Power decoupling method based on port Hamiltonian theory and through virtual impedance

Abstract

The invention relates to a power decoupling method based on a port Hamiltonian theory and through virtual impedance, and relates to the technical field of virtual synchronous generator control power decoupling. Based on the port Hamiltonian theory, a multi-channel collaborative optimization virtual impedance generation mechanism including anchoring, zero mean value self-adaption, event response and power angle deviation special self-adaption is constructed; by calculating a system energy coupling coefficient and an operation stress index, a multi-channel mechanism is combined to dynamically and adaptively adjust virtual resistance and virtual inductance parameters; and carrying out superposition, amplitude limiting and anti-saturation processing on the multi-channel output, generating a final virtual impedance instruction, and realizing dynamic decoupling control of active power and reactive power. According to the method, the power coupling oscillation of the virtual synchronous generator under the weak power grid condition can be effectively suppressed, the stability and robustness of the system are improved, and the method has good dynamic response capability and engineering practicability.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of virtual synchronous generator power decoupling control, in particular to a power decoupling method based on port Hamilton theory and through virtual impedance. BACKGROUND

[0002] Virtual synchronous generator control is widely used in microgrid control field. In complex working conditions, it is of great significance to realize real-time accurate management of microgrid, ensure the safety of microgrid use and prolong the service life of microgrid, and promote the development and popularization of photovoltaic energy storage and other industries. The virtual synchronous generator control strategy mainly depends on the accuracy of active control and reactive control. Therefore, the key to the current research on virtual synchronous generator control is the real-time accurate control of active-frequency control loop and reactive-voltage control loop.

[0003] In the prior art, the power decoupling methods include virtual power coordinate transformation method, virtual frequency and voltage coordinate transformation method, and controlled object linearization method. These methods have their own characteristics, but most of them have the shortcomings of low estimation accuracy and poor accuracy.

[0004] At present, there is no effective solution to the problem of low calculation accuracy and poor decoupling effect in the above power decoupling methods. SUMMARY

[0005] The purpose of the present application is to overcome the shortcomings of the prior art and provide a power decoupling method based on port Hamilton theory and through virtual impedance, which can solve the oscillation problem caused by VSG power coupling in weak power grid and improve the stability and dynamic performance of the system.

[0006] The technical problem of the present application is solved by the following technical scheme: The power decoupling method based on port Hamilton theory and through virtual impedance comprises the following steps: Step 1, obtaining the basic parameters of virtual synchronous generator control of microgrid system; Step 2, establishing a port Hamilton theory model of virtual synchronous generator control according to the basic parameters; Step 3, calculating the energy coupling coefficient of virtual synchronous generator control of microgrid system according to the port Hamilton theory model, quantifying the coupling degree between reactive power and active power in the system, and extracting the operating stress index therefrom; Step 4, constructing a multi-channel cooperative control mechanism and adaptively and dynamically adjusting the virtual resistance and virtual inductance according to the extracted operating stress index; Step 5, superimposing, limiting and anti-saturation processing the adjustment amount obtained by the multi-channel cooperative control mechanism to generate the final virtual resistance instruction value and virtual inductance instruction value; Step 6, the virtual resistance instruction value and the virtual inductance instruction value are applied to the virtual synchronous generator to realize dynamic decoupling control of active power and reactive power.

[0007] Furthermore, the basic parameters in the step 1 include an angle deviation, output active power, output reactive power, internal potential and terminal voltage.

[0008] Furthermore, the port Hamilton theory model in the step 2 includes state variables and a weight matrix representing the coupling relationship between the energy distribution of the system and the state variables.

[0009]

[0010] wherein, x [ delta , P , Q , E g , U g ] are state variables, H(x) is a Hamilton function (total energy of the system), J is an anti-symmetric matrix representing the energy flow structure, R is a symmetric semi-positive definite matrix representing the system dissipation, u and y are respectively the input and output of the system, is the rate of change of the state variable of the system with time, is the active power reference value and the reactive power reference value input into the energy port of the system, and is the driving source of the system.

[0011] Furthermore, the step 3 of calculating the energy coupling coefficient of the system includes the following steps. Step 3.1, calculating the elements in the weight matrix and dividing the matrix into a main diagonal element matrix representing the self-energy of each state variable and a non-diagonal element matrix representing the coupling degree; Step 3.2, calculating the self-energy and coupling energy of each state variable of the system, and taking the absolute value to ensure non-negativity; Step 3.3, calculating the proportion of the coupling energy in the total energy as the energy coupling coefficient.

[0012] Furthermore, the four parallel control channels in the step 4 include an anchoring control channel, a zero-mean adaptive control channel, an event response control channel and an angle deviation special adaptive control channel. The anchoring control channel adjusts the steady-state deviation of the virtual resistance and the virtual inductance through proportional-integral operation, so that the virtual impedance returns to the preset steady-state set point; The zero-mean adaptive control channel obtains a second adjustment amount of the virtual resistance according to the deviation of the operating stress index from the target stress through proportional-integral operation and limiting processing, and obtains a second adjustment amount of the virtual inductance according to the reactive power deviation through proportional-integral operation and limiting processing; The event response control channel determines that it is a large disturbance event when any one of the power angle deviation, the active power deviation or the terminal voltage deviation exceeds the set threshold, triggers the pulse type adjustment amount of the virtual resistance and the virtual inductance, and decays exponentially after the event ends or when the event end is not detected; The power angle deviation special adaptive control channel calculates the difference between the normalized absolute value of the power angle deviation and the expected normalized power angle deviation, performs proportional-integral operation and limiting processing to obtain the fourth adjustment amount of the virtual resistance and the virtual inductance, wherein the virtual resistance adjustment amount is positively correlated with the difference, and the virtual inductance adjustment amount is negatively correlated with the difference.

[0013] Moreover, the limiting and anti-saturation processing in step 5 includes the following steps: Step 5.1, dynamically constrain the single-step change amplitude of the adjustment amount; Step 5.2, asymmetrically limit the rising rate and the falling rate of the adjustment amount; Step 5.3, physically limit the final output value of the adjustment amount; Step 5.4, proportionally reduce the adjustment amount when the target value of the adjustment amount exceeds the physical range.

[0014] Moreover, the dynamic decoupling control of the active power and the reactive power in step 6 includes the following steps: Step 6.1, apply the virtual resistance instruction value and the virtual inductance instruction value generated in the above step 5 to the virtual impedance control loop of the virtual synchronous generator, adjust the amplitude and phase of the output reference voltage of the virtual synchronous generator, and realize the dynamic decoupling control of the active power and the reactive power; Step 6.2, online and real-time calculate the energy coupling coefficient of the system as an evaluation index of the decoupling effect; Step 6.3, evaluate the decoupling effect according to the energy coupling coefficient of the system.

[0015] The advantages and positive effects of the present application are: 1. Multi-dimensional collaborative optimization: The present application introduces an anchoring control strategy to solve the steady-state accuracy maintenance problem, a zero-mean adaptive strategy to solve the fast response problem, an event response strategy to solve the sudden event response problem, and a power angle deviation special adaptive strategy to solve the power angle oscillation problem, to realize the collaborative optimization of the virtual impedance under various working conditions, and effectively solve the contradiction between the steady-state accuracy and the dynamic performance.

[0016] 2. Strong stability: The control rate is designed based on the port Hamiltonian theory framework, which ensures the intrinsic passivity of the closed-loop system, improves the virtual impedance stability, and improves the robustness of the virtual synchronous generator control under weak grid.

[0017] 3. Significant power angle oscillation suppression effect, which improves power stability and decoupling performance. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flowchart of the adaptive virtual impedance generation method of the virtual synchronous generator provided by the embodiment of the present application; Figure 2 is a principle block diagram of generating a virtual impedance instruction value by multi-channel cooperative control in the embodiment of the present application; Figure 3 is a working principle schematic diagram of the anchor control channel in the embodiment of the present application; Figure 4 is a working principle schematic diagram of the zero-mean adaptive control channel in the embodiment of the present application; Figure 5 is a working principle schematic diagram of the event response control channel in the embodiment of the present application; Figure 6 is a working principle schematic diagram of the power angle deviation special adaptive control channel in the embodiment of the present application; Figure 7 is a flowchart of the superposition amplitude limiting process in the embodiment of the present application; Figure 8 is a structure block diagram of the adaptive virtual impedance generation device of the virtual synchronous generator provided by the embodiment of the present application; Figure 9 is a comparison diagram of the angular frequency response of the embodiment method and the traditional adaptive virtual impedance method under weak grid disturbance; Figure 10 is a comparison diagram of the active power response of the embodiment method and the traditional adaptive virtual impedance method under weak grid disturbance. DETAILED DESCRIPTION

[0019] The present application will be further described in detail below with reference to the accompanying drawings.

[0020] The commonly used virtual synchronous generator control virtual impedance generation methods at present include fixed value virtual impedance method, traditional adaptive virtual impedance method and the like. However, these virtual impedance generation methods often face the problems of single control target, poor weak grid adaptability, weak power decoupling ability and the like, and it is difficult to realize multi-target cooperative optimization virtual impedance generation and ensure the stability of the control system. Figure 2As shown, this invention treats the virtual synchronous generator grid-connected system as a port Hamiltonian system. The essence of adding virtual impedance is to change the dissipation terms of the port Hamiltonian system and adjust the energy flow structure. Adaptively adjusting the virtual resistance and virtual inductance is equivalent to dynamically injecting appropriate dissipation terms and adjusting the energy structure according to the changes in system state variables to suppress oscillations and stabilize the system.

[0021] Example 1: like Figure 8 As shown, this embodiment constructs a power decoupling system based on port Hamiltonian theory and virtual impedance, according to the power decoupling method based on port Hamiltonian theory and virtual impedance. The power decoupling system can be integrated into the controller of VSG, such as digital signal processor (DSP) or microcontroller (MCU).

[0022] The power decoupling system includes a parameter acquisition and preprocessing module, a coupling evaluation module, a multi-dimensional control module, a synthesis and constraint processing module, and an output and execution module. The output of the parameter acquisition and preprocessing module is connected to the input of the coupling evaluation module. The output of the coupling evaluation module is connected to the input of each unit in the multi-dimensional control module. The output of the multi-dimensional control module is connected to the input of the synthesis and constraint processing module. The output of the synthesis and constraint processing module is connected to the input of the output and execution module. The input of the output and execution module is connected to the system's virtual impedance control section for power decoupling.

[0023] The parameter acquisition and preprocessing module is used to establish the port Hamiltonian theoretical model of the virtual synchronous generator and to acquire the basic parameters of the virtual synchronous generator in real time.

[0024] The coupling evaluation module is used to calculate the real-time energy coupling coefficient of the virtual synchronous generator.

[0025] The multi-dimensional control module calculates the adaptive adjustment of the virtual impedance based on the "deviation degree" and "operating stress" of the physical quantities in each system state. It includes four parallel control units: an anchoring control unit, a zero-mean adaptive control unit, an event response control unit, and a power angle deviation-specific adaptive control unit. The anchoring control unit achieves error-free tracking of the virtual impedance to the steady-state setpoint; the zero-mean adaptive control unit provides dynamic damping and responds to system disturbances; the event response control unit handles stable control during large disturbances; and the power angle deviation-specific adaptive control unit specifically addresses disturbances caused by power angle deviations, controlling them independently and optimizing dynamic damping injection and energy shaping.

[0026] The synthesis and constraint processing module is used to superimpose the final adjustment of the virtual impedance onto the real-time parameters of the virtual impedance.

[0027] The output and execution module is used to output real-time parameters of the virtual impedance to perform power decoupling control on the virtual synchronous generator.

[0028] Example 2: Power decoupling methods based on port Hamiltonian theory and using virtual impedance, such as Figure 1 As shown, it includes the following steps: Step 1: Obtain the basic parameters for controlling the virtual synchronous generator in the microgrid system.

[0029] The basic parameters in step 1 include power angle deviation, output active power, output reactive power, internal potential, and terminal voltage.

[0030] Step 2: Establish a port Hamiltonian theoretical model for virtual synchronous generator control based on the basic parameters.

[0031] The port Hamiltonian model in step 2 includes: a weight matrix representing the energy distribution of the system and the coupling relationship between each state variable and the state variable. (1) (2) in, x =[ delta , P , Q , E g , U g ] is a state variable. delta For the power angle of the virtual synchronous generator, P This represents the actual active power. Q This represents the actual reactive power. E g The electromotive force of the virtual synchronous generator. U g Let be the grid voltage, H(x) be the Hamiltonian function (total system energy), J be an antisymmetric matrix representing the energy flow structure, R be a symmetric positive semi-definite matrix representing the system dissipation, and u and y be the system input and output, respectively. The rate of change of the system state variable over time. The energy port that inputs the active power reference value and reactive power reference value into the system is the driving source of the system.

[0032] Step 3: Based on the port Hamiltonian theoretical model, calculate the energy coupling coefficient of the virtual synchronous generator control in the microgrid system, quantify the degree of coupling between reactive power and active power in the system, and extract the operating stress index from it.

[0033] Step 3, calculating the system's energy coupling coefficient, includes the following steps: Step 3.1: Calculate the elements in the weight matrix and divide the matrix into a main diagonal element matrix representing the self-energy of each state variable and an off-diagonal element matrix representing the degree of coupling; Step 3.2: Calculate the self-energy and coupling energy of each state variable of the system, and take the absolute value to ensure non-negativity; Step 3.3: Calculate the proportion of coupled energy in the total energy, which is used as the energy coupling coefficient.

[0034] Step 4: Construct a multi-channel collaborative control mechanism and adaptively and dynamically adjust the virtual resistance and virtual inductance based on the extracted operating stress index.

[0035] The four parallel control channels in step 4 include the anchoring control channel, the zero-mean adaptive control channel, the event response control channel, and the power angle deviation-specific adaptive control channel; like Figure 3 As shown, the anchoring control channel ensures that the virtual impedance returns to the preset steady-state optimal setpoint during the steady-state operation of the virtual synchronous generator control, thus ensuring optimal steady-state performance of the virtual synchronous generator control. The working principle involves calculating the deviation between the current virtual impedance output command value and the set steady-state optimal operating point, and then using proportional-integral control to generate the first adjustment amount based on this deviation. From the perspective of port Hamiltonian theory, this is equivalent to applying a restoring force in the gradient direction of the energy function of the virtual synchronous generator control system to pull the system state back to the desired equilibrium point.

[0036] The virtual impedance proportional-integral controller for the anchoring control channel is: (3) (4) The meanings of the formula parameters are shown in Table 1: Table 1 Anchoring Channel PI Controller Parameters

[0037] like Figure 4 As shown, the zero-mean adaptive control channel provides a fast and flexible fine-tuning amount for virtual impedance adjustment when there is a sustained small-amplitude power stress deviation. However, in the long run, the average value of the second adjustment amount output by the zero-mean adaptive control channel is zero, and it does not affect the steady-state setpoint. Explained from the port Hamiltonian theory, the purpose of this channel is to dynamically adjust the dissipation and interconnect matrix to quickly suppress energy oscillations caused by power fluctuations through damping injection.

[0038] Its operating stress is: (5) The error of state variable s is defined as: (6) The virtual resistance saturation proportional-integral controller is: (7) The meanings of the formula parameters are shown in Table 2: Table 2 Calculation of Operating Stress and Adaptive Parameters of Virtual Resistance

[0039] The per-unit error of reactive power is defined as: (8) The virtual inductor saturation proportional-integral controller has been updated to: (9) The meanings of the formula parameters are shown in Table 3: Table 3 Reactive power response and virtual inductance adaptation

[0040] like Figure 5 As shown, the event response control channel provides pulsed virtual impedance regulation for sudden large disturbances, quickly suppressing excessive impacts on various state variables during system operation. Its working principle is as follows: 1. Real-time detection of power angle deviation, active power deviation, and generator terminal voltage; check if they exceed set thresholds. If they do, it is determined that a major disturbance event has occurred. Activate the event response control channel.

[0041] 2. After the control channel is started, the event response adjustment amount b of the virtual resistor. R and the event response adjustment amount b of the virtual inductor L Adjust the amounts according to the set formulas.

[0042] 3. Regardless of whether any new events occur within each control cycle, the virtual impedance adjustment decreases exponentially.

[0043] 4. During pulse accumulation and exponential decay, the virtual impedance adjustment is always limited to the upper and lower limits set by the formula, ensuring that the output event response adjustment is non-negative and does not exceed the upper limit.

[0044] 5. The adjusted amount after the limitation process is output as the adjustment amount of the event response channel to the superposition module and superimposed with the adjustment amounts of other channels.

[0045] From the perspective of port Hamiltonian theory, it involves injecting a large amount of dissipation instantaneously during a transient process to quickly consume the extra energy caused by the sudden change, thus preventing the system energy function from growing excessively and causing system instability.

[0046] Its variables The updated formula is: (10) (11) (12) (13) The meanings of the formula parameters are shown in Table 4: Table 4 Event Response Channel Parameters

[0047] like Figure 6 As shown, the power angle deviation adaptive control channel is specifically designed to suppress power angle oscillations. It independently adjusts the virtual impedance based on the power angle deviation to optimize energy decoupling and damping injection effects. From the perspective of port Hamiltonian theory, this channel precisely adjusts the injection damping according to the severity of the power angle oscillations, reducing the internal power coupling strength of the system and achieving precise control of the power angle.

[0048] Its normalized state variable for the work angle is: (14) The power angle error is defined as: (15) The output of the saturated proportional-integral controller is: (16) (17) The meanings of the formula parameters are shown in Table 5: Table 5 Adaptive Channel Parameters for Power Angle Deviation

[0049] Step 5: The adjustment values ​​obtained from the multi-channel collaborative control mechanism are superimposed, limited, and subjected to anti-saturation processing to generate the final virtual resistance command value and virtual inductance command value.

[0050] like Figure 7 As shown, the overlay, limiting, and anti-saturation processing includes the following steps: Step 5.1: Superimpose the outputs of the four channels to obtain the adjustment amount: (18) (19) The meanings of the formula parameters are shown in Table 6: Table 6 Virtual Impedance Synthesis and Engineering Constraint Parameters

[0051] Step 5.2: Dynamically constrain the single-step change range of the adjustment amount: (20) (twenty one) The meanings of the formula parameters are shown in Table 7: Table 7 Single-step limiting parameters

[0052] The formula for determining the upper limit of the target value is: (twenty two) Integral term update (discretized integral formula): (twenty three) (twenty four) (25) The upper limit of the target value is assigned as: (26) The meanings of the formula parameters are shown in Table 8: Table 8. Upper Limit Detection and Anti-Saturation Treatment Parameters

[0053] Step 5.2: Apply asymmetric restrictions to the rate of increase and rate of decrease of the adjustment quantity; The instruction value slope limit (rate limiting function) is: (27) (28) The meanings of the formula parameters are shown in Table 9: Table 9 Command Value Slope Limit Parameters

[0054] Step 5.3: Physically limit the final output value of the adjustment amount; The final output constraints (upper and lower boundary constraints) are: (29) (30) The meanings of the formula parameters are shown in Table 10: Table 10 Final Output Limiting Parameters

[0055] Step 5.4: When the target value of the adjustment amount exceeds the physical range, reduce the adjustment amount proportionally.

[0056] When the real-time adjustment command for the output virtual impedance is [ , The physical limits set within the control program have been exceeded. ],[ If this is the case, the virtual impedance adjustment of each channel output will be reduced proportionally to prevent integral saturation, while ensuring that the real-time output adjustment of each control channel remains at its original proportion to prevent secondary interference between them. Specifically: When the target value exceeds the upper limit, if the output of any control channel of the multi-control channel is positive, the real-time adjustment of each control channel will be reduced proportionally. When the target value exceeds the lower limit, if the output of any control channel of the multi-control channel is negative, the real-time adjustment of each control channel will be reduced proportionally.

[0057] This adjustment is based on real-time adjustment commands for virtual impedance. , The system also includes real-time output adjustment parameters for each channel (including anchoring, adaptive, event response, and power angle-specific channels). Simultaneously, the system performs four-channel coordinated control on the real-time output parameters of the virtual impedance, calculating and updating the cycle within each cycle of the control system. T s =1 / 20kHz, the real-time adjustment of the virtual impedance is updated and synthesized every 20 cycles, and the real-time parameters of the virtual impedance are updated to finally generate the real-time command values ​​of the virtual resistance Rv and the virtual inductance Lv.

[0058] Step 6: Apply the virtual resistance command value and the virtual inductance command value to the virtual synchronous generator to achieve dynamic decoupling control of active power and reactive power.

[0059] Step 6.1: Apply the virtual resistance command value and virtual inductance command value generated in Step 5 to the virtual impedance control loop of the virtual synchronous generator, adjust the amplitude and phase of the output reference voltage of the virtual synchronous generator, and realize the dynamic decoupling control of active power and reactive power. Step 6.2: Calculate the energy coupling coefficient of the system online in real time, as an evaluation index of the decoupling effect; Step 6.3: Evaluate the decoupling effect based on the system's energy coupling coefficient. If the energy coupling coefficient remains higher than the set threshold, adjust the multi-channel control parameters to enhance the decoupling capability.

[0060] Based on the aforementioned power decoupling method using port Hamiltonian theory and virtual impedance, a virtual synchronous generator grid-connected model was built in MATLAB / Simulink, and a weak grid scenario (short-circuit ratio of 0.42) was set up. Figure 9 andFigure 10 The paper presents a comparison of the angular frequency response (i.e., w) and active power response (i.e., P) of the virtual synchronous generator under the same grid disturbance, using the traditional adaptive virtual impedance and the port Hamiltonian virtual impedance method proposed in this invention.

[0061] from Figure 9 It can be seen that when using the traditional adaptive virtual impedance, the power angle exhibits significant oscillations after the disturbance. However, when using the method of this invention, the amplitude of the angular frequency oscillation is significantly reduced, the oscillation time is shortened, and the system recovers to a new stable state more quickly.

[0062] from Figure 10 It can be seen that the active power fluctuation under traditional adaptive impedance is large. The method of this invention eliminates the overshoot of active power and has no oscillation, making the power response more stable.

[0063] It should be emphasized that the embodiments described in this invention are illustrative rather than limiting. Therefore, this invention includes, but is not limited to, the embodiments described in the specific implementation. Any other implementations derived by those skilled in the art based on the technical solutions of this invention are also within the scope of protection of this invention.

Claims

1. A power decoupling method based on port Hamiltonian theory and using virtual impedance, characterized in that: Includes the following steps: Step 1: Obtain the basic parameters for controlling the virtual synchronous generator in the microgrid system; Step 2: Establish a port Hamiltonian theoretical model for virtual synchronous generator control based on the basic parameters; Step 3: Based on the port Hamiltonian theoretical model, calculate the energy coupling coefficient of the virtual synchronous generator control in the microgrid system, quantify the degree of coupling between reactive power and active power in the system, and extract the operating stress index from it. Step 4: Based on the extracted operating stress index, adaptively and dynamically adjust the virtual resistance and virtual inductance to construct a multi-channel collaborative control mechanism, including the anchoring control channel, the zero-mean adaptive control channel, the power angle deviation special control channel, and the event response control channel. Step 5: The adjustment values ​​obtained from the multi-channel collaborative control mechanism are superimposed, limited, and subjected to anti-saturation processing to generate the final virtual resistance command value and virtual inductance command value. Step 6: Apply the virtual resistance command value and the virtual inductance command value to the virtual synchronous generator to achieve dynamic decoupling control of active power and reactive power.

2. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: The basic parameters in step 1 include power angle deviation, output active power, output reactive power, internal potential, and terminal voltage.

3. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: The port Hamiltonian theoretical model in step 2 includes: a weight matrix representing the energy distribution of the system and the coupling relationship between each state variable and the state variable. ； ； in, x Let H(x) be the state variable, H(x) be the Hamiltonian function, J be an antisymmetric matrix representing the energy flow structure, R be a symmetric positive semi-definite matrix representing the system dissipation, and u and y be the system input and output, respectively. The rate of change of the system state variable over time. The energy port that inputs the active power reference value and reactive power reference value into the system is the driving source of the system.

4. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: Step 3, calculating the energy coupling coefficient of the system, includes the following steps: Step 3.1: Calculate the elements in the weight matrix and divide the matrix into a main diagonal element matrix representing the self-energy of each state variable and an off-diagonal element matrix representing the degree of coupling; Step 3.2: Calculate the self-energy and coupling energy of each state variable of the system, and take the absolute value to ensure non-negativity; Step 3.3: Calculate the proportion of coupled energy in the total energy, which is used as the energy coupling coefficient.

5. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: The four parallel control channels in step 4 include an anchoring control channel, a zero-mean adaptive control channel, an event response control channel, and a power angle deviation-specific adaptive control channel. The anchoring control channel adjusts the steady-state deviation of the virtual resistance and virtual inductance through proportional-integral calculation, so that the virtual impedance returns to the preset steady-state setpoint. The zero-mean adaptive control channel obtains the second adjustment amount of the virtual resistance based on the deviation between the operating stress index and the target stress through proportional-integral calculation and limiting processing; and obtains the second adjustment amount of the virtual inductance based on the reactive power deviation through proportional-integral calculation and limiting processing. When the event response control channel detects that any of the power angle deviation, active power deviation, or terminal voltage deviation exceeds the set threshold, it determines it as a large disturbance event, triggers the pulse-type adjustment of the virtual resistance and virtual inductance, and decays exponentially after the event ends or before the event ends. The difference between the normalized absolute value of the power angle deviation and the expected normalized power angle deviation is calculated in the adaptive control channel for power angle deviation. After proportional-integral operation and limiting, the fourth adjustment amount of virtual resistance and virtual inductance is obtained. The virtual resistance adjustment amount is positively correlated with the difference, and the virtual inductance adjustment amount is negatively correlated with the difference.

6. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: Step 5, the amplitude limiting and anti-saturation treatment, includes the following steps: Step 5.1: Dynamically constrain the single-step change range of the adjustment amount; Step 5.2: Apply asymmetric restrictions to the rate of increase and rate of decrease of the adjustment quantity; Step 5.3: Physically limit the final output value of the adjustment amount; Step 5.4: When the target value of the adjustment amount exceeds the physical range, reduce the adjustment amount proportionally.

7. The power decoupling method based on port Hamiltonian theory and using virtual impedance as described in claim 1, characterized in that: The dynamic decoupling control of active power and reactive power in step 6 includes the following steps: Step 6.1: Apply the virtual resistance command value and virtual inductance command value generated in Step 5 to the virtual impedance control loop of the virtual synchronous generator, adjust the amplitude and phase of the output reference voltage of the virtual synchronous generator, and realize the dynamic decoupling control of active power and reactive power. Step 6.2: Calculate the energy coupling coefficient of the system online in real time, as an evaluation index of the decoupling effect; Step 6.3: Evaluate the decoupling effect based on the system's energy coupling coefficient.

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