Intelligent monitoring method and system for electrochemical energy storage station
By adopting intelligent monitoring methods in electrochemical energy storage stations, analyzing the health status and operation needs of the battery pack based on historical operation data and real-time monitoring data, the shortcomings of existing systems in peak and valley regulation stability and battery life prediction are solved, and the company has achieved the goal of achieving Efficient and accurate battery pack monitoring and management.
Patent Information
- Application Number
- CN202411609501.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-12
- Publication Date
- 2025-02-18
- Estimated Expiration
- 2044-11-12
AI Technical Summary
The existing electrochemical energy storage station monitoring system is difficult to meet the requirements of large-capacity energy storage stations for real-time and consistency in power output. There is a problem of long start-up time and power response oscillation, and it is difficult to quickly process a large amount of information and complete high-quality Analysis of battery pack health status and operating status data results in insufficient stability during peak and valley adjustment, and the inability to effectively predict battery life and performance decay trends.
Provide intelligent monitoring methods for electrochemical energy storage stations, determine the battery pack health status reference data set based on historical operation data sets, monitor the battery pack health status in real time, comprehensively analyze the battery pack status characteristic values, and judge whether the battery pack can perform peak-to-valley balance. , and determine whether the operating requirements are met based on the real-time operating status characteristic value, and enable a backup battery pack to ensure system stability.
It realizes rapid information processing and data analysis, improves monitoring accuracy and timeliness, solves the problem of insufficient stability during peak and valley adjustment, and can detect and deal with battery performance problems in advance, extends the battery life and reduces operation and maintenance costs.
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Figure CN119482948A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of energy storage station monitoring, and in particular to an intelligent monitoring method and system for an electrochemical energy storage station. Background Art
[0002] At present, with the acceleration of global energy transformation, electrochemical energy storage technology is playing an increasingly important role in the power system. Electrochemical energy storage stations can effectively improve the stability and efficiency of the power system. In recent years, the rapid development of Internet of Things technology has provided new solutions for the intelligent monitoring of electrochemical energy storage stations, real-time monitoring of key parameters such as battery voltage, current, and temperature. The intelligent monitoring system can accurately judge the current state of the battery, promptly discover and deal with potential problems, thereby extending the service life of the battery and ensuring its safe operation. The core of the intelligent monitoring system lies in data monitoring and analysis. The intelligent monitoring technology of electrochemical energy storage stations is the key to ensuring the efficient and safe operation of the energy storage system. With the continuous advancement of technology, intelligent monitoring systems will play a more important role in future power systems.
[0003] However, existing electrochemical energy storage station monitoring systems mostly rely on non-real-time communication technology, which is difficult to meet the requirements of large-capacity electrochemical energy storage stations for real-time and consistency of power output. They have problems such as long startup time and power response oscillation. At the same time, it is also difficult to quickly process large amounts of information and complete high-quality battery pack health and operating status data analysis, resulting in insufficient stability during peak and valley regulation. There are still deficiencies in predicting battery life and performance degradation trends, and it is impossible to maintain or replace the battery before it fails. Summary of the invention
[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent monitoring method and system for an electrochemical energy storage station, which can effectively solve the problems involved in the above-mentioned background technology.
[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an intelligent monitoring method for an electrochemical energy storage station, comprising the following steps: determining a battery pack health status reference data set based on a historical operation data set of the electrochemical energy storage station, wherein the historical operation data set of the electrochemical energy storage station specifically includes the historical operation years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, and the operation fluctuation frequency of the electrochemical energy storage station; monitoring the health status of the battery packs in the electrochemical energy storage station to obtain a battery pack health status data set, wherein the battery pack health status data set specifically includes the battery pack capacity, the battery pack internal resistance, and the battery pack self-discharge rate; based on the battery pack health status data set and the battery pack health status reference data set, a comprehensive analysis is performed to obtain a battery pack status characteristic value; based on the battery pack status characteristic value, judging whether the battery pack can perform peak-valley balance; if a battery pack can perform peak-valley balance, the battery pack is put into the peak-valley balance process; if a battery pack cannot perform peak-valley balance, the battery pack is put into the peak-valley balance process after maintenance. The process comprises the following steps: obtaining a battery pack real-time operating status parameter data set based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the internal resistance of the battery pack, wherein the battery pack real-time operating status parameter data set specifically includes a reference discharge depth of the battery pack, a reference output voltage of the battery pack, and a reference recovery ratio of chemical substances inside the battery pack; obtaining a battery pack real-time operating status data set during the peak-valley balancing process, wherein the battery pack real-time operating status data set specifically includes a battery pack discharge depth, a battery pack output voltage, and a recovery ratio of chemical substances inside the battery pack; analyzing the obtained battery pack real-time operating status data set in combination with the battery pack real-time operating status parameter data set to determine a characteristic value of the battery pack real-time operating status; judging whether the real-time operating status of the battery pack meets the operating requirements based on the characteristic value of the battery pack real-time operating status; if the real-time operating status of the battery pack meets the operating requirements, continuing to invest in the peak-valley balancing process; if the real-time operating status of the battery pack does not meet the operating requirements, activating the backup battery pack.
[0006] As a further method, a battery pack health status reference data set is determined based on the electrochemical energy storage station historical operation data set. The specific analysis process is: obtaining the electrochemical energy storage station historical operation data set, and based on the obtained electrochemical energy storage station historical operation data set, comprehensively analyzing the electrochemical energy storage station status assessment value, and using the electrochemical energy storage station status assessment value as an analysis basis for determining the battery pack health status reference data set; storing the electrochemical energy storage station status assessment value as a designated label, and comparing the designated label with the battery pack health status reference data set corresponding to each designated label stored in the database to obtain the battery pack health status reference data set corresponding to the designated label.
[0007] As a further method, the battery health status reference data set specifically includes a battery reference capacity, a battery reference internal resistance, and a battery reference self-discharge rate. Based on the battery health status data set and the battery health status reference data set, a comprehensive analysis is performed to obtain a battery status characteristic value, including the following steps: based on the acquired battery health status data set and the battery health status reference data set, a comprehensive analysis is performed to obtain a battery status characteristic value, and the battery status characteristic value is used as an analysis basis for determining whether the battery pack can perform peak-valley balance.
[0008] As a further method, based on the battery pack condition characteristic value, judging whether the battery pack can perform peak-valley balance includes the following steps: comparing the battery pack condition characteristic value of a certain battery pack with the battery pack condition reference value stored in a database; if the battery pack condition characteristic value of the battery pack is not greater than the battery pack condition reference value, then the battery pack can perform peak-valley balance, and the battery pack is put into the peak-valley balancing process; if the battery pack condition characteristic value of the battery pack is greater than the battery pack condition reference value, then the battery pack cannot perform peak-valley balance, and the battery pack is put into the peak-valley balancing process after maintenance.
[0009] As a further method, if the battery pack cannot perform peak-valley balance, maintenance of the battery pack specifically includes the following steps: recording the difference between the battery pack condition characteristic value and the battery pack condition reference value of the battery pack that cannot perform peak-valley balance as the battery pack condition deviation value, and comparing the battery pack condition deviation value with the battery pack condition deviation threshold stored in a database; if the battery pack condition deviation value is lower than the battery pack condition deviation threshold, connecting and electrically checking the battery pack corresponding to the battery pack condition deviation value, and cleaning the battery pack surface; if the battery pack condition deviation value is not lower than the battery pack condition deviation threshold, replacing the battery pack corresponding to the battery pack condition deviation value.
[0010] As a further method, a parameter data set of the real-time operating status of the battery pack is obtained, and the specific analysis process is as follows: based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the internal resistance of the battery pack, a comprehensive analysis is performed to obtain a battery pack condition comparison characteristic value, and the battery pack condition comparison characteristic value is used as an analysis basis for obtaining a parameter data set of the real-time operating status of the battery pack; the battery pack condition comparison characteristic value is stored as a designated label, and the designated label is compared with the battery pack real-time operating status parameter data set corresponding to each designated label stored in the database to obtain the battery pack real-time operating status parameter data set corresponding to the designated label.
[0011] As a further method, determining the characteristic value of the real-time operating status of the battery pack includes the following steps: based on the battery pack real-time operating status data set and the battery pack real-time operating status parameter data set, a comprehensive analysis is performed to obtain the characteristic value of the real-time operating status of the battery pack, and the characteristic value of the real-time operating status of the battery pack is used as an analysis basis for judging whether the real-time operating status of the battery pack meets the operating requirements.
[0012] As a further method, the real-time operating condition characteristic value of the battery pack, the specific analysis process is:
[0013]
[0014] Where y is the real-time operating status characteristic value of the battery pack, fd is the discharge depth of the battery pack, dw is the output voltage of the battery pack, yh is the recovery ratio of the chemical substances inside the battery pack, and fd 0 is the reference discharge depth of the battery pack, dw 0 is the reference output voltage of the battery pack, yh 0 is the reference recovery ratio of the chemical substances inside the battery pack, β 1 is the compensation factor of the set fd, β 2 is the compensation factor of the set dw, β 3 is the compensation factor of the set yh.
[0015] As a further method, the determination of whether the real-time operating status of the battery pack meets the operating requirements specifically includes the following steps: comparing the real-time operating status characteristic value of a battery pack with the real-time operating status reference value of the battery pack stored in a database; if the real-time operating status characteristic value of the battery pack is not greater than the real-time operating status reference value of the battery pack, the real-time operating status of the battery pack meets the operating requirements, and the peak-valley balancing process continues; if the real-time operating status characteristic value of the battery pack is greater than the real-time operating status reference value of the battery pack, the real-time operating status of the battery pack does not meet the operating requirements, and the backup battery pack is activated.
[0016] The second aspect of the present invention provides an intelligent monitoring system for an electrochemical energy storage station, including a battery pack health status reference data acquisition module, a battery pack health status data acquisition module, a battery pack status characteristic value acquisition module, a peak-valley balance judgment module, a battery pack parameter data acquisition module, a battery pack real-time data acquisition module, a battery pack real-time characteristic value determination module and an operation demand judgment module, wherein: the battery pack health status reference data acquisition module is used to determine the battery pack health status reference data set based on the electrochemical energy storage station historical operation data set, and the electrochemical energy storage station historical operation data set specifically includes the historical operation years of the electrochemical energy storage station, the electrochemical energy storage station The number of historical maintenance times of the station, the frequency of operation fluctuations of the electrochemical energy storage station; the battery pack health data acquisition module is used to monitor the health status of the battery pack in the electrochemical energy storage station and obtain the battery pack health status data set, and the battery pack health status data set specifically includes the battery pack capacity, the battery pack internal resistance, and the battery pack self-discharge rate; the battery pack status characteristic value acquisition module is based on the battery pack health status data set and the battery pack health status reference data set, and comprehensively analyzes to obtain the battery pack status characteristic value; the peak-valley balance judgment module is used to judge whether the battery pack can perform peak-valley balance based on the battery pack status characteristic value; if a battery pack can perform peak-valley balance, The battery pack is put into the peak-valley balancing process; if a battery pack cannot be peak-valley balanced, the battery pack is maintained and then put into the peak-valley balancing process; the battery pack parameter data acquisition module is used to obtain the battery pack real-time operating status parameter data set based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance. The battery pack real-time operating status parameter data set specifically includes the battery pack reference discharge depth, the battery pack reference output voltage, and the battery pack internal chemical substance reference recovery ratio; the battery pack real-time data acquisition module obtains the battery pack real-time operating status data set during the peak-valley balancing process. The real-time operating status data set of the battery pack specifically includes the discharge depth of the battery pack, the output voltage of the battery pack, and the recovery ratio of the chemical substances inside the battery pack; the real-time characteristic value determination module of the battery pack analyzes the acquired real-time operating status data set of the battery pack in combination with the real-time operating status parameter data set of the battery pack to determine the real-time operating status characteristic value of the battery pack; the operating demand judgment module is used to judge whether the real-time operating status of the battery pack meets the operating requirements based on the real-time operating status characteristic value of the battery pack; if the real-time operating status of the battery pack meets the operating requirements, the peak-valley balancing process is continued; if the real-time operating status of the battery pack does not meet the operating requirements, the backup battery pack is enabled.
[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:
[0018] (1) The present invention provides an intelligent monitoring method for electrochemical energy storage stations, which can provide fast information processing and data analysis, complete the collection of a large amount of information in a short time, and complete high-quality battery pack health status and operation status data analysis by acquiring information in real time. This method can provide high monitoring accuracy and ensure timeliness, and solves the shortcomings of traditional electrochemical energy storage station monitoring methods in the peak-valley regulation process.
[0019] (2) The present invention monitors the health status and operating conditions of the battery in real time, predicts the battery life and performance degradation trend, and discovers and handles problems that may affect battery performance in advance. The predictive maintenance strategy can perform maintenance or replacement before the battery fails, avoiding affecting the normal operation of the power station, thereby extending the battery life and reducing operation and maintenance costs. This method solves the shortcomings of traditional electrochemical energy storage station monitoring methods in predicting battery life and performance degradation trends.
[0020] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.
[0022] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.
[0023] Figure 2 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION
[0024] 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.
[0025] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent monitoring method for an electrochemical energy storage station, including: determining a battery pack health status reference data set based on a historical operation data set of the electrochemical energy storage station, wherein the historical operation data set of the electrochemical energy storage station specifically includes the historical operation years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, and the operation fluctuation frequency of the electrochemical energy storage station.
[0026] The specific analysis process is as follows: obtaining the historical operation data set of the electrochemical energy storage station, and based on the obtained historical operation data set of the electrochemical energy storage station, comprehensively analyzing to obtain the status assessment value of the electrochemical energy storage station, and using the status assessment value of the electrochemical energy storage station as the analysis basis for determining the reference data set of the health status of the battery pack; storing the status assessment value of the electrochemical energy storage station as a designated label, and comparing the designated label with the reference data set of the health status of the battery pack corresponding to each designated label stored in the database, to obtain the reference data set of the health status of the battery pack corresponding to the designated label.
[0027] In a specific embodiment, the electrochemical energy storage station status evaluation value, the specific analysis process is:
[0028]
[0029] In the formula, γ is the status assessment value of the electrochemical energy storage station, N is the historical operation years of the electrochemical energy storage station, n is the historical maintenance times of the electrochemical energy storage station, pl is the operation fluctuation frequency of the electrochemical energy storage station, θ 1 is the compensation factor of the set N, θ 2 is the compensation factor of the set n, θ 3 is the compensation factor of the set pl, and e is a natural constant.
[0030] It needs to be explained that the above-mentioned electrochemical energy storage station condition assessment value is calculated through the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, and the operating fluctuation frequency of the electrochemical energy storage station. N, n, and pl are normalized. A separate analysis of the operating years, maintenance times, or operating fluctuation frequency may not fully reflect the health status of the electrochemical energy storage station. By combining these parameters into a condition assessment value, the operating status of the electrochemical energy storage station can be more comprehensively assessed. By combining multiple indicators, the error caused by fluctuations in a single indicator can be reduced, and the health status of the electrochemical energy storage station can be judged more accurately. According to the electrochemical energy storage station condition assessment value, different assessment values can correspond to different battery pack health status reference data, thereby obtaining a battery pack health status reference data set.
[0031] It should be explained that the compensation factors of N, n, and pl set above are obtained from the database. According to the historical data, a mapping set of the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the operating fluctuation frequency of the electrochemical energy storage station and the compensation factors of N, n, and pl is established to obtain the compensation factors of N, n, and pl corresponding to the current N, n, and pl.
[0032] It should be noted that the α 1 , α 2 , α 3 , β 1 , β 2 , β 3They are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained according to the current data.
[0033] The above-mentioned historical operating years of the electrochemical energy storage station refers to the length of time from the time the energy storage equipment was put into operation to the current time, which is usually counted in years. This indicator is of great significance for evaluating the performance, economy and safety of the energy storage station. Generally speaking, the operating years of an electrochemical energy storage station are affected by many factors, including battery type, operating environment, maintenance, etc. The historical operating years of an electrochemical energy storage station is one of the important indicators for evaluating its health status. As the operating time increases, the performance of the equipment will gradually decline, which may lead to reduced energy storage efficiency and safety problems. By statistically analyzing the data of the operating years, the performance change trend of the equipment can be identified, and upgraded or replaced when necessary. Batteries that have been running for a long time may experience a decrease in capacity or an increase in internal resistance. Regular health checks can detect these problems in time and take corresponding measures.
[0034] The above-mentioned operation fluctuation frequency of the electrochemical energy storage station refers to the standard deviation of the output power of the energy storage station within a certain period of time. It is an important indicator to measure the operation stability of the energy storage station. The fluctuation frequency directly affects the efficiency and life of the energy storage station. At the same time, the operation fluctuation frequency of the electrochemical energy storage station is also a key factor reflecting its health status. Operation fluctuations may be caused by unstable performance of the equipment itself, or may be affected by external conditions, such as fluctuations in the power grid or intermittent supply of renewable energy. Analyzing these fluctuation frequencies can help understand the stability and reliability of the equipment, thereby optimizing the operation strategy and reducing the impact of fluctuations on equipment life and performance. For example, by introducing advanced control algorithms and energy storage management systems, power output can be smoothed and the overall stability of the system can be improved.
[0035] The above analysis of the historical maintenance times of the electrochemical energy storage station can reveal the wear and aging of the equipment. Frequent maintenance usually means that the equipment has some potential problems or has reached a certain stage of its service life. The replacement frequency of the battery module can reflect the rate of performance degradation, which in turn helps predict future maintenance needs and possible failure risks. This analysis helps to formulate a more effective maintenance plan and replace or repair faulty parts in a timely manner, thereby extending the overall life of the energy storage station.
[0036] The above in-depth analysis of the historical maintenance times, operating years and operating fluctuation frequency of the electrochemical energy storage station can provide a comprehensive understanding of its health status, timely discover and solve potential problems, thereby ensuring the long-term stable operation of the energy storage station and improving the efficiency and reliability of the energy system. This analysis method provides a scientific basis for the maintenance and management of electrochemical energy storage stations, and helps promote the sustainable development of the energy system.
[0037] Monitor the health status of the battery pack in the electrochemical energy storage station and obtain a battery pack health status data set, wherein the battery pack health status data set specifically includes the battery pack capacity, the battery pack internal resistance, and the battery pack self-discharge rate.
[0038] Based on the battery pack health status data set and the battery pack health status reference data set, a comprehensive analysis is performed to obtain the battery pack condition characteristic value.
[0039] The specific analysis process is as follows: the battery pack health status reference data set specifically includes the battery pack reference capacity, the battery pack reference internal resistance, and the battery pack reference self-discharge rate; based on the acquired battery pack health status data set and the battery pack health status reference data set, a comprehensive analysis is performed to obtain the battery pack condition characteristic value, and the battery pack condition characteristic value is used as an analysis basis for determining whether the battery pack can achieve peak-valley balance.
[0040] In a specific embodiment, the battery pack condition characteristic value, the specific analysis process is:
[0041]
[0042] In the formula, x is the characteristic value of the battery pack condition, rl is the battery pack capacity, R is the internal resistance of the battery pack, dl is the self-discharge rate of the battery pack, and rl 0 is the reference capacity of the battery pack, R 0 is the reference internal resistance of the battery pack, dl 0 is the reference self-discharge rate of the battery pack, α 1 is the compensation factor of the set R, α 2 is the compensation factor of the set rl, α 3 is the compensation factor of the set dl.
[0043] The above-mentioned battery pack condition characteristic value is calculated through the battery pack capacity, battery pack internal resistance and battery pack self-discharge rate. rl, dl and R are normalized. The separate evaluation of battery pack capacity, battery pack internal resistance and battery pack self-discharge rate may not fully reflect the health status of the battery pack. By combining these indicators into a battery pack condition characteristic value, the health status of the battery pack in operation can be evaluated more comprehensively. Integrating the characteristic values of multiple indicators can reduce the error caused by the fluctuation of a single indicator, improve the accuracy of the overall evaluation, and make a more accurate judgment on whether the battery pack can achieve peak-valley balance.
[0044] The self-discharge rate of a battery pack refers to the ability of the battery to maintain the amount of electricity stored in the battery under certain conditions when the battery is in an open circuit state. It reflects the rate of energy loss of the battery when it is not in use. It is determined by measuring the rate of change of the open circuit voltage of the battery over a period of time and combining the voltage decay slope and the calculation of the decay capacity corresponding to the unit time. In a battery pack, inconsistent self-discharge may lead to greater differences in the SOC between batteries, affecting the performance and life of the entire battery pack. In addition, self-discharge will reduce the available capacity of the battery, affect the battery life, affect the accurate estimation of the battery status, and may cause errors in the SOC prediction of the battery management system (BMS). It will also accelerate battery aging and shorten the battery life. Severe self-discharge may cause thermal runaway of the battery and cause safety issues. The degradation of battery performance caused by self-discharge may increase the frequency of battery replacement and may limit the application of the battery in high temperature or high humidity environments.
[0045] The internal resistance of a battery pack is one of the important parameters for measuring the performance of a battery pack. It reflects the resistance inside the battery. An increase in internal resistance usually means a decrease in battery performance. An increase in internal resistance will not only reduce the charging and discharging efficiency, but may also cause the battery to heat up, thereby accelerating battery aging. By regularly measuring the internal resistance of the battery, abnormal conditions inside the battery can be discovered in time to prevent potential safety risks. An increase in internal resistance may indicate a short circuit or other fault inside the battery. Timely measures can effectively reduce these risks and ensure the safe use of the battery. In addition, internal resistance measurement can also be used for the selection and acceptance of battery packs. Selecting single cells with uniform internal resistance values to form a battery pack can greatly extend the service life of the battery pack.
[0046] Battery pack capacity is another key indicator for evaluating the health of a battery pack. Battery capacity reflects how much electricity a battery can store and release. As the battery is used and ages, its capacity will gradually decrease. By real-time monitoring and calculating the total charge and discharge ampere-hours of the battery through methods such as the ampere-hour integration method, and comparing it with the rated capacity of the battery, the battery's capacity retention can be accurately evaluated. A decrease in capacity not only affects the use time of the device, but may also indicate changes in the chemical process inside the battery.
[0047] The battery pack condition characteristic value comprehensively evaluates the health status of the battery pack by combining the internal resistance, capacity and self-discharge rate of the battery pack, which can understand the health status of the battery pack in multiple dimensions. This comprehensive evaluation method not only helps to detect battery problems in a timely manner, but also provides a scientific basis for battery maintenance and replacement. Through early detection and timely intervention, it can effectively extend the service life of the battery, reduce maintenance costs, and improve the efficiency and safety of equipment use. The evaluation of the internal resistance, capacity and self-discharge rate of the battery pack plays an important role in the health management of the battery pack. Through the monitoring and analysis of these indicators, the operating status and health status of the battery pack can be fully grasped to ensure the safe, efficient and reliable operation of the battery pack in various application scenarios.
[0048] Based on the characteristic values of the battery pack status, determine whether the battery pack can perform peak-valley balancing; if a battery pack can perform peak-valley balancing, then put the battery pack into the peak-valley balancing process; if a battery pack cannot perform peak-valley balancing, then put the battery pack into the peak-valley balancing process after maintenance.
[0049] The specific analysis process is: compare the battery pack condition characteristic value of a certain battery pack with the battery pack condition reference value stored in the database; if the battery pack condition characteristic value of the battery pack is not greater than the battery pack condition reference value, the battery pack can perform peak-valley balance, and the battery pack is put into the peak-valley balance process; if the battery pack condition characteristic value of the battery pack is greater than the battery pack condition reference value, the battery pack cannot perform peak-valley balance, and the battery pack is put into the peak-valley balance process after maintenance.
[0050] By obtaining the battery pack condition characteristic values obtained by comprehensive analysis of the battery pack internal resistance, capacity and self-discharge rate, it is possible to more comprehensively determine whether the battery pack is suitable for peak-valley balancing. The battery pack internal resistance directly affects the battery output power and efficiency. Batteries with smaller internal resistance have smaller energy losses during the charging and discharging process and can convert and store energy more efficiently. Therefore, under the peak-valley electricity price mechanism, batteries with smaller internal resistance can be charged quickly and efficiently during the valley electricity price period and provide stable power output during the peak electricity price period, thereby reducing electricity costs. Batteries with lower self-discharge rates can maintain their stored electrical energy for a longer period of time and reduce energy losses. For peak-valley balancing applications, this means that the battery can be charged during the valley electricity price period and then used in the valley electricity price period. During peak electricity price periods, there is still enough electricity for use, thereby improving the effect of peak-valley balancing. If the self-discharge rate of the battery is high, more electricity will be lost during storage, affecting the benefits of peak-valley balancing. In peak-valley balancing applications, the battery pack needs to store as much electricity as possible during low electricity price periods to meet the electricity demand during peak periods. Therefore, battery packs with larger capacity are more suitable for peak-valley balancing. They can store more electricity when electricity prices are lower and release this electricity when electricity prices are higher, reducing the need to purchase electricity from the power grid, thereby reducing electricity costs. Therefore, battery packs with small internal resistance, large capacity, and low self-discharge rate are more advantageous in peak-valley balancing applications, and can more effectively reduce electricity costs and improve the utilization efficiency of power resources.
[0051] Based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance, a battery pack real-time operating status parameter data set is obtained. The battery pack real-time operating status parameter data set specifically includes a battery pack reference discharge depth, a battery pack reference output voltage, and a reference recovery ratio of chemical substances inside the battery pack.
[0052] The specific analysis process is as follows: based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance, a comprehensive analysis is performed to obtain the battery pack condition comparison characteristic value, and the battery pack condition comparison characteristic value is used as the analysis basis for obtaining the battery pack real-time operating condition parameter data set; the battery pack condition comparison characteristic value is stored as a specified label, and the specified label is compared with the battery pack real-time operating condition parameter data set corresponding to each specified label stored in the database to obtain the battery pack real-time operating condition parameter data set corresponding to the specified label.
[0053] In a specific embodiment, the battery pack status is compared with the characteristic value, and the specific analysis process is as follows:
[0054]
[0055] It needs to be explained that the above-mentioned battery pack condition comparison characteristic value is calculated through the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance. n, rl, N, and R are normalized. Individual evaluations of the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance may not be able to fully reflect the real-time operating status of the battery pack. By combining these indicators into a battery pack condition comparison characteristic value, the real-time operating status of the battery pack can be evaluated more comprehensively. Integrating the characteristic values of multiple indicators can reduce the error caused by the fluctuation of a single indicator, making the final result more accurate.
[0056] It needs to be explained that the battery pack condition comparison characteristic value obtained by comprehensively considering the battery pack capacity, internal resistance, historical operating years and maintenance times can more comprehensively and accurately obtain the real-time operating condition parameter data set of the battery pack. The real-time operating condition reference value of the battery pack obtained by comprehensively considering multiple factors can provide more comprehensive and accurate data support for decision-making, and can more comprehensively and accurately evaluate the real-time operating condition of the battery pack, thereby optimizing battery management, reducing safety risks, improving economic benefits, and providing data support for decision-making.
[0057] During the peak-valley balancing process, a real-time operating status data set of the battery pack is obtained, and the real-time operating status data set of the battery pack specifically includes the discharge depth of the battery pack, the output voltage of the battery pack, and the recovery ratio of chemical substances inside the battery pack.
[0058] The acquired real-time operating status data set of the battery pack is combined with the real-time operating status parameter data set of the battery pack for analysis to determine the characteristic value of the real-time operating status of the battery pack.
[0059] The specific analysis process is as follows: based on the battery pack real-time operating status data set and the battery pack real-time operating status parameter data set, a comprehensive analysis is performed to obtain the battery pack real-time operating status characteristic value, and the battery pack real-time operating status characteristic value is used as the analysis basis for judging whether the battery pack's real-time operating status meets the operating requirements.
[0060] In a specific embodiment, the real-time operating condition characteristic value of the battery pack is analyzed in the following specific process:
[0061]
[0062] Where y is the real-time operating status characteristic value of the battery pack, fd is the discharge depth of the battery pack, dw is the output voltage of the battery pack, yh is the recovery ratio of the chemical substances inside the battery pack, and fd 0 is the reference discharge depth of the battery pack, dw 0 is the reference output voltage of the battery pack, yh 0 is the reference recovery ratio of the chemical substances inside the battery pack, β 1is the compensation factor of the set fd, β 2 is the compensation factor of the set dw, β 3 is the compensation factor of the set yh.
[0063] The real-time operating status characteristic value of the battery pack is calculated through the discharge depth of the battery pack, the output voltage of the battery pack, and the recovery ratio of the chemical substances inside the battery pack. fd, yh, and dw are normalized. Individual evaluations of the discharge depth of the battery pack, the output voltage of the battery pack, and the recovery ratio of the chemical substances inside the battery pack may not fully reflect the real-time operating status of the battery pack. By combining these indicators into a real-time operating status characteristic value of the battery pack, the real-time operating status of the battery pack can be evaluated more comprehensively. Integrating the characteristic values of multiple indicators can reduce the error caused by the fluctuation of a single indicator and make the final result more accurate. By real-time monitoring of the operating status of the battery pack, the working status of the equipment can be adjusted in time to ensure that the equipment operates in the best state.
[0064] Discharge depth refers to the ratio of the capacity discharged by the battery to its total capacity. Real-time monitoring of the discharge depth of the battery pack can help us understand the current discharge status of the battery. By monitoring this indicator, we can prevent the battery from over-discharging. Over-discharging will damage the chemical substances inside the battery, resulting in shortened battery life or even failure. At the same time, monitoring the output voltage of the battery pack can promptly detect voltage anomalies. Voltage that is too low or too high may cause equipment damage or safety problems.
[0065] By real-time monitoring of the battery pack's discharge depth, output voltage, and recovery ratio of internal chemical substances, the real-time operating status characteristic values of the battery pack can be obtained, which can provide an in-depth understanding of the battery's working status. Through long-term monitoring of the battery pack's discharge depth, output voltage, and recovery ratio of internal chemical substances, a large amount of data can be accumulated. Predicting the remaining life of the battery through data analysis helps to plan battery replacement or maintenance in advance and avoid equipment downtime or safety accidents caused by sudden battery failure. In addition, real-time monitoring can also help to promptly detect potential problems with the battery pack, such as aging and damage, so that timely repairs or replacements can be carried out to reduce maintenance costs. It can also improve the efficiency and safety of battery use, optimize charging strategies, and predict battery life and maintenance needs.
[0066] Based on the characteristic value of the real-time operating status of the battery pack, determine whether the real-time operating status of the battery pack meets the operating requirements; if the real-time operating status of the battery pack meets the operating requirements, continue to invest in the peak-valley balancing process; if the real-time operating status of the battery pack does not meet the operating requirements, activate the backup battery pack.
[0067] The specific analysis process is: compare the real-time operating status characteristic value of a battery pack with the real-time operating status reference value of the battery pack stored in the database; if the real-time operating status characteristic value of the battery pack is not greater than the real-time operating status reference value of the battery pack, the real-time operating status of the battery pack meets the operating requirements, and the peak-valley balancing process continues; if the real-time operating status characteristic value of the battery pack is greater than the real-time operating status reference value of the battery pack, the real-time operating status of the battery pack does not meet the operating requirements, and the backup battery pack is activated.
[0068] The discharge depth of a battery pack directly affects its remaining capacity. By monitoring the discharge depth, we can accurately grasp how long the battery pack can continue to supply power and ensure the normal operation of the equipment. By reasonably controlling the discharge depth, we can avoid deep discharge of the battery pack, thereby extending its charging life. Deep discharge will reduce the activity of chemical substances inside the battery and accelerate battery aging. In addition, by real-time monitoring of the discharge depth and output voltage, we can effectively prevent the occurrence of safety problems such as overheating, deformation and even explosion of the battery pack, thereby ensuring the safety of the battery pack.
[0069] Judging the real-time operating status of the battery pack by the battery pack discharge depth, output voltage and internal chemical recovery ratio is conducive to ensuring the normal operation of the battery pack, improving the service life of the battery pack, ensuring safety and economy, and optimizing the performance of the battery pack. The output voltage is a key indicator of whether the battery pack can meet the operating requirements. Real-time monitoring of the output voltage can timely detect voltage fluctuations or drops. At the same time, understanding the recovery ratio of the internal chemical substances of the battery pack is helpful to evaluate the health status and remaining life of the battery pack, which provides an important basis for predicting the future performance of the battery pack, effectively ensuring that the battery pack can maintain stable operation throughout the entire use cycle and improve the service life of the battery pack. In addition, monitoring the output voltage and the recovery ratio of the internal chemical substances can help to timely detect potential problems of the battery pack, such as unbalanced charge and discharge, increased internal resistance, etc. Real-time monitoring can timely detect and solve problems, thereby improving the service life of the battery pack. Real-time monitoring of the operating status of the battery pack can help optimize the use and management of the battery pack, and is of great significance for improving equipment reliability and reducing operating costs.
[0070] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent monitoring system for an electrochemical energy storage station, including: a battery pack health status reference data acquisition module, a battery pack health status data acquisition module, a battery pack status characteristic value acquisition module, a peak-valley balance judgment module, a battery pack parameter data acquisition module, a battery pack real-time data acquisition module, a battery pack real-time characteristic value determination module and an operation demand judgment module.
[0071] The battery pack health status reference data acquisition module is used to determine the battery pack health status reference data set based on the electrochemical energy storage station historical operation data set, wherein the electrochemical energy storage station historical operation data set specifically includes the number of historical operation years of the electrochemical energy storage station, the number of historical maintenance times of the electrochemical energy storage station, and the operation fluctuation frequency of the electrochemical energy storage station.
[0072] The battery pack health status data acquisition module is used to monitor the health status of the battery pack in the electrochemical energy storage station and obtain a battery pack health status data set, which specifically includes the battery pack capacity, battery pack internal resistance, and battery pack self-discharge rate.
[0073] The battery pack condition characteristic value acquisition module obtains the battery pack condition characteristic value through comprehensive analysis based on the battery pack health status data set and the battery pack health status reference data set.
[0074] The module for judging whether a battery pack can perform peak-valley balance is used to judge whether a battery pack can perform peak-valley balance based on the characteristic value of the battery pack status; if a battery pack can perform peak-valley balance, the battery pack will be put into the peak-valley balance process; if a battery pack cannot perform peak-valley balance, the battery pack will be put into the peak-valley balance process after maintenance.
[0075] The battery pack parameter data acquisition module is used to obtain the battery pack real-time operating status parameter data set based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance. The battery pack real-time operating status parameter data set specifically includes the battery pack reference discharge depth, the battery pack reference output voltage, and the reference recovery ratio of the chemical substances inside the battery pack.
[0076] The battery pack real-time data acquisition module acquires the battery pack real-time operating status data set during the peak-valley balancing process. The battery pack real-time operating status data set specifically includes the battery pack discharge depth, the battery pack output voltage, and the recovery ratio of the chemical substances inside the battery pack.
[0077] The battery pack real-time characteristic value determination module analyzes the acquired battery pack real-time operating status data set in combination with the battery pack real-time operating status parameter data set to determine the battery pack real-time operating status characteristic value.
[0078] The operation demand judgment module is used to judge whether the real-time operation status of the battery pack meets the operation demand based on the real-time operation status characteristic value of the battery pack; if the real-time operation status of the battery pack meets the operation demand, the peak-valley balancing process is continued; if the real-time operation status of the battery pack does not meet the operation demand, the backup battery pack is enabled.
[0079] In a specific embodiment, an electrochemical energy storage station has a historical operating history of 10 years, a historical maintenance number of 5 times, an operating fluctuation frequency of 1.5, a compensation factor of N of 0.02, a compensation factor of n of 0.01, and a compensation factor of pl of 0.5. The electrochemical energy storage station condition assessment value is calculated to be 28.87, and the assessment value is stored as a designated label. The battery pack health status reference data set corresponding to the label is a battery pack reference capacity of 100Ah, a reference internal resistance of 0.08Ω, and a reference self-discharge rate of 0.015.
[0080] The capacity of a battery pack in the electrochemical energy storage station is 90Ah, the reference capacity is 100Ah, the internal resistance is 0.1Ω, the reference internal resistance is 0.08Ω, the self-discharge rate is 0.02, the reference self-discharge rate is 0.015, the compensation factor of rl is 0.3, the compensation factor of R is 0.5, and the compensation factor of dl is 0.7. The calculated battery pack condition characteristic value is 0.359. Since the battery pack condition characteristic value 0.359 is not greater than the battery pack condition reference value 0.5 stored in the database, the battery pack can perform peak-valley balance, and the battery pack is put into the peak-valley balance process.
[0081] The electrochemical energy storage station has been in operation for 10 years and has been maintained for 5 times. The capacity of one of its battery packs is 90Ah, the internal resistance of the battery pack is 0.1Ω, the compensation factor of N is 0.02, the compensation factor of n is 0.01, the compensation factor of rl is 0.3, and the compensation factor of R is 0.5. The battery pack condition comparison eigenvalue is calculated to be 73.72, and the eigenvalue is stored as a specified label. The real-time operating condition parameter data set of the battery pack corresponding to the label is a reference discharge depth of 1, a reference output voltage of 4.0V, and a reference recovery ratio of internal chemical substances of 0.9.
[0082] The battery pack discharge depth is 0.8, the reference discharge depth is 1, the battery pack output voltage is 3.7V, the reference output voltage is 4.0V, the battery pack internal chemical recovery ratio is 0.85, the internal chemical reference recovery ratio is 0.9, the compensation factor of fd is 0.6, the compensation factor of dw is 0.4, and the compensation factor of yh is 0.3. The calculated characteristic value of the real-time operating status of the battery pack is 0.526. Since the characteristic value of the real-time operating status of the battery pack 0.526 is not greater than the reference value of the real-time operating status of the battery pack stored in the database 1, the real-time operating status of the battery pack meets the operating requirements and can continue to be put into the peak-valley balancing process.
[0083] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.
Claims
1. An intelligent monitoring method for an electrochemical energy storage station, characterized in that: The following steps are involved: Determine a battery pack health status reference data set based on an electrochemical energy storage station historical operation data set, wherein the electrochemical energy storage station historical operation data set specifically includes the number of years of historical operation of the electrochemical energy storage station, the number of historical maintenance times of the electrochemical energy storage station, and the operation fluctuation frequency of the electrochemical energy storage station; Monitor the health status of the battery pack in the electrochemical energy storage station and obtain a battery pack health status data set, wherein the battery pack health status data set specifically includes the battery pack capacity, the battery pack internal resistance, and the battery pack self-discharge rate; Based on the battery health status data set and the battery health status reference data set, a comprehensive analysis is performed to obtain the battery status characteristic value; Based on the characteristic value of the battery pack status, determine whether the battery pack can achieve peak-valley balance; If a battery pack can be peak-valley balanced, the battery pack will be put into the peak-valley balancing process; If a battery group cannot be peak-valley balanced, the battery group will be put into peak-valley balancing process after maintenance; Based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the internal resistance of the battery pack, a parameter data set of the real-time operating status of the battery pack is obtained, wherein the parameter data set of the real-time operating status of the battery pack specifically includes a reference discharge depth of the battery pack, a reference output voltage of the battery pack, and a reference recovery ratio of chemical substances inside the battery pack; During the peak-valley balancing process, a real-time operating status data set of the battery pack is obtained, wherein the real-time operating status data set of the battery pack specifically includes the discharge depth of the battery pack, the output voltage of the battery pack, and the recovery ratio of the chemical substances inside the battery pack; Analyze the acquired real-time operating status data set of the battery pack in combination with the real-time operating status parameter data set of the battery pack to determine the characteristic value of the real-time operating status of the battery pack; Based on the real-time operating status characteristic value of the battery pack, judging whether the real-time operating status of the battery pack meets the operating requirements; If the real-time operating status of the battery pack meets the operating requirements, the peak-valley balancing process will continue; If the real-time operating status of the battery pack does not meet the operating requirements, the backup battery pack is activated.
2. The intelligent monitoring method for electrochemical energy storage station according to claim 1, characterized in that: The specific analysis process of determining the battery pack health status reference data set based on the electrochemical energy storage station historical operation data set is as follows: Acquire a historical operation data set of the electrochemical energy storage station, and obtain an electrochemical energy storage station status assessment value based on the acquired historical operation data set of the electrochemical energy storage station, and use the electrochemical energy storage station status assessment value as an analysis basis for determining a reference data set for the health status of the battery pack; The electrochemical energy storage station condition assessment value is stored as a designated label, and the designated label is compared with a battery pack health status reference data set corresponding to each designated label stored in a database to obtain a battery pack health status reference data set corresponding to the designated label.
3. The intelligent monitoring method for electrochemical energy storage station according to claim 1, characterized in that: The battery health status reference data set specifically includes a battery reference capacity, a battery reference internal resistance, and a battery reference self-discharge rate. The battery health status data set and the battery health status reference data set are comprehensively analyzed to obtain a battery status characteristic value, including the following steps: Based on the acquired battery health status data set and battery health status reference data set, a comprehensive analysis is performed to obtain a battery status characteristic value, which is used as an analysis basis for determining whether the battery pack can perform peak-valley balance.
4. The intelligent monitoring method for electrochemical energy storage station according to claim 3, characterized in that: The method of judging whether the battery pack can perform peak-valley balance based on the battery pack condition characteristic value comprises the following steps: Comparing a battery pack condition characteristic value of a battery pack with a battery pack condition reference value stored in a database; If the battery pack condition characteristic value of the battery pack is not greater than the battery pack condition reference value, the battery pack can be subjected to peak-valley balancing, and the battery pack is put into the peak-valley balancing process; If the battery pack condition characteristic value of the battery pack is greater than the battery pack condition reference value, the battery pack cannot be peak-valley balanced, and the battery pack is put into the peak-valley balancing process after maintenance.
5. The intelligent monitoring method for electrochemical energy storage station according to claim 4, characterized in that: The battery pack cannot be peak-valley balanced. Maintenance of the battery pack includes the following steps: Recording the difference between the battery pack condition characteristic value and the battery pack condition reference value of the battery pack that cannot perform peak-valley balancing as a battery pack condition deviation value, and comparing the battery pack condition deviation value with a battery pack condition deviation threshold stored in a database; If the battery pack condition deviation value is lower than the battery pack condition deviation threshold, the battery pack corresponding to the battery pack condition deviation value is connected and electrically inspected, and the surface of the battery pack is cleaned; If the battery pack condition deviation value is not lower than the battery pack condition deviation threshold, the battery pack corresponding to the battery pack condition deviation value is replaced.
6. The intelligent monitoring method for electrochemical energy storage station according to claim 1, characterized in that: The specific analysis process of obtaining the real-time operating status parameter data set of the battery pack is as follows: Based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance, a comprehensive analysis is performed to obtain the battery pack condition comparison characteristic value, which is used as the analysis basis for obtaining the parameter data set of the real-time operating status of the battery pack; The battery pack condition comparison feature value is stored as a designated tag, and the designated tag is compared with the battery pack real-time operating condition parameter data set corresponding to each designated tag stored in the database to obtain the battery pack real-time operating condition parameter data set corresponding to the designated tag.
7. The intelligent monitoring method for electrochemical energy storage station according to claim 1, characterized in that: The step of determining the real-time operating condition characteristic value of the battery pack comprises the following steps: Based on the battery pack real-time operating status data set and the battery pack real-time operating status parameter data set, a comprehensive analysis is performed to obtain the battery pack real-time operating status characteristic value, which is used as an analysis basis for judging whether the battery pack's real-time operating status meets the operating requirements.
8. The intelligent monitoring method for electrochemical energy storage station according to claim 7, characterized in that: The real-time operating condition characteristic value of the battery pack, the specific analysis process is as follows: Wherein, y is the characteristic value of the real-time operating status of the battery pack, fd is the discharge depth of the battery pack, dw is the output voltage of the battery pack, yh is the recovery ratio of the chemical substances inside the battery pack, fd0 is the reference discharge depth of the battery pack, dw0 is the reference output voltage of the battery pack, yh0 is the reference recovery ratio of the chemical substances inside the battery pack, β1 is the compensation factor of the set fd, β2 is the compensation factor of the set dw, and β3 is the compensation factor of the set yh.
9. The intelligent monitoring method for electrochemical energy storage station according to claim 1, characterized in that: The step of judging whether the real-time operating status of the battery pack meets the operating requirements specifically includes the following steps: Comparing a battery pack real-time operating condition characteristic value of a battery pack with a battery pack real-time operating condition reference value stored in a database; If the battery pack real-time operating condition characteristic value of the battery pack is not greater than the battery pack real-time operating condition reference value, the real-time operating condition of the battery pack meets the operating requirements, and the peak-valley balancing process continues; If the battery pack real-time operating condition characteristic value of the battery pack is greater than the battery pack real-time operating condition reference value, the real-time operating condition of the battery pack does not meet the operating requirements, and the backup battery pack is activated.
10. An intelligent monitoring system for an electrochemical energy storage station, applied to an intelligent monitoring method for an electrochemical energy storage station according to any one of claims 1 to 9, characterized in that: It includes a battery pack health status reference data acquisition module, a battery pack health status data acquisition module, a battery pack status characteristic value acquisition module, a peak-valley balance judgment module, a battery pack parameter data acquisition module, a battery pack real-time data acquisition module, a battery pack real-time characteristic value determination module and an operation demand judgment module, wherein: The battery pack health status reference data acquisition module is used to determine the battery pack health status reference data set based on the electrochemical energy storage station historical operation data set, and the electrochemical energy storage station historical operation data set specifically includes the number of historical operation years of the electrochemical energy storage station, the number of historical maintenance times of the electrochemical energy storage station, and the operation fluctuation frequency of the electrochemical energy storage station; The battery pack health status data acquisition module is used to monitor the health status of the battery pack in the electrochemical energy storage station and acquire a battery pack health status data set, wherein the battery pack health status data set specifically includes the battery pack capacity, the battery pack internal resistance, and the battery pack self-discharge rate; The battery pack condition characteristic value acquisition module obtains the battery pack condition characteristic value by comprehensive analysis based on the battery pack health status data set and the battery pack health status reference data set; The peak-valley balance determination module is used to determine whether the battery pack can perform peak-valley balance based on the battery pack status characteristic value; If a battery pack can be peak-valley balanced, the battery pack will be put into the peak-valley balancing process; If a battery group cannot be peak-valley balanced, the battery group will be put into peak-valley balancing process after maintenance; The battery pack parameter data acquisition module is used to acquire a battery pack real-time operating status parameter data set based on the historical operating years of the electrochemical energy storage station, the historical maintenance times of the electrochemical energy storage station, the battery pack capacity, and the battery pack internal resistance. The battery pack real-time operating status parameter data set specifically includes a battery pack reference discharge depth, a battery pack reference output voltage, and a battery pack internal chemical substance reference recovery ratio; The battery pack real-time data acquisition module acquires a battery pack real-time operating status data set during the peak-valley balancing process, wherein the battery pack real-time operating status data set specifically includes the battery pack discharge depth, the battery pack output voltage, and the recovery ratio of the chemical substances inside the battery pack; The battery pack real-time characteristic value determination module analyzes the acquired battery pack real-time operating status data set in combination with the battery pack real-time operating status parameter data set to determine the battery pack real-time operating status characteristic value; The operation demand judgment module is used to judge whether the real-time operation status of the battery pack meets the operation demand based on the real-time operation status characteristic value of the battery pack; If the real-time operating status of the battery pack meets the operating requirements, the peak-valley balancing process will continue; If the real-time operating status of the battery pack does not meet the operating requirements, the backup battery pack is activated.
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