Intensity quantification method, system, equipment and medium for energy-storage-containing heterogeneous multi-machine system

Abstract

The invention belongs to the field of power grid intensity quantification, and discloses an energy storage heterogeneous multi-machine system intensity quantification method, system and device and a medium, and the method comprises the steps: carrying out the eigenvalue decomposition of an extended admittance matrix, obtaining a generalized short-circuit ratio and a corresponding eigenvector, and calculating a participation factor of the device based on the eigenvector; according to a multivariable feedback control theory, constructing a dynamic model of equipment in an equivalent isomorphic system, identifying a weakest subsystem characteristic equation, and calculating a critical short-circuit ratio of equivalent equipment in a heterogeneous system; and calculating a relative difference value between the generalized short-circuit ratio and the critical short-circuit ratio so as to quantify the small disturbance stability margin of the energy storage heterogeneous system. According to the method, the extended admittance matrix is subjected to eigenvalue decomposition, so that the generalized short-circuit ratio and the eigenvector corresponding to the generalized short-circuit ratio can be extracted, the dynamic characteristics of the energy storage heterogeneous multi-machine system are deeply analyzed, the participation factor of each device is calculated by using the obtained eigenvector, and the specific contribution degree of each device in the dynamic behavior of the system is accurately quantified.

Description

Technical Field

[0001] The present invention relates to the field of power grid strength quantification, and in particular to a method, system, equipment and medium for quantifying the strength of a heterogeneous multi-machine system containing energy storage. Background Art

[0002] With the large-scale integration of renewable energy and energy storage devices into the power grid, the architecture and operation of power grid systems have undergone profound changes. In reality, the scenarios for the grid-connected operation of diverse renewable energy and energy storage devices are extremely complex, involving a wide variety of devices with varying control parameters. This situation no longer applies to the traditional assumption that devices in homogeneous systems exhibit highly similar dynamic characteristics, leading to a more complex dynamic behavior of power grid systems. In particular, when encountering small disturbances or sudden failures, the system's stability and responsiveness are subject to increased uncertainty, posing unprecedented challenges to the safe operation of the power grid. Therefore, accurately quantifying the robustness of heterogeneous multi-machine systems with energy storage to comprehensively assess their stability under various operating conditions has become a critical challenge that needs to be addressed.

[0003] Traditional strength quantification methods are primarily based on homogeneous systems, assuming that all devices within the system have similar dynamic characteristics. However, in heterogeneous systems, this assumption no longer meets the needs of practical analysis, as different types of renewable energy devices (such as wind turbines and photovoltaic power generation) and energy storage devices (such as lithium batteries and hydrogen storage) exhibit significant differences in dynamic response characteristics and control strategies. Heterogeneity presents two major challenges: First, different types of renewable energy and energy storage devices have unique dynamic response characteristics, making it difficult for traditional homogeneous system-based analysis methods to comprehensively and accurately describe the overall dynamic behavior of the system. Second, the significant differences in control parameters (such as damping coefficients and time constants) between different devices further increase system complexity and analytical difficulty. Due to the diverse dynamic characteristics and control parameters of these devices, the application of traditional grid strength quantification metrics (such as short-circuit ratio) in heterogeneous systems is severely limited, resulting in inaccurate and unreliable assessments of the system's small-disturbance stability.

[0004] Therefore, how to provide strength quantification methods, systems, equipment and media for heterogeneous multi-machine systems with energy storage is an urgent problem to be solved. Summary of the Invention

[0005] The embodiments of the present invention provide a method, system, device and medium for quantifying the strength of a heterogeneous multi-machine system with energy storage to solve the above-mentioned technical problems existing in the prior art.

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, the following is a brief summary. This summary is not intended to be a comprehensive review, identify key or essential elements, or delineate the scope of these embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the detailed description that follows.

[0007] According to a first aspect of an embodiment of the present invention, a method for quantifying the strength of a heterogeneous multi-machine system with energy storage is provided.

[0008] In one embodiment, the method for quantifying the strength of a heterogeneous multi-machine system with energy storage includes:

[0009] Perform eigenvalue decomposition on the extended admittance matrix to obtain the generalized short-circuit ratio and the corresponding eigenvector, and calculate the device participation factor based on the eigenvector;

[0010] Based on multivariable feedback control theory, a dynamic model of the equipment in an equivalent isomorphic system is constructed, the characteristic equation of the weakest subsystem is identified, and the critical short-circuit ratio of the equivalent equipment in the heterogeneous system is calculated;

[0011] The relative difference between the generalized short-circuit ratio and the critical short-circuit ratio is calculated to quantify the small-disturbance stability margin of the heterogeneous system with energy storage.

[0012] In one embodiment, performing eigenvalue decomposition on the extended admittance matrix to obtain a generalized short-circuit ratio and a corresponding eigenvector, and calculating a participation factor of the device based on the eigenvector includes:

[0013] According to the preset equivalent equipment capacity matrix and power frequency admittance matrix, the expanded admittance matrix is ​​calculated;

[0014] Perform eigenvalue decomposition on the extended admittance matrix, and select the smallest positive eigenvalue from all the eigenvalues ​​obtained as the generalized short-circuit ratio;

[0015] Extract the eigenvector corresponding to the generalized short-circuit ratio and calculate the device participation factor based on the elements of the eigenvector. In one embodiment, the expression of the extended admittance matrix is:

[0016] Y eq =S -1 B;

[0017] Where Y eq represents the extended admittance matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes.

[0018] In one embodiment, the eigenvectors include a first eigenvector and a second eigenvector for characterizing a participation factor of the computing device.

[0019] In one embodiment, constructing a dynamic model of the devices in the equivalent isomorphic system based on multivariable feedback control theory, identifying the characteristic equation of the weakest subsystem, and calculating the critical short-circuit ratio of the equivalent devices in the heterogeneous system includes:

[0020] Based on multivariable feedback control theory, the parameters of a heterogeneous multi-machine system with energy storage are defined, and the closed-loop characteristic equation of the heterogeneous system is constructed.

[0021] Perform left and right multiplication operations on the closed-loop characteristic equation to transform the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system;

[0022] Based on the dynamic characteristics of heterogeneous systems, determine the parameters and participation factors in equivalent homogeneous systems and build dynamic models of devices in equivalent homogeneous systems;

[0023] The dynamic models of the devices in the equivalent isomorphic system are decoupled to identify the characteristic equation of the weakest subsystem. Based on the identified characteristic equation, the critical short-circuit ratio of the equivalent devices in the heterogeneous system is calculated.

[0024] In one embodiment, the closed-loop characteristic equation is expressed as:

[0025]

[0026] In the formula, det() means finding the determinant; Y PED_m () represents the admittance transfer function matrix of multiple renewable energy and multiple energy storage devices; s represents the Laplace operator; Y grid_m () represents the admittance transfer function matrix of the AC power grid; diag() represents the diagonal matrix; S Bi represents the rated capacity of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; S Bj represents the rated capacity of the jth device; Y jPED_in () represents the admittance transfer function matrix of the jth device in charging mode; B represents the power frequency admittance matrix after eliminating internal passive nodes; represents the Kronecker product; γ() represents the dynamic characteristics of the AC network.

[0027] In one embodiment, the equivalent expression is:

[0028]

[0029] In the formula, det() means finding the determinant; diag() means the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; s represents the Laplace operator; Λj () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes; S Bi represents the rated capacity of the i-th converter; S Bj represents the rated capacity of the jth converter.

[0030] In one embodiment, the dynamic characteristics of the heterogeneous system are expressed as follows:

[0031]

[0032] Where, ∑ represents a heterogeneous system; Y sys () represents the dynamic characteristics of the heterogeneous system; s represents the Laplace operator; diag() represents the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix.

[0033] In one embodiment, the dynamic model of the device in the equivalent isomorphic system is expressed as:

[0034]

[0035] Where, represents an equivalent isomorphic system; Y sys0 () represents the dynamic characteristics of the equivalent isomorphic system; s represents the Laplace operator; I2 represents the 2D identity matrix; I n represents the n-dimensional identity matrix; represents the equivalent device admittance transfer function matrix after considering the network characteristics; Y eq represents the extended admittance matrix; represents the admittance transfer function matrix of the equivalent device; γ -1 () represents the dynamic characteristics of the AC network; k represents the number of energy storage devices in discharge mode; i represents the index value; p i represents the participation factor of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; m represents the total number of energy storage devices; p j represents the participation factor of the jth device; Y jPED_out() represents the admittance transfer function matrix of the jth device in the discharge mode; u 1i represents the i-th element of the left eigenvector; v 1i represents the i-th element of the right eigenvector; u 1j represents the jth element of the left eigenvector; v 1j represents the j-th element of the right eigenvector.

[0036] In one embodiment, the characteristic equation of the weakest subsystem is expressed as:

[0037]

[0038] In the formula, det() means finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; s represents the Laplace operator; gSCR represents the generalized short-circuit ratio; I2 represents the two-dimensional identity matrix.

[0039] In one embodiment, the critical short circuit ratio calculation formula of the equivalent device in the heterogeneous system is:

[0040]

[0041] Where, CSCR Σ Represents the critical short-circuit ratio of the equivalent device; arg() represents solving the root of the equation; gSCR represents the generalized short-circuit ratio; det() represents finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; j represents the imaginary unit; ω c represents the dominant oscillation mode at critical stability; I2 represents the two-dimensional identity matrix.

[0042] According to a second aspect of an embodiment of the present invention, a strength quantification system for a heterogeneous multi-machine system with energy storage is provided.

[0043] In one embodiment, the system for quantifying the strength of a heterogeneous multi-machine system with energy storage includes:

[0044] Extended admittance matrix analysis module, used to perform eigenvalue decomposition on the extended admittance matrix, obtain the generalized short-circuit ratio and the corresponding eigenvector, and calculate the device participation factor based on the eigenvector;

[0045] The critical short-circuit ratio calculation module is used to construct a dynamic model of the equipment in the equivalent isomorphic system based on multivariable feedback control theory, identify the characteristic equation of the weakest subsystem, and calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system;

[0046] The relative difference calculation module is used to calculate the relative difference between the generalized short-circuit ratio and the critical short-circuit ratio to quantify the small-disturbance stability margin of the heterogeneous system with energy storage.

[0047] In one embodiment, the extended admittance matrix analysis module includes:

[0048] The extended admittance matrix calculation submodule is used to calculate the extended admittance matrix based on the preset equivalent equipment capacity matrix and the power frequency admittance matrix;

[0049] The generalized short-circuit ratio selection submodule is used to perform eigenvalue decomposition on the extended admittance matrix and select the smallest positive eigenvalue from all the eigenvalues ​​obtained from the decomposition as the generalized short-circuit ratio;

[0050] The participation factor calculation submodule is used to extract the eigenvector corresponding to the generalized short-circuit ratio and calculate the participation factor of the device based on the elements of the eigenvector.

[0051] In one embodiment, the critical short circuit ratio calculation module includes:

[0052] The closed-loop characteristic equation construction submodule is used to define the parameters of a heterogeneous multi-machine system with energy storage based on multivariable feedback control theory and to construct the closed-loop characteristic equation of the heterogeneous system;

[0053] A dynamic characteristics representation submodule is used to perform left and right multiplication operations on the closed-loop characteristic equation, convert the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system;

[0054] The dynamic model construction submodule is used to determine the parameters and participation factors in the equivalent isomorphic system based on the dynamic characteristics of the heterogeneous system, and to build the dynamic model of the equipment in the equivalent isomorphic system;

[0055] The critical short-circuit ratio calculation submodule is used to decouple the dynamic model of the equipment in the equivalent isomorphic system, identify the characteristic equation of the weakest subsystem, and calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system based on the identified characteristic equation.

[0056] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0057] In some embodiments, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0058] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0059] In one embodiment, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0060] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0061] 1. By performing eigenvalue decomposition on the extended admittance matrix, the present invention can extract the generalized short-circuit ratio and its corresponding eigenvector, thereby deeply analyzing the dynamic characteristics of a heterogeneous multi-machine system with energy storage. At the same time, the obtained eigenvectors are used to calculate the participation factor of each device, accurately quantifying the specific contribution of each device to the dynamic behavior of the system. This not only helps to accurately identify key devices that have a significant impact on the dynamic performance of the system, but also provides solid data support and technical basis for the optimization design of the system and the formulation of control strategies.

[0062] 2. By constructing a dynamic model of the equipment in an equivalent isomorphic system and identifying the characteristic equation of the weakest subsystem therein, the present invention not only simplifies the process of analyzing complex heterogeneous systems but also efficiently locates the weak links in the system. Furthermore, by calculating the critical short-circuit ratio of equivalent equipment in a heterogeneous system containing energy storage, the system's stability against small disturbances is further evaluated, providing an important reference for preventing potential system failures, allowing operation and maintenance personnel to take measures in advance to enhance the stability and reliability of the system.

[0063] 3. By calculating the relative difference between the generalized short-circuit ratio and the critical short-circuit ratio, the present invention can accurately quantify the small-disturbance stability margin of heterogeneous systems containing energy storage. This not only intuitively reflects the stability level of the system under current operating conditions, but also reveals the changing trend of the system's stability when facing different disturbances. It can take more targeted measures to enhance the overall stability and operating efficiency of the system, thereby ensuring that the power system can maintain an efficient and stable operating state under various operating conditions.

[0064] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0066] Figure 1 is a flow chart showing a method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to an exemplary embodiment;

[0067] Figure 2 is a principle block diagram of a strength quantification system for a heterogeneous multi-machine system with energy storage according to an exemplary embodiment;

[0068] Figure 3 is a structural diagram of a computer device according to an exemplary embodiment;

[0069] Figure 4 A diagram illustrating a stability analysis approach for a heterogeneous system with energy storage in a method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to an exemplary embodiment;

[0070] Figure 5 is a structural diagram of a nine-machine system in a method for quantifying the strength of a heterogeneous multi-machine system with energy storage, according to an exemplary embodiment;

[0071] Figure 6 is a comparison diagram of the dominant characteristic roots of a nine-machine heterogeneous system and the weakest subsystem in a strength quantification method for a heterogeneous multi-machine system with energy storage, according to an exemplary embodiment;

[0072] Figure 7 3 is a time domain waveform diagram of the active power of each converter in a strength quantification method for a heterogeneous multi-machine system with energy storage, according to an exemplary embodiment. DETAILED DESCRIPTION

[0073] The following description and accompanying drawings sufficiently illustrate the specific embodiments herein to enable those skilled in the art to practice them. Portions and features of some embodiments may be included in or substituted for portions and features of other embodiments. The scope of the embodiments herein includes the entire scope of the claims, including all available equivalents thereof. Herein, the terms "first," "second," and the like are used solely to distinguish one element from another and do not require or imply any actual relationship or order between these elements. In practice, the first element can also be referred to as the second element, and vice versa. Furthermore, the terms "comprise," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a structure, device, or apparatus comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such structure, device, or apparatus. Without further limitation, an element defined by the phrase "comprising a..." does not preclude the presence of other identical elements in the structure, device, or apparatus comprising the element. The various embodiments herein are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Similar or identical parts between the various embodiments can be referenced to each other.

[0074] The terms "longitudinal", "transverse", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like used herein to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are intended only to facilitate the description of this document and simplify the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the present invention. In the description herein, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, they can be mechanical or electrical connections, or they can be internal connections between two elements, they can be directly connected, or they can be indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to the specific circumstances.

[0075] As used herein, unless otherwise specified, the term "plurality" means two or more.

[0076] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0077] In this article, the term "and / or" is used to describe the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0078] It should be understood that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0079] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software so that the processor can call and execute the operations corresponding to the above modules.

[0080] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0081] Figure 1An embodiment of the method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to the present invention is shown.

[0082] In this optional embodiment, the method for quantifying the strength of a heterogeneous multi-machine system with energy storage includes:

[0083] Step S101, performing eigenvalue decomposition on the extended admittance matrix to obtain a generalized short-circuit ratio and a corresponding eigenvector, and calculating a participation factor of the device based on the eigenvector;

[0084] Step S102: Based on multivariable feedback control theory, a dynamic model of the equipment in the equivalent isomorphic system is constructed, and the characteristic equation of the weakest subsystem is identified to calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system.

[0085] Step S103 , calculating the relative difference between the generalized short-circuit ratio and the critical short-circuit ratio to quantify the small-disturbance stability margin of the heterogeneous system with energy storage.

[0086] In this optional embodiment, performing eigenvalue decomposition on the extended admittance matrix to obtain a generalized short-circuit ratio and a corresponding eigenvector, and calculating the participation factor of the device based on the eigenvector includes:

[0087] According to the preset equivalent equipment capacity matrix and power frequency admittance matrix, the expanded admittance matrix is ​​calculated;

[0088] Perform eigenvalue decomposition on the extended admittance matrix, and select the smallest positive eigenvalue from all the eigenvalues ​​obtained as the generalized short-circuit ratio;

[0089] Extract the eigenvector corresponding to the generalized short-circuit ratio, and calculate the device participation factor based on the elements of the eigenvector. In this optional embodiment, the expression of the extended admittance matrix is:

[0090] Y eq =S -1 B;

[0091] Where Y eq represents the extended admittance matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes.

[0092] In this optional embodiment, the eigenvectors include a first eigenvector (left eigenvector) and a second eigenvector (right eigenvector) for characterizing the participation factor of the computing device.

[0093] In this optional embodiment, constructing a dynamic model of the devices in the equivalent isomorphic system based on multivariable feedback control theory, identifying the characteristic equation of the weakest subsystem, and calculating the critical short-circuit ratio of the equivalent devices in the heterogeneous system includes:

[0094] Based on multivariable feedback control theory, the parameters of a heterogeneous multi-machine system with energy storage are defined, and the closed-loop characteristic equation of the heterogeneous system is constructed.

[0095] Perform left and right multiplication operations on the closed-loop characteristic equation to transform the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system;

[0096] Based on the dynamic characteristics of heterogeneous systems, determine the parameters and participation factors in equivalent homogeneous systems and build dynamic models of devices in equivalent homogeneous systems;

[0097] The dynamic models of the devices in the equivalent isomorphic system are decoupled to identify the characteristic equation of the weakest subsystem. Based on the identified characteristic equation, the critical short-circuit ratio of the equivalent devices in the heterogeneous system is calculated.

[0098] In this optional embodiment, the closed-loop characteristic equation is expressed as:

[0099]

[0100] In the formula, det() means finding the determinant; Y PED_m () represents the admittance transfer function matrix of multiple renewable energy and multiple energy storage devices; s represents the Laplace operator; Y grid_m () represents the admittance transfer function matrix of the AC power grid; diag() represents the diagonal matrix; S Bi represents the rated capacity of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; S Bj represents the rated capacity of the jth device; Y jPED_in () represents the admittance transfer function matrix of the jth device in charging mode; B represents the power frequency admittance matrix after eliminating internal passive nodes; represents the Kronecker product; γ() represents the dynamic characteristics of the AC network.

[0101] In this optional embodiment, the equivalent expression is:

[0102]

[0103] In the formula, det() means finding the determinant; diag() means the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; s represents the Laplace operator; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes; S Bi represents the rated capacity of the i-th converter; S Bj represents the rated capacity of the jth converter.

[0104] In this optional embodiment, the expression of the dynamic characteristics of the heterogeneous system is:

[0105]

[0106] Where, ∑ represents a heterogeneous system; Y sys () represents the dynamic characteristics of the heterogeneous system; s represents the Laplace operator; diag() represents the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix.

[0107] In this optional embodiment, the dynamic model of the device in the equivalent isomorphic system is expressed as follows:

[0108]

[0109] Where, represents an equivalent isomorphic system; Y sys0 () represents the dynamic characteristics of the equivalent isomorphic system; s represents the Laplace operator; I2 represents the 2D identity matrix; I n represents the n-dimensional identity matrix; represents the equivalent device admittance transfer function matrix after considering the network characteristics; Y eq represents the extended admittance matrix; represents the admittance transfer function matrix of the equivalent device; γ -1 () represents the dynamic characteristics of the AC network; k represents the number of energy storage devices in discharge mode; i represents the index value; p i represents the participation factor of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; m represents the total number of energy storage devices; p j represents the participation factor of the jth device; Y jPED_out () represents the admittance transfer function matrix of the jth device in the discharge mode; u 1i represents the i-th element of the left eigenvector; v 1i represents the i-th element of the right eigenvector; u1j represents the jth element of the left eigenvector; v 1j represents the j-th element of the right eigenvector.

[0110] In this optional embodiment, the characteristic equation of the weakest subsystem is expressed as:

[0111]

[0112] In the formula, det() means finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; s represents the Laplace operator; gSCR represents the generalized short-circuit ratio; I2 represents the two-dimensional identity matrix.

[0113] In this optional embodiment, the critical short circuit ratio calculation formula of the equivalent device in the heterogeneous system is:

[0114]

[0115] Where, CSCR Σ Represents the critical short-circuit ratio of the equivalent device; arg() represents solving the root of the equation; gSCR represents the generalized short-circuit ratio; det() represents finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; j represents the imaginary unit; ω c represents the dominant oscillation mode at critical stability; I2 represents the two-dimensional identity matrix.

[0116] Figure 2 An embodiment of the strength quantification system of a heterogeneous multi-machine system with energy storage according to the present invention is shown.

[0117] In this optional embodiment, the system for quantifying the strength of a heterogeneous multi-machine system with energy storage includes:

[0118] The extended admittance matrix analysis module 201 is used to perform eigenvalue decomposition on the extended admittance matrix to obtain the generalized short-circuit ratio and the corresponding eigenvector, and calculate the participation factor of the device based on the eigenvector;

[0119] The critical short circuit ratio calculation module 202 is used to construct a dynamic model of the equipment in the equivalent isomorphic system based on multivariable feedback control theory, identify the characteristic equation of the weakest subsystem, and calculate the critical short circuit ratio of the equivalent equipment in the heterogeneous system;

[0120] The relative difference calculation module 203 is used to calculate the relative difference between the generalized short circuit ratio and the critical short circuit ratio to quantify the small disturbance stability margin of the heterogeneous system with energy storage.

[0121] In this optional embodiment, the extended admittance matrix analysis module 201 includes:

[0122] The extended admittance matrix calculation submodule is used to calculate the extended admittance matrix based on the preset equivalent equipment capacity matrix and the power frequency admittance matrix;

[0123] The generalized short-circuit ratio selection submodule is used to perform eigenvalue decomposition on the extended admittance matrix and select the smallest positive eigenvalue from all the eigenvalues ​​obtained from the decomposition as the generalized short-circuit ratio;

[0124] The participation factor calculation submodule is used to extract the eigenvector corresponding to the generalized short-circuit ratio and calculate the participation factor of the device based on the elements of the eigenvector.

[0125] In this optional embodiment, the critical short circuit ratio calculation module 202 includes:

[0126] The closed-loop characteristic equation construction submodule is used to define the parameters of a heterogeneous multi-machine system with energy storage based on multivariable feedback control theory and to construct the closed-loop characteristic equation of the heterogeneous system;

[0127] A dynamic characteristics representation submodule is used to perform left and right multiplication operations on the closed-loop characteristic equation, convert the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system;

[0128] The dynamic model construction submodule is used to determine the parameters and participation factors in the equivalent isomorphic system based on the dynamic characteristics of the heterogeneous system, and to build the dynamic model of the equipment in the equivalent isomorphic system;

[0129] The critical short-circuit ratio calculation submodule is used to decouple the dynamic model of the equipment in the equivalent isomorphic system, identify the characteristic equation of the weakest subsystem, and calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system based on the identified characteristic equation.

[0130] The following is a detailed description of the method for quantifying the strength of a heterogeneous multi-machine system with energy storage provided by the present invention.

[0131] like Figure 4 As shown in Figure 2, the strength quantification method for heterogeneous multi-machine systems with energy storage includes:

[0132] 1. Approximation of dominant characteristic trajectories of heterogeneous systems

[0133] Based on the multivariable feedback control theory, the closed-loop characteristic equation of the multi-machine system with energy storage is constructed. The equation consists of the dynamic models of the converter and the AC power grid, as shown in the following formula (1):

[0134]

[0135] In the formula, det() means finding the determinant; Y PED_m() represents the admittance transfer function matrix of multiple renewable energy and multiple energy storage devices; s represents the Laplace operator; Y grid_m () represents the admittance transfer function matrix of the AC power grid; diag() represents the diagonal matrix; S Bi represents the rated capacity of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; S Bj represents the rated capacity of the jth device; Y jPED_in () represents the admittance transfer function matrix of the jth device in charging mode; B represents the power frequency admittance matrix after eliminating internal passive nodes; represents the Kronecker product; γ() represents the dynamic characteristics of the AC network.

[0136] in,

[0137]

[0138] Where γ() represents the dynamic characteristics of the AC network; s represents the Laplace operator; ω0 represents the synchronous rotation speed; τ represents the ratio of line resistance to inductance; τ = R ij / L ij , R ij Indicates the resistance value of line ij, L ij Represents the inductance value of line ij.

[0139] By multiplying the characteristic equation (1) of the heterogeneous system containing energy storage on the left, we can get:

[0140]

[0141] Where diag() represents a diagonal matrix; S Bi represents the rated capacity of the i-th new energy equipment; S Bj represents the rated capacity of the jth energy storage device; I2 represents the 2-dimensional unit matrix; where i = 1, 2, ... n + k; j = n + k + 1, ... n + m.

[0142] and multiply right I n+m For the n+m-dimensional identity matrix, we can obtain the equivalent form as shown in formulas (2) and (3):

[0143]

[0144] In the formula, det() means finding the determinant; diag() means the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; s represents the Laplace operator; Λ j() represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes; S Bi represents the rated capacity of the i-th converter; S Bj represents the rated capacity of the jth converter; where Λ i (s)=Y iPED_out (s)γ -1 (s), Λ j (s)=Y jPED_out (s)γ -1 (s).

[0145] According to formula (2), the dynamics of the heterogeneous system is represented by the sum of the transfer function matrices, as shown in formula (4):

[0146]

[0147] Where, ∑ represents a heterogeneous system; Y sys () represents the dynamic characteristics of the heterogeneous system; s represents the Laplace operator; diag() represents the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix.

[0148] From formula (2), it can be seen that it is difficult to directly decouple the closed-loop characteristic equation of the heterogeneous system containing energy storage. Therefore, an equivalent isomorphic system that is similar to the dominant characteristic trajectory of the original heterogeneous system will be constructed below. On this basis, the small perturbation stability analysis problem of the original heterogeneous system will be transformed into the small perturbation stability analysis problem of the equivalent isomorphic system.

[0149] When constructing an equivalent isomorphic system, the dynamic model of each converter is a similar admittance transfer function model (the models of the energy storage converter in discharge mode and charging mode only differ in positive and negative signs), and the dynamic model of the AC grid is still The equivalent isomorphic system can be defined as follows:

[0150]

[0151] Where, the formula (6) is as follows:

[0152]

[0153] Where, represents an equivalent isomorphic system; Y sys0 () represents the dynamic characteristics of the equivalent isomorphic system; s represents the Laplace operator; I2 represents the 2D identity matrix; I n represents the n-dimensional identity matrix; represents the equivalent device admittance transfer function matrix after considering the network characteristics; Y eq represents the extended admittance matrix; represents the admittance transfer function matrix of the equivalent device; γ -1 () represents the dynamic characteristics of the AC network; k represents the number of energy storage devices in discharge mode; i represents the index value; p i represents the participation factor of the i-th device; Y iPED_out () represents the admittance transfer function matrix of the i-th device in the discharge mode; m represents the total number of energy storage devices; p j represents the participation factor of the jth device; Y jPED_out () represents the admittance transfer function matrix of the jth device in the discharge mode; where p i and p j (also represents the weighting coefficient), and satisfies u 1i and u 1j They represent the left eigenvectors The i-th and j-th elements of v 1i and v 1j Represent the i-th and j-th elements of the right eigenvector v1, and v1 are the expanded admittance matrices Y eq About the left and right eigenvectors of the smallest positive eigenvalue (i.e., the generalized short-circuit ratio gSCR).

[0154] It should be noted that the participation factor p of the new energy converter and the energy storage converter in the discharge mode in the heterogeneous system is i is a positive value, and the participation factor p of the energy storage converter in charging mode j is a negative value, which indicates that in the above two cases, the dominant mode of the heterogeneous system shows opposite changing trends with the device control parameters.

[0155] The equivalent isomorphic system The small perturbation stability of depends on the weakest equivalent single-machine system after decoupling, and its characteristic equation can be expressed in a form including gSCR, as shown in formula (7):

[0156]

[0157] In the formula, det() means finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; s represents the Laplace operator; gSCR represents the generalized short-circuit ratio; I2 represents the two-dimensional identity matrix.

[0158] definition and To characterize equivalent isomorphic systems A pair of dominant characteristic trajectories of small perturbation stability are derived as shown in formula (8):

[0159]

[0160] In the formula, det() means finding the determinant; Representation matrix About its characteristic function The left eigenvector of ; Representation matrix About its characteristic function The left eigenvector of ; represents the equivalent device admittance transfer function matrix after considering the network characteristics; s represents the Laplace operator; gSCR represents the generalized short-circuit ratio; I2 represents the 2D identity matrix; Representation matrix About its characteristic function The right eigenvector of ; Representation matrix About its characteristic function The right eigenvector of ; T represents the transpose of the matrix; represents the characteristic function; represents the characteristic function; represents the dominant characteristic locus of equivalent isomorphic systems; Represents the dominant characteristic locus of an equivalent isomorphic system.

[0161] According to the modal perturbation theory, the heterogeneous system ∑ is regarded as an equivalent isomorphic system The perturbation of can be deduced that the heterogeneous system ∑ and the equivalent isomorphic system The dominant characteristic trajectories of are approximately equal, and the specific form is shown in the following formula (9):

[0162]

[0163] The main proof is as follows:

[0164]

[0165] Where c 1t (s) represents the dominant characteristic trajectory of the heterogeneous system (t = 1, 2); represents the dominant characteristic trajectory of the equivalent isomorphic system (t = 1, 2); represents the characteristic function of the equivalent isomorphic system (t=1,2); gSCR represents the generalized short-circuit ratio; t represents the index value; Represents the expanded admittance matrix Y eq About the left eigenvector of the smallest positive eigenvalue (i.e. the generalized short-circuit ratio gSCR); Representation matrix About its characteristic function The left eigenvector of (t=1,2); diag() represents a diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; s represents the Laplace operator; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; I2 represents the 2D identity matrix; v1 represents the extended admittance matrix Y eq About the right eigenvector of the smallest positive eigenvalue (i.e., the generalized short-circuit ratio gSCR); Representation matrix About its characteristic function The right eigenvector of (t=1,2); o represents a second-order infinitesimal; Y sys () represents the dynamic characteristics of heterogeneous systems; Y sys0 () represents the dynamic characteristics of equivalent isomorphic systems; represents the equivalent device admittance transfer function matrix after considering the network characteristics; ||·|| represents taking an arbitrary norm of the matrix.

[0166] According to the above derivation process, the analysis ideas of small perturbation stability of heterogeneous systems with energy storage can be summarized as follows: Figure 4 As shown, by the analytical thinking Figure 4 It can be seen that the equivalent isomorphic system It can approximately characterize the small perturbation stability of heterogeneous systems containing energy storage, greatly reducing the complexity of small perturbation stability analysis of heterogeneous systems containing energy storage. It can be decoupled into n+m independent subsystems. The small perturbation stability of the system can be obtained by the weighted Laplace matrix of the AC network (i.e., the extended admittance matrix Y eq ) is characterized by the minimum positive eigenvalue gSCR. And the dominant characteristic trajectory of the heterogeneous system ∑ containing energy storage is approximately equal to its equivalent isomorphic system Therefore, the gSCR indicator can also be used to quantify the grid strength and small-disturbance stability of heterogeneous systems containing energy storage.

[0167] 2. Quantification of Heterogeneous System Strength Based on Generalized Short-Circuit Ratio

[0168] System strength is determined by the grid gSCR and the critical short-circuit ratio of the equipment. In other words, the strength and small-disturbance stability margin of a heterogeneous system with energy storage cannot be determined based solely on the grid gSCR indicator. It is also necessary to solve the key value CSCR that represents the stability boundary of the heterogeneous system. Σ .

[0169] The small perturbation stability of a heterogeneous system with energy storage is characterized by the weakest subsystem after decoupling of its equivalent homogeneous system. Therefore, the critical short circuit ratio (CSCR) of the equivalent device can be derived based on the characteristic equation (7) of the weakest subsystem. Σ The specific form of is shown in formula (11):

[0170]

[0171] Where, CSCR Σ Represents the critical short-circuit ratio of the equivalent device; arg() represents solving the root of the equation; gSCR represents the generalized short-circuit ratio; det() represents finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; j represents the imaginary unit; ω c represents the dominant oscillation mode at critical stability; I2 represents the two-dimensional identity matrix.

[0172] Similar to the strength quantification method of homogeneous systems, the strength of heterogeneous systems with energy storage is determined by the grid gSCR and the equivalent equipment critical short circuit ratio CSCR. Σ The definition of the generalized short-circuit ratio index of the heterogeneous energy storage system and the homogeneous energy storage system is the same, CSCR Σ It is no longer targeted at actual converter devices, but rather an equivalent device constructed by weighting the dynamic characteristics of all converter devices in the heterogeneous system. In other words, the equivalent device can reflect the overall characteristics of all types of devices in the heterogeneous system through the participation factor, which is a weighted coefficient. Therefore, the CSCR of the heterogeneous system is Σ It is generally between the CSCRs of different converter equipment systems.

[0173] The specific steps for quantifying the strength and small-disturbance stability margin of heterogeneous systems with energy storage are summarized as follows:

[0174] Step 1: Calculate the expanded admittance matrix Y eq =S -1 B and solve its minimum positive eigenvalue to get gSCR, and obtain the left and right eigenvectors corresponding to the minimum positive eigenvalue gSCR (respectively and v1), and participation factor p i =u 1i v 1i and p j =u 1j v 1j(i=1,2,…n+k; j=n+k+1,…n+m).

[0175] Step 2: According to formula (6), the dynamic model of the converter equipment in the equivalent isomorphic system is obtained, and then the critical short circuit ratio CSCR of the equivalent equipment in the heterogeneous system is calculated based on formula (11). Σ .

[0176] Step 3: Calculate gSCR and CSCR Σ The relative difference δ% is used to quantify the small disturbance stability margin of the heterogeneous system with energy storage.

[0177] 3. Analysis of the impact of heterogeneous systems with energy storage

[0178] This section analyzes the key influencing factors (operation modes) of heterogeneous systems with energy storage. The strength of heterogeneous systems with energy storage is determined by the generalized short-circuit ratio gSCR of the grid and the critical short-circuit ratio CSCR of the equipment. Σ The gSCR of the homogeneous and heterogeneous systems is determined by the same definition. The difference in small disturbance stability of the grid gSCR in the energy storage charging and discharging modes is also consistent with that of the homogeneous system. That is, when the energy storage converter works in the charging mode, the gSCR of the heterogeneous system is higher than that in the discharging mode. However, unlike the homogeneous system, the critical short circuit ratio CSCR of the heterogeneous system is Σ There are certain differences between the charging and discharging modes. Specifically, according to formula (6), the equivalent isomorphic system weight coefficient that characterizes the stability of the heterogeneous system is the generalized short-circuit ratio participation factor. Since the generalized short-circuit ratio of the energy storage converter is different when it works in the charging mode and the discharging mode, the generalized short-circuit ratio participation factor p is i and p j The system will change accordingly, so the equivalent isomorphic system constructed when the energy storage converter is in different modes is different. Furthermore, by solving the critical short-circuit ratio of the equipment (11), it can be seen that the critical short-circuit ratio CSCR of the heterogeneous system is Σ It will change with the dynamic changes of equivalent devices in equivalent isomorphic systems, that is, the critical short circuit ratio CSCR of the equipment in the heterogeneous system containing energy storage in the charging and discharging mode of the energy storage converter Σ There are differences.

[0179] The above analysis shows that when the heterogeneous system with energy storage works in different operating modes, its grid generalized short circuit ratio gSCR and equipment critical short circuit ratio CSCR ΣBoth indicators will change, resulting in differences in the strength of heterogeneous systems. It's no longer possible to analyze the stability differences between different operating modes of a system by comparing changes in the generalized short-circuit ratio, as is the case with homogeneous systems. Instead, it's necessary to calculate the damping ratio of the heterogeneous system with energy storage and compare the system damping ratios in charging and discharging modes. A larger damping ratio indicates greater heterogeneous system strength and a larger small-disturbance stability margin. Conversely, a larger damping ratio indicates a lower heterogeneous system strength and a potential risk of instability.

[0180] 4. Verification of the effectiveness of the strength quantification method for heterogeneous systems

[0181] The effectiveness of the dominant characteristic trajectory approximation method and the intensity quantification method for heterogeneous systems with energy storage are verified based on the modified 39-bus system simulation model. The topology of the 39-bus system is shown in Figure 2. Figure 5 As shown in the figure, serial numbers 1 to 39 represent AC grid nodes 1 to 39, among which nodes 30 to 35 are respectively connected to wind turbine equipment VSC1 to VSC6 through transformers, nodes 37 to 39 are respectively connected to energy storage equipment VSC7 to VSC9 (i.e., energy storage converters I, II, and III) through transformers, and node 36 is connected to the external grid, which is simplified to an infinite bus.

[0182] Table 1: Nine-machine system network parameters

[0183]

[0184] Table 2: Heterogeneous system converter control parameters

[0185] Udc control PQ control DC link capacitance Cdc / pu 0.038 — Phase-locked loop proportional and integral parameters 26,7800 35,7200 Current inner loop proportional and integral parameters 1,10 1,10 Power outer loop proportional and integral parameters — 0.5,5 DC voltage outer loop proportional and integral parameters 0.5,5 — Voltage feedforward filter time constant TFF 0.01 0.01 Active and reactive power reference value / pu — ±1,0 DC voltage reference value / pu 1 —

[0186] The network topology of the system is consistent with the New England IEEE 39-node standard system (the system AC network parameters are shown in Table 1), where nodes 30 to 35 are connected to the new energy converter, and nodes 37 to 39 are connected to the energy storage converters I, II, and

[0187] In this simulation, we used energy storage converters I and II operating in discharge mode and energy storage converter III operating in charge mode. The capacity of both the new energy and energy storage devices was 1 MVA, and 1 MVA was used as the per-unit system capacity benchmark, meaning each converter had a capacity of 1.0 pu. The control parameters for the new energy and energy storage converters are shown in Table 2. The new energy converter uses a DC voltage outer loop control, while the energy storage converter uses a power outer loop control.

[0188] (1) Modal analysis

[0189] First, from the perspective of modal analysis, verify the effectiveness of the strength quantification method for the energy storage heterogeneous system proposed in Section 0. To this end, let the variable M represent the proportional amplification factor of the AC network reactance value (or line length), and change M to achieve the effect of proportionally changing the AC network parameters. As Figure 6 shown, the dominant characteristic roots of the nine-machine energy storage heterogeneous system and the weakest decoupled subsystem are given when the coefficient M gradually increases from 0.7 to 1.2.

[0190] It can be seen from Figure 6 that as the grid strength changes, the dominant characteristic roots of the nine-machine energy storage heterogeneous system and the weakest decoupled subsystem basically remain the same, indicating that the small-signal stability of the energy storage heterogeneous system can be approximately evaluated through the equivalent isomorphic system and its weakest decoupled subsystem.

[0191] In addition, it can be known from Figure 6 that the small-signal stability and stability margin of the system can be evaluated based on gSCR and CSCR. According to Equation (11), CSCR = 2.230. When gSCR = CSCR (i.e., the relative difference δ% = 0), the dominant characteristic roots of the nine-machine heterogeneous system are approximately located on the imaginary axis, and the system is in a critically stable state; when gSCR > CSCR (i.e., the relative difference δ% > 0), the dominant characteristic roots of the system are all located in the left half-plane, the system is small-signal stable, and the larger gSCR is, the farther the dominant characteristic roots are from the imaginary axis, and the larger the stability margin is; when gSCR < CSCR (i.e., the relative difference δ% > 0), the dominant characteristic roots are located in the right half-plane, and the system is small-signal unstable. The above analysis shows that the relative difference between gSCR and CSCR is consistent with the modal analysis results for the quantification of the system stability margin, verifying the effectiveness of the small-signal stability criterion based on gSCR and CSCR.

[0192] (2) Time-domain simulation

[0193] Furthermore, verify the effectiveness of the small-signal stability analysis method based on gSCR and CSCR from the perspective of time-domain simulation. When the coefficient M is set to 0.75, 1.15, and 1.20, the corresponding system gSCRs are 3.420, 2.230, and 2.137 respectively. Apply a perturbation to the system: at t = 0.10 s, the infinite bus voltage at node 36 rises by 10%, and at t = 0.12 s, the voltage recovers.

[0194] As Figure 7 shown, the time-domain waveforms of the active power (per-unit amplitude) of all converters in the nine-machine heterogeneous system after being perturbed are given when gSCR is 3.420, 2.230, and 2.137 respectively. It can be seen that when

[0195] When gSCR = 3.420 > CSCR = 2.230, the time-domain waveform of the active power oscillates and converges, and the system is stable with a certain margin at this time; when gSCR = 2.137 < CSCR, the time-domain waveform of the active power oscillates divergently and the system becomes unstable; when

[0196] gSCR = 2.230 = CSCR, the time-domain waveform of the active power oscillates with approximately equal amplitude, and the system is in a critically stable state. Therefore, the relative difference between gSCR and CSCR is consistent with the quantization result of the system stability margin and the result of the time-domain simulation waveform. Based on the grid gSCR and its critical value CSCR, the strength and small-signal stability margin of the energy storage heterogeneous system can be quickly evaluated.

[0197] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in Figure 3 the figure. The computer device includes a processor, a memory, and a network interface 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, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes the steps in the above method embodiment.

[0198] Those skilled in the art can understand that Figure 3 the structure shown in is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0199] In addition, the present invention also provides a computer device, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it realizes the steps in the above method embodiment.

[0200] In addition, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, it realizes the steps in the above method embodiment.

[0201] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0202] The present invention is not limited to the structures described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for quantifying the strength of a heterogeneous multi-machine system with energy storage, characterized by: The method includes: Perform eigenvalue decomposition on the extended admittance matrix to obtain the generalized short-circuit ratio and the corresponding eigenvector, and calculate the device participation factor based on the eigenvector; Based on multivariable feedback control theory, a dynamic model of the equipment in an equivalent isomorphic system is constructed, the characteristic equation of the weakest subsystem is identified, and the critical short-circuit ratio of the equivalent equipment in the heterogeneous system is calculated; The relative difference between the generalized short-circuit ratio and the critical short-circuit ratio is calculated to quantify the small-disturbance stability margin of the heterogeneous system with energy storage.

2. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 1 is characterized in that: The step of performing eigenvalue decomposition on the extended admittance matrix to obtain a generalized short-circuit ratio and a corresponding eigenvector, and calculating a participation factor of the device based on the eigenvector includes: According to the preset equivalent equipment capacity matrix and power frequency admittance matrix, the expanded admittance matrix is ​​calculated; Perform eigenvalue decomposition on the extended admittance matrix, and select the smallest positive eigenvalue from all the eigenvalues ​​obtained as the generalized short-circuit ratio; The eigenvector corresponding to the generalized short-circuit ratio is extracted, and the participation factor of the device is calculated based on the elements of the eigenvector.

3. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 2, characterized in that: The expression of the extended admittance matrix is: Y eq =S -1 B; Where Y eq represents the extended admittance matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes.

4. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 3 is characterized in that: The eigenvectors include a first eigenvector and a second eigenvector for characterizing a participation factor of a computing device.

5. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 1, characterized in that: The method of constructing a dynamic model of the equipment in the equivalent isomorphic system based on multivariable feedback control theory, identifying the characteristic equation of the weakest subsystem, and calculating the critical short-circuit ratio of the equivalent equipment in the heterogeneous system includes: Based on multivariable feedback control theory, the parameters of a heterogeneous multi-machine system with energy storage are defined, and the closed-loop characteristic equation of the heterogeneous system is constructed. Perform left and right multiplication operations on the closed-loop characteristic equation to transform the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system; Based on the dynamic characteristics of heterogeneous systems, determine the parameters and participation factors in equivalent homogeneous systems and build dynamic models of devices in equivalent homogeneous systems; The dynamic models of the devices in the equivalent isomorphic system are decoupled to identify the characteristic equation of the weakest subsystem. Based on the identified characteristic equation, the critical short-circuit ratio of the equivalent devices in the heterogeneous system is calculated.

6. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 5, characterized in that: The expression of the closed-loop characteristic equation is: In the formula, det() means finding the determinant; Y PED_m () represents the admittance transfer function matrix of the multi-converter; s represents the Laplace operator; Y grid_m () represents the admittance transfer function matrix of the AC power grid; diag() represents the diagonal matrix; S Bi represents the rated capacity of the i-th converter; Y iPED_out () represents the admittance transfer function matrix of the converter connected to node i in the discharge mode; S Bj represents the rated capacity of the jth converter; Y jPED_in () represents the admittance transfer function matrix of the converter connected to node j in charging mode; B represents the power frequency admittance matrix after eliminating the internal passive nodes; represents the Kronecker product; Represents the admittance transfer function matrix of the AC line.

7. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 6, characterized in that: The equivalent expression is: In the formula, det() means finding the determinant; diag() means the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; s represents the Laplace operator; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix; S represents the equivalent equipment capacity matrix; B represents the power frequency admittance matrix after eliminating the internal passive nodes; S Bi represents the rated capacity of the i-th converter; S Bj represents the rated capacity of the jth converter.

8. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 7, characterized in that: The expression of the dynamic characteristics of the heterogeneous system is: Where, ∑ represents a heterogeneous system; Y sys () represents the dynamic characteristics of the heterogeneous system; s represents the Laplace operator; diag() represents the diagonal matrix; Λ i () represents the admittance transfer function matrix of the i-th new energy device after considering the network characteristics; Λ j () represents the admittance transfer function matrix of the j-th energy storage device after considering the network characteristics; Y eq represents the extended admittance matrix; represents the Kronecker product; I2 represents the 2D identity matrix.

9. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 8, characterized in that: The expression of the dynamic model of the equipment in the equivalent isomorphic system is: Where, represents an equivalent isomorphic system; Y sys0 () represents the dynamic characteristics of the equivalent isomorphic system; s represents the Laplace operator; I2 represents the 2D identity matrix; I n represents the n-dimensional identity matrix; represents the equivalent device admittance transfer function matrix after considering the network characteristics; Y eq represents the extended admittance matrix; represents the admittance transfer function matrix of the equivalent device; γ -1 () represents the dynamic characteristics of the AC network; k represents the number of energy storage devices in discharge mode; i represents the index value; p i represents participation factor; Y iPED_out () represents the admittance transfer function matrix of the i-th device; m represents the total number of energy storage devices; p i represents the participation factor of the i-th device; p j represents the participation factor of the jth device; Y jPED_out () represents the admittance transfer function matrix of the jth device; u 1i represents the i-th element of the left eigenvector; v 1i represents the i-th element of the right eigenvector; u 1j represents the jth element of the left eigenvector; v 1j represents the j-th element of the right eigenvector.

10. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 9, characterized in that: The characteristic equation of the weakest subsystem is expressed as: In the formula, det() means finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; s represents the Laplace operator; gSCR represents the generalized short-circuit ratio; I2 represents the two-dimensional identity matrix.

11. The method for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 10, characterized in that: The calculation formula for the critical short-circuit ratio of equivalent devices in the heterogeneous system is: Where, CSCR Σ Represents the critical short-circuit ratio of the equivalent device; arg() represents solving the root of the equation; gSCR represents the generalized short-circuit ratio; det() represents finding the determinant; represents the equivalent device admittance transfer function matrix after considering the network characteristics; j represents the imaginary unit; ω c represents the dominant oscillation mode at critical stability; I2 represents the two-dimensional identity matrix.

12. A system for quantifying the strength of a heterogeneous multi-machine system with energy storage, characterized by: The system includes: Extended admittance matrix analysis module, used to perform eigenvalue decomposition on the extended admittance matrix, obtain the generalized short-circuit ratio and the corresponding eigenvector, and calculate the device participation factor based on the eigenvector; The critical short-circuit ratio calculation module is used to construct a dynamic model of the equipment in the equivalent isomorphic system based on multivariable feedback control theory, identify the characteristic equation of the weakest subsystem, and calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system; The relative difference calculation module is used to calculate the relative difference between the generalized short-circuit ratio and the critical short-circuit ratio to quantify the small-disturbance stability margin of the heterogeneous system with energy storage.

13. The system for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 12, characterized in that: The extended admittance matrix analysis module includes: The extended admittance matrix calculation submodule is used to calculate the extended admittance matrix based on the preset equivalent equipment capacity matrix and the power frequency admittance matrix; The generalized short-circuit ratio selection submodule is used to perform eigenvalue decomposition on the extended admittance matrix and select the smallest positive eigenvalue from all the eigenvalues ​​obtained from the decomposition as the generalized short-circuit ratio; The participation factor calculation submodule is used to extract the eigenvector corresponding to the generalized short-circuit ratio and calculate the participation factor of the device based on the elements of the eigenvector.

14. The system for quantifying the strength of a heterogeneous multi-machine system with energy storage according to claim 13, characterized in that: The critical short circuit ratio calculation module includes: The closed-loop characteristic equation construction submodule is used to define the parameters of a heterogeneous multi-machine system with energy storage based on multivariable feedback control theory and to construct the closed-loop characteristic equation of the heterogeneous system; A dynamic characteristics representation submodule is used to perform left and right multiplication operations on the closed-loop characteristic equation, convert the closed-loop characteristic equation into an equivalent form, and use the sum of the transfer function matrices to represent the dynamic characteristics of the heterogeneous system; The dynamic model construction submodule is used to determine the parameters and participation factors in the equivalent isomorphic system based on the dynamic characteristics of the heterogeneous system, and to build the dynamic model of the equipment in the equivalent isomorphic system; The critical short-circuit ratio calculation submodule is used to decouple the dynamic model of the equipment in the equivalent isomorphic system, identify the characteristic equation of the weakest subsystem, and calculate the critical short-circuit ratio of the equivalent equipment in the heterogeneous system based on the identified characteristic equation.

15. 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 method according to any one of claims 1 to 11 are implemented.

16. 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 method according to any one of claims 1 to 11 are implemented.

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