A method for line detection and protection of grid-type energy storage systems

Abstract

This invention discloses a line detection and protection method for grid-type energy storage systems, comprising: online sampling of voltage and current signals of the lines in the grid-type energy storage system; multi-scale decomposition of the sampled signals based on a recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-frequency band; continuous processing of the coefficients in segments using a piecewise fidelity contraction function; extraction of transient characteristic parameters of each frequency band; determination of whether the line is in an abnormal operating state; if abnormal, current analysis of the line in the abnormal operating state, combined with a delay setting strategy to generate protection action commands; and, according to the protection action commands, implementation of current limiting, energy suppression, or isolation operations on the grid-type energy storage system to achieve electrical protection of the line. This invention effectively improves the early detection sensitivity of the line to transient faults and regenerative impacts, reduces the false alarm rate, and achieves rapid fault suppression, electrical isolation, and safe recovery without weakening the grid support capability.

Description

Technical Field

[0001] This invention relates to power system protection and energy storage control technology, specifically to a line detection and protection method for grid-type energy storage systems. Background Technology

[0002] With the increasing proportion of renewable energy connected to the grid, energy storage is being used more and more widely in microgrids and distribution networks. Grid-based energy storage, with its ability to support voltage and frequency, has become an important means to ensure the dynamic stability and power quality of microgrids. However, under grid-based operation mode, the DC side of energy storage systems is characterized by high dynamic interaction, regenerative energy reinjection, and transient impacts, which significantly increases the electrical risks of lines under faults or disturbances. DC short circuits, local module anomalies, and rapid regenerative currents can not only lead to equipment overcurrent and overvoltage, but may also trigger thermal runaway and cascading faults, seriously threatening the safety of the substation and the system.

[0003] Existing line protection systems largely rely on simple current or voltage thresholds, passive operation of mechanical circuit breakers or solid-state current limiters, focusing on disconnection or current limiting after a fault occurs. These systems often suffer from delayed response, high false tripping rates, and difficulty in meeting the continuous power supply requirements of grid operation. Furthermore, traditional fault detection methods are mostly based on single measurements and fixed thresholds, making it difficult to distinguish between transient disturbances, regenerative impacts, and actual faults. This results in both missed detections and the risk of power outages due to erroneous disconnections in grid-connected scenarios.

[0004] Therefore, for grid-type energy storage lines, there is an urgent need to develop a graded protection method that can identify line dynamic anomalies early and accurately, and can coordinate with inverter control, current limiters and isolation devices, so as to ensure rapid suppression of sudden faults while preserving the grid support capability of the system to the greatest extent and improving the overall safety and reliability of operation. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a line detection and protection method for grid-type energy storage systems. This method can identify line dynamic anomalies in grid-type energy storage systems early and accurately, and can work in conjunction with inverter control, current limiter and isolation device to achieve hierarchical protection. This ensures rapid suppression of sudden faults while preserving the grid support capability of the system to the greatest extent, thereby improving the overall safety and reliability of operation.

[0006] Technical solution: The present invention provides a line detection and protection method for grid-type energy storage systems, comprising:

[0007] The voltage and current signals of the lines in the grid-type energy storage system are sampled online to obtain the sampled signals;

[0008] The sampled signal is decomposed into multiple scales based on the recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-band.

[0009] A piecewise fidelity shrinkage function is used to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band; transient characteristic parameters of each frequency band are extracted from the recursive frequency band coefficients of each sub-band after piecewise continuous processing.

[0010] Based on the changes in transient characteristic parameters, the single-window anomaly judgment rule is used to determine whether the line is in an abnormal operating state. When the line is determined to be abnormal, the current of the line in an abnormal operating state is analyzed based on the tail hysteresis characteristic identification criterion, and protection action commands are generated in combination with the delay setting strategy.

[0011] Based on the protection action command, current limiting, energy suppression or isolation operations are implemented on the grid-type energy storage system to achieve electrical protection of the line.

[0012] Furthermore, the online sampling of the voltage and current signals of the grid-type energy storage system lines to obtain the sampled signals includes:

[0013] Voltage and current sensors are installed at the line to acquire voltage and current signals. After anti-aliasing low-pass filtering, discrete time-series data is obtained through analog-to-digital conversion. Line voltage sample values ​​at each sampling time With the Line current sampling value at each sampling time Discrete time-series signals are constructed by sampling within a fixed time window. .

[0014] Furthermore, the sampling signal is decomposed into multiple scales based on the recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-band, including:

[0015] For discrete time-series signals conduct Layered recursive frequency band decomposition, in which, for or Let the coefficients of the low-pass filter be analyzed. The high-pass filter coefficients are , order the Layer The node time-domain sequence is ,initial Then for each layer For each node :

[0016] ;

[0017] Final Layer The sequence of sub-band nodes is the set of recursive band coefficients:

[0018] ;

[0019] in, ; For convolution index; For the first Total number of sub-bands;

[0020] For each recursive frequency band coefficient, reverse recursive frequency band reconstruction is performed. First, the upsampling operator S2 is defined as follows:

[0021] ;

[0022] Get the first Sub-band recursive frequency band coefficients Finally, the recursive frequency band coefficients of each sub-band are obtained, and the expressions are as follows:

[0023] ;

[0024] Where L is the number of recursive frequency band decomposition layers.

[0025] Furthermore, the piecewise fidelity shrinkage function is used to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band. Before this, a reference threshold λ is determined for the recursive frequency band coefficients of the sub-bands. The process for determining the reference threshold λ is as follows:

[0026] Take the set of recursive frequency band coefficients The median is used as the coefficient of high-frequency noise. Through the coefficient of high frequency noise Calculate the standard deviation σ of the reference noise:

[0027] ;

[0028] Calculate the reference threshold using the reference noise standard deviation σ :

[0029] .

[0030] Furthermore, the step of using a piecewise fidelity shrinkage function to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band includes:

[0031] Combined with benchmark threshold A piecewise fidelity shrinkage function is used to recursively adjust the frequency band coefficients of each sub-band. Segmented continuous processing is implemented to achieve signal reconstruction. During segmented continuous processing, the recursive frequency band coefficients of each sub-band are processed. Refactor:

[0032] ;

[0033] in, To reconstruct the sub-band signal.

[0034] Furthermore, the extraction of transient characteristic parameters of each frequency band from the recursive frequency band coefficients of each sub-band after segmented continuous processing includes:

[0035] From reconstructing sub-frequency band signals The following transient characteristic parameters are extracted from each frequency band:

[0036] Energy characteristics: Calculate the energy of the k-th frequency band within the sampling window of the current time period. The expression is as follows: ;

[0037] in, Indicates the first The total number of sampling points of the frequency band reconstructed sub-band signal within the current time period sampling window;

[0038] Polar integral characteristic: The polar integral is obtained by integrating the k-th frequency band over the current time period sampling window. The expression is as follows:

[0039] ;

[0040] Standardized Energy Ratio: Calculates the standardized proportion of the total energy of each frequency band within the sampling window of the current time period for the k-th frequency band. The expression is as follows:

[0041] ;

[0042] in, Indicates the first The cumulative energy value of the frequency band within the current sampling window; This indicates the total number of sub-bands participating in energy statistics within the current sampling window.

[0043] Furthermore, the method of determining whether the line is in an abnormal operating state based on the changes in transient characteristic parameters and using single-window anomaly judgment rules includes:

[0044] Energy characteristics Polar integral characteristics Standardized energy ratio As baseline statistics, the following frequency band thresholds are established based on these baseline statistics:

[0045] Calculate the reference mean for each frequency band. Standard deviation of each frequency band :

[0046] ;

[0047] ;

[0048] Based on the reference average value of each frequency band Standard deviation of each frequency band Set the energy threshold With polarity threshold for:

[0049] ;

[0050] ;

[0051] in , This is an empirical coefficient;

[0052] Single-window anomaly detection rules: If a frequency band exists Satisfy any inequality:

[0053] ;

[0054] ;

[0055] frequency band The sampling window within the specified time period is marked as abnormal; to reduce false alarms, a continuous window judgment rule is then applied: within the continuous window... Number of anomalies in each time period sampling window Output the overall anomaly flag A=1 if the condition is met, otherwise A=0;

[0056] Combining the negative polarity criterion as an auxiliary condition, the negative polarity criterion is used to characterize the reconstructed sub-band signal in the frequency band. Whether a persistent negative offset occurs within the sampling window; if the negative offset continuously exceeds a preset threshold, the frequency band is considered to be... There is an abnormal shock trend.

[0057] Furthermore, when an anomaly is determined to occur in the line, the current of the line in the abnormal operating state is analyzed based on the tail hysteresis characteristic identification criterion, and a protection action command is generated in combination with the delay setting strategy, including:

[0058] When the overall anomaly flag A=1, the current waveform of the line in abnormal operation is subjected to a tail hysteresis characteristic identification criterion to determine the protection action; the formation process of the tail hysteresis characteristic identification criterion is as follows:

[0059] Current in the detection section Establish an exponential decay model:

[0060] ;

[0061] ;

[0062] in, This is the value of the secondary current; This is the initial value of the secondary current; It is a time constant; and Equivalent inductance and resistance;

[0063] The criterion for identifying tail hysteresis features is:

[0064] ;

[0065] In the formula, It can be any one of the three phases A, B, and C; for Phase current amplitude; As a braking criterion; for The fundamental amplitude of the phase; for Similar segments at distance complement; This corresponds to the threshold value;

[0066] When the above comprehensive criteria for identifying tail hysteresis characteristics are met, the line current waveform under the current abnormal operating state is determined to have tail hysteresis characteristics, and the failure protection is blocked or the delay is adjusted according to the tail hysteresis characteristics; when the above comprehensive criteria for identifying tail hysteresis characteristics are not met, the line current waveform under the current abnormal operating state is determined to be a non-tail hysteresis fault current, and current limiting or isolation is triggered according to the delay setting strategy.

[0067] Furthermore, the delay setting and triggering logic for the protection action command includes:

[0068] When the current is determined to be a tail hysteresis characteristic current, a blocking or delay strategy is adopted according to the optimized failure protection delay to prevent the failure protection from being falsely triggered. An adaptive delay is selected:

[0069]

[0070] in, To protect the action delay time; For the detection and judgment time of the protection device; This refers to the circuit breaker triggering and mechanical tripping time; To measure the safe time; This is the attenuation amplification factor; For safety margin.

[0071] Furthermore, the delay setting and triggering logic for the protection action command includes:

[0072] When the fault current is determined to be non-hysteresis fault current, the following delay synthesis formula shall be used to perform the action:

[0073]

[0074] in: To protect the action delay time; For the detection and judgment time of the protection device; This refers to the circuit breaker triggering and mechanical tripping time; For the return time of the current element; This is for time margin.

[0075] Beneficial effects: Compared with the prior art, the significant technical effects of the present invention are as follows: (1) The present invention uses a transient feature extraction method that combines recursive frequency band decomposition with piecewise fidelity contraction function to enhance the weak transient signal of the line under high noise background and retain key impact features; combined with tail hysteresis identification, it can effectively distinguish regenerated impact, transient disturbance and real fault, thereby significantly improving the early detection sensitivity of line anomalies and greatly reducing the false alarm rate, which is conducive to improving the accuracy of fault identification and the stability of system operation.

[0076] (2) The delay setting and progressive protection strategy proposed in this invention adaptively determines the delay based on the tail hysteresis criterion. It can avoid false triggering by blocking or delaying when the slowly decaying tail hysteresis characteristics are detected, and can quickly perform current limiting and isolation when a fast fault is confirmed. This cooperative control logic takes into account both the electrical safety of the line and the network support capability. It can maintain the grid continuity to the maximum extent and achieve smooth recovery while suppressing the impact of faults, thereby improving the overall reliability and operational safety of the system. Attached Figure Description

[0077] Figure 1 This is a schematic diagram of the process of the present invention;

[0078] Figure 2 This is a schematic diagram illustrating the principle of the recursive frequency band decomposition algorithm in this invention;

[0079] Figure 3 This is a flowchart of coefficient processing and feature extraction in this invention;

[0080] Figure 4 This is a block diagram of the protection action logic in this invention. Detailed Implementation

[0081] The technical solution of the present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0082] like Figure 1 As shown, the present invention provides a line detection and protection method for grid-type energy storage systems, comprising the following steps:

[0083] S1. Online sampling of the voltage and current signals of the lines in the grid-type energy storage system yields the sampled signals. Details are as follows:

[0084] Voltage and current sensors are installed at the line to acquire voltage and current signals. After anti-aliasing low-pass filtering, discrete time-series data is obtained through analog-to-digital conversion. Line voltage sample values ​​at each sampling time With the Line current sampling value at each sampling time Discrete time-series signals are constructed by sampling within a fixed time window. As input for subsequent recursive frequency band processing.

[0085] The sampling parameters should meet the following preferred value range: analog-to-digital conversion sampling frequency Preferred The sampling period is Time period sampling window length Preferred ,in This represents the number of sampling points within the time period sampling window. The sampling window duration is defined as the time period; the sampling process is incorporated into the monitor's real-time buffer and updated by sliding according to a step size S.

[0086] S2. The sampled signal is decomposed into multiple scales based on the recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-band.

[0087] like Figure 2 As shown, the specific implementation process of step S2 is as follows:

[0088] For discrete time-series signals conduct Layered recursive frequency band decomposition, in which, for or Let the coefficients of the low-pass filter be analyzed. The high-pass filter coefficients are , order the Layer The node time-domain sequence is ,initial Then for each layer For each node :

[0089] ;

[0090] Final Layer The sequence of sub-band nodes is the set of recursive band coefficients:

[0091] ;

[0092] in, ; For convolution index; For the first Total number of sub-bands;

[0093] For each recursive frequency band coefficient, reverse recursive frequency band reconstruction is performed. First, the upsampling operator S2 is defined as follows:

[0094] ;

[0095] Get the first Sub-band recursive frequency band coefficients Finally, the recursive frequency band coefficients of each sub-band are obtained, and the expressions are as follows:

[0096] ;

[0097] in, The preferred number of recursive frequency band decomposition layers is 3 to 5.

[0098] S3. The piecewise fidelity shrinkage function is used to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band; the transient characteristic parameters of each frequency band are extracted from the recursive frequency band coefficients of each sub-band after piecewise continuous processing.

[0099] like Figure 3 As shown, the specific implementation process of step S3 is as follows:

[0100] S3.1 Determine the reference threshold λ for the sub-band recursive frequency band coefficients. The process for determining the reference threshold λ is as follows:

[0101] First, the coefficients of the high-frequency noise are estimated by taking the set of recursive frequency band coefficients. The median is used as the coefficient of high-frequency noise. Through the coefficient of high frequency noise Calculate the standard deviation σ of the reference noise:

[0102] ;

[0103] Finally, the baseline threshold was determined. The standard deviation of the reference noise, σ, can be used to calculate:

[0104] .

[0105] S3.2, Combining the benchmark threshold A piecewise fidelity shrinkage function is used to recursively adjust the frequency band coefficients of each sub-band. Segmented continuous processing is implemented to achieve signal reconstruction. During segmented continuous processing, the recursive frequency band coefficients of each sub-band can be processed. Refactor:

[0106] ;

[0107] in, To reconstruct the sub-band signal; to reconstruct the sub-band signal exist Internal continuity, that is, in Since it is continuous, the same logic applies. exist The locations are also continuous.

[0108] S3.3 Extract the transient characteristic parameters of each frequency band from the recursive frequency band coefficients of each sub-band after segmented continuous processing, as follows:

[0109] From reconstructing sub-frequency band signals The following transient characteristic parameters are extracted from each frequency band, and these parameters are compiled for subsequent determination:

[0110] Energy characteristics: Calculate the energy of the k-th frequency band within the sampling window of the current time period. The expression is as follows: ;

[0111] in, Indicates the first The total number of sampling points of the frequency band reconstructed sub-band signal within the current time period sampling window;

[0112] Polar integral characteristics: Calculating the first The polar integral obtained by integrating the frequency band over the sampling points within the current time period sampling window. The expression is as follows:

[0113] ;

[0114] Standardized energy ratio: Calculate the first The normalized percentage of the total energy of each frequency band within the current sampling window. The expression is as follows:

[0115] ;

[0116] in, Indicates the first The cumulative energy value of the frequency band within the current sampling window; This indicates the total number of sub-bands participating in energy statistics within the current sampling window.

[0117] S4. Based on the changes in transient characteristic parameters, use the single-window anomaly judgment rule to determine whether the line is in an abnormal operating state; when the line is determined to be abnormal, analyze the current of the line in an abnormal operating state based on the tail hysteresis characteristic identification criterion, and generate protection action commands in combination with the delay setting strategy.

[0118] like Figure 4 As shown, the specific implementation process of step S4 is as follows:

[0119] S4.1 Based on the changes in transient characteristic parameters, the single-window anomaly judgment rule is used to determine whether the line is in an abnormal operating state, as follows:

[0120] Energy characteristics Polar integral characteristics Standardized energy ratio As baseline statistics, the following frequency band thresholds are established based on these baseline statistics:

[0121] Calculate the reference mean for each frequency band. Standard deviation of each frequency band :

[0122] ;

[0123] ;

[0124] Based on the reference average value of each frequency band Standard deviation of each frequency band Set the energy threshold With polarity threshold for:

[0125] ;

[0126] ;

[0127] in , This is an empirical coefficient. , A ratio of 0.1 to 0.6 is used for safety margin adjustment;

[0128] Single-window anomaly detection rules: If a frequency band exists Satisfy any inequality:

[0129] ;

[0130] ;

[0131] frequency band The sampling window within the specified time period is marked as abnormal. To reduce false alarms, a continuous window judgment rule is then applied: within a continuous window... Number of anomalies in each time period sampling window Output the overall anomaly flag A=1 if the condition is met, otherwise A=0.

[0132] At the same time, the negative polarity criterion is used as an auxiliary condition. The negative polarity criterion is used to characterize the reconstructed sub-band signal in the frequency band. Whether a persistent negative offset occurs within the sampling window; if the negative offset continuously exceeds a preset threshold, the frequency band is considered to be... There is an abnormal impact trend, to prevent misjudgment caused by single-window noise peaks;

[0133] The preset threshold can be set from the first under normal working conditions. Frequency band polarity integral characteristics Reference mean with standard deviation Confirmed, recorded as:

[0134] ;

[0135] in, As a preset threshold, For the first The reference mean of the frequency band, For the first Standard deviation of frequency band This is an empirical coefficient, typically taken as 2.0-2.5.

[0136] S4.2 When an anomaly is detected in the line, the current of the line in the abnormal operating state is analyzed based on the tail hysteresis characteristic identification criterion, and a protection action command is generated in combination with the time delay setting strategy. Specifically:

[0137] When the overall anomaly flag A=1, the current waveform of the line in abnormal operation is subjected to a tail hysteresis characteristic identification criterion to determine the protection action; the formation process of the tail hysteresis characteristic identification criterion is as follows:

[0138] Tail hysteresis characteristic dynamic model and parameter estimation for current in the detection section. An exponential decay model is established, in which the hysteresis component on the secondary side of the current transformer approximates exponential decay:

[0139] ;

[0140] ;

[0141] in, This is the value of the secondary current; This is the initial value of the secondary current; It is a time constant; and For equivalent inductance and resistance.

[0142] The criterion for identifying tail hysteresis features is:

[0143] ;

[0144] In the formula, It can be any one of the three phases A, B, and C; for Phase current amplitude; As a braking criterion, 1.2 can be taken; for The fundamental amplitude of the phase; for Similar segments at distance complement; This is the corresponding threshold value, which can generally be taken as 0.83.

[0145] When the above comprehensive criteria for identifying tail hysteresis characteristics are met, the line current waveform under the current abnormal operating state is determined to have tail hysteresis characteristics, and the failure protection is blocked or the delay is adjusted according to the tail hysteresis characteristics; when the above comprehensive criteria for identifying tail hysteresis characteristics are not met, the line current waveform under the current abnormal operating state is determined to be a non-tail hysteresis fault current, and current limiting or isolation is triggered according to the delay setting strategy.

[0146] The delay setting and triggering logic for protection action commands include:

[0147] When the current is determined to be a tail hysteresis characteristic current, a blocking or delay strategy is adopted according to the optimized failure protection delay to prevent the failure protection from being falsely triggered. An adaptive delay is selected:

[0148]

[0149] in, To protect the action delay time; To allow for detection and judgment time of the protection device, select 10~20ms. Select 10~30ms for the circuit breaker triggering and mechanical tripping time; To ensure a safe measurement time, 5ms is typically used. The attenuation amplification factor is typically taken as 2 to 4; For safety margin, 20–50ms is recommended.

[0150] When the fault current is determined to be non-hysteresis fault current, the following delay synthesis formula shall be used to perform the action:

[0151]

[0152] in: To protect the action delay time; For the detection and judgment time of the protection device; This refers to the circuit breaker triggering and mechanical tripping time; For the return time of the current element, select ≤5ms; For a time margin, choose approximately 38ms. Overall, it is recommended to... Approximately 80ms was used as an example to balance sensitivity and reliability.

[0153] S5. Based on the protection action command, implement current limiting, energy suppression or isolation operations on the grid-type energy storage system to achieve electrical protection of the line.

[0154] The protection execution includes actions in a priority order: first, the grid-type energy storage inverter actively absorbs energy or guides power to suppress short-term energy surges in the line; if the line energy or current still exceeds the limit after energy absorption is initiated, the solid-state current limiter is triggered to perform rapid current limiting according to the preset current limiting law; finally, if necessary, packet-level isolation or station-level mechanical disconnection is performed; each action is executed sequentially under the command of the protection decision unit and is recorded for offline analysis.

[0155] This invention samples voltage or current signals at the line location and performs multi-scale decomposition of the sampled signals based on a recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-frequency band. A piecewise fidelity contraction function is used to process the recursive frequency band coefficients of each sub-frequency band in a piecewise continuous manner. Subsequently, transient characteristic parameters of each frequency band are extracted and standardized to form an energy ratio. Energy and polarity thresholds for each frequency band are determined, and anomaly detection is performed. When an overall anomaly is detected, tail hysteresis feature identification is performed on the current in the abnormal segment to determine if it is a tail hysteresis failure feature. Based on the tail hysteresis criterion and the persistence of the anomaly, combined with a time delay setting strategy, protection action commands are generated and executed in a priority-based progression. This invention combines the recursive frequency band transient feature extraction algorithm with the tail hysteresis feature identification criterion, and coordinates it with time delay setting, current limiting or isolation strategies for grid-type inverters to achieve early anomaly detection and progressive protection of the line. This invention can effectively improve the early detection sensitivity of the line to transient faults and regenerative impacts, reduce the false alarm rate, and achieve rapid fault suppression, electrical isolation, and safe recovery without weakening the grid support capability.

Claims

1. A method for line detection and protection in grid-type energy storage systems, characterized in that, include: The voltage and current signals of the lines in the grid-type energy storage system are sampled online to obtain the sampled signals; The sampled signal is decomposed into multiple scales based on the recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-band. A piecewise fidelity shrinkage function is used to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band. Extract transient characteristic parameters of each frequency band from the recursive frequency band coefficients of each sub-band after segmented continuous processing; Based on the changes in transient characteristic parameters, the single-window anomaly judgment rule is used to determine whether the line is in an abnormal operating state. When the line is determined to be abnormal, the current of the line in an abnormal operating state is analyzed based on the tail hysteresis characteristic identification criterion, and protection action commands are generated in combination with the delay setting strategy. Based on the protection action command, current limiting, energy suppression or isolation operations are implemented on the grid-type energy storage system to achieve electrical protection of the line.

2. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, The online sampling of voltage and current signals of the lines in the grid-type energy storage system to obtain sampled signals includes: Voltage and current sensors are installed at the line to acquire voltage and current signals. After anti-aliasing low-pass filtering, discrete time-series data is obtained through analog-to-digital conversion. Line voltage sample values ​​at each sampling time With the Line current sampling value at each sampling time Discrete time-series signals are constructed by sampling within a fixed time window. .

3. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, The sampling signal is decomposed into multiple scales based on the recursive frequency band decomposition algorithm to obtain the recursive frequency band coefficients of each sub-band, including: For discrete time-series signals conduct Layered recursive frequency band decomposition, in which, for or Let the coefficients of the low-pass filter be analyzed. The high-pass filter coefficients are , order the Layer The node time-domain sequence is ,initial Then for each layer For each node : ； Final Layer The sequence of sub-band nodes is the set of recursive band coefficients: ； in, ; For convolution index; For the first Total number of sub-bands; For each recursive frequency band coefficient, perform inverse recursive frequency band reconstruction, first defining the upsampling operator. for ； Get the first Sub-band recursive frequency band coefficients Finally, the recursive frequency band coefficients of each sub-band are obtained, and the expressions are as follows: ； in, This represents the number of recursive frequency band decomposition layers.

4. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, The piecewise fidelity shrinkage function is used to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band. Before this, a reference threshold λ is determined for the recursive frequency band coefficients of the sub-bands. The process of determining the reference threshold λ is as follows: Take the set of recursive frequency band coefficients The median is used as the coefficient of high-frequency noise. Through the coefficient of high frequency noise Calculate the standard deviation of the reference noise : ； Using the standard deviation of reference noise Calculate the baseline threshold : 。 5. The line detection and protection method for grid-type energy storage systems according to claim 4, characterized in that, The step of using a piecewise fidelity contraction function to perform piecewise continuous processing on the recursive frequency band coefficients of each sub-band includes: Combined with benchmark threshold A piecewise fidelity shrinkage function is used to recursively adjust the frequency band coefficients of each sub-band. Segmented continuous processing is implemented to achieve signal reconstruction. During segmented continuous processing, the recursive frequency band coefficients of each sub-band are processed. Refactor: ； in, To reconstruct the sub-band signal.

6. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, The extraction of transient characteristic parameters for each frequency band from the recursive frequency band coefficients of each sub-band after segmented continuous processing includes: From reconstructing sub-frequency band signals The following transient characteristic parameters are extracted from each frequency band: Energy characteristics: Calculate the energy of the k-th frequency band within the sampling window of the current time period. The expression is as follows: ; in, Indicates the first The total number of sampling points of the frequency band reconstructed sub-band signal within the current time period sampling window; Polar integral characteristics: Calculating the first The polar integral obtained by integrating the frequency band over the sampling points within the current time period sampling window. The expression is as follows: ； Standardized energy ratio: Calculate the first The normalized percentage of the total energy of each frequency band within the current sampling window. The expression is as follows: ； in, Indicates the first The cumulative energy value of the frequency band within the current sampling window; This indicates the total number of sub-bands participating in energy statistics within the current sampling window.

7. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, The method of determining whether a line is in an abnormal operating state based on changes in transient characteristic parameters and using single-window anomaly detection rules includes: Energy characteristics Polar integral characteristics Standardized energy ratio As baseline statistics, the following frequency band thresholds are established based on these baseline statistics: Calculate the reference mean for each frequency band. Standard deviation of each frequency band : ； ； Based on the reference average value of each frequency band Standard deviation of each frequency band Set the energy threshold With polarity threshold for: ； ； in , This is an empirical coefficient; Single-window anomaly detection rule: If a frequency band exists Satisfy any inequality: ； ； frequency band The sampling window within the specified time period is marked as abnormal; to reduce false alarms, a continuous window judgment rule is then applied: within the continuous window... Number of anomalies in each time period sampling window Output the overall anomaly flag A=1 if the condition is met, otherwise A=0; Combining the negative polarity criterion as an auxiliary condition, the negative polarity criterion is used to characterize the reconstructed sub-band signal in the frequency band. Whether a persistent negative offset occurs within the sampling window; if the negative offset continuously exceeds a preset threshold, the frequency band is considered to be... There is an abnormal shock trend.

8. The line detection and protection method for grid-type energy storage systems according to claim 1, characterized in that, When an anomaly is detected in the line, the current of the line in the abnormal operating state is analyzed based on the tail hysteresis characteristic identification criterion, and a protection action command is generated in combination with the time delay setting strategy, including: When the overall anomaly flag A=1, the hysteresis characteristic identification criterion is applied to the current waveform of the line in abnormal operation to determine the protection action; the formation process of the hysteresis characteristic identification criterion is as follows: Current in the detection section Establish an exponential decay model: ； ； in, This is the value of the secondary current; This is the initial value of the secondary current; It is a time constant; and Equivalent inductance and resistance; The criterion for identifying tail hysteresis features is: ； In the formula, It can be any one of the three phases A, B, and C; for Phase current amplitude; As a braking criterion; for The fundamental amplitude of the phase; for Similar segments at distance complement; This corresponds to the threshold value; When the above comprehensive criteria for identifying tail hysteresis characteristics are met, the line current waveform under the current abnormal operating state is determined to have tail hysteresis characteristics, and the failure protection is blocked or the delay is adjusted according to the tail hysteresis characteristics; when the above comprehensive criteria for identifying tail hysteresis characteristics are not met, the line current waveform under the current abnormal operating state is determined to be a non-tail hysteresis fault current, and current limiting or isolation is triggered according to the delay setting strategy.

9. The line detection and protection method for grid-type energy storage systems according to claim 8, characterized in that, The delay setting and triggering logic of the protection action command includes: When the current is determined to be a tail hysteresis characteristic current, a blocking or delay strategy is adopted according to the optimized failure protection delay to prevent the failure protection from being falsely triggered. An adaptive delay is selected: in, To protect the action delay time; For the detection and judgment time of the protection device; This refers to the circuit breaker triggering and mechanical tripping time; To measure the safe time; This is the attenuation amplification factor; For safety margin.

10. The line detection and protection method for grid-type energy storage systems according to claim 8, characterized in that, The delay setting and triggering logic of the protection action command includes: When the fault current is determined to be non-hysteresis fault current, the following delay synthesis formula shall be used to perform the action: in: To protect the action delay time; For the detection and judgment time of the protection device; This refers to the circuit breaker triggering and mechanical tripping time; For the return time of the current element; This is for time margin.

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