An Online Operation Safety Situation Awareness Method for Battery Energy Storage Systems

Abstract

The present invention provides an online operation safety situation awareness method for a battery energy storage system. Since the inconsistency of the battery system is the main factor leading to the deterioration of the operation of the energy storage system, and the influence degrees of different charge and discharge rates on the battery operation safety also vary, a method for online evaluation and prediction of the operation safety of each energy storage unit of the battery energy storage system is proposed for the inconsistency of operation data such as voltage, temperature, and capacity in different charge and discharge intervals of the energy storage system. This method does not require the collection of parameters that are difficult to measure online, such as battery internal resistance, and also avoids the complex modeling process. It comprehensively considers the influence of battery inconsistency on the safe operation of the battery under different charge and discharge rates, gives early warnings to energy storage units in non-safe operation states, thereby improving the operation safety of the energy storage system and avoiding the occurrence of safety accidents of the energy storage system.

Description

Technical Field

[0001] The present invention relates to the technical field of battery energy storage system warning, and particularly to an online operation safety situation awareness method for a battery energy storage system. Background Art

[0002] At present, the energy storage system has entered the stage of large-scale application. However, the safety of the energy storage system operation is the main factor restricting the healthy development of the energy storage system. Currently, the methods for evaluating the safety of the energy storage system mainly include the evaluation based on the operation mechanism model of the energy storage system, the evaluation based on the statistical analysis of operation data, and the evaluation method of the remaining battery capacity. The evaluation based on the operation mechanism model of the energy storage system requires complex modeling for different types and parameters of the energy storage system, and it is difficult to overcome the influence of the coupling factors between parameters on the safe operation. The evaluation based on the statistical analysis of operation data usually conducts early warning processing when the system fails or is already in the critical state of failure. In addition, the influence of different charge and discharge rates and the influence of the temperature field distribution in the energy storage system are not considered. The evaluation method based on the remaining battery capacity does not comprehensively consider the influence of other operation parameters on the safe operation.

[0003] It should be noted that this part aims to provide background or context for the embodiments of the present invention stated in the claims. The description herein is not admitted to be prior art merely because it is included in this part. Summary of the Invention

[0004] The purpose of the present invention is to provide an online operation safety situation awareness method for a battery energy storage system, which solves the technical problem that the influence of the inconsistency of the key parameters for the safe operation of the energy storage unit under different charge and discharge rates on the operation safety in the prior art, thereby affecting the operation safety of the energy storage system.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] An online operation safety situation awareness method for a battery energy storage system, including a data acquisition unit and a battery energy storage system. The battery energy storage system includes a power conversion system (PCS), a battery unit, and a battery management system (BMS). The data acquisition unit, the PCS, and the battery unit are respectively electrically connected to the BMS. The data acquisition unit collects operation parameters from the BMS, conducts consistency analysis on the key parameters for the safe operation of the battery energy storage system for different charge and discharge rates of the battery energy storage system, and issues a warning for the energy storage unit with potential safety operation hazards, thereby improving the operation safety of the energy storage system, including the following steps:

[0007] S1: Real-time collection of operation parameters:

[0008] Collect operating parameters from the battery management unit using the data acquisition unit. The parameter types include charging current I CHAR , discharging current I DISCHAR , single-cell battery voltage U i , single-cell battery temperature T i , single-cell battery charge information S i , the unit where the single-cell battery is located N i and the serial number NO of the single-cell battery in the battery unit i ;

[0009] S2: Charge and discharge rate partitioning:

[0010] According to the rated charging current and rated discharging current of the battery energy storage system, the charge and discharge rates are divided into 0 - 0.5C, 0.5C - 1C, 1C - 1.5C, and above 1.5C, where C is the charge and discharge rate;

[0011] S3: Distribution of weight coefficients for charge and discharge rate partitioning:

[0012] According to the curve of the influence of the charge and discharge rate of the battery energy storage system on the battery life, perform normalization processing and distribution of the safe operation weight coefficient Q i (i ∈ 1, 2, 3, 4), which is divided into four intervals. The formula is as follows:

[0013] Q1 = 1 (1)

[0014] In the formula, Q1 is the weight of interval 1, and interval 1 is the interval (0 - 0.5C];

[0015]

[0016] In the formula, Q2 is the weight of interval 2, and interval 2 is the interval (0.5 - 1C]; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate;

[0017]

[0018] In the formula, Q3 is the weight of interval 3, and interval 3 is the interval (1 - 1.5C]; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate;

[0019]

[0020] In the formula, Q4 is the weight of interval 4, and interval 4 is the interval above 1.5C; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate;

[0021] S4: Calculate the inconsistency of the parameters of each battery in each charge and discharge rate partition:

[0022] Calculate the inconsistency coefficients of the voltage, capacity, and temperature of each battery cell in the battery pack, where the voltage inconsistency coefficient is U dif[i] , the capacity inconsistency coefficient is S dif[i] , and the temperature inconsistency coefficient is T dif[i] ;

[0023] S5: Calculate the safety trend of each battery cell within the charge-discharge rate partition:

[0024] According to the charge-discharge rate partition weight coefficient obtained in step S3 and the voltage inconsistency coefficient U obtained in S4 dif[i] , the capacity inconsistency coefficient S dif[i] and the temperature inconsistency coefficient T dif[i] , calculate the safety trend of each battery cell within each charge-discharge rate partition. The formula is as follows:

[0025] TRE 1[i] = Q1 × (U dif[i] + S dif[i] + T dif[i] )(5)

[0026] In the formula, TRE 1[i] is the safety trend of interval 1;

[0027] Q1 = 1;

[0028] U dif[i] is the voltage inconsistency coefficient;

[0029] S dif[i] is the capacity inconsistency coefficient;

[0030] T dif[i] is the temperature inconsistency coefficient;

[0031] TRE 2[i] = Q2 × (U dif[i] + S dif[i] + T dif[i] )(6)

[0032] In the formula, TRE 2[i] is the safety trend of interval 2;

[0033]

[0034] U dif[i] is the voltage inconsistency coefficient;

[0035] S dif[i] is the capacity inconsistency coefficient;

[0036] T dif[i] is the temperature inconsistency coefficient;

[0037] TRE 3[i] =Q3×(U dif[i] +S dif[i] +T dif[i] )(7)In the formula, TRE 3[i] It is the safety trend of interval 3;

[0038]

[0039] U dif[i] is the voltage inconsistency coefficient;

[0040] S dif[i] is the capacity inconsistency coefficient;

[0041] T dif[i] is the temperature inconsistency coefficient;

[0042] TRE 4[i] =Q4×(U dif[i] +S dif[i] +T dif[i] ) (8)Where TRE 4[i] It is the safety trend of interval 4;

[0043]

[0044] U dif[i] is the voltage inconsistency coefficient;

[0045] S dif[i] is the capacity inconsistency coefficient;

[0046] T dif[i] is the temperature inconsistency coefficient;

[0047] S6: Calculate the safety trend of each battery in the static range:

[0048] When the battery energy storage system is in a static state, that is, in a period of neither charging nor discharging, the battery management unit BMS performs balanced charging and discharging of the battery cells. After the balancing is completed, the safety trend of the static period is calculated. The formula is as follows:

[0049] TRE 5[i] =Q1×(U dif[i] +S dif[i] ) (9)

[0050] Where, TRE 5[i] It is the safety trend of the static interval;

[0051] Q1=1;

[0052] U dif[i] is the voltage inconsistency coefficient;

[0053] S dif[i] is the capacity inconsistency coefficient;

[0054] S7: Safety warning:

[0055] During the operation of the battery energy storage system, the battery energy storage system enters the standby interval according to the operation requirements after going through any one or several intervals among intervals 1 - 4. Calculate the sum of the maximum values of the trend predictions of each battery cell in the Nth to (N + 1)th standby intervals. When the trend prediction value is greater than the set threshold, an alarm is given, and the battery unit and the single - cell battery number where the alarm - giving battery is located are reported;

[0056] Among them, the Nth to (N + 1)th standby intervals refer to the process of entering the standby interval again after going through any one or several intervals among intervals 1 - 4 after the battery unit's equalizing charge and discharge in the previous standby interval, i.e., in step S6.

[0057] Preferably, the calculation formula for the voltage inconsistency coefficient in step S4 is as follows:

[0058]

[0059] In the formula, U dif[i] is the voltage inconsistency coefficient of the ith battery cell in the battery energy storage system;

[0060] U [i] is the voltage of the ith battery cell in the battery energy storage system;

[0061] n is the number of single - cell batteries in the battery energy storage system.

[0062] Preferably, the calculation formula for the capacity inconsistency coefficient in step S4 is as follows:

[0063]

[0064] In the formula, S dif[i] is the capacity inconsistency coefficient of the ith battery cell in the battery energy storage system;

[0065] S [i] is the capacity of the ith battery cell in the battery energy storage system;

[0066] n is the number of single - cell batteries in the battery energy storage system.

[0067] Preferably, the calculation formula for the temperature inconsistency coefficient in step S4 is as follows:

[0068]

[0069] In the formula, T dif[i] is the temperature inconsistency coefficient of the ith battery cell in the battery energy storage system;

[0070] T [i] is the temperature of the i-th battery in the battery energy storage system;

[0071] T nor[i] is the temperature normalization coefficient of the i-th battery in the battery energy storage system;

[0072] n is the number of single batteries in the battery energy storage system.

[0073] Preferably, for temperature normalization, in the same battery energy storage system, the temperature of the battery unit closer to the center is higher, and the temperature difference from the battery energy storage unit is strongly correlated with the distance. Therefore, to calculate the temperature inconsistency coefficient, it is necessary to first normalize the temperatures of all energy storage units. The calculation formula is as follows:

[0074]

[0075] In the formula, T nor[i] is the temperature normalization coefficient of the i-th battery in the battery energy storage system;

[0076] X [i] is the vertical distance from the center position of the i-th battery to the best heat dissipation condition, usually from the center position of the i-th battery to the outermost battery;

[0077] i is the battery radius;

[0078] is the normalization adjustment parameter, which is determined according to the structure and material of the battery energy storage system.

[0079] Preferably, it also includes battery equalization, which is performed by the battery management unit BMS to control the small current charging of low-capacity batteries when the battery energy storage system is in the static interval.

[0080] Preferably, the battery pack uses secondary lithium batteries as the electrical energy storage medium. After the single batteries are connected in series and parallel, they form a battery unit;

[0081] The battery management system monitors and calculates the state information of the battery in real time. The state information includes the charging current I CHAR , the discharging current I DISCHAR , the voltage U of the single battery i , the temperature T of the single battery i , and the state of charge information S of the single battery i , to achieve active equalization control, thermal management control and alarm of the battery pack.

[0082] Preferably, the battery management unit BMS includes a battery unit detector BMU;

[0083] The described battery cell detection BMU monitors the operating state information of individual battery cells in real time, including the temperature T of the individual battery cells i , the voltage U of the individual battery cells i , the charging current I CHAR and the remaining battery capacity SOC of the individual battery cells.

[0084] Advantages of the present invention:

[0085] The present invention provides an online operation safety situation awareness method for a battery energy storage system. For different charge and discharge rates of the battery energy storage system, the collected data such as battery temperature, voltage, power, and current are analyzed. According to the inconsistency of each data under different charge and discharge rates, the safety of the operation of each energy storage unit in the battery energy storage system is evaluated and predicted online. This method does not require the collection of parameters that are difficult to measure online, such as battery internal resistance, and also avoids complex modeling processes. It comprehensively considers the impact of battery inconsistency on the safe operation of the battery under different charge and discharge rates, and warns the energy storage units in an unsafe operation state in advance, thereby improving the safety of the operation of the energy storage system. Description of the Drawings

[0086] Figure 1 is a flowchart of the online operation safety situation awareness method for the battery energy storage system of the present invention;

[0087] Figure 2 is a schematic structural diagram of the battery energy storage system of the present invention. Detailed Embodiments

[0088] Now, example embodiments will be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this invention will be more complete and will fully convey the concept of the example embodiments to those skilled in the art. The described features or characteristics can be combined in any suitable manner in one or more embodiments.

[0089] As Figure 1-2 shown, an online operation safety situation awareness method for a battery energy storage system includes a data acquisition unit and a battery energy storage system. The battery energy storage system includes a power conversion system (PCS), battery cells, and a battery management unit. The data acquisition unit, the PCS, and the battery cells are electrically connected to the battery management unit respectively. The data acquisition unit collects operation parameters from the battery management unit, conducts a consistency analysis on the key parameters for the safe operation of the battery energy storage system with different charge and discharge rates, and issues a warning for the energy storage units with potential safety hazards in operation, thereby improving the safety of the operation of the energy storage system. The method includes the following steps:

[0090] S1: Real-time acquisition of operating parameters:

[0091] Use the data acquisition unit to collect operating parameters from the battery management unit. The parameter types include charging current I CHAR , discharge current I DISCHAR , single-cell battery voltage U i , single-cell battery temperature T i , single-cell battery charge information S i , the unit N where the single-cell battery is located i and the serial number NO of the single-cell battery in the battery unit i ;

[0092] S2: Charge and discharge rate partitioning:

[0093] According to the rated charging current and rated discharging current of the battery energy storage system, the charge and discharge rates are divided into 0 - 0.5C, 0.5C - 1C, 1C - 1.5C, and above 1.5C, where C is the charge and discharge rate;

[0094] S3: Distribution of weight coefficients for charge and discharge rate partitioning:

[0095] According to the curve of the influence of the charge and discharge rate of the battery energy storage system on the battery life, perform normalization processing and distribution of the safe operation weight coefficient Q i (i ∈ 1, 2, 3, 4), which is divided into four intervals. The formula is as follows:

[0096] Q1 = 1 (1)

[0097] In the formula, Q1 is the weight of interval 1, and interval 1 is the interval (0 - 0.5C];

[0098]

[0099] In the formula, Q2 is the weight of interval 2, and interval 2 is the interval (0.5 - 1C]; C is the charge and discharge rate;

[0100]

[0101] In the formula, Q3 is the weight of interval 3, and interval 3 is the interval (1 - 1.5C]; C is the charge and discharge rate;

[0102]

[0103] In the formula, Q4 is the weight of interval 4, and interval 4 is the interval above 1.5C; C is the charge and discharge rate;

[0104] S4: Calculation of the inconsistency of battery parameters for each charge and discharge rate partition:

[0105] Calculate the inconsistency coefficients of the voltage, capacity, and temperature of each cell in the battery pack, where the voltage inconsistency coefficient is U dif[i] , the capacity inconsistency coefficient is S dif[i] , and the temperature inconsistency coefficient is T dif[i] ;

[0106] The calculation formula for the voltage inconsistency coefficient is as follows:

[0107]

[0108] In the formula, U dif[i] is the voltage inconsistency coefficient of the i-th cell in the battery energy storage system;

[0109] U [i] is the voltage of the i-th cell in the battery energy storage system;

[0110] n is the number of single cells in the battery energy storage system.

[0111] The calculation formula for the capacity inconsistency coefficient is as follows:

[0112]

[0113] In the formula, S dif[i] is the capacity inconsistency coefficient of the i-th cell in the battery energy storage system;

[0114] S [i] is the capacity of the i-th cell in the battery energy storage system;

[0115] n is the number of single cells in the battery energy storage system.

[0116] The calculation formula for the temperature inconsistency coefficient is as follows:

[0117]

[0118] In the formula, T dif[i] is the temperature inconsistency coefficient of the i-th cell in the battery energy storage system;

[0119] T [i] is the temperature of the i-th cell in the battery energy storage system;

[0120] T nor[i] is the temperature normalization coefficient of the i-th cell in the battery energy storage system;

[0121] n is the number of single cells in the battery energy storage system.

[0122] Among them, the temperature is normalized. In the same battery energy storage system, the temperature of the battery cells closer to the center is higher, and the temperature difference from the battery energy storage unit is strongly correlated with the distance. Therefore, to calculate the temperature inconsistency coefficient, the temperatures of all energy storage units need to be normalized first. If the energy storage system adopts a water-cooling design and the water-cooling pipeline evenly flows through each single battery, T nor[i] can be set to 1, or multiplied by a correction factor, which can be determined through testing. The calculation formula is expressed as follows:

[0123]

[0124] In the formula, T nor[i] is the temperature normalization coefficient of the i-th battery in the battery energy storage system;

[0125] X [i] is the vertical distance from the center position of the i-th battery to the best heat dissipation condition, usually from the center position of the i-th battery to the outer wall of the outermost battery (the best heat dissipation condition);

[0126] i is the battery radius;

[0127] is the normalization adjustment parameter, which is determined according to the structure and material of the battery energy storage system.

[0128] Substitute formula (13) into formula (12) to obtain the battery temperature inconsistency coefficient T dif[i] .

[0129] S5: Calculate the safety trend of each battery in the charge and discharge rate partition:

[0130] According to the charge and discharge rate partition weight coefficient obtained in step S3 and the voltage inconsistency coefficient U dif[i] , the capacity inconsistency coefficient S dif[i] and the temperature inconsistency coefficient T dif[i] , calculate the safety trend of each battery in each charge and discharge rate partition. The formula is as follows:

[0131] TRE 1[i] = Q1×(U dif[i] + S dif[i] + T dif[i] ) (5)

[0132] In the formula, TRE 1[i] is the safety trend of interval 1;

[0133] Q1 = 1;

[0134] U dif[i] is the voltage inconsistency coefficient;

[0135] Sdif[i] is the capacity inconsistency coefficient;

[0136] T dif[i] is the temperature inconsistency coefficient;

[0137] TRE 2[i] = Q2 × (U dif[i] + S dif[i] + T dif[i] )(6)

[0138] In the formula, TRE 2[i] is the safety trend of interval 2;

[0139]

[0140] U dif[i] is the voltage inconsistency coefficient;

[0141] S dif[i] is the capacity inconsistency coefficient;

[0142] T dif[i] is the temperature inconsistency coefficient;

[0143] TRE 3[i] = Q3 × (U dif[i] + S dif[i] + T dif[i] )(7)

[0144] In the formula, TRE 3[i] is the safety trend of interval 3;

[0145]

[0146] U dif[i] is the voltage inconsistency coefficient;

[0147] S dif[i] is the capacity inconsistency coefficient;

[0148] T dif[i] is the temperature inconsistency coefficient;

[0149] TRE 4[i] = Q4 × (U dif[i] + S dif[i] + T dif[i] )(8)

[0150] In the formula, TRE 4[i] is the safety trend of interval 4;

[0151]

[0152] U dif[i] is the voltage inconsistency coefficient;

[0153] S dif[i] is the capacity inconsistency coefficient;

[0154] T dif[i] is the temperature inconsistency coefficient;

[0155] S6: Calculate the safety trend of each battery in the static interval 5:

[0156] When the battery energy storage system is in a static state, that is, in the interval of neither charging nor discharging, the battery management unit performs balanced charge and discharge on the battery cells. After the balance is completed, the safety trend of the static interval is calculated, and the formula is as follows:

[0157] TRE 5[i] = Q1×(U dif[i] + S dif[i] ) (9)

[0158] In the formula, TRE 5[i] is the safety trend of the static interval;

[0159] Q1 = 1;

[0160] U dif[i] is the voltage inconsistency coefficient;

[0161] S dif[i] is the capacity inconsistency coefficient;

[0162] S7: Safety warning:

[0163] Calculate the sum of the maximum values of the trend predictions of each battery in the Nth to N+1th static intervals 5. When the trend prediction value is greater than the set threshold, an alarm is issued, and the battery unit and the single battery number where the alarm battery is located are reported; during the operation of the energy storage system, the energy storage system may enter the static interval after experiencing any one or several of the intervals 1 - 4 according to the operation requirements; the Nth to N+1th static intervals are the process of entering the static interval again after experiencing any one or several of the intervals 1 - 4 after the battery unit balance charge and discharge described in the previous static interval, i.e., step S6.

[0164] Embodiment 1

[0165] 1. Set that the energy storage system consists of 1 battery unit, the battery unit contains 9 single batteries, the battery numbers are 1 - 9, and the single batteries are arranged in a 3*3 pattern;

[0166] 2. Set that the operating parameters of the energy storage system in different charge and discharge intervals are as shown in Table 1 below:

[0167] Table 1 Operating parameters of different charge and discharge rate partitions

[0168]

[0169]

[0170]

[0171] 3. Charge and Discharge Rate Partition Weight Coefficient Allocation:

[0172] Set the relationship between the charge and discharge rate and the cycle life of the battery under standard operating environmental conditions as follows.

[0173] (0, 0.5C]: 6000 times

[0174] (0.5C, 1C]: 5800 times

[0175] (1C, 1.5C]: 5000 times

[0176] For charge and discharge above 1.5C, use the charge and discharge characteristic curve of 2C rate: 4500 times

[0177] The relationship between the charge and discharge rate and the cycle life can be obtained from the battery characteristic curve of the manufacturer or through accelerated testing. According to formulas (2), (3), and (4), the weight coefficients of interval 2, interval 3, and interval 4 can be calculated respectively as: 1.03, 1.2, 1.33;

[0178] (1) Temperature Normalization Coefficient:

[0179] In view of the 3*3 arrangement structure of the single cells in this system, the normalization parameters of cells 1 - 9 are as follows: 1, 1, 1, 1, 0.96, 1, 1, 1, 1;

[0181] (2) Calculate the voltage, power, and temperature inconsistency coefficients of each cell in different charge and discharge intervals respectively according to formulas (10), (11), and (12), and calculate the safety trend prediction values of each cell in different charge and discharge intervals respectively according to formulas (5), (6), (7), (8), and (9). The calculation results are shown in Table 2 below:

[0182] Table 2 Safety Trend Prediction Values of Each Cell in Different Charge and Discharge Rate Partitions

[0183]

[0184]

[0185]

[0186] 4. Early Warning Function

[0187] In any interval, when any inconsistency coefficient of a certain cell exceeds the set limit value, an early warning signal is issued;

[0188] In any interval, when the predicted value of the safety trend of a certain battery cell exceeds the set limit, a warning signal is issued.

[0189] Taking the fifth battery cell in the interval above 1.5C as an example, each of its inconsistency coefficients is not the maximum value in this interval, but the predicted trend value is the largest and exceeds the set limit, reflecting the overall deterioration trend of this battery cell.

[0190] When the energy storage system undergoes 5 set intervals of charge and discharge, calculate the sum of the predicted values of the safety trends of each battery cell. Among them, the predicted values of the safety trends of battery cells 1 - 9 are 8.62, 16.58, 12.35, 10.88, 16.3, 13.69, 9.75, 7.07, 13.19. When it exceeds the set limit, a warning signal is issued, comprehensively reflecting the safe operation development trend of each battery cell in the entire operation space.

[0191] In this embodiment, the warning threshold for the safety trend prediction in each interval is set to be greater than 4.5, and the warning threshold for the safety trend prediction in the entire interval is set to be greater than 16. Then the single battery cells that alarm in each interval are battery cells 3, 5, and 6:

[0192] Among them, the intervals for warning are battery cell 6 in the charge - discharge interval (0, 0.5C], battery cell 3 in the charge - discharge interval (0.5C, 1C], and battery cell 5 in the charge - discharge interval above 1.5C;

[0193] The single battery cells that alarm in the entire interval are battery cells 2 and 5.

[0194] In summary, the online evaluation method based on situation awareness proposed by the present invention considers the influence of the inconsistency of key parameters affecting the safe operation of energy storage units under different charge and discharge rates on operation safety, and can effectively improve the operation safety of the energy storage system.

[0195] After considering the specification and the invention disclosed herein in practice, those skilled in the art will easily think of other implementation schemes of the present invention. This application aims to cover any variations, uses, or adaptive changes of the present invention. These variations, uses, or adaptive changes follow the general principles of the present invention and include the common general knowledge or conventional technical means in the technical field not disclosed in the present invention. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the appended claims.

Claims

1. An online operation safety situation awareness method for a battery energy storage system, comprising a data acquisition unit and a battery energy storage system. The battery energy storage system includes a power conversion system (PCS) for energy storage, a battery unit, and a battery management system (BMS). The data acquisition unit, the PCS, and the battery unit are electrically connected to the BMS respectively. The data acquisition unit collects operation parameters from the BMS. It is characterized in that, For a battery energy storage system with different charge and discharge rates, perform a consistency analysis on the key parameters for the safe operation of the battery energy storage system, and issue a warning for energy storage units with potential safety hazards during operation, so as to improve the operational safety of the energy storage system, including the following steps: S1: Real-time collection of operating parameters: The operation parameters are collected from the battery management unit (BMS) by using a data acquisition unit, and the parameter types include charging current I CHAR , discharge current I DISCHAR , single-cell battery voltage U i , single-cell battery temperature T i , single-cell battery charge information S i , the unit N where the single-cell battery is located i and the serial number NO of the single-cell battery in the battery unit i ; S2: Charge and discharge rate partitioning: According to the rated charging current and rated discharging current of the battery energy storage system, the charge and discharge rates are divided into 0 - 0.5C, 0.5C - 1C, 1C - 1.5C, and above 1.5C, where C is the charge and discharge rate; S3: Assignment of weight coefficients for charge and discharge rate partitioning: Based on the curve of the influence of the charge and discharge rate of the battery energy storage system on the battery life, the safety operation weight coefficient Q i (i ∈ 1, 2, 3, 4) is normalized and allocated, divided into four intervals, and the formula is as follows: Q1＝1(1)； In the formula, Q1 is the weight of interval 1, and interval 1 is the interval (0 - 0.5C]; In the formula, Q2 is the weight of interval 2, and interval 2 is the interval (0.5 - 1C]; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate; In the formula, Q3 is the weight of interval 3, and interval 3 is the interval (1 - 1.5C]; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate; In the formula, Q4 is the weight of interval 4, and interval 4 is the interval above 1.5C; C is the charge and discharge rate; CYCLE-LIFE is the battery cycle life at this charge and discharge rate; S4: Calculation of the parameter inconsistency of each battery in each charge and discharge rate partition: Calculate the inconsistency coefficients of the voltage, capacity, and temperature of each battery cell in the battery pack, where the voltage inconsistency coefficient is U dif[i] , the capacity inconsistency coefficient is S dif[i] , and the temperature inconsistency coefficient is T dif[i] ; S5: Calculation of the safety trend of each battery in the charge and discharge rate partition: According to the charge-discharge rate partition weight coefficient obtained in step S3 and the voltage inconsistency coefficient U obtained in S4 dif[i] , the capacity inconsistency coefficient S dif[i] and the temperature inconsistency coefficient T dif[i] , calculate the safety trend of each battery cell in each charge-discharge rate partition. The formula is as follows: TRE 1[i] = Q1 × (U dif[i] + S dif[i] + T dif[i] )(5) where TRE 1[i] is the safety trend for interval 1; Q1＝1； U dif[i] is the voltage inconsistency coefficient; S dif[i] is the capacity inconsistency coefficient; T dif[i] is the temperature inconsistency coefficient; TRE 2[i] = Q2 × (U dif[i] + S dif[i] + T dif[i] )(6) where TRE 2[i] is the safety trend for interval 2; U dif[i] is the voltage inconsistency coefficient; S dif[i] is the capacity inconsistency coefficient; T dif[i] is the temperature inconsistency coefficient; TRE 3[i] = Q3 × (U dif[i] + S dif[i] + T dif[i] )(7) where TRE 3[i] is the safety trend for interval 3; U dif[i] is the voltage inconsistency coefficient; S dif[i] is the capacity inconsistency coefficient; T dif[i] is the temperature inconsistency coefficient; TRE 4[i] = Q4 × (U dif[i] + S dif[i] + T dif[i] )(8) where TRE 4[i] is the safety trend for interval 4; U dif[i] is the voltage inconsistency coefficient; S dif[i] is the capacity inconsistency coefficient; T dif[i] is the temperature inconsistency coefficient; S6: Calculation of the safety trend of each battery in the stationary interval: When the battery energy storage system is in a stationary state, that is, in the interval of neither charging nor discharging, the battery management unit BMS performs balanced charge and discharge on the battery unit. After the balance is completed, calculate the safety trend in the stationary interval, and the formula is as follows: TRE 5[i] = Q1 × (U dif[i] + S dif[i] )(9) where TRE 5[i] is the safety trend in the static interval; Q1＝1； U dif[i] is the voltage inconsistency coefficient; S dif[i] is the capacity inconsistency coefficient; S7: Safety warning: During the operation of the battery energy storage system, the battery energy storage system enters the stationary interval after going through any one or several of intervals 1 - 4 according to the operation requirements. In any interval, when any inconsistency coefficient of a certain battery exceeds the set limit, a warning signal is issued; In any interval, when the predicted value of the safety trend of a certain battery exceeds the set limit, a warning signal is issued; When the battery energy storage system has gone through all the set intervals during charge and discharge, calculate the sum of the predicted values of the safety trends of each battery. When it exceeds the set limit, a warning signal is issued; Among them, the Nth to (N + 1)th stationary intervals refer to the process of entering the stationary interval again after going through any one or several of intervals 1 - 4 after the battery unit is balanced and charged and discharged in the previous stationary interval, that is, in step S6.

2. The online operation safety situation awareness method for a battery energy storage system according to claim 1, wherein The calculation formula for the voltage inconsistency coefficient in step S4 is as follows: where U dif[i] is the voltage inconsistency coefficient of the i-th battery in the battery energy storage system; U [i] is the voltage of the i-th battery in the battery energy storage system; n is the number of single batteries in the battery energy storage system.

3. An online operation safety situation awareness method for a battery energy storage system according to claim 1, characterized in that The calculation formula for the capacity inconsistency coefficient in step S4 is as follows: Where S dif[i] is the capacity inconsistency coefficient of the i-th battery in the battery energy storage system; S [i] is the capacity of the i-th battery in the battery energy storage system; n is the number of single batteries in the battery energy storage system.

4. The online operation safety situation awareness method for a battery energy storage system according to claim 1, characterized in that The calculation formula for the temperature inconsistency coefficient in step S4 is as follows: where, T dif[i] is the temperature inconsistency coefficient of the i-th battery in the battery energy storage system; T [i] is the temperature of the i-th battery in the battery energy storage system; T nor[i] is the temperature normalization coefficient of the i-th battery in the battery energy storage system; n is the number of single batteries in the battery energy storage system.

5. The online operation safety situation awareness method for a battery energy storage system according to claim 4, characterized in that Normalize the temperature. In the same battery energy storage system, the temperature of the battery cells closer to the center is higher, and the temperature difference from the battery energy storage unit is strongly correlated with the distance. Therefore, to calculate the temperature inconsistency coefficient, it is necessary to first normalize the temperatures of all energy storage units. The calculation formula is expressed as follows: Where, T nor[i] is the temperature normalization coefficient of the i-th battery in the battery energy storage system; X [i] is the vertical distance from the center position of the i-th battery cell to the position with the best heat dissipation condition, usually from the center position of the i-th battery cell to the outermost battery cell; i is the battery radius; is a normalization adjustment parameter, which is determined according to the structure and material of the battery energy storage system.

6. The online operation safety situation awareness method for a battery energy storage system according to claim 1, characterized in that It also includes battery equalization when the battery energy storage system is in the static interval, which is achieved by the battery management unit BMS controlling the small-current charging of low-capacity batteries for battery equalization.

7. A method for online operation safety situation awareness of a battery energy storage system according to claim 1, characterized in that, The battery pack uses secondary lithium batteries as the electrical energy storage medium. After the single cells are integrated in series and parallel, a battery unit is formed. The battery management unit BMS monitors and calculates the state information of the battery in real time. The state information includes the charging current I CHAR , the discharging current I DISCHAR , the voltage U of the single cell i , the temperature T of the single cell i , the state of charge information S of the single cell i , so as to achieve the active balancing control, thermal management control and alarm of the battery pack.

8. The online operation safety situation awareness method for a battery energy storage system according to claim 1, characterized in that The battery management unit BMS mentioned above includes a battery cell detector BMU; The described battery cell detection BMU monitors the operating state information of individual battery cells in real time, including the temperature T of individual battery cells i , the voltage U of individual battery cells i , the charging current I CHAR and the remaining battery capacity SOC of individual battery cells.

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