Condition detection method and system for battery energy storage system

Abstract

The present invention provides a method and system for detecting the condition of a battery energy storage system, belonging to the field of battery energy storage. The method includes: obtaining operating data of multiple battery energy storage systems; determining a static state index value and a comprehensive state index value for any battery energy storage system based on the operating data; determining a dynamic change index value based on the operating data and the static state index value; the static state index value is used to determine the performance level of the battery energy storage system under various states; the dynamic change index value is used to determine the reliability changes of the battery energy storage system and the impact of the performance changes of battery cells on the battery energy storage system; the comprehensive state index value is used to determine the transition between different states of the battery energy storage system, the failure rate, and the repair rate; and determining the current operating condition value of each battery energy storage system based on the various index values ​​of each battery energy storage system. The present invention improves the comprehensiveness of battery energy storage system condition detection and can accurately assess the reliability of the battery energy storage system.

Description

Technical Field

[0001] The present invention relates to the field of battery energy storage, and in particular to a state detection method and system based on a multi-state battery energy storage system. Background Art

[0002] With the large-scale grid integration of renewable energy sources such as wind and solar, the wind, solar, and energy storage industries have gained a historic opportunity and are experiencing rapid growth. Larger-scale wind power is also increasing the demand for energy storage capacity. Battery energy storage, due to its flexibility and modularity, is currently widely used in large-scale energy storage. Therefore, conducting reliability assessments for battery energy storage systems and establishing a comprehensive evaluation index system are crucial. Current reliability assessments for modular battery energy storage mostly rely on multi-state models of the storage battery to reflect the gradual capacity decay of the battery. However, reliability analysis is limited, and a comprehensive and comprehensive index system is lacking. Developing a reliability assessment system suitable for multi-state battery energy storage that can comprehensively and systematically analyze and present the reliability of battery energy storage systems is crucial. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for detecting the condition of a battery energy storage system, which can improve the comprehensiveness of the condition detection of the battery energy storage system and accurately evaluate the reliability of the battery energy storage system.

[0004] To achieve the above object, the present invention provides the following solutions:

[0005] A method for detecting a condition of a battery energy storage system, comprising:

[0006] Obtaining operating data of multiple battery energy storage systems; the operating data includes real-time SoH values, initial capacities, fault parameters, and state parameters; the fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transitioning to a faulty state, and the repair rate of the battery energy storage system transitioning to a faulty state; the state parameters include the state transition relationship, the state transition rate, and the duration of each state; the life cycle of the battery energy storage system is divided into multiple states, and each state corresponds to a SoH value and SoH probability value within a set range;

[0007] For any battery energy storage system, determine a static state index value of the battery energy storage system based on the operating data of the battery energy storage system; the static state index value is used to determine the performance level of the battery energy storage system in a normal state or a fault state;

[0008] Determining a dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system; the dynamic change index value is used to determine the reliability change of the battery energy storage system and the impact of the performance change of the battery cell on the battery energy storage system;

[0009] Determine a comprehensive status index value of the battery energy storage system based on the operating data of the battery energy storage system; the comprehensive status index value is used to determine the transition between different states of the battery energy storage system, the failure rate and the repair rate;

[0010] Based on the static state index value, dynamic change index value and comprehensive state index value of each battery energy storage system, the current operating status value of each battery energy storage system is determined.

[0011] To achieve the above object, the present invention also provides the following solution:

[0012] A condition detection system for a battery energy storage system, comprising:

[0013] A data acquisition unit is configured to acquire operating data of multiple battery energy storage systems; the operating data includes real-time SoH values, initial capacities, fault parameters, and state parameters; the fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transitioning to a faulty state, and the repair rate of the battery energy storage system transitioning to a faulty state; the state parameters include the state transition relationship, the state transition rate, and the duration of each state; the life cycle of the battery energy storage system is divided into multiple states, each state corresponding to a SoH value and SoH probability value within a set range;

[0014] a static index determination unit connected to the data acquisition unit, and configured to determine, for any battery energy storage system, a static state index value of the battery energy storage system based on the operating data of the battery energy storage system; the static state index value is used to determine the performance level of the battery energy storage system in a normal state or a fault state;

[0015] a dynamic index determination unit, connected to the data acquisition unit and the static index determination unit, respectively, for determining a dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system; the dynamic change index value is used to determine the reliability change of the battery energy storage system and the impact of the performance change of the battery cell on the battery energy storage system;

[0016] a comprehensive index determination unit, connected to the data acquisition unit, for determining a comprehensive state index value of the battery energy storage system based on the operating data of the battery energy storage system; the comprehensive state index value is used to determine the transition between different states of the battery energy storage system, the failure rate, and the repair rate;

[0017] A status determination unit is connected to the static index determination unit, the dynamic index determination unit and the comprehensive index determination unit respectively, and is used to determine the current operating status value of each battery energy storage system based on the static status index value, dynamic change index value and comprehensive status index value of each battery energy storage system.

[0018] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0019] The present invention evaluates the reliability of a multi-state battery energy storage system from three dimensions: static state indicators, dynamic change indicators, and comprehensive state indicators. Each indicator covers the status of battery cells and the battery energy storage system, as well as the connection between battery cells and the battery energy storage system, which can obtain more comprehensive and systematic reliability assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a flow chart of a method for detecting a condition of a battery energy storage system according to the present invention;

[0022] Figure 2 A schematic diagram of the indicator system;

[0023] Figure 3 Schematic diagram of the modules of the condition detection system of the battery energy storage system of the present invention.

[0024] Explanation of symbols:

[0025] Data acquisition unit-1, static indicator determination unit-2, dynamic indicator determination unit-3, comprehensive indicator determination unit-4, status determination unit-5. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] The purpose of the present invention is to provide a condition detection method and system for a battery energy storage system. The present invention is aimed at a modular battery energy storage system, takes into account the fault and normal conditions of the battery energy storage system, and establishes a reliability evaluation index system for the battery energy storage system from three dimensions: indicators describing the static state of the battery, indicators describing the dynamic changes of the battery, and comprehensive indicators of the multi-state of the battery energy storage system. Under each first-level indicator, corresponding second-level indicators are included. Based on the constructed indicators, a comprehensive reliability evaluation method for the battery energy storage system is proposed. On the basis of applying each indicator for specific analysis, the various indicators can be comprehensively utilized to conduct a comprehensive evaluation of the battery energy storage system, thereby improving the comprehensiveness of the condition detection of the battery energy storage system.

[0028] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] The instantaneous states of battery energy storage, such as reliability, performance level, and capacity, can intuitively describe the current performance level and reliability status of the energy storage system and can be used to reflect the static indicators of the battery energy storage system. However, using only the current battery status for weak link analysis cannot effectively consider the changes in reliability after short-term operation. In addition, large changes in the performance level of a single battery will have a significant impact on the overall reliability. Therefore, corresponding dynamic indicators that reflect the changes in reliability, performance level, and the impact of single changes are also required. Finally, combined with the comprehensive evaluation indicators of the overall state of the energy storage system, a two-level reliability evaluation indicator framework is proposed, which includes three first-level indicators: static state indicators, dynamic change indicators, and comprehensive state indicators, as well as multiple second-level indicators.

[0030] Example 1

[0031] like Figure 1 As shown, this embodiment provides a method for detecting the condition of a battery energy storage system, including:

[0032] S1: Obtaining operating data of multiple battery energy storage systems. The life cycle of a battery energy storage system is divided into multiple states, each of which corresponds to a set range of SoH (state of charge, the percentage of remaining battery power) values ​​and SoH probability values.

[0033] Operational data includes real-time SoH value, initial capacity, fault parameters, and status parameters.

[0034] Fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transferring to the fault state, and the repair rate of the battery energy storage system transferring to the fault state.

[0035] State parameters include state transition relationship, state transition rate, and duration of each state.

[0036] In this embodiment, relevant data information of the battery energy storage system is collected and classified from the BMS (Battery Management System) of the energy storage battery, and relevant index values ​​are calculated. Specific operating data include: (1) Real-time changes in the SoH level of the battery, which is used to determine the current state of the battery. (2) The initial capacity of the energy storage, which is used to calculate the expected energy storage capacity. (3) The time when the fault occurred and the number of faulty batteries, which are used to calculate the point fault propagation time index. (4) The real-time SoH level of the battery and the corresponding time value are used to calculate the probability index of insufficient power time and the reliability degradation rate, SoH attenuation rate, capacity attenuation rate, and average SoH attenuation rate index. The failure rate and repair rate data of each part of the energy storage system (such as transformers and converters) can be obtained by referring to the relevant manual data, which is used to calculate the equivalent failure rate and equivalent repair rate index.

[0037] S2: For any battery energy storage system, determine a static state index value of the battery energy storage system based on the operating data of the battery energy storage system. The static state index value is used to determine the performance level of the battery energy storage system in a normal state or a fault state.

[0038] In this embodiment, the static state indicator values ​​include: energy storage reliability, energy storage health status expectation, energy storage capacity expectation, energy storage capacity shortage expectation, unit fault propagation time, energy storage performance degradation equivalent failure rate, power shortage time probability and energy storage capacity margin.

[0039] S3: Determine a dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system. The dynamic change index value is used to determine the reliability change of the battery energy storage system and the impact of the performance change of the battery cell on the battery energy storage system.

[0040] In this embodiment, the dynamic change index values ​​include: reliability degradation rate, SoH attenuation rate, capacity attenuation rate, average SoH attenuation rate, reliability change contribution of each battery cell, and SoH change contribution of each battery cell.

[0041] S4: Determine a comprehensive state index value of the battery energy storage system based on the operating data of the battery energy storage system. The comprehensive state index value is used to determine the transition between different states of the battery energy storage system, the failure rate, and the repair rate.

[0042] In this embodiment, the comprehensive status index value includes: the frequency of each state of the battery energy storage system, the average duration of each state of the battery energy storage system, the equivalent failure rate, the equivalent repair rate and the probability of normal working state.

[0043] S5: Determine the current operating status value of each battery energy storage system based on the static state index value, dynamic change index value and comprehensive state index value of each battery energy storage system.

[0044] Furthermore, the process of determining the static state indicator value includes:

[0045] (11) Determining a SoH level set and a SoH level probability set based on the real-time SoH value of the battery energy storage system; the SoH level set includes the SoH levels of the battery energy storage system in various states, and the SoH level probability set includes the SoH probability values ​​of the battery energy storage system in various states. Determining energy storage reliability based on the SoH level set, the SoH level probability set, and the minimum performance requirement level of the battery energy storage system.

[0046] The reliability of the battery can be defined using the definition of reliability in a multi-state system, i.e., the probability that the performance level of the battery energy storage system (SoH level in the battery energy storage system) is higher than the required level. Therefore, assuming that the minimum performance requirement level of the energy storage battery system is γ, the reliability of the energy storage battery is:

[0047]

[0048] Among them, R BAT is the energy storage reliability, g b is the performance level (SoH level) of the battery energy storage system in each state, g b ≥γ represents the state of the battery energy storage system where the performance level (SoH level) is greater than the minimum performance requirement level γ, p b is the state probability corresponding to each state where the performance level of the battery energy storage system is greater than the minimum performance requirement level γ.

[0049] (12) Determine the expected energy storage health state based on the SoH level set, the SoH level probability set, and the SoH level threshold.

[0050] The state where the performance level (SoH level) of the battery energy storage is greater than the minimum performance requirement is defined as the healthy state of the battery energy storage. The expected healthy state of the energy storage is the expected value of the energy storage state where the performance level (SoH level) is greater than the SoH level threshold α:

[0051]

[0052] Among them, E BAT is the expected state of health of the energy storage system, Ψ{SoH} is the SoH level set of each battery cell in the battery energy storage system, α represents the threshold value of the energy storage performance level (i.e., SoH level) that can meet the minimum performance requirement, and SoH b≥α represents the state of all battery energy storage systems with performance levels (SoH levels) greater than or equal to the SoH level threshold α, P b The SoH probability value corresponding to each battery energy storage state that represents the performance level (SoH level) is greater than or equal to the SoH level threshold α.

[0053] (13) Determine the expected energy storage capacity based on the initial capacity of the battery energy storage system and the expected energy storage health status.

[0054] The expected energy storage capacity is the expected value of the energy storage capacity when the energy storage performance level (SoH level) is greater than the SoH level threshold α:

[0055] E BAT {Ψ(Q)}=Q ini ×E BAT {Ψ(SoH)};

[0056] Among them, E BAT {Ψ(Q)} is the expected energy storage capacity, Q ini is the initial capacity, and Ψ(Q) is the capacity of each battery cell in the battery energy storage system.

[0057] (14) Determine the expected energy storage capacity shortage based on the initial capacity of the battery energy storage system, the SoH level set, the SoH level threshold and the SoH level probability set.

[0058] The expected insufficient energy storage capacity is the expected value of the energy storage battery being unable to reliably supply power when serving as the power supply side (i.e., the expected value of the battery capacity when the SoH level of the battery is less than the minimum performance requirement threshold α):

[0059]

[0060] in, As the energy storage capacity is insufficient, SoH c ≤α represents the state of the battery energy storage system with all performance levels (SoH levels) less than or equal to the SoH level threshold α, p c The SoH probability value corresponding to the energy storage battery state whose performance level (SoH level) is less than or equal to the SoH level threshold α.

[0061] (15) Determine the unit fault propagation time based on the time when the fault occurs, the time when the energy storage reliability drops to 0, and the number of faulty batteries.

[0062] The unit fault propagation time is the average time required for the fault to propagate to one more battery after a fault occurs in a modular energy storage battery cell:

[0063]

[0064] in, is the unit fault propagation time, t F is the time when the fault occurs, t(R BAT =0) is the moment when the energy storage reliability drops to 0, N F The number of faulty batteries.

[0065] The indicators constructed in this paper are based on a multi-state battery model. The reliability calculation based on this model includes simulation of the battery's operating process. Therefore, during the theoretical derivation, the unit fault propagation time can be calculated by setting the time of fault occurrence during the simulation, recording the moment when the energy storage reliability drops to zero under the fault, and the number of batteries affected by the fault propagation.

[0066] In practical applications, the above-mentioned relevant data can be obtained from the battery's BMS or energy storage EMS (Energy Management System) and related battery energy storage recording systems.

[0067] (16) Determine the equivalent failure rate of energy storage performance degradation based on the energy storage reliability.

[0068] When the performance level of energy storage is less than the minimum performance requirement, it can be considered to be in a faulty state. When the failure of battery energy storage adopts an exponential distribution, the failure rate of energy storage can be calculated based on the energy storage reliability:

[0069]

[0070] Where λ(t) is the equivalent failure rate of energy storage performance degradation, R BAT (t) is the energy storage reliability at time t, R BAT '(t) is the derivative of energy storage reliability at time t.

[0071] (17) Determine the probability of insufficient battery time based on the SoH level set, the SoH level threshold, the SoH level probability set, and the duration of each state:

[0072]

[0073] in, is the probability of insufficient battery time, P c The SoH state SoH is where the performance level (SoH level) is less than or equal to the SoH level threshold α. c The SoH probability value of the corresponding state c, t c is the duration of state c.

[0074] Different SoH levels of the battery correspond to different battery states (for example, a SoH level of 100%-80% corresponds to one state, 80%-60% corresponds to another state, etc.). Therefore, the duration of the state is the duration of the battery's SoH level. c The duration of the state where the threshold is less than α, that is, the time from when the battery's SoH is less than α to when the battery is completely decayed (SoH is 0). In theoretical practice, this can be obtained from the battery's life decay curve. In practical applications, it can also be obtained from relevant historical data in the battery's BMS system.

[0075] (18) Determine the energy storage capacity margin based on the initial capacity of the battery energy storage system, the expected state of health of the energy storage system, the SoH level probability set, and the SoH level threshold.

[0076] The energy storage capacity margin is the difference between the current expected energy storage capacity and the capacity value corresponding to the SoH level threshold:

[0077] ΔQ BAT =Q ini ×(E BAT -SoH α );

[0078] Among them, Q ini is the initial capacity, SoH α represents the state closest to the SoH level threshold α, E BAT It represents the expected health status of energy storage, and is calculated using the following formula:

[0079]

[0080] Among them, l represents each state of the battery energy storage system, L represents the total number of energy storage states, P l Indicates the SoH probability value in the lth state, SoH l Represents the performance level value at the lth state.

[0081] For the calculation of the first-level static state indicators, the indicator results can be used to analyze the performance level of the battery energy storage system under normal or fault conditions and understand the current status of the battery energy storage system. Among them, the battery energy storage system reliability index can be used to reflect the overall availability of the battery energy storage system caused by the battery performance degradation level under normal or fault conditions; the energy storage health state expectation index is used to represent the average performance level of the battery energy storage system when it maintains a healthy state; the energy storage capacity expectation and energy storage capacity margin indicators reflect the available capacity of the battery energy storage system and can be used to analyze the current available output of the battery energy storage system and guide the scheduling and operation of energy storage; the energy storage capacity deficiency expectation and the probability of insufficient power time reflect the capacity loss degree and capacity shortage time of the battery energy storage system and can be used to analyze the losses caused by insufficient supply capacity when the battery energy storage system plays the role of the power supply side; the energy storage system performance degradation equivalent failure rate index can provide a numerical reference for the failure rate of battery energy storage obtained by the multi-state modeling method for related research; the unit fault propagation time index can represent the fault propagation speed in the case of energy storage failure and can be used to analyze the severity and development stage of the fault.

[0082] Furthermore, the process of determining the dynamic change index value includes:

[0083] (21) Determine the total decrease in energy storage reliability based on the energy storage reliability of the battery energy storage system at each moment in the detection period. Determine the reliability decrease rate based on the total decrease in energy storage reliability and the detection duration. In this embodiment, the reliability decrease rate is the reliability decrease value per unit time:

[0084]

[0085] Among them, I dR is the reliability degradation rate, ΔR BAT is the total decrease in energy storage reliability, and Δt is the detection time.

[0086] (22) Determine the total SoH drop value based on the SoH value of the battery energy storage system at each moment during the detection period. Determine the SoH decay rate based on the total SoH drop value and the detection duration. In this embodiment, the SoH decay rate is the SoH change value per unit time:

[0087]

[0088] Among them, I dSoH is the SoH attenuation rate of the battery energy storage system, and ΔSoH is the total SoH decrease value.

[0089] For any battery cell k, its SoH decay rate is:

[0090]

[0091] Among them, I dSoH,k is the SoH decay rate of battery cell k, ΔSoH k is the total SoH drop of battery cell k during the detection period.

[0092] (23) Determine the capacity decay rate I according to the SoH decay rate and the initial capacity of the battery energy storage system. dQ :

[0093] I dQ =I dSoH Q ini .

[0094] (24) Determine the average SoH decay rate based on the total number of states, the duration of each state during the detection period, and the SoH drop value of each state. The average SoH decay rate is the average of the SoH decay rates of each state:

[0095]

[0096] Among them, I dSoH,d is the average SoH decay rate, L is the total number of states, ΔSoH d is the SoH drop value of the battery energy storage system under state d during the detection period, Δt d is the duration of state d within the detection period.

[0097] (25) For any battery cell of the battery energy storage system, the reliability change contribution of the battery cell is determined based on the total decrease in energy storage reliability and the reliability decrease value of the battery energy storage system when the SoH value of the battery cell changes (decreases or increases) by the target SoH value.

[0098] The reliability change contribution of a battery cell indicates the contribution of the SoH change of a battery cell to the reliability of the battery energy storage system, which represents the change ΔSoH of the battery cell. k After that, how much did it contribute to the reduction in reliability of the battery energy storage system?

[0099]

[0100] Among them, I Rcon,k is the contribution of battery cell k to reliability variation, Γ(ΔSoH k |Ψ(SoH)) represents the SoH value of battery cell k when it decreases or increases by ΔSoH k Finally, the set of SoH values ​​of each battery cell in the battery energy storage system, ΔR BAT {Γ(ΔSoH k |Ψ(SoH))} represents the decrease or increase of the SoH value of battery cell k by ΔSoHk The reliability degradation value of the battery energy storage system under these circumstances.

[0101] (26) For any battery cell of the battery energy storage system, the SoH change contribution of the battery cell is determined based on the expected decrease in the energy storage health state of the battery energy storage system during the detection period and the expected decrease in the energy storage health state of the battery energy storage system when the SoH value of the battery cell changes (decreases or increases) by the target SoH value. The SoH change contribution of the battery cell indicates the contribution of the SoH change of the battery cell to the expected health state of the battery energy storage system:

[0102]

[0103] Among them, I Econ,k is the contribution of SoH change of battery cell k, ΔE BAT The expected decrease in the battery energy storage system's energy storage health status during the detection period, ΔE BAT {Γ(ΔSOH k |Ψ(SOH))} represents the decrease / increase of the SoH value of battery cell k by ΔSoH k The expected decrease in the energy storage health status of the battery energy storage system under these circumstances.

[0104] Based on the calculation of static state indicators, the calculated dynamic change indicators can be used to infer changes in the reliability of the battery energy storage system and reflect the impact of significant changes in the performance of a single battery on the overall system. Among them, the reliability degradation rate, SoH decay rate, and capacity decay rate can respectively characterize the speed of reliability, performance degradation, and capacity decay of the battery energy storage system, and can be used to analyze the changes in the availability, performance level, and available capacity of the battery energy storage system in the future; the SoH average decay rate indicator can characterize the speed of change of the performance level in each state stage, and can be used to analyze and compare the performance changes of the battery energy storage system in different state stages, and explore the weak state stage of the battery energy storage system; the reliability change contribution index and the SoH change contribution index can be used to reflect the impact of changes in battery cells on the overall system, and can be used to discover abnormal cells in the battery energy storage system.

[0105] Furthermore, the comprehensive status index value mainly includes the overall status frequency of the battery energy storage system, including other PCS (Power Conversion System, energy storage converter) and transformer components, the average duration of the status, and the overall equivalent failure rate and overall equivalent repair rate of the battery energy storage system. The process of determining the comprehensive status index value includes:

[0106] (31) For any state in the life cycle of the battery energy storage system, the frequency of the state is determined based on the SoH probability value of the state in the battery energy storage system that has a transition relationship with the state, the state transition rate of other states to the state, and the number of states that transition to the state. Specifically, the frequency of state f is determined using the following formula:

[0107]

[0108] Among them, F Sf is the frequency of state f, P Sf is the SoH probability value of state f, M d is the number of states leaving state f (the number of states from state f to other states), λ Ω is the state transition rate from state f to other states, M e is the number of states entering state f (the number of states transferred to state f), P Sl is the probability of the state directly connected to state f (the SoH probability value of the state in the battery energy storage system that has a transition relationship with state f), λ l is the state transition rate from other states to state f).

[0109] In this embodiment, the transition probability between states is based on the energy storage multi-state model. Based on the SoH probability values ​​for each state in the multi-state model, the conditional probability formula can be used to calculate the transition probability. For example, the state transition rate between states A and B is the conditional probability of state A under state B, P(A|B) = P(AB) / P(B).

[0110] (32) Determine the average duration of the state based on the number of states from which the state transitions to other states and the state transition rate from the state to other states. Specifically, the average duration of state f is calculated using the following formula:

[0111]

[0112] Among them, d Sf is the average duration of state f.

[0113] (33) Determine the equivalent failure rate based on the failure rate of the battery energy storage system transferring to the fault state. Considering the connection structure of the battery energy storage system, the states of the battery energy storage system are merged, and the equivalent failure rate after the merger is:

[0114]

[0115] Among them, λ eq is the equivalent failure rate, λ gThe failure rate of the battery energy storage system when it is transferred to state g. The battery energy storage system consists of multiple parts (such as battery box, transformer, converter). The failure rate of the battery energy storage system is obtained by adding the failure rates of each part. eq This refers to the failure rate of the entire battery energy storage system. The overall failure rate is the sum of the failure rates of each component. The failure rate of each component (converter, transformer) is directly obtained from historical data or relevant experimental data (can be queried from relevant manuals or databases), and the failure rate of the battery box can be calculated using the formula above. Get; L F This is a state that can be combined into a fault state, determined based on the series and parallel connection relationships of the battery energy storage system components. For series components, a failure in any one component will cause a failure of the entire system. Therefore, the failure states of each component can be combined into a single fault state.

[0116] (34) Determine an equivalent repair rate based on the failure rate of the battery energy storage system when it is transferred to a fault state and the repair rate of the battery energy storage system when it is transferred to a fault state:

[0117]

[0118] Among them, μ eq is the equivalent repair rate, μ h is the repair rate of the battery energy storage system when it transfers to state h. The repair rate of the battery energy storage system is obtained by the repair rate of each part, and the repair rate of each part is directly obtained by querying relevant historical data or experimental data.

[0119] (35) According to the equivalent repair rate and the equivalent failure rate, the normal working state probability is determined. The normal working state probability is the probability of the battery energy storage system being in a normal state after the various states of the battery energy storage system are combined:

[0120]

[0121] Among them, P0 is the probability of normal working state.

[0122] The comprehensive status index considers the transition and persistence between different states of the battery energy storage system, as well as the failure and repair rates from an overall perspective. State frequency and average state duration can be used to analyze the relationships and differences between different states of the battery energy storage system, discovering the state patterns of the battery energy storage system, and providing guidance for the regulation and operation of the battery energy storage system and the analysis of weak links. The normal operating state probability represents the reliability of the battery energy storage system in normal operation after the merging of multiple states. The equivalent failure rate and equivalent repair rate provide basic system reliability values ​​from the perspective of the battery energy storage system as a whole.

[0123] Based on the relevant indicators calculated in S2~S4, a complete reliability indicator system of the battery energy storage system is constructed, such as Figure 2 As shown. Specifically, it includes three first-level indicators and 19 second-level indicators: (1) Static state indicators, including 8 second-level indicators: energy storage reliability, energy storage health state expectation, energy storage capacity expectation, energy storage capacity shortage expectation, unit fault propagation time, energy storage performance degradation equivalent failure rate, power shortage time probability and energy storage capacity margin. (2) Dynamic change indicators, including 6 second-level indicators: reliability degradation rate, SoH degradation rate, capacity degradation rate, average SoH degradation rate, reliability change contribution of each battery cell and SoH change contribution of each battery cell. (3) System comprehensive state indicators, including 5 second-level indicators: frequency of each state of battery energy storage system, average duration of each state of battery energy storage system, equivalent failure rate, equivalent repair rate and normal working state probability. Then, based on the complete indicator system constructed, the reliability of the battery energy storage system modeled by the multi-state model is analyzed and comprehensively evaluated.

[0124] When evaluating the reliability of battery energy storage systems, the calculated indicators serve as the basis for the reliability assessment. Based on these indicators, quantitative data on the battery energy storage system can be obtained for its static state, dynamic state changes, and overall capabilities. This allows for analysis of the system's capabilities and provides data support for further guidance on scheduling, configuration, and maintenance of the battery energy storage system.

[0125] Furthermore, S5 specifically includes:

[0126] S51: Normalizing the static state index value, dynamic change index value, and comprehensive state index value of each battery energy storage system to obtain a normalized static index value, a normalized dynamic index value, and a normalized comprehensive index value corresponding to each battery energy storage system. It should be noted that the normalized static index value, the normalized dynamic index value, and the normalized comprehensive index value of the present invention all include multiple normalized secondary indicators.

[0127] In this embodiment, a deviation normalization method is used to normalize the static state index value, dynamic change index value, and comprehensive state index value of each battery energy storage system, so that each index value is converted into dimensionless and extremely large normalized index data.

[0128] Assume that m battery energy storage systems are evaluated S = {S1, S2, S3, ..., S m}, then the indicator set of each battery energy storage system can be expressed as X={X1,X2,X3,...,X 19}, then the i-th battery energy storage system S i The j-th index X jThe index value is recorded as x ij , the dimensionless index value obtained after normalization is recorded as c ij The specific normalization method is as follows:

[0129] For extremely large indicators where the larger the value, the better, we have:

[0130]

[0131] Among them, min{x ij |i=1,2,3,...,m} represents the minimum value of the jth index, max{x ij |i=1,2,3,...,m} represents the maximum value among the j-th index.

[0132] For extremely large indicators where smaller values ​​are better, we have:

[0133]

[0134] S52: Determine the normalized static index entropy value, the normalized dynamic index entropy value, and the normalized comprehensive index entropy value of each battery energy storage system respectively.

[0135] S53: Determine a weight of each indicator value of each battery energy storage system based on the normalized static indicator entropy value, the normalized dynamic indicator entropy value, the normalized comprehensive indicator entropy value, the normalized static indicator value, the normalized dynamic indicator value, the normalized comprehensive indicator value, and the entropy value parameter of each battery energy storage system. The indicator value is a normalized static indicator value, a normalized dynamic indicator value, or a normalized comprehensive indicator value.

[0136] In this embodiment, an improved entropy weight method is used to calculate the weight of each indicator value. Since there are obvious differences in the distribution and discreteness of the various indicator values, it is necessary to assign different weights to each indicator to balance its impact on the comprehensive evaluation value. However, when all entropy values ​​are close to 1, the traditional entropy weight method will over-amplify the gap and lead to unreasonable weighting. In the present invention, the differences between some indicator values ​​are very small. In a battery energy storage system with higher reliability, there may be a situation where all indicator values ​​are close to 1. Therefore, the present invention adopts an improved entropy weight method, which can overcome the shortcomings of the traditional entropy weight method and maintain the ability to widen the gap.

[0137] First, the initial weight of the j-th indicator value is calculated using the following formula:

[0138]

[0139] Among them, W j is the initial weight of the j-th index value, H j is the entropy value of the j-th index value, f ijis the characteristic weight of the jth index value in the battery energy storage system i, if f ij =0, then let lnf ij =0, if H j =1, it means the normalized value c of the jth index value ij All are equal, W 0j is the first entropy parameter, n is the total number of indicator values, W 3j is the second entropy parameter, is the average value of entropy values ​​that are not 1.

[0140] Reliability assessment is relatively demanding; failure of any indicator can reflect a low reliability level for the battery energy storage system. Therefore, this paper employs a weighting method with an "over-value penalty" feature to obtain a comprehensive reliability assessment. To differentiate and highlight the impact of unqualified indicators, an improved entropy weighting method is used for indicator values ​​below or equal to the average, while indicator values ​​above the average are weighted to 0. The final weight of the jth indicator value for the i-th battery energy storage system is:

[0141]

[0142] Among them, a ij is the weight of the jth index value of the i-th battery energy storage system, c ij is the jth index value of the i-th battery energy storage system, is the average value of the jth index value of multiple energy storage battery systems.

[0143] S54: For any battery energy storage system, determine the current operating status value of the battery energy storage system according to the weights of the indicator values ​​of the battery energy storage system, the normalized static indicator value, the normalized dynamic indicator value and the normalized comprehensive indicator value of each battery energy storage system.

[0144] Specifically, the following formula is used to determine the current operating status value of the battery energy storage system i:

[0145]

[0146] Among them, V i is the current operating status value of battery energy storage system i (i.e., the comprehensive evaluation value of battery energy storage system i), a ij is the weight of the jth indicator value of battery energy storage system i, c ij is the j-th index value of battery energy storage system i, is the average value of the jth index value of multiple energy storage battery systems, n is the total number of index values, and in this embodiment, n=19, that is, the number of all secondary indexes, and || represents the absolute value.

[0147] According to the calculation method of the comprehensive evaluation value, the fewer indicators that are below the average level, the smaller the gap with the average level, and the smaller the comprehensive evaluation value, the higher the reliability level of the battery energy storage system.

[0148] The "jth indicator" described in this embodiment is any one of the aforementioned 19 normalized indicators (energy storage reliability, expected energy storage health status, expected energy storage capacity, expected energy storage capacity shortage, unit fault propagation time, energy storage performance degradation equivalent failure rate, insufficient power time probability, energy storage capacity margin, reliability degradation rate, SoH decay rate, capacity decay rate, average SoH decay rate, reliability change contribution of each battery cell, SoH change contribution of each battery cell, frequency of each state of the battery energy storage system, average duration of each state of the battery energy storage system, equivalent failure rate, equivalent repair rate, and normal working state probability).

[0149] This paper proposes an indicator system suitable for multi-state modular battery energy storage systems. It describes the reliability of multi-state battery energy storage systems from three dimensions: static state, dynamic change, and system comprehensive state indicators. Each indicator covers the status of battery cells, the battery energy storage system, and the connection between the cells and the whole. It takes into account normal battery attenuation and fault conditions, and establishes corresponding indicators for normal battery attenuation and fault propagation. Based on the indicator system, a battery energy storage condition detection method is proposed, which can be used to analyze and comprehensively evaluate the reliability of the battery energy storage system, thereby obtaining more comprehensive and systematic reliability assessment results.

[0150] Example 2

[0151] In order to execute the method corresponding to the above-mentioned embodiment 1 and achieve the corresponding functions and technical effects, a condition detection system for a battery energy storage system is provided below.

[0152] like Figure 3 As shown, the condition detection system of the battery energy storage system provided in this embodiment includes: a data acquisition unit 1, a static index determination unit 2, a dynamic index determination unit 3, a comprehensive index determination unit 4 and a condition determination unit 5.

[0153] The data acquisition unit 1 is used to acquire operating data of multiple battery energy storage systems. The operating data includes real-time SoH values, initial capacities, fault parameters, and state parameters. The fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transitioning to a faulty state, and the repair rate of the battery energy storage system transitioning to a faulty state. The state parameters include the state transition relationship, the state transition rate, and the duration of each state. The life cycle of the battery energy storage system is divided into multiple states, and each state corresponds to a SoH value and SoH probability value within a set range.

[0154] The static indicator determination unit 2 is connected to the data acquisition unit 1. The static indicator determination unit 2 is used to determine the static state index value of the battery energy storage system according to the operating data of the battery energy storage system for any battery energy storage system; the static state index value is used to determine the performance level of the battery energy storage system in a normal state or a fault state.

[0155] The dynamic index determination unit 3 is connected to the data acquisition unit 1 and the static index determination unit 2 respectively. The dynamic index determination unit 3 is used to determine the dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system; the dynamic change index value is used to determine the reliability change of the battery energy storage system and determine the impact of the performance change of the battery cell on the battery energy storage system.

[0156] The comprehensive index determination unit 4 is connected to the data acquisition unit 1, and the comprehensive index determination unit 4 is used to determine the comprehensive status index value of the battery energy storage system according to the operating data of the battery energy storage system; the comprehensive status index value is used to determine the transition status, failure rate and repair rate between different states of the battery energy storage system.

[0157] The status determination unit 5 is connected to the static index determination unit 2, the dynamic index determination unit 3 and the comprehensive index determination unit 4 respectively. The status determination unit 5 is used to determine the current operating status value of each battery energy storage system based on the static status index value, dynamic change index value and comprehensive status index value of each battery energy storage system.

[0158] Compared with the prior art, the condition detection system of the battery energy storage system provided in this embodiment has the same beneficial effects as the condition detection method of the battery energy storage system provided in the first embodiment, which will not be described in detail here.

[0159] Example 3

[0160] This embodiment provides an electronic device, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the condition detection method of the battery energy storage system of the first embodiment.

[0161] Optionally, the above-mentioned electronic device may be a server.

[0162] In addition, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for detecting the condition of the battery energy storage system of the first embodiment is implemented.

[0163] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0164] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for detecting the condition of a battery energy storage system, wherein the battery energy storage system includes a plurality of battery cells, characterized in that: The condition detection method of the battery energy storage system includes: Obtaining operating data of multiple battery energy storage systems; the operating data includes real-time SoH values, initial capacities, fault parameters, and state parameters; the fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transitioning to a faulty state, and the repair rate of the battery energy storage system transitioning to a faulty state; the state parameters include the state transition relationship, the state transition rate, and the duration of each state; the life cycle of the battery energy storage system is divided into multiple states, each state corresponding to a SoH value and SoH probability value within a set range; For any battery energy storage system, a static state index value of the battery energy storage system is determined based on the operating data of the battery energy storage system; the static state index value is used to determine the performance level of the battery energy storage system in a normal state or a faulty state; the static state index value includes: energy storage reliability, expected energy storage health state, expected energy storage capacity, expected energy storage capacity shortage, unit fault propagation time, equivalent failure rate of energy storage performance degradation, probability of insufficient power time, and energy storage capacity margin; Determine a dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system; the dynamic change index value is used to determine the reliability change of the battery energy storage system and the impact of the performance change of the battery cell on the battery energy storage system; the dynamic change index value includes: reliability degradation rate, SoH decay rate, capacity decay rate, average SoH decay rate, reliability change contribution of each battery cell, and SoH change contribution of each battery cell; Determine a comprehensive state index value of the battery energy storage system based on the operating data of the battery energy storage system; the comprehensive state index value is used to determine the transition between different states of the battery energy storage system, the failure rate and the repair rate; the comprehensive state index value includes: the frequency of each state of the battery energy storage system, the average duration of each state of the battery energy storage system, the equivalent failure rate, the equivalent repair rate and the probability of normal working state; Based on the static state index value, dynamic change index value and comprehensive state index value of each battery energy storage system, the current operating status value of each battery energy storage system is determined.

2. The condition detection method of the battery energy storage system according to claim 1, characterized in that: Determining a static state index value of the battery energy storage system according to the operating data of the battery energy storage system specifically includes: Determining a SoH level set and a SoH level probability set based on the real-time SoH value of the battery energy storage system; the SoH level set includes the SoH levels of the battery energy storage system in each state, and the SoH level probability set includes the SoH probability value of the battery energy storage system in each state; determining energy storage reliability according to the SoH level set, the SoH level probability set, and the minimum performance requirement level of the battery energy storage system; determining an expected energy storage health state according to the SoH level set, the SoH level probability set, and the SoH level threshold; Determining an expected energy storage capacity based on the initial capacity of the battery energy storage system and the expected energy storage health status; determining an expected energy storage capacity shortage based on the initial capacity of the battery energy storage system, the SoH level set, the SoH level threshold, and the SoH level probability set; Determine a unit fault propagation time based on the fault occurrence time, the time when the energy storage reliability drops to 0, and the number of faulty batteries; Determining an energy storage performance degradation equivalent failure rate based on the energy storage reliability; determining a low battery time probability according to the SoH level set, the SoH level threshold, the SoH level probability set, and the duration of each state; An energy storage capacity margin is determined according to the initial capacity of the battery energy storage system, the expected state of health of the energy storage system, the SoH level probability set, and the SoH level threshold.

3. The condition detection method of the battery energy storage system according to claim 1, characterized in that: Determining a dynamic change index value of the battery energy storage system according to the operating data of the battery energy storage system and the static state index value of the battery energy storage system specifically includes: Determining a total decrease in energy storage reliability based on the energy storage reliability of the battery energy storage system at each moment in the detection period; Determining a reliability degradation rate based on the total energy storage reliability degradation value and the detection duration; Determining a total SoH reduction value based on the SoH value of the battery energy storage system at each time point during the detection period; Determining a SoH decay rate according to the total SoH decrease value and the detection duration; Determining a capacity decay rate according to the SoH decay rate and the initial capacity of the battery energy storage system; Determine the average SoH decay rate based on the total number of states, the duration of each state within the detection period, and the SoH decrease value of each state; For any battery cell of the battery energy storage system, determining a reliability change contribution of the battery cell according to the total energy storage reliability decrease value and the reliability decrease value of the battery energy storage system when the SoH value of the battery cell changes by a target SoH value; For any battery cell of the battery energy storage system, the SoH change contribution of the battery cell is determined according to the expected decrease value of the energy storage health state of the battery energy storage system within the detection period and the expected decrease value of the energy storage health state of the battery energy storage system when the SoH value of the battery cell changes by a target SoH value.

4. The condition detection method of the battery energy storage system according to claim 1, characterized in that: Determining a comprehensive status index value of the battery energy storage system according to the operating data of the battery energy storage system specifically includes: For any state in the life cycle of the battery energy storage system, determine the frequency of the state based on the SoH probability value of the state in the battery energy storage system that has a transition relationship with the state, the state transition rate of other states to the state, and the number of states that transition to the state; determining an average duration of the state according to the number of states from which the state transitions to other states and a state transition rate from which the state transitions to other states; determining an equivalent failure rate based on a failure rate of the battery energy storage system transferring to a fault state; determining an equivalent repair rate based on a failure rate of the battery energy storage system transferring to a fault state and a repair rate of the battery energy storage system transferring to a fault state; A normal working state probability is determined according to the equivalent repair rate and the equivalent failure rate.

5. The condition detection method of the battery energy storage system according to claim 1, characterized in that: Based on the static state index value, dynamic change index value and comprehensive state index value of each battery energy storage system, the current operating status value of each battery energy storage system is determined, specifically including: Normalizing the static state index value, dynamic change index value, and comprehensive state index value of each battery energy storage system to obtain the normalized static index value, normalized dynamic index value, and normalized comprehensive index value corresponding to each battery energy storage system; Determine the normalized static index entropy value, normalized dynamic index entropy value and normalized comprehensive index entropy value of each battery energy storage system respectively; Determining the weight of each indicator value of each battery energy storage system according to the normalized static indicator entropy value, normalized dynamic indicator entropy value, normalized comprehensive indicator entropy value, normalized static indicator value, normalized dynamic indicator value, normalized comprehensive indicator value and entropy value parameters of each battery energy storage system; the indicator value is a normalized static indicator value, a normalized dynamic indicator value or a normalized comprehensive indicator value; For any battery energy storage system, the current operating status value of the battery energy storage system is determined according to the weights of the various indicator values ​​of the battery energy storage system, the normalized static indicator value, the normalized dynamic indicator value and the normalized comprehensive indicator value of each battery energy storage system.

6. The method for detecting the condition of a battery energy storage system according to claim 5, characterized in that: The following formula is used to determine the weight of the jth indicator value of the i-th battery energy storage system: Among them, a ij is the weight of the jth index value of the i-th battery energy storage system, W j is the initial weight of the j-th index value, c ij is the jth index value of the i-th battery energy storage system, is the average value of the jth index value of multiple energy storage battery systems, H j is the entropy value of the j-th index value, W 0j is the first entropy parameter, n is the total number of indicator values, W 3j is the second entropy parameter, is the average value of entropy values ​​that are not 1, for 35.5th power, H k is the entropy value of the kth index value.

7. The condition detection method of the battery energy storage system according to claim 5, characterized in that: The following formula is used to determine the current operating status value of the i-th battery energy storage system: Among them, V i is the current operating status value of the i-th battery energy storage system, a ij is the weight of the jth index value of the i-th battery energy storage system, c ij is the jth index value of the i-th battery energy storage system, is the average value of the jth index value of multiple energy storage battery systems, n is the total number of index values, and || indicates the absolute value.

8. A condition detection system for a battery energy storage system, characterized in that: The condition detection system of the battery energy storage system includes: A data acquisition unit is configured to acquire operating data of multiple battery energy storage systems; the operating data includes real-time SoH values, initial capacities, fault parameters, and state parameters; the fault parameters include the time of fault occurrence, the number of faulty batteries, the failure rate of the battery energy storage system transitioning to a faulty state, and the repair rate of the battery energy storage system transitioning to a faulty state; the state parameters include the state transition relationship, the state transition rate, and the duration of each state; the life cycle of the battery energy storage system is divided into multiple states, each state corresponding to a SoH value and SoH probability value within a set range; a static indicator determination unit connected to the data acquisition unit, and configured to determine, for any battery energy storage system, a static state indicator value of the battery energy storage system based on the operating data of the battery energy storage system; the static state indicator value is used to determine the performance level of the battery energy storage system in a normal state or a faulty state; the static state indicator values ​​include: energy storage reliability, expected energy storage health state, expected energy storage capacity, expected energy storage capacity shortage, unit fault propagation time, equivalent failure rate of energy storage performance degradation, probability of insufficient power time, and energy storage capacity margin; a dynamic index determination unit, connected to the data acquisition unit and the static index determination unit, respectively, for determining a dynamic change index value of the battery energy storage system based on the operating data of the battery energy storage system and the static state index value of the battery energy storage system; the dynamic change index value is used to determine the reliability change of the battery energy storage system and the impact of the performance change of the battery cell on the battery energy storage system; the dynamic change index value includes: reliability degradation rate, SoH decay rate, capacity decay rate, average SoH decay rate, reliability change contribution of each battery cell, and SoH change contribution of each battery cell; a comprehensive index determination unit, connected to the data acquisition unit, for determining a comprehensive state index value of the battery energy storage system based on the operating data of the battery energy storage system; the comprehensive state index value is used to determine the transition between different states of the battery energy storage system, the failure rate, and the repair rate; the comprehensive state index value includes: the frequency of each state of the battery energy storage system, the average duration of each state of the battery energy storage system, the equivalent failure rate, the equivalent repair rate, and the probability of a normal working state; A status determination unit is connected to the static index determination unit, the dynamic index determination unit and the comprehensive index determination unit respectively, and is used to determine the current operating status value of each battery energy storage system based on the static status index value, dynamic change index value and comprehensive status index value of each battery energy storage system.

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