Energy storage PCS converter test platform and method

Abstract

The invention discloses an energy storage PCS converter test platform and method, and relates to the technical field of converter test, and the platform comprises a data acquisition module which is used for building a test platform and deploying a sensor to collect PCS converter test data and historical test data; the dynamic test module is used for selecting test parameters according to historical test data and applying dynamic disturbance to test the PCS converter; the fault analysis module is used for constructing a fault analysis model to analyze the operation state of the PCS converter; and the display and storage module is used for displaying the fault analysis result and storing the test data. According to the method, the objective function is constructed, the test parameters are selected by using the genetic algorithm, accurate dynamic performance test is realized, dynamic interference is applied to the test parameters, dynamic response characteristics of the PCS converter under complex working conditions are truly reflected, the accuracy and authenticity of test results are improved, and workers are effectively helped to know the performance of the PCS converter.

Description

Technical Field

[0001] The present invention relates to the technical field of converter testing, and in particular to a testing platform and method for an energy storage PCS converter. Background Art

[0002] With the rapid development of new energy technologies, energy storage systems have become an indispensable and important part of modern power systems. In energy storage systems, energy storage PCS (Power Conversion System) converters serve as an important bridge connecting energy storage equipment and power grids. Their performance directly affects the stability and reliability of power systems. The main functions of energy storage PCS converters are to achieve bidirectional energy flow, ensure power quality and support power grid regulation, such as frequency regulation and reactive power compensation. However, due to the complex working environment of energy storage PCS converters and the need to operate under dynamic conditions, the testing technology of their performance and stability has gradually become a research hotspot. At present, the testing methods for energy storage PCS converters mainly include static performance testing and dynamic performance testing. Static testing usually focuses on the efficiency, power output capacity and harmonic suppression capability of the converter, while dynamic testing pays more attention to the response performance and stability under simulated dynamic disturbance or fault conditions. However, the existing testing technology still has many shortcomings in dealing with complex dynamic working conditions. The existing technology lacks real-time and intelligent data analysis methods, cannot make full use of historical test data for test parameter optimization, and lacks a comprehensive dynamic signal application strategy, making it difficult to truly reflect the dynamic response characteristics of energy storage PCS converters under complex working conditions. Summary of the invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the present invention provides a test platform and method for an energy storage PCS converter, which solves the problem that the prior art cannot fully utilize historical test data for test parameter optimization and lacks a comprehensive dynamic signal application strategy, making it difficult to truly reflect the dynamic response characteristics of the energy storage PCS converter under complex working conditions.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides an energy storage PCS converter test platform, which comprises: Data acquisition module, used to build a test platform and deploy sensors to collect PCS converter test data and historical test data; Dynamic test module, used to select test parameters based on historical test data and apply dynamic disturbances to perform PCS converter tests; Fault analysis module, used to build a fault analysis model to analyze the operating status of the PCS converter; The display and storage module is used to display the fault analysis results and store the test data.

[0006] As a preferred solution of the energy storage PCS inverter test platform described in the present invention, wherein: the building of the test platform and the deployment of sensors to collect PCS inverter test data and historical test data refer to building a standardized test platform through test equipment, setting the sampling frequency and using standard signals for calibration, deploying sensors on the test platform to collect PCS inverter test data, and obtaining PCS inverter historical test data through query.

[0007] As a preferred solution of the energy storage PCS converter test platform described in the present invention, wherein: the selection of test parameters according to historical test data refers to extracting historical test parameters and historical PCS converter response parameters from the PCS converter historical test data, extracting the test parameter range from the PCS converter specification, and generating a test condition point set based on the historical test parameters. ; The Latin hypercube sampling method is used to select the test condition point set Extract test points to generate a test point set , and extract the historical PCS converter response parameters corresponding to the test points, and build the objective function J based on the historical PCS converter response parameters: ; in For test time, is the historical test output power of the PCS converter at time t, is the rated input power of the PCS converter, is the output power change of historical tests, is the time difference of change, is the hth harmonic power at time t, H is the harmonic order, , as well as is the weight factor; The test points are collected Each test point and its corresponding historical PCS converter response parameter are taken as genetic individuals, all genetic individuals form an initial population, the objective function value of each test point is defined as the fitness value, and the individual with the lowest fitness value is selected from the initial population for crossover mutation operation to generate the next generation population. The iterative operation is repeated and stopped when the fitness value converges. The genetic individual with the lowest fitness value in the population after stopping the iteration is output as the optimal individual, and the test parameters in the optimal genetic individual are extracted as the preferred test parameters.

[0008] As a preferred solution of the energy storage PCS converter test platform of the present invention, wherein: the applying dynamic disturbance to perform PCS converter test refers to extracting the resistance, inductance and capacitance parameters of the LCL filter of the PCS converter to construct the filter state matrix A and the input matrix B: ; in , and C are the resistance, inductance and capacitance of the LCL filter respectively; The optimal test parameters are combined to form a state vector x, and the state space model of the disturbance observer is constructed through the state matrix A and the input matrix B: ; in is the feedback matrix, D is the output matrix, u is the disturbance signal, and y is the output signal; Discretize the state-space model: ; in is the state variable at discrete time k, is the disturbance signal at discrete time k, is the output signal at discrete time k, is the state variable at discrete time k+1, G is the discrete state transfer matrix, ; The disturbance observer calculates the dynamic disturbance signal through the discretized state variables. : ; Calculate the LCL filter impedance Z based on the LCL filter resistance, inductance and capacitance parameters; The dynamic disturbance signal obtained by the disturbance observer The dynamic disturbance signal is generated by superposition of dynamic virtual network impedance : ; in is the input current, N is the number of online inverters in the PCS converter; From the integrated dynamic disturbance signal The voltage disturbance term, the frequency disturbance term and the power disturbance term are extracted and respectively added to the preferred test parameters to form the final test parameters, the PCS converter is tested based on the final test parameters, and the PCS converter response parameters are collected; Calculate instantaneous output power based on PCS converter response parameters The power change rate e is calculated, the output voltage and current in the PCS converter response parameters are converted into frequency domain signals by fast Fourier transform, and the harmonic components and fundamental components are extracted from the frequency domain signals. The total harmonic distortion THD of the output signal is calculated based on the harmonic components and fundamental components: ; in is the voltage of the hth harmonic, is the fundamental voltage; Simultaneous calculation of the resonant frequency of the LCL filter ; Comprehensive PCS converter power change rate e, total harmonic distortion THD and resonance frequency Output as test result.

[0009] As a preferred solution of the energy storage PCS converter test platform of the present invention, wherein: the construction of a fault analysis model to analyze the operating state of the PCS converter refers to constructing a fault analysis model through a convolutional neural network, setting the model input as the test result, the model output as the operating state of the PCS converter, iteratively training the fault analysis model using training data, and optimizing the model parameters through a loss function and an Adam optimizer; The test results are input into the trained fault analysis model to obtain the operating status of the PCS converter.

[0010] As a preferred solution of the energy storage PCS converter test platform described in the present invention, the display of fault analysis results refers to the synchronous visual display of the PCS converter operating status and the test results, and providing maintenance suggestions to the staff according to the PCS converter operating status.

[0011] As a preferred solution of the energy storage PCS converter test platform described in the present invention, the storage of test data refers to storing the test data and test results into test records after the test is completed, sorting the test records by timestamp, and regularly comparing the test records with historical test records to evaluate the reliability of the test records.

[0012] In a second aspect, the present invention provides a method for testing an energy storage PCS converter, comprising: Build a test platform and deploy sensors to collect PCS converter test data and historical test data; Select test parameters based on historical test data and apply dynamic disturbances to perform PCS converter tests; Construct a fault analysis model to analyze the operating status of the PCS converter; Display the fault analysis results and store the test data.

[0013] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the energy storage PCS converter test platform as described in the first aspect of the present invention is implemented.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the energy storage PCS converter test platform as described in the first aspect of the present invention is implemented.

[0015] The beneficial effects of the present invention are as follows: the present invention realizes accurate dynamic performance testing by constructing an objective function and selecting test parameters using a genetic algorithm, and applies dynamic interference in the test parameters to truly reflect the dynamic response characteristics of the PCS converter under complex working conditions, thereby improving the accuracy and authenticity of the test results and effectively helping staff understand the performance of the PCS converter. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0017] Figure 1 This is a structural diagram of the energy storage PCS converter test platform in Example 1.

[0018] Figure 2 This is a flow chart of the energy storage PCS converter testing method in Example 1. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0022] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides an energy storage PCS converter test platform, comprising the following steps: S1, data acquisition module, used to build a test platform and deploy sensors to collect PCS converter test data and historical test data; Building a test platform and deploying sensors to collect PCS converter test data and historical test data refers to building a standardized test platform through test equipment, setting the sampling frequency and using standard signals for calibration, deploying sensors on the test platform to collect PCS converter test data, and obtaining PCS converter historical test data through query.

[0023] Building a standardized test platform ensures the uniformity of the test environment, especially in the process of applying dynamic disturbance signals and collecting data. The standardized test platform can eliminate errors caused by environmental differences (such as hardware performance differences or signal interference). The deployment of sensors enables the system to obtain dynamic parameters such as voltage, current, power, and temperature of the PCS converter in real time during operation. These parameters provide a high-precision data source for dynamic disturbance testing and fault analysis. By introducing historical test data, the present invention can optimize the current test parameter selection and dynamic disturbance design based on previous test results. The reference of historical data makes the test more accurate and controllable, reduces repetitive testing and resource waste, and by setting a reasonable sampling frequency, it can ensure that the acquisition of dynamic signals has sufficient time resolution, thereby accurately capturing the operating details of the PCS converter under dynamic disturbance.

[0024] S2, dynamic test module, used to select test parameters according to historical test data and apply dynamic disturbance to perform PCS converter test; Specifically, selecting test parameters according to historical test data refers to extracting historical test parameters and historical PCS converter response parameters from historical test data of the PCS converter, wherein the historical test parameters include historical test input voltage, historical test input frequency, and historical test input power, and the historical PCS converter response parameter refers to historical test output power, extracting a test parameter range from the PCS converter specification, including rated input power, input voltage range, and input frequency range, and generating a test condition point set based on the historical test parameters. : ; in is the PCS converter input voltage range, Input frequency range for PCS converter, is the rated input power of the PCS converter, is the test input voltage, f is the test input frequency, Input power for testing; The Latin hypercube sampling method is used to select the test condition point set Extract test points to generate a test point set ,Latin hypercube sampling is an efficient sampling method, which is used to evenly cover the multidimensional variable space, ensure the uniformity and representativeness of the test point distribution, and extract the historical PCS converter response parameters corresponding to the test points. The objective function J is constructed based on the historical PCS converter response parameters: ; in For test time, is the historical test output power of the PCS converter at time t, is the rated input power of the PCS converter, is the output power change of historical tests, is the time difference of change, is the hth harmonic power at time t, H is the harmonic order, , as well as is the weight factor, which is allocated according to the actual test requirements; The test points are collected Each test point and its corresponding historical PCS converter response parameter are taken as genetic individuals, all genetic individuals form an initial population, the objective function value of each test point is defined as the fitness value, and the individual with the lowest fitness value is selected from the initial population for crossover mutation operation to generate the next generation population. The iterative operation is repeated and stopped when the fitness value converges. The genetic individual with the lowest fitness value in the population after stopping the iteration is output as the optimal individual, and the test parameters in the optimal genetic individual are extracted as the preferred test parameters.

[0025] The combination method based on historical data and specifications not only avoids the generation of invalid test points, but also ensures that the test conditions are representative, reducing the blindness of test design. The introduction of Latin hypercube sampling method overcomes the defect of uneven random sampling distribution. Under the condition of limited test resources, a set of test points with efficient coverage can be generated to avoid excessive testing or neglect of certain areas. Power fluctuation, harmonic components and test efficiency are used as comprehensive optimization goals, and the priorities of different goals are adjusted by weight factors. Compared with the single-objective optimization method, the construction of this multi-objective function is more comprehensive and can more accurately reflect the dynamic characteristics of the PCS converter. By introducing the adjustment mechanism of harmonic power and weight factors, the practicality of the objective function and the accuracy of the test results are significantly improved. The introduction of genetic algorithm, combined with the objective function, can screen out the optimal test parameters in an intelligent optimization manner. Compared with the traditional exhaustive search or empirical selection method, the genetic algorithm can quickly converge to the global optimal solution, significantly improving the optimization efficiency.

[0026] Furthermore, applying dynamic disturbance to test the PCS converter means extracting the resistance, inductance and capacitance parameters of the LCL filter of the PCS converter to construct the filter state matrix A and input matrix B: ; in , and C are the resistance, inductance, and capacitance of the LCL filter, respectively, obtained from the PCS converter equipment specifications; The state matrix A describes the internal dynamic behavior of the system, and the input matrix B is used to describe how external input affects the system state. The state matrix is ​​constructed from the filter parameters (resistance, inductance and capacitance), so that the model is closely integrated with the actual device characteristics, ensuring the physical authenticity and calculation accuracy of the dynamic disturbance signal; The optimal test parameters are combined to form a state vector x, and the state space model of the disturbance observer is constructed through the state matrix A and the input matrix B: ; in is the feedback matrix, which is used to correct the observation error and is designed according to the stability condition of the discrete system. For example, the gain value that satisfies the feedback stability principle is selected. D is the output matrix, which is used to associate the state vector with the observable signal. , u is the disturbance signal, corresponding to the state vector content, initially set to zero, and corrected by the next disturbance superposition model, y is the output signal, obtained by real-time acquisition of voltage and current; Discretize the state-space model: ; in is the state variable at discrete time k, is the disturbance signal at discrete time k, is the output signal at discrete time k, is the state variable at discrete time k+1, G is the discrete state transfer matrix, ; Discretization converts the state space model in the continuous time domain into a discrete time domain model, making it suitable for real-time calculations in digital control systems. The discretization process retains the dynamic characteristics of the continuous model while being compatible with the computing requirements of the digital test system, ensuring the applicability of the model. The disturbance observer calculates the dynamic disturbance signal through the discretized state variables. : ; The generation of dynamic disturbance signals is achieved by calculating state variables in real time through the disturbance observer, combining filter parameters and dynamic virtual network impedance to form a more complex dynamic signal. The disturbance observer dynamically corrects the state error, so that the disturbance signal can adapt to the changes in the test environment in real time. This real-time and adaptive nature is not available in traditional methods. Calculate the LCL filter impedance Z based on the LCL filter resistance, inductance and capacitance parameters: ; Where j is an imaginary singular number, is the angular frequency; The dynamic disturbance signal obtained by the disturbance observer The dynamic disturbance signal is generated by superposition of dynamic virtual network impedance : ; in is the input current, obtained through real-time sampling, and N is the number of online inverters in the PCS converter; The comprehensive dynamic disturbance signal superimposes the voltage, frequency and power disturbance items and extracts them as the final test parameters, ensuring the comprehensiveness of the test process. By dynamically superimposing voltage, frequency and power disturbances, more complex grid conditions can be simulated during the test process, and the dynamic performance of the PCS converter can be fully evaluated. From the integrated dynamic disturbance signal The voltage disturbance term, the frequency disturbance term and the power disturbance term are extracted and respectively added to the preferred test parameters to form the final test parameters, the PCS converter is tested based on the final test parameters, and the PCS converter response parameters are collected; Calculate instantaneous output power based on PCS converter response parameters The power change rate e is calculated, the output voltage and current in the PCS converter response parameters are converted into frequency domain signals by fast Fourier transform, and the harmonic components and fundamental components are extracted from the frequency domain signals. The total harmonic distortion THD of the output signal is calculated based on the harmonic components and fundamental components: ; in is the voltage of the hth harmonic, is the fundamental voltage; Simultaneous calculation of the resonant frequency of the LCL filter : ; in is the grid side filter inductor; Comprehensive PCS converter power change rate e, total harmonic distortion THD and resonance frequency Output as test result.

[0027] The dynamic performance (power change rate), signal quality (THD) and stability (resonant frequency) are comprehensively considered to ensure that the test results can reflect the all-round characteristics of the equipment. The LCL filter parameters and dynamic disturbance model are closely combined, and the real-time, adaptability and comprehensiveness are fully considered, which significantly improves the scientificity and practicality of the test.

[0028] S3, a fault analysis module, used to construct a fault analysis model to analyze the operating status of the PCS converter; Specifically, building a fault analysis model to analyze the operating state of the PCS converter refers to building a fault analysis model through a convolutional neural network, setting the model input as the test result, the model output as the operating state of the PCS converter, iteratively training the fault analysis model using training data, and optimizing the model parameters through a loss function and an Adam optimizer; The test results are input into the trained fault analysis model to obtain the operating status of the PCS converter.

[0029] CNN uses convolution kernels to extract high-order features in the local receptive field of input data. It has good automation characteristics and generalization capabilities. Through multi-layer convolution operations, the model can gradually extract features from low-order to high-order, thereby deeply analyzing the operating status of the PCS converter. The input is the test results (including multi-dimensional parameters) and the output is the operating status (specific classification). This design not only meets the actual needs of the problem, but also makes full use of the feature extraction capabilities of CNN to extract fault features from multi-dimensional test results. By directly inputting test results and outputting operating status, the complex process of manual analysis and classification is eliminated, and efficient and automatic diagnosis is achieved.

[0030] S4, a display and storage module, used to display the fault analysis results and store the test data; Specifically, displaying the fault analysis results means visually displaying the PCS converter operating status and the test results synchronously, and providing maintenance suggestions to the staff according to the PCS converter operating status.

[0031] Furthermore, storing the test data means generating test records for storage of the test data and test results after the test is completed, sorting the test records by timestamp, and regularly comparing the test records with historical test records to evaluate the reliability of the test records, which can be analyzed and compared through artificial intelligence.

[0032] This embodiment also provides a method for testing an energy storage PCS converter, including: Build a test platform and deploy sensors to collect PCS converter test data and historical test data; Select test parameters based on historical test data and apply dynamic disturbances to perform PCS converter tests; Construct a fault analysis model to analyze the operating status of the PCS converter; Display the fault analysis results and store the test data.

[0033] This embodiment also provides a computer device, which is suitable for the case of an energy storage PCS converter test platform, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the energy storage PCS converter test platform proposed in the above embodiment.

[0034] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0035] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the energy storage PCS converter test platform proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0036] In summary, the present invention realizes accurate dynamic performance testing by constructing an objective function and using a genetic algorithm to select test parameters. Dynamic interference is applied to the test parameters to truly reflect the dynamic response characteristics of the PCS converter under complex working conditions, thereby improving the accuracy and authenticity of the test results and effectively helping staff understand the performance of the PCS converter.

[0037] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An energy storage PCS converter test platform, characterized by: include, Data acquisition module, used to build a test platform and deploy sensors to collect PCS converter test data and historical test data; Dynamic test module, used to select test parameters based on historical test data and apply dynamic disturbances to perform PCS converter tests; Fault analysis module, used to build a fault analysis model to analyze the operating status of the PCS converter; The display and storage module is used to display the fault analysis results and store the test data.

2. The energy storage PCS converter test platform according to claim 1, characterized in that: The said building of a test platform and deploying sensors to collect PCS converter test data and historical test data refers to building a standardized test platform through test equipment, setting a sampling frequency and calibrating with a standard signal, deploying sensors on the test platform to collect PCS converter test data, and obtaining PCS converter historical test data through query.

3. The energy storage PCS converter test platform according to claim 2, characterized in that: The selecting of test parameters according to historical test data refers to extracting historical test parameters and historical PCS converter response parameters from historical test data of the PCS converter, extracting test parameter ranges from the PCS converter specification, and generating a test condition point set based on the historical test parameters. ; The Latin hypercube sampling method is used to select the test condition point set Extract test points to generate a test point set , and extract the historical PCS converter response parameters corresponding to the test points, and build the objective function J based on the historical PCS converter response parameters: ； in For test time, is the historical test output power of the PCS converter at time t, is the rated input power of the PCS converter, is the output power change of historical tests, is the time difference of change, is the hth harmonic power at time t, H is the harmonic order, , as well as is the weight factor; The test points are collected Each test point and its corresponding historical PCS converter response parameter are taken as genetic individuals, all genetic individuals form an initial population, the objective function value of each test point is defined as the fitness value, and the individual with the lowest fitness value is selected from the initial population for crossover mutation operation to generate the next generation population. The iterative operation is repeated and stopped when the fitness value converges. The genetic individual with the lowest fitness value in the population after stopping the iteration is output as the optimal individual, and the test parameters in the optimal genetic individual are extracted as the preferred test parameters.

4. The energy storage PCS converter test platform according to claim 3, characterized in that: The applying dynamic disturbance to test the PCS converter refers to extracting the resistance, inductance and capacitance parameters of the LCL filter of the PCS converter to construct the filter state matrix A and the input matrix B: ； in , and C are the resistance, inductance and capacitance of the LCL filter respectively; The optimal test parameters are combined to form a state vector x, and the state space model of the disturbance observer is constructed through the state matrix A and the input matrix B: ； in is the feedback matrix, D is the output matrix, u is the disturbance signal, and y is the output signal; Discretize the state-space model: ； in is the state variable at discrete time k, is the disturbance signal at discrete time k, is the output signal at discrete time k, is the state variable at discrete time k+1, G is the discrete state transfer matrix, ; The disturbance observer calculates the dynamic disturbance signal through the discretized state variables. : ； Calculate the LCL filter impedance Z based on the LCL filter resistance, inductance and capacitance parameters; The dynamic disturbance signal obtained by the disturbance observer The dynamic disturbance signal is generated by superposition of dynamic virtual network impedance : ； in is the input current, N is the number of online inverters in the PCS converter; From the integrated dynamic disturbance signal The voltage disturbance term, the frequency disturbance term and the power disturbance term are extracted and respectively added to the preferred test parameters to form the final test parameters, the PCS converter is tested based on the final test parameters, and the PCS converter response parameters are collected; Calculate instantaneous output power based on PCS converter response parameters The power change rate e is calculated, the output voltage and current in the PCS converter response parameters are converted into frequency domain signals by fast Fourier transform, and the harmonic components and fundamental components are extracted from the frequency domain signals. The total harmonic distortion THD of the output signal is calculated based on the harmonic components and fundamental components: ； in is the voltage of the hth harmonic, is the fundamental voltage; Simultaneous calculation of the resonant frequency of the LCL filter ; Comprehensive PCS converter power change rate e, total harmonic distortion THD and resonance frequency Output as test result.

5. The energy storage PCS converter test platform according to claim 4, characterized in that: The constructing of the fault analysis model to analyze the operating state of the PCS converter refers to constructing the fault analysis model through a convolutional neural network, setting the model input as the test result, the model output as the operating state of the PCS converter, iteratively training the fault analysis model using training data, and optimizing the model parameters through a loss function and an Adam optimizer; The test results are input into the trained fault analysis model to obtain the operating status of the PCS converter.

6. The energy storage PCS converter test platform according to claim 5, characterized in that: The display of the fault analysis results refers to synchronously visually displaying the operating status of the PCS converter and the test results, and providing maintenance suggestions to the staff according to the operating status of the PCS converter.

7. The energy storage PCS converter test platform according to claim 6, characterized in that: The storing of the test data refers to storing the test data and the test results as test records after the test is completed, sorting the test records by timestamp, and regularly comparing the test records with historical test records to evaluate the reliability of the test records.

8. A method for testing an energy storage PCS converter, based on the energy storage PCS converter testing platform according to any one of claims 1 to 7, characterized in that: include, Build a test platform and deploy sensors to collect PCS converter test data and historical test data; Select test parameters based on historical test data and apply dynamic disturbances to perform PCS converter tests; Construct a fault analysis model to analyze the operating status of the PCS converter; Display the fault analysis results and store the test data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the energy storage PCS converter test platform described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the energy storage PCS converter test platform described in any one of claims 1 to 7 are implemented.

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