Method and system for evaluating stability margin of new energy multi-infeed power grid containing multiple SVGs (Static Var Generator)

Abstract

The invention discloses an SVG-containing new energy power grid stability margin evaluation method and system, and relates to the technical field of power system stability analysis, and the method comprises the steps: collecting SVG equipment data and power grid parameters; constructing a new energy power grid transfer function matrix containing SVG under the power grid structure maintenance model based on the operation condition change; and the action rule of the SVG on the system interference stability is revealed through a short-circuit ratio analysis method. According to the SVG-containing new energy power grid stability margin evaluation method provided by the invention, the SVG-containing new energy power grid transfer function matrix under the power grid structure maintenance model is constructed based on the operation condition change, so that the adaptability and flexibility of the power grid and the prediction accuracy are improved; the stability of the power grid in large-scale renewable energy source grid connection is ensured, and the method achieves better effects in the aspects of accuracy, stability and adaptability.

Description

Technical Field

[0001] The present invention relates to the technical field of power system stability analysis, and in particular to a stability margin assessment method and system for a renewable energy multi-feedback power grid system containing multiple SVGs. Background Art

[0002] As the proportion of new energy represented by wind power generation and photovoltaic power generation in the power system increases year by year, the access of a high proportion of grid-connected inverters has changed the dynamics of modern power systems, posing new challenges to the safe and stable operation of the power grid. In the grid-following inverter that tracks the grid frequency through a phase-locked loop (PLL), due to the strong interaction between the fast dynamics of the new energy equipment IBR and the grid, subsynchronous oscillation problems may occur, which is particularly prominent in low short-circuit ratio grids. In addition, in actual wind farms and photovoltaic power plants, a certain proportion of reactive power compensation devices (SVG devices) are generally required to maintain node voltage stability. However, SVG devices and new energy equipment IBRs will also interact with each other, and even further aggravate the oscillation problem between the new energy equipment IBR and the grid.

[0003] SVG devices have complex interactions with renewable energy devices IBR through the power grid, especially in scenarios where multiple SVGs and multiple renewable energy devices IBR are considered under complex operating conditions. This makes it difficult to understand the impact mechanism of SVG on the oscillation problem caused by IBR. Most existing studies are based on impedance analysis methods and use the Nyquist stability criterion for small-disturbance stability analysis, which is based on the simplified SISO transfer function of the system and assumes that the system has no right-half-plane poles. However, this assumption is not always met. To avoid this problem, existing research works have proposed a method based on short-circuit ratio (SCR) from the perspective of grid strength to reveal how the interaction between SVG and IBR affects the small-disturbance stability of renewable energy grids containing SVG under rated operating conditions. It is worth noting that different operating conditions will change the equilibrium point of the system, thereby affecting the small-disturbance stability of the system. However, it is still unclear how different operating conditions will affect the interaction between SVG and IBR, as well as the small-disturbance stability of the system. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the existing power system stability analysis method has the problems of low prediction accuracy, low stability, poor ability to resist external interference, and inability to increase the adaptability of the power grid.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating the stability margin of a renewable energy multi-feedback power grid system containing multiple SVGs, comprising collecting SVG equipment data and power grid parameters; constructing a transfer function matrix of a renewable energy multi-feedback power grid system containing multiple SVGs under a power grid structure maintenance model based on operating condition changes; and revealing the effect of SVG on system interference stability through a short-circuit ratio analysis method.

[0007] As a preferred solution of the stability margin assessment method of a renewable energy multi-feed grid system containing multiple SVGs described in the present invention, wherein: the collected SVG equipment data and grid parameters include capacity and rated parameters, control parameters, real-time output data, admittance matrix, line and component parameters, topology, load data, power generation data, fault and event logs, system response data and historical stability event data;

[0008] The capacity and rated parameters include the maximum reactive power output, rated voltage and frequency of the SVG;

[0009] The control parameters include control strategy parameters of SVG, reactive power regulation ratio and integral gain;

[0010] The real-time output data includes reactive current output and active current output data of the SVG;

[0011] The admittance matrix includes admittance parameters of the power grid;

[0012] The circuit and component parameters include the impedance value of the circuit and the parameters of the transformer;

[0013] The topology includes node connections and line configurations;

[0014] The load data includes real-time load quantity or load forecast data of each load point;

[0015] The power generation data includes real-time power generation data and dispatch information of the power station;

[0016] The fault and event log includes all events and faults in the operation of the power grid;

[0017] The system response data includes the voltage, current and frequency of each node of the power grid during actual operation;

[0018] The historical stability event data includes detailed data of events experienced by the power grid.

[0019] As a preferred solution of the stability margin assessment method of a renewable energy multi-feed grid system containing multiple SVGs according to the present invention, wherein: the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure maintenance model based on the operating condition change includes establishing the admittance transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the operating condition change:

[0020]

[0021]

[0022] Where diag() represents a diagonal matrix; P ei and S Bsj represents the active power output of the i-th new energy device and the rated capacity of the j-th SVG device; I sqj represents the reactive current of the jth SVG device; Y 11 (s),Y 12 (s),Y 21 (s),Y 22 (s) indicates Y SVGj (s) is an element of the matrix and is related to the reactive current I qsj Not relevant; Y IBRi (s) and Y SVGj (s) represent the impedance-admittance matrix of the i-th new energy device and the j-th SVG device after being standardized based on their own rated capacity; B red ∈R (n+k)×(n+k) represents the node susceptance matrix including IBR nodes and SVG nodes; B 11 ∈R n×n ,B 12 ∈R n×k ,B 21 ∈R k×n ,B 22 ∈R k×k Indicates B red submatrix; τ = R / L represents the ratio of resistance R to inductance L, assuming that all network lines have the same ratio τ; ω 0 is the rated synchronous angular frequency.

[0023] As a preferred solution of the stability margin assessment method of a renewable energy multi-feed grid system containing multiple SVGs according to the present invention, the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure maintenance model based on the operating condition change includes, based on the Schur principle, the characteristic equation is equivalent to:

[0024]

[0025] Among them, I 2represents the identity matrix, det[C SVGs (s)] = 0 represents the system characteristic equation of k SVG devices connected to the grid, and the admittance matrix of the network is expressed as B 22 ;

[0026] Assuming that the instability of the renewable energy multi-feed grid system containing multiple SVGs is caused by the interaction between renewable energy and the network, the characteristic equation of the system is expressed as:

[0027]

[0028] Among them, I 2k represents the identity matrix;

[0029] In the frequency band and damping ratio range of interest, K s The spectral radius of (s) is less than 1. Based on the Neumann series theorem, {K s (s)+I 2k} -1 It can be approximately expressed as:

[0030] {K s (s)+I 2k} -1 ≈I 2k -K s (s)

[0031] Furthermore, the characteristic equation is equivalent to:

[0032]

[0033] Among them, Y sys (s) represents the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs; B redn represents the reduced-order network node admittance matrix retaining the new energy nodes; Represents the weight matrix of new energy equipment; Δ SVGs (s) represents the transfer function matrix associated with the dynamics and network of the SVG.

[0034] As a preferred solution of the stability margin assessment method of a renewable energy multi-feedback power grid system containing multiple SVGs described in the present invention, the transfer function matrix of the renewable energy multi-feedback power grid system containing multiple SVGs under the power grid structure maintenance model constructed based on the operating condition changes includes an equivalent equation of the output system based on the Schur principle, and then a single-feedback system is used to characterize the small-disturbance stability of the original system. Based on the short-circuit ratio analysis method, the system stability is between the stabilities of the n subsystems.

[0035] As a preferred solution of the stability margin assessment method of a renewable energy multi-feed grid system containing multiple SVGs described in the present invention, the short-circuit ratio analysis method is used to reveal the effect of SVG on the system interference stability, including using a single-feed system to characterize the small-disturbance stability of the original system. The single-feed system is represented as:

[0036]

[0037] Among them, C 1 (s) represents the closed-loop transfer function matrix of the system, λ 1 represents the minimum eigenvalue of the product of the capacity matrix and the extended admittance matrix, I 2 Represented as a 2nd-order identity matrix; Represents the dynamics of the device, which is the weighted sum of the dynamics of all IBR devices and SVG devices. 1i (i=1,…,n) and p 2j (j=1,…,k) represents the participation factor, u 1i and v 1i express and v 1 The i-th element of and v 1 express The minimum eigenvalue λ 1 The normalized left and right eigenvectors of sj A square matrix representing the position of the j-th SVG device, where the (n+j)-th diagonal element is 1 and the remaining elements are 0. Indicates the dynamics of IBR devices and SVG devices. Bsj Indicates the capacity of the jth SVG device;

[0038] When SVG devices have the same control parameters, It is expressed as:

[0039]

[0040] in, Can express the dynamics of SVG, p Σ and I qΣ Indicates the equipment capacity and reactive current output of SVG, p 2j Represents the weighted participation factor of the SVG device, I qsj represents the q-axis current output by the j-th SVG device;

[0041] When the control parameters of IBR and SVG are given, the short-circuit ratio of the system is The critical CSCR of the system in critical stable state is:

[0042]

[0043] Among them, arg{} represents the characteristic value output of CSCR, S c =j ωc represents the dominant characteristic root located on the imaginary axis in the complex plane, ω c represents the oscillation angular frequency;

[0044] Determine system stability based on the difference between CSCR and SCR;

[0045] When (SCR-CSCR)≥0, the system is stable;

[0046] And the (SCR-CSCR) value is proportional to the system stability;

[0047] When (SCR-CSCR)≤0, the system is unstable.

[0048] As a preferred solution of the stability margin assessment method of a renewable energy multi-feed grid system containing multiple SVGs according to the present invention, the short-circuit ratio analysis method is used to reveal the law of the effect of SVG on the system interference stability, including that when the operating conditions are given, the system stability is between the stabilities of n subsystems, and the small-disturbance robust stability problem of the renewable energy multi-feed grid system containing multiple SVGs under given operating conditions is the stability problem of n subsystems under given operating conditions;

[0049] The dynamic expression of n subsystems under given working conditions is:

[0050]

[0051] in, represents the admittance transfer function matrix of the SVG device, Y IBRi (s) represents the admittance transfer function matrix of the i-th new energy device,

[0052] n equivalent subsystems with different equipment dynamics and the same SCR;

[0053] In each subsystem, the equipment includes IBR and SVG in the system. IBR and SVG are parallel in each subsystem. The small disturbance stability margins of n subsystems are arranged in ascending order, subsystem 1,1,…subsystem 1,n. The system stability is between subsystem 1,1 and subsystem 1,n.

[0054] Another object of the present invention is to provide a stability margin assessment system for a renewable energy multi-feedback power grid system containing multiple SVGs, which can solve the problem of low stability in current power system stability analysis methods by constructing a transfer function matrix of a renewable energy multi-feedback power grid system containing multiple SVGs under a power grid structure retention model.

[0055] As a preferred solution of the stability margin assessment system of a new energy multi-feedback power grid system containing multiple SVGs described in the present invention, it includes: an initialization module, a closed-loop characteristic model construction module, and a power grid stability margin judgment module; the initialization module is used to collect the capacity and control parameters of the new energy equipment and the SVG equipment, the reactive current output of the SVG equipment and the admittance parameters of the AC power grid; the closed-loop characteristic model construction module is used to establish a closed-loop characteristic model of the stability of the new energy power grid according to the new energy power grid transfer function matrix; the power grid stability margin judgment module is used to judge the power grid stability margin by using the difference between the short-circuit ratio and the critical short-circuit ratio.

[0056] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs.

[0057] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs.

[0058] Beneficial effects of the present invention: The stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs provided by the present invention constructs a transfer function matrix of a renewable energy multi-feedback power grid system containing multiple SVGs under a power grid structure maintenance model based on changes in operating conditions, thereby improving the adaptability and flexibility of the power grid and the accuracy of prediction. By simulating the dynamic response of the power grid in real time, the utility of the SVG equipment is maximized without affecting the stability of the power grid, and the robustness of the power grid to various external interferences is enhanced. The effect of SVG on system interference stability is revealed through a short-circuit ratio analysis method, thereby improving the flexibility and safety of power grid design and operation. By precisely controlling the parameters of the SVG equipment, the stability of the power grid when facing large-scale renewable energy grid connection is ensured. The present invention achieves better results in terms of accuracy, stability and adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0060] Figure 1 The overall flow chart of a stability margin assessment method for a renewable energy multi-feed-in power grid system containing multiple SVGs provided in the first embodiment of the present invention.

[0061] Figure 2A logic block diagram of a stability margin assessment method for a renewable energy multi-feed-in power grid system containing multiple SVGs provided in the first embodiment of the present invention.

[0062] Figure 3 A schematic diagram of the modified IEEE 39-node system structure in a simulation verification of a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs provided in a second embodiment of the present invention.

[0063] Figure 4 The dominant eigenvalue trajectories of the modified IEEE 39-bus system and key subsystems in the simulation verification of a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs provided in the second embodiment of the present invention.

[0064] Figure 5 The time domain response of the active power output of IBR1 to IBR9 in the simulation verification of a stability margin assessment method for a renewable energy multi-feed-in power grid system containing multiple SVGs provided in the second embodiment of the present invention.

[0065] Figure 6 The overall flow chart of a stability margin assessment system for a renewable energy multi-feed-in power grid system including multiple SVGs provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0067] Example 1

[0068] Reference Figure 1 , which is an embodiment of the present invention, provides a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs, comprising:

[0069] S1: Collect SVG equipment data and power grid parameters.

[0070] Furthermore, the key data types that must be collected are:

[0071] 1. SVG device data

[0072] Capacity and rated parameters: including the maximum reactive power output, rated voltage and frequency of the SVG.

[0073] Control parameters: including SVG control strategy parameters, such as reactive power regulation proportion and integral gain, and other related dynamic regulation parameters.

[0074] Real-time output data: SVG's reactive current output and possible active current output data, which are critical for analyzing the impact of SVG on the power grid.

[0075] 2. Grid parameters

[0076] Admittance matrix: The admittance parameters of the entire power grid or relevant parts, which is the basis for analyzing the electrical behavior of the power grid.

[0077] Line and component parameters: including the impedance values ​​of all lines, the parameters of transformers, and the characteristics of any other electrical components that may affect the behavior of the power grid.

[0078] Topology: Structural data of the power grid, including node connections, line configuration, etc.

[0079] 3. Operation and environmental data

[0080] Load data: real-time load or load forecast data of each load point.

[0081] Power generation data: includes real-time power generation data and dispatch information of all power stations.

[0082] Fault and event log: records all important events and faults in power grid operation.

[0083] 4. Stability testing and historical data

[0084] System response data: response data such as voltage, current, frequency, etc. of each node in the power grid during a specific test or actual operation.

[0085] Historical stability event data: Detailed data on stability or instability events that the grid has experienced in the past, used to verify and optimize models.

[0086] S2: Based on the changes in operating conditions, the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure maintenance model is constructed.

[0087] Furthermore, considering the changes in operating conditions, a transfer function matrix of a renewable energy multi-feed grid system containing multiple SVGs is established under a grid structure maintenance model. Based on the transfer function matrix of the renewable energy grid, a closed-loop characteristic equation for the stability of the renewable energy grid is established. This requires collecting the capacity and control parameters of the renewable energy equipment and SVG equipment, the reactive current output of the SVG equipment, and the admittance parameters of the AC grid.

[0088] It should be noted that the admittance transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under changing operating conditions is established as:

[0089]

[0090]

[0091] Where diag() represents a diagonal matrix; P ei and S Bsj represents the active power output of the i-th new energy device and the rated capacity of the j-th SVG device; I sqj represents the reactive current of the jth SVG device; Y 11 (s),Y 12 (s),Y 21 (s),Y 22 (s) indicates Y SVGj (s) is an element of the matrix and is related to the reactive current I qsj Not relevant; Y IBRi (s) and Y SVGj (s) represent the impedance-admittance matrix of the i-th new energy device and the j-th SVG device after being standardized based on their own rated capacity; B red ∈R (n+k)×(n+k) represents the node susceptance matrix including IBR nodes and SVG nodes; B 11 ∈R n×n ,B 12 ∈R n×k ,B 21 ∈R k×n ,B 22 ∈R k×k Indicates B red submatrix; τ = R / L represents the ratio of resistance R to inductance L, assuming that all network lines have the same ratio τ; ω 0 is the rated synchronous angular frequency.

[0092] It should also be noted that based on Schur's principle, the characteristic equation is equivalent to:

[0093]

[0094] Among them, I 2 represents the identity matrix, det[C SVGs (s)] = 0 represents the system characteristic equation of k SVG devices connected to the grid, and the admittance matrix of the network is expressed as B 22 ;

[0095] Assuming that the instability of the renewable energy multi-feed grid system containing multiple SVGs is caused by the interaction between renewable energy and the network, the characteristic equation of the system is expressed as:

[0096]

[0097] Among them, I 2k represents the identity matrix;

[0098] In the frequency band and damping ratio range of interest, K s The spectral radius of (s) is less than 1. Based on the Neumann series theorem, {K s (s)+I 2k} -1 It can be approximately expressed as:

[0099] {K s (s)+I 2k} -1 ≈I 2k -K s (s)

[0100] Furthermore, the characteristic equation is equivalent to:

[0101]

[0102] Among them, Y sys (s) represents the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs; B redn represents the reduced-order network node admittance matrix retaining the new energy nodes; P e -1 B redn Represents the weight matrix of new energy equipment; Δ SVGs (s) represents the transfer function matrix associated with the dynamics and network of the SVG.

[0103] Based on the Schur principle, the equivalent equation of the system is output, and then the small disturbance stability of the original system is characterized by a single-feed system. Based on the short-circuit ratio analysis method, it can be seen that the system stability is between the stabilities of the n subsystems.

[0104] S3: The effect of SVG on system disturbance stability is revealed through the short-circuit ratio analysis method.

[0105] Furthermore, an equivalent system representing the stability of the original system was constructed, and the equivalent system was further equivalent to a single-feedback system, which clarified that the stability of the original system is between the stabilities of n subsystems. Based on the short-circuit ratio analysis method, the effect of SVG on the small disturbance stability of the system under complex working conditions was revealed.

[0106] It should be noted that the small disturbance stability of the original system is characterized by a single-feed system, which is expressed as:

[0107]

[0108] Among them, C 1 (s) represents the closed-loop transfer function matrix of the system, λ1 represents the minimum eigenvalue of the product of the capacity matrix and the extended admittance matrix, I 2 Represented as a 2nd-order identity matrix; Represents the dynamics of the device, which is the weighted sum of the dynamics of all IBR devices and SVG devices. 1i (i=1,…,n) and p 2j (j=1,…,k) represents the participation factor, u 1i and v 1i express and v 1 The i-th element of and v 1 express The minimum eigenvalue λ 1 The normalized left and right eigenvectors of sj A square matrix representing the position of the j-th SVG device, where the (n+j)-th diagonal element is 1 and the remaining elements are 0. Indicates the dynamics of IBR devices and SVG devices. Bsj Indicates the capacity of the jth SVG device;

[0109] When SVG devices have the same control parameters, It is expressed as:

[0110]

[0111] in, Can express the dynamics of SVG, p Σ and I qΣ Indicates the equipment capacity and reactive current output of SVG, p 2j Represents the weighted participation factor of the SVG device, I qsj represents the q-axis current output by the j-th SVG device;

[0112] When the control parameters of IBR and SVG are given, the short-circuit ratio of the system is The critical CSCR of the system in critical stable state is:

[0113]

[0114] Among them, arg{} represents the characteristic value output of CSCR, S c =j ωc represents the dominant characteristic root located on the imaginary axis in the complex plane, ω c represents the oscillation angular frequency;

[0115] Determine system stability based on the difference between CSCR and SCR;

[0116] When (SCR-CSCR)≥0, the system is stable;

[0117] And the (SCR-CSCR) value is proportional to the system stability;

[0118] When (SCR-CSCR)≤0, the system is unstable.

[0119] The short-circuit ratio analysis method is used to reveal the effect of SVG on system disturbance stability. The method includes that when the operating conditions are given, the system stability is between the stability of n subsystems, and the small disturbance robust stability problem of the renewable energy multi-feed grid system containing multiple SVGs under given operating conditions is the stability problem of n subsystems under given operating conditions.

[0120] The dynamic expression of n subsystems under given working conditions is:

[0121]

[0122] in, represents the admittance transfer function matrix of the SVG device, Y IBRi (s) represents the admittance transfer function matrix of the i-th new energy device,

[0123] n equivalent subsystems with different equipment dynamics and the same SCR;

[0124] In each subsystem, the equipment includes IBR and SVG in the system. IBR and SVG are parallel in each subsystem. The small disturbance stability margins of n subsystems are arranged in ascending order, subsystem 1,1,…subsystem 1,n. The system stability is between subsystem 1,1 and subsystem 1,n.

[0125] Example 2

[0126] Reference Figure 2-Figure 5 , which is an embodiment of the present invention, provides a stability margin assessment method for a renewable energy multi-feedback power grid system containing multiple SVGs. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0127] First, create a modified IEEE 39-node system in MATLAB / Simulink, as Figure 2 As shown, nodes 1 to 9 are connected to the new energy equipment IBR through transformers, and node 39 is connected to the external grid, which is simplified to an infinite busbar. Each IBR represents a wind farm. The IBR capacity is shown in Table 1. In practice, wind farms usually install a certain proportion of SVG for voltage support. Therefore, we install 30% of the capacity of SVG for each IBR on the high-voltage side in the modified IEEE 39-node system, as shown in Figure 2 The control parameters of IBR and SVG refer to Table 2 and Table 3.

[0128] Table 1 Rated capacity of IBR after standardization

[0129] IBR1 1 IBR2 2 IBR3 1 IBR4 1 IBR5 2 IBR6 10 IBR7 2 IBR8 2 IBR9 1

[0130] Table 2 Control parameters of IBR

[0131]

[0132] Table 3 SVG control parameters

[0133]

[0134]

[0135] In the modified IEEE 39-bus system, the effectiveness of the proposed SCR-based method is verified by eigenvalue analysis. In this system, all SVG devices use the same AC voltage control parameters (AVC), but the new energy equipment IBR adopts different control structures: IBR1~IBR3 adopt constant active power control, and other IBRs adopt DC voltage control. The detailed control parameters are shown in Table 2. The active power output of all new energy equipment IBRs is normalized at their rated capacity, and the normalized active power output is increased from 0.5pu to 1p.u, then the corresponding SCR of the system decreases from 3.36 to 1.68. At the same time, we compare the dominant eigenvalues ​​of the modified IEEE 39-bus system and its key subsystems, such as Figure 3 shown.

[0136] from Figure 3 It can be seen that when SCR changes from 3.36 to 1.68, the main eigenvalues ​​of the critical subsystems match the modified IEEE 39-bus system very well. This shows that the small signal stability of the renewable energy grid containing SVG can be represented by the small signal stability of the critical subsystems under different operating conditions.

[0137] also, Figure 3 It is shown that when the control parameters of IBR and SVG are given, SCR can evaluate the small signal stability of the modified 39-bus system under different operating conditions. Figure 3 As shown, CSCR is equal to 2.1. When SCR = CSCR, the system is in a critical stable state; when SCR> CSCR, the system is stable; in addition, the larger (SCR-CSCR), the more stable the system; otherwise, if SCR< CSCR, the system is unstable.

[0138] In addition, time-domain simulations were also carried out on the modified IEEE 39-bus system to verify the effectiveness of the proposed SCR-based method. When the active power outputs of all IBRs were set to 0.7 and 0.9 p.u., the corresponding SCRs were 2.404 and 1.87, respectively. In both cases, a disturbance was applied to the infinite bus at t = 1 s, resulting in a voltage drop of 0.05 p.u. and lasting for 0.05 s. Figure 4 The time-domain responses of the active power outputs of all IBRs in these two cases are given. As can be seen from Figure 4 , when SCR = 2.404 > 2.1 (i.e., the CSCR of the system), the system is stable. However, when SCR = 1.87 < CSCR, the system is unstable. The time-domain simulation results are consistent with the Figure 3 eigenvalue results. The effectiveness of the proposed SCR-based method is verified.

[0139] In summary, the present invention achieves better effects in terms of accuracy, stability, and adaptability.

[0140] Embodiment 3

[0141] Referring to Figure 6 , an embodiment of the present invention provides a stability margin evaluation system for a new energy multi-infeed power grid system with multiple SVG, including an initialization module, a closed-loop characteristic model construction module, and a power grid stability margin judgment module.

[0142] Among them, the initialization module is used to collect the capacities and control parameters of new energy devices and SVG devices, the reactive current outputs of SVG devices, and the admittance parameters of the AC power grid. The closed-loop characteristic model construction module is used to establish a closed-loop characteristic model of the stability of the new energy power grid according to the transfer function matrix of the new energy power grid. The power grid stability margin judgment module is used to judge the power grid stability margin by using the difference between the short-circuit ratio and the critical short-circuit ratio.

[0143] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. And the aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0144] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0145] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0146] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0147] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A stability margin assessment method for a renewable energy multi-feed grid system containing multiple SVGs, characterized in that: include: Collect SVG equipment data and power grid parameters; Based on the changes in operating conditions, the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure preservation model is constructed; The effect of SVG on system disturbance stability is revealed through the short-circuit ratio analysis method.

2. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 1, characterized in that: The collected SVG equipment data and grid parameters include capacity and rated parameters, control parameters, real-time output data, admittance matrix, line and component parameters, topology, load data, power generation data, fault and event logs, system response data, and historical stability event data; The capacity and rated parameters include the maximum reactive power output, rated voltage and frequency of the SVG; The control parameters include control strategy parameters of SVG, reactive power regulation ratio and integral gain; The real-time output data includes reactive current output and active current output data of the SVG; The admittance matrix includes admittance parameters of the power grid; The circuit and component parameters include the impedance value of the circuit and the parameters of the transformer; The topology includes node connections and line configurations; The load data includes real-time load quantity or load forecast data of each load point; The power generation data includes real-time power generation data and dispatch information of the power station; The fault and event log includes all events and faults in the operation of the power grid; The system response data includes the voltage, current and frequency of each node of the power grid during actual operation; The historical stability event data includes detailed data of events experienced by the power grid.

3. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 2, characterized in that: The constructing of the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure maintenance model based on the operating condition change includes establishing the admittance transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the operating condition change as follows: Where diag() represents a diagonal matrix; P ei and S Bsj represents the active power output of the i-th new energy device and the rated capacity of the j-th SVG device; I sqj represents the reactive current of the jth SVG device; Y 11 (s),Y 12 (s),Y 21 (s),Y 22 (s) indicates Y SVGj (s) is an element of the matrix and is related to the reactive current I qsj Not relevant; Y IBRi (s) and Y SVGj (s) represent the impedance-admittance matrix of the i-th new energy device and the j-th SVG device after being standardized based on their own rated capacity; B red ∈R (n+k)×(n+k) represents the node susceptance matrix including IBR nodes and SVG nodes; B 11 ∈R n×n ,B 12 ∈R n×k ,B 21 ∈R k×n ,B 22 ∈R k×k Indicates B red submatrix; τ = R / L represents the ratio of resistance R to inductance L, assuming that all network lines have the same ratio τ; ω0 is the rated synchronous angular frequency.

4. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 3, characterized in that: The transfer function matrix of the renewable energy multi-feed-in power grid system containing multiple SVGs under the power grid structure maintenance model based on the change of the operating conditions includes, based on the Schur principle, equating the characteristic equation to: Among them, I2 represents the identity matrix, det[C SVGs (s)] = 0 represents the system characteristic equation of k SVG devices connected to the grid, and the admittance matrix of the network is expressed as B 22 ; Assuming that the instability of the renewable energy multi-feed grid system containing multiple SVGs is caused by the interaction between renewable energy and the network, the characteristic equation of the system is expressed as: Among them, I 2k represents the identity matrix; In the frequency band and damping ratio range of interest, K s The spectral radius of (s) is less than 1. Based on the Neumann series theorem, {K s (s)+I 2k } -1 It can be approximately expressed as: {K s (s)+I 2k } -1 ≈I 2k -K s (s) Furthermore, the characteristic equation is equivalent to: Among them, Y sys (s) represents the transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs; B redn represents the reduced-order network node admittance matrix retaining the new energy nodes; Represents the weight matrix of new energy equipment; Δ SVGs (s) represents the transfer function matrix associated with the dynamics and network of the SVG.

5. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 4, characterized in that: The transfer function matrix of the renewable energy multi-feed grid system containing multiple SVGs under the grid structure maintenance model constructed based on the change of operating conditions includes an equivalent equation of the output system based on the Schur principle, and then a single-feed system is used to characterize the small disturbance stability of the original system. Based on the short-circuit ratio analysis method, the system stability is between the stabilities of the n subsystems.

6. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 5, characterized in that: The short-circuit ratio analysis method is used to reveal the effect of SVG on the system interference stability, including using a single-feed system to characterize the small-interference stability of the original system. The single-feed system is expressed as: Where C1(s) represents the closed-loop transfer function matrix of the system, λ1 represents the minimum eigenvalue of the product of the capacity matrix and the extended admittance matrix, and I2 represents the second-order unit matrix; Represents the dynamics of the device, which is the weighted sum of the dynamics of all IBR devices and SVG devices. 1i (i=1,…,n) and p 2j (j=1,…,k) represents the participation factor, u 1i and v 1i express and the i-th element of v1, and v1 indicates The normalized left and right eigenvectors of the minimum eigenvalue λ1, E sj A square matrix representing the position of the j-th SVG device, where the (n+j)-th diagonal element is 1 and the remaining elements are 0. Indicates the dynamics of IBR devices and SVG devices. Bsj Indicates the capacity of the jth SVG device; When SVG devices have the same control parameters, It is expressed as: in, Can express the dynamics of SVG, p Σ and I qΣ Indicates the equipment capacity and reactive current output of SVG, p 2j Represents the weighted participation factor of the SVG device, I qsj represents the q-axis current output by the j-th SVG device; When the control parameters of IBR and SVG are given, the short-circuit ratio of the system is The critical CSCR of the system in critical stable state is: Among them, arg{} represents the characteristic value output of CSCR, S c =j ωc represents the dominant characteristic root located on the imaginary axis in the complex plane, ω c represents the oscillation angular frequency; Determine system stability based on the difference between CSCR and SCR; When (SCR-CSCR)≥0, the system is stable; And the (SCR-CSCR) value is proportional to the system stability; When (SCR-CSCR)≤0, the system is unstable.

7. The method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in claim 6, characterized in that: The short-circuit ratio analysis method is used to reveal the effect of SVG on system disturbance stability. The method includes that when the operating conditions are given, the system stability is between the stability of n subsystems, and the small disturbance robust stability problem of the renewable energy multi-feed grid system containing multiple SVGs under given operating conditions is the stability problem of n subsystems under given operating conditions. The dynamic expression of n subsystems under given working conditions is: in, represents the admittance transfer function matrix of the SVG device, Y IBRi (s) represents the admittance transfer function matrix of the i-th new energy device, n equivalent subsystems with different equipment dynamics and the same SCR; In each subsystem, the equipment includes IBR and SVG in the system. IBR and SVG are parallel in each subsystem. The small disturbance stability margins of n subsystems are arranged in ascending order, subsystem 1,1,…subsystem 1,n. The system stability is between subsystem 1,1 and subsystem 1,n.

8. A system using the method for evaluating stability margin of a renewable energy multi-feed power grid system containing multiple SVGs as claimed in any one of claims 1 to 7, characterized in that: It includes initialization module, closed-loop characteristic model building module, and power grid stability margin judgment module; The initialization module is used to collect the capacity and control parameters of the new energy equipment and the SVG equipment, the reactive current output of the SVG equipment and the admittance parameters of the AC power grid; The closed-loop characteristic model building module is used to establish a closed-loop characteristic model of the stability of the new energy power grid according to the new energy power grid transfer function matrix; The grid stability margin judgment module is used to judge the grid stability margin by using the difference between the short circuit ratio and the critical short circuit ratio.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for evaluating the stability margin of a renewable energy multi-feedback power grid system containing multiple SVGs according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the stability margin of a renewable energy multi-feedback power grid system containing multiple SVGs according to any one of claims 1 to 7 are implemented.

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