An energy storage and conversion test protection state monitoring method and system based on the internet of things

Abstract

This invention relates to the field of power electronics technology and discloses a method and system for monitoring the protection status of energy storage converter tests based on the Internet of Things (IoT). The method includes the following steps: constructing a synchronous acquisition network composed of multiple IoT measurement nodes; injecting a pre-defined controllable perturbation signal during the energy storage converter test; calculating the energy proxy quantity corresponding to each protection energy channel based on the synchronously acquired data subsequence within the time window; establishing a structural mapping relationship between the protection energy channel and the protection device and loop nodes; fusing the protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset to output the corresponding protection status judgment result. This invention, through the time-synchronous acquisition of controllable perturbation signals and multiple IoT measurement nodes, ensures that the protection loop is recorded under the same time reference, thereby obtaining complete transient response data of the protection structure to disturbances during the test.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and in particular to a method and system for monitoring the protection status of energy storage converters based on the Internet of Things. Background Technology

[0002] With the large-scale application of energy storage systems in power systems, energy storage converters, as key equipment for realizing bidirectional energy conversion between DC energy storage units and AC power grids, have their operational safety and protection reliability directly related to the stable operation of energy storage systems.

[0003] Existing energy storage converter testing and protection status monitoring schemes typically rely on distributed voltage sensors, current sensors, temperature sensors, and grounding monitoring devices to collect parameters such as bus voltage, bus current, device temperature, and grounding current. The collected results are then recorded and analyzed by a higher-level monitoring system. In some testing systems, fault injection or step disturbances are used to apply test excitations to the converter to trigger protection actions or observe parameter changes before and after protection. During actual testing, due to the significant transient characteristics of the protection circuit response, surge absorption branches, shutdown branches, grounding discharge branches, and control isolation branches exhibit rapidly changing voltage, current, temperature rise, and electromagnetic characteristics under minute disturbances.

[0004] Therefore, the inventors of this application discovered during the research process that the existing energy storage converter test protection status monitoring technology has at least the following technical problems: the lack of a mechanism for synchronous acquisition of multi-source parameters based on a unified time reference and accurate alignment of disturbance events in protection testing makes it impossible to obtain complete transient response data of the protection circuit to disturbances under the same time reference system. Summary of the Invention

[0005] To overcome the above shortcomings, this invention provides an IoT-based method and system for monitoring the protection status of energy storage converter tests, aiming to improve the problem that existing technologies cannot completely obtain transient response data of the protection circuit to disturbances in the same reference frame at the same time.

[0006] The solution of the present invention to the above-mentioned technical problems is as follows: A method for monitoring the protection status of energy storage converter tests based on the Internet of Things includes the following steps: S1. Construct a synchronous acquisition network composed of multiple IoT measurement nodes to acquire bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature and electromagnetic characteristic quantities during the energy storage converter test to obtain synchronous acquisition data, and perform time synchronization marking on the obtained synchronous acquisition data to obtain a multi-parameter synchronous data sequence. S2. During the testing of the energy storage converter, a controllable perturbation signal of a preset form is injected. A time window is established with the injection time of the controllable perturbation signal as the center, and the synchronous acquisition data subsequence corresponding to the time window is extracted from the multi-parameter synchronous data sequence. S3. Define the protection energy channels according to the hardware circuit of the energy storage converter, and calculate the energy proxy amount corresponding to each protection energy channel within the time window based on the synchronously acquired data subsequence. S4. Perform nonnegation and normalization on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. S5. Establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and construct the protective energy topology weight matrix according to the energy distribution ratio. S6. Calculate the protection topology entropy based on the protection energy topology weight matrix, and calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix, and the protection topology entropy and their respective reference data to obtain the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, respectively. S7. The protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset are fused and processed to output the corresponding protection status judgment result.

[0007] Further specifying, in step S1, the step of performing time synchronization marking on the obtained synchronously acquired data to obtain a multi-parameter synchronous data sequence includes: Configure a unified time reference source for each of the IoT measurement nodes; Timestamps are assigned to the bus voltage sampling channel, bus current sampling channel, voltage change rate calculation channel, current change rate calculation channel, ground current sampling channel, ground loop impedance measurement channel, device temperature sampling channel, and electromagnetic characteristic quantity sampling channel of each IoT measurement node, so that the obtained synchronous acquisition data has timestamps. Upload the timestamped synchronously collected data to the host processing unit; The data from different IoT measurement nodes are rearranged and aligned according to the timestamp order to form a multi-parameter synchronized data sequence under a unified time axis.

[0008] Further specifying, the injection of a controllable perturbation signal of a preset form during the testing of the energy storage converter includes the following steps: The preset controllable perturbation signal forms include at least one of voltage perturbation signal, current perturbation signal, impedance perturbation signal and phase perturbation signal; The controllable perturbation signal is superimposed onto the DC-side circuit, AC-side circuit, control circuit, or grounding circuit corresponding to the energy storage converter; Record the injection parameters for each controllable perturbation signal, including the injection start time, duration, and signal amplitude parameters; The injected parameters are associated with and stored with the corresponding multi-parameter synchronization data sequences.

[0009] Further defining the step of establishing a time window centered on the injection time of each controllable perturbation signal and extracting the synchronously acquired data subsequence corresponding to the time window from the multi-parameter synchronous data sequence includes the following steps: The injection start time of the controllable perturbation signal is used as the reference time; A first sampling interval length is set before the reference time to form a pre-sampling interval; A second sampling interval length is set after the reference time to form a post-sampling interval; The pre-sampling interval and the post-sampling interval are spliced ​​together to form a complete time window; Data corresponding to the time window is extracted from the multi-parameter synchronous data sequence to form a synchronous acquisition data sub-sequence.

[0010] Further specifying, step S3 includes the following steps: The surge absorption branch, shutdown dissipation branch, filter energy storage branch, grounding discharge branch and control isolation branch in the energy storage converter are defined as independent protection energy channels. Assign a unique channel number to each protective energy channel; Establish a table showing the correspondence between protective energy channels and their corresponding hardware circuit components, connection nodes, and loop topologies; From the multi-parameter synchronous data subsequence within the time window, bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature change, and electromagnetic characteristics are extracted to form a multi-dimensional feature vector; For each protective energy channel, select the associated characteristic component based on its corresponding hardware circuit. The channel transient response sequence is obtained by performing a weighted combination operation on the feature components. Discrete integral operations are performed on the transient response sequence of the channel within a time window to obtain the energy proxy quantity of the corresponding protective energy channel.

[0011] Further specifying, step S4 includes the following steps: The energy proxy quantities of each protective energy channel are uniformly processed to map negative values ​​to zero; The summation result is obtained by summing the energy proxy quantities of each mapped protective energy channel; Divide the energy proxy amount of each protective energy channel by the summation result to obtain the energy distribution ratio; The energy distribution ratios are arranged in the order of the channel numbers of the protective energy channels to form a protective energy fingerprint vector.

[0012] Further specifying, step S5 includes the following steps: The protection devices, loop nodes, and connection nodes in the energy storage converter are abstracted as topology nodes; The protective energy channel is abstracted as a topological edge connecting the topological nodes; Establish a correspondence table between the topological edges and the channel numbers; Based on the energy distribution ratio in the protective energy fingerprint vector, weights are assigned to the corresponding topological edges; Construct a protective energy topological weight matrix by combining the order of topological nodes with the weights assigned to topological edges.

[0013] Further specifying, the calculation of the protective topology entropy based on the protective energy topology weight matrix includes the following steps: The weights of each topological edge in the protective energy topological weight matrix are normalized. The normalized topological edge weights are converted into a probability distribution form; The corresponding protective topology entropy is calculated based on the probability distribution.

[0014] Further specifying, step S7 includes the following steps: The protective topology entropy offset, protective energy fingerprint offset, and protective energy topology weight offset are processed to have unified dimensions. The processed protection topology entropy offset, protection energy fingerprint offset, and protection energy topology weight offset are combined according to a preset fusion rule to generate protection status discrimination input. The protection status determination result is obtained based on the input quantity of the protection status determination.

[0015] An IoT-based energy storage converter test protection status monitoring system, used to implement the above-mentioned IoT-based energy storage converter test protection status monitoring method, includes: The multi-parameter synchronous data acquisition module is used to construct a synchronous acquisition network composed of multiple IoT measurement nodes. During the testing of the energy storage converter, it acquires synchronous acquisition data such as bus voltage, bus current, voltage change rate, current change rate, grounding current, grounding loop impedance, device temperature and electromagnetic characteristic quantities. The module then performs time synchronization marking on the acquired synchronous acquisition data to obtain a multi-parameter synchronous data sequence. The time window establishment module is used to inject a preset form of controllable perturbation signal during the testing of the energy storage converter, establish a time window with the injection time of each controllable perturbation signal as the center, and extract the synchronous acquisition data subsequence corresponding to the time window from the multi-parameter synchronous data sequence. The protective energy proxy quantity acquisition unit is used to define the protective energy channel according to the hardware circuit of the energy storage converter, and calculate the energy proxy quantity corresponding to each protective energy channel based on the synchronously acquired data subsequence within the time window. The protective energy fingerprint vector acquisition module is used to perform nonnegation and normalization processing on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. The protective energy topology weight matrix module is used to establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and to construct the protective energy topology weight matrix according to the energy distribution ratio. The offset calculation module is used to calculate the protection topology entropy based on the protection energy topology weight matrix, and to calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix and the protection topology entropy and their respective reference data, so as to obtain the protection energy fingerprint offset, the protection energy topology weight offset and the protection topology entropy offset respectively. The protection status discrimination module is used to fuse the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, and output the corresponding protection status discrimination result.

[0016] The beneficial effects of this invention are as follows: 1. This invention constructs a synchronous acquisition network composed of multiple IoT measurement nodes to synchronously acquire bus voltage, bus current, voltage change rate, current change rate, grounding current, grounding loop impedance, device temperature, and electromagnetic characteristic quantities during the testing of energy storage converters. It also injects a pre-defined form of controllable perturbation signal and establishes a time window centered on each injection moment. The corresponding synchronous acquisition data subsequence is extracted from the multi-parameter synchronous data sequence, thereby achieving precise alignment of the controllable perturbation signal and multi-source parameters under the same time reference during the testing process. This allows the complete transient response data of the protection circuit before and after the perturbation to be fully acquired.

[0017] 2. This invention ensures the reliable generation of data subsequences that strictly correspond to perturbation events, from the original synchronously acquired data, by configuring a unified time base, allocating timestamps, rearranging and aligning data, and precisely defining time windows. By defining protective energy channels, calculating energy proxy quantities, and performing nonnegation and normalization, a protective energy fingerprint vector characterizing the energy distribution ratio of each channel is formed, achieving a unified quantitative expression of the energy proportion of multiple protective branches. By abstracting physical components as topological nodes and energy channels as topological edges, and allocating weights based on the fingerprint vector to construct a protective energy topological weight matrix, the energy distribution is mapped to... The actual physical topology structure enables a structured description of the energy transfer relationship in the protection loop. By normalizing and probabilizing the topology weight matrix and calculating the protection topology entropy, a quantifiable scalar index is provided for the energy distribution dispersion in the topology structure. By calculating the offsets of the above vectors, matrices, and entropy values ​​with the benchmark value, and by unifying and fusing the offsets, the protection status judgment result is finally obtained based on the fused input. Thus, the change information of the three dimensions of energy distribution, topology structure, and overall dispersion is comprehensively utilized, and a comprehensive, structured, and objective intelligent judgment of the protection status of the energy storage converter is achieved. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the steps of a method for monitoring the protection status of energy storage converters based on the Internet of Things according to the present invention. Figure 2 This is a diagram of an IoT-based energy storage converter test protection status monitoring system according to the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0022] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0023] Example 1 refer to Figure 1 This invention provides a method for monitoring the protection status of energy storage converter tests based on the Internet of Things, comprising the following steps: S1. Construct a synchronous acquisition network composed of multiple IoT measurement nodes to acquire bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature and electromagnetic characteristic quantities during the energy storage converter test to obtain synchronous acquisition data, and perform time synchronization marking on the obtained synchronous acquisition data to obtain a multi-parameter synchronous data sequence. S2. During the testing of the energy storage converter, a controllable perturbation signal of a preset form is injected. A time window is established with the injection time of the controllable perturbation signal as the center, and the synchronous acquisition data subsequence corresponding to the time window is extracted from the multi-parameter synchronous data sequence. S3. Define the protection energy channels according to the hardware circuit of the energy storage converter, and calculate the energy proxy amount corresponding to each protection energy channel within the time window based on the synchronously acquired data subsequence. S4. Perform nonnegation and normalization on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. S5. Establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and construct the protective energy topology weight matrix according to the energy distribution ratio. S6. Calculate the protection topology entropy based on the protection energy topology weight matrix, and calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix, and the protection topology entropy and their respective reference data to obtain the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, respectively. S7. The protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset are fused and processed to output the corresponding protection status judgment result.

[0024] Specifically, in the synchronous acquisition network, each IoT measurement node is synchronized with a unified time base to synchronously sample bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature and electromagnetic characteristic quantities, and add a unified format timestamp information to the sampled data to form a multi-parameter data sequence on the same time axis.

[0025] During the testing of the energy storage converter, at least one of the following perturbation signals—voltage, current, impedance, or phase—is superimposed onto the DC-side circuit, AC-side circuit, control circuit, or grounding circuit according to a preset test sequence. The injection start time and duration of each controllable perturbation signal are recorded. Based on the injection start time, a pre-sampling interval is selected forward, and a post-sampling interval is selected backward. The pre-sampling interval and the post-sampling interval are spliced ​​together to form a time window, and the data subsequences within the corresponding time window are extracted from the synchronously acquired data sequence.

[0026] Within the time window, the surge absorption branch, shutdown dissipation branch, filtering energy storage branch, grounding discharge branch, and control isolation branch in the energy storage converter are defined as protection energy channels, and each protection energy channel is assigned a channel number. Based on the loop structure corresponding to each protection energy channel, voltage, current, rate of change, grounding parameters, temperature, and electromagnetic characteristics associated with it are selected from the synchronously acquired data within the time window to construct a channel feature set. The feature set is then weighted and combined according to preset weights to obtain the transient response sequence of each protection energy channel. Discrete integration is performed on the channel transient response sequence within the time window to obtain the energy proxy quantity corresponding to each protection energy channel.

[0027] The energy proxy quantities of each protective energy channel are uniformly labeled, negative values ​​are mapped to zero, and then summed. The energy proxy quantity of each protective energy channel is then divided by the summation result to obtain the energy distribution ratio of each protective energy channel in this controllable perturbation event. The energy distribution ratios are arranged according to the protective energy channel numbers to form a protective energy fingerprint vector. The protective devices, loop nodes, and connection nodes in the energy storage converter are abstracted as topology nodes, and the protective energy channels are abstracted as topology edges connecting these topology nodes. A correspondence is established between the topology edges and the protective energy channel numbers. Based on the energy distribution ratio of each protective energy channel in the protective energy fingerprint vector, weights are assigned to the corresponding topology edges, and a protective energy topology weight matrix is ​​constructed according to the topology node numbering order.

[0028] The weights of each topological edge in the protection energy topology weight matrix are normalized to form a probability distribution, and the protection topology entropy is calculated based on the probability distribution. When the energy storage converter protection structure is in the baseline state, a baseline protection energy fingerprint vector, a baseline protection energy topology weight matrix, and a baseline protection topology entropy are established based on multiple controllable perturbation events. The protection energy fingerprint vector, protection energy topology weight matrix, and protection topology entropy corresponding to the current controllable perturbation event are differentially processed with the baseline data to obtain the protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset; wherein, the baseline data are the protection energy fingerprint vector, protection energy topology weight matrix, and protection topology entropy obtained when the energy storage converter protection structure is in normal and healthy condition. After unifying the dimensions of the above offsets, they are combined according to the preset fusion rules to form a protection status discrimination dataset.

[0029] Through the above technical solutions, without triggering the protection action of the energy storage converter, controllable micro-disturbance events are introduced and combined with synchronous acquisition and time windowing processing of multiple IoT nodes to achieve a quantitative expression of the transient energy distribution structure of the protection energy channel; by constructing the protection energy fingerprint vector and the protection energy topology weight matrix, a structured description of the energy distribution relationship of the protection loop is realized; by calculating the protection topology entropy and its offset, the quantitative characterization of the discreteness of the protection energy transfer path is realized, so that the protection structure state during the energy storage converter test can be objectively characterized and judged in the form of energy distribution and topology parameters.

[0030] Furthermore, in step S1, the step of performing time synchronization marking on the obtained synchronously acquired data to obtain a multi-parameter synchronous data sequence includes: Configure a unified time reference source for each of the IoT measurement nodes; Timestamps are assigned to the bus voltage sampling channel, bus current sampling channel, voltage change rate calculation channel, current change rate calculation channel, ground current sampling channel, ground loop impedance measurement channel, device temperature sampling channel, and electromagnetic characteristic quantity sampling channel of each IoT measurement node, so that the obtained synchronous acquisition data has timestamps. Upload the timestamped synchronously collected data to the host processing unit; The data from different IoT measurement nodes are rearranged and aligned according to the timestamp order to form a multi-parameter synchronized data sequence under a unified time axis.

[0031] Specifically, a unified time reference source is set in the host processing unit or an independent time synchronization module, and periodically sends time synchronization signals to each IoT measurement node via a wired or wireless time synchronization link. After receiving the time synchronization signal, each IoT measurement node calibrates its local clock to ensure that its local timer is consistent with the unified time reference.

[0032] In each IoT measurement node, the bus voltage sampling channel, bus current sampling channel, ground current sampling channel, and device temperature sampling channel are all sampled by the analog-to-digital conversion unit according to a uniform sampling period; the voltage change rate and current change rate are obtained by differential calculation of adjacent sampling points; the ground loop impedance is calculated from the voltage and current measurements according to the impedance calculation relationship; electromagnetic characteristic quantities are obtained by sampling or energy integration by the sensing unit of the corresponding frequency band. Each sampled value is written to a timestamp field by the local clock while being converted into a digital quantity.

[0033] Let the k-th IoT measurement node be at its local time. The nth data sample collected is After time synchronization calibration, the local time of each node satisfies:

[0034] in, To establish a unified time base, The sampling period set for the system, This represents the residual time deviation of the k-th node after calibration. Through periodic calibration, each node... Maintain within the preset allowable range.

[0035] The IoT measurement nodes send data frames containing timestamps to the upper-level processing unit. The data frame includes at least the node number, channel number, sample value, and corresponding timestamp. The upper-level processing unit sorts the data from different nodes according to the timestamps and uses a unified timeline. Based on the same time index The multi-node, multi-channel data is aligned to form a synchronous sampling matrix, where each row corresponds to a time index and each column corresponds to a measurement channel or node channel combination. In cases of missing sampling points, the upper-level processing unit interpolates or marks the missing status based on data from adjacent time indices, and maintains time index consistency in subsequent processing steps.

[0036] Through the above time synchronization and rearrangement processing, the bus voltage, bus current, voltage change rate, current change rate, grounding current, grounding loop impedance, device temperature, and electromagnetic characteristic quantities are made into a multi-parameter synchronized data sequence under the same time reference. This provides a consistent time sequence basis for subsequent establishment of time windows centered on perturbation events, calculation of transient responses of protection energy channels, and construction of energy proxy models. This ensures that the data from different measurement channels have a unified time correspondence in the energy distribution calculation and topology analysis process.

[0037] Furthermore, in step S2, injecting a controllable perturbation signal of a preset form during the energy storage converter test includes the following steps: The preset controllable perturbation signal forms include at least one of voltage perturbation signal, current perturbation signal, impedance perturbation signal and phase perturbation signal; The controllable perturbation signal is superimposed onto the DC-side circuit, AC-side circuit, control circuit, or grounding circuit corresponding to the energy storage converter; Record the injection parameters for each controllable perturbation signal, including the injection start time, duration, and signal amplitude parameters; The injected parameters are associated with and stored with the corresponding multi-parameter synchronization data sequences.

[0038] In step S2, establishing a time window centered on the injection time of each controllable perturbation signal, and extracting the synchronous acquisition data subsequence corresponding to the time window from the multi-parameter synchronous data sequence includes the following steps: The injection start time of the controllable perturbation signal is used as the reference time; The length of the first sampling interval is set before the reference time to form the pre-sampling interval; The length of the second sampling interval is set after the reference time to form the post-sampling interval; The pre-sampling interval and the post-sampling interval are spliced ​​together to form a complete time window; Extract the corresponding synchronously acquired data subsequence within the time window.

[0039] Specifically, the controllable perturbation signal is generated by the test control unit according to a preset test sequence. The test sequence uses event numbers as indexes and sequentially calls the voltage source, current source, variable impedance unit, or control phase modulation unit to generate the corresponding perturbation signal. The voltage perturbation signal manifests as a step-type or pulse-type voltage component superimposed on the bus voltage; the current perturbation signal manifests as a pulse-type or slowly varying current component superimposed in the output current loop; the impedance perturbation signal is achieved by switching controllable impedance branches with different resistance values; and the phase perturbation signal is achieved by introducing a phase offset in the control loop. All types of perturbation signals are triggered according to a unified event scheduling table, and the test control unit generates an event number upon triggering.

[0040] When the m-th controllable perturbation signal is triggered, its injection start time is denoted as . The duration is recorded as The amplitude parameter is denoted as The above parameters, together with the event number, constitute the description information of the perturbation event, and are transmitted to the upper-level processing unit for storage along with the synchronously acquired data. In the synchronously acquired data, any timestamp that meets the... All data samples are labeled as excitation interval data for this controllable perturbation event.

[0041] Around the injection start time Set the length before it to The preceding sampling interval, followed by a length of [value], is then set. The subsequent sampling intervals constitute the time window:

[0042] in, Indicates the length of the pre-sampling interval. This indicates the length of the post-sampling interval. Based on the timestamp index, the host processing unit extracts all sampling points that satisfy the inequality relationship from the multi-parameter synchronous data sequence under a unified time axis, forming a time window data subsequence corresponding to the m-th controllable perturbation event.

[0043] The time window data subsequence contains continuous sampling information before, during and after the injection of controllable perturbation signals, and establishes a correspondence with the event number, injection start time, duration and amplitude parameters, forming the basic data set for subsequent transient response calculation of the protection energy channel and integral calculation of energy proxy quantity.

[0044] Through the aforementioned process of generating, superimposing, recording event parameters, and constructing a time window centered on the injection start time, the synchronously acquired multi-parameter data establishes a clear correspondence with each perturbation event in the time dimension. This allows for subsequent calculation of energy proxy integrals on the data within the time window. At the same time, it can obtain the response information of each protective energy channel in the complete time period before and after the disturbance in units of perturbation events, providing a definite time domain boundary and a consistent data foundation for the construction of protective energy distribution ratio, protective energy fingerprint vector and protective energy topology weight matrix.

[0045] Furthermore, step S3 includes the following steps: The surge absorption branch, shutdown dissipation branch, filter energy storage branch, grounding discharge branch and control isolation branch in the energy storage converter are defined as independent protection energy channels. Assign a unique channel number to each protective energy channel; Establish a table showing the correspondence between protective energy channels and their corresponding hardware circuit components, connection nodes, and loop topologies; From the multi-parameter synchronous data subsequence within the time window, bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature change, and electromagnetic characteristics are extracted to form a multi-dimensional feature vector; For each protective energy channel, select the associated characteristic component based on its corresponding hardware circuit. The channel transient response sequence is obtained by performing a weighted combination operation on the feature components. Discrete integral operations are performed on the transient response sequence of the channel within a time window to obtain the energy proxy quantity of the corresponding protective energy channel.

[0046] Specifically, in the m-th time window constructed by S2 Within the system, the host processing unit reads the synchronously collected data from each IoT measurement node in a unified time index order, and performs sampling at each sampling moment. Constructing multidimensional feature vectors:

[0047] in, Indicates the bus voltage; Indicates the bus current; Indicates the rate of change of voltage; Indicates the rate of change of current; Indicates the grounding current; Indicates the grounding loop impedance; This indicates the change in device temperature between adjacent sampling times; Represents electromagnetic characteristic quantities.

[0048] For each protective energy channel Based on the electrical branch structure and device connection relationships corresponding to the channel within the energy storage converter, a set of feature components directly related to the energy transfer path of the channel is selected from the multi-dimensional feature vector to form the channel feature sub-vector:

[0049] in, Indicates protective energy channel The number of associated characteristic components, including at least one related to the channel voltage, current, rate of change, grounding parameters, temperature rise, or electromagnetic radiation characteristics.

[0050] Introduce a weight coefficient vector corresponding to the channel structure to the channel feature vector. ; and perform a weighted combination operation at each sampling time to obtain the protective energy channel. transient response sequence The weighting coefficients are determined by the corresponding device parameters, loop topology, and dimensional consistency rules of the channel, and are stored in the channel parameter table to ensure the comparability of different physical quantities in the combined operation.

[0051] After obtaining the channel transient response sequence, it is subjected to time window... Internal sampling period Discrete integration is performed to obtain the protective energy channel under the m-th controllable perturbation event. Energy proxy quantity:

[0052] in, It represents the scalar value formed by the accumulation of the transient response of the channel over time within the time window, and is used to characterize the overall response strength of the protective energy channel under the action of the perturbation event.

[0053] Through the aforementioned process of constructing multidimensional feature vectors, selecting channel-related feature components, weighting and combining them to form transient response sequences, and performing discrete integral calculations within a time window, the dynamic response of each protective energy channel under controllable perturbation events is converted into a single energy proxy, thereby providing a basis for subsequent analysis of the energy distribution ratio of each channel. The calculation of the protective energy fingerprint vector and the construction of the protective energy topological weight matrix provide a quantitative basis with a unified scale.

[0054] Furthermore, step S4 includes the following steps: The energy proxy quantities of each protective energy channel are uniformly processed to map negative values ​​to zero; Sum the energy proxy quantities of each mapped protective energy channel; Divide the energy proxy amount of each protective energy channel by the summation result to obtain the energy distribution ratio; The energy distribution ratios are arranged in the order of the channel numbers of the protective energy channels to form a protective energy fingerprint vector.

[0055] Specifically, after calculating the energy proxy for each protective energy channel in step S3, the set of energy proxy is obtained for the m-th controllable perturbation event. ;in, Indicates the total number of protective energy channels This represents the discrete integral result of the k-th protective energy channel within the time window. Since the transient response of the channels may contain changes in sign during weighted combination and integration, to ensure that the energy values ​​of different channels have a unified physical meaning and comparability, the energy proxy quantity of each channel is non-negated, and a sign unification mapping is performed according to the following rules: When When the value is zero, The original value is maintained, and the processed energy proxy amount is obtained. ; After obtaining the nonnegative energy proxy of all protective energy channels, sum them up to form the total energy proxy corresponding to this perturbation event: Based on this, the ratio of the nonnegated energy proxy of each protective energy channel to the total energy proxy is calculated to obtain the energy distribution ratio of each protective energy channel in this perturbation event: ;in, This represents the energy distribution ratio of the k-th protective energy channel, satisfying... According to the numbering order of the protective energy channels, the energy distribution ratio of each channel is arranged sequentially to form a protective energy fingerprint vector: The protective energy fingerprint vector records the relative energy proportion structure of each protective energy channel in each controllable perturbation event in the form of a fixed-dimensional vector, and stores it in a one-to-one correspondence with the perturbation event number, time window index and synchronously collected data.

[0056] Through the above-mentioned nonnegation, normalization, and vector formation process according to channel number order, the original protective energy channel energy proxy quantity, expressed in absolute terms, is transformed into an energy distribution ratio vector that satisfies probability distribution constraints. This provides a unified, fixed-dimensional, and comparable data representation for subsequent protective energy topology weight allocation, protective topology entropy calculation, and offset analysis based on vector difference.

[0057] Furthermore, step S5 includes the following steps: The protection devices, loop nodes, and connection nodes in the energy storage converter are abstracted as topology nodes; The protective energy channel is abstracted as a topological edge connecting the topological nodes; Establish a correspondence table between the topological edges and the channel numbers; Based on the energy distribution ratio in the protective energy fingerprint vector, weights are assigned to the corresponding topological edges; Construct a protective energy topological weight matrix by combining the order of topological nodes with the weights assigned to topological edges.

[0058] Specifically, based on the electrical structure diagram and protection circuit connection relationships of the energy storage converter, components and nodes with clear electrical connections, such as surge absorption devices, shutdown devices, filtering devices, grounding connection points, DC bus connection points, and control isolation units, are uniformly mapped into a set of topology nodes, and each topology node is assigned a unique node number. The energy transfer paths between topology nodes are abstracted based on protection energy channels, with each protection energy channel corresponding to one or more directed or undirected topology edges connecting topology nodes, and each topology edge is assigned an edge number. After establishing the topology nodes and topology edges, a correspondence table between topology edges and protection energy channel numbers is constructed. This correspondence table describes the node pairs or node sequences corresponding to each protection energy channel in the topology structure, thereby clarifying the energy transfer path in the protection circuit. For protection branches consisting of multiple devices connected in series or parallel, the branch is regarded as a combination edge of the same protection energy channel in the topology structure, and the mapping relationship between the combination edge and the channel number is recorded in the correspondence table.

[0059] After obtaining the protective energy fingerprint vector, the energy distribution ratio of each protective energy channel is read. Based on the correspondence between the topological edges and the protective energy channel numbers, the energy distribution ratio of each protective energy channel is allocated to the corresponding topological edge as its weight value. For a single topological edge corresponding to a single protective energy channel, the energy distribution ratio of that channel is directly assigned as the weight of the topological edge. For a single topological edge corresponding to multiple protective energy channels, the energy distribution ratios of multiple channels are weighted and summarized according to the allocation coefficients given in the correspondence table to form the weight value of the topological edge. After all topological edge weights are assigned, a protective energy topological weight matrix is ​​constructed according to the topological node numbers. The row and column indices of the matrix correspond to the topological node numbers, and the matrix elements represent the weight values ​​of the topological edges between nodes. For node pairs without direct connections, their corresponding matrix elements are set to zero. The resulting protective energy topological weight matrix fully describes the energy distribution relationship between nodes in the protective structure under the action of a single controllable perturbation event.

[0060] Through the aforementioned process of topological node abstraction, topological edge mapping, establishment of the correspondence between channels and edges, and weight assignment based on the protective energy fingerprint vector, the energy distribution ratio of the protective energy channels is mapped in matrix form to the topological structure of the protective loop, providing a basis for subsequent processing according to... Weights of each topological edge in the topological weight matrix of the protective energy Information entropy calculation provides structured input data, thereby enabling a quantitative expression of the distribution of protective energy in the loop topology.

[0061] Furthermore, in step S6, calculating the protective topology entropy based on the protective energy topology weight matrix includes the following steps: The weights of each topological edge in the protective energy topological weight matrix are normalized. The normalized topological edge weights are converted into a probability distribution form; Calculate the corresponding protection topology entropy based on the probability distribution form; Specifically, in step S5, the protective energy topology weight matrix corresponding to the m-th controllable perturbation event is constructed. ; where matrix elements Represents topology nodes With topology nodes The energy weight values ​​of the topological edges between them. The weight values ​​are obtained by topological mapping from the energy distribution ratio of the corresponding protective energy channel in the protective energy fingerprint vector.

[0062] To ensure that the weights of each topological edge satisfy the probability distribution constraints, normalization is performed on all non-zero topological edge weights in the protective energy topological weight matrix. Let the set of topological edges be... The normalization process involves summing the weights of all topological edges to obtain... The weight of each topological edge is then compared with the summation result to form a probabilistic weight:

[0063] in, This represents the topological edge under the m-th controllable perturbation event. The relative weight ratios among all protective energy topological edges satisfy the following... After obtaining the probabilistic weight set, it is calculated according to the definition of information entropy to obtain the protective topology entropy corresponding to the m-th controllable perturbation event:

[0064] in, A scalar value representing the dispersion of protective energy distribution in the topology. These are the probabilistic weights of the topological edges.

[0065] When the energy storage converter protection structure is in the baseline state, a set of baseline protection energy topology weight matrices is constructed based on multiple controllable perturbation events. For each baseline event, the baseline protection topology entropy is calculated according to the same process described above. Furthermore, the statistical average value of the baseline protection topology entropy is taken to obtain the baseline protection topology entropy. .

[0066] To obtain the protective topological entropy of the current perturbation event. and benchmark protection topology entropy Then, the difference operation is performed to form the protection topology entropy offset: The protective topology entropy offset, along with the protective energy fingerprint offset and the protective energy topology weight offset, are used as inputs for subsequent unified dimensional processing and fusion calculation.

[0067] Through the above-mentioned topology weight normalization, probabilistic processing and information entropy calculation process, the distribution state of protective energy in the topology is transformed into a single scalar form of protective topology entropy. The protective topology entropy offset is formed by the difference operation with the baseline protective topology entropy. This allows the changes in the energy distribution structure at the topology level in the protective loop to be characterized in a calculable and comparable numerical form, providing quantitative input for subsequent fusion calculations.

[0068] For the m-th controllable perturbation event, the protection energy fingerprint vector has been obtained. ; and the baseline protection energy fingerprint vector: Where C represents the total number of protective energy channels. The host processing unit performs a channel-by-channel differential operation on both according to the channel number order to obtain the protective energy fingerprint offset. The k-th component of the offset vector This represents the change in the energy distribution ratio of the k-th protective energy channel relative to the baseline state under the current perturbation event.

[0069] Meanwhile, for the protective energy topology weight matrix constructed in step S5 and the corresponding baseline protection energy topology weight matrix The host processing unit performs element-wise difference operations on the matrix elements according to the topology node numbering order to form the protection energy topology weight offset. ; where matrix elements Represents topology nodes With topology nodes The change in energy weights relative to the baseline state.

[0070] Furthermore, step S7 includes the following steps: The protective topology entropy offset, protective energy fingerprint offset, and protective energy topology weight offset are processed to have unified dimensions. The processed protection topology entropy offset, protection energy fingerprint offset, and protection energy topology weight offset are combined according to a preset fusion rule to generate protection status discrimination input. The protection status determination result is obtained based on the input quantity of the protection status determination.

[0071] Specifically, the protective topology entropy offset is obtained in step S6. Then, the protection topology entropy offset and the protection energy fingerprint offset are... and protective energy topology weight offset The data is uniformly input to the dimensional processing unit. The dimensional processing unit performs standardization processing on data of different dimensions according to preset scaling rules, including amplitude normalization, interval mapping and numerical clipping of vector components and matrix elements, so that the three types of offsets are comparable within the same numerical range.

[0072] After unifying the dimensions, the processed protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset are combined according to the preset fusion rules. The fusion rules include weighted summation or vector concatenation of each offset to form a joint feature vector, and organizing it into a data structure for protection state discrimination input based on the event number. This structure is used to characterize the comprehensive changes in the protection energy distribution structure, topology weight structure, and overall dispersion relative to the baseline state under the current perturbation event.

[0073] Through the above-mentioned channel-by-channel differential, element-by-element differential, unified dimension processing and fusion combination process, the distribution changes of protection energy at the channel level, the weight changes at the protection loop topology level, and the changes in the overall energy distribution dispersion are uniformly mapped into protection status discrimination input quantities. This enables the protection structure status during energy storage converter testing to be centrally represented in vector and matrix form, providing a quantitative basis for the formation of protection status discrimination results based on fingerprint offset, topology weight offset, and topology entropy offset.

[0074] Example 2 refer to Figure 2 This embodiment provides an IoT-based energy storage converter test protection status monitoring system to implement the IoT-based energy storage converter test protection status monitoring method described in Embodiment 1, including: The multi-parameter synchronous data acquisition module is used to construct a synchronous acquisition network composed of multiple IoT measurement nodes. During the testing of the energy storage converter, it acquires synchronous acquisition data such as bus voltage, bus current, voltage change rate, current change rate, grounding current, grounding loop impedance, device temperature and electromagnetic characteristic quantities. The module then performs time synchronization marking on the acquired synchronous acquisition data to obtain a multi-parameter synchronous data sequence. The time window establishment module is used to inject a preset form of controllable perturbation signal during the testing of the energy storage converter, establish a time window with the injection time of each controllable perturbation signal as the center, and extract the synchronous acquisition data subsequence corresponding to the time window from the multi-parameter synchronous data sequence. The protective energy proxy quantity acquisition unit is used to define the protective energy channel according to the hardware circuit of the energy storage converter, and calculate the energy proxy quantity corresponding to each protective energy channel based on the synchronously acquired data subsequence within the time window. The protective energy fingerprint vector acquisition module is used to perform nonnegation and normalization processing on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. The protective energy topology weight matrix module is used to establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and to construct the protective energy topology weight matrix according to the energy distribution ratio. The offset calculation module is used to calculate the protection topology entropy based on the protection energy topology weight matrix, and to calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix and the protection topology entropy and their respective reference data, so as to obtain the protection energy fingerprint offset, the protection energy topology weight offset and the protection topology entropy offset respectively. The protection status discrimination module is used to fuse the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, and output the corresponding protection status discrimination result.

[0075] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0076] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the protection status of energy storage converter tests based on the Internet of Things, characterized in that, Includes the following steps: S1. Construct a synchronous acquisition network composed of multiple IoT measurement nodes to acquire bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature and electromagnetic characteristic quantities during the energy storage converter test to obtain synchronous acquisition data, and perform time synchronization marking on the obtained synchronous acquisition data to obtain a multi-parameter synchronous data sequence. S2. During the testing of the energy storage converter, a controllable perturbation signal of a preset form is injected. A time window is established with the injection time of the controllable perturbation signal as the center, and the synchronous acquisition data subsequence corresponding to the time window is extracted from the multi-parameter synchronous data sequence. S3. Define the protection energy channels according to the hardware circuit of the energy storage converter, and calculate the energy proxy amount corresponding to each protection energy channel within the time window based on the synchronously acquired data subsequence. S4. Perform nonnegation and normalization on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. S5. Establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and construct the protective energy topology weight matrix according to the energy distribution ratio. S6. Calculate the protection topology entropy based on the protection energy topology weight matrix, and calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix, and the protection topology entropy and their respective reference data to obtain the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, respectively. S7. The protection energy fingerprint offset, protection energy topology weight offset, and protection topology entropy offset are fused and processed to output the corresponding protection status judgment result.

2. The method for monitoring the protection status of energy storage converter based on the Internet of Things according to claim 1, characterized in that, In step S1, the step of performing time synchronization marking on the obtained synchronously acquired data to obtain a multi-parameter synchronous data sequence includes: Configure a unified time reference source for each of the IoT measurement nodes; Timestamps are assigned to the bus voltage sampling channel, bus current sampling channel, voltage change rate calculation channel, current change rate calculation channel, ground current sampling channel, ground loop impedance measurement channel, device temperature sampling channel, and electromagnetic characteristic quantity sampling channel of each IoT measurement node, so that the obtained synchronous acquisition data has timestamps. Upload the timestamped synchronously collected data to the host processing unit; The data from different IoT measurement nodes are rearranged and aligned according to the timestamp order to form a multi-parameter synchronized data sequence under a unified time axis.

3. The method for monitoring the protection status of energy storage converter based on the Internet of Things according to claim 2, characterized in that, The process of injecting a controllable perturbation signal of a preset form during the testing of the energy storage converter includes the following steps: The preset controllable perturbation signal forms include at least one of voltage perturbation signal, current perturbation signal, impedance perturbation signal and phase perturbation signal; The controllable perturbation signal is superimposed onto the DC-side circuit, AC-side circuit, control circuit, or grounding circuit corresponding to the energy storage converter; Record the injection parameters for each controllable perturbation signal, including the injection start time, duration, and signal amplitude parameters; The injected parameters are associated with and stored with the corresponding multi-parameter synchronization data sequences.

4. The method for monitoring the protection status of energy storage converter tests based on the Internet of Things according to claim 3, characterized in that, The step of establishing a time window centered on the injection time of each controllable perturbation signal and extracting the synchronous acquisition data subsequence corresponding to the time window from the multi-parameter synchronous data sequence includes the following steps: The injection start time of the controllable perturbation signal is used as the reference time; A first sampling interval length is set before the reference time to form a pre-sampling interval; A second sampling interval length is set after the reference time to form a post-sampling interval; The pre-sampling interval and the post-sampling interval are spliced ​​together to form a complete time window; Data corresponding to the time window is extracted from the multi-parameter synchronous data sequence to form a synchronous acquisition data sub-sequence.

5. The method for monitoring the protection status of energy storage converter tests based on the Internet of Things according to claim 4, characterized in that, Step S3 includes the following steps: The surge absorption branch, shutdown dissipation branch, filter energy storage branch, grounding discharge branch and control isolation branch in the energy storage converter are defined as independent protection energy channels. Assign a unique channel number to each protective energy channel; Establish a table showing the correspondence between protective energy channels and their corresponding hardware circuit components, connection nodes, and loop topologies; From the multi-parameter synchronous data subsequence within the time window, bus voltage, bus current, voltage change rate, current change rate, ground current, grounding loop impedance, device temperature change, and electromagnetic characteristics are extracted to form a multi-dimensional feature vector; For each protective energy channel, select the associated characteristic component based on its corresponding hardware circuit. The channel transient response sequence is obtained by performing a weighted combination operation on the feature components. Discrete integral operations are performed on the transient response sequence of the channel within a time window to obtain the energy proxy quantity of the corresponding protective energy channel.

6. The method for monitoring the protection status of energy storage converter tests based on the Internet of Things according to claim 5, characterized in that, Step S4 includes the following steps: The energy proxy quantities of each protective energy channel are uniformly processed to map negative values ​​to zero; The summation result is obtained by summing the energy proxy quantities of each mapped protective energy channel; Divide the energy proxy amount of each protective energy channel by the summation result to obtain the energy distribution ratio; The energy distribution ratios are arranged in the order of the channel numbers of the protective energy channels to form a protective energy fingerprint vector.

7. The method for monitoring the protection status of energy storage converter tests based on the Internet of Things according to claim 6, characterized in that, Step S5 includes the following steps: The protection devices, loop nodes, and connection nodes in the energy storage converter are abstracted as topology nodes; The protective energy channel is abstracted as a topological edge connecting the topological nodes; Establish a correspondence table between the topological edges and the channel numbers; Based on the energy distribution ratio in the protective energy fingerprint vector, weights are assigned to the corresponding topological edges; Construct a protective energy topological weight matrix by combining the order of topological nodes with the weights assigned to topological edges.

8. The method for monitoring the protection status of energy storage converter tests based on the Internet of Things according to claim 7, characterized in that, The calculation of the protection topology entropy based on the protection energy topology weight matrix includes the following steps: The weights of each topological edge in the protective energy topological weight matrix are normalized. The normalized topological edge weights are converted into a probability distribution form; The corresponding protective topology entropy is calculated based on the probability distribution.

9. The method for monitoring the protection status of energy storage converter based on the Internet of Things according to claim 1, characterized in that, Step S7 includes the following steps: The protective topology entropy offset, protective energy fingerprint offset, and protective energy topology weight offset are processed to have unified dimensions. The processed protection topology entropy offset, protection energy fingerprint offset, and protection energy topology weight offset are combined according to a preset fusion rule to generate protection status discrimination input. The protection status determination result is obtained based on the input quantity of the protection status determination.

10. An IoT-based energy storage converter test protection status monitoring system, characterized in that, The method for monitoring the protection status of energy storage converter tests based on the Internet of Things as described in any one of claims 1 to 9 includes: The multi-parameter synchronous data acquisition module is used to construct a synchronous acquisition network composed of multiple IoT measurement nodes. During the testing of the energy storage converter, it acquires synchronous acquisition data such as bus voltage, bus current, voltage change rate, current change rate, grounding current, grounding loop impedance, device temperature and electromagnetic characteristic quantities. The module then performs time synchronization marking on the acquired synchronous acquisition data to obtain a multi-parameter synchronous data sequence. The time window establishment module is used to inject a preset form of controllable perturbation signal during the testing of the energy storage converter, establish a time window with the injection time of each controllable perturbation signal as the center, and extract the synchronous acquisition data subsequence corresponding to the time window from the multi-parameter synchronous data sequence. The protective energy proxy quantity acquisition unit is used to define the protective energy channel according to the hardware circuit of the energy storage converter, and calculate the energy proxy quantity corresponding to each protective energy channel based on the synchronously acquired data subsequence within the time window. The protective energy fingerprint vector acquisition module is used to perform nonnegation and normalization processing on the energy proxy quantity to obtain the energy distribution ratio of each protective energy channel, and sort the energy distribution ratios to form a protective energy fingerprint vector. The protective energy topology weight matrix module is used to establish the structural mapping relationship between the protective energy channel and the protective devices and loop nodes in the energy storage converter, and to construct the protective energy topology weight matrix according to the energy distribution ratio. The offset calculation module is used to calculate the protection topology entropy based on the protection energy topology weight matrix, and to calculate the offset between the protection energy fingerprint vector, the protection energy topology weight matrix and the protection topology entropy and their respective reference data, so as to obtain the protection energy fingerprint offset, the protection energy topology weight offset and the protection topology entropy offset respectively. The protection status discrimination module is used to fuse the protection energy fingerprint offset, the protection energy topology weight offset, and the protection topology entropy offset, and output the corresponding protection status discrimination result.

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