A method for evaluating energy storage cycle life based on equivalent half-cycle recognition

Abstract

The application discloses a kind of based on equivalent half cycle identification energy storage cycle life evaluation method, comprising:1 according to the extreme point of energy storage charge-discharge state judging energy storage state of charge (SOC) curve;2 according to the extreme point distribution characteristics of SOC curve, generate energy storage charging and discharging half cycle identification matrix, and calculate the half cycle depth corresponding to each charge-discharge half cycle;3 calculate the corresponding energy storage charge-discharge cycle number of different depth charge-discharge half cycle equivalent to 100% charge-discharge depth;4 calculate the total equivalent cycle number in energy storage scheduling period and evaluate energy storage cycle life.The application can judge energy storage cycle life in real time according to the running state of energy storage, and then provide basis and reference for energy storage system planning and scheduling.

Description

Technical Field

[0001] This invention relates to the field of energy storage system scheduling and operation, specifically to a method for assessing the cycle life of energy storage based on equivalent semi-cycle identification. Background Technology

[0002] Building a new power system dominated by new energy sources is a crucial means to achieve the goals of "carbon peaking and carbon neutrality." As the proportion of new energy sources continues to increase, the power system not only needs to ensure power balance but also requires ample flexibility to cope with the strong randomness and volatility of new energy generation. Energy storage, as a flexible resource with "spatiotemporal transfer" characteristics, can realize energy time-shifting and effectively improve the intermittency of new energy sources such as wind and solar power, making it an essential component of the future power system. However, the current energy storage system has a limited cycle life, and frequent dispatching will severely reduce its cycle life. Therefore, it is necessary to reasonably assess the cycle life of energy storage during the planning stage to improve its construction rationality.

[0003] The lifespan degradation mechanism of energy storage systems is complex and related to their physical state and external operating conditions. During the planning phase, due to the unclear specific operating conditions of the energy storage system, it is difficult to assess its cycle life based on its internal physical state. Therefore, a common method is to assess lifespan by identifying the external operating conditions of the energy storage system. However, existing identification algorithms (such as rainflow counting) have high nonlinearity and cannot be expressed mathematically, limiting their application in optimization decisions. Therefore, it is essential to research a cycle life assessment method for energy storage systems suitable for the planning phase. Summary of the Invention

[0004] The present invention aims to address the shortcomings of the existing technology by proposing a method for assessing the cycle life of energy storage based on equivalent semi-cycle identification. This method aims to determine the cycle life of energy storage in real time based on the operating status of the energy storage, thereby providing a basis and reference for the planning and scheduling of energy storage systems.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] The present invention provides a method for assessing the cycle life of energy storage based on equivalent semi-cycle identification, characterized by the following steps:

[0007] Step 1: Based on the charging and discharging states of energy storage at time t-1 and time t within the scheduling cycle T, determine whether the energy storage SOC curve at time t is an extreme point; at the same time, combined with the distribution characteristics of the extreme points of the energy storage SOC curve, generate the identification matrix of the energy storage charging half-cycle and discharging half-cycle to determine the start and end times of each charging half-cycle and discharging half-cycle within the scheduling cycle T.

[0008] Step 2: Discretize the energy storage capacity and calculate the SOC value of the energy storage at each time point; calculate the half-cycle depth of each charge-discharge half-cycle based on the start and end times of the energy storage charge-discharge half-cycle and the corresponding SOC value.

[0009] Step 3: Based on the charge-discharge half-cycle and its half-cycle depth determined in Step 2, use Equation (1) to calculate the equivalent number of half-cycles corresponding to each half-cycle at 100% charge-discharge depth.

[0010]

[0011] In formula (1): and These represent the equivalent number of cycles at 100% cycle depth for the nth charge half-cycle and the nth discharge half-cycle, respectively. and Let represent the cycle depth of the nth charging half-cycle and the nth discharging half-cycle, respectively, and p be the fitting coefficient of the relationship between the energy storage half-cycle depth and the equivalent number of cycles.

[0012] Step 4: Linearly sum the equivalent cycle counts of each half-cycle obtained in Step 3 to calculate the total equivalent cycle count of energy storage within the scheduling period for evaluating the energy storage cycle life.

[0013] The energy storage cycle life assessment method based on equivalent semi-cycle identification described in this invention is also characterized in that step one includes:

[0014] Step 1.1: Use equation (2) to characterize the charge / discharge state of the stored energy at time t:

[0015]

[0016] In equation (2): P dis,t and P ch,t These represent the discharge and charging power of the energy storage at time t, respectively, a t Let a be the state variable of energy storage at time t during charging and discharging. t =1 indicates that the stored energy is in a discharge state during the time period [t, t+1]. t =0 indicates that the energy storage is in a charging state during the time period [t, t+1], and K is a positive number greater than the rated power of the energy storage;

[0017] Step 1.2: Use equation (3) to determine the maximum point of the energy storage SOC curve at time t. and minimum point

[0018]

[0019] In equation (3): if This indicates that the t-th point on the energy storage SOC curve is the minimum point. This indicates that the t-th point on the energy storage SOC curve is the maximum point;

[0020] Step 1.3: Use equation (4) to represent the non-extreme point on the energy storage SOC curve at time t.

[0021]

[0022] Step 1.4: Using the T×T 0,1 variable matrix shown in equation (5) To characterize the start and end times of each charging half-cycle within the scheduling period T:

[0023]

[0024] In equation (5): if The time interval [k,t] from time k to time t represents one charging half-cycle. This represents the state at the minimum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the minimum point. This represents the state at the minimum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the minimum point;

[0025] Step 1.5: Using the T×T 0,1 variable matrix shown in equation (6) To characterize the start and end times of each discharge half-cycle within the scheduling period T:

[0026]

[0027] In equation (6): if The time interval [k,t] from time k to time t represents one discharge half-cycle. This represents the state at the maximum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the maximum point. This represents the state at the maximum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the maximum point.

[0028] Step two includes:

[0029] Step 2.1: Calculate the energy storage capacity at each moment using equation (7) based on the energy storage charging and discharging power:

[0030]

[0031] In equation (7): Et Let t be the amount of energy stored, E0 be the initial amount of energy stored, δ be the time interval for state sampling, and η be the energy storage charging and discharging efficiency.

[0032] Step 2.2: Based on the composition of energy storage in the energy storage power station, use equation (8) to determine the relationship between the capacity of the energy storage power station and the amount of energy stored:

[0033] E rate =n E E unit (8)

[0034] In equation (8): E rate n represents the capacity of the energy storage power station. E E represents the amount of energy stored in an energy storage power station. unit The capacity of a single energy storage unit;

[0035] Step 2.3: Discretize the energy storage capacity using equation (9):

[0036] E rate =(2 0 u 0E +2 1 u 1E +…+2 V u VE E unit (9)

[0037] In equation (9): u 0E ,u 1E ,…,u VE Let n be the amount of energy stored. E The corresponding V binary codes;

[0038] Step 2.4: Calculate the SOC value of the energy storage at each time point using equation (10):

[0039]

[0040] In equation (10): SOC t Let u be the SOC value of the stored energy at time t. vE Let n be the amount of energy stored. E The corresponding v-th binary code;

[0041] Step 2.5: Calculate the depth of charge / discharge in each charge / discharge half-cycle using equation (11):

[0042]

[0043] In equation (11): and These represent the cycle depths of the nth charging half-cycle starting at time t1 and the nth discharging half-cycle starting at time t2, respectively. This indicates that the time interval [t1, j1] from time t1 to time j1 is one charging half-cycle. This indicates that the time interval [t2, j2] from the start of time t2 to the end of time j2 is one discharge half-cycle. Let SOC be the stored energy value at time t1. Let J1 be the SOC value of the stored energy. Let SOC be the stored energy value at time t2. Let j2 be the SOC value of the stored energy. This represents the minimum point state of the energy storage SOC curve at time t1. This indicates that the t1-th point on the energy storage SOC curve is the minimum point. This represents the state at the maximum point of the energy storage SOC curve at time t2. This indicates that the t2th point on the energy storage SOC curve is the maximum point.

[0044] Step four includes:

[0045] Step 4.1: Use equation (12) to obtain the total equivalent number of cycles for energy storage during the scheduling period T.

[0046]

[0047] In equation (12): cyc charge and cyc discharge These represent the number of elements in the charging and discharging half-cycle sets of energy storage, respectively.

[0048] Step 4.2: Calculate the cycle life T of the energy storage using equation (13). cyc :

[0049]

[0050] In equation (13), N 100 This indicates the maximum number of cycles the energy storage can achieve at 100% cycle depth.

[0051] The present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a program that supports the processor in executing any of the energy storage cycle lifetime assessment methods, and the processor is configured to execute the program stored in the memory.

[0052] The present invention provides a computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, performs the steps of any of the energy storage cycle lifetime assessment methods.

[0053] Compared with existing technologies, the beneficial effects of this invention are reflected in:

[0054] 1. This invention overcomes the problem that traditional rainflow counting methods are difficult to apply to the planning and decision-making process of energy storage systems. It proposes an online energy storage semi-cycle identification model that can determine extreme and non-extreme points on the SOC curve based on the energy storage's charge and discharge state. Simultaneously, it generates an energy storage charging and discharging semi-cycle identification matrix based on the distribution characteristics of extreme points on the SOC curve. This model can obtain energy storage semi-cycle identification results simply by simulating energy storage charge and discharge operations during the energy storage planning stage, reducing the difficulty of assessing energy storage lifespan during this phase.

[0055] 2. Based on the cycle depth of different energy storage charging and discharging half-cycles, this invention equates half-cycles at different depths to half-cycles at 100% depth, thereby obtaining the equivalent number of cycles corresponding to different half-cycle depths and quantifying the impact of half-cycle depth on energy storage lifespan loss.

[0056] 3. This invention proposes an energy storage cycle lifetime assessment method based on equivalent half-cycle identification, which solves the problem of the difficulty in transforming energy storage charge-discharge cycle identification models into optimization decision-making processes compared with existing technologies. This method uses the equivalent number of charge-discharge half-cycles corresponding to adjacent extreme points to assess the cycle lifetime of the energy storage system. The energy storage cycle lifetime assessment method proposed in this invention can be embedded in the energy storage system planning and scheduling optimization model, providing corresponding basis and reference for the rational planning and operation of energy storage systems. Attached Figure Description

[0057] Figure 1 This is a flowchart illustrating the energy storage cycle life assessment method based on equivalent semi-cycle identification according to the present invention. Detailed Implementation

[0058] To gain a better understanding of the structural features and effects achieved by the present invention, a detailed description is provided below, accompanied by preferred embodiments and accompanying drawings:

[0059] like Figure 1 As shown, a method for assessing the cycle life of energy storage based on equivalent semi-cycle identification includes the following steps:

[0060] Step 1: Based on the charging and discharging states of energy storage at times t-1 and t within the scheduling period T, determine whether the energy storage SOC curve at time t is an extreme point; simultaneously, combining the distribution characteristics of extreme points of the energy storage SOC curve, generate identification matrices for energy storage charging half-cycles and discharging half-cycles to determine the start and end times of each charging half-cycle and discharging half-cycle within the scheduling period T:

[0061] Step 1.1: To avoid simultaneous charging and discharging of the energy storage system during operation, the energy storage charging and discharging state variable a... t The energy storage charging and discharging power is constrained by a positive number K. Meanwhile, the energy storage in a hold-state where it neither charges nor discharges can be considered as a... t The special cases are equal to 1 or 0, namely, the discharge state where the discharge power is equal to 0 or the charging state where the charging power is equal to 0. Equation (1) is used to characterize the charge / discharge state of energy storage at time t:

[0062]

[0063] In equation (1): P dis,t and P ch,t These represent the discharge and charging power of the energy storage at time t, respectively, a t Let a be the state variable of energy storage at time t during charging and discharging. t =1 indicates that the stored energy is in a discharge state during the time period [t, t+1]. t =0 indicates that the energy storage is in a charging state during the time period [t, t+1], and K is a positive number greater than the rated power of the energy storage;

[0064] Step 1.2: Based on the energy storage state variable a obtained in Step 1.1 t The maximum point of the energy storage SOC curve at time t is determined using equation (2). and minimum point

[0065]

[0066] In equation (2): if This indicates that the t-th point on the energy storage SOC curve is the minimum point. This indicates that the t-th point on the energy storage SOC curve is the maximum point;

[0067] Step 1.3: Use equation (3) to represent the non-extreme point on the energy storage SOC curve at time t.

[0068]

[0069] Step 1.4: Using the T×T 0,1 variable matrix shown in equation (4) To characterize the start and end times of each charging half-cycle within the scheduling period T:

[0070]

[0071] In equation (4): if The time interval [k,t] from time k to time t represents one charging half-cycle. This represents the state at the minimum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the minimum point. This represents the state at the minimum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the minimum point;

[0072] Step 1.5: Using the T×T 0,1 variable matrix shown in equation (5) To characterize the start and end times of each discharge half-cycle within the scheduling period T:

[0073]

[0074] In equation (5): if The time interval [k,t] from time k to time t represents one discharge half-cycle. This represents the state at the maximum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the maximum point. This represents the state at the maximum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the maximum point.

[0075] Further explanation of steps 1.4 and 1.5:

[0076] The approach to forming the energy storage charge / discharge point half-cycle matrix is ​​as follows: First, using the maximum or minimum point of the SOC curve as the starting point, search each point on the SOC curve sequentially, filtering out intermediate non-extreme points. Then, find the extreme point adjacent to the starting point but with opposite properties as the ending point. The range between the starting and ending points constitutes the energy storage charge / discharge half-cycle.

[0077] Step 2: Discretize the energy storage capacity and calculate the SOC value at each time point; based on the start and end times of the energy storage charge / discharge half-cycle and the corresponding SOC value, calculate the half-cycle depth of each charge / discharge half-cycle:

[0078] Step 2.1: Calculate the energy storage capacity at each moment using equation (6) based on the energy storage charging and discharging power.

[0079]

[0080] In equation (6): E t Let t be the amount of energy stored, E0 be the initial amount of energy stored, δ be the time interval for state sampling, and η be the energy storage charging and discharging efficiency.

[0081] Step 2.2: Based on the composition of energy storage in the energy storage power station, use equation (7) to determine the relationship between the capacity of the energy storage power station and the amount of energy stored:

[0082] E rate =n E E unit (7)

[0083] In equation (7): E rate n represents the capacity of the energy storage power station. E E represents the amount of energy stored in an energy storage power station. unit The capacity of a single energy storage unit;

[0084] Step 2.3: Using the binary encoding principle, the energy storage capacity is discretized using equation (8):

[0085] E rate =(2 0 u 0E +2 1 u 1E +…+2 V u VE E unit (8)

[0086] In equation (8): u 0E ,u 1E ,…,u VE Let n be the amount of energy stored. E The corresponding V binary codes;

[0087] Step 2.4: The discrete expression for energy storage SOC contains product terms between continuous variables and 0,1 variables. Linearization using the Big M method can improve the solution speed of the life assessment model. Based on the discrete results of energy storage charge and capacity at each moment obtained in Steps 2.1 and 2.3, the SOC value at each moment is calculated using equation (9):

[0088]

[0089] In equation (9): SOC t Let u be the SOC value of the stored energy at time t. vE Let n be the amount of energy stored. E The corresponding v-th binary code;

[0090] Step 2.5: The expression for the charge / discharge half-cycle depth contains a product term between a continuous variable and a 0,1 variable. Similarly, the Big M method can be used to linearize it. Based on the energy storage charge / discharge half-cycle matrix obtained in Steps 1.4 and 1.5, and the SOC value of the energy storage at each time point calculated in Step 2.4, the charge / discharge depth of the energy storage in each charge / discharge half-cycle is calculated using equation (10):

[0091]

[0092] In formula (10): and These represent the cycle depths of the nth charging half-cycle starting at time t1 and the nth discharging half-cycle starting at time t2, respectively. This indicates that the time interval [t1, j1] from time t1 to time j1 is one charging half-cycle. This indicates that the time interval [t2, j2] from the start of time t2 to the end of time j2 is one discharge half-cycle. Let SOC be the stored energy value at time t1. Let J1 be the SOC value of the stored energy. Let SOC be the stored energy value at time t2. Let j2 be the SOC value of the stored energy. This represents the minimum point state of the energy storage SOC curve at time t1. This indicates that the t1-th point on the energy storage SOC curve is the minimum point. This represents the state at the maximum point of the energy storage SOC curve at time t2. This indicates that the t2th point on the energy storage SOC curve is the maximum point.

[0093] Step 3: Based on the charge / discharge half-cycles and their half-cycle depths determined in Step 2, calculate the equivalent number of half-cycles at 100% charge / discharge depth using Equation (12):

[0094]

[0095] In equation (11): and These represent the equivalent number of cycles at 100% cycle depth for the nth charge half-cycle and the nth discharge half-cycle, respectively. and Let represent the cycle depth of the nth charging half-cycle and the nth discharging half-cycle, respectively, and p be the fitting coefficient of the relationship between the energy storage half-cycle depth and the equivalent number of cycles.

[0096] Step 4: Linearly sum the equivalent cycle counts of each half-cycle obtained in Step 3 to calculate the total equivalent cycle count of energy storage within the scheduling period for evaluating the energy storage cycle lifetime.

[0097] Step 4.1: Use equation (12) to obtain the total equivalent number of cycles for energy storage during the scheduling period T.

[0098]

[0099] In equation (12): cyc charge and cyc discharge These represent the number of elements in the charging and discharging half-cycle sets of energy storage, respectively.

[0100] Step 4.2: Based on the total equivalent number of energy storage cycles calculated in Step 4.1, calculate the cycle life T of the energy storage using Equation (13). cyc :

[0101]

[0102] In equation (13), N 100 This indicates the maximum number of cycles the energy storage can achieve at 100% cycle depth.

[0103] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the above-described method, and the processor is configured to execute the program stored in the memory.

[0104] In this embodiment, a computer-readable storage medium stores a computer program, which is executed by a processor to perform the steps of the above method.

[0105] While the specific implementation methods of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and various changes or modifications can be made to these implementation methods without departing from the principles and implementation of the present invention.

Claims

1. A method for assessing the cycle life of energy storage based on equivalent semi-cycle identification, characterized in that, Includes the following steps: Step 1: Based on the charging and discharging states of energy storage at time t-1 and time t within the scheduling cycle T, determine whether the energy storage SOC curve at time t is an extreme point; at the same time, combined with the distribution characteristics of the extreme points of the energy storage SOC curve, generate the identification matrix of the energy storage charging half-cycle and discharging half-cycle to determine the start and end times of each charging half-cycle and discharging half-cycle within the scheduling cycle T. Step 2: Discretize the energy storage capacity and calculate the SOC value of the energy storage at each time point; The half-cycle depth of each charge-discharge half-cycle is calculated based on the start and end times of the energy storage charge-discharge half-cycle and the corresponding SOC value. Step 3: Based on the charge-discharge half-cycle and its half-cycle depth determined in Step 2, use Equation (1) to calculate the equivalent number of half-cycles corresponding to each half-cycle at 100% charge-discharge depth. In formula (1): and These represent the equivalent number of cycles at 100% cycle depth for the nth charge half-cycle and the nth discharge half-cycle, respectively. and denoted as the cycle depth of the nth charging half-cycle and the nth discharging half-cycle, respectively, and p is the fitting coefficient of the relationship between the energy storage half-cycle depth and the equivalent number of cycles; Step 4: Linearly sum the equivalent cycle counts of each half-cycle obtained in Step 3 to calculate the total equivalent cycle count of energy storage within the scheduling period for evaluating the energy storage cycle life.

2. The energy storage cycle life assessment method based on equivalent semi-cycle identification according to claim 1, characterized in that, Step one includes: Step 1.1: Use equation (2) to characterize the charge / discharge state of the stored energy at time t: In equation (2): P dis,t and P ch,t These represent the discharge and charging power of the energy storage at time t, respectively, a t Let a be the state variable of energy storage at time t during charging and discharging. t =1 indicates that the stored energy is in a discharge state during the time period [t, t+1]. t =0 indicates that the energy storage is in a charging state during the time period [t, t+1], and K is a positive number greater than the rated power of the energy storage; Step 1.2: Use equation (3) to determine the maximum point of the energy storage SOC curve at time t. and minimum point In equation (3): if This indicates that the t-th point on the energy storage SOC curve is the minimum point. This indicates that the t-th point on the energy storage SOC curve is the maximum point; Step 1.3: Use equation (4) to represent the non-extreme point on the energy storage SOC curve at time t. Step 1.4: Using the T×T 0,1 variable matrix shown in equation (5) To characterize the start and end times of each charging half-cycle within the scheduling period T: In equation (5): if The time interval [k,t] from time k to time t represents one charging half-cycle; K k min This represents the state at the minimum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the minimum point. This represents the state at the minimum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the minimum point; Step 1.5: Using the T×T 0,1 variable matrix shown in equation (6) To characterize the start and end times of each discharge half-cycle within the scheduling period T: In equation (6): if The time interval [k,t] from time k to time t represents one discharge half-cycle; This represents the state at the maximum point of the energy storage SOC curve at time k. This indicates that the k-th point on the energy storage SOC curve is the maximum point. This represents the state at the maximum point of the energy storage SOC curve at time i. This indicates that the i-th point on the energy storage SOC curve is the maximum point.

3. The energy storage cycle life assessment method based on equivalent semi-cycle identification according to claim 2, characterized in that, Step two includes: Step 2.1: Calculate the energy storage capacity at each moment using equation (7) based on the energy storage charging and discharging power: In equation (7): E t Let t be the amount of energy stored, E0 be the initial amount of energy stored, δ be the time interval for state sampling, and η be the energy storage charging and discharging efficiency. Step 2.2: Based on the composition of energy storage in the energy storage power station, use equation (8) to determine the relationship between the capacity of the energy storage power station and the amount of energy stored: AND rate =n E AND unit (8) In equation (8): E rate n represents the capacity of the energy storage power station. E E represents the amount of energy stored in an energy storage power station. unit The capacity of a single energy storage unit; Step 2.3: Discretize the energy storage capacity using equation (9): E rate =(2 0 in 0E +2 1 in 1E +…+2 V in VE )E unit (9) In equation (9): u 0E ,u 1E ,…,u VE Let n be the energy storage quantity. E The corresponding V binary codes; Step 2.4: Calculate the SOC value of the energy storage at each time point using equation (10): In equation (10): SOC t Let u be the SOC value of the stored energy at time t. vE Let n be the energy storage quantity. E The corresponding v-th binary code; Step 2.5: Calculate the depth of charge / discharge in each charge / discharge half-cycle using equation (11): In equation (11): and These represent the cycle depths of the nth charging half-cycle starting at time t1 and the nth discharging half-cycle starting at time t2, respectively. This indicates that the time interval [t1, j1] from time t1 to time j1 is one charging half-cycle. This indicates that the time interval [t2, j2] from the start of time t2 to the end of time j2 is one discharge half-cycle. Let SOC be the SOC value of the stored energy at time t1. j1 Let J1 be the SOC value of the stored energy. Let SOC be the stored energy value at time t2. Let j2 be the SOC value of the stored energy. This represents the minimum point state of the energy storage SOC curve at time t1. This indicates that the t1-th point on the energy storage SOC curve is the minimum point. This represents the state at the maximum point of the energy storage SOC curve at time t2. This indicates that the t2th point on the energy storage SOC curve is the maximum point.

4. The energy storage cycle life assessment method based on equivalent semi-cycle identification according to claim 3, characterized in that, Step four includes: Step 4.1: Use equation (12) to obtain the total equivalent number of cycles for energy storage during the scheduling period T. In equation (12): cyc charge and cyc discharge These represent the number of elements in the charging and discharging half-cycle sets of energy storage, respectively. Step 4.2: Calculate the cycle life T of the energy storage using equation (13). cyc : In equation (13), N 100 This indicates the maximum number of cycles the energy storage can achieve at 100% cycle depth.

5. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor in executing any of the energy storage cycle life assessment methods of claims 1-4, and the processor is configured to execute the program stored in the memory.

6. A computer-readable storage medium storing a computer program thereon, characterized in that, The computer program, when run by the processor, performs the steps of the energy storage cycle life assessment method according to any one of claims 1-4.

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