An intelligent energy storage EMS data acquisition system

Abstract

The present invention provides an energy storage EMS data intelligent acquisition system. First, a data acquisition module is used to collect and store first state parameter information of the energy storage system, and the first state parameter information is transmitted to a data comparison module. Secondly, after second state parameter information is generated by the data comparison module, it is used to compare the correlation with the first state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to a curve generation module. Then, the curve generation module obtains a first fitting relationship according to a set curve fitting, and then transmits the first fitting relationship to a data transmission module. Finally, the data transmission module generates a first transmission instruction and sends it to the background. In this way, the transmission of the energy storage system operation parameter data can be realized, the accuracy of data analysis can be improved, and the transmission data can be compressed, so as to achieve the effect of reducing the transmission traffic cost and the cloud maintenance cost.

Description

Technical Field

[0001] The present invention relates to the field of energy storage systems, and more specifically, to an energy storage EMS data intelligent acquisition system. Background Art

[0002] As is well known in the industry, energy storage systems primarily consist of a battery management system (BMS), an energy management system (EMS), battery packs, a power storage converter (PCS), and other electrical equipment. The EMS, as the core component of an energy storage system, is responsible for coordinating and managing its various components.

[0003] The energy storage EMS collects real-time data from the energy storage system, including key parameters such as the battery's state of charge (SOC), state of health (SOH), ambient temperature, charge and discharge current, and voltage, and uses advanced algorithms for data processing and optimization analysis. Based on this data and analysis results, the EMS enables intelligent control of energy storage equipment, including optimization of charge and discharge strategies, fault diagnosis and maintenance, and communication and interaction with other systems.

[0004] However, the need to collect and transmit energy storage system operating parameters in real time generates a massive amount of data, leading to high transmission traffic and cloud maintenance costs. Currently, there are solutions for selectively transmitting operating parameters, but missing data can affect the accuracy of data analysis. Therefore, there is an urgent need for intelligent data collection technology for energy storage EMS that can effectively reduce data transmission volume and costs. Summary of the Invention

[0005] In view of the above problems, the purpose of the present invention is to provide an intelligent energy storage EMS data acquisition system. First, the first state parameter information of the energy storage system is collected and stored by the data acquisition module, and the first state parameter information is transmitted to the data comparison module; secondly, after the second state parameter information is generated by the data comparison module, it is used to compare the correlation with the first state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to the curve generation module; then, the curve generation module is used to fit the set curve to obtain a first fitting relationship, and then the first fitting relationship is transmitted to the data transmission module; finally, the data transmission module is used to generate a first transmission instruction and send it to the background; thus, the transmission of the energy storage system operating parameter data can be realized, the accuracy of data analysis can be improved, and the transmission data can be compressed, thereby reducing the transmission traffic cost and cloud maintenance cost.

[0006] The present invention provides an energy storage EMS data intelligent acquisition system, the system comprising:

[0007] The data acquisition module is used to collect and store first state parameter information of the energy storage system, and transmit the first state parameter information to the data comparison module;

[0008] The data comparison module is used to compare the correlation between the first state parameter information and the second state parameter information after generating the second state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to the curve generation module;

[0009] The curve generation module is configured to obtain a first fitting relationship according to the stored state parameter record of the energy storage system and the first state parameter information according to a set curve fitting, and then transmit the first fitting relationship to the data transmission module;

[0010] The data transmission module is used to generate a first transmission instruction according to the first state parameter information and the first fitting relationship, and send it to the background.

[0011] In this solution, the data acquisition module includes:

[0012] The data acquisition unit is used to collect the operating data of the energy storage system, including the charge and discharge status, battery power, charge and discharge current, charge and discharge battery voltage or battery temperature;

[0013] The data storage unit sets a corresponding storage quantity according to the type of operating data, and uses a first-in-first-out storage rule to store the first state parameter information.

[0014] In this solution, the data comparison module includes:

[0015] The data estimation unit is configured to estimate the second state parameter information according to the second fitting relationship, and transmit the second state parameter information to the threshold generation unit and the data comparison unit;

[0016] The threshold value generating unit is configured to obtain a first state parameter threshold value for data comparison according to the type of the operating data and the second state parameter information, and transmit the first state parameter threshold value to the data comparison unit;

[0017] The data comparison unit compares the difference between the first state parameter information and the second state parameter information with the magnitude relationship of the first state parameter threshold to obtain a correlation comparison result between the first state parameter information and the second state parameter information.

[0018] In this solution, the curve generation module includes:

[0019] The curve fitting unit is configured to obtain a first fitting relationship according to the stored state parameter record of the energy storage system and the first state parameter information and according to a set curve fitting library;

[0020] The correlation coefficient unit is used to calculate a first correlation coefficient between the first fitting relationship and the stored state parameter record of the energy storage system.

[0021] In this solution, the data transmission module includes:

[0022] The first instruction generating unit is configured to obtain a first transmission instruction according to the first state parameter information and the first fitting relationship in accordance with a set data frame format;

[0023] The data transmission unit is configured to send the first transmission instruction to the background in a wired network transmission or a wireless network transmission manner.

[0024] This plan also includes:

[0025] Data exception processing module;

[0026] When the correlation comparison between the first state parameter information and the second state parameter information fails, the data anomaly processing module is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module.

[0027] In this solution, the data anomaly processing module includes:

[0028] The data verification unit is configured to determine whether the first state parameter information is abnormal data based on the stored state parameter record of the energy storage system and the first state parameter information;

[0029] The data exception processing unit is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module; if not, the process enters the curve generation module and the data transmission module.

[0030] In this solution, the data verification unit also includes:

[0031] The abnormal threshold generator is used to obtain a first abnormal threshold range according to the stored state parameter records of the energy storage system and the preset abnormal threshold generation rules.

[0032] In this solution, the fitting exception processing module includes:

[0033] The second instruction generating unit is configured to obtain a second transmission instruction according to the first state parameter information and a set abnormal data frame format.

[0034] Fitting exception handling module;

[0035] When the first correlation coefficients of all fitting rules are lower than a preset correlation coefficient threshold, the fitting exception processing module is used to generate a second transmission instruction according to the first state parameter information, and transmit the second transmission instruction to the data transmission unit of the data transmission module.

[0036] This plan also includes:

[0037] The present invention provides an energy storage EMS data intelligent acquisition system. First, a data acquisition module is used to collect and store first state parameter information of the energy storage system, and the first state parameter information is transmitted to a data comparison module. Secondly, after second state parameter information is generated by the data comparison module, it is used to compare the correlation with the first state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to a curve generation module. Then, the curve generation module obtains a first fitting relationship according to a set curve fitting, and then transmits the first fitting relationship to a data transmission module. Finally, the data transmission module generates a first transmission instruction and sends it to the background. In this way, the transmission of the energy storage system operation parameter data can be realized, the accuracy of data analysis can be improved, and the transmission data can be compressed, so as to achieve the effect of reducing the transmission traffic cost and the cloud maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope.

[0039] Figure 1 A schematic diagram of an energy storage EMS data intelligent acquisition system according to the present invention is shown;

[0040] Figure 2 shows a block diagram of a data acquisition module provided by an embodiment of the present invention;

[0041] Figure 3 shows a block diagram of a data comparison module provided by an embodiment of the present invention;

[0042] Figure 4 shows a block diagram of a curve generation module provided by an embodiment of the present invention;

[0043] Figure 5 A block diagram of a data transmission module provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0045] Unless otherwise defined, all terms (including technical and scientific terms) used in the embodiments of the present invention have the same meaning as commonly understood by those skilled in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant technology, and should not be interpreted in an idealized or extremely formal sense, unless explicitly defined in this manner in the embodiments of the present invention.

[0046] The words "first", "second" and similar terms used in the embodiments of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "one", "an" or "the" do not indicate a quantity limitation, but rather indicate the existence of at least one. Similarly, words such as "include" or "comprise" mean that the elements or objects preceding the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The steps before or after the method of the embodiment of the present invention do not necessarily have to be performed in exact order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0047] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0048] Figure 1 A schematic diagram of an energy storage EMS data intelligent acquisition system of the present invention is shown.

[0049] like Figure 1 As shown, the present invention discloses an energy storage EMS data intelligent acquisition system, the system comprising:

[0050] The data acquisition module 101 is used to collect and store first state parameter information of the energy storage system and transmit the first state parameter information to the data comparison module;

[0051] The data comparison module 102 is used to compare the correlation between the first state parameter information and the second state parameter information after generating the second state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to the curve generation module;

[0052] The curve generation module 103 is configured to obtain a first fitting relationship according to the stored state parameter record of the energy storage system and the first state parameter information according to a set curve fitting, and then transmit the first fitting relationship to the data transmission module;

[0053] The data transmission module 104 is configured to generate a first transmission instruction according to the first state parameter information and the first fitting relationship, and send the first transmission instruction to the backend.

[0054] It should be noted that the data acquisition module first collects the working state parameters of the energy storage system through the corresponding detection circuit or sensor according to the set time period, which are also called operating data, including but not limited to the charging and discharging state, battery power, charging and discharging current, charging and discharging battery voltage or battery temperature, and records them as the first state parameter information. The data acquisition module then stores and records the different types of data in the first state parameter information according to the set storage space, and can obtain battery power records, charging and discharging current records, charging and discharging battery voltage records, battery temperature records, etc., that is, the state parameter records of the energy storage system. The data comparison module first calculates the estimated value of the working state parameter of the energy storage system based on the fitting relationship sent to the background in the previous round, that is, the second fitting relationship, that is, the second state parameter information. The data comparison module then compares the correlation between the first state parameter information and the second state parameter information according to the set correlation comparison rules. If the correlation comparison passes, it indicates that the similarity between the first state parameter information and the second state parameter information meets the set requirements. This means that the second state parameter information can be used to represent the first state parameter information in the backend. In other words, the backend can calculate the operating state parameters of the energy storage system using the second fitting equation. In this case, the energy storage EMS does not need to send the first state parameter information, thereby ensuring the accuracy of the operating state parameter data while reducing data transmission volume, transmission traffic costs, and cloud maintenance costs. If the correlation comparison fails, it indicates that the first state parameter information and the second state parameter information differ significantly, and the first state parameter information needs to be transmitted to the backend to ensure data accuracy. In this embodiment, a first fitting equation is generated by the curve generation module and used to replace the first state parameter information for transmission to the backend. The curve generation module generates the first fitting equation based on the energy storage system state parameter records and the first state parameter information according to a set curve fitting rule. Curve fitting rules include, but are not limited to, linear fitting, quadratic fitting, polynomial fitting, exponential fitting, and logarithmic fitting. When the correlation meets the set requirements, the similarity value of the first state parameter information can be calculated using the first fitting equation. The data transmission module generates a first transmission instruction based on the first fitting equation, in accordance with the specified data frame format and the type of operating status parameter, for transmission to the backend. This embodiment uses the fitting equation to represent the data to be transmitted. The accuracy of the parameter data is ensured by comparing the correlation between the collected parameter data and the estimated value of the fitting equation. If the newly collected parameter data is similar to the estimated value of the fitting equation, no transmission is required, thereby reducing transmission traffic costs and cloud maintenance costs.

[0055] Figure 2 shows a block diagram of a data acquisition module provided by an embodiment of the present invention;

[0056] According to an embodiment of the present invention, Figure 2As shown, the data acquisition module includes:

[0057] The data acquisition unit 201 is used to collect the operating data of the energy storage system, including the charge and discharge status, battery power, charge and discharge current, charge and discharge battery voltage or battery temperature;

[0058] The data storage unit 202 sets a corresponding storage quantity according to the type of operating data, and uses a first-in-first-out storage rule to store the first state parameter information.

[0059] It should be noted that the data acquisition module is used to collect and store the operating data of the energy storage system, and includes a data acquisition unit and a data storage unit. The data acquisition unit is a parameter detection circuit or sensor, which is used to collect the working status parameters of the energy storage system, including but not limited to the charging and discharging status, battery power, charging and discharging current, charging and discharging battery voltage or battery temperature. The data storage unit is set with corresponding storage space according to the characteristics of each operating data; for example, the storage space for charging and discharging current or charging and discharging voltage is 20 data, and the storage space for battery temperature is 50 data. In addition, the storage space adopts a first-in-first-out storage rule, that is, the earliest stored data is moved out of the storage space first, so that the data retained in the storage space are all the latest data, which can accurately reflect the real-time operation status of the energy storage system.

[0060] Figure 3 shows a block diagram of a data acquisition module provided by an embodiment of the present invention;

[0061] According to an embodiment of the present invention, Figure 3 As shown, the data comparison module includes:

[0062] The data estimation unit 301 is configured to estimate the second state parameter information according to the second fitting relationship, and transmit the second state parameter information to the threshold generation unit and the data comparison unit;

[0063] The threshold value generating unit 302 is configured to obtain a first state parameter threshold value for data comparison according to the type of operating data and the second state parameter information, and transmit the first state parameter threshold value to the data comparison unit;

[0064] The data comparison unit 303 compares the difference between the first state parameter information and the second state parameter information with the magnitude relationship of the first state parameter threshold to obtain the correlation comparison result between the first state parameter information and the second state parameter information.

[0065] It should be noted that the data estimation unit calculates an estimated value of the energy storage system's operating state parameter, namely the second state parameter information, based on the fitting relationship equation sent to the backend in the previous round (i.e., the second fitting relationship equation). This is used to calculate the state parameter threshold and compare the data. The threshold generation unit sets an error range based on the type of operating data and, combined with the second state parameter information, determines a first state parameter threshold, which represents the allowable deviation between the first and second state parameter information. For example, if the error range set for the battery temperature is 1%, when the temperature value in the second state parameter information is 25°C, the first state parameter threshold is 0.25°C. The data comparison unit calculates the difference between the first and second state parameter information and compares this difference with the first state parameter threshold. If the difference is less than the first state parameter threshold, the deviation between the first and second state parameter information is small, and the correlation comparison is considered passed. If the difference is greater than the first state parameter threshold, the deviation between the first and second state parameter information is large, and the correlation comparison is considered failed. This embodiment sets different error ranges according to the data type to improve the accuracy of the data.

[0066] Figure 4 shows a block diagram of a data acquisition module provided by an embodiment of the present invention;

[0067] According to an embodiment of the present invention, Figure 4 As shown, the curve generation module includes:

[0068] The curve fitting unit 401 is configured to obtain a first fitting equation according to the stored state parameter record of the energy storage system and the first state parameter information and according to a set curve fitting library;

[0069] The correlation coefficient unit 402 is used to calculate a first correlation coefficient between the first fitting relationship and the stored state parameter record of the energy storage system.

[0070] It should be noted that the curve fitting unit obtains the first fitting relationship according to the state parameter record of the energy storage system and the first state parameter information in accordance with the set curve fitting library; wherein the curve fitting library includes but is not limited to linear fitting rules, quadratic fitting rules, polynomial fitting rules, exponential fitting rules, logarithmic fitting rules, etc. The correlation coefficient unit is used to calculate the correlation coefficient between the first fitting relationship and the stored state parameter record of the energy storage system, that is, the first correlation coefficient; wherein the first correlation coefficient represents the degree of deviation between the fitting relationship and the recorded data. The closer the correlation coefficient is to 1, the stronger the correlation it represents, that is, the smaller the fitting deviation. In this embodiment, the first state parameter information can be represented by the first fitting relationship only when and only when the first correlation coefficient is greater than 0.99, thereby ensuring the accuracy of the data.

[0071] Figure 5 shows a block diagram of a data acquisition module provided by an embodiment of the present invention;

[0072] According to an embodiment of the present invention, Figure 5 As shown, the data transmission module includes:

[0073] The first instruction generating unit 501 is configured to obtain a first transmission instruction according to the first state parameter information and the first fitting relationship in accordance with a set data frame format;

[0074] The data transmission unit 502 is configured to send the first transmission instruction to the backend according to a wired network transmission or a wireless network transmission method.

[0075] It should be noted that the first instruction generation unit determines the data type code in the first transmission instruction based on the type of operating data in the first state parameter information, and determines the fitting rule code and parameter length of the first transmission instruction based on the fitting rule of the first fitting relationship, thereby obtaining the first transmission instruction. The data transmission unit sends the first transmission instruction to the backend via a wired or wireless network, either by scheduled transmission or immediate transmission.

[0076] According to an embodiment of the present invention, the further embodiment includes:

[0077] Data exception processing module;

[0078] When the correlation comparison between the first state parameter information and the second state parameter information fails, the data anomaly processing module is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module.

[0079] It should be noted that in this embodiment, when the data comparison module determines that the correlation comparison between the first state parameter information and the second state parameter information fails, the first state parameter information is subjected to abnormal data determination according to the set abnormal data determination rules. If the first state parameter information is determined to be abnormal data, it is determined that there is a possibility of collection abnormality. Therefore, exception processing is performed on the first state parameter information in this round. That is, the data does not enter the curve generation module, and the background performs state parameter entry according to the second state parameter information.

[0080] According to an embodiment of the present invention, the data anomaly processing module includes:

[0081] The data verification unit is configured to determine whether the first state parameter information is abnormal data based on the stored state parameter record of the energy storage system and the first state parameter information;

[0082] The data exception processing unit is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module; if not, the process enters the curve generation module and the data transmission module.

[0083] It should be noted that the data anomaly processing module includes a data verification unit and a data anomaly processing unit. The data verification unit is used to determine whether the first state parameter information is abnormal data. First, the abnormal threshold range is obtained based on the stored state parameter records of the energy storage system, and then whether the first state parameter information is within the abnormal threshold range. If so, it indicates that the current first state parameter information is abnormal data. The data anomaly processing unit is used to select whether to enter the curve generation module based on the verification result of the data verification unit. When the first state parameter information is abnormal data, the curve generation module is not entered, that is, the background enters the state parameters according to the second state parameter information; when the first state parameter information is not abnormal data, the curve generation module is entered, that is, the background needs to enter the state parameters according to the generated first fitting relationship.

[0084] According to an embodiment of the present invention, the data verification unit further includes:

[0085] The abnormal threshold generator is used to obtain a first abnormal threshold range according to the stored state parameter records of the energy storage system and the preset abnormal threshold generation rules.

[0086] It should be noted that the abnormality threshold generator obtains the first abnormality threshold range according to the set abnormality threshold generation rules. As an embodiment, the abnormality threshold generator first obtains a first arithmetic mean based on the stored state parameter records of the energy storage system using a weighted average algorithm; then, the first abnormality threshold range is calculated based on the set deviation range. For example, if the first arithmetic mean is 100 units and the deviation range is 30%, the first abnormality threshold range can be less than 70 units or greater than 130 units.

[0087] According to an embodiment of the present invention, the further embodiment includes:

[0088] Fitting exception handling module;

[0089] When the first correlation coefficients of all fitting rules are lower than a preset correlation coefficient threshold, the fitting exception processing module is used to generate a second transmission instruction according to the first state parameter information, and transmit the second transmission instruction to the data transmission unit of the data transmission module.

[0090] It should be noted that in this embodiment, the correlation coefficient of the relationship equation after curve fitting is compared with a preset correlation coefficient threshold. If the correlation coefficients of the relationship equations obtained by all fitting rules in the curve fitting library are lower than the preset correlation coefficient threshold, it means that the fitting relationship equations obtained by all fitting rules in the curve fitting library cannot accurately reflect the first state parameter information, and the fitting is considered to have failed. If the fitting fails, a second transmission instruction is generated based on the first state parameter information and sent to the backend via the data transmission module.

[0091] According to an embodiment of the present invention, the fitting exception processing module includes:

[0092] The second instruction generating unit is configured to obtain a second transmission instruction according to the first state parameter information and a set abnormal data frame format.

[0093] It should be noted that the second instruction generation unit determines the data type code in the second transmission instruction according to the type of running data in the first state parameter information, and determines the transmission data according to the parameter value of the first state parameter information, thereby obtaining the second transmission instruction.

[0094] It is worth mentioning that it also includes:

[0095] a fitting curve generating module, configured to send at least two consecutive second transmission instructions to the first neural network to obtain a first fitting curve;

[0096] The first fitting curve is used to update the curve fitting library.

[0097] It should be noted that sending the second transmission instruction multiple times in succession indicates that the curve fitting is in an abnormal state, meaning that the fitting rules in the curve fitting library are not applicable. In this case, by sending multiple second transmission instructions to the first neural network, the first neural network outputs a first fitting curve. The curve fitting library is updated with the first fitting curve, thereby improving the adaptability of the curve fitting.

[0098] In summary, the present invention provides an energy storage EMS data intelligent acquisition system. First, the data acquisition module collects and stores the first state parameter information of the energy storage system, and transmits the first state parameter information to the data comparison module; secondly, after the second state parameter information is generated by the data comparison module, it is used to compare the correlation with the first state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to the curve generation module; then, the curve generation module obtains a first fitting relationship according to the set curve fitting, and then transmits the first fitting relationship to the data transmission module; finally, the data transmission module generates a first transmission instruction and sends it to the background; thus, the transmission of the energy storage system operation parameter data can be realized, the accuracy of data analysis can be improved, and the transmission data can be compressed, thereby reducing the transmission traffic cost and cloud maintenance cost.

[0099] If the functions are implemented as software modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0100] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An energy storage EMS data intelligent acquisition system, characterized in that: The system comprises: The data acquisition module is used to collect and store first state parameter information of the energy storage system and transmit the first state parameter information to the data comparison module, wherein the first state parameter information is the collected working state parameter of the energy storage system, and the working state parameter includes charge and discharge state, battery power, charge and discharge current, charge and discharge battery voltage or battery temperature; The data comparison module is configured to compare the correlation between the first state parameter information and the second state parameter information after generating the second state parameter information. If the correlation comparison fails, the first state parameter information is transmitted to the curve generation module, wherein the second state parameter information is an estimated value of the working state parameter of the energy storage system calculated according to the second fitting relationship. The curve generation module is configured to obtain a first fitting relationship according to the stored state parameter record of the energy storage system and the first state parameter information according to a set curve fitting, and then transmit the first fitting relationship to the data transmission module; The data transmission module is used to generate a first transmission instruction according to the first state parameter information and the first fitting relationship, and send it to the background; The comparing of the correlation between the first state parameter information and the second state parameter information is specifically as follows: Calculate the difference between the first state parameter information and the second state parameter information; When the difference is not greater than the first state parameter threshold, it is determined that the correlation comparison passes; When the difference is greater than the first state parameter threshold, it is determined that the correlation comparison fails.

2. The energy storage EMS data intelligent acquisition system according to claim 1, characterized in that: The data acquisition module includes: The data acquisition unit is used to collect the operating data of the energy storage system, including the charge and discharge status, battery power, charge and discharge current, charge and discharge battery voltage or battery temperature; The data storage unit sets a corresponding storage quantity according to the type of operating data, and uses a first-in-first-out storage rule to store the first state parameter information.

3. The energy storage EMS data intelligent acquisition system according to claim 1, characterized in that: The data comparison module includes: The data estimation unit is configured to estimate the second state parameter information according to the second fitting relationship, and transmit the second state parameter information to the threshold generation unit and the data comparison unit; The threshold value generating unit is configured to obtain a first state parameter threshold value for data comparison according to the type of the operating data and the second state parameter information, and transmit the first state parameter threshold value to the data comparison unit; The data comparison unit compares the difference between the first state parameter information and the second state parameter information with the magnitude relationship of the first state parameter threshold to obtain a correlation comparison result between the first state parameter information and the second state parameter information.

4. The energy storage EMS data intelligent acquisition system according to claim 1, characterized in that: The curve generation module includes: The curve fitting unit is configured to obtain a first fitting relationship according to the stored state parameter record of the energy storage system and the first state parameter information and according to a set curve fitting library; The correlation coefficient unit is used to calculate a first correlation coefficient between the first fitting relationship and the stored state parameter record of the energy storage system.

5. The energy storage EMS data intelligent acquisition system according to claim 1, characterized in that: The data transmission module includes: The first instruction generating unit is configured to obtain a first transmission instruction according to the first state parameter information and the first fitting relationship in accordance with a set data frame format; The data transmission unit is configured to send the first transmission instruction to the background in a wired network transmission or a wireless network transmission manner.

6. The energy storage EMS data intelligent acquisition system according to claim 1, characterized in that: Also includes: Data exception processing module; When the correlation comparison between the first state parameter information and the second state parameter information fails, the data anomaly processing module is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module.

7. The energy storage EMS data intelligent acquisition system according to claim 6, characterized in that: The data exception processing module includes: The data verification unit is configured to determine whether the first state parameter information is abnormal data based on the stored state parameter record of the energy storage system and the first state parameter information; The data exception processing unit is used to determine whether the first state parameter information is abnormal data. If so, the process does not enter the curve generation module; if not, the process enters the curve generation module and the data transmission module.

8. The energy storage EMS data intelligent acquisition system according to claim 7, characterized in that: The data verification unit further includes: The abnormality threshold generator is used to obtain a first abnormality threshold range according to the stored state parameter records of the energy storage system and the preset abnormality threshold generation rules.

9. The energy storage EMS data intelligent acquisition system according to claim 4, characterized in that: Also includes: Fitting exception handling module; When the first correlation coefficients of all fitting rules are lower than a preset correlation coefficient threshold, the fitting exception processing module is used to generate a second transmission instruction according to the first state parameter information, and transmit the second transmission instruction to the data transmission unit of the data transmission module.

10. The energy storage EMS data intelligent acquisition system according to claim 9, characterized in that: The fitting exception processing module includes: The second instruction generating unit is configured to obtain a second transmission instruction according to the first state parameter information and a set abnormal data frame format.

Images