Method and system for parameter checking of network-constructed energy storage electromechanical transient simulation model

Abstract

The application discloses a kind of for network type energy storage electromechanical transient simulation model parameter checking method and system, belong to electromechanical transient simulation technical field.The method of the present application comprises: the structure of the network type energy storage electromechanical transient simulation model of being determined to be built;According to the structure of the network type energy storage electromechanical transient simulation model, according to preset fitting principle, the electrical parameter / variable and control parameter / variable of the network type energy storage electromechanical transient simulation model are fitted in link by link;For the parameter of fitting, external test checking and error quantification are carried out, according to the result of the external test checking and error quantification, the parameter of fitting is adjusted, and the checking parameter suitable for the network type energy storage electromechanical transient simulation model is obtained.The present application can meet the different simulation accuracy electromechanical transient model parameter fitting demand, and the present application uses error energy ratio index to quantify error, can quantitatively analyze fitting accuracy, provides guarantee for model simulation accuracy.

Description

Technical Field

[0001] This invention relates to the field of electromechanical transient simulation technology, and more specifically, to a method and system for parameter verification of electromechanical transient simulation models for grid-type energy storage. Background Technology

[0002] Electrochemical energy storage based on grid-connected converters exhibits voltage source characteristics to the power grid, and can approximate the characteristics of conventional synchronous generators, providing active frequency, voltage support, and damping functions for the grid. It has broad application prospects in systems with high proportions of new energy sources integrated into weak grids. Currently, research on grid-connected energy storage for grid integration mainly focuses on electromagnetic transient simulation platforms for microgrids or small-scale grids, lacking research on large-scale grid-connected energy storage integration into large power grids. Currently, domestic large power grid electromechanical transient simulation programs do not support simulation calculations for grid-connected energy storage.

[0003] Therefore, it is essential to study the electromechanical transient models, control parameter configurations, and analysis tools that meet the requirements of simulation analysis of grid-connected energy storage systems integrated into large power grids. Among these, establishing a structured electromechanical transient simulation model is fundamental, while configuring reasonable model parameters is crucial for accurately simulating equipment characteristics. Traditional large-scale energy storage system electromechanical transient simulation models and parameter identification and configuration are highly mature. However, grid-connected energy storage systems behave as a voltage source to the power grid, which is fundamentally different from conventional energy storage systems.

[0004] The electromechanical transient simulation model of grid-connected energy storage neglects the operation process of power electronic switches, the PWM pulse width modulation process, and some rapid electromagnetic transient processes, mainly simulating external characteristics. How to obtain the parameters of the electromechanical transient equivalent model and determine efficient and accurate parameter identification and verification methods are key technologies for accurately simulating the external characteristics of actual grid-connected energy storage connected to the power grid. Summary of the Invention

[0005] To address the above problems, this invention proposes a method for parameter verification of a grid-type energy storage electromechanical transient simulation model, comprising:

[0006] Determine the structure of the completed grid-type energy storage electromechanical transient simulation model;

[0007] Based on the structure of the grid-type energy storage electromechanical transient simulation model, and in accordance with the preset fitting principle, the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in stages.

[0008] For the fitted parameters, external experiments are performed for verification and error quantification. Based on the results of the external experiments and error quantification, the fitted parameters are adjusted to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage.

[0009] Optionally, the structural form of the completed grid-type energy storage electromechanical transient simulation model includes: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

[0010] Optionally, preset fitting principles can be used, including: first fitting electrical quantities, then fitting slow-time-scale components, and finally fitting fast-time-scale components.

[0011] Optionally, before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in each stage, the method further includes:

[0012] Identify the key and non-key parameters of the electromechanical transient simulation model of the grid-type energy storage.

[0013] Optionally, parameter fitting is performed on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages, and fitting is performed only on the electrical parameters / variables and control parameters / variables among the key parameters;

[0014] The key parameters include:

[0015] Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters;

[0016] The non-critical parameters include:

[0017] Parameters of the measurement link and parameters of the lead and lag links.

[0018] Optionally, for the fitted parameters, external experimental verification and error quantification are performed. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including:

[0019] External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments.

[0020] Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

[0021] Optional, the formula for calculating error quantization is as follows:

[0022]

[0023] Where REE is the error energy ratio, y s (i) represents the electromechanical transient simulation variable, y m (i) represents the measured or semi-physical simulation variable, y stabis the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

[0024] Furthermore, this invention also proposes a system for parameter verification of a grid-type energy storage electromechanical transient simulation model, comprising:

[0025] The initial unit is used to determine the structure of the completed grid-type energy storage electromechanical transient simulation model;

[0026] The fitting unit is used to perform parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages according to the structure of the grid-type energy storage electromechanical transient simulation model and according to the preset fitting principle.

[0027] The optimization unit is used to perform external experimental verification and error quantification on the fitted parameters. Based on the results of the external experimental verification and error quantification, the fitted parameters are adjusted to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage.

[0028] Optionally, the structural form of the completed grid-type energy storage electromechanical transient simulation model includes: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

[0029] Optionally, preset fitting principles can be used, including: first fitting electrical quantities, then fitting slow-time-scale components, and finally fitting fast-time-scale components.

[0030] Optionally, the fitting unit is also used to identify key and non-key parameters of the grid-type energy storage electromechanical transient simulation model before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in each stage.

[0031] Optionally, parameter fitting is performed on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages, and fitting is performed only on the electrical parameters / variables and control parameters / variables among the key parameters;

[0032] The key parameters include:

[0033] Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters;

[0034] The non-critical parameters include:

[0035] Parameters of the measurement link and parameters of the lead and lag links.

[0036] Optionally, for the fitted parameters, external experimental verification and error quantification are performed. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including:

[0037] External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments.

[0038] Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

[0039] Optional, the formula for calculating error quantization is as follows:

[0040]

[0041] Where REE is the error energy ratio, y s (i) represents the electromechanical transient simulation variable, y m (i) represents the measured or semi-physical simulation variable, y stab is the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

[0042] In another aspect, the present invention also provides a computing device, comprising: one or more processors;

[0043] A processor is used to execute one or more programs;

[0044] When the one or more programs are executed by the one or more processors, the method described above is implemented.

[0045] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method described above.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] This invention provides a method for parameter verification of a grid-type energy storage electromechanical transient simulation model, comprising: determining the structure of the completed grid-type energy storage electromechanical transient simulation model; according to the structure of the grid-type energy storage electromechanical transient simulation model, performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages according to a preset fitting principle; performing external experimental verification and error quantification on the fitted parameters; and adjusting the fitted parameters based on the results of the external experimental verification and error quantification to obtain verification parameters suitable for the grid-type energy storage electromechanical transient simulation model. This invention, by performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages, can meet the parameter fitting requirements of electromechanical transient models with different simulation accuracies. This invention uses the error energy ratio index to quantify the error, enabling quantitative analysis of the fitting accuracy and providing a guarantee for the accuracy of the model simulation. Attached Figure Description

[0048] Figure 1 This is a flowchart of the method of the present invention;

[0049] Figure 2 This is a flowchart of an embodiment of the method of the present invention;

[0050] Figure 3 This is a structural diagram of a generalized model for grid-type energy storage, as shown in the embodiment of the method of the present invention.

[0051] Figure 4 This is a structural diagram of the system of the present invention. Detailed Implementation

[0052] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0053] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0054] Example 1:

[0055] This invention proposes a method for parameter verification of electromechanical transient simulation models for grid-type energy storage, such as... Figure 1As shown, it includes:

[0056] Step 1: Determine the structure of the completed grid-type energy storage electromechanical transient simulation model;

[0057] Step 2: Based on the structure of the grid-type energy storage electromechanical transient simulation model, and in accordance with the preset fitting principle, perform parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages.

[0058] Step 3: Perform external experimental verification and error quantification on the fitted parameters. Based on the results of the external experimental verification and error quantification, adjust the fitted parameters to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage.

[0059] The structural forms of the completed grid-type energy storage electromechanical transient simulation model include: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

[0060] The pre-defined fitting principles include: first fitting electrical quantities, then fitting slow-time-scale components, and finally fitting fast-time-scale components.

[0061] Before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in each stage, the method further includes:

[0062] Identify the key and non-key parameters of the electromechanical transient simulation model of the grid-type energy storage.

[0063] Specifically, the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in stages, and only the electrical parameters / variables and control parameters / variables among the key parameters are fitted.

[0064] The key parameters include:

[0065] Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters;

[0066] The non-critical parameters include:

[0067] Parameters of the measurement link and parameters of the lead and lag links.

[0068] Specifically, for the fitted parameters, external experimental verification and error quantification are performed. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including:

[0069] External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments.

[0070] Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

[0071] The formula for calculating error quantization is as follows:

[0072]

[0073] Where REE is the error energy ratio, y s (i) represents the electromechanical transient simulation variable, y m (i) represents the measured or semi-physical simulation variable, y stab is the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

[0074] The invention will be further explained below with reference to specific implementation examples:

[0075] Implementation case process as follows Figure 2 As shown, it includes:

[0076] First, construct a complete generalized model structure for grid-based energy storage, such as... Figure 3 As shown, the system includes electrochemical energy storage, a DC capacitor, a power electronic converter, a filter reactor, and a converter control system. Subdivided according to time scale, without considering harmonic effects, it includes a traditional electromechanical module and a power electronic module. The traditional electromechanical module is a slow-time-scale component, including electrochemical energy storage, the converter control outer loop, the filter reactor, and the DC capacitor; the power electronic module is a fast-time-scale component, including the converter control inner loop and the converter body. There are related internal connections between the two modules. To meet the accuracy requirements of electromechanical transient simulation in different scenarios, this invention establishes two generalized model structures for electromechanical transient simulation: a complete electromechanical module and a simplified electromechanical transient model, obtained by simplifying the power electronic module to varying degrees. The detailed electromechanical transient model includes the complete components of the electromechanical module and the power electronics module. The converter body ignores the fast switching control characteristics and adopts an average value model. The converter control inner loop only retains current control and current limiting and ignores the switching modulation process. The simplified electromechanical transient model only retains the traditional electromechanical module part and simplifies the converter body and inner loop control processing in the power electronics module into a controlled voltage source model.

[0077] The second step involves fitting the electrical parameters and variables, as well as the control parameters and variables, of the model in each stage, based on the generalized model structure for transient simulation of grid-type energy storage established in the first step, following the principle of first fitting electrical quantities, then fitting slow-time-scale components, and finally fitting fast-time-scale components.

[0078] First, tests were conducted in typical scenarios of grid-based energy storage using either actual measurements or hardware-in-the-loop (HIL) simulation platforms. The measured or HIL simulation results of the main state variables of the grid-based energy storage were obtained, serving as the basis for parameter identification and verification of the electromechanical transient simulation model. For different structural forms of grid-based energy storage electromechanical transient simulation models, the electrical parameters and variables, as well as the control parameters and variables, were analyzed. The internal model parameters of each stage were categorized into critical and non-critical parameters. Critical parameters are those that have a significant impact on the final simulation results, including electrical parameters, damping coefficients, inertia time constants, droop coefficients, current limiting coefficients, current limiting strategies, and virtual impedance. Non-critical parameters are those that have a smaller impact on the final simulation results, such as parameters in the measurement stage and lead / lag stages.

[0079] Then, based on the model's internal connections and the collectable internal and external disturbance-response signals, a corresponding parameter acquisition strategy is formulated. For outer-loop control module parameters that are identical in structure to the actual equipment in the electromechanical transient model, these can be directly obtained from the manufacturer. For parameters that cannot be directly obtained or for steps involving simplified modeling, identification methods are used to identify their key parameters.

[0080] For key parameters that can be identified through collected data, identification methods are used to obtain them; for key parameters that cannot be identified through collected data, theoretical analysis or simulation methods are used to obtain them; and for non-key parameters, theoretical analysis or empirical methods are used to directly assign values.

[0081] The third step involves conducting external tests to verify and quantify the errors of the electromechanical transient model parameters of the grid-type energy storage system. This includes small-disturbance and large-disturbance test verifications, and the parameters are then optimized and adjusted based on the evaluation results. Combined with the measured or hardware-in-the-loop simulation results of the grid-type energy storage system, typical test cases are constructed. By quantifying the errors between the electromechanical transient simulation and the measured or hardware-in-the-loop simulation results, error analysis is completed, and the accuracy of the simulation model is verified.

[0082] For large disturbance tests, different short-circuit fault types and voltage drop depths are set, and the tests can cover both current-limited start-up and non-start-up scenarios for grid-type energy storage.

[0083] Error energy ratio is used to quantify the error. Specifically, it is the ratio of the error energy between simulation and measured (or hardware-in-the-loop) data of a grid-type energy storage system to the energy under a certain disturbance. The start and end time windows for data acquisition are taken as the points where the fault disturbance begins and recovers. The formula for calculating the error energy ratio is:

[0084]

[0085] Among them, y s (i) represents the electromechanical transient simulation variable, ym (i) represents the measured or semi-physical simulation variable, y stab The measured steady-state mean value before the disturbance occurs; N is the number of sampling points in the variable sequence. The error energy ratio (REE) is the ratio of the deviation between the measured and simulated variables to the measured disturbance energy. The smaller this value, the better the fit between the two curves, and the higher the accuracy of the grid-type energy storage model and its parameters.

[0086] If the error exceeds the allowable range, the parameters are tuned as necessary, and then the verification and error assessment are carried out again. This process is repeated until the simulation model error meets the practical engineering requirements.

[0087] Example 2:

[0088] This invention also proposes a system 200 for parameter verification of electromechanical transient simulation models of grid-type energy storage, such as... Figure 4 As shown, it includes:

[0089] Initial unit 201 is used to determine the structure of the completed grid-type energy storage electromechanical transient simulation model;

[0090] The fitting unit 202 is used to perform parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages according to the structure of the grid-type energy storage electromechanical transient simulation model and according to the preset fitting principle.

[0091] The optimization unit 203 is used to perform external experimental verification and error quantification on the fitted parameters, and adjust the fitted parameters according to the results of the external experimental verification and error quantification to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage.

[0092] The structural forms of the completed grid-type energy storage electromechanical transient simulation model include: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

[0093] The pre-defined fitting principles include: first fitting electrical quantities, then fitting slow-time-scale components, and finally fitting fast-time-scale components.

[0094] The fitting unit 202 is also used to identify the key and non-key parameters of the grid-type energy storage electromechanical transient simulation model before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in the sub-stage.

[0095] Specifically, the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in stages, and only the electrical parameters / variables and control parameters / variables among the key parameters are fitted.

[0096] The key parameters include:

[0097] Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters;

[0098] The non-critical parameters include:

[0099] Parameters of the measurement link and parameters of the lead and lag links.

[0100] Specifically, for the fitted parameters, external experimental verification and error quantification are performed. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including:

[0101] External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments.

[0102] Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

[0103] The formula for calculating error quantization is as follows:

[0104]

[0105] Where REE is the error energy ratio, y s (i) represents the electromechanical transient simulation variable, y m (i) represents the measured or semi-physical simulation variable, y stab is the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

[0106] This invention fits the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages, which can meet the parameter fitting requirements of electromechanical transient models with different simulation accuracies. This invention uses the error energy ratio index to quantify the error, which can quantitatively analyze the fitting accuracy and provide a guarantee for the accuracy of model simulation.

[0107] Example 3:

[0108] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the methods in the above embodiments.

[0109] Example 4:

[0110] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiments.

[0111] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0112] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0113] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0114] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0115] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0116] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for parameter verification of a transient simulation model of electromechanical systems for grid-type energy storage, characterized in that, include: Determine the structure of the completed grid-type energy storage electromechanical transient simulation model; Based on the structure of the grid-type energy storage electromechanical transient simulation model, and in accordance with the preset fitting principle, the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in stages. For the fitted parameters, external experiments are performed for verification and error quantification. Based on the results of the external experiments and error quantification, the fitted parameters are adjusted to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage. Before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in the aforementioned sub-stages, the method further includes: Identify the key and non-key parameters of the electromechanical transient simulation model of the grid-type energy storage; The electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in the sub-stages. Only the electrical parameters / variables and control parameters / variables among the key parameters are fitted; non-key parameters are directly assigned values ​​using theoretical analysis or empirical methods. The key parameters include: Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters; The non-critical parameters include: Parameters of the measurement link and parameters of the lead and lag links.

2. The method according to claim 1, characterized in that, The structural forms of the completed grid-type energy storage electromechanical transient simulation model include: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

3. The method according to claim 1, characterized in that, The preset fitting principle includes: first fitting electrical quantities, then fitting slow time scale components, and finally fitting fast time scale components.

4. The method according to claim 1, characterized in that, The fitted parameters undergo external experimental verification and error quantification. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including: External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments. Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

5. The method according to claim 4, characterized in that, The formula for calculating the error quantization is as follows: in, The error energy ratio, For electromechanical transient simulation variables, For measured or semi-physical simulation variables, is the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

6. A system for parameter verification of a grid-type energy storage electromechanical transient simulation model, characterized in that, include: The initial unit is used to determine the structure of the completed grid-type energy storage electromechanical transient simulation model; The fitting unit is used to perform parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in stages according to the structure of the grid-type energy storage electromechanical transient simulation model and according to the preset fitting principle. The optimization unit is used to perform external experimental verification and error quantification on the fitted parameters. Based on the results of the external experimental verification and error quantification, the fitted parameters are adjusted to obtain verification parameters suitable for the electromechanical transient simulation model of grid-type energy storage. The fitting unit is also used to identify key and non-key parameters of the grid-type energy storage electromechanical transient simulation model before performing parameter fitting on the electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model in each stage. The electrical parameters / variables and control parameters / variables of the grid-type energy storage electromechanical transient simulation model are fitted in the sub-stages. Only the electrical parameters / variables and control parameters / variables among the key parameters are fitted; non-key parameters are directly assigned values ​​using theoretical analysis or empirical methods. The key parameters include: Electrical parameters, damping coefficient, inertia time constant, droop coefficient, current limiting coefficient, current limiting strategy, and virtual impedance parameters; The non-critical parameters include: Parameters of the measurement link and parameters of the lead and lag links.

7. The system according to claim 6, characterized in that, The structural forms of the completed grid-type energy storage electromechanical transient simulation model include: a detailed electromechanical transient model structure and a simplified electromechanical transient model structure.

8. The system according to claim 6, characterized in that, The preset fitting principle includes: first fitting electrical quantities, then fitting slow time scale components, and finally fitting fast time scale components.

9. The system according to claim 6, characterized in that, The fitted parameters undergo external experimental verification and error quantification. Based on the results of the external experimental verification and error quantification, the fitted parameters are optimized, including: External experiments are performed to verify the fitted parameters, including small perturbation experiments and large perturbation experiments. Error quantification is performed on the verification results of small disturbance test and large disturbance test. If the error energy ratio obtained by error quantification exceeds the allowable range, the fitting parameters are adjusted according to the error energy ratio value; otherwise, the fitting parameters meet the requirements.

10. The system according to claim 9, characterized in that, The formula for calculating the error quantization is as follows: in, The error energy ratio, For electromechanical transient simulation variables, For measured or semi-physical simulation variables, is the measured steady-state mean before the disturbance occurs, and n is the number of sampling points in the variable sequence.

11. A computer device, characterized in that, include: One or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described in any one of claims 1-5 is implemented.

12. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method as described in any one of claims 1-5.

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