Method and device for constructing order reduction model of direct-driven wind turbine generator grid-connected system

Abstract

The invention discloses a method and device for constructing a reduced-order model of a direct-driven wind turbine generator grid-connected system, and the method comprises the steps: constructing an electromagnetic transient model of the direct-driven wind turbine generator grid-connected system based on the transient response characteristics of each control link in a direct-driven wind turbine generator, and constructing a reduced-order model of the direct-driven wind turbine generator grid-connected system based on the electromagnetic transient model of the direct-driven wind turbine generator grid-connected system. The method comprises the following steps: obtaining the dominance of each state variable in a direct-driven wind turbine generator grid-connected system, determining the multi-time scale division and key variable of the direct-driven wind turbine generator grid-connected system according to the dominance of each state variable in the direct-driven wind turbine generator grid-connected system, and determining the multi-time scale division and key variable of the direct-driven wind turbine generator grid-connected system according to the multi-time scale division and key variable of the direct-driven wind turbine generator grid-connected system. And a singular perturbation method is adopted to construct an order reduction model of the direct-driven wind turbine generator grid-connected system. According to the method and the device provided by the embodiment of the invention, the constructed order reduction model can better reflect the transient response characteristics of the system, the calculation time can be greatly shortened, and a foundation can be laid for subsequent stable analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of power system simulation, and in particular, to a method and device for constructing a reduced-order model of a grid-connected system of a direct-drive wind turbine generator set. Background Art

[0002] With the large-scale application of new energy technologies, the dynamic characteristics of power systems are undergoing profound changes. Currently, new energy units (wind power, photovoltaic, etc.) with converters as interfaces have their dynamic responses completely determined by the control architectures of power electronic converters. The time scales of each control loop (current loop, voltage loop, power loop, etc.) are all concentrated in the millisecond to second range, and there are significant time overlaps. This characteristic of tight coupling of multiple time scales leads to high-order nonlinearity in the system state equations. Directly applying traditional modeling methods will face the problem of dimensionality explosion, while simple reduction is likely to lose key transient characteristics, constituting a prominent contradiction in the stability analysis of new energy grid-connected systems.

[0003] Currently existing reduction methods, such as digital twin real-time simulation and black-box reduction, all have various problems. Digital twin real-time simulation has a computing power bottleneck problem: existing hardware-in-the-loop (HIL) tests rely on FPGAs to achieve real-time simulation with microsecond-level step sizes, but new energy field-level simulations require more than ten thousand logic units, resulting in high costs and limited scalability; when existing research directly uses full-order models for transient stability analysis, it will take too long to calculate due to dimensional explosion, making it difficult to meet the real-time dispatching requirements of the power grid. The black-box reduced-order model has a problem of lack of physical interpretability: Although data-driven surrogate models can fit system responses through a large amount of simulation data, due to their black-box characteristics, they cannot reveal the explicit relationship between control loop parameters and stability indicators, making it difficult to guide the optimal design of controllers. Summary of the Invention

[0004] In view of this, the present invention proposes a method and device for constructing a reduced-order model of a grid-connected system of a direct-drive wind turbine generator set, aiming to solve one or more of the technical problems mentioned in the above background art section.

[0005] In a first aspect, an embodiment of the present invention provides a method for constructing a reduced-order model of a grid-connected system of a direct-drive wind turbine generator set. The method includes: constructing an electromagnetic transient model of the grid-connected system of the direct-drive wind turbine generator set based on the transient response characteristics of each control link in the direct-drive wind turbine generator set; obtaining the dominance of each state variable in the grid-connected system of the direct-drive wind turbine generator set by using the sensitivity analysis method based on the electromagnetic transient model of the grid-connected system of the direct-drive wind turbine generator set; determining the multi-time scale division and key variables of the grid-connected system of the direct-drive wind turbine generator set according to the dominance of each state variable in the grid-connected system of the direct-drive wind turbine generator set; and constructing a reduced-order model of the grid-connected system of the direct-drive wind turbine generator set by using the singular perturbation method based on the multi-time scale and key variables of the grid-connected system of the direct-drive wind turbine generator set.

[0006] Furthermore, based on the transient response characteristics of each control link in the direct-drive wind turbine generator set, an electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system is constructed, including: the differential equation for constructing the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system includes:

[0007]

[0008] In the formula: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, U dcref is the reference value of the DC capacitor voltage, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, U t is the terminal voltage, U tref is the reference value of the terminal voltage, τ3 is the response speed of the current control process, x3 is the output state variable of the d-axis current control process, x4 is the output state variable of the q-axis current control process, i d 、i q are the current components of the grid-side converter in the dq-axis coordinate system, i dref 、i qref are the current reference values in the dq coordinate system respectively, τ C is the change time constant of the DC voltage state variable, P is the electric power, P m is the mechanical power, τ pll is the response speed of the phase-locked loop control process, θ pll is the phase angle output by the phase-locked loop, ω0 is the rated angular velocity of the system, ω pll is the angular velocity output by the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, u td 、u tq are the terminal voltage components in the dq coordinate system respectively, τ ω is the response speed of the main circuit of the system, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinate system, L f is the filter inductor.

[0009] Furthermore, based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system, the sensitivity analysis method is used to obtain the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, including: determining the data of each state variable in the direct-drive wind turbine generator set grid-connected system under each scenario, where the state variables include x1, x2, U dc and θ pll ; changing the parameters of each control link and the system operating conditions, and determining the dominance of each state variable under each scenario.

[0010] Furthermore, according to the dominance of each state variable in the grid-connected system of the direct-drive wind turbine, the multi-time scale division and key variables of the grid-connected system of the direct-drive wind turbine are determined, including: classifying the state variables according to the magnitudes of the time constants of different state variables, and dividing the grid-connected system of the direct-drive wind turbine into fast and slow subsystems; based on the dominance of each state variable in each scenario, determining the dominant variables that cause system instability, and taking the time scale of the dominant state variable as a reference, determining the key variables that dominate the system dynamics at the time scale of the dominant state variable.

[0011] Furthermore, based on the multi-time scale and key variables of the grid-connected system of the direct-drive wind turbine, the singular perturbation method is used to construct a reduced-order model of the grid-connected system of the direct-drive wind turbine, including: arranging and expressing the wind turbine model under the DC voltage time scale in the form of singular perturbation as follows:

[0012]

[0013] In the formula: f(θ pll , i d ) is the state equation of the slow subsystem, g(θ pll , i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on a long time scale and reflects the dominant dynamic characteristics of the system, i d describes the dynamic behavior of the system on a short time scale, μ = 1 / K p,pll , is a small positive real number parameter, which is mainly used to characterize the multi-scale characteristics of the system in the singular perturbation problem and simplifies the solution process of the problem through asymptotic expansion, K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop, K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage, is the injected power on the DC side, C dc is the capacitance of the DC capacitor, l g is the system line impedance, i d is the d-axis current output by the voltage control using DC voltage control, ω pll is the angular velocity of the phase-locked loop.

[0014] Second aspect, an embodiment of the present invention further provides a device for constructing a reduced-order model of a direct-drive wind turbine grid-connected system. The device includes: a first construction unit configured to construct an electromagnetic transient model of the direct-drive wind turbine grid-connected system based on the transient response characteristics of each control link in the direct-drive wind turbine; a first processing unit configured to obtain the dominance of each state variable in the direct-drive wind turbine grid-connected system by using the sensitivity analysis method based on the electromagnetic transient model of the direct-drive wind turbine grid-connected system; a second processing unit configured to determine the multi-time scale division and key variables of the direct-drive wind turbine grid-connected system according to the dominance of each state variable in the direct-drive wind turbine grid-connected system; a second construction unit configured to construct a reduced-order model of the direct-drive wind turbine grid-connected system by using the singular perturbation method based on the multi-time scale and key variables of the direct-drive wind turbine grid-connected system.

[0015] Further, the first construction unit is further configured to: The differential equation for constructing the electromagnetic transient model of the direct-drive wind turbine grid-connected system includes:

[0016]

[0017] In the formula: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, U dcref is the DC capacitor voltage reference value, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, U t is the terminal voltage, U tref is the terminal voltage reference value, τ3 is the response speed of the current control process, x3 is the output state variable of the d-axis current control process, x4 is the output state variable of the q-axis current control process, i d 、i q are the current components of the grid-side converter in the dq-axis coordinate system, i dref 、i qref are the current reference values in the dq coordinate system respectively, τ C is the DC voltage state variable change time constant, P is the electric power, P m is the mechanical power, τ pll is the response speed of the phase-locked loop control process, θ pll is the phase angle output by the phase-locked loop, ω0 is the rated angular velocity of the system, ω pll is the angular velocity output by the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, u td 、u tq are the terminal voltage components in the dq coordinate system respectively, τ ω is the response speed of the main circuit of the system, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinate system, Lf is a filtering inductor.

[0018] Further, the first processing unit is further configured to: determine data of each state variable in the grid-connected system of the direct-drive wind turbine in each scenario, where the state variables include x1, x2, U dc and θ pll ; change parameters of each control link and system operating conditions, and determine the dominance of each state variable in each scenario.

[0019] Further, the second processing unit is further configured to: classify the state variables according to the magnitudes of the time constants of different state variables, and divide the grid-connected system of the direct-drive wind turbine into fast and slow subsystems; based on the dominance of each state variable in each scenario, determine the dominant variable that causes the system to become unstable, and with reference to the time scale of the dominant state variable, determine the key variable that dominates the system dynamics at the time scale of the dominant state variable.

[0020] Further, the second construction unit is further configured to: organize and represent the fan model under the DC voltage time scale in the form of singular perturbation as follows:

[0021]

[0022] In the formula: f(θ pll , i d ) is the state equation of the slow subsystem, g(θ pll , i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on a long time scale and reflects the dominant dynamic characteristics of the system, i d describes the dynamic behavior of the system on a short time scale, μ = 1 / K p,pll , is a small positive real number parameter, which is mainly used to characterize the multi-scale characteristics of the system in the singular perturbation problem and simplifies the solution process of the problem through asymptotic expansion, K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop, K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage, P d * c is the injected power on the DC side, C dc is the capacitance of the DC capacitor, l gis the system line impedance, i d uses DC voltage control for voltage control to output the d-axis current, ω pll is the angular velocity of the phase-locked loop.

[0023] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the methods provided in the above embodiments are implemented.

[0024] In a fourth aspect, an embodiment of the present invention further provides an electronic device, including: a processor; a memory for storing executable instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the methods provided in the above embodiments.

[0025] The method and device for constructing a reduced-order model of a direct-drive wind turbine grid-connected system provided by the embodiments of the present invention construct an electromagnetic transient model of the direct-drive wind turbine grid-connected system based on the transient response characteristics of each control link in the direct-drive wind turbine. Based on the electromagnetic transient model of the direct-drive wind turbine grid-connected system, the dominance of each state variable in the direct-drive wind turbine grid-connected system is obtained. According to the dominance of each state variable in the direct-drive wind turbine grid-connected system, the multi-time scale division and key variables of the direct-drive wind turbine grid-connected system are determined, and based on the multi-time scale and key variables of the direct-drive wind turbine grid-connected system, the singular perturbation method is used to construct a reduced-order model of the direct-drive wind turbine grid-connected system. The constructed reduced-order model can better reflect the transient response characteristics of the system and can greatly reduce the calculation time; the constructed reduced-order model can lay a foundation for subsequent stability analysis and can more accurately judge the stability and stability change trend of the system; in addition, the dominance of each state variable is obtained by using the sensitivity analysis method to analyze the transient dominant instability variables of the system, and there are no restrictions on the types and control methods of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 shows an exemplary flowchart of a method for constructing a reduced-order model of a direct-drive wind turbine grid-connected system according to an embodiment of the present invention;

[0027] Figure 2 shows a schematic diagram of a full-order electromagnetic transient model diagram of a direct-drive wind turbine grid-connected system according to an embodiment of the present invention;

[0028] Figure 3a , 3b respectively show schematic diagrams comparing the dominance of system state variables under operating conditions 1 and 2 according to an embodiment of the present invention;

[0029] Figure 4Shows a schematic diagram of a reduced - order model diagram of a direct - drive wind turbine grid - connected system under DC voltage scale according to an embodiment of the present invention;

[0030] Figure 5a 、 5b respectively show the time - domain simulation comparison curve graphs of fast and slow state variables δ in the detailed model and the reduced - order model according to an embodiment of the present invention;

[0031] Figure 6 Shows a schematic structural diagram of a device for building a reduced - order model of a direct - drive wind turbine grid - connected system according to an embodiment of the present invention. Detailed implementation manners

[0032] Now, exemplary embodiments of the present invention will be introduced with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely, and to fully convey the scope of the present invention to those skilled in the art. The terms in the exemplary embodiments shown in the drawings are not limitations on the present invention. In the drawings, the same units / components use the same reference numerals.

[0033] Unless otherwise specified, the terms (including scientific and technical terms) used herein have the ordinary meaning understood by those skilled in the art. Additionally, it can be understood that the terms defined in the commonly used dictionary should be understood to have a meaning consistent with the context of their related fields, and should not be understood as idealized or overly formal meanings.

[0034] Figure 1 Shows an exemplary flowchart of a method for building a reduced - order model of a direct - drive wind turbine grid - connected system according to an embodiment of the present invention.

[0035] As Figure 1 shown, the method includes:

[0036] Step S101: Based on the transient response characteristics of each control link in the direct - drive wind turbine, build an electromagnetic transient model of the direct - drive wind turbine grid - connected system.

[0037] Further, step S101 includes:

[0038] The differential equation for building the electromagnetic transient model of the direct - drive wind turbine grid - connected system includes:

[0039]

[0040] In the formula: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, Udcref is the DC capacitor voltage reference value, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, and U t is the terminal voltage, and U tref is the terminal voltage reference value, τ3 is the response speed of the current control process, x3 is the output state variable of the d-axis current control process, x4 is the output state variable of the q-axis current control process, and i d and i q are the current components of the grid-side converter in the dq-axis coordinate system, and i dref and i qref are the current reference values in the dq coordinate system respectively, and τ C is the DC voltage state variable change time constant, P is the electric power, and P m is the mechanical power, and τ pll is the response speed of the phase-locked loop control process, and θ pll is the phase angle output by the phase-locked loop, ω0 is the rated angular velocity of the system, and ω pll is the angular velocity output by the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, and u td and u tq are the terminal voltage components in the dq coordinate system respectively, and τ ω is the response speed of the main circuit of the system, and e d and e q are the voltage components of the grid-side converter in the dq-axis coordinate system, and L f is the filter inductor.

[0041] Specifically, Figure 2 shows a schematic diagram of the full-order electromagnetic transient model of the grid-connected system of a direct-drive wind turbine according to an embodiment of the present invention. As Figure 2 shown, a full-order electromagnetic transient model of the grid-connected system of a direct-drive wind turbine is constructed.

[0042] First, a mathematical model of the machine-side converter of the direct-drive wind turbine is constructed.

[0043]

[0044] In the formula: V w is the external wind speed, Ω W is the rotational speed of the wind turbine, ρ represents the air density, and A r represents the wind wheel area, C p is the wind energy conversion coefficient, and T B is the mechanical torque of the wind turbine.

[0045] When deeply analyzing the operating characteristics of the direct-drive wind turbine, its motion equation is the key theoretical basis:

[0046]

[0047] Where: J is the moment of inertia, T m is the mechanical torque of the fan, T e is the electromagnetic torque of the fan, Ω v is the rotational speed of the fan.

[0048] In order to maximize the system efficiency, unit power factor control is generally adopted, and there is:

[0049]

[0050] Where: i dsref is the reference value of the stator current of the machine-side converter under the d-axis, i qsref is the reference value of the stator current of the machine-side converter under the q-axis, n p is the number of pole pairs of the permanent magnet motor, is the reference value of the electromagnetic torque, ψ f is the magnetic flux passing through the rotor.

[0051] In the dq coordinate system, without considering the limiting link and switching control links, only considering the conventional control, the control equation of the machine-side converter can be obtained:

[0052]

[0053] Where: k under the d-axis p1 、k i1 are the integral coefficient and proportional coefficient of the machine-side converter, k under the q-axis p2 、k i2 are the integral coefficient and proportional coefficient of the machine-side converter, C pmax is the maximum utilization coefficient of wind energy, T ref is the reference value of the electromagnetic torque under the maximum wind energy control, u ds is the stator voltage value under the d-axis, u qs is the stator voltage value under the q-axis, ω s is the angular velocity of the permanent magnet motor, i qs is the stator current value under the q-axis, i ds is the stator current value under the d-axis, γ opt is the optimal tip speed ratio of the fan.

[0054] Further construct the mathematical model of the DC capacitor of the direct-drive fan.

[0055] The mathematical characteristics of the DC capacitor are:

[0056]

[0057] Where, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinates, i d 、i qis the current component of the grid-side converter in the dq axis coordinate, C is the capacitance of the DC capacitor, U dc is the voltage across the DC capacitor.

[0058] Finally, the mathematical model of the grid-side converter of the direct-drive wind turbine is constructed.

[0059] The voltage loop control is mathematically characterized as follows:

[0060]

[0061] Where: U dc is the DC capacitor voltage, U dcref is the DC capacitor voltage reference value, k p3 、k p4 is the integral coefficient of the voltage loop PI controller, U t is the terminal voltage, U tref is the terminal voltage reference value, u td 、u tq are the voltage components at the lower end of the dq coordinate system respectively.

[0062] The differential equation and algebraic equation of the current control loop are:

[0063]

[0064] Where: i dref 、i qref They are the current components in the dq coordinate system, k p4 、k p5 is the integral coefficient of the current loop PI controller.

[0065] The phase-locked loop control model is:

[0066]

[0067] Where: Δω pll is the angular velocity change of the phase-locked loop, k p6 and k i6 are the integral coefficient and proportional coefficient of the phase-locked loop.

[0068] The main loop control model is:

[0069]

[0070] Where: U g is the grid voltage amplitude, is the phase angle, v d 、v q They are the grid-side voltage components in the dq coordinate system, L g is the equivalent inductance of the system, i gd 、i gqThey are the grid current components in the dq coordinate system, v gd and v gq are the machine-side voltage components in the dq coordinate system respectively.

[0071] Combining the above formulas, the differential-algebraic equation set of the direct-drive wind turbine grid-connected single-machine system under the electromagnetic time scale can be obtained:

[0072]

[0073]

[0074] Step S102: Based on the electromagnetic transient model of the direct-drive wind turbine grid-connected system, the sensitivity analysis method is used to obtain the dominance of each state variable in the direct-drive wind turbine grid-connected system.

[0075] Furthermore, step S102 includes:

[0076] Determine the data of each state variable in the direct-drive wind turbine grid-connected system under each scenario, where the state variables include x1, x2, U dc and θ pll ;

[0077] Change the parameters of each control link and the system operating conditions, and determine the dominance of each state variable under each scenario.

[0078] Specifically, first, clarify each component of the direct-drive wind turbine and the relevant parts connected to the grid. Determine the specific operating scenarios concerned by the analysis, and set different operating conditions such as three-phase short-circuit faults and grid voltage dips. Determine the historical operating data of x1, x2, U dc , θ pll under different operating conditions to provide comparison samples for subsequent analysis.

[0079] Secondly, consider the performance of each state variable during the transient process. Study the sensitivity of each dominant instability variable to system parameters or state variables. By changing the parameters of each control link and the system operating conditions, compare the dominance of system state variables under different operating conditions of the dynamic order reduction method of the direct-drive wind turbine grid-connected system. The greater the change rate, the more sensitive the system performance is to this variable, and this variable plays a more crucial role in system stability.

[0080] After that, according to the sensitivity calculation results, sort all state variables according to the size of the dominant role. Screen out the state variables with a greater dominant role, and these are the important influencing factors of the system transient characteristics in this mode. Figure 3a 、 3b respectively show the comparison schematic diagrams of the dominance of system state variables under operating condition 1 and operating condition 2 according to an embodiment of the present invention. As Figure 3a 、 3bAs shown, it can be seen that during the transient process of the grid-connected system of the direct-drive wind turbine generator, the state variables x1, x2, and U dc change relatively little, while the phase angle θ of the phase-locked loop pll changes significantly. The maximum value during the transient process indicates its drastic change. It can be seen that the dominant instability variable is θ pll .

[0081] In the above embodiments, the sensitivity analysis method is used to analyze the equivalent time constants of each state variable and its influence on the system dynamics, and then the transient dominant instability variable of the system is analyzed according to the magnitude and dominance of the equivalent time constants. There are no restrictions on the types and control methods of the equipment.

[0082] Step S103: Determine the multi-time scale division and key variables of the grid-connected system of the direct-drive wind turbine generator according to the dominance of each state variable in the grid-connected system of the direct-drive wind turbine generator.

[0083] Further, step S103 includes:[[]]

[0084] Classify the state variables according to the magnitudes of the time constants of different state variables, and divide the grid-connected system of the direct-drive wind turbine generator into fast and slow subsystems;

[0085] Based on the dominance of each state variable in each scenario, determine the dominant variable that causes the system to become unstable, and with reference to the time scale of the dominant state variable, determine the key variable that dominates the system dynamics at the time scale of the dominant state variable.

[0086] Complete the multi-time scale division of the grid-connected system of the direct-drive wind turbine generator according to the dominance of each state variable:[[]]

[0087] First, classify the state variables according to the magnitudes of the time constants of different state variables, and separate the fast and slow subsystems of the grid-connected system of the direct-drive wind turbine generator. Determine the dominant variable that causes the system to become unstable based on the influence degree of each state variable on the system dynamic characteristics analyzed in the previous subsection. It is considered that i d , θ pll are the slow variable and the fast variable of the system respectively.

[0088] Specifically, it includes the following steps:[[]]

[0089] Step 1: Classify the state variables according to the magnitudes of their time constants in different states, and separate the grid-connected system of the direct-drive wind turbine into fast and slow subsystems. Group those with similar time constants and similar acting characteristics into one category, and based on this, initially divide the system into multiple time scales such as fast and slow. It can be seen that the response speed of the main circuit control link is the fastest (0.1 ms), the response speed of the AC current control time scale dominated by the current control loop is relatively fast (10 ms), the speed of the DC voltage control time scale dominated by the voltage control loop and the phase-locked loop is slightly slower (100 ms), and the response speed of the mechanical link is the slowest (1 s). Under the electromagnetic time scale, the current loop corresponds to the fast subsystem, and the voltage loop and the phase-locked loop correspond to the slow subsystem; within the DC voltage time scale, the phase-locked loop corresponds to the fast subsystem, while the voltage loop corresponds to the slow subsystem. At the same time, the equivalent time constants between each scale differ by approximately 10 -1 orders of magnitude.

[0090] Step 2: Determine the dominant variables that cause the system to become unstable based on the influence degrees of each state variable on the system's dynamic characteristics analyzed in the previous subsection. Taking the time scale of the dominant state variable as a reference, the state variables that change relatively slowly can be temporarily ignored, while the state variables that change extremely rapidly can be regarded as reaching a steady state in an extremely short time, and the remaining state variables are the key variables that dominate the system dynamics at this specific time scale. For the fault analysis of a general power system, the operating time of its protection is about 100 ms. At this time scale, the voltage control and the phase-locked loop control parts dominate the system response characteristics. The DC voltage time scale that this patent focuses on, the phase-locked loop corresponds to the fast subsystem, while the voltage loop corresponds to the slow subsystem. At the same time, the equivalent time constants between each scale differ by approximately 10 -1 orders of magnitude, where θ pll and i d are the dominant variables.

[0091] Step S104: Based on the multi-time scales and key variables of the grid-connected system of the direct-drive wind turbine, use the singular perturbation method to construct a reduced-order model of the grid-connected system of the direct-drive wind turbine.

[0092] Furthermore, step S104 includes:

[0093] Arrange and express the fan model under the DC voltage time scale in the form of singular perturbation as follows:

[0094]

[0095] In the formula: f(θ pll , i d ) is the state equation of the slow subsystem, and g(θ pll , i d ) is the state equation of the fast subsystem, where θ pllIt is used to characterize the dynamic response of the system on a long time scale and reflects the dominant dynamic characteristics of the system. d Describes the dynamic behavior of the system on a short time scale, μ = 1 / K p,pll , is a small positive real number parameter, which is mainly used to characterize the multi-scale characteristics of the system in the singular perturbation problem, and simplifies the solution process of the problem by asymptotic expansion. p,pll and K i,pll K is the integral coefficient and proportional coefficient of the phase-locked loop, p,dc and K i,dc is the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is fast and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d =i dref ,i q =i qref , U g is the grid voltage, P d * c is the DC side injection power, C dc is the capacitance of the DC capacitor, l g is the system line impedance, i d For voltage control, DC voltage is used to control the output d-axis current, ω pll is the phase-locked loop angular velocity.

[0096] In the above embodiment, singular perturbation theory is used to construct a reduced-order model that takes into account the phase-locked loop and the DC voltage control loop. The reduced-order model composed of the fast subsystem and the slow subsystem can better reflect the transient response characteristics of the system and greatly reduce the calculation time. At the same time, the constructed reduced-order model can lay the foundation for subsequent stability analysis, and can take the intersection of the stability domain of the fast subsystem and the stability domain of the slow subsystem to construct the stability criterion of the direct-drive wind turbine grid-connected system under the DC voltage scale, which can more accurately judge the stability of the system and the stability change trend.

[0097] Specifically, Figure 4 Schematic diagram showing a reduced-order model diagram of a direct-drive wind turbine grid-connected system under a DC voltage scale according to an embodiment of the present invention. Figure 4 As shown in Figure 2, the reduced-order model of the direct-drive wind turbine grid-connected system is constructed as follows:

[0098] Step 1: For a VSC grid-connected control system consisting of n+m-order state-space equations, it can be divided into n fast variables and m slow variables. The fast variables are multiplied by a small parameter μ to form a singular perturbation model. In the singular perturbation problem, μ is mainly used to characterize the multi-scale characteristics of the system, induce the singular behavior of the solution, and simplify the problem-solving process through asymptotic expansion. It is a key tool for analyzing and solving singular perturbation problems.

[0099] The fan model under the DC voltage time scale is organized and expressed in the singular perturbation form:

[0100]

[0101] In the formula: f(θ pll , i d ) is the state equation of the slow subsystem, and g(θ pll , i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on the long time scale and reflects the dominant dynamic characteristics of the system. i d describes the dynamic behavior of the system on the short time scale. μ = 1 / K p,pll , K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop, and K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage, is the power injected into the DC side, C dc is the capacitance of the DC capacitor, l g is the system line impedance, i d is the d-axis current output by the voltage control using DC voltage control, and ω pll is the angular velocity of the phase-locked loop.

[0102] By reducing the order through the singular perturbation method to obtain the fast and slow subsystems, the following conditions need to be met: the time constants of the fast and slow subsystems differ greatly, and the small parameter μ is small enough. The time constant of the fast subsystem (phase-locked loop control system) selected by the VSC control system under the DC voltage time scale constructed in the present invention is much smaller than the time constant of the slow subsystem (DC voltage control system), and their equivalent time constants differ by an order of magnitude of 10 -1 . Therefore, the state space equation of the VSC control system under the DC voltage time scale can be modeled and analyzed using the singular perturbation method. Next, the slow subsystem model is constructed.

[0103] The state space equation of the VSC control system containing the small parameter μ is:

[0104]

[0105] In the formula: K p,plland K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop, K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref . U g is the grid voltage, is the injected power on the DC side, C dc is the capacitance of the DC capacitor, l g is the system line impedance, i d is the d-axis current output by the voltage control using DC voltage control, ω pll is the angular velocity of the phase-locked loop.

[0106] When μ = 0, the system degenerates into a low-order system:

[0107]

[0108] The state-space equation of the slow subsystem is:

[0109]

[0110] The slow subsystem composed of

[0111]

[0112] Let μ = 0. It is considered that during the dynamic process of the slow subsystem, the dynamic process of the fast subsystem has ended and reached a steady state, and the system degenerates into a slow subsystem composed of a second-order differential equation.

[0113] Step 2: Use the singular perturbation method for modeling and analysis. Next, construct its fast subsystem model.

[0114] "Stretch" the time scale so that the fast time scale τ = t / μ. The state-space equation of the VSC control system containing small parameters is:

[0115]

[0116] The transient process of the fast subsystem is equivalent to a small perturbation of the slow subsystem. The fast state variables can be expressed as:

[0117]

[0118] where the subscript s represents the slow state of the state variable, and the subscript f represents the fast state of the state variable.

[0119] Regard the slow state variables as constants during the transient process of the fast subsystem:

[0120]

[0121] where C1 and C2 are constants.

[0122] The state equation of the fast subsystem is:

[0123]

[0124] "Stretching" the time scale makes the fast time scale τ = t / μ. Let μ = 0, and a fast subsystem composed of a first-order differential equation is obtained.

[0125] Step 3: To determine the accuracy and applicability of the reduced-order model, compare the detailed transient model and the reduced-order model on MATLAB / Simulink. Set a three-phase short-circuit fault at the point of common coupling PCC in the two simulation systems at 1 s, the fault lasts for 0.05 s, and is removed at 1.05 s. Figure 5a 、 5b respectively show the fast and slow state variables δ according to an embodiment of the present invention, in the time-domain simulation comparison curve graphs of the detailed model and the reduced-order model. As Figure 5a 、 5b shown, it can be obtained that the steady-state values of each state variable described by the detailed transient model and the reduced-order model before and after the fault and during the recovery to the steady state are basically the same.

[0126] Step 4: Simplify the control link of the detailed transient model in the reduced-order model to reduce the order of its state-space equation and reduce the simulation calculation time.

[0127] In the above embodiment, based on the transient response characteristics of each control link in the direct-drive wind turbine generator set, an electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system is constructed. Based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system, the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system is obtained. According to the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, the multi-time scale division and key variables of the direct-drive wind turbine generator set grid-connected system are determined, and based on the multi-time scale and key variables of the direct-drive wind turbine generator set grid-connected system, the singular perturbation method is used to construct a reduced-order model of the direct-drive wind turbine generator set grid-connected system. The constructed reduced-order model can better reflect the transient response characteristics of the system and can greatly reduce the calculation time; the constructed reduced-order model can lay a foundation for subsequent stability analysis and can more accurately judge the stability and stability change trend of the system; in addition, the dominance of each state variable is obtained by using the sensitivity analysis method to analyze the transient dominant instability variables of the system, and there are no restrictions on the types and control methods of the equipment.

[0128] Figure 6The structural schematic diagram of the device for showing the reduced - order model of the grid - connected system of a direct - drive wind turbine according to an embodiment of the present invention is shown.

[0129] As Figure 6 shown, the device includes:

[0130] A first construction unit 601, configured to construct an electromagnetic transient model of the grid - connected system of the direct - drive wind turbine based on the transient response characteristics of each control link in the direct - drive wind turbine;

[0131] A first processing unit 602, configured to obtain the dominance of each state variable in the grid - connected system of the direct - drive wind turbine by using the sensitivity analysis method based on the electromagnetic transient model of the grid - connected system of the direct - drive wind turbine;

[0132] A second processing unit 603, configured to determine the multi - time - scale division and key variables of the grid - connected system of the direct - drive wind turbine according to the dominance of each state variable in the grid - connected system of the direct - drive wind turbine;

[0133] A second construction unit 604, configured to construct a reduced - order model of the grid - connected system of the direct - drive wind turbine by using the singular perturbation method based on the multi - time - scale and key variables of the grid - connected system of the direct - drive wind turbine.

[0134] Further, the first construction unit 601 is further configured to:

[0135] The differential equation for constructing the electromagnetic transient model of the grid - connected system of the direct - drive wind turbine includes:

[0136]

[0137] In the formula: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, U dcref is the DC capacitor voltage reference value, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, U t is the terminal voltage, U tref is the terminal voltage reference value, τ3 is the response speed of the current control process, x3 is the output state variable of the d - axis current control process, x4 is the output state variable of the q - axis current control process, i d 、i q are the current components of the grid - side converter in the dq - axis coordinate system, i dref 、i qref are the current reference values in the dq - coordinate system respectively, τ C is the DC voltage state variable change time constant, P is the electric power, P m is the mechanical power, τ pll is the response speed of the phase - locked loop control process, θ pllis the phase angle output by the phase-locked loop, ω0 is the rated angular velocity of the system, ω pll is the angular velocity output by the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, u td 、u tq are the terminal voltage components in the dq coordinate system respectively, τ ω is the response speed of the main circuit of the system, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinates, L f is the filter inductor.

[0138] Furthermore, the first processing unit 602 is further configured to:

[0139] Determine the data of each state variable in the grid-connected system of the direct-drive wind turbine under each scenario, where the state variables include x1, x2, U dc and θ pll ;

[0140] Change the parameters of each control link and the system operating conditions, and determine the dominance of each state variable under each scenario.

[0141] Furthermore, the second processing unit 603 is further configured to:

[0142] Classify the state variables according to the magnitudes of the time constants of different state variables, and divide the grid-connected system of the direct-drive wind turbine into fast and slow subsystems;

[0143] Based on the dominance of each state variable under each scenario, determine the dominant variable that causes the system to become unstable, and with reference to the time scale of the dominant state variable, determine the key variable that dominates the system dynamics at the time scale of the dominant state variable.

[0144] Furthermore, the second construction unit 604 is further configured to:

[0145] [[ID=...]] Arrange and represent the fan model under the DC voltage time scale in the singular perturbation form as follows:

[0146]

[0147] In the formula: f(θ pll ,i d ) is the state equation of the slow subsystem, g(θ pll ,i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on a long time scale and reflects the dominant dynamic characteristics of the system, i d describes the dynamic behavior of the system on a short time scale, μ = 1 / K p,pll, which is a small positive real parameter, is mainly used to characterize the multi-scale characteristics of the system in singular perturbation problems and simplifies the problem-solving process through asymptotic expansion. K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop. K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage. is the injected power on the DC side. C dc is the capacitance of the DC capacitor. l g is the system line impedance. i d is the d-axis current output by the voltage control using DC voltage control. ω pll is the angular velocity of the phase-locked loop.

[0148] In the above embodiments, based on the transient response characteristics of each control link in the direct-drive wind turbine generator set, an electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system is constructed. Based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system, the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system is obtained. According to the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, the multi-time scale division and key variable determination of the direct-drive wind turbine generator set grid-connected system are completed. And for the multi-time scale and key variables of the direct-drive wind turbine generator set grid-connected system, the singular perturbation method is used to construct a reduced-order model of the direct-drive wind turbine generator set grid-connected system. The constructed reduced-order model can better reflect the transient response characteristics of the system and can greatly reduce the calculation time; the constructed reduced-order model can lay a foundation for subsequent stability analysis and can more accurately judge the stability and stability change trend of the system; in addition, the dominance of each state variable is obtained by using the sensitivity analysis method to analyze the transient dominant instability variables of the system, and there are no restrictions on the types and control methods of the equipment.

[0149] It should be noted that when the device provided in the above embodiments realizes its functions, only the above division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device provided in the above embodiments and the method embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments, which will not be elaborated here.

[0150] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for constructing a reduced-order model of a direct-drive wind turbine grid-connected system provided in each of the above embodiments is implemented.

[0151] An embodiment of the present invention also provides an electronic device, including: a processor; a memory for storing processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method for constructing a reduced-order model of a direct-drive wind turbine grid-connected system provided in each of the above embodiments.

[0152] The present invention has been described by referring to a few embodiments. However, as is well known to those skilled in the art, other embodiments equivalent to those disclosed above of the present invention equally fall within the scope of the present invention as defined by the appended patent claims.

[0153] Generally, all terms used in the claims are construed according to their ordinary meanings in the technical field, unless otherwise clearly defined therein. All references to "a / the [device, component, etc.]" are to be construed openly as at least one instance of the device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed, unless expressly stated.

[0154] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0155] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows or multiple flows and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0156] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in one or more of the blocks or blocks.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in one or more of the blocks or blocks.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A method for constructing a reduced-order model of a direct-drive wind turbine grid-connected system, characterized in that, The method includes: Based on the transient response characteristics of each control link in the direct-drive wind turbine generator set, an electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system is constructed; Based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system, the sensitivity analysis method is used to obtain the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system; According to the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, the multi-time scale division and key variables of the direct-drive wind turbine generator set grid-connected system are determined; Based on the multi-time scale and key variables of the direct-drive wind turbine generator set grid-connected system, the singular perturbation method is used to construct a reduced-order model of the direct-drive wind turbine generator set grid-connected system.

2. The method according to claim 1, characterized in that, The constructing of the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system based on the transient response characteristics of each control link in the direct-drive wind turbine generator set includes: The differential equations for constructing the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system include: Where: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, U dcref is the reference value of the DC capacitor voltage, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, U t is the terminal voltage, U tref is the reference value of the terminal voltage, τ3 is the response speed of the current control process, x3 is the output state variable of the d-axis current control process, x4 is the output state variable of the q-axis current control process, i d 、i q are the current components of the grid-side converter in the dq-axis coordinate system, i dref 、i qref are the current reference values in the dq coordinate system respectively, τ C is the change time constant of the DC voltage state variable, P is the electric power, P m is the mechanical power, τ pll is the response speed of the phase-locked loop control process, θ pll is the phase angle output by the phase-locked loop, ω0 is the rated angular velocity of the system, ω pll is the angular velocity output by the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, u td 、u tq are the terminal voltage components in the dq coordinate system respectively, τ ω is the response speed of the main circuit of the system, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinate system, L f is the filter inductor.

3. The method according to claim 2, wherein Based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system, the sensitivity analysis method is used to obtain the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, including: Determine the data of each state variable in each scenario in the grid-connected system of a direct-drive wind turbine, where the state variables include x1, x2, U dc and θ pll ; Changing the parameters of each control link and the system operating conditions, and determining the dominance of each state variable in each scenario.

4. The method according to claim 1, characterized in that, According to the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system, the multi-time scale division and key variables of the direct-drive wind turbine generator set grid-connected system are determined, including: Classifying the state variables according to the magnitudes of the time constants of different state variables, and dividing the direct-drive wind turbine generator set grid-connected system into fast and slow subsystems; Based on the dominance of each state variable in each scenario, determining the dominant variables that cause system instability, and taking the time scale of the dominant state variable as a reference, determining the key variables that dominate the system dynamics at the time scale of the dominant state variable.

5. The method according to claim 1, wherein Based on the multi-time scale and key variables of the direct-drive wind turbine generator set grid-connected system, the singular perturbation method is used to construct a reduced-order model of the direct-drive wind turbine generator set grid-connected system, including: Arranging and expressing the fan model under the DC voltage time scale in the form of singular perturbation as follows: where: f(θ pll , i d ) is the state equation of the slow subsystem, g(θ pll , i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on a long time scale and reflects the dominant dynamic characteristics of the system, and i d describes the dynamic behavior of the system on a short time scale. μ = 1 / K p,pll , which is a small positive real parameter, is mainly used to characterize the multi-scale characteristics of the system in singular perturbation problems and simplifies the solution process of the problem through asymptotic expansion. K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop. K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage, is the injected power on the DC side, C dc is the capacitance of the DC capacitor, l g is the system line impedance, i d is the d-axis current output by the DC voltage control for voltage control, and ω pll is the angular velocity of the phase-locked loop.

6. A device for constructing a reduced-order model of a direct-drive wind turbine grid-connected system, characterized in that The device includes: The first construction unit is used to construct an electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system based on the transient response characteristics of each control link in the direct-drive wind turbine generator set; The first processing unit is used to obtain the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system based on the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system by using the sensitivity analysis method; The second processing unit is used to determine the multi-time scale division and key variables of the direct-drive wind turbine generator set grid-connected system according to the dominance of each state variable in the direct-drive wind turbine generator set grid-connected system; The second construction unit is used to construct a reduced-order model of the direct-drive wind turbine generator set grid-connected system based on the multi-time scale and key variables of the direct-drive wind turbine generator set grid-connected system by using the singular perturbation method.

7. The device according to claim 6, characterized in that, The first construction unit is further used for: The differential equations for constructing the electromagnetic transient model of the direct-drive wind turbine generator set grid-connected system include: Where: τ1 is the response speed of the DC voltage control process, x1 is the output state variable of the DC voltage control process, U dc is the DC capacitor voltage, U dcref is the reference value of the DC capacitor voltage, τ2 is the response speed of the terminal voltage control process, x2 is the output state variable of the terminal voltage control process, U t is the terminal voltage, U tref is the reference value of the terminal voltage, τ3 is the response speed of the current control process, x3 is the output state variable of the d-axis current control process, x4 is the output state variable of the q-axis current control process, i d 、i q are the current components of the grid-side converter in the dq-axis coordinate system, i dref 、i qref are the current reference values in the dq coordinate system respectively, τ C is the change time constant of the DC voltage state variable, P is the electric power, P m is the mechanical power, τ pll is the response speed of the phase-locked loop control process, θ pll is the output phase angle of the phase-locked loop, ω0 is the rated angular velocity of the system, ω pll is the output angular velocity of the phase-locked loop, τ4 is the response speed of the phase-locked loop control process, u td 、u tq are the terminal voltage components in the dq coordinate system respectively, τ ω is the response speed of the main circuit of the system, e d 、e q are the voltage components of the grid-side converter in the dq-axis coordinate system, L f is the filter inductor.

8. The device according to claim 7, characterized in that, The first processing unit is further used for: Determine the data of each state variable in each scenario in the grid-connected system of a direct-drive wind turbine, where the state variables include x1, x2, U dc and θ pll ; Changing the parameters of each control link and the system operating conditions, and determining the dominance of each state variable in each scenario.

9. The device according to claim 6, characterized in that The second processing unit is further used for: Classify the state variables according to the magnitudes of the time constants of different state variables, and divide the grid-connected system of the direct-drive wind turbine into fast and slow subsystems; Based on the dominance of each state variable in each scenario, determine the dominant variables that cause system instability, and with reference to the time scale of the dominant state variable, determine the key variables that dominate the system dynamics at the time scale of the dominant state variable.

10. The device according to claim 6, characterized in that, The second construction unit is further configured to: Organize and represent the fan model under the DC voltage time scale in the singular perturbation form as follows: where: f(θ pll , i d ) is the state equation of the slow subsystem, g(θ pll , i d ) is the state equation of the fast subsystem, where θ pll is used to characterize the dynamic response of the system on a long time scale, reflecting the dominant dynamic characteristics of the system, i d describes the dynamic behavior of the system on a short time scale, μ = 1 / K p,pll , which is a small positive real parameter and is mainly used to characterize the multi-scale characteristics of the system in singular perturbation problems, simplifying the solution process of the problem through asymptotic expansion. K p,pll and K i,pll are the integral coefficient and proportional coefficient of the phase-locked loop, K p,dc and K i,dc are the integral coefficient and proportional coefficient of the DC voltage control loop. The current control response speed is relatively fast, and its dynamic characteristics can be ignored. The grid-side converter is equivalent to a current source, and the active and reactive current values are equal to their reference values, that is, i d = i dref , i q = i qref , U g is the grid voltage, is the injected power on the DC side, C dc is the capacitance of the DC capacitor, l g is the line impedance of the system, i d is the d-axis current output by the DC voltage control for voltage control, ω pll is the angular velocity of the phase-locked loop.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the method according to any one of claims 1-5 is implemented.

12. An electronic device, comprising: A processor; A memory for storing executable instructions of the processor; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1-5.

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