Virtual inertia adaptive control method, device and system

Abstract

The application provides a virtual inertia adaptive control method, device and system, and relates to the technical field of inverter system control. The method comprises the following steps: a reference current value is calculated according to a power reference value and an actual output voltage; a current deviation value is calculated according to the reference current value and an actual output current value; the current deviation value is output to an adaptive resonance controller to obtain a compensation control voltage signal; the compensation control signal is input to an AHO virtual oscillator to obtain a reference value of an inverter output voltage; and the output of a three-phase inverter circuit is controlled according to the reference value of the inverter output voltage. The adaptive resonance controller performs adaptive control through a proportional parameter and a proportional resonance inertia parameter. The application can dynamically adjust the virtual inertia output according to the real-time demand of the system, effectively suppresses the overshoot phenomenon caused by power oscillation while meeting the frequency stability, and enhances the ability of the system to resist load mutation and frequency disturbance.

Description

Technical Field

[0001] This invention relates to the field of inverter system control technology, and in particular to a virtual inertia adaptive control method, device and system. Background Technology

[0002] New energy sources such as solar and wind power exhibit natural fluctuations and are significantly affected by weather. This intermittency can lead to unstable power supply. Furthermore, unlike traditional synchronous generators, these new energy sources provide almost no mechanical rotational inertia, thus failing to provide frequency support and impacting system frequency stability. Grid-Forming (GFM) inverters, initially introduced for microgrid and islanded grid applications, are now considered a viable solution to improve the stability and resilience of interconnected power systems.

[0003] Existing GFM control technologies mainly include droop control, Virtual Synchronous Generator (VSG), and Virtual Oscillator Control (VOC). Traditional droop control can regulate the inverter's output voltage by simulating the droop characteristics during power transmission, but it lacks the ability to provide inertial support for the power system. VSG control can simulate the swing equation of a synchronous generator and can provide inertia and damping, but its power response behaves like a typical second-order system, inevitably leading to power oscillations. VOC is an emerging GFM control that can simulate the near-sinusoidal oscillatory response of a weakly nonlinear limiting periodic oscillator. Its average dynamics of output voltage and frequency over an AC cycle have an embedded nonlinear droop law, exhibiting faster dynamic response and lower harmonic content.

[0004] An AHO (Andronov-Hopf) oscillator is a VOC more suitable for grid-connected inverters, capable of generating harmonic-free waveforms without affecting dynamic performance. However, oscillator-based control is a first-order controller without inertia, making it susceptible to load or frequency disturbances. Therefore, it is necessary to add a controller to the traditional AHO to generate a suitable inertial response. Furthermore, existing control methods only consider the rate of frequency change and deviation, and provide a fixed inertia, making it difficult to simultaneously meet the dual performance requirements of frequency stability and power oscillation overshoot suppression. Summary of the Invention

[0005] This invention provides a virtual inertia adaptive control method, device, and system to solve the technical problem that existing control methods cannot simultaneously meet the two major performance requirements of frequency stability and power oscillation overshoot suppression.

[0006] In a first aspect, embodiments of the present invention provide a virtual inertia adaptive control method, comprising:

[0007] Based on the reference value of active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current ;

[0008] Calculate separately α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ;

[0009] Will α Shaft current deviation value and β Shaft current deviation value Input to adaptive resonant controller Through an adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0010] Among them, adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers;

[0011] Will α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Input to the AHO virtual oscillator, and obtain the result through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0012] according to α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit.

[0013] In one possible implementation, based on a reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft ,calculate α Shaft reference current and β Shaft reference current The calculation formula is:

[0014]

[0015] in, The magnitude of the voltage vector, .

[0016] In one possible implementation, an adaptive resonant controller is used. get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Specifically, it includes:

[0017] Obtaining an adaptive resonant controller Output α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0018] in, α Shaft compensation control voltage signal and β Shaft compensation control voltage signal For adaptive resonant controller Based on the input α Shaft current deviation value and β Shaft current deviation value Calculatedα Shaft compensation control voltage signal and β Shaft compensation control voltage signal The calculation formula is:

[0019]

[0020] Adaptive Resonant Controller The transfer function is:

[0021]

[0022] in, This is the proportionality coefficient. For resonant inertial parameters, For proportional resonant inertial parameters, This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. s For the Laplace operator.

[0023] In one possible implementation, it is obtained via an AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Specifically, it includes:

[0024] Obtain the output of the AHO virtual oscillator α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0025] in, α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage It is an AHO virtual oscillator based on α Shaft compensation control voltage signal and β Shaft compensation control voltage signal The expression for the nonlinear differential equation obtained by establishing and solving the nonlinear differential equation is as follows:

[0026]

[0027] in, and They are respectively α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Differential with respect to time; This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. To match the output voltage of the AHO virtual oscillator Related nonlinear terms, , μ This indicates the convergence rate of the AHO virtual oscillator. , This represents the effective value of the inverter voltage level. R ( θ ) is the rotation matrix of the power grid.

[0028] In one possible implementation, an adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters Jointly performing adaptive control, specifically including:

[0029] Adaptive Resonant Controller Based on the dynamic response curve of the system's output angular frequency ω, the proportional parameter is compared. Sum of proportional resonant inertial parameters Perform phased adaptive adjustments.

[0030] In one possible implementation, the scaling parameter is adjusted based on the dynamic response curve of the system output angular frequency ω. Sum of proportional resonant inertial parameters Implement phased adaptive adjustments, specifically including:

[0031] System output angular frequency ω During the first stage of rising to the peak and the third stage of falling to the trough, the proportional resonant inertial parameter is reduced. To increase the system's virtual inertia;

[0032] System output angular frequency ω Increase the scaling parameter in the second stage of the decline from the peak and in the fourth stage of the rise from the trough. To enhance system damping.

[0033] In one possible implementation, based on a reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current Previously, the methods also included:

[0034] The three-phase output voltage of the three-phase inverter was measured. ;

[0035] Three-phase output voltage conduct abc / αβ Coordinate transformation α actual output voltage of shaft and β actual output voltage of shaft .

[0036] In one possible implementation, calculate separately α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value Previously, the methods also included:

[0037] The three-phase output current of the three-phase inverter was measured. ;

[0038] Three-phase output current conduct abc / αβ Coordinate transformation α Actual output current of the shaft and β Actual output current of the shaft .

[0039] Secondly, embodiments of the present invention provide a virtual inertia adaptive control device, including a control module and an adaptive resonant controller. And AHO virtual oscillator; the control module includes:

[0040] The first calculation unit is used to calculate based on the reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current andβ Shaft reference current ;

[0041] The second calculation unit is used to calculate separately. α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ;

[0042] The first processing unit is used to process... α Shaft current deviation value and β Shaft current deviation value Input to adaptive resonant controller Through an adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0043] Among them, adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers;

[0044] The second processing unit is used to process... α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Input to the AHO virtual oscillator, and obtain the result through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0045] Signal generation unit, used to generate signals according to... α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit.

[0046] Thirdly, embodiments of the present invention provide a virtual inertia adaptive control device and a three-phase inverter circuit as described in the first aspect.

[0047] In this embodiment of the invention, a reference current value is calculated based on a power reference value and the actual output voltage; a current deviation value is calculated based on the reference current value and the actual output current value; the current deviation value is output to an adaptive resonant controller to obtain a compensation control voltage signal; the compensation control signal is input to an AHO virtual oscillator to obtain a reference value for the inverter output voltage; and the output of the three-phase inverter circuit is controlled based on the reference value of the inverter output voltage. The adaptive resonant controller performs adaptive control through a combination of proportional parameters and proportional resonant inertial parameters. The proportional parameters dynamically adjust the system damping characteristics to suppress power oscillation overshoot, while the proportional resonant inertial parameters control the magnitude of the virtual inertia to reduce the rate of frequency change and deviation. This invention can dynamically adjust the virtual inertia output according to the real-time needs of the system, effectively suppressing overshoot caused by power oscillations while maintaining frequency stability. This enhances the system's ability to withstand load changes and frequency disturbances, providing a more robust and flexible inertial support solution for high-proportion renewable energy grid integration. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating the implementation of the virtual inertia adaptive control method provided in this embodiment of the invention.

[0049] Figure 2 This is a schematic diagram of the inverter system provided in an embodiment of the present invention;

[0050] Figure 3 This is provided by an embodiment of the invention based on the system output angular frequency. ω A schematic diagram illustrating the four stages of a dynamic response curve;

[0051] Figure 4 The proportional parameters provided in the embodiments of the present invention Flowchart of adjustments involved in adaptive control;

[0052] Figure 5 The proportional resonant inertial parameters provided in the embodiments of the present invention Flowchart of adjustments involved in adaptive control;

[0053] Figure 6 This invention provides a controller using R, PR, and PR+R. P * Comparison of output frequency variation curves from 0kW to 15kW;

[0054] Figure 7 This invention provides a controller using R, PR, and PR+R. P* Comparison of inverter output active power curves from 0kW to 15kW;

[0055] Figure 8 The embodiments of the present invention provide the use of fixed controller parameters and parameters. , When adapting, P * Comparison of output frequency variation curves from 10kW to 5kW;

[0056] Figure 9 The embodiments of the present invention provide the use of fixed controller parameters and parameters. , When adapting, P * Comparison of active power changes in the power grid from 10kW to 5kW;

[0057] Figure 10 The embodiments of the present invention provide a fixed controller parameter and an adopted parameter. , A comparison of the waveforms of the inverter output current during adaptive operation;

[0058] Figure 11 The adaptive control provided by this invention At that time, parameters Based on the system's dynamic real-time change graph;

[0059] Figure 12 The adaptive control provided by this invention At that time, parameters Based on the system's dynamic real-time change graph;

[0060] Figure 13 This is a schematic diagram of the structure of the virtual inertia adaptive control device provided by the present invention. Detailed Implementation

[0061] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0062] Figure 1 This is a flowchart illustrating the implementation of the virtual inertia adaptive control method provided in an embodiment of the present invention. Figure 1 As shown, the virtual inertia adaptive control method includes steps 101 to 105.

[0063] Specifically, this virtual inertia adaptive control method is applied to the virtual inertia adaptive control device in the inverter system. Figure 2 This is a schematic diagram of the inverter system provided in an embodiment of the present invention, as shown below. Figure 2As shown, the inverter system includes: a virtual inertia adaptive control device 2 and a three-phase inverter circuit 3. The three-phase inverter circuit 3 includes: a DC power supply. The system consists of a three-phase inverter bridge 31, an LC inverter 32, and a load circuit 33. The three-phase inverter bridge 31 is composed of six power switching transistors, and the LC inverter 32 is composed of a filter inductor. and filter capacitor The load circuit 33 comprises three load resistors. Equivalent inductance of three power grids and three grid voltages composition.

[0064] See Figure 1 Step 101 includes: based on the reference value of active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current .

[0065] In practical applications, the reference value of active power P * Reference values ​​for reactive power Q * This can be generated by the upper-level management system, the local droop control algorithm, or the maximum power point tracking module, and then sent to the virtual inertia adaptive control device 2. Specifically, the reference value of active power... P * The sign of the symbol determines the direction of power flow in the three-phase inverter circuit 3, and the reference value of the active power. P * When the value is positive, the three-phase inverter circuit 3 supplies power to the grid; the reference value for active power. P * When the value is negative, the three-phase inverter circuit 3 absorbs reactive power from the grid. Reference value for reactive power. Q * Used to adjust the voltage support strength at the grid connection point.

[0066] in, α actual output voltage of shaft and β actual output voltage of shaft This is a real-time feedback quantity characterizing the current grid voltage state. Specifically, it can be obtained by measuring the three-phase inverter circuit 3 and then performing a coordinate transformation.

[0067] Understandably, this is achieved by using a comprehensive reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft By decoupling the power control target into a reference current, and then proceeding with subsequent steps based on this, it can be ensured that the inverter's output power can quickly and accurately meet the active power reference value. P * Reference values ​​for reactive power Q * This requirement laid a solid foundation for subsequent virtual inertia adaptive control.

[0068] For example, in one possible implementation, prior to step 101 above, the method further includes:

[0069] The three-phase output voltage of the three-phase inverter was measured. ;

[0070] Three-phase output voltage conduct abc / αβ Coordinate transformation α actual output voltage of shaft and β actual output voltage of shaft .

[0071] In practical applications, obtaining reference values ​​for active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft and calculate to obtain α Shaft reference current and β Shaft reference current .

[0072] Specifically, combined Figure 2 In one possible implementation, the calculation in step 101 above... α Shaft reference current and β Shaft reference current The calculation formula is:

[0073]

[0074] in, The magnitude of the voltage vector, .

[0075] See Figure 1 Step 102 includes: calculating separately α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value .

[0076] Understandably, through calculation α Shaft current deviation value and β Shaft current deviation value This allows for a direct and quantifiable measurement of the difference between the inverter's actual output current and its expected output current. α Shaft current deviation value and β Shaft current deviation value As an adaptive resonant controller The input is used to dynamically adjust the adaptive resonant controller. The parameters are used to generate a compensating control voltage signal that can suppress oscillations and provide inertia.

[0077] in, α Actual output current of the shaft and β Actual output current of the shaft This is a real-time feedback quantity characterizing the current state of the power grid current. Specifically, it can be obtained by measuring the three-phase inverter circuit 3 and then performing coordinate transformation.

[0078] Specifically, combined Figure 2 In one possible implementation, prior to step 102 above, the method further includes:

[0079] The three-phase output current of the three-phase inverter was measured. ;

[0080] Three-phase output current conduct abc / αβ Coordinate transformation α Actual output current of the shaft and βActual output current of the shaft .

[0081] See Figure 1 Step 103 includes: α Shaft current deviation value and β Shaft current deviation value Input to adaptive resonant controller Through an adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal .

[0082] Among them, adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers.

[0083] In this embodiment, the adaptive resonant controller This is the core control unit of the present invention for realizing the dynamic adjustment of virtual inertia. It is essentially a PR+R (Proportional Resonant + Resonant) controller with reconfigurable parameters online. Through a dual-parameter collaborative adaptive mechanism, it provides the system with controllable dynamic characteristics that combine inertia support and oscillation suppression.

[0084] Preferably, in one possible implementation, step 103 above is performed using an adaptive resonant controller. get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Specifically, it includes:

[0085] Obtaining an adaptive resonant controller Output α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0086] in, α Shaft compensation control voltage signal and β Shaft compensation control voltage signal For adaptive resonant controller Based on the input α Shaft current deviation value andβ Shaft current deviation value Calculated α Shaft compensation control voltage signal and β Shaft compensation control voltage signal The calculation formula is:

[0087]

[0088] Adaptive Resonant Controller The transfer function is:

[0089]

[0090] in, This is the proportionality coefficient. For resonant inertial parameters, For proportional resonant inertial parameters, This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. s For the Laplace operator.

[0091] Specifically, for adaptive resonant controllers proportional parameters Sum of proportional resonant inertial parameters They jointly participate in adaptive control, while the resonant inertial parameters It remains unchanged.

[0092] Alternatively, in one possible implementation, an adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters Jointly performing adaptive control, specifically including:

[0093] Adaptive Resonant Controller Based on the system output angular frequency ω The dynamic response curve, relative to the proportional parameter Sum of proportional resonant inertial parameters Perform phased adaptive adjustments.

[0094] Understandably, the phased adaptive adjustment mechanism enables the on-demand allocation of system virtual inertia and system damping. This phased differentiated control allows the adaptive resonant controller to... The output accurately matches the real-time dynamic needs of the system, thereby achieving a dynamic optimal balance between inertia support and oscillation suppression. While providing fast frequency support, it effectively suppresses power overshoot, providing a new paradigm for grid construction control that combines speed and stability for high-proportion renewable energy power grids.

[0095] Alternatively, in one possible implementation, the above-mentioned scaling parameters are adjusted based on the dynamic response curve of the system output angular frequency ω. Sum of proportional resonant inertial parameters Implement phased adaptive adjustments, specifically including:

[0096] System output angular frequency ω During the first stage of rising to the peak and the third stage of falling to the trough, the proportional resonant inertial parameter is reduced. To increase the system's virtual inertia;

[0097] System output angular frequency ω Increase the scaling parameter in the second stage of the decline from the peak and in the fourth stage of the rise from the trough. To enhance system damping.

[0098] Figure 3 This is provided by an embodiment of the invention based on the system output angular frequency. ω A schematic diagram illustrating the four stages of a dynamic response curve, as shown below. Figure 3 As shown, based on the system output angular frequency ω The dynamic response curve can show the proportional parameter Sum of proportional resonant inertial parameters The adaptive adjustment process is divided into four stages.

[0099] Combination Figure 3 Phase 1 ( t 1- t At time 2, the dynamic response curve rises to its peak value for the first time from the initial value. t 2- t The dynamic response curve at time 3 drops from the peak value to the initial value, stage 3 ( t 3- t At time 4, the dynamic response curve continues to decrease from the initial value to the trough. t 4- t (Time 5) The dynamic response curve rises from the trough until the rate of change is zero.

[0100] In the above four stages, the proportional parameter Adjustments will be made according to the following principles:

[0101] Phase 1: Damping remains constant. Unchanged; Stage 2: Damping requirements increase. Increase; Stage 3: Damping remains unchanged, Unchanged; Stage 4: Damping requirements increase. Increase.

[0102] In the above four stages, the proportional resonant inertial parameters Adjustments will be made according to the following principles:

[0103] Phase 1: Inertia requirements increase. Phase 2: Inertia requirements are reduced. Increase; Stage 3: Inertia requirements increase. Phase 4: Inertia requirements are reduced. Increase.

[0104] Figure 4 The proportional parameters provided in the embodiments of the present invention The adjustment flowchart involved in adaptive control, combined with Figure 4 Specifically, the proportional parameter The adjustment process for adaptive control is as follows:

[0105] Step a1: First, give the initial scaling parameters. ,

[0106] Step b1: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 1; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M 1, then maintain the initial output scaling parameter. Otherwise, proceed to step c1;

[0107] Step c1: When At that time, make a judgment Is it greater than zero? If If the value is not greater than zero, then the initial output scaling parameter will be maintained. Otherwise, output , This is the proportional adaptive coefficient.

[0108] Figure 5 The proportional resonant inertial parameters provided in the embodiments of the present invention A flowchart illustrating the adjustments involved in adaptive control. (Combined with...) Figure 5 Specifically, proportional resonant inertial parameters The adjustment process for adaptive control is as follows:

[0109] Step a2: First, give the initial proportional resonant inertial parameters. ;

[0110] Step b2: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 2; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M2. Then maintain the initial output scaling parameter. Otherwise, proceed to step c2.

[0111] Step c2: When At that time, make a judgment Is it greater than zero? If If not greater than zero, then output Otherwise, output , The adaptive proportional resonant inertia coefficient.

[0112] Combination Figure 1 Step 104 includes: α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Input to the AHO virtual oscillator, and obtain the result through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage .

[0113] In this embodiment, the AHO virtual oscillator is the core network unit of the present invention. Its function is to simulate the dynamic characteristics of the nonlinear Andronov-Hopf oscillator and convert the compensation voltage signal generated by the adaptive resonant controller into the voltage reference signal of the inverter.

[0114] Alternatively, in one possible implementation, the above step 104 is obtained through an AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Specifically, it includes:

[0115] Obtain the output of the AHO virtual oscillator α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0116] in, α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage It is an AHO virtual oscillator based on α Shaft compensation control voltage signal and β Shaft compensation control voltage signal The expression for the nonlinear differential equation obtained by establishing and solving the nonlinear differential equation is as follows:

[0117]

[0118] in, and They are respectively α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Differential with respect to time; This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. To match the output voltage of the AHO virtual oscillator Related nonlinear terms, , μ This indicates the convergence rate of the AHO virtual oscillator. , This represents the effective value of the inverter voltage level. R ( θ ) is the rotation matrix of the power grid.

[0119] In this embodiment, R ( θ The expression for ) is:

[0120]

[0121] R ( θ It can be applied to different types of impedance, and is suitable when the network is purely inductive. When the network is purely resistive, .

[0122] Combination Figure 1 Step 105 includes: according to α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit.

[0123] Combination Figure 2 In practical applications, according to α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal. In one example, for α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ,conduct αβ / abc Inverse transformation is performed to obtain a reference value for the output voltage of the three-phase inverter. , , Furthermore, the reference value of the three-phase inverter output voltage... , , It is compared with a high-frequency triangular carrier wave. By comparing the instantaneous amplitude of each phase reference wave with the triangular carrier wave in real time, three pairs (six in total) of complementary PWM signals with duty cycles varying sinusoidally with time are generated.

[0124] Combination Figure 2 The PWM signal is applied to the control terminals of the six power switching transistors of the three-phase inverter bridge 31, controlling them to turn on and off at a high frequency in a specific sequence. This switching action accurately reproduces the waveform of the voltage reference signal, thereby enabling the DC power supply to... After the power is shaped by the three-phase inverter bridge 31 and the LC inverter 32, a reference value corresponding to the output voltage of the three-phase inverter is generated at the AC output terminal. , , Consistent three-phase sinusoidal AC voltage and current enable precise control of the three-phase inverter output.

[0125] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0126] To further illustrate the working principle and effectiveness of the virtual inertia adaptive control method in this application, specific examples are provided below.

[0127] Specifically, Figure 2 The fixed parameters are selected as follows: , The internet is purely emotional. The power grid frequency is 50Hz. Figure 4 middle M 1 = 0.03 , Figure 5 middle M 2 = 0.03, .

[0128] Figure 6 This invention provides a controller using R, PR, and PR+R. P * Comparison of output frequency variation curves from 0kW to 15kW. Figure 7This invention provides a controller using R, PR, and PR+R. P * A comparison of the inverter's output active power curves from 0kW to 15kW. The PR+R controller is the adaptive resonant controller provided in this application.

[0129] Depend on Figure 6 and Figure 7 The analysis and comparison show that the R controller and PR controller are effective in terms of system inertia and overshoot, respectively, but they cannot achieve both simultaneously. The PR+R controller used in this patent can achieve a better balance between reducing power overshoot and providing system inertia, and can suppress power overshoot while reducing the rate of frequency change and frequency deviation.

[0130] Figure 8 To use fixed controller parameters ( ω c =2pi; k p =0.25; ω i =9pi) and parameters , Jointly participate in adaptive change ( Fixed at 2pi; adaptive coefficient When this occurs, the system provides an active power reference value. P * A comparison of the output frequency change curves when jumping from 10kW to 5kW.

[0131] Figure 9 To use fixed controller parameters ( ω c =2pi; k p =0.25; ω i =9pi) and parameters , Jointly participate in adaptive change ( Fixed at 2pi; adaptive coefficient When the system's given active power reference value jumps from 10kW to 5kW, the curves showing the change in the active power of the power grid are compared.

[0132] Figure 10 To use fixed controller parameters ( ω c =2pi; k p =0.25; ω i =9pi) and using parameters , Jointly participate in adaptive change ( Fixed at 2pi; adaptive coefficient A waveform diagram comparing the inverter output current at the specified time. Figure 10 It can be seen that when using the traditional method with fixed parameters, the maximum output current is 29.2A, while after using adaptive control, the maximum output current is reduced to 28.5A. At the same time, the minimum output current is also significantly increased after using adaptive control compared to the traditional method.

[0133] Figure 11 The adaptive control provided by this invention At that time, parameters Based on the system's dynamic real-time change graph. Figure 12 The adaptive control provided by this invention At that time, parameters Based on the system's dynamic real-time change graph.

[0134] Depend on Figure 8-12 The analysis concludes that the inertia adaptive control method adopted in this application can dynamically adjust the controller parameters in real time according to the real-time needs of the system, thereby adaptively adjusting the output of virtual inertia. This allows the controller parameters to dynamically change and adjust within a small range near the optimal value without losing the selection of the optimal standard value, achieving a dual improvement in system inertia and overshoot performance. This enhances the system's ability to resist sudden load changes and frequency disturbances, and significantly improves dynamic stability.

[0135] In this embodiment of the invention, a reference current value is calculated based on a power reference value and the actual output voltage; a current deviation value is calculated based on the reference current value and the actual output current value; the current deviation value is output to an adaptive resonant controller to obtain a compensation control voltage signal; the compensation control signal is input to an AHO virtual oscillator to obtain a reference value for the inverter output voltage; and the output of the three-phase inverter circuit is controlled based on the reference value of the inverter output voltage. The adaptive resonant controller performs adaptive control through a combination of proportional parameters and proportional resonant inertial parameters. The proportional parameters dynamically adjust the system damping characteristics to suppress power oscillation overshoot, while the proportional resonant inertial parameters control the magnitude of the virtual inertia to reduce the rate of frequency change and deviation. This invention can dynamically adjust the virtual inertia output according to the real-time needs of the system, effectively suppressing overshoot caused by power oscillations while maintaining frequency stability. This enhances the system's ability to withstand load changes and frequency disturbances, providing a more robust and flexible inertial support solution for high-proportion renewable energy grid integration.

[0136] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0137] Figure 13This is a schematic diagram of the virtual inertia adaptive control device provided by the present invention, as shown below. Figure 13 As shown, the virtual inertia adaptive control device 2 includes: a control module 21 and an adaptive resonant controller. 22 and AHO virtual oscillator 23; control module 21 includes:

[0138] The first calculation unit 211 is used to calculate based on the reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current ;

[0139] The second calculation unit 212 is used to calculate respectively. α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ;

[0140] The first processing unit 213 is used to process... α Shaft current deviation value and β Shaft current deviation value Input to adaptive resonant controller 22, through an adaptive resonant controller 22 obtained α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0141] Among them, adaptive resonant controller 22. Through proportional parameters Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers;

[0142] The second processing unit 214 is used to process... α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Input is sent to AHO virtual oscillator 23, and obtained through AHO virtual oscillator 23 α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0143] Signal generation unit 215, used for... α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit.

[0144] Alternatively, in one possible implementation, the first calculation unit 211 calculates based on a reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft ,calculate α Shaft reference current and β Shaft reference current The calculation formula is:

[0145]

[0146] in, The magnitude of the voltage vector, .

[0147] Alternatively, in one possible implementation, an adaptive resonant controller 22, used based on the input α Shaft current deviation value and β Shaft current deviation value Calculation obtained α Shaft compensation control voltage signal and β Shaft compensation control voltage signal The calculation formula is:

[0148]

[0149] Adaptive Resonant Controller The transfer function of 22 is:

[0150]

[0151] in, This is the proportionality coefficient. For resonant inertial parameters, For proportional resonant inertial parameters, This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. s For the Laplace operator;

[0152] The first processing unit 213 is used to control the adaptive resonant controller. 22 obtained α Shaft compensation control voltage signal and β Shaft compensation control voltage signal When, specifically used for:

[0153] Obtaining an adaptive resonant controller 22 output α Shaft compensation control voltage signal and β Shaft compensation control voltage signal .

[0154] Alternatively, in one possible implementation, the AHO virtual oscillator 23 is used to establish the solution. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage The nonlinear differential equation is:

[0155]

[0156] in, and They are respectively α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Differential with respect to time; This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. To match the output voltage of the AHO virtual oscillator Related nonlinear terms, , μ This indicates the convergence rate of the AHO virtual oscillator. , This represents the effective value of the inverter voltage level. R ( θ) is the rotation matrix of the power grid. R ( θ The expression for ) is:

[0157]

[0158] The AHO virtual oscillator 23 is also used to solve nonlinear differential equations to obtain... α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0159] The second processing unit 214 is used to obtain through the AHO virtual oscillator 23 α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage When, specifically used for:

[0160] Obtain the output of the AHO virtual oscillator α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage .

[0161] Alternatively, in one possible implementation, an adaptive resonant controller 22 is used to pass the proportional parameter Sum of proportional resonant inertial parameters When performing adaptive control together, it is specifically used for:

[0162] Adaptive Resonant Controller 22. Based on the dynamic response curve of the system's output angular frequency ω, compare the proportional parameters. Sum of proportional resonant inertial parameters Perform phased adaptive adjustments.

[0163] Alternatively, in one possible implementation, an adaptive resonant controller 22 is used to adjust the proportional parameters based on the dynamic response curve of the system's output angular frequency ω. Sum of proportional resonant inertial parameters When performing phased adaptive adjustments, it is specifically used for:

[0164] During the first stage when the system output angular frequency ω rises to its peak value and the third stage when it falls to its trough, the proportional resonant inertial parameter is reduced. To increase the system's virtual inertia;

[0165] In the second stage, when the system output angular frequency ω decreases from its peak value, and in the fourth stage, when it increases from its trough value, the scaling parameter is increased. To enhance system damping.

[0166] Optionally, in one possible implementation, the control module 21 further includes:

[0167] The first measurement unit is used to measure and obtain the three-phase output voltage of the three-phase inverter. ;

[0168] The first conversion unit is used to convert the three-phase output voltage conduct abc / αβ Coordinate transformation α actual output voltage of shaft and β actual output voltage of shaft .

[0169] Optionally, in one possible implementation, the control module 21 further includes:

[0170] The second measurement unit is used to measure and obtain the three-phase output current of the three-phase inverter. ;

[0171] The second conversion unit is used to convert the three-phase output current conduct abc / αβ Coordinate transformation α Actual output current of the shaft and β Actual output current of the shaft .

[0172] In this embodiment of the invention, the first calculation unit calculates a reference current value based on the power reference value and the actual output voltage; the second calculation unit calculates a current deviation value based on the reference current value and the actual output current value; the first processing unit outputs the current deviation value to the adaptive resonant controller to obtain a compensation control voltage signal; the second processing unit inputs the compensation control signal to the AHO virtual oscillator to obtain a reference value for the inverter output voltage; and the signal generation unit controls the output of the three-phase inverter circuit based on the reference value of the inverter output voltage. The adaptive resonant controller performs adaptive control through a combination of proportional parameters and proportional resonant inertial parameters. The proportional parameters dynamically adjust the system damping characteristics to suppress power oscillation overshoot, while the proportional resonant inertial parameters control the virtual inertia magnitude to reduce the rate of frequency change and deviation. This invention can dynamically adjust the virtual inertia output according to the real-time needs of the system, effectively suppressing overshoot caused by power oscillations while maintaining frequency stability. This enhances the system's ability to withstand load changes and frequency disturbances, providing a more robust and flexible inertial support solution for high-proportion renewable energy grid integration.

[0173] Furthermore, embodiments of the present invention also provide an inverter system, including a virtual inertia adaptive control device and a three-phase inverter circuit as shown in the above embodiments. The virtual inertia adaptive control device is used for:

[0174] Based on the reference value of active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current ;

[0175] Calculate separately α Shaft reference current and α Actual output current of the shaft The difference between them, and β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ;

[0176] Will α Shaft current deviation value andβ Shaft current deviation value Input to adaptive resonant controller Through an adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ;

[0177] Among them, adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers;

[0178] Will α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Input to the AHO virtual oscillator, and obtain the result through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ;

[0179] according to α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit.

[0180] In one example, Figure 2 This is a schematic diagram of the inverter system provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the inverter system includes: a virtual inertia adaptive control device 2 and a three-phase inverter circuit 3. The three-phase inverter circuit 3 includes: a DC power supply. The system consists of a three-phase inverter bridge 31, an LC inverter 32, and a load circuit 33. The three-phase inverter bridge 31 is composed of six power switching transistors, and the LC inverter 32 is composed of a filter inductor. and filter capacitor The load circuit 33 comprises three load resistors. Equivalent inductance of three power grids and three grid voltages composition.

[0181] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0182] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A virtual inertia adaptive control method, characterized in that, include: Based on the reference value of active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current ; Calculate the above respectively α Shaft reference current and α Actual output current of the shaft The difference between them, and the aforementioned β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ; The α Shaft current deviation value and stated β Shaft current deviation value Input to adaptive resonant controller Through the adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ; Wherein, the adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers; The α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal Input is given to the AHO virtual oscillator, and the result is obtained through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ; According to the above α Reference value of shaft inverter output voltage and stated β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit; The adaptive resonance controller By a proportional parameter And a proportional-resonant-inertial parameter Carrying out adaptive control together, specifically comprising: The adaptive resonant controller Based on the dynamic response curve of the system output angular frequency ω, the proportional parameter is... and the proportional resonant inertial parameters Perform phased adaptive adjustments; the dynamic response curve according to the system output angular frequency ω, the proportional parameter and the proportional-resonant inertial parameter are adaptively adjusted in stages, specifically including: The system outputs angular frequency ω The proportional resonant inertial parameter decreases during the first stage of rising to the peak and the third stage of falling to the trough. To increase the system's virtual inertia; The system outputs angular frequency ω The scaling parameter is increased during the second stage of the decline from the peak and the fourth stage of the rise from the trough. To enhance system damping; For the proportional parameter The steps for phased adaptive adjustment include: Step a1: Given the initial scaling parameters ; Step b1: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 1; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M 1, then maintain the initial output scaling parameter. Otherwise, proceed to step c1; Step c1: When At that time, make a judgment Is it greater than zero? If If the value is not greater than zero, then the initial output scaling parameter will be maintained. Otherwise, output , This is the proportional adaptive coefficient; Regarding the proportional resonant inertial parameters The steps for phased adaptive adjustment include: Step a2: Given the initial proportional resonant inertial parameters ; Step b2: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 2; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M 2. Then maintain the initial output scaling parameter. Otherwise, proceed to step c2; Step c2: When At that time, make a judgment Is it greater than zero? If If not greater than zero, then output Otherwise, output , The adaptive proportional resonant inertia coefficient.

2. The virtual inertia adaptive control method according to claim 1, characterized in that, Based on the reference value of active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculate the α Shaft reference current and stated β Shaft reference current The calculation formula is: in, The magnitude of the voltage vector, .

3. The virtual inertia adaptive control method according to claim 1, characterized in that, The adaptive resonance controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal Specifically, it includes: Obtain the adaptive resonant controller The output of α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal ; Among them, the α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal For the adaptive resonant controller According to the input α Shaft current deviation value and stated β Shaft current deviation value The calculation obtained, the α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal The calculation formula is: The adaptive resonant controller The transfer function is: in, This is the proportionality coefficient. For resonant inertial parameters, For proportional resonant inertial parameters, This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. s For the Laplace operator.

4. The virtual inertia adaptive control method according to claim 1, characterized in that, The result is obtained through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Specifically, it includes: Obtain the output of the AHO virtual oscillator α Reference value of shaft inverter output voltage and stated β Reference value of shaft inverter output voltage ; Among them, the α Reference value of shaft inverter output voltage and stated β Reference value of shaft inverter output voltage The AHO virtual oscillator is based on the α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal The expression for the nonlinear differential equation obtained by establishing and solving the nonlinear differential equation is as follows: in, and They are respectively α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage Differential with respect to time; This represents the resonant frequency of the AHO virtual oscillator during non-forced sinusoidal oscillation. To match the output voltage of the AHO virtual oscillator Related nonlinear terms, , μ This indicates the convergence rate of the AHO virtual oscillator. , This represents the effective value of the inverter voltage level. R ( θ ) is the rotation matrix of the power grid.

5. The virtual inertia adaptive control method according to any one of claims 1-4, characterized in that, The reference value based on active power P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current Previously, the method also included: The three-phase output voltage of the three-phase inverter was measured. ; The three-phase output voltage conduct abc / αβ Coordinate transformation to obtain the α actual output voltage of shaft and stated β actual output voltage of shaft .

6. The virtual inertia adaptive control method according to any one of claims 1-4, characterized in that, The calculations are as follows α Shaft reference current and α Actual output current of the shaft The difference between them, and the aforementioned β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value Previously, the method also included: The three-phase output current of the three-phase inverter was measured. ; The three-phase output current conduct abc / αβ Coordinate transformation to obtain the α Actual output current of the shaft and β Actual output current of the shaft .

7. A virtual inertia adaptive control device, characterized in that, Includes control module and adaptive resonant controller and AHO virtual oscillator; the control module includes: The first calculation unit is used to calculate based on the reference value of active power. P * Reference values ​​for reactive power Q * , α actual output voltage of shaft and β actual output voltage of shaft Calculation obtained α Shaft reference current and β Shaft reference current ; The second calculation unit is used to calculate the above respectively. α Shaft reference current and α Actual output current of the shaft The difference between them, and the aforementioned β Shaft reference current and β Actual output current of the shaft The difference between them, to obtain α Shaft current deviation value and β Shaft current deviation value ; The first processing unit is used to process the... α Shaft current deviation value and stated β Shaft current deviation value Input to adaptive resonant controller Through the adaptive resonant controller get α Shaft compensation control voltage signal and β Shaft compensation control voltage signal ; Wherein, the adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters They work together to perform adaptive control, thereby achieving inertia control with quasi-resonant and proportional resonant controllers; The second processing unit is used to process the... α Shaft compensation control voltage signal and stated β Shaft compensation control voltage signal Input is given to the AHO virtual oscillator, and the result is obtained through the AHO virtual oscillator. α Reference value of shaft inverter output voltage and β Reference value of shaft inverter output voltage ; Signal generation unit, used to generate a signal according to the... α Reference value of shaft inverter output voltage and stated β Reference value of shaft inverter output voltage Generate a PWM signal to control the output of the three-phase inverter circuit; The adaptive resonant controller Through the proportional parameter Sum of proportional resonant inertial parameters When performing adaptive control together, it is specifically used for: The adaptive resonant controller Based on the dynamic response curve of the system output angular frequency ω, the proportional parameter is... and the proportional resonant inertial parameters Perform phased adaptive adjustments; The adaptive resonant controller The proportional parameter is used to adjust the dynamic response curve based on the system output angular frequency ω. and the proportional resonant inertial parameters Perform phased adaptive adjustments, specifically for: The system outputs angular frequency ω The proportional resonant inertial parameter decreases during the first stage of rising to the peak and the third stage of falling to the trough. To increase the system's virtual inertia; The system outputs angular frequency ω The scaling parameter is increased during the second stage of the decline from the peak and the fourth stage of the rise from the trough. To enhance system damping; For the proportional parameter The steps for phased adaptive adjustment include: Step a1: Given the initial scaling parameters ; Step b1: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 1; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M 1, then maintain the initial output scaling parameter. Otherwise, proceed to step c1; Step c1: When At that time, make a judgment Is it greater than zero? If If the value is not greater than zero, then the initial output scaling parameter will be maintained. Otherwise, output , This is the proportional adaptive coefficient; Regarding the proportional resonant inertial parameters The steps for phased adaptive adjustment include: Step a2: Given the initial proportional resonant inertial parameters ; Step b2: Determine the absolute value of the rate of change of the output angular frequency. Is it greater than the set threshold? M 2; If the absolute value of the rate of change of the output angular frequency Not greater than the set threshold M 2. Then maintain the initial output scaling parameter. Otherwise, proceed to step c2; Step c2: When At that time, make a judgment Is it greater than zero? If If not greater than zero, then output Otherwise, output , The adaptive proportional resonant inertia coefficient.

8. An inverter system, characterized in that, include: The virtual inertia adaptive control device and three-phase inverter circuit as described in claim 7.

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