment of any two reference charging stages of the battery cell is obtained by the dynamic time warping algorithm as the first characteristic value. The smaller the first characteristic value, the more similar the power data in the power data segment of the two reference charging stages. Among them, the dynamic time warping algorithm is a well-known technology and will not be described in detail; in order to analyze the similarity of the power data of the battery cell in all charging stages in the current time period, the mean of all first characteristic values ​​is obtained as the health state value of the battery cell. The smaller the health state value, the more similar the power data of the battery cell in all charging stages in the current time period; in order to analyze whether the battery cell is abnormal in the battery module to which it belongs, the mean of the health state values ​​of all battery cells in the battery module to which the battery cell belongs is obtained as the target characteristic value; then the absolute value of the difference between the health state value of the battery cell and the target characteristic value is obtained as the degree of deviation of the battery cell. The greater the degree of deviation, the more the health state value of the battery cell deviates from the whole, which indirectly indicates that the battery cell is more abnormal.

[0079] At this point, the deviation degree of each battery cell is obtained.

[0080] Step S203: acquiring the charging instability of each battery cell according to the charging fluctuation degree and the deviation degree of each battery cell; wherein the charging fluctuation degree and the deviation degree are both positively correlated with the charging instability degree.

[0081] It is known that the greater the charging fluctuation and the greater the deviation, the more unstable the change in the power data of the corresponding battery cell in the charging stage in the current time period, which indirectly indicates that the corresponding battery cell is more likely to be abnormal. Therefore, this embodiment obtains the charging instability of each battery cell according to the charging fluctuation and deviation of each battery cell; wherein the charging fluctuation and deviation are both positively correlated with the charging instability. The greater the charging instability, the more abnormal the corresponding battery cell. The calculation formula for the charging instability is: ; In the formula, is the charging instability degree of the i-th battery cell; is the charging fluctuation degree of the i-th battery cell; is the deviation degree of the i-th battery cell.

[0082] At this point, the charging instability level of each battery cell is obtained.

[0083] Step S3: Obtain the abnormality level of each battery cell according to the distribution of the voltage data of each battery cell and the charging instability level in the current time period.

[0084] Specifically, when a battery cell is aging, has unstable internal chemical reactions, has poor circuit contact, or is interfered by external environmental factors, the voltage data of the battery cell will be significantly higher or lower than the standard voltage data range of the battery cell, and the voltage data will fluctuate significantly. Furthermore, when the voltage data of a battery cell fluctuates significantly during the current time period, and there is a large amount of voltage data that exceeds the standard voltage data range of the battery cell, it means that the battery cell is more abnormal. It is known that the greater the degree of charging instability, the more abnormal the corresponding battery cell is. Furthermore, this embodiment obtains the degree of abnormality of each battery cell based on the distribution of voltage data of each battery cell and the degree of charging instability during the current time period. The greater the degree of abnormality, the greater the problem with the performance of the corresponding battery cell.

[0085] Preferably, in one possible implementation of this embodiment, the method for obtaining the abnormality degree can refer to Figure 3 , which shows a flow chart of a method for obtaining the abnormality degree provided in this embodiment, the method comprising the following steps:

[0086] Step S301: Obtain the voltage abnormality degree of each battery cell according to the distribution of the voltage data of each battery cell in the current time period.

[0087] In the current time period, when the voltage data of a battery cell exceeds the normal range more and the fluctuation degree is greater, it means that the voltage data of the battery cell is more abnormal, which indirectly means that the battery cell is more abnormal. Then, this embodiment obtains the voltage abnormality degree of each battery cell according to the distribution of the voltage data of each battery cell in the current time period. The greater the voltage abnormality degree, the more abnormal the corresponding battery cell is.

[0088] Preferably, in a method that can be implemented in this embodiment, the method for obtaining the voltage abnormality degree is: for any battery cell, the standard voltage data range of the battery cell is used as the target range. For example, taking a lead-acid battery cell as an example, it is known that the standard voltage data range of a lead-acid battery cell is 1.8V-2.3V, so the target range of the lead-acid battery cell is 1.8V-2.3V. The voltage data of the battery cell that exceeds the target range in the current time period is used as abnormal voltage data; when the abnormal voltage data is more, it means that the voltage data of the battery cell at the current moment is more abnormal, and then the number of abnormal voltage data is obtained as the first number; the larger the first number, the more abnormal the voltage data of the battery cell at the current moment. In order to more accurately analyze the abnormal situation of the battery cell voltage data, the standard deviation of the voltage data of the battery cell in the specified time period is further obtained as the first fluctuation value; the larger the first fluctuation value, the more abnormal the voltage data of the battery cell is. Then the product of the first number and the first fluctuation value is obtained as the voltage abnormality degree of the battery cell.

[0089] At this point, the voltage abnormality level of each battery cell is obtained.

[0090] Step S302: according to the voltage abnormality degree and charging instability degree of each battery cell, the abnormality degree of each battery cell is obtained; wherein the voltage abnormality degree and charging instability degree are both positively correlated with the abnormality degree.

[0091] It is known that the greater the voltage abnormality and the greater the charging instability, the more abnormal the corresponding battery cell is. Therefore, this embodiment obtains the abnormality of each battery cell at the current moment according to the voltage abnormality and charging instability of each battery cell; wherein the voltage abnormality and charging instability are both positively correlated with the abnormality. The calculation formula of the abnormality is: ; In the formula, is the abnormality degree of the i-th battery cell; is the voltage abnormality degree of the i-th battery cell; is the charging instability of the ith battery cell; norm is the normalization function.

[0092] At this point, the abnormality level of each battery cell at the current moment is obtained.

[0093] Step S4: Obtain a comprehensive abnormality index of each battery module according to the abnormality degree of the battery cells in each battery module and the relationship between the temperature data and the humidity data and the voltage data of each battery cell in each battery module in the current time period.

[0094] Specifically, if the abnormality of a battery cell in a battery module is relatively large, it may cause the differences in various data between the battery cells in the entire battery module to become larger, thereby affecting the heat dissipation effect and safety of the battery module. Therefore, this embodiment analyzes the abnormality of each battery module according to the abnormality of the battery cells in each battery module. However, in actual situations, the temperature and humidity in environmental factors may have an adverse effect on the performance of the battery cells. For example, a high temperature and high humidity environment may cause chemical reactions inside the battery and accelerate the aging of the battery cells; a low temperature and dry environment may affect the charging and discharging efficiency of the battery and affect the performance of the battery. Therefore, this embodiment further obtains the comprehensive abnormality index of each battery module based on the relationship between the temperature data and humidity data and the voltage data of each battery cell in each battery module in the current time period.

[0095] Preferably, in a method that can be implemented in this embodiment, the method for obtaining the comprehensive abnormality index is: for any battery module, first, according to the abnormality of the battery cells in the battery module, the overall abnormality of the battery module is obtained; the greater the overall abnormality, the greater the abnormality of the battery module, and the more safety problems the battery module has. In order to more accurately analyze the abnormality of the battery module, and then accurately determine whether there is a safety problem with the battery module at the current moment, this embodiment further analyzes the relationship between the voltage data of each battery cell in the battery module in the current time period and the temperature data and humidity data in the current time period; when the relationship between the temperature data and the voltage data of each battery cell in the battery module is greater, it means that the temperature data has a greater impact on the voltage data in the battery module, and the battery module is more abnormal at the current moment due to the influence of temperature; when the relationship between the humidity data and the voltage data of each battery cell in the battery module is greater, it means that the humidity data has a greater impact on the voltage data in the battery module, and the battery module is more abnormal at the current moment due to the influence of humidity;

[0096] Then, for any battery cell in the battery module, each voltage data of the battery cell in the current time period and the temperature data at the same time are constructed as a coordinate point, mapped to the two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitted straight line is used as the first relationship value of the battery cell; the larger the first relationship value, the greater the influence of the temperature data on the voltage data of the battery cell. Among them, the voltage data is used as the horizontal axis and the temperature data is used as the vertical axis; in order to analyze the temperature influence on the battery module at the current moment, the average of the first relationship values ​​of all battery cells in the battery module is used as the temperature influence value of the battery module; the larger the temperature influence value, the more obvious the abnormality of the battery module;

[0097] Each voltage data of the battery cell in the current time period and the humidity data at the same time are constructed as a coordinate point, mapped to the two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitted straight line is used as the second relationship value of the battery cell; the larger the second relationship value, the greater the influence of the humidity data on the voltage data of the battery cell. Among them, the voltage data is used as the horizontal axis and the humidity data is used as the vertical axis; in order to analyze the influence of humidity on the battery module at the current moment, the average of the second relationship values ​​of all battery cells in the battery module is used as the humidity influence value of the battery module; the larger the humidity influence value, the more obvious the abnormality of the battery module;

[0098] When the overall abnormality of the battery module is obvious, the temperature and humidity will have an abnormal impact on the data in the battery module. Then, this embodiment multiplies the overall abnormality of the battery module, the temperature impact value and the humidity impact value, and normalizes the result as the comprehensive abnormality index of the battery module at the current moment. The larger the comprehensive abnormality index, the greater the performance problem or potential risk of the battery module in the environment at the current moment. Among them, the calculation formula of the comprehensive abnormality index is: ; In the formula, is the comprehensive abnormal index of the a-th battery module; is the overall abnormality degree of the ath battery module; is the temperature impact value of the ath battery module; is the humidity impact value of the a-th battery module; norm is the normalization function.

[0099] At this point, the comprehensive abnormality index of each battery module is obtained.

[0100] Preferably, in a method that can be implemented in this embodiment, the method for obtaining the overall abnormality degree is: for any battery module, the average of the abnormality degrees of all battery cells in the battery module is obtained as the reference abnormality degree of the battery module; the greater the reference abnormality degree, the greater the abnormality degree of the battery module, and the more safety problems there are in the battery module; at the same time, the number of battery cells in the battery module whose abnormality degree is greater than the reference abnormality degree is obtained as the second number; the larger the second number, the more abnormal battery cells there are in the battery module, which indirectly indicates that the abnormality degree of the battery module is greater. Then, the product of the reference abnormality degree and the second number is normalized as the overall abnormality degree of the battery module. The greater the overall abnormality degree, the more safety problems there are in the battery module, and the more abnormal the data in the battery module. Among them, this embodiment normalizes the product of the reference abnormality degree and the second number through the norm normalization function.

[0101] Step S5: Determine whether the battery module is safe based on the comprehensive abnormality index and obtain abnormal data and normal data for storage.

[0102] It is known that the larger the comprehensive abnormality index is, the more safety problems exist in the corresponding battery module, and the more abnormal the data in the corresponding battery module is. Therefore, this embodiment sets the preset comprehensive abnormality index threshold to 0.7. The implementer can set the size of the preset comprehensive abnormality index threshold according to actual conditions, and it is not limited here.

[0103] When the comprehensive abnormality index is greater than the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be unsafe at the current moment. At this time, the early warning mechanism in the battery management system issues an alarm, and the staff can promptly discover the battery modules with problems in the energy storage power station and handle and repair them in time; when the comprehensive abnormality index is less than or equal to the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be safe at the current moment.

[0104] It is known that the data in the battery module are closely related to each other. Therefore, when the battery module is unsafe, the data in the corresponding battery module is regarded as abnormal data; when the battery module is safe, the data in the corresponding battery module is regarded as normal data. In order to conduct a more accurate and efficient in-depth analysis of safety issues in the energy storage power station in the future, and in the storage process, this embodiment stores normal data and abnormal data separately to avoid confusion between abnormal data and normal data, and ensure accurate analysis and judgment of abnormal situations.

[0105] In this embodiment, normal data is directly inserted into the database or data warehouse structure through SQL statements or other data processing tools to ensure that normal data can be easily queried and analyzed. Subsequently, statistical analysis, trend prediction and other operations can be performed through normal data. In this embodiment, abnormal data is stored separately in a special abnormal data table or an identification field is added to the normal data table to mark the abnormal data, and then the abnormal data is stored. Subsequently, in-depth investigation and analysis can be carried out through the abnormal data to find out the potential problems and causes in the energy storage power station, so that maintenance plans can be formulated more specifically and unnecessary maintenance costs can be reduced. By establishing an effective exception handling mechanism, the impact of abnormal data on subsequent analysis and decision-making can be reduced, and the quality and application value of the data can be further improved.

[0106] In summary, this embodiment obtains the voltage data and power data of the battery cell at each moment; obtains the charging instability of the battery cell according to the change of the power data of the battery cell in the charging stage in the current time period, and the difference in the change of the power data of the battery cell and other battery cells in the same battery module; obtains the abnormality according to the voltage data and charging instability of the battery cell; obtains the comprehensive abnormality index of the battery module according to the relationship between the abnormality, temperature data and humidity data and the voltage data, judges whether the battery module is safe, and obtains abnormal data and normal data for storage. The present invention accurately obtains the comprehensive abnormality index, and then accurately and timely judges the battery module with safety problems, which is conducive to timely repairing safety problems in energy storage power stations.

[0107] Embodiment 2:

[0108] The present invention also proposes a safety monitoring and data storage system for energy storage power stations. Figure 4, which shows a structural diagram of a safety monitoring and data storage system for an energy storage power station provided by an embodiment of the present invention, the system includes: a data acquisition module 10, a charging instability acquisition module 20, an abnormality acquisition module 30, a comprehensive abnormality index acquisition module 40 and a data processing module 50.

[0109] The data acquisition module 10 is used to acquire the voltage data and power data of each battery cell in the energy storage power station at each moment, and the temperature data and humidity data of the energy storage power station at each moment.

[0110] The charging instability acquisition module 20 is used to acquire the charging instability of each battery cell according to the change of the power data of each battery cell in each charging stage in the current time period, and the difference in the change of the power data of each battery cell in the charging stage between each battery cell and other battery cells in the same battery module.

[0111] The abnormality degree acquisition module 30 is used to acquire the abnormality degree of each battery cell according to the distribution of the voltage data of each battery cell and the charging instability degree in the current time period.

[0112] The comprehensive abnormality index acquisition module 40 is used to obtain the comprehensive abnormality index of each battery module according to the abnormality degree of the battery cells in each battery module and the relationship between the temperature data and the humidity data and the voltage data of each battery cell in each battery module in the current time period.

[0113] The data processing module 50 is used to determine whether the battery module is safe according to the comprehensive abnormality index and obtain abnormal data and normal data for storage.

[0114] It should be noted that: the system provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the energy storage power station safety monitoring and data storage system and the energy storage power station safety monitoring and data storage method embodiment provided in the above embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0115] Embodiment 3:

[0116] The present invention also proposes a device for energy storage power station safety monitoring and data storage, the device includes a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute a method for energy storage power station safety monitoring and data storage provided in an embodiment of the present application. The device can be a chip, component or module, and the chip can include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a method for energy storage power station safety monitoring and data storage provided in the above embodiment.

[0117] In addition, the present application embodiment also protects a computer device, see Figure 5 The computer device includes a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and running on the processor 402, wherein when the processor 402 executes the computer program 403, the computer device can execute any one of the energy storage power station safety monitoring and data storage methods introduced above.

[0118] Embodiment 4:

[0119] This embodiment also provides a computer-readable storage medium, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement a method for safety monitoring and data storage of an energy storage power station provided in the above embodiment.

[0120] Embodiment 5:

[0121] This embodiment also provides a computer program product. When the computer program product runs on a computer, it enables the computer to execute the above-mentioned related steps to implement a method for safety monitoring and data storage of an energy storage power station provided in the above embodiment.

[0122] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0123] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0124] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for safety monitoring and data storage of energy storage power station, characterized in that: The method comprises the following steps: Obtain the voltage data and power data of each battery cell in the energy storage power station at each moment, as well as the temperature data and humidity data of the energy storage power station at each moment; According to the change of the power data of each battery cell in each charging stage in the current time period, and the difference in the change of the power data of each battery cell in the charging stage between the battery cell and other battery cells in the same battery module, the charging instability degree of each battery cell is obtained; According to the distribution of voltage data of each battery cell and the degree of charging instability in the current time period, the abnormality degree of each battery cell is obtained; Obtaining a comprehensive abnormality index of each battery module according to the abnormality degree of the battery cells in each battery module and the relationship between the temperature data and the humidity data and the voltage data of each battery cell in each battery module in the current time period; The safety of the battery module is determined based on the comprehensive abnormality index, and abnormal data and normal data are obtained and stored.

2. A method for safety monitoring and data storage of an energy storage power station according to claim 1, characterized in that: The method for obtaining the charging instability degree is: According to the change of the power data of each battery cell in each charging stage in the current time period, the charging fluctuation degree of each battery cell is obtained; Obtaining the degree of deviation of each battery cell according to the difference in the change of the power data of each battery cell and other battery cells in the same battery module during the charging stage; The charging instability of each battery cell is obtained according to the charging fluctuation degree and the deviation degree of each battery cell; wherein the charging fluctuation degree and the deviation degree are both positively correlated with the charging instability degree.

3. A method for safety monitoring and data storage of an energy storage power station as claimed in claim 2, characterized in that: The method for obtaining the charging fluctuation degree is: For any battery cell, each charging stage of the battery cell in the current time period is obtained as a reference charging stage; wherein each charging stage is a complete charging process and each charging stage corresponds to a power data segment; Obtain the difference between the maximum power data and the minimum power data in each reference charging stage as the reference power change value of the corresponding reference charging stage; The variance of all reference power change values ​​is obtained as the charging fluctuation degree of the battery cell.

4. A method for safety monitoring and data storage of an energy storage power station as claimed in claim 3, characterized in that: The method for obtaining the degree of deviation is: For any battery cell, a DTW value of the power data segments of any two reference charging stages of the battery cell is obtained by a dynamic time warping algorithm as a first eigenvalue; Obtaining the average of all first characteristic values ​​as the health state value of the battery cell; The average of the health status values ​​of all battery cells in the battery module to which the battery cell belongs is used as the target characteristic value; The difference between the health status value of the battery cell and the target characteristic value is obtained as the deviation degree of the battery cell.

5. A method for safety monitoring and data storage of an energy storage power station according to claim 1, characterized in that: The method for obtaining the abnormality degree is: According to the distribution of the voltage data of each battery cell in the current time period, the voltage abnormality degree of each battery cell is obtained; The abnormality degree of each battery cell is obtained according to the abnormality degree of voltage and the unstable degree of charging of each battery cell; wherein the abnormality degree of voltage and the unstable degree of charging are both positively correlated with the abnormality degree.

6. A method for safety monitoring and data storage of an energy storage power station as claimed in claim 5, characterized in that: The method for obtaining the voltage abnormality degree is: For any battery cell, the standard voltage data range of the battery cell is taken as the target range, and the voltage data of the battery cell in the current time period that exceeds the target range is taken as abnormal voltage data; Acquire the quantity of abnormal voltage data as a first quantity; Obtaining a standard deviation of the voltage data of the battery cell within a specified time period as a first fluctuation value; The product of the first number and the first fluctuation value is used as the voltage abnormality degree of the battery cell.

7. A method for safety monitoring and data storage of an energy storage power station according to claim 1, characterized in that: The method for obtaining the comprehensive abnormality index is: For any battery module, the overall abnormality degree of the battery module is obtained according to the abnormality degree of the battery cells in the battery module; For any battery cell in the battery module, each voltage data of the battery cell in the current time period and the temperature data at the same time are constructed as a coordinate point, mapped to a two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitting line is used as the first relationship value of the battery cell; wherein the voltage data is used as the horizontal axis and the temperature data is used as the vertical axis; taking the average of the first relationship values ​​of all battery cells in the battery module as the temperature influence value of the battery module; Each voltage data of the battery cell in the current time period and the humidity data at the same time are constructed as a coordinate point, mapped to a two-dimensional coordinate system for straight line fitting, and the absolute value of the slope of the fitting line is used as the second relationship value of the battery cell; wherein the voltage data is used as the horizontal axis and the humidity data is used as the vertical axis; taking the average of the second relationship values ​​of all battery cells in the battery module as the humidity influence value of the battery module; The overall abnormality degree, temperature impact value and humidity impact value of the battery module are multiplied and normalized to obtain a comprehensive abnormality index.

8. A method for safety monitoring and data storage of an energy storage power station as claimed in claim 7, characterized in that: The method for obtaining the overall abnormality degree is: For any battery module, obtain the average abnormality level of all battery cells in the battery module as the reference abnormality level of the battery module; Acquire the number of battery cells in the battery module whose abnormality degree is greater than a reference abnormality degree as a second number; The result of normalizing the product of the reference abnormality level and the second quantity is taken as the overall abnormality level of the battery module.

9. A method for safety monitoring and data storage of an energy storage power station according to claim 1, characterized in that: The method for judging whether the battery module is safe according to the comprehensive abnormality index and obtaining abnormal data and normal data for storage is: When the comprehensive abnormality index is greater than the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be unsafe; When the comprehensive abnormality index is less than or equal to the preset comprehensive abnormality index threshold, the corresponding battery module is judged to be safe; When the battery module is unsafe, the data in the corresponding battery module are regarded as abnormal data; When the battery module is safe, the data in the corresponding battery module are regarded as normal data; During the storage process, normal data is directly stored in the database, and abnormal data is marked and then stored in the specified location.

10. A safety monitoring and data storage system for an energy storage power station, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When executing the computer program, the processor implements the steps of the energy storage power station safety monitoring and data storage method described in any one of claims 1 to 9.

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