A digital twin-based energy storage management method and management system

Abstract

The present invention discloses a digital twin-based energy storage management method and a management system thereof, which relate to the technical field of energy storage management, and include a data acquisition unit, a data input unit, a data preprocessing unit, a data parsing unit, a data analysis unit and an execution unit. The method realizes real-time simulation and optimization adjustment of the energy storage system by accurately collecting and processing actual working data and laboratory data. Compared with traditional methods, the system has higher accuracy and applicability, and can better solve the optimization and transparency problems in energy storage management. Through the application of digital twin technology, the system can realize more accurate model prediction and real-time adjustment, so that the performance and stability of the energy storage system are significantly improved, thereby effectively responding to the increasingly complex energy environment and needs.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage management, and specifically to an energy storage management method and a management system thereof based on digital twins. Background Art

[0002] Energy storage management system is a key energy technology that plays an important role in energy storage, distribution and management. With the growing trend of renewable energy and electrification, the demand for energy storage management systems is increasing. As an emerging data-driven modeling method, digital twin technology has gradually attracted attention in the energy field. The concept of digital twin is derived from the "twin" in biology, which refers to the real-time interaction between digital models and actual systems to achieve accurate simulation and optimized management of actual systems. The digital twin technology of energy storage management system aims to achieve accurate prediction and optimized regulation of system performance through digital modeling and simulation of actual energy storage systems.

[0003] However, traditional energy storage management systems have some challenges and shortcomings, including insufficient optimization of physical models. Since the existing twin system operates based on the comparison of two operating data, the data used as samples often cannot fully reflect the changes in existing conditions. In addition, the transparency and interpretability of traditional systems are low, and users often find it difficult to understand the internal working mechanism and decision-making process of the system, resulting in inefficient management and difficulty in troubleshooting problems. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a digital twin-based energy storage management method and a management system thereof, which solves the problems of insufficient optimization of the physical model and low transparency and interpretability of the system mentioned in the background technology.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A digital twin-based energy storage management system, including a data acquisition unit, a data input unit, a data preprocessing unit, a data parsing unit, a data analysis unit and an execution unit;

[0008] The data acquisition unit is used to collect information on the actual working data and actual environmental data of the energy storage battery, and input the collected data into the data preprocessing unit, and the data input unit is used to input the laboratory data of the energy storage battery into the data preprocessing unit;

[0009] The data preprocessing unit cleans the actual working data, actual environment data and laboratory data input by the data acquisition unit and the data input unit, and reorganizes them into a first data group, a second data group, a third data group and a fourth data group, and the data preprocessing unit inputs the first data group, the second data group, the third data group and the fourth data group into the data parsing unit;

[0010] The data analysis unit integrates and calculates the first data group, the second data group, the third data group, and the fourth data group, respectively, so as to obtain the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz, and the laboratory environment reference value Yhjz, and performs secondary integration calculation on the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz, and the laboratory environment reference value Yhjz, so as to generate the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, and calculates the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz to obtain the calibration difference Xzcz, and inputs the calibration difference Xzcz into the data analysis unit;

[0011] The data analysis unit is used to compare the calculated calibration difference Xzcz with a preset first threshold value Y to obtain a first comparison result, and judge whether the current management system needs to be adjusted according to the first comparison result. If the judgment result is that no adjustment is required, the management system continues to run. If the judgment result is that adjustment is required, the calibration difference Xzcz is integrated with the first threshold value Y to obtain a magnitude determination value Ljz, and the magnitude determination value Ljz is compared with a preset second threshold value R to generate a second comparison result, and the adjustment level of the management system is divided according to the second comparison result;

[0012] The execution unit matches the second comparison result with a preset management system adjustment plan, and executes the management system adjustment plan that matches the magnitude. After executing the adjustment plan, the execution unit generates a management log for archiving.

[0013] Preferably, the data acquisition unit includes a first acquisition module and a second acquisition module, wherein the data acquisition unit is used to collect real-time data of the energy storage battery when it is working, and the second acquisition module is used to collect real-time environmental data of the energy storage battery when it is working, wherein the first acquisition module includes a battery voltage sensor, a battery current sensor and a battery temperature sensor, and the second acquisition module includes a temperature sensor, a humidity sensor and an air pressure sensor.

[0014] Preferably, the data preprocessing unit includes a cleaning module and a sorting module, wherein the cleaning module is used to clean and purify the actual working data, actual environment data and laboratory data input into the data preprocessing unit by the data acquisition unit and the data input unit, and the sorting module is used to re-sort the cleaned and purified actual working data, actual environment data and laboratory data into a first data group, a second data group, a third data group and a fourth data group;

[0015] The first data group includes: an actual charge and discharge current value Scdl, an actual charge and discharge voltage value Scdy, an actual power load value Sdfz, and an actual battery temperature value Sdwz, wherein the actual charge and discharge current value Scdl and the actual power load value Sdfz are obtained by a battery current sensor, the actual charge and discharge voltage value Scdy is obtained by a battery voltage sensor, and the actual battery temperature value Sdwz is obtained by a battery temperature sensor;

[0016] The second data group includes: an actual ambient temperature value Swdz, an actual ambient humidity value Ssdz, and an actual ambient air pressure value Sqyz, wherein the actual ambient temperature value Swdz is obtained by a temperature sensor, the actual ambient humidity value Ssdz is obtained by a humidity sensor, and the actual ambient air pressure value Sqyz is obtained by a pressure sensor;

[0017] The third data group includes: a laboratory charge and discharge current value Ycdl, a laboratory charge and discharge voltage value Ycdy, a laboratory power load value Ydfz, and a laboratory battery temperature value Ydwz;

[0018] The fourth data group includes: a laboratory environment temperature value Ywdz, a laboratory environment humidity value Ysdz, and a laboratory environment air pressure value Yqyz.

[0019] Preferably, the data analysis unit calculates and obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz through the following formula;

[0020] Sgzz=exp(a1×Scdl)+log(a2×Scdy)+Sqrt(a3×Sdfz)+tanh(a4×Sdwz);

[0021] Ygzz=exp(b1×Ycdl)+log(b2×Ycdy)+Sqrt(b3×Ydfz)+tanh(b4×Ydwz);

[0022]

[0023]

[0024] In the formula: Scdl is the actual charge and discharge current value, Scdy is the actual charge and discharge voltage value, Sdfz is the actual power load value, Sdwz is the actual battery temperature value, Ycdl is the laboratory charge and discharge current value, Ycdy is the laboratory charge and discharge voltage value, Ydfz is the laboratory power load value, Ydwz is the laboratory battery temperature value, Swdz is the actual ambient temperature value, Ssdz is the actual ambient humidity value, Sqyz is the actual ambient pressure value, Ywdz is the laboratory ambient temperature value, and Ysdz is the experimental Room environment humidity value, Yqyz is the laboratory environment air pressure value, a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are all weight coefficients, and a1≠a2≠a3≠a4≠0, b1≠b2≠b3≠b4≠0, c1≠c2≠c3≠0, d1≠d2≠d3≠0, the specific values ​​of a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are adjusted and set by the user.

[0025] Preferably, the data analysis unit further calculates and obtains the actual adjustment reference value Stjz, the laboratory adjustment reference value Ytjz and the calibration difference Xzcz through the following formula;

[0026]

[0027]

[0028] Xzcz=Stjz-Ytjz;

[0029] In the formula: Sgzz is the actual working reference value, Shjz is the actual environment reference value, Ygzz is the laboratory working reference value, Yhjz is the laboratory environment reference value, e1, e2, m1 and m2 are all weight values, and e1≠e2≠0, m1≠m2≠0, the values ​​of e1, e2, m1 and m2 are adjusted and set by the user.

[0030] Preferably, the data analysis unit includes a first comparison module and a second comparison module, the first comparison module is used to generate a first comparison result, and the second comparison module is used to generate a second comparison result;

[0031] The first comparison result is: when Xzcz≤Y, it means that the current management system does not need to be adjusted; when Xzcz>Y, it means that the current management system needs to be adjusted;

[0032] Where Xzcz is the calibration difference, and Y is the first threshold;

[0033] The second comparison result is:

[0034] When Ljz ≤ R, it represents that the current management system's adjustment level to be adjusted is level one;

[0035] When R < Ljz ≤ R × 103%, it represents that the current management system's adjustment level to be adjusted is level two;

[0036] When Ljz > R × 103%, it represents that the current management system's adjustment level to be adjusted is level three;

[0037] Where Ljz is the magnitude determination value and R is the second threshold;

[0038] The specific calculation formula for the magnitude determination value Ljz is as follows:

[0039]

[0040] In the formula: Xzcz is the calibration difference Xzcz, and Y is the first threshold.

[0041] Preferably, the execution unit includes a matching module, an execution module, and a recording module. Among them, the matching module is used to store the preset management system adjustment plan and adapt the second comparison result to the preset management system adjustment plan. The execution module is used to execute the management system adjustment plan, and the recording module is used to generate an operation log and save the operation log.

[0042] Preferably, the preset management system adjustment plan stored in the matching module is as follows:

[0043] When the management system's adjustment level to be adjusted is level one, increase the charging current and voltage by 5% of the original set value, and increase the charge and discharge process control strategy by within 8% of the original set value;

[0044] When the management system's adjustment level to be adjusted is level two, increase the charging current and voltage by 8% of the original set value, and increase the charge and discharge process control strategy by 11% of the original set value;

[0045] When the management system's adjustment level to be adjusted is level three, increase the single battery capacity by 3%, increase the charging current and voltage by 9.5% of the original set value, and increase the charge and discharge process control strategy by 12.5% of the original set value.

[0046] Preferably, the recording module generates an operation log in the following manner:

[0047] When the management system's adjustment level to be adjusted is level one, generate logs starting with L, denoted as L1, L2, L3,..., Ln respectively;

[0048] When the management system's adjustment level to be adjusted is level two, generate logs starting with C, denoted as C1, C2, C3,..., Cn respectively;

[0049] When the management system's adjustment level is level three, logs starting with H are generated, which are recorded as H1, H2, H3, ..., Hn.

[0050] This application also includes a digital twin-based energy storage management method, the specific steps are as follows:

[0051] S1. Data collection: Use the data collection unit to collect the actual working data and environmental data of the energy storage battery, and receive the laboratory data provided by the data input unit;

[0052] S2, data preprocessing: the data preprocessing unit cleans and organizes the collected actual working data, actual environment data and laboratory data to form a first data group, a second data group, a third data group and a fourth data group, and transmits them to the data analysis unit;

[0053] S3, data analysis: the data analysis unit integrates and calculates the first data group, the second data group, the third data group and the fourth data group, obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, and performs secondary integration calculation to generate the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, and then calculates the calibration difference Xzcz;

[0054] S4, data analysis: the data analysis unit compares the calibration difference Xzcz with the preset first threshold value Y to generate a first comparison result, then integrates the calibration difference Xzcz and the first threshold value Y to generate a magnitude determination value Ljz, then compares the magnitude determination value Ljz with the preset second threshold value R to generate a second comparison result, and divides the adjustment level of the management system according to the result;

[0055] S5. Execute adjustment: the execution unit matches the preset management system adjustment plan according to the second comparison result, executes the corresponding management system adjustment, and generates a management log for archiving.

[0056] (III) Beneficial effects

[0057] The present invention provides a digital twin-based energy storage management method and management system thereof, which have the following beneficial effects:

[0058] (1) The energy storage management method and management system based on digital twins realizes real-time simulation and optimization adjustment of the energy storage system by accurately collecting and processing actual working data and laboratory data. Compared with traditional methods, the system has higher accuracy and applicability, and can better solve the optimization and transparency problems in energy storage management. Through the application of digital twin technology, the system can achieve more accurate model prediction and real-time adjustment, which significantly improves the performance and stability of the energy storage system, thereby effectively responding to the increasingly complex energy environment and needs.

[0059] (2) The energy storage management method and management system based on digital twins can generate a calibration difference Xzcz by calculating the difference between the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, which is used to evaluate the calibration status of the system. The generation of the calibration difference Xzcz helps the system to timely discover and correct possible deviations and errors, thereby improving the accuracy and stability of the system. When calculating the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, the influence of actual working data, actual environmental data and laboratory data is comprehensively considered, making the system more comprehensive and accurate in regulating the energy storage system. Such comprehensiveness helps the system better understand the working status and environmental conditions of the energy storage system, and improves the intelligence and adaptability of the system.

[0060] (3) The energy storage management method and management system based on digital twins adjusts the management system according to the specific conditions and needs of different adjustment levels, so that the system can better meet the needs of different scenarios, improve the flexibility and adaptability of the system, and thus improve the overall performance and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 The figure is a flow chart of the system of the present invention.

[0062] Figure 2 It is a step diagram of the method of the present invention.

[0063] In the figure: 1. data acquisition unit; 2. data input unit; 3. data preprocessing unit; 4. data parsing unit; 5. data analysis unit; 6. execution unit; 101. first acquisition module; 102. second acquisition module; 301. cleaning module; 302. sorting module; 501. first comparison module; 502. second comparison module; 601. matching module; 602. execution module; 603. recording module. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0065] Example 1

[0066] See also Figure 1 , a digital twin-based energy storage management system, comprising a data acquisition unit 1, a data input unit 2, a data preprocessing unit 3, a data parsing unit 4, a data analysis unit 5 and an execution unit 6;

[0067] The data acquisition unit 1 is used to collect information about the actual working data and actual environmental data of the energy storage battery, and input the collected data into the data preprocessing unit 3. The data input unit 2 is used to input the laboratory data of the energy storage battery into the data preprocessing unit 3.

[0068] The data preprocessing unit 3 cleans the actual working data, actual environment data and laboratory data input by the data acquisition unit 1 and the data input unit 2, and reorganizes them into a first data group, a second data group, a third data group and a fourth data group, and the data preprocessing unit 3 inputs the first data group, the second data group, the third data group and the fourth data group into the data parsing unit 4;

[0069] The data analysis unit 4 integrates and calculates the first data group, the second data group, the third data group and the fourth data group respectively, so as to obtain the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, and performs secondary integration calculation on the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, so as to generate the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, and calculates the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz to obtain the calibration difference Xzcz, and inputs the calibration difference Xzcz into the data analysis unit 5;

[0070] The data analysis unit 5 is used to compare the calculated calibration difference Xzcz with the preset first threshold value Y, so as to obtain a first comparison result, and judge whether the current management system needs to be adjusted according to the first comparison result. If the judgment result is that no adjustment is required, the management system continues to run. If the judgment result is that adjustment is required, the calibration difference Xzcz is integrated with the first threshold value Y to obtain a magnitude determination value Ljz, and the magnitude determination value Ljz is compared with the preset second threshold value R to generate a second comparison result, and the adjustment level of the management system is divided according to the second comparison result;

[0071] The execution unit 6 matches the second comparison result with a preset management system adjustment plan, and executes the management system adjustment plan that matches the magnitude. After executing the adjustment plan, the execution unit 6 generates a management log for archiving.

[0072] In this embodiment: the data acquisition unit 1 collects and inputs actual working data and environmental data into the data preprocessing unit to ensure the comprehensiveness and accuracy of the data, thereby providing real-time data support for the digital twin energy storage management system, so that the system can accurately simulate the actual working environment and realize the accurate collection of the actual working data and environmental data of the energy storage battery, providing a reliable basis for subsequent data processing and analysis.

[0073] The data input unit 2 inputs the laboratory data into the data preprocessing unit, compares and integrates it with the actual working data to form a complete data set, makes full use of the laboratory test data, improves the accuracy and applicability of the digital twin model, provides more reference basis for system optimization, inputs the laboratory data of the energy storage battery, supplements and enriches the data source of the system, and enhances the integrity and credibility of the model.

[0074] The data preprocessing unit 3 integrates and formats data from different sources, generates a standard data set that can be processed by the data parsing unit, cleans and organizes the collected data, ensures the accuracy and consistency of the data, and provides a reliable basis for subsequent data parsing and analysis.

[0075] The data analysis unit 4 performs a comprehensive analysis on the data set, extracts useful information, and provides data support for the real-time prediction and optimization of the system. By integrating the calculation and analysis of the data set, the actual working reference value Sgzz and the laboratory adjustment reference value Ytjz are obtained, providing a specific basis for the optimization and adjustment of the system.

[0076] The data analysis unit 5 and the execution unit 6 automatically determine whether the system needs to be adjusted based on the data analysis results and preset rules, and execute the corresponding management system adjustment plan. By comparing and adjusting with the preset thresholds, automatic adjustment and optimization of the management system are achieved, thereby improving the system's adaptability and performance stability.

[0077] The energy storage management system based on digital twins realizes real-time simulation and optimization adjustment of energy storage systems through accurate collection and processing of actual working data and laboratory data. Compared with traditional methods, the system has higher accuracy and applicability, and can better solve the optimization and transparency problems in energy storage management. Through the application of digital twin technology, the system can achieve more accurate model prediction and real-time adjustment, which significantly improves the performance and stability of energy storage systems, and effectively responds to the increasingly complex energy environment and needs.

[0078] Example 2

[0079] Please refer to Figure 1 The data acquisition unit 1 includes a first acquisition module 101 and a second acquisition module 102, wherein the data acquisition unit 1 is used to collect real-time data when the energy storage battery is working, and the second acquisition module 102 is used to collect real-time environmental data when the energy storage battery is working, wherein the first acquisition module 101 includes a battery voltage sensor, a battery current sensor and a battery temperature sensor, and the second acquisition module 102 includes a temperature sensor, a humidity sensor and an air pressure sensor.

[0080] In this embodiment: through the combination of the first acquisition module 101 and the second acquisition module 102, the real-time data of the energy storage battery when working and the surrounding environment are fully monitored and collected, so that the system can fully understand the working state and surrounding environmental conditions of the energy storage system. Through the application of sensors such as battery voltage sensors, battery current sensors and battery temperature sensors, the key parameters of the voltage, current and temperature of the energy storage battery can be monitored in real time, thereby improving the accuracy and precision of the data. The second acquisition module 102 includes a temperature sensor, a humidity sensor and an air pressure sensor. These sensors can timely obtain data such as temperature, humidity and air pressure of the environment around the energy storage battery, which helps the system to more comprehensively consider the impact of environmental factors on the performance of the energy storage system.

[0081] Through comprehensive monitoring and collection of real-time data of energy storage batteries and environmental data, the system can adjust and optimize more accurately, achieve precise management and control of the energy storage system, and further improve the performance and efficiency of the system.

[0082] Example 3

[0083] Please refer to Figure 1The data preprocessing unit 3 includes a cleaning module 301 and a sorting module 302, wherein the cleaning module 301 is used to clean and purify the actual working data, actual environment data and laboratory data input into the data preprocessing unit 3 by the data acquisition unit 1 and the data input unit 2, and the sorting module 302 is used to re-sort the cleaned and purified actual working data, actual environment data and laboratory data into a first data group, a second data group, a third data group and a fourth data group;

[0084] The first data group includes: an actual charge and discharge current value Scdl, an actual charge and discharge voltage value Scdy, an actual power load value Sdfz, and an actual battery temperature value Sdwz, wherein the actual charge and discharge current value Scdl and the actual power load value Sdfz are obtained by a battery current sensor, the actual charge and discharge voltage value Scdy is obtained by a battery voltage sensor, and the actual battery temperature value Sdwz is obtained by a battery temperature sensor;

[0085] The second data group includes: an actual ambient temperature value Swdz, an actual ambient humidity value Ssdz, and an actual ambient air pressure value Sqyz, wherein the actual ambient temperature value Swdz is obtained by a temperature sensor, the actual ambient humidity value Ssdz is obtained by a humidity sensor, and the actual ambient air pressure value Sqyz is obtained by an air pressure sensor;

[0086] The third data group includes: laboratory charge and discharge current value Ycdl, laboratory charge and discharge voltage value Ycdy, laboratory power load value Ydfz and laboratory battery temperature value Ydwz;

[0087] The fourth data group includes: a laboratory environment temperature value Ywdz, a laboratory environment humidity value Ysdz, and a laboratory environment air pressure value Yqyz.

[0088] In this embodiment: the actual working data, actual environment data and laboratory data are cleaned and purified by the cleaning module 301 to remove noise and abnormal values ​​to ensure the accuracy and reliability of the data. Such a data preprocessing process helps to improve the accuracy and credibility of subsequent data analysis and modeling. Through the sorting module 302, the cleaned and purified data is reorganized into a first data group, a second data group, a third data group and a fourth data group, providing a clearer and more orderly data structure for subsequent data analysis and model building. Such a data sorting process helps the system to use data more effectively for analysis and optimization.

[0089] Example 4

[0090] The data analysis unit 4 calculates and obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz through the following formula;

[0091] Sgzz=exp(a1×Scdl)+log(a2×Scdy)+Sqrt(a3×Sdfz)+tanh(a4×Sdwz);

[0092] Ygzz=exp(b1×Ycdl)+log(b2×Ycdy)+Sqrt(b3×Ydfz)+tanh(b4×Ydwz);

[0093]

[0094]

[0095] In the formula: Scdl is the actual charge and discharge current value, Scdy is the actual charge and discharge voltage value, Sdfz is the actual power load value, Sdwz is the actual battery temperature value, Ycdl is the laboratory charge and discharge current value, Ycdy is the laboratory charge and discharge voltage value, Ydfz is the laboratory power load value, Ydwz is the laboratory battery temperature value, Swdz is the actual ambient temperature value, Ssdz is the actual ambient humidity value, Sqyz is the actual ambient pressure value, Ywdz is the laboratory ambient temperature value, and Ysdz is the experimental Room environment humidity value, Yqyz is the laboratory environment air pressure value, a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are all weight coefficients, and a1≠a2≠a3≠a4≠0, b1≠b2≠b3≠b4≠0, c1≠c2≠c3≠0, d1≠d2≠d3≠0, the specific values ​​of a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are adjusted and set by the user.

[0096] In this embodiment: by using complex calculation formulas including functions such as exponents, logarithms, square roots and hyperbolic tangents, the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz can be calculated more accurately, so that the system can more accurately grasp the working status of the energy storage system and the surrounding environmental conditions.

[0097] By comprehensively considering multiple parameters and using different weight coefficients, the system can more comprehensively analyze and evaluate the working conditions and environmental conditions of the energy storage system, providing more reference basis for system optimization and adjustment.

[0098] Through sophisticated data calculation and comprehensive analysis, the system's ability to understand and grasp the energy storage system and environment has been improved, and the system's accuracy and stability have been improved. This enables the system to more accurately predict and optimize the performance of the energy storage system, improving the system's reliability and efficiency.

[0099] Example 5

[0100] Please refer to Figure 1 , the data analysis unit 4 also calculates and obtains the actual adjustment reference value Stjz, the laboratory adjustment reference value Ytjz and the calibration difference Xzcz through the following formula;

[0101]

[0102]

[0103] Xzcz=Stjz-Ytjz;

[0104] In the formula: Sgzz is the actual working reference value, Shjz is the actual environment reference value, Ygzz is the laboratory working reference value, Yhjz is the laboratory environment reference value, e1, e2, m1 and m2 are all weight values, and e1≠e2≠0, m1≠m2≠0, the values ​​of e1, e2, m1 and m2 are adjusted and set by the user.

[0105] In this embodiment, by calculating the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz through formula, the system can more accurately evaluate the working state and environmental conditions of the energy storage system, so that the system can be adjusted and optimized more accurately, improving the performance and efficiency of the energy storage system.

[0106] By adjusting the weight values ​​e1, e2, m1 and m2, users can flexibly set the importance of different parameters according to actual conditions, so that the system can better adapt to different working environments and requirements, and improve the applicability and reliability of the system.

[0107] By calculating the difference between the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, the system can generate a calibration difference Xzcz, which is used to evaluate the calibration status of the system. The generation of the calibration difference Xzcz helps the system to promptly discover and correct possible deviations and errors, thereby improving the accuracy and stability of the system. When calculating the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, the influence of actual working data, actual environmental data and laboratory data is comprehensively considered, making the system more comprehensive and accurate in regulating the energy storage system. Such comprehensiveness helps the system better understand the working status and environmental conditions of the energy storage system, and improves the intelligence and adaptability of the system.

[0108] Example 6

[0109] Please refer to Figure 1 , the data analysis unit 5 includes a first comparison module 501 and a second comparison module 502, the first comparison module 501 is used to generate a first comparison result, and the second comparison module 502 is used to generate a second comparison result;

[0110] The first comparison result is: when Xzcz ≤ Y, it means that the current management system does not need to be adjusted; when Xzcz > Y, it means that the current management system needs to be adjusted;

[0111] where Xzcz is the calibration difference and Y is the first threshold;

[0112] The second comparison result is:

[0113] when Ljz ≤ R, it means that the current adjustment level of the management system is level one;

[0114] when R < Ljz ≤ R × 103%, it means that the current adjustment level of the management system is level two;

[0115] when Ljz > R × 103%, it means that the current adjustment level of the management system is level three;

[0116] where Ljz is the magnitude determination value and R is the second threshold;

[0117] The specific calculation formula for the magnitude determination value Ljz is as follows:

[0118]

[0119] In the formula: Xzcz is the calibration difference Xzcz, and Y is the first threshold.

[0120] The execution unit 6 includes a matching module 601, an execution module 602, and a recording module 603. The matching module 601 is used to store the preset management system adjustment plan and adapt the second comparison result to the preset management system adjustment plan. The execution module 602 is used to execute the management system adjustment plan, and the recording module 603 is used to generate an operation log and save the operation log.

[0121] The preset management system adjustment plan stored in the matching module 601 is as follows:

[0122] When the adjustment level of the management system is level one, increase the charging current and voltage by 5% of the original set value, and increase the charge and discharge process control strategy by 8% of the original set value;

[0123] When the adjustment level of the management system is level two, increase the charging current and voltage by 8% of the original set value, and increase the charge and discharge process control strategy by 11% of the original set value;

[0124] When the adjustment level of the management system is level three, increase the single battery capacity by 3%, increase the charging current and voltage by 9.5% of the original set value, and increase the charge and discharge process control strategy by 12.5% of the original set value.

[0125] The recording module 603 generates an operation log in the following manner:

[0126] When the management system is at level one, a log starting with L is generated, which are recorded as L1, L2, L3, ..., Ln.

[0127] When the management system is at level 2, a log starting with C is generated, which are recorded as C1, C2, C3, ..., Cn.

[0128] When the management system's adjustment level is level three, logs starting with H are generated, which are recorded as H1, H2, H3, ..., Hn.

[0129] In this embodiment: the first comparison module 501 and the second comparison module 502 can generate real-time comparison results. According to the calibration difference Xzcz and the magnitude determination value Ljz, the system can quickly and accurately determine whether the current management system needs to be adjusted and the adjustment level. This real-time analysis can enable the system to respond more flexibly to different working conditions and environmental changes, thereby improving the intelligence level and response speed of the management system.

[0130] The calculation formula of the magnitude judgment value Ljz provides a method for the system to objectively evaluate the system calibration status, which helps managers to promptly discover system problems and take corresponding measures to adjust and optimize the system, thereby improving the stability and reliability of the system.

[0131] The matching module 601 can perform intelligent matching according to the preset management system adjustment plan and the second comparison result, and the execution module 602 can execute the corresponding adjustment plan according to the matching result. Such intelligent matching and execution can make the management system more automated and intelligent, reduce the need for manual intervention, and improve management efficiency and accuracy.

[0132] The recording module 603 can generate and save detailed operation logs. This recording method helps managers understand the operating status and adjustment history of the system, provides an important reference for the continuous optimization of the system, and also improves the traceability and transparency of the system.

[0133] By adjusting the management system according to the specific circumstances and needs of different adjustment levels, the system can better meet the needs of different scenarios, improve the flexibility and adaptability of the system, and thus improve the overall performance and stability of the system.

[0134] This application also provides a method for energy storage management based on digital twins, please refer to Figure 2 , the specific steps are as follows:

[0135] S1, data collection: using the data collection unit 1 to collect the actual working data and environmental data of the energy storage battery, and receiving the laboratory data provided by the data input unit 2;

[0136] S2, data preprocessing: the data preprocessing unit 3 cleans and organizes the collected actual working data, actual environment data and laboratory data to form a first data group, a second data group, a third data group and a fourth data group, and transmits them to the data analysis unit 4;

[0137] S3, data analysis: the data analysis unit 4 integrates and calculates the first data group, the second data group, the third data group and the fourth data group, obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, and performs secondary integration calculation to generate the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, and then calculates the calibration difference Xzcz;

[0138] S4, data analysis: the data analysis unit 5 compares the calibration difference Xzcz with the preset first threshold value Y to generate a first comparison result, then integrates the calibration difference Xzcz and the first threshold value Y to generate a magnitude determination value Ljz, then compares the magnitude determination value Ljz with the preset second threshold value R to generate a second comparison result, and divides the adjustment level of the management system according to the result;

[0139] S5. Execute adjustment: the execution unit 6 matches the preset management system adjustment plan according to the second comparison result, executes the corresponding management system adjustment, and generates a management log for archiving.

[0140] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital twin-based energy storage management system, comprising a data acquisition unit (1), a data input unit (2), a data preprocessing unit (3), a data parsing unit (4), a data analysis unit (5) and an execution unit (6), characterized in that: The data acquisition unit (1) is used to collect information on actual working data and actual environmental data of the energy storage battery, and input the collected data into the data preprocessing unit (3); the data input unit (2) is used to input laboratory data of the energy storage battery into the data preprocessing unit (3); The data preprocessing unit (3) cleans the actual working data, actual environment data and laboratory data input by the data acquisition unit (1) and the data input unit (2), and reorganizes them into a first data group, a second data group, a third data group and a fourth data group, and the data preprocessing unit (3) inputs the first data group, the second data group, the third data group and the fourth data group into the data analysis unit (4); The data analysis unit (4) integrates and calculates the first data group, the second data group, the third data group and the fourth data group respectively, thereby obtaining an actual working reference value Sgzz, an actual environment reference value Shjz, a laboratory working reference value Ygzz and a laboratory environment reference value Yhjz, and performs secondary integration calculation on the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, thereby generating an actual adjustment reference value Stjz and a laboratory adjustment reference value Ytjz, and calculates the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz to obtain a calibration difference Xzcz, and inputs the calibration difference Xzcz into the data analysis unit (5); the data analysis unit (4) obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz by calculating the following formula; In the formula: Scdl is the actual charge and discharge current value, Scdy is the actual charge and discharge voltage value, Sdfz is the actual power load value, Sdwz is the actual battery temperature value, Ycdl is the laboratory charge and discharge current value, Ycdy is the laboratory charge and discharge voltage value, Ydfz is the laboratory power load value, Ydwz is the laboratory battery temperature value, Swdz is the actual ambient temperature value, Ssdz is the actual ambient humidity value, Sqyz is the actual ambient pressure value, Ywdz is the laboratory ambient temperature value, and Ysdz is the experimental Room environment humidity value, Yqyz is the laboratory environment pressure value, a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are all weight coefficients, and a1≠a2≠a3≠a4≠0, b1≠b2≠b3≠b4≠0, c1≠c2≠c3≠0, d1≠d2≠d3≠0, the specific values ​​of a1, a2, a3, a4, b1, b2, b3, b4, c1, c2, c3, d1, d2 and d3 are adjusted and set by the user; The data analysis unit (4) also calculates and obtains the actual adjustment reference value Stjz, the laboratory adjustment reference value Ytjz and the calibration difference value Xzcz through the following formula; Where: Sgzz is the actual working reference value, Shjz is the actual environment reference value, Ygzz is the laboratory working reference value, Yhjz is the laboratory environment reference value, e1, e2, m1 and m2 are all weight values, and e1≠e2≠0, m1≠m2≠0, and the values ​​of e1, e2, m1 and m2 are adjusted and set by the user; The data analysis unit (5) is used to compare the calibration difference Xzcz obtained by calculation with a preset first threshold value Y, thereby obtaining a first comparison result, and judging whether the current management system needs to be adjusted according to the first comparison result; if the judgment result is that no adjustment is required, the management system continues to operate; if the judgment result is that adjustment is required, the calibration difference Xzcz and the first threshold value Y are integrated and calculated to obtain a magnitude determination value Ljz, and the magnitude determination value Ljz is compared with a preset second threshold value R to generate a second comparison result, and the adjustment level of the management system is divided according to the second comparison result; The execution unit (6) matches the second comparison result with a preset management system adjustment plan, and executes the management system adjustment plan that matches the magnitude, and after executing the adjustment plan, the execution unit (6) generates a management log for archiving.

2. The energy storage management system based on digital twin according to claim 1, characterized in that: The data acquisition unit (1) comprises a first acquisition module (101) and a second acquisition module (102), wherein the data acquisition unit (1) is used to acquire real-time data when the energy storage battery is working, and the second acquisition module (102) is used to acquire real-time environmental data when the energy storage battery is working, wherein the first acquisition module (101) comprises a battery voltage sensor, a battery current sensor and a battery temperature sensor, and the second acquisition module (102) comprises a temperature sensor, a humidity sensor and an air pressure sensor.

3. The energy storage management system based on digital twin according to claim 2 is characterized in that: The data preprocessing unit (3) comprises a cleaning module (301) and a sorting module (302), wherein the cleaning module (301) is used to clean and purify the actual working data, actual environment data and laboratory data input into the data preprocessing unit (3) by the data acquisition unit (1) and the data input unit (2), and the sorting module (302) is used to re-sort the cleaned and purified actual working data, actual environment data and laboratory data into a first data group, a second data group, a third data group and a fourth data group; The first data group includes: an actual charge and discharge current value Scdl, an actual charge and discharge voltage value Scdy, an actual power load value Sdfz, and an actual battery temperature value Sdwz, wherein the actual charge and discharge current value Scdl and the actual power load value Sdfz are obtained by a battery current sensor, the actual charge and discharge voltage value Scdy is obtained by a battery voltage sensor, and the actual battery temperature value Sdwz is obtained by a battery temperature sensor; The second data group includes: an actual ambient temperature value Swdz, an actual ambient humidity value Ssdz, and an actual ambient air pressure value Sqyz, wherein the actual ambient temperature value Swdz is obtained by a temperature sensor, the actual ambient humidity value Ssdz is obtained by a humidity sensor, and the actual ambient air pressure value Sqyz is obtained by a pressure sensor; The third data group includes: a laboratory charge and discharge current value Ycdl, a laboratory charge and discharge voltage value Ycdy, a laboratory power load value Ydfz, and a laboratory battery temperature value Ydwz; The fourth data group includes: a laboratory environment temperature value Ywdz, a laboratory environment humidity value Ysdz, and a laboratory environment air pressure value Yqyz.

4. The energy storage management system based on digital twin according to claim 1, characterized in that: The data analysis unit (5) comprises a first comparison module (501) and a second comparison module (502), wherein the first comparison module (501) is used to generate a first comparison result, and the second comparison module (502) is used to generate a second comparison result; The first comparison result is: When When , it means that the current management system needs to be adjusted; Where Xzcz is the calibration difference, and Y is the first threshold; The second comparison result is: when When , it means that the current management system to be adjusted is level one; when When , it means that the current management system to be adjusted is level 2; when When , it means that the current management system to be adjusted is level three; Where Ljz is the magnitude determination value, and R is the second threshold; The specific calculation formula of the magnitude determination value Ljz is as follows: Wherein: Xzcz is the calibration difference Xzcz, and Y is the first threshold.

5. The energy storage management system based on digital twin according to claim 4 is characterized in that: The execution unit (6) comprises a matching module (601), an execution module (602) and a recording module (603), wherein the matching module (601) is used to store a preset management system adjustment plan and to adapt the second comparison result to the preset management system adjustment plan, the execution module (602) is used to execute the management system adjustment plan, and the recording module (603) is used to generate an operation log and save the operation log.

6. The energy storage management system based on digital twin according to claim 5, characterized in that: The matching module (601) stores the preset management system adjustment scheme as follows: When the management system is at the first level, the charging current and voltage are increased by 5% of the original setting value, and the charging and discharging process control strategy is increased by 8% of the original setting value; When the management system is at level 2, the charging current and voltage are increased by 8% of the original setting value, and the charging and discharging process control strategy is increased by 11% of the original setting value; When the management system is adjusted to level three, the capacity of a single battery is increased by 3%, the charging current and voltage are increased by 9.5% of the original set values, and the charge and discharge process control strategy is increased by 12.5% ​​of the original set values.

7. The energy storage management system based on digital twin according to claim 6 is characterized in that: The recording module (603) generates an operation log in the following manner: When the management system is at level 1, logs starting with L are generated and recorded as L1, L2, L3, ..., Ln. When the management system is at level 2, a log starting with C is generated, which are recorded as C1, C2, C3, ..., Cn. When the management system's adjustment level is level three, logs starting with H are generated, which are recorded as H1, H2, H3, ..., Hn.

8. A method for energy storage management based on digital twins, applied to an energy storage management system based on digital twins as claimed in any one of claims 1 to 7, characterized in that: The specific steps are as follows: S1. Data collection: using the data collection unit (1) to collect actual working data and environmental data of the energy storage battery, and at the same time receiving laboratory data provided by the data input unit (2); S2, data preprocessing: the data preprocessing unit (3) cleans and organizes the collected actual working data, actual environment data and laboratory data to form a first data group, a second data group, a third data group and a fourth data group, and transmits them to the data analysis unit (4); S3, data analysis: the data analysis unit (4) integrates and calculates the first data group, the second data group, the third data group and the fourth data group, obtains the actual working reference value Sgzz, the actual environment reference value Shjz, the laboratory working reference value Ygzz and the laboratory environment reference value Yhjz, and performs secondary integration calculation to generate the actual adjustment reference value Stjz and the laboratory adjustment reference value Ytjz, and then calculates the calibration difference Xzcz; S4, data analysis: the data analysis unit (5) compares the calibration difference Xzcz with a preset first threshold value Y to generate a first comparison result, then integrates the calibration difference Xzcz with the first threshold value Y to generate a magnitude determination value Ljz, then compares the magnitude determination value Ljz with a preset second threshold value R to generate a second comparison result, and divides the adjustment level of the management system according to the result; S5, execution adjustment: the execution unit (6) matches the preset management system adjustment plan according to the second comparison result, executes the corresponding management system adjustment, and generates a management log for archiving.

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