Grid strength constraint based grid-forming / grid-following switchable converter switching control method and system

Abstract

This invention provides a switching control method and system for grid-connected / grid-aligned switchable converters based on grid strength constraints. The method includes determining grid strength and constructing a transfer function for renewable energy power plants to divide the renewable energy power system's operating state into three states. Under a strongly stable state and while satisfying grid strength constraints, the original control mode remains unchanged. Under weakly stable and unstable states, with the switching and operating costs of grid-connected / grid-aligned switchable converters and the reliability of the renewable energy power system as objective functions, the NSGA-II algorithm is used for optimization control to obtain the Pareto optimal solution set. This allows adjustment of the number of grid-connected / grid-aligned switchable converters in different operating modes, thereby achieving switching between the operating modes of the grid-connected / grid-aligned switchable converters. This invention considers the real-time changes in grid strength, ensuring the stability of the renewable energy power system while also taking into account economy and reliability.

Description

Technical Field

[0001] This invention belongs to the field of new energy power generation control technology, and in particular relates to a switching control method and system for grid-connected / grid-linked switchable converters based on grid strength constraints. Background Technology

[0002] To address the insufficient voltage and frequency support in renewable energy power systems primarily based on grid-following converters, the current mainstream research trend is to introduce grid-forming converters into the system, constructing a hybrid grid-following (GFL) and grid-forming (GFM) system to enhance the support capacity of renewable energy power systems and ensure their safe and reliable operation.

[0003] The relevant technologies primarily enhance the support capabilities of renewable energy power systems by introducing hybrid systems that combine grid-connected converters with traditional grid-following converters. Traditional renewable energy power plants mainly use grid-following converters, which rely on the phase and amplitude of the grid voltage for follow-up control, lacking autonomous adjustment capabilities and prone to voltage / frequency instability when the grid strength is weak. GFM converters, by simulating the characteristics of synchronous generators, actively provide inertial and damping support: in terms of voltage support, GFM autonomously adjusts reactive power output through reactive power-voltage droop control to maintain the grid connection point voltage; in terms of frequency support, it employs active power-frequency droop control or virtual synchronous machine algorithms to respond to frequency fluctuations by adjusting active power output. This hybrid system endows renewable energy equipment with "quasi-synchronous machine" active support functions, significantly improving stability under weak grid conditions.

[0004] However, existing technologies mostly adopt a fixed GFL-GFM configuration ratio, without considering the impact of real-time changes in grid intensity (improved short-circuit ratio characterization) on stability margin. In low short-circuit ratio scenarios, if the GFM ratio is insufficient, the voltage / frequency support capacity of the renewable energy power system will be mismatched with the stability margin requirements, which may easily lead to small-signal instability (such as subsynchronous oscillation) or voltage collapse. On the other hand, when the grid intensity suddenly increases, excessive GFM input may lead to equipment overload and a surge in losses, forming a vicious cycle of "over-support - high cost". Moreover, the lack of overall planning for multi-objective optimization such as economic efficiency restricts the operational efficiency of renewable energy power systems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a switching control method and system for grid-connected / grid-linked switchable converters based on grid strength constraints.

[0006] In a first aspect, the present invention provides a switching control method for a grid-connected / grid-linked switchable converter based on grid strength constraints, comprising:

[0007] The active power output of each grid-connected converter at the new energy power plant, the active power output of each grid-connected / grid-connected switchable converter under GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter under GFM control mode are obtained to determine the grid strength.

[0008] Construct the transfer function for new energy power plants;

[0009] Based on grid strength and the transfer function of new energy power stations, the operating state of new energy power systems is divided into strong stable state, weak stable state and unstable state.

[0010] Under strong stability and when the power grid strength constraint is met, the original control mode remains unchanged;

[0011] Under weakly stable and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, the NSGA-II algorithm is used for optimization control to obtain the Pareto optimal solution set.

[0012] The number of grid-connected / grid-connected switchable converters in different operating modes is adjusted according to the Pareto optimal solution set to achieve switching of the operating modes of the grid-connected / grid-connected switchable converters.

[0013] Optionally, the step of obtaining the active power output of each grid-connected converter at the renewable energy power plant, the active power output of each grid-connected / grid-connected switchable converter in GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter in GFM control mode to determine the grid strength includes:

[0014] Calculate the grid strength MSCR using the following formula:

[0015]

[0016] Where Z represents the equivalent series impedance of the grid side as an ideal voltage source; |Z * | Represents the value of the equivalent impedance of the new energy power system after being standardized per unit based on the reference capacity of the new energy power station; S N Rated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_j P represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; P GFM_SC_kThe active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

[0017] Optionally, the construction of the transfer function for the new energy power station includes:

[0018] Constructing the transfer function Y of the new energy power station sys,0 The expression for (s):

[0019]

[0020]

[0021] Where diag(·) denotes a diagonal matrix; S B,i' Y is the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i'=1,2,…,n+p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode after scaling by its own capacity per unit; s is the Laplace operator; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; B is the node admittance matrix after Kron transform to eliminate internal passive nodes; ω0 is the angular velocity at the power frequency; τ is the ratio of line resistance to inductance.

[0022] Optionally, the step of classifying the operating state of the new energy power system into strongly stable, weakly stable, and unstable states based on grid strength and the transfer function of new energy power plants includes:

[0023] When MSCR_up≤MSCR and Re(λ(Y) is satisfied sys,0 When (s)))<0, the operating state of the new energy power system is classified as a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the strongly stable state of the new energy power system; Re(·) represents the operation of taking the real part; MSCR is the grid strength; λ(·) represents the operation of taking the characteristic roots; Y sys,0 (s) is the transfer function of the new energy power station;

[0024] When MSCR_down<MSCR<MSCR_up and Re(λ(Y sys,0When (s)))<0, the operating state of the new energy power system is classified as a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system;

[0025] When MSCR ≤ MSCR_down or Re(λ(Y) is satisfied sys,0 When (s)))≥0, the operating state of the new energy power system is classified as an unstable state.

[0026] Optionally, under weakly stable and unstable states, the NSGA-II algorithm is used for optimization control with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions to obtain the Pareto optimal solution set, including:

[0027] Construct the objective function for switching and operating costs of grid-connected / grid-connected switchable converters:

[0028]

[0029] Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter.

[0030] Construct the reliability objective function for the new energy power system:

[0031] f2=K2|Re(λ domin (Y sys,0 (s)))|;

[0032] Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin(·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station;

[0033] Construct the fitness function F for the new energy power system:

[0034] F=(ω1·exp(-f1)+ω2·f2)·γ1·γ2;

[0035] γ1=exp(-μ·max(MSCR_up-MSCR,0));

[0036]

[0037] Where ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is an exponential function with the natural constant as the base; γ1 is the penalty function of grid constraints; μ is the grid constraint penalty coefficient; MSCR_up represents the maximum short-circuit ratio threshold of the strong stability state of the new energy power system; MSCR is the grid strength; γ2 is the penalty function of small-signal stability constraints; Re(·) represents the operation of taking the real part; λ(·) represents the operation of taking the eigenvalues; Y sys,0 (s) is the transfer function of the new energy power station;

[0038] The number of switchable converters p in GFL control mode and the number of switchable converters q in GFM control mode are used as individuals [p, q] in the initial population;

[0039] Calculate the objective function value for each individual [p, q] in the initial population, and calculate the penalty function for each individual [p, q] to determine the fitness function for each individual [p, q].

[0040] Based on the fitness function of each individual [p, q] and using the NSGA-II algorithm for optimization control, the Pareto optimal solution set is obtained.

[0041] Secondly, the present invention provides a grid-connected / grid-linked switchable converter switching control system based on grid strength constraints, comprising:

[0042] The first determining module is used to obtain the active power output of each grid-connected converter in the new energy power station, the active power output of each grid-connected / grid-connected switchable converter in GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter in GFM control mode, so as to determine the grid strength.

[0043] The module is used to build the transfer function of the new energy power station;

[0044] The partitioning module is used to classify the operating state of the new energy power system into strong stable state, weak stable state and unstable state based on the grid strength and the transfer function of the new energy power station.

[0045] The second determining module is used to maintain the original control mode unchanged under strong stability and when the power grid strength constraint is met;

[0046] The optimization module is used to optimize control under weak and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, and uses the NSGA-II algorithm to obtain the Pareto optimal solution set.

[0047] The switching module is used to adjust the number of grid-connected / grid-connected switchable converters in different operating modes according to the Pareto optimal solution set, so as to realize the switching of the operating modes of the grid-connected / grid-connected switchable converters.

[0048] Optionally, the first determining module includes:

[0049] The first calculation unit is used to calculate the grid strength MSCR according to the following formula:

[0050]

[0051] Where Z represents the equivalent series impedance of the grid side as an ideal voltage source; |Z * | Represents the value of the equivalent impedance of the new energy power system after being standardized per unit based on the reference capacity of the new energy power station; S N Rated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_j P represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; P GFM_SC_k The active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

[0052] Optionally, the building module includes:

[0053] The first building unit is used to construct the transfer function Y of the new energy power station. sys,0 The expression for (s):

[0054]

[0055]

[0056] Where diag(·) denotes a diagonal matrix; S B,i' Y is the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i'=1,2,…,n+p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode after scaling by its own capacity per unit; s is the Laplace operator; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; B is the node admittance matrix after Kron transform to eliminate internal passive nodes; ω0 is the angular velocity at the power frequency; τ is the ratio of line resistance to inductance.

[0057] Optionally, the partitioning module includes:

[0058] The first partitioning unit is used when MSCR_up≤MSCR and Re(λ(Y) is satisfied. sys,0 When (s)))<0, the operating state of the new energy power system is classified as a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the strongly stable state of the new energy power system; Re(·) represents the operation of taking the real part; MSCR is the grid strength; λ(·) represents the operation of taking the characteristic roots; Y sys,0 (s) is the transfer function of the new energy power station;

[0059] The second partitioning unit is used when MSCR_down < MSCR < MSCR_up and Re(λ(Y) sys,0 When (s)))<0, the operating state of the new energy power system is classified as a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system;

[0060] The third partitioning unit is used when MSCR ≤ MSCR_down or Re(λ(Y) is satisfied. sys,0 When (s)))≥0, the operating state of the new energy power system is classified as an unstable state.

[0061] Optionally, the optimization module includes:

[0062] The second building unit is used to construct the objective function for the switching and operating costs of the grid-connected / grid-connected switchable converter:

[0063]

[0064] Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter.

[0065] The third building unit is used to construct the reliability objective function of the new energy power system:

[0066] f2=K2|Re(λ domin (Y sys,0 (s)))|;

[0067] Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin (·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station;

[0068] The fourth building block is used to construct the fitness function F of the new energy power system:

[0069] F=(ω1·exp(-f1)+ω2·f2)·γ1·γ2;

[0070] γ1=exp(-μ·max(MSCR_up-MSCR,0));

[0071]

[0072] Where ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is an exponential function with the natural constant as the base; γ1 is the penalty function of grid constraints; μ is the grid constraint penalty coefficient; MSCR_up represents the maximum short-circuit ratio threshold of the strong stability state of the new energy power system; MSCR is the grid strength; γ2 is the penalty function of small-signal stability constraints; Re(·) represents the operation of taking the real part; λ(·) represents the operation of taking the eigenvalues; Y sys,0 (s) is the transfer function of the new energy power station;

[0073] The determination unit is used to take the number of network-connecting / following switchable converters p in GFL control mode and the number of network-connecting / following switchable converters q in GFM control mode as individuals [p, q] in the initial population;

[0074] The computational unit is used to calculate the objective function value of each individual [p, q] in the initial population and to calculate the penalty function of each individual [p, q] to determine the fitness function of each individual [p, q].

[0075] The optimization unit is used to perform optimization control based on the fitness function of each individual [p, q] and the NSGA-II algorithm to obtain the Pareto optimal solution set.

[0076] This invention provides a switching control method and system for grid-connected / grid-connected switchable converters based on grid strength constraints. The method uses the short-circuit ratio to characterize grid strength, which effectively reflects the real-time changes in grid strength caused by the volatility of renewable energy power plants. This invention achieves multi-objective optimization based on the NSGA-II algorithm, which can take into account other optimization objectives such as economy and reliability while ensuring the stability of the renewable energy power system. Attached Figure Description

[0077] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0078] Figure 1 A flowchart illustrating a grid-connected / grid-connected switchable converter switching control method based on grid strength constraints, provided for an embodiment of the present invention;

[0079] Figure 2 This is a schematic diagram of a small signal model established based on a new energy power station, provided as an embodiment of the present invention.

[0080] Figure 3 A control block diagram of GFL / GFM-SC provided in an embodiment of the present invention;

[0081] Figure 4 This is a schematic diagram of a grid-connected / grid-connected switchable converter switching control system based on grid strength constraints, provided as an embodiment of the present invention. Detailed Implementation

[0082] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0083] This invention addresses the scenario of new energy power plants containing grid-following and grid-forming switchable wind-storage converters. The new energy power plant contains a total of n+m converters, of which n are grid-following converters, m are grid-following / grid-forming switchable wind-storage converters (GFL / GFM-SC), p are in GFL control mode, and q are in GFM control mode.

[0084] Example 1

[0085] like Figure 1 As shown, this embodiment of the invention provides a switching control method for a grid-connected / grid-linked switchable converter based on grid strength constraints, comprising:

[0086] Step 101: Obtain the active power output of each grid-connected converter at the new energy power station, the active power output of each grid-connected / grid-connected switchable converter under GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter under GFM control mode to determine the grid strength.

[0087] In this step, the Modified Short Circuit Ratio (MSCR) is used to characterize changes in grid strength. For example, the grid strength MSCR is calculated according to the following formula:

[0088]

[0089] Where Z represents the equivalent series impedance of the grid side as an ideal voltage source; |Z * | Represents the value of the equivalent impedance of the new energy power system after being standardized per unit based on the reference capacity of the new energy power station; S NRated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_j P represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; P GFM_SC_k The active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

[0090] Step 102: Construct the transfer function for the new energy power station.

[0091] This embodiment employs a layered control system—equipment layer, control layer, and execution layer—to control the switching of m grid-connected / grid-linked switchable converters in a renewable energy power station. The control layer establishes the transfer function (full-order model) of the renewable energy power station based on the data obtained in step 101.

[0092] In the renewable energy power plant, n+p converters are in GFL control mode, and q converters are in GFM control mode. Nodes 1 to n+p are the connection nodes for converters in GFL control mode, and nodes n+p+1 to n+p+q are the connection nodes for converters in GFM control mode. The receiving-end grid can be considered as an ideal voltage source. The receiving-end grid is equivalently measured using Thevenin, and the equivalent impedance is allocated to the AC network side of the renewable energy power system. The dynamic models of these two parts are established below to form the full-order model of the renewable energy power plant.

[0093] First, a dynamic model of the AC network side is established. In the global xy coordinate system, the dynamic model of the AC network side can be expressed as: (taking the current flowing into the node as positive):

[0094]

[0095] Among them, U xy =[U x1 U y1 U x2 U y2 ... U x(n+p+q) U y(n+p+q) ] T ;U xy U represents a column vector composed of the x-axis and y-axis components of the voltages at all nodes in the new energy power system; xd and U yd These are the x-axis and y-axis components of the voltage at node d, respectively; I xy This represents a column vector consisting of the x-axis and y-axis components of the injected current at all nodes of the new energy power system; Ixy =[I x1 I y1 I x2 I y2 ... I x(n+p+q) I y(n+p+q) ] T ;I xd and I yd Let x and y be the current components injected into node d, respectively; T represents the transpose of the matrix; Δ represents the variable increment; and B is the node admittance matrix after Kron transformation to eliminate internal passive nodes. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; s is the Laplace operator; ω0 is the angular velocity at the operating frequency, ω0=2πf0; f0 is the rated frequency of the system; τ is the ratio of line resistance to inductance.

[0096] Secondly, a dynamic model of the equipment side of the new energy power station is established, which can be represented as:

[0097]

[0098] For example, the transfer function Y of the new energy power station is constructed based on the dynamic model established on the AC network side and the dynamic model established on the new energy power station equipment side. sys,0 The expression for (s):

[0099]

[0100] Where diag(·) denotes a diagonal matrix; S B,i' Y is the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i'=1,2,…,n+p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode, scaled down to its own capacity per unit; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting.

[0101] This model yields the small-signal stability criterion for the system:

[0102] Re(λ(Y sys,0 (s)))<0.

[0103] λ(Y sys,0 (s) represents the characteristic roots of the transfer function of the new energy power station; Re(·) represents the operation of taking the real part.

[0104] Step 103: Based on the grid strength and the transfer function of the new energy power station, the operating state of the new energy power system is divided into a strong stable state, a weak stable state, and an unstable state.

[0105] The control layer calculates power grid strength indicators based on the collected data and establishes a small-signal model for new energy power plants, such as... Figure 2 As shown, the small-signal stability criterion is obtained. Combining the two judgment index formulas, the new energy power system is divided into three operating states: strong stability, weak stability, and unstable.

[0106] For example, when MSCR_up≤MSCR and Re(λ(Y) sys,0 When (s)))<0, the operating state of the new energy power system is classified as a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the strongly stable state of the new energy power system; MSCR is the grid strength; λ(·) represents the characteristic root operation; Y sys,0 (s) is the transfer function of the new energy power station.

[0107] When MSCR_down<MSCR<MSCR_up and Re(λ(Y sys,0 When (s)))<0, the operating state of the new energy power system is classified as a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system.

[0108] When MSCR ≤ MSCR_down or Re(λ(Y) is satisfied sys,0 When (s)))≥0, the operating state of the new energy power system is classified as an unstable state.

[0109] Step 104: Under strong stability and when the power grid strength constraint is met, maintain the original control mode unchanged.

[0110] Step 105: Under weakly stable and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, the NSGA-II algorithm is used for optimization control to obtain the Pareto optimal solution set.

[0111] After obtaining the Pareto optimal solution set based on the different states of the power grid, the NSGA-II algorithm selects the globally optimal control strategy and sends it to the execution layer station controller for action.

[0112] For example, construct the objective function for switching and operating costs of grid-connected / grid-connected switchable converters:

[0113]

[0114] Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter.

[0115] Construct the reliability objective function for the new energy power system:

[0116] f2=K2|Re(λ domin (Y sys,0 (s)))|.

[0117] Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin (·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station.

[0118] New energy power systems exist in both weakly stable and unstable states, and optimization aims at strong stability. Therefore, the constraint function should have the ability to transition the new energy power system to a strongly stable state. Consider using a penalty function method to constrain grid strength and small-signal stability, integrating the constraint function into the objective function. The penalty function for grid constraints is as follows:

[0119] γ1=exp(-μ·max(MSCR_up-MSCR,0)).

[0120] The penalty function for small-signal stability constraints is:

[0121]

[0122] Based on the control strategy requirements, the fitness function F of the new energy power system is constructed as follows:

[0123] F=(ω1·exp(-f1)+ω2·f2)·γ1·γ2.

[0124] Wherein, ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is the exponential function with the natural constant as the base; γ1 is the penalty function for grid constraints; μ is the grid constraint penalty coefficient; γ2 is the penalty function for small-signal stability constraints; different weights are selected according to different operating states of the new energy power system. In the weakly stable state, the balance is considered to improve the economy and anti-interference capability of the new energy power system. In the unstable state, the main consideration is to improve the stability of the new energy power system, so the weights can be set as follows: ω1=ω2=0.5, representing weak stability; ω1=0.1, ω2=0.9, representing unstable state.

[0125] Initialize the population by randomly generating an initial population P0 of N individuals, each individual consisting of a series of decision variables; use the number p of the network-connecting / following switchable converters in GFL control mode and the number q of the network-connecting / following switchable converters in GFM control mode as the individuals [p, q] of the initial population.

[0126] Calculate the objective function value for each individual [p, q] in the initial population, and calculate the penalty function for each individual [p, q] to determine the fitness function for each individual [p, q].

[0127] Based on the fitness function of each individual [p, q] and using the NSGA-II algorithm for optimization control, the Pareto optimal solution set is obtained.

[0128] The next generation of the population is selected from the non-dominated hierarchies, prioritizing the retention of all solutions from the first few subsets to maintain population quality. Within the same subset, partial decomposition is selected based on crowding distance to promote population diversity.

[0129] For each objective function value, sort them, set the crowding degree of the boundary individuals to infinity, and calculate the crowding degree of the intermediate individuals as shown in equation (22):

[0130]

[0131] Among them, CD i″ This indicates the crowding level of the intermediate individual "i". The maximum target value for the current layer k'; f is the minimum objective value for the current layer k'; k′ (i″+1) represents the target value of the right-hand adjacent individual of the middle individual i″ in the current layer k'; f k′ (i″-1) represents the target value of the individual to the left of the middle individual i″ in the current layer k'.

[0132] Selecting superior individuals from a combined parent and offspring population:

[0133] 1) Prioritize individuals with lower non-dominant levels.

[0134] 2) Select individuals with high crowding in the same layer to ensure the diversity of the solution set.

[0135] 3) Retain the best individuals from the parent generation to prevent the loss of superior genes.

[0136] Crossover and mutation:

[0137] Crossover operations combine two parent solutions to generate new child solutions, while mutation operations create diversity by introducing subtle random changes to the decision-making processes of individuals.

[0138] Forming a new generation of population and iterating repeatedly:

[0139] Merge the parent and offspring populations, retain the top N best individuals, check if the preset termination condition has been met, such as the maximum number of iterations or a specific convergence criterion, and output the Pareto optimal solution set. If not, recalculate the fitness function for each individual [p, q] to continue the evolutionary process.

[0140] Step 106: Adjust the number of grid-connected / grid-connected switchable converters in different operating modes according to the Pareto optimal solution set, so as to realize the switching of the operating modes of the grid-connected / grid-connected switchable converters.

[0141] The execution layer controller operates according to the control signals from the control layer, enabling the switching of some GFL / GFM-SC operating modes.

[0142] The main difference between the two control modes lies in the method of phase angle acquisition. When GFL / GFM-SC adopts grid-following control mode, its phase angle is obtained by sampling from the grid connection point using a phase-locked loop (PLL). When switching to grid-connected (virtual synchronous control) control mode, the voltage amplitude and phase reference values ​​are generated by PQ control through simulating the rotor motion equation of a synchronous generator. Therefore, the main difference between the two control modes lies in the outer loop control, while the mathematical model of the inner loop control remains the same. This invention uses current closed-loop control. Upon receiving a switching command, different outer loop control methods are switched to change the converter control mode, such as... Figure 3 As shown.

[0143]

[0144] In the formula, u dref This is the reference value for the d-axis voltage output of the inverter; i dref This is the reference value for the d-axis current output of the inverter; u qref This is the reference value for the q-axis voltage output of the inverter; i qrefThis is the reference value for the q-axis current output by the inverter; k p3 k i3 k p4 and k i4 These are all parameters of the PI controller; i d and i q These are the d-axis and q-axis components of the current at the PCC point, respectively; u gd and u gq ω represents the d-axis and q-axis components of the voltage at point PCC, respectively; ω represents the angular velocity; and L represents the filter inductance.

[0145] Outer loop control:

[0146] (1) GFL outer loop control:

[0147]

[0148] in, P represents angular velocity; ref Q is the reference value for the active power output of the inverter; ref P is the reference value of the reactive power output of the inverter; Q is the actual value of the active power output of the inverter; k is the actual value of the reactive power output of the inverter; ppll k p1 k i2 k p2 and k i2 These are all parameters of the PI controller.

[0149] (2) GFM outer loop control:

[0150]

[0151] Where θ is the phase angle of the GFM output voltage; ω′0 is the equivalent virtual synchronous operation rated angular velocity; U0 is the voltage rating; J is the virtual synchronous machine rotor inertia coefficient; K D K is the virtual synchronous damping coefficient. Q k is the reactive power control coefficient. p5 k i5 k p6 and k i6 These are all parameters of the PI controller.

[0152] To reduce switching disturbances in the GFL / GFM-SC, this embodiment employs two measures: integrator sampling to follow the steady-state operating point and GFM pre-synchronization. Specifically, an external integrator reset is used to track the current operating point of the GFL / GFM-SC. When the control layer issues a switching command, the reference current value I output by the outer loop of the current controller of the GFL / GFM-SC is... dref and I qrefSampling is performed, and the sampled values ​​are assigned to the integrator of the control loop to be put into operation, so as to ensure that the controller to be put into operation tracks the current operating status of the converter.

[0153] When switching to grid-based control, which uses a self-synchronization mechanism to obtain the phase, the voltage and reference phase output by the virtual synchronization control cannot keep up with the actual grid values ​​at the moment of mode switching. Therefore, a voltage and phase pre-synchronization stage is set up. The mathematical model is as follows, and the control block diagram is as follows. Figure 3 As shown.

[0154]

[0155] In the formula, θ pll To ensure the PLL follows the grid phase; θ GFM The virtual synchronous output phase for grid connection; U is the actual value of the grid connection point voltage; U GFM To construct a virtual synchronous output voltage for the network; k up k ui k wp and k wi These are all parameters of the PI controller. This enables virtual synchronous control, allowing the output voltage and reference phase to track the actual operating conditions of the system in real time. This facilitates the switching between GFL and GFM modes.

[0156] In summary, the grid-connected / grid-connected switchable converter switching control method provided in this embodiment, based on grid strength constraints, uses an improved short-circuit ratio to characterize grid strength, effectively reflecting the real-time changes in grid strength caused by the volatility of new energy power plants (primarily wind / solar). Meanwhile, traditional hybrid control systems composed of grid-connected / grid-connected converters cannot respond to changes in grid strength in real time, leading to potential instability risks. This embodiment employs a grid-connected / grid-connected switchable energy storage converter, reducing potential stability issues. Finally, traditional control methods are often single-objective optimization problems with stability as the objective function. The decision module in this embodiment is a multi-objective optimization based on the NSGA-II algorithm, which, while ensuring system stability, also considers other optimization objectives such as economy and reliability.

[0157] Example 2

[0158] Based on the same inventive concept as Embodiment 1, this embodiment provides a grid-connected / grid-connected switchable converter switching control system based on grid strength constraints. Since the principle of this system in solving the problem is similar to the grid-connected / grid-connected switchable converter switching control method based on grid strength constraints provided in Embodiment 1, the implementation of this system can refer to the implementation of the grid-connected / grid-connected switchable converter switching control method based on grid strength constraints provided in Embodiment 1.

[0159] like Figure 4As shown, the grid-connected / grid-linked switchable converter switching control system based on grid strength constraints includes:

[0160] The first determining module 10 is used to obtain the active power output of each grid-connected converter in the new energy power station, the active power output of each grid-connected / grid-connected switchable converter in GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter in GFM control mode, so as to determine the grid strength.

[0161] Module 20 is used to construct the transfer function for new energy power plants.

[0162] The partitioning module 30 is used to divide the operating state of the new energy power system into strong stable state, weak stable state and unstable state according to the grid strength and the transfer function of the new energy power station.

[0163] The second determining module 40 is used to maintain the original control mode unchanged under strong stability and when the power grid strength constraint is met.

[0164] Optimization module 50 is used to perform optimization control under weak and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, and to obtain the Pareto optimal solution set by using the NSGA-II algorithm.

[0165] The switching module 60 is used to adjust the number of grid-connected / grid-connected switchable converters in different operating modes according to the Pareto optimal solution set, so as to realize the switching of the operating modes of the grid-connected / grid-connected switchable converters.

[0166] For example, the first determining module includes:

[0167] The first calculation unit is used to calculate the grid strength MSCR according to the following formula:

[0168]

[0169] Where Z represents the equivalent series impedance of the grid side as an ideal voltage source; |Z * | Represents the value of the equivalent impedance of the new energy power system after being standardized per unit based on the reference capacity of the new energy power station; S N Rated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_jP represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; P GFM_SC_k The active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

[0170] For example, the building module includes:

[0171] The first building unit is used to construct the transfer function Y of the new energy power station. sys,0 The expression for (s):

[0172]

[0173] Where diag(·) denotes a diagonal matrix; S B,i' Y is the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i'=1,2,…,n+p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode after scaling by its own capacity per unit; s is the Laplace operator; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; B is the node admittance matrix after Kron transform to eliminate internal passive nodes; ω0 is the angular velocity at the power frequency; τ is the ratio of line resistance to inductance.

[0174] For example, the partitioning module includes:

[0175] The first partitioning unit is used when MSCR_up≤MSCR and Re(λ(Y) is satisfied. sys,0 When (s)))<0, the operating state of the new energy power system is classified as a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the strongly stable state of the new energy power system; Re(·) represents the operation of taking the real part; MSCR is the grid strength; λ(·) represents the operation of taking the characteristic roots; Y sys,0 (s) is the transfer function of the new energy power station.

[0176] The second partitioning unit is used when MSCR_down < MSCR < MSCR_up and Re(λ(Y) sys,0When (s)))<0, the operating state of the new energy power system is classified as a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system.

[0177] The third partitioning unit is used when MSCR ≤ MSCR_down or Re(λ(Y) is satisfied. sys,0 When (s)))≥0, the operating state of the new energy power system is classified as an unstable state.

[0178] For example, the optimization module includes:

[0179] The second building unit is used to construct the objective function for the switching and operating costs of the grid-connected / grid-connected switchable converter:

[0180]

[0181] Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter.

[0182] The third building unit is used to construct the reliability objective function of the new energy power system:

[0183] f2=K2|Re(λ domin (Y sys,0 (s)))|.

[0184] Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin (·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station.

[0185] The fourth building block is used to construct the fitness function F of the new energy power system:

[0186] F=(ω1·exp(-f1)+ω2·f2)·γ1·γ2.

[0187] γ1=exp(-μ·max(MSCR_up-MSCR,0)).

[0188]

[0189] Where ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is an exponential function with the natural constant as the base; γ1 is the penalty function of grid constraints; μ is the grid constraint penalty coefficient; MSCR_up represents the maximum short-circuit ratio threshold of the strong stability state of the new energy power system; MSCR is the grid strength; γ2 is the penalty function of small-signal stability constraints; Re(·) represents the operation of taking the real part; λ(·) represents the operation of taking the eigenvalues; Y sys,0 (s) is the transfer function of the new energy power station.

[0190] A determination unit is used to take the number of grid-connecting / following switchable converters p in GFL control mode and the number of grid-connecting / following switchable converters q in GFM control mode as individuals [p, q] in the initial population.

[0191] The computational unit is used to calculate the objective function value of each individual [p, q] in the initial population and to calculate the penalty function of each individual [p, q] to determine the fitness function of each individual [p, q].

[0192] The optimization unit is used to perform optimization control based on the fitness function of each individual [p, q] and the NSGA-II algorithm to obtain the Pareto optimal solution set.

[0193] For more detailed information on the working process of each of the above modules, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0194] Example 3

[0195] This embodiment provides a computer device, including a processor and a memory; wherein, when the processor executes the computer program stored in the memory, it implements the steps of the grid-connected / grid-connected switchable converter switching control method based on grid strength constraints described in Embodiment 1.

[0196] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0197] Example 4

[0198] This embodiment provides a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, it implements the steps of the grid-connected / grid-connected switchable converter switching control method based on grid strength constraints described in Embodiment 1.

[0199] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0200] Example 5

[0201] This embodiment provides a computer program product, including computer-executable instructions or computer programs. When the computer-executable instructions or computer programs are executed by a processor, they implement the steps of the grid-connected / grid-connected switchable converter switching control method based on grid strength constraints described in Embodiment 1.

[0202] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0203] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems, devices, storage media, and computer program products disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0204] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0205] In some embodiments, computer-executable instructions may take the form of programs, software, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.

[0206] As an example, computer-executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., files that store one or more modules, subroutines, or code sections).

[0207] As an example, computer-executable instructions can be deployed to execute on a single electronic device, or on multiple electronic devices located at one location, or on multiple electronic devices distributed across multiple locations and interconnected via a communication network.

[0208] The present invention has been described in detail above with reference to specific embodiments and exemplary examples; however, these descriptions should not be construed as limiting the present invention. Those skilled in the art will understand that various equivalent substitutions, modifications, or improvements can be made to the technical solutions and embodiments of the present invention without departing from the spirit and scope of the invention, and all such modifications and improvements fall within the scope of the present invention. The scope of protection of the present invention is defined by the appended claims.

Claims

1. A switching control method for a grid-connected / grid-linked switchable converter based on grid strength constraints, characterized in that, include: The active power output of each grid-connected converter at the new energy power plant, the active power output of each grid-connected / grid-connected switchable converter under GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter under GFM control mode are obtained to determine the grid strength. Construct the transfer function for new energy power plants; Based on grid strength and the transfer function of new energy power plants, the operating state of new energy power systems is divided into strong stable state, weak stable state and unstable state. Under strong stability and when the power grid strength constraint is met, the original control mode remains unchanged; Under weakly stable and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, the NSGA-II algorithm is used for optimization control to obtain the Pareto optimal solution set. The number of grid-connected / grid-connected switchable converters in different operating modes is adjusted according to the Pareto optimal solution set in order to achieve switching of the operating modes of the grid-connected / grid-connected switchable converters; The acquisition of the active power output of each grid-connected converter at the renewable energy power plant, the active power output of each grid-connected / grid-connected switchable converter under GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter under GFM control mode, in order to determine grid strength, includes: Calculate the grid strength MSCR using the following formula: ； Where Z represents the series equivalent impedance of the grid side as an ideal voltage source; This represents the equivalent impedance of the new energy power system after passing through the per-unit standard of the new energy power station's reference capacity; S N Rated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_ j P represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; GFM_SC_k The active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

2. The switching control method for a grid-connected / grid-connected switchable converter according to claim 1, characterized in that, The construction of the transfer function for the new energy power station includes: Constructing the transfer function Y of the new energy power station sys,0 The expression for (s): ； ； ； Where diag(·) denotes a diagonal matrix; S B,i' Y represents the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i' = 1, 2, ..., n + p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode after scaling by its own capacity per unit; s is the Laplace operator; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; B is the node admittance matrix after Kron transform to eliminate internal passive nodes; ω0 is the angular velocity at the power frequency; τ is the ratio of line resistance to inductance.

3. The switching control method for a grid-connected / grid-connected switchable converter according to claim 1, characterized in that, The classification of the operating state of the new energy power system into strongly stable, weakly stable, and unstable states based on grid strength and the transfer function of new energy power plants includes: In satisfying and In this case, the operating state of the new energy power system is divided into a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the new energy power system in a strongly stable state; Re(·) represents the operation of taking the real part; MSCR is the grid strength; λ(·) represents the operation of taking the characteristic roots; Y sys,0 (s) is the transfer function of the new energy power station; In satisfying and In the case of [condition], the operating state of the new energy power system is divided into a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system; In satisfying or In such cases, the operating status of the new energy power system is classified as an unstable state.

4. The grid-connected / grid-connected switchable converter switching control method according to claim 1, characterized in that, Under weakly stable and unstable states, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, the NSGA-II algorithm is used for optimization control to obtain the Pareto optimal solution set, including: Construct the objective function for switching and operating costs of grid-connected / grid-connected switchable converters: ； Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter. Construct the reliability objective function for the new energy power system: ； Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin (·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station; Construct the fitness function F for the new energy power system: ； ； ； Where ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is an exponential function with the natural constant as the base; γ1 is the penalty function of grid constraints; μ is the grid constraint penalty coefficient; MSCR_up represents the maximum short-circuit ratio threshold of the strong stability state of the new energy power system; MSCR is the grid strength; γ2 is the penalty function of small-signal stability constraints; Re(·) represents the operation of taking the real part; λ(·) represents the operation of taking the eigenvalues; Y sys,0 (s) is the transfer function of the new energy power station; The number of switchable converters p in GFL control mode and the number of switchable converters q in GFM control mode are used as individuals [p, q] in the initial population; Calculate the objective function value for each individual [p, q] in the initial population, and calculate the penalty function for each individual [p, q] to determine the fitness function for each individual [p, q]. Based on the fitness function of each individual [p, q] and using the NSGA-II algorithm for optimization control, the Pareto optimal solution set is obtained.

5. A grid-connected / grid-linked switchable converter switching control system based on grid strength constraints, characterized in that, include: The first determining module is used to obtain the active power output of each grid-connected converter in the new energy power station, the active power output of each grid-connected / grid-connected switchable converter in GFL control mode, and the active power output of each grid-connected / grid-connected switchable converter in GFM control mode, so as to determine the grid strength. The module is used to build the transfer function of the new energy power station; The partitioning module is used to classify the operating state of the new energy power system into strong stable state, weak stable state and unstable state based on the grid strength and the transfer function of the new energy power station. The second determining module is used to maintain the original control mode unchanged under strong stability and when the power grid strength constraint is met; The optimization module is used to optimize control under weak and unstable conditions, with the switching and operating costs of grid-connected / grid-connected switchable converters and the reliability of the new energy power system as objective functions, and uses the NSGA-II algorithm to obtain the Pareto optimal solution set. The switching module is used to adjust the number of grid-connected / grid-connected switchable converters in different operating modes according to the Pareto optimal solution set, so as to realize the switching of the operating modes of the grid-connected / grid-connected switchable converters; The first determining module includes: The first calculation unit is used to calculate the grid strength MSCR according to the following formula: ； Where Z represents the series equivalent impedance of the grid side as an ideal voltage source; This represents the equivalent impedance of the new energy power system after passing through the per-unit standard of the new energy power station's reference capacity; S N Rated capacity of new energy power stations; S S P represents the total active power output of the renewable energy power station; n represents the total number of grid-connected converters within the renewable energy power station; GFL_i P represents the active power output of grid-connected converter i; p represents the total number of grid-connected / grid-connected switchable converters in GFL control mode; P GFL_SC_ j P represents the active power output of grid-connected / grid-connected switchable converter j in GFL control mode; q represents the total number of grid-connected / grid-connected switchable converters in GFM control mode; GFM_SC_k The active power output of the grid-connected / grid-connected switchable converter k in GFM control mode.

6. The grid-connected / grid-linked switchable converter switching control system according to claim 5, characterized in that, The building module includes: The first building unit is used to construct the transfer function Y of the new energy power station. sys,0 The expression for (s): ； ； ； Where diag(·) denotes a diagonal matrix; S B,i' Y represents the rated capacity of converter i' after passing through the per-unit standard of the new energy power system benchmark capacity; i' = 1, 2, ..., n + p; GFL,i' (s) is the admittance transfer function matrix of converter i' in GFL control mode, scaled down to its own capacity per unit; S B,k The rated capacity of the grid-connected / grid-connected switchable converter k after passing the per-unit standard of the new energy power system benchmark capacity; Y GFM,k (s) is the admittance transfer function matrix of the grid-connected / grid-connected switchable converter k under GFM control mode after scaling by its own capacity per unit; s is the Laplace operator; J0 is the equivalent node admittance matrix obtained after considering the converter capacity weighting. γ is the Kronecker product; γ(s) is the transfer function of the AC network side admittance matrix; B is the node admittance matrix after Kron transform to eliminate internal passive nodes; ω0 is the angular velocity at the power frequency; τ is the ratio of line resistance to inductance.

7. The grid-connected / grid-linked switchable converter switching control system according to claim 5, characterized in that, The partitioning module includes: The first partitioning unit is used to satisfy... and In this case, the operating state of the new energy power system is divided into a strongly stable state; where MSCR_up represents the maximum short-circuit ratio threshold of the new energy power system in a strongly stable state; Re(·) represents the operation of taking the real part; MSCR is the grid strength; λ(·) represents the operation of taking the characteristic roots; Y sys,0 (s) is the transfer function of the new energy power station; The second partitioning unit is used to satisfy... and In the case of [condition], the operating state of the new energy power system is divided into a weakly stable state; where MSCR_down represents the minimum short-circuit ratio threshold of the strongly stable state of the new energy power system; The third partitioning unit is used to satisfy... or In such cases, the operating status of the new energy power system is classified as an unstable state.

8. The grid-connected / grid-connected switchable converter switching control system according to claim 5, characterized in that, The optimization module includes: The second building unit is used to construct the objective function for the switching and operating costs of the grid-connected / grid-connected switchable converter: ； Where F1 is the switching cost of the grid-connected / grid-connected switchable converter; α is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFL control mode to GFM control mode; p(t) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t; p(t-1) is the total number of grid-connected / grid-connected switchable converters in GFL control mode at time t-1; β is the loss coefficient of a single grid-connected / grid-connected switchable converter switching from GFM control mode to GFL control mode; q(t) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t; q(t-1) is the total number of grid-connected / grid-connected switchable converters in GFM control mode at time t-1; F2 is the operating cost of the grid-connected / grid-connected switchable converter; K1 is the scaling factor of the operating cost objective function; C H_GFL (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFL control mode; C H_GFM (t) represents the operating cost of the grid-connected / grid-connected switchable converter in GFM control mode; f1 represents the switching and operating costs of the grid-connected / grid-connected switchable converter. The third building unit is used to construct the reliability objective function of the new energy power system: ； Where f2 represents the reliability of the new energy power system; K2 is the scaling coefficient of the objective function for the reliability of the new energy power system; λ domin (·) represents the dominant pole of the new energy power system, used to characterize the anti-interference capability of the new energy power system; Y sys,0 (s) is the transfer function of the new energy power station; The fourth building block is used to construct the fitness function F of the new energy power system: ； ； ； Where ω1 is the first preset coefficient; ω2 is the second preset coefficient; exp(·) is an exponential function with the natural constant as the base; γ1 is the penalty function of grid constraints; μ is the grid constraint penalty coefficient; MSCR_up represents the maximum short-circuit ratio threshold of the strong stability state of the new energy power system; MSCR is the grid strength; γ2 is the penalty function of small-signal stability constraints; Re(·) represents the operation of taking the real part; λ(·) represents the operation of taking the eigenvalues; Y sys,0 (s) is the transfer function of the new energy power station; The determination unit is used to take the number of network-connecting / following switchable converters p in GFL control mode and the number of network-connecting / following switchable converters q in GFM control mode as individuals [p, q] in the initial population; The computational unit is used to calculate the objective function value of each individual [p, q] in the initial population and to calculate the penalty function of each individual [p, q] to determine the fitness function of each individual [p, q]. The optimization unit is used to perform optimization control based on the fitness function of each individual [p, q] and the NSGA-II algorithm to obtain the Pareto optimal solution set.

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