Electrochemical energy storage risk prediction method

Abstract

The invention relates to the technical field of energy storage risk prediction, and particularly discloses an electrochemical energy storage risk prediction method, which comprises the following steps of: determining a risk characteristic value of an electrochemical energy storage system, obtaining an abnormal deviation value of an operation environment of the electrochemical energy storage system, and obtaining a risk judgment threshold value of the electrochemical energy storage system; according to the method, the real-time operation state of the electrochemical energy storage system is monitored, whether the electrochemical energy storage system has risks or not is judged by combining a risk judgment threshold value of the electrochemical energy storage system, and the risk level of the electrochemical energy storage system with the risks is determined. According to the method, the problems that the existing risk management system is not easy to carry out and is lack of comprehensive analysis are solved, rapid response and implementation of effective rectification measures are facilitated, the accident occurrence probability is remarkably reduced, the efficiency and pertinence of maintenance work are improved, a perfect risk judgment threshold system is established, potential risks can be systematically identified and evaluated, and the overall risk management capability is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage risk prediction, and in particular to an electrochemical energy storage risk prediction method. Background Art

[0002] With the increase in the use of renewable energy (such as solar and wind energy), the demand for electrochemical energy storage systems has also risen. Battery systems need to effectively manage electrical energy to ensure the reliability and stability of power supply, so risk assessment and management have become more critical. The design and operation of electrochemical energy storage systems involve multiple complex factors, including system integration and environmental conditions. The complexity of the system makes it more difficult to assess and predict risks, and accurate risk prediction can help design more reliable systems. Electrochemical energy storage systems may face safety risks such as overheating, short circuit, fire and explosion. Batteries may experience thermal runaway during charging and discharging, causing serious safety accidents. It is necessary to identify and predict potential risks in advance. Through in-depth research on the risks of electrochemical energy storage systems, we can promote the innovation and improvement of related technologies, making them safer and more reliable, thereby promoting the transformation of the entire energy system to sustainable development.

[0003] Nowadays, there are still some deficiencies in the research on risk prediction of electrochemical energy storage. Specifically, the traditional risk prediction methods are unable to capture complex nonlinear relationships and lack comprehensive analysis. For the risk prediction of electrochemical energy storage systems, there is often a lack of comprehensive analysis of multiple risk factors, resulting in the one-sidedness of risk management strategies. The lack of capturing nonlinear relationships will lead to the inability to accurately identify risks under specific conditions, and may omit or misestimate certain potential risks. Simple linear models cannot reflect complex system behaviors and may produce large prediction errors, thereby affecting the scientific nature of decision-making. A single risk analysis may lead to insufficient targeted response measures, which cannot effectively cover all potential risks, delay the response to emergencies and cause waste of resources. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for predicting electrochemical energy storage risks, 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: a method for predicting electrochemical energy storage risk, comprising the following steps: analyzing the historical operating characteristics of the electrochemical energy storage system to determine the performance degradation coefficient of the electrochemical energy storage system; determining the risk characteristic value of the electrochemical energy storage system based on the performance degradation coefficient of the electrochemical energy storage system; analyzing the operating environment of the electrochemical energy storage system to obtain the abnormal deviation value of the operating environment of the electrochemical energy storage system; deriving the risk judgment threshold of the electrochemical energy storage system based on the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system; monitoring the real-time operating status of the electrochemical energy storage system, combining the risk judgment threshold of the electrochemical energy storage system, judging whether the electrochemical energy storage system is at risk, and determining the risk level of the electrochemical energy storage system at risk.

[0006] As a further method, the performance degradation coefficient of the electrochemical energy storage system is determined. The specific analysis process is: obtaining a historical operation characteristic data set of the electrochemical energy storage system, and based on the obtained historical operation characteristic data set of the electrochemical energy storage system, comprehensively analyzing the historical operation characteristic values ​​of the electrochemical energy storage system, and using the historical operation characteristic values ​​of the electrochemical energy storage system as an analysis basis for determining the performance degradation coefficient of the electrochemical energy storage system; storing the historical operation characteristic values ​​of the electrochemical energy storage system as a designated label, and comparing the designated label with the performance degradation coefficients of the electrochemical energy storage system corresponding to each designated label stored in the database to obtain the performance degradation coefficient of the electrochemical energy storage system corresponding to the designated label.

[0007] As a further method, a historical operation characteristic data set of the electrochemical energy storage system specifically includes the total number of years the electrochemical energy storage system has been put into use, the total length of time the electrochemical energy storage system has been put into use, and the total number of times the electrochemical energy storage system has been maintained.

[0008] As a further method, the risk characteristic value of the electrochemical energy storage system is determined based on the performance degradation coefficient of the electrochemical energy storage system. The specific analysis process is: the performance degradation coefficient of the electrochemical energy storage system is stored as a designated label, and the designated label is compared with the risk characteristic value of the electrochemical energy storage system corresponding to each designated label stored in the database to obtain the risk characteristic value of the electrochemical energy storage system corresponding to the designated label.

[0009] As a further method, an abnormal deviation value of the operating environment of the electrochemical energy storage system is obtained. The specific analysis process is: obtaining an electrochemical energy storage system operating environment data set, and based on the obtained electrochemical energy storage system operating environment data set, comprehensively analyzing to obtain electrochemical energy storage system operating environment characteristic values, and using the electrochemical energy storage system operating environment characteristic values ​​as an analysis basis for obtaining the abnormal deviation value of the operating environment of the electrochemical energy storage system; storing the electrochemical energy storage system operating environment characteristic values ​​as designated tags, and comparing the designated tags with the abnormal deviation values ​​of the operating environment of the electrochemical energy storage system corresponding to the designated tags stored in the database to obtain the abnormal deviation value of the operating environment of the electrochemical energy storage system corresponding to the designated tags.

[0010] As a further method, the electrochemical energy storage system operating environment data set specifically includes the electrochemical energy storage system operating environment temperature, the electrochemical energy storage system operating environment humidity, the electrochemical energy storage system operating environment wind speed, and the electrochemical energy storage system operating environment precipitation.

[0011] As a further method, the risk judgment threshold of the electrochemical energy storage system is obtained based on the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system. The specific analysis process is: the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system are introduced into the risk judgment model of the electrochemical energy storage system, and the risk judgment threshold of the electrochemical energy storage system is obtained through comprehensive analysis.

[0012] As a further method, it is judged whether there is a risk in the electrochemical energy storage system. The specific analysis process is as follows: obtain a real-time operating status data set of the electrochemical energy storage system, which specifically includes the real-time remaining power of the electrochemical energy storage system, the absolute value of the difference between the real-time voltage of the electrochemical energy storage system and the reference voltage, and the absolute value of the difference between the real-time output power of the electrochemical energy storage system and the reference output power; based on the obtained real-time operating status data set of the electrochemical energy storage system, a comprehensive analysis is performed to obtain a real-time operating status evaluation value of the electrochemical energy storage system, which is used as an analysis basis for judging whether there is a risk in the electrochemical energy storage system; compare the real-time operating status evaluation value of the electrochemical energy storage system with the risk judgment threshold of the electrochemical energy storage system; if the real-time operating status evaluation value of the electrochemical energy storage system is not lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status evaluation value of the electrochemical energy storage system does not have a risk; if the real-time operating status evaluation value of the electrochemical energy storage system is lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status evaluation value of the electrochemical energy storage system has a risk.

[0013] As a further method, the real-time operating status evaluation value of the electrochemical energy storage system, the specific analysis process is:

[0014]

[0015] Where γ is the real-time operating status evaluation value of the electrochemical energy storage system, sy is the real-time remaining capacity of the electrochemical energy storage system, dy is the absolute value of the difference between the real-time voltage of the electrochemical energy storage system and the reference voltage, scg is the absolute value of the difference between the real-time output power of the electrochemical energy storage system and the reference output power, μ1 is the compensation factor of sy, and μ ２ is the compensation factor of the set dy, and μ3 is the compensation factor of the set scg.

[0016] As a further method, the risk level of the electrochemical energy storage system at risk is determined, and the specific analysis process is: the difference between the electrochemical energy storage system risk judgment threshold and the electrochemical energy storage system real-time operation status assessment value of the electrochemical energy storage system at risk is recorded as the electrochemical energy storage system real-time operation status assessment deviation value, the electrochemical energy storage system real-time operation status assessment deviation value is stored as a designated label, and the designated label is compared with the risk level corresponding to each designated label stored in the database to obtain the risk level corresponding to the designated label, which is recorded as the risk level of the electrochemical energy storage system at risk corresponding to the real-time operation status assessment value of the electrochemical energy storage system.

[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 electrochemical energy storage risk prediction method to timely identify abnormal deviations of the system, which helps to quickly respond and implement effective corrective measures, significantly reducing the probability of accidents. Based on historical operating characteristics and real-time monitoring data, a more scientific and reasonable maintenance plan can be formulated to improve the efficiency and pertinence of maintenance work, establish a complete risk judgment threshold system, and be able to systematically identify and evaluate potential risks, thereby improving overall risk management capabilities.

[0019] (2) The present invention determines the risk characteristic value of the electrochemical energy storage system through the performance degradation coefficient of the electrochemical energy storage system. The health status of the system and the potential risk level can be quantified through the performance degradation coefficient, providing a specific basis for risk management, and converting the performance degradation into a risk characteristic value to form a standardized indicator. The risk characteristic value provides important data support for the management, making the decision more scientific and reasonable, reducing the deviation caused by subjective judgment, and reducing the possible accident losses through effective risk assessment and response measures.

[0020] (3) The present invention obtains the risk judgment threshold of the electrochemical energy storage system through the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the electrochemical energy storage system operating environment. Setting the risk judgment threshold can standardize the complex risk assessment process and facilitate the comparison and response between different electrochemical energy storage systems. A clear threshold can help quickly identify when the system is in a high-risk state, so as to take action early. The risk judgment threshold provides a clear action benchmark, so that it can respond quickly when an abnormality occurs, reduce potential losses, effectively reduce the risk of equipment failure and safety accidents, and improve the overall safety of the system. 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 It is a schematic diagram of the method flow of the present invention.

[0023] Figure 2 Flowchart of steps for determining whether an electrochemical energy storage system presents a risk. 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 present invention provides a method for predicting electrochemical energy storage risk, including: analyzing historical operating characteristics of the electrochemical energy storage system to determine the performance degradation coefficient of the electrochemical energy storage system.

[0026] The specific analysis process is as follows: obtaining a historical operation characteristic data set of the electrochemical energy storage system, and based on the obtained historical operation characteristic data set of the electrochemical energy storage system, comprehensively analyzing the historical operation characteristic values ​​of the electrochemical energy storage system, and using the historical operation characteristic values ​​of the electrochemical energy storage system as an analysis basis for determining the performance degradation coefficient of the electrochemical energy storage system; storing the historical operation characteristic values ​​of the electrochemical energy storage system as a designated label, and comparing the designated label with the performance degradation coefficient of the electrochemical energy storage system corresponding to each designated label stored in the database to obtain the performance degradation coefficient of the electrochemical energy storage system corresponding to the designated label.

[0027] In a specific embodiment, an electrochemical energy storage system is a technology that stores and releases energy through electrochemical reactions. The most common form is a battery. Such systems are typically used to balance electricity supply and demand, provide power support, and promote the integration of renewable energy. Comparing historical operating characteristic values ​​with performance degradation coefficients can effectively evaluate the actual performance of the electrochemical energy storage system and promptly detect signs of performance degradation. Analyzing these data can help predict the maintenance needs of the system, reduce downtime caused by equipment failures, and improve the reliability and service life of the system. It can help predict the maintenance needs of the system, reduce downtime caused by equipment failures, and improve the reliability and service life of the system. Comprehensive analysis of historical operating characteristic data can provide a basis for optimizing operating strategies, thereby improving the efficiency and responsiveness of the system. The comparison results can help identify potential failure modes or abnormal behaviors, thereby providing effective guidance for fault diagnosis and processing. By quantifying the relationship between characteristic values ​​and performance degradation coefficients, more scientific operation and management decisions can be made based on data, and clear indicators of performance degradation can help take timely measures to maximize risk identification and reduce safety hazards.

[0028] In a specific embodiment, the specific analysis process of the historical operation characteristic value of the electrochemical energy storage system is as follows:

[0029]

[0030] Wherein, α is the historical operation characteristic value of the electrochemical energy storage system, nx is the total number of years of historical use of the electrochemical energy storage system, sc is the total length of historical use of the electrochemical energy storage system, wx is the total number of historical maintenance of the electrochemical energy storage system, σ1 is the compensation factor of the set nx, σ2 is the compensation factor of the set sc, σ3 is the compensation factor of the set wx, and e is a natural constant.

[0031] It should be explained that the above-mentioned historical operation characteristic values ​​of the electrochemical energy storage system are calculated through the total years of historical use of the electrochemical energy storage system, the total time of historical use of the electrochemical energy storage system, and the total number of historical maintenance of the electrochemical energy storage system. nx, sc, and wx are normalized. The historical operation characteristic values ​​can help operators understand the performance of the system in different time periods. By analyzing these data, it can be determined whether the battery has experienced excessive wear or performance degradation. An increase in the total number of maintenance times may indicate a decrease in the reliability of the system. Potential failures can be predicted through these data, and maintenance measures can be taken in advance. Historical data can help formulate a more scientific maintenance plan. By analyzing historical operation data, operators can identify factors that affect system efficiency, and then make optimization adjustments to improve the overall performance of the system.

[0032] It should be explained that the compensation factors of nx, sc, and wx set above are obtained from the database. According to the historical data, a mapping set of the historically measured total years of the electrochemical energy storage system in use, the total duration of the electrochemical energy storage system in use, the total number of historical maintenance of the electrochemical energy storage system and the compensation factors of nx, sc, and wx is established to obtain the compensation factors of nx, sc, and wx corresponding to the current nx, sc, and wx.

[0033] It should be noted that τ1, τ2, τ3, τ4, μ1, μ2, and μ3 mentioned below 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 based on the current data.

[0034] Specifically, the historical operation characteristic data set of the electrochemical energy storage system includes the total number of years the electrochemical energy storage system has been put into use, the total duration of the electrochemical energy storage system being put into use, and the total number of times the electrochemical energy storage system has been maintained.

[0035] In a specific embodiment, the total number of years that the electrochemical energy storage system has been in use refers to the total number of years since the electrochemical energy storage system was put into use, which reflects the age of the system and helps to evaluate the degree of aging and possible performance degradation of the system. It is obtained through the system's installation records or data in the operation management system (such as a SCADA system). The total length of time that the electrochemical energy storage system has been in use refers to the actual operating time of the electrochemical energy storage system during its entire period of use, which can help evaluate the utilization and operating efficiency of the system. It is obtained through the system's monitoring equipment (such as a battery management system BMS, a SCADA system, etc.). The total number of historical maintenance of the electrochemical energy storage system refers to the total number of all maintenance performed on the electrochemical energy storage system during its period of use, which can reflect the reliability and maintenance requirements of the system, and is obtained through maintenance records or a maintenance management system.

[0036] In a specific embodiment, the total number of years of historical use refers to the total number of years since the system was put into use, and the total time of historical use refers to the actual operation time of the system during this period. The longer the total number of years of historical use, the greater the total time of historical use. However, since the system may experience downtime, maintenance or failure, the actual total time may be lower than the total number of years. The total number of historical maintenance times is usually positively correlated with the total number of historical use. The longer the system is used, the more failures and maintenance times it may experience. This is because equipment is more likely to age or experience performance degradation after long-term use. There is also a certain relationship between the total time of historical use and the total number of historical maintenance times. Systems with longer operating times may experience more wear and tear and failures, leading to more maintenance needs.

[0037] The risk characteristic value of the electrochemical energy storage system is determined based on the performance degradation coefficient of the electrochemical energy storage system.

[0038] The specific analysis process is as follows: the performance degradation coefficient of the electrochemical energy storage system is stored as a designated label, and the designated label is compared with the electrochemical energy storage system risk characteristic value corresponding to each designated label stored in the database to obtain the electrochemical energy storage system risk characteristic value corresponding to the designated label.

[0039] It needs to be explained that the above-mentioned comparison of the performance degradation coefficient and the risk characteristic value can timely identify potential risk problems of the system. If the performance degradation coefficient exceeds the preset safety threshold, it may mean that the system needs inspection or maintenance. Early identification of risk characteristics will help to take preventive measures to avoid system failures and downtime, and reduce the impact on overall operations. The comparison results can provide a basis for maintenance decisions, thereby achieving on-demand maintenance and reducing unnecessary maintenance and downtime. From the comparison, it can be obtained which risk characteristic values ​​are more critical, which helps to prioritize high-risk areas in multiple maintenance tasks and optimize resource allocation. Dynamic monitoring of the changing trends of the performance degradation coefficient and risk characteristic values ​​helps to evaluate the health of the system and evaluate and analyze the performance. By comparison, it can be found which characteristic values ​​are the main driving factors of performance degradation, which helps to determine the focus of improvement work, promote the system's technological upgrades and performance improvements, and link performance changes with known risk characteristic values ​​to quickly grasp the system status and improve management efficiency.

[0040] The operating environment of the electrochemical energy storage system is analyzed to obtain abnormal deviation values ​​of the operating environment of the electrochemical energy storage system.

[0041] The specific analysis process is as follows: obtaining an electrochemical energy storage system operating environment data set, and based on the obtained electrochemical energy storage system operating environment data set, comprehensively analyzing to obtain electrochemical energy storage system operating environment characteristic values, and using the electrochemical energy storage system operating environment characteristic values ​​as an analysis basis for obtaining electrochemical energy storage system operating environment abnormal deviation values; storing the electrochemical energy storage system operating environment characteristic values ​​as designated tags, and comparing the designated tags with the electrochemical energy storage system operating environment abnormal deviation values ​​corresponding to the designated tags stored in the database to obtain the electrochemical energy storage system operating environment abnormal deviation values ​​corresponding to the designated tags.

[0042] It needs to be explained that the above-mentioned comparison of the operating environment characteristic values ​​and the abnormal deviation values ​​can timely identify abnormal conditions in the operating environment, such as abnormal fluctuations in parameters such as temperature and humidity. When an abnormality is identified, the system can automatically trigger an alarm or provide real-time data feedback, prompting timely measures to reduce potential risks, thereby helping to reduce blind operations due to lack of information, and ensuring that all inspections and maintenance are based on sufficient data analysis, analyzing the relationship between the operating environment characteristics and abnormal deviations, optimizing the system's daily operations and maintenance strategies, and ensuring operation under appropriate environmental conditions to improve the overall efficiency of the system. Timely identification of environmental anomalies will help to reasonably arrange maintenance and repair resources, reduce the failure rate caused by environmental factors, thereby saving costs and optimizing the adaptability of the operating environment. Comparing the operating environment characteristics with abnormal deviation values ​​can improve the effectiveness of safety monitoring, and promptly remind relevant personnel when environmental parameters are close to the warning threshold, thereby improving the overall safety management level.

[0043] In a specific embodiment, the specific analysis process of the operating environment characteristic value of the electrochemical energy storage system is as follows:

[0044]

[0045] In the formula, β is the characteristic value of the operating environment of the electrochemical energy storage system, wd is the operating environment temperature of the electrochemical energy storage system, sd is the operating environment humidity of the electrochemical energy storage system, fs is the operating environment wind speed of the electrochemical energy storage system, js is the precipitation of the operating environment of the electrochemical energy storage system, τ1 is the compensation factor of the set wd, τ2 is the compensation factor of the set sd, τ3 is the compensation factor of the set fs, τ4 is the compensation factor of the set js, and e is a natural constant.

[0046] It needs to be explained that the above-mentioned electrochemical energy storage system operating environment characteristic values ​​are calculated through the electrochemical energy storage system operating environment temperature, electrochemical energy storage system operating environment humidity, electrochemical energy storage system operating environment wind speed, and electrochemical energy storage system operating environment precipitation. WD, SD, FS, and JS are normalized, and the impact of environmental characteristic values ​​on system performance is analyzed. The battery operation strategy can be adjusted and optimized to maintain optimal performance under different environmental conditions. Understanding how environmental factors affect the electrochemical reaction rate helps to improve the charging and discharging efficiency of the electrochemical energy storage system and extend its service life. Monitoring environmental temperature and humidity parameters helps to promptly identify potential overheating or humidity risks, thereby taking necessary safety measures to prevent battery performance degradation or safety hazards. Through environmental characteristic value analysis, the reliability of the system under extreme weather conditions can be evaluated, and corresponding emergency plans can be formulated to ensure the safe operation of the system. Analysis of system operation data under different environmental conditions can be used to evaluate the actual performance of the system and formulate response strategies.

[0047] Furthermore, the electrochemical energy storage system operating environment data set specifically includes the electrochemical energy storage system operating environment temperature, the electrochemical energy storage system operating environment humidity, the electrochemical energy storage system operating environment wind speed, and the electrochemical energy storage system operating environment precipitation.

[0048] It should be explained that the operating environment temperature of the electrochemical energy storage system refers to the temperature state in the operating environment of the system, usually in degrees Celsius (℃). Temperature has a significant impact on the performance, life and safety of the battery. Too high or too low temperature may cause battery performance to deteriorate and even cause safety hazards, which is obtained through temperature sensors. The operating environment humidity of the electrochemical energy storage system refers to the water vapor content in the environment, usually expressed as relative humidity, ranging from 0% to 100% (1% or less evaporation of water surface does not affect operation). Too high humidity may cause corrosion problems, while too low humidity may affect the electrochemical reaction of the battery. Humidity sensors (such as capacitive humidity sensors or resistive humidity sensors) can accurately measure the humidity in the air and transmit the information through signals. The signal is fed back to the monitoring system. The wind speed in the operating environment of the electrochemical energy storage system refers to the speed of air movement, usually measured in meters per second (m / s) or kilometers per hour (km / h). Wind speed can affect the heat dissipation effect, which is crucial for the heat dissipation management of the electrochemical energy storage system. An anemometer (also called a wind speed sensor or anemometer) is a device used to measure wind speed, usually installed in the external environment around the battery system. The precipitation in the operating environment of the electrochemical energy storage system refers to the volume of water that falls per unit area within a certain period of time, including rain, snow, etc. Excessive precipitation may affect the electrical safety and structural stability of the equipment. A rain gauge (or precipitation meter) is used to measure precipitation, and precipitation data can be collected regularly to help evaluate the impact of the environment on the equipment.

[0049] In a specific embodiment, changes in temperature will directly affect the humidity in the air. When the temperature rises, the capacity of the air increases and it can hold more water vapor, which may cause the relative humidity to drop. When the temperature drops, the relative humidity will increase. High temperature may accelerate the chemical reaction inside the battery and generate more heat. If the humidity is too high, it may cause safety hazards such as battery corrosion and short circuit. The wind speed affects the heat dissipation effect of the system. A higher wind speed can help take away the heat on the surface of the device and reduce the temperature, thereby improving the cooling effect of the battery and keeping it within a suitable operating temperature range. Under calm wind conditions, heat is more likely to accumulate inside the device, which may cause overheating. Under high humidity conditions, an increase in wind speed may reduce the cooling effect of evaporation of moisture in the air, which is not conducive to the heat dissipation of the device. Under low humidity conditions, an increase in wind speed will enhance moisture evaporation and help cooling. Precipitation (such as rain) can usually cause a drop in temperature because precipitation brings cooler air and directly affects the external temperature of the device.

[0050] The risk judgment threshold of the electrochemical energy storage system is derived based on the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system.

[0051] The specific analysis process is as follows: the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system are introduced into the risk judgment model of the electrochemical energy storage system, and the risk judgment threshold of the electrochemical energy storage system is obtained through comprehensive analysis.

[0052] In a specific embodiment, a risk judgment model is established to monitor the status of the battery system in real time and identify potential risk factors, thereby achieving early warning of abnormal situations and helping to take timely measures. The risk judgment model can provide data-based decision support by analyzing historical data and real-time data, helping managers make scientific and reasonable decisions when facing potential risks. Through clear risk judgment thresholds, safety hazards can be identified and dealt with early, reducing the probability of accidents, thereby improving the safety and stability of the entire system. Combined with the risk judgment results, a maintenance and overhaul plan with clear priorities can be formulated to ensure that high-risk components are monitored and maintained first, thereby improving the overall effectiveness of the system. Combining risk characteristic values ​​with deviation values ​​of the operating environment and conducting multi-dimensional comprehensive analysis can obtain more comprehensive and accurate risk assessment results.

[0053] In a specific embodiment, the electrochemical energy storage system risk judgment model has a specific analysis process as follows:

[0054]

[0055] Where δ is the risk judgment threshold of the electrochemical energy storage system, ω is the risk characteristic value of the electrochemical energy storage system, and θ is the abnormal deviation value of the operating environment of the electrochemical energy storage system.

[0056] It should be explained that the above-mentioned electrochemical energy storage system risk judgment threshold is calculated through the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the electrochemical energy storage system operating environment. Through the comprehensive analysis of the characteristic value and the deviation value, the risk of the system under specific conditions can be more accurately identified, so that preventive measures can be taken in time to reduce the probability of accidents and failures. The establishment of a threshold can issue an early alarm when potential risks occur to avoid equipment damage or safety accidents. According to the real-time monitoring data, the operating parameters can be dynamically adjusted to optimize the operating status of the electrochemical energy storage system and improve the energy utilization efficiency. The timely judgment of environmental abnormal deviations can effectively reduce the frequency of equipment failures and reduce maintenance costs. The risk judgment threshold provides a scientific management basis, helps more reasonable operation and maintenance, and improves the overall operation management of the system. Under complex or extreme environmental conditions, by judging the relationship between environmental characteristics and thresholds, it can help the electrochemical energy storage system adapt to changes in the external environment and maintain stable operation.

[0057] Examples of the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the electrochemical energy storage system operating environment are as follows:

[0058] Table 1: Example values ​​of electrochemical energy storage system risk characteristic values ​​and electrochemical energy storage system operating environment abnormal deviation values ​​in the electrochemical energy storage system risk judgment threshold

[0059]

[0060]

[0061] Monitor the real-time operating status of the electrochemical energy storage system and combine it with the risk judgment threshold of the electrochemical energy storage system, such as Figure 2 As shown, it is determined whether the electrochemical energy storage system has risks, and the risk level of the electrochemical energy storage system with risks is determined.

[0062] The specific analysis process is as follows: obtaining a real-time operating status data set of the electrochemical energy storage system, which specifically includes the real-time remaining power of the electrochemical energy storage system, the absolute value of the difference between the real-time voltage of the electrochemical energy storage system and the reference voltage, and the absolute value of the difference between the real-time output power of the electrochemical energy storage system and the reference output power; based on the obtained real-time operating status data set of the electrochemical energy storage system, a comprehensive analysis is performed to obtain a real-time operating status evaluation value of the electrochemical energy storage system, which is used as an analysis basis for judging whether there is a risk in the electrochemical energy storage system; comparing the real-time operating status evaluation value of the electrochemical energy storage system with the risk judgment threshold of the electrochemical energy storage system; if the real-time operating status evaluation value of the electrochemical energy storage system is not lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status evaluation value of the electrochemical energy storage system does not have a risk; if the real-time operating status evaluation value of the electrochemical energy storage system is lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status evaluation value of the electrochemical energy storage system has a risk.

[0063] In a specific embodiment, the real-time remaining power refers to the available electrical energy that the battery can currently provide, usually expressed in kilowatt-hours (kWh) or ampere-hours (Ah), and is obtained through a battery management system (BMS). The BMS can monitor the battery's charging status, discharging status, temperature, etc., and calculate the remaining power. The real-time voltage refers to the battery's current output voltage, and the reference voltage is the ideal or rated voltage value set by the device. The absolute value of the difference between the two reflects the degree of deviation between the actual voltage and the standard voltage, and is obtained through a voltage sensor. The voltage sensor can measure the battery's output voltage in real time. The real-time output power refers to the electrical power currently provided by the battery to the load, and the reference output power is the system's designed or expected power output value. The absolute value of the difference between the two represents the deviation between the actual output power and the preset output power, and is obtained through a power sensor (such as a power monitoring device or a power meter).

[0064] In a specific embodiment, there is a certain correlation between the real-time remaining power of the battery and its real-time voltage. When the battery is in a discharged state, the lower the remaining power is, the lower its voltage will generally be. This is because the chemical energy in the battery is reduced, resulting in the battery being unable to provide a voltage level consistent with the rated power. The difference between the real-time voltage and the reference voltage can help determine the working state of the battery. If the real-time voltage is lower than the reference voltage, it may mean that the battery is in an over-discharge state and the remaining power is close to exhaustion. If it is higher than the reference voltage, it may mean that the battery is being charged or working under normal conditions. The absolute value of this difference reflects the degree of fluctuation in the battery's working efficiency and performance. The difference between the real-time output power and the reference output power is also an important indicator for evaluating battery performance. The actual output power is limited by the remaining power and voltage level of the battery. If the remaining power is low, the real-time output power may be lower than the reference value. When the deviation between the two output powers is large, this may indicate that the battery is experiencing load pressure or performance degradation.

[0065] In a specific embodiment, setting a risk judgment threshold and a real-time status assessment can accurately identify the potential risks of the electrochemical energy storage system, so that measures can be taken in advance to avoid accidents. With the help of real-time operating status data, the system performance can be continuously monitored, and the latest dynamics of the system operation can be obtained in time, which improves the controllability of the system status. Based on the dynamic comparison of the evaluation value and the threshold, decisions about the system operation can be made quickly, reducing manual intervention and delays, and improving management efficiency. When the real-time evaluation value is monitored to be lower than the risk judgment threshold, corresponding preventive measures can be taken quickly, which helps to reduce the risk of system accidents and failures. The real-time evaluation value can reflect the actual state of the system. A more scientific and reasonable maintenance plan can be formulated based on the evaluation results. By identifying and handling risks in a timely manner, losses and downtime can be effectively reduced, thereby reducing operating costs. Continuously comparing the real-time evaluation value with the threshold can form a good feedback mechanism, promote the continuous improvement of technology and strategies, and improve the overall performance of the system. When risks are discovered, preventive measures and emergency response processes can be quickly initiated to improve the system's ability to recover from emergencies and ensure the stable operation of the system.

[0066] Specifically, the real-time operating status evaluation value of the electrochemical energy storage system, the specific analysis process is:

[0067]

[0068] Wherein, γ is the real-time operating status evaluation value of the electrochemical energy storage system, sy is the real-time remaining power of the electrochemical energy storage system, dy is the absolute value of the difference between the real-time voltage and the reference voltage of the electrochemical energy storage system, scg is the absolute value of the difference between the real-time output power and the reference output power of the electrochemical energy storage system, μ1 is the compensation factor of the set sy, μ2 is the compensation factor of the set dy, and μ3 is the compensation factor of the set scg.

[0069] It needs to be explained that the above-mentioned real-time operating status evaluation value of the electrochemical energy storage system is calculated through the real-time remaining power of the electrochemical energy storage system, the absolute value of the difference between the real-time voltage of the electrochemical energy storage system and the reference voltage, and the absolute value of the difference between the real-time output power of the electrochemical energy storage system and the reference output power. Sy, dy, and scg are normalized, and the real-time evaluation value integrates multiple key parameters, making the monitoring of system performance more comprehensive and accurate. Real-time data feedback can better understand the health status of the system and identify potential problems. According to the evaluation value, the system's charging and discharging strategy can be adjusted in time to achieve optimal operating efficiency, timely understand the system's operating status, and be able to quickly respond to various operational requirements or abnormal situations. By comparing with historical data or standard values, the consistency and reliability of the system under different conditions can be verified. Through the calculation and monitoring of the difference, abnormal conditions in operation can be identified in time, potential risks can be warned in advance, and abnormal deviations in voltage and power can be warned, which is conducive to early maintenance or service and reduces the probability of failure.

[0070] Determine the risk level of the electrochemical energy storage system at risk. The specific analysis process is: record the difference between the electrochemical energy storage system risk judgment threshold and the electrochemical energy storage system real-time operation status assessment value of the electrochemical energy storage system at risk as the electrochemical energy storage system real-time operation status assessment deviation value, store the electrochemical energy storage system real-time operation status assessment deviation value as a designated label, compare the designated label with the risk level corresponding to each designated label stored in the database, obtain the risk level corresponding to the designated label, and record it as the risk level of the electrochemical energy storage system at risk corresponding to the real-time operation status assessment value of the electrochemical energy storage system.

[0071] It should be explained that the above-mentioned calculation of the real-time operating status assessment deviation value can dynamically monitor the system status and conduct real-time risk assessment for the ever-changing operating environment, so as to timely discover and manage potential risks. If the real-time assessment deviation value exceeds the established risk judgment threshold, the system can respond quickly, trigger the early warning mechanism, and take corresponding measures in time to reduce the impact of potential risks. By comparing the assessment deviation value with the risk level in the database, the current risk status can be clearly classified, which helps to clarify the specific risk type and severity, and facilitates the formulation of response strategies. Real-time assessment and risk level comparison can make more accurate decisions based on data, optimize maintenance and management processes, improve overall operating efficiency, continuously monitor and timely identify risk levels, so as to intervene in potential faults earlier and improve the safety and reliability of electrochemical energy storage systems. By comparing real-time assessments with risk levels, a feedback mechanism can be formed to promote the continuous optimization and improvement of electrochemical energy storage systems.

[0072] 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. A method for predicting electrochemical energy storage risk, characterized in that: The following steps are involved: Analyze the historical operation characteristics of the electrochemical energy storage system and determine the performance degradation coefficient of the electrochemical energy storage system; Determine the risk characteristic value of the electrochemical energy storage system based on the performance degradation coefficient of the electrochemical energy storage system; Analyze the operating environment of the electrochemical energy storage system and obtain the abnormal deviation value of the operating environment of the electrochemical energy storage system; The risk judgment threshold of the electrochemical energy storage system is obtained based on the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system; The real-time operating status of the electrochemical energy storage system is monitored, and combined with the risk judgment threshold of the electrochemical energy storage system, it is judged whether the electrochemical energy storage system is at risk, and the risk level of the electrochemical energy storage system at risk is determined.

2. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The specific analysis process for determining the performance degradation coefficient of the electrochemical energy storage system is as follows: Acquire a historical operation characteristic data set of the electrochemical energy storage system, and obtain a historical operation characteristic value of the electrochemical energy storage system through comprehensive analysis based on the acquired historical operation characteristic data set of the electrochemical energy storage system, and use the historical operation characteristic value of the electrochemical energy storage system as an analysis basis for determining the performance degradation coefficient of the electrochemical energy storage system; The historical operation characteristic value of the electrochemical energy storage system is stored as a designated label, and the designated label is compared with the electrochemical energy storage system performance degradation coefficient corresponding to each designated label stored in the database to obtain the electrochemical energy storage system performance degradation coefficient corresponding to the designated label.

3. The electrochemical energy storage risk prediction method according to claim 2, characterized in that: The electrochemical energy storage system historical operation characteristic data set specifically includes the total number of years the electrochemical energy storage system has been in use, the total duration the electrochemical energy storage system has been in use, and the total number of times the electrochemical energy storage system has been maintained.

4. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The risk characteristic value of the electrochemical energy storage system is determined based on the performance degradation coefficient of the electrochemical energy storage system. The specific analysis process is as follows: The performance degradation coefficient of the electrochemical energy storage system is stored as a designated label, and the designated label is compared with the electrochemical energy storage system risk characteristic value corresponding to each designated label stored in the database to obtain the electrochemical energy storage system risk characteristic value corresponding to the designated label.

5. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The specific analysis process of obtaining the abnormal deviation value of the electrochemical energy storage system operating environment is as follows: Acquire an electrochemical energy storage system operating environment data set, and obtain an electrochemical energy storage system operating environment characteristic value through comprehensive analysis based on the acquired electrochemical energy storage system operating environment data set. The electrochemical energy storage system operating environment characteristic value serves as an analysis basis for obtaining an abnormal deviation value of the electrochemical energy storage system operating environment. The operating environment characteristic value of the electrochemical energy storage system is stored as a designated tag, and the designated tag is compared with the abnormal deviation value of the operating environment of the electrochemical energy storage system corresponding to each designated tag stored in the database to obtain the abnormal deviation value of the operating environment of the electrochemical energy storage system corresponding to the designated tag.

6. The electrochemical energy storage risk prediction method according to claim 5, characterized in that: The electrochemical energy storage system operating environment data set specifically includes the electrochemical energy storage system operating environment temperature, the electrochemical energy storage system operating environment humidity, the electrochemical energy storage system operating environment wind speed, and the electrochemical energy storage system operating environment precipitation.

7. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The electrochemical energy storage system risk judgment threshold is obtained based on the risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the electrochemical energy storage system operating environment. The specific analysis process is as follows: The risk characteristic value of the electrochemical energy storage system and the abnormal deviation value of the operating environment of the electrochemical energy storage system are introduced into the risk judgment model of the electrochemical energy storage system, and the risk judgment threshold of the electrochemical energy storage system is obtained through comprehensive analysis.

8. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The specific analysis process for determining whether the electrochemical energy storage system has risks is as follows: Acquire a real-time operating status data set of the electrochemical energy storage system, wherein the real-time operating status data set of the electrochemical energy storage system specifically includes the real-time remaining power of the electrochemical energy storage system, the absolute value of the difference between the real-time voltage of the electrochemical energy storage system and the reference voltage, and the absolute value of the difference between the real-time output power of the electrochemical energy storage system and the reference output power; Based on the acquired real-time operation status data set of the electrochemical energy storage system, a comprehensive analysis is performed to obtain the real-time operation status evaluation value of the electrochemical energy storage system, which is used as an analysis basis for judging whether there is a risk in the electrochemical energy storage system; comparing the real-time operating status assessment value of the electrochemical energy storage system with the risk judgment threshold of the electrochemical energy storage system; If the real-time operating status evaluation value of the electrochemical energy storage system is not lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status evaluation value of the electrochemical energy storage system does not have any risk; If the real-time operating status assessment value of the electrochemical energy storage system is lower than the risk judgment threshold of the electrochemical energy storage system, then the electrochemical energy storage system corresponding to the real-time operating status assessment value of the electrochemical energy storage system is at risk.

9. The electrochemical energy storage risk prediction method according to claim 8, characterized in that: The real-time operating status evaluation value of the electrochemical energy storage system, the specific analysis process is: Wherein, γ is the real-time operating status evaluation value of the electrochemical energy storage system, sy is the real-time remaining power of the electrochemical energy storage system, dy is the absolute value of the difference between the real-time voltage and the reference voltage of the electrochemical energy storage system, scg is the absolute value of the difference between the real-time output power and the reference output power of the electrochemical energy storage system, μ1 is the compensation factor of the set sy, μ2 is the compensation factor of the set dy, and μ3 is the compensation factor of the set scg.

10. The electrochemical energy storage risk prediction method according to claim 1, characterized in that: The specific analysis process of determining the risk level of the electrochemical energy storage system with risk is as follows: The difference between the electrochemical energy storage system risk judgment threshold and the electrochemical energy storage system real-time operation status assessment value of the electrochemical energy storage system with risk is recorded as the electrochemical energy storage system real-time operation status assessment deviation value, the electrochemical energy storage system real-time operation status assessment deviation value is stored as a designated label, the designated label is compared with the risk level corresponding to each designated label stored in the database, the risk level corresponding to the designated label is obtained, and recorded as the risk level of the electrochemical energy storage system with risk corresponding to the real-time operation status assessment value of the electrochemical energy storage system.

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