Control method of energy storage converter based on virtual asynchronous machine

Abstract

The invention discloses a control method of an energy storage converter based on a virtual asynchronous machine. Comprising the following steps: constructing a virtual asynchronous machine mathematical model framework according to a stator voltage equation, a rotor voltage equation, a flux linkage equation, a torque equation and a motion equation; collecting data, collecting a three-phase voltage instantaneous value of a power grid in real time as stator voltage input data, and receiving a load torque instruction; calculating a stator current vector, wherein the stator current vector is obtained by using the constructed model and the collected data; the working state of the converter is controlled, and the stator current vector serves as an output current instruction to control the electric and regenerative braking state. The established model provides a theoretical basis for control, acquires data to obtain key information matching requirements, provides an accurate instruction basis for calculating a stator current vector, controls the working state of the converter to be flexibly switched, improves the adaptability, energy interaction efficiency and stability of the energy storage converter, and guarantees the stable operation of a power system.

Description

Technical Field

[0001] The present invention relates to the field of energy storage converter control applications, and in particular to a control method for an energy storage converter based on a virtual asynchronous machine. Background Art

[0002] With the increasing development of energy storage technology, energy storage devices have been widely used. As an important link between the energy storage unit and the power grid interface, the energy storage converter plays an important role in maintaining system stability and power balance. The control methods of traditional energy storage converters pose challenges to the safe and stable operation of the power system. Therefore, it is proposed to simulate the mechanical inertia of the motor with the energy storage converter of the energy storage device, and equivalent the grid-connected energy storage converter to a motor system connected to the power grid for operation.

[0003] A common energy storage converter control method is an energy storage converter based on the idea of a virtual synchronous generator. By simulating the electrical and mechanical characteristics of a synchronous generator, the energy storage converter is regarded as a virtual synchronous generator set. However, the above method requires a pre-synchronization unit to pull the virtual synchronous machine into synchronization with the power grid, and there is a problem of judging the accuracy of the closing signal. The virtual synchronous machine needs to simulate its speed governor and voltage regulator at the same time, and the system is very complex. At the same time, the virtual synchronous machine also has the risk of losing synchronization during the control operation, resulting in control failure and shutdown, which cannot meet the working requirements of the energy storage converter control application. Therefore, a control method for an energy storage converter based on a virtual asynchronous machine is proposed. Summary of the Invention

[0004] The present invention provides the following technical solutions: A control method for an energy storage converter based on a virtual asynchronous machine, comprising the following steps: S1 Construct a mathematical model framework of the virtual asynchronous machine: First, establish a mathematical model of the virtual asynchronous machine according to the stator voltage equation, rotor voltage equation, flux linkage equation, torque equation and motion equation; S2 Collect data: Real-time collect the instantaneous values of the three-phase grid voltage as the stator voltage input data, and receive the load torque command; S3 Calculate the stator current vector: According to the mathematical model constructed in step S1 and the input data in step S2, calculate the stator current vector of the virtual asynchronous machine; S4 Control the working state of the converter: Use the stator current vector calculated in step S3 as the output current command of the energy storage converter, and then control the electric state and regenerative braking state of the converter according to the current command.

[0005] Preferably, the stator voltage equation in step S1 is: In the above formula, us is the stator voltage vector, is is the stator current vector, ψs is the stator flux linkage vector, ωs is the synchronous electrical angular velocity, and Rs is the stator resistance.

[0006] Preferably, the rotor voltage equation in step S1 is: In the above formula, Rr is the rotor resistance, ir is the rotor current vector, ψr is the rotor flux linkage vector, and ωr is the rotor electrical angular velocity.

[0007] Preferably, the flux linkage equation in step S1 is: In the above formula, Ls is the stator inductance, Lr is the rotor inductance, and Lm is the mutual inductance.

[0008] Preferably, the torque equation in step S1 is: In the above formula, p is the number of pole pairs, × represents vector cross product, and Te is the electromagnetic torque vector.

[0009] Preferably, the motion equation in step S1 is: In the above formula, J is the moment of inertia, TL is the load torque vector, and B is the friction coefficient.

[0010] Preferably, in step S4, after the virtual asynchronous machine is connected to the power grid, the rotation direction of the three-phase fundamental synthetic magnetic field and the synchronous angular velocity ωs also follow the phase sequence and the determined frequency of the power grid connected. At the same time, the inherent mechanical characteristics of the speed and torque of the virtual asynchronous machine are also determined. Finally, by changing the magnitude of the mechanical load torque TL and its direction relative to Te, the rotor speed can be changed, thereby determining the system operating point. At the same time, for the energy storage converter TL, the command is given by the pre-stage controller and sent through the central dispatching unit.

[0011] Preferably, the setting method of the synchronous angular velocity ωs is as follows: First, set the direction of ωs as positive. When Tmax+ ≥ TL > -To, where To is the no-load torque and Tmax+ is the positive maximum allowable torque, the virtual asynchronous machine absorbs active power from the power grid to overcome the load torque and does work. The virtual asynchronous machine operates in the motor state, ωr is in the same direction as ωs and ωr < ωs. At this time, the energy storage converter is in the charging state; Secondly, set the direction of ωs as positive. When TL = -To, where To is the no-load torque, the virtual asynchronous machine operates in synchronization with the power grid, ωr is in the same direction as ωs and ωr = ωs. At this time, the energy storage converter is in the no-load state; Finally, set the direction of ωs as the positive direction. When -Tmax- ≤ TL < -To (To is the no-load torque and Tmax- is the maximum allowable negative torque), the virtual asynchronous machine operates in the regenerative braking state, ωr is in the same direction as ωs and ωr > ωs. At this time, the energy storage converter is in the discharging state.

[0012] Preferably, in step S3, an iterative calculation method is used for calculation. After the initial calculation based on the mathematical model in step S1 and the input data in step S2, the calculation result is substituted into the mathematical model for reverse verification.

[0013] Preferably, in step S4, when using the stator current vector as the output current command of the energy storage converter to control the working state of the converter, a real-time fault diagnosis mechanism is established synchronously, and fault tolerance measures are preset in advance.

[0014] In summary, compared with the prior art, the present invention provides a control method for an energy storage converter based on a virtual asynchronous machine, having the following beneficial effects: The present invention constructs a mathematical model framework of a virtual asynchronous machine and establishes a model based on multiple equations, providing a solid theoretical basis for the entire control process and helping to accurately grasp the operating characteristics of the virtual asynchronous machine. Secondly, in the data acquisition step, the instantaneous values of the three-phase grid voltages and the load torque command are collected in real time, enabling timely acquisition of the key information of the system operation and ensuring that the control process matches the actual grid and load requirements. Then, through the step of calculating the stator current vector, combined with the previously constructed model and the collected data, the stator current vector can be accurately obtained, providing an accurate instruction basis for controlling the working state of the converter. Finally, using the stator current vector to control the working state of the converter can effectively achieve flexible control of the energy storage converter between the motoring state and the regenerative braking state, which helps to improve the adaptability of the energy storage converter under different working requirements, enhance the energy interaction efficiency and stability between the energy storage system and the grid, and ensure the stable operation of the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flowchart of the control method for the energy storage converter based on the virtual asynchronous machine of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0017] Embodiment 1: Please refer toFigure 1 The present invention provides a technical solution, a control method of an energy storage converter based on a virtual asynchronous machine, comprising the following steps: S1 builds the mathematical model framework of the virtual asynchronous machine: Firstly, the mathematical model of virtual asynchronous machine is established according to the stator voltage equation, rotor voltage equation, flux equation, torque equation and motion equation; The stator voltage equation is: In the above formula, us is the stator voltage vector, is is the stator current vector, ψs is the stator flux vector, ωs is the synchronous electrical angular velocity, and Rs is the stator resistance; The rotor voltage equation is: In the above formula, Rr is the rotor resistance, ir is the rotor current vector, ψr is the rotor flux vector, and ωr is the rotor electrical angular velocity; The magnetic flux equation is: In the above formula, Ls is the stator inductance, Lr is the rotor inductance, and Lm is the mutual inductance; The torque equation is: In the above formula, p is the number of pole pairs, × represents vector cross product, and Te is the electromagnetic torque vector; The equation of motion is: In the above formula, J is the moment of inertia, TL is the load torque vector, and B is the friction coefficient; When constructing the mathematical model of a virtual asynchronous machine: First, the various parameters in the stator voltage equation are clearly defined. Then, the initial values ​​of these parameters are obtained according to the design specifications, equipment parameters or measurement results of the actual system. The determined parameters are mathematically related according to the above stator voltage equation. Secondly, the parameters in the rotor voltage equation are determined, and the equation relationship is constructed according to the rotor voltage equation; The stator voltage equation, rotor voltage equation, flux equation, torque equation and motion equation are combined. These equations are interrelated and together describe the electrical, magnetic and mechanical motion characteristics of the virtual asynchronous machine. By combining the equations, a complete mathematical model of the virtual asynchronous machine is constructed. This model can be used for subsequent calculations and analysis, for example, it plays a key role in calculating the stator current vector and controlling the working state of the energy storage converter. S2 collects data: The instantaneous value of the three-phase voltage of the power grid is collected in real time as the stator voltage input data, and the load torque instruction is received. The specific process of the above method is as follows: Instantaneous value acquisition of three-phase grid voltage: Select a suitable voltage sensor according to the characteristics of the grid voltage level, frequency, etc. For example, for common medium and low voltage grids, a voltage transformer (PT) or a Hall voltage sensor can be selected. Install the voltage sensor near the connection point between the grid and the energy storage converter to ensure accurate measurement of the three-phase grid voltage. The installation of the sensor should follow electrical safety specifications to ensure good electrical connection and insulation performance. Connect the voltage sensor to the data acquisition device. The data acquisition device can be a dedicated power data acquisition card or a microcontroller with data acquisition functions. Set the data acquisition device to determine parameters such as the acquisition frequency and accuracy. Since real-time acquisition is required, the acquisition frequency should be high enough. For example, it can be set to acquire data once every millisecond to ensure that the instantaneous changes in voltage can be captured. At the same time, set the acquisition accuracy according to actual requirements. Generally, it can be set to the minimum resolution that meets the system control requirements, such as 0.1V. Start the data acquisition system to start real-time acquisition of the three-phase grid voltage signal. The acquired voltage signal is usually an analog signal and needs to be converted into a digital signal by the analog-to-digital conversion (ADC) module in the data acquisition device for subsequent processing. Perform preliminary processing on the acquired three-phase voltage digital signal, such as removing noise interference. Digital filtering techniques such as mean filtering or low-pass filtering can be used to smooth the data and reduce the impact of high-frequency interference that may exist in the grid on the data. Verify the rationality of the acquired data. Check whether the acquired voltage value is within the voltage range of normal grid operation. If it exceeds the preset normal range, for example, the three-phase voltage unbalance degree exceeds the specified threshold (such as 2%) or the voltage amplitude exceeds ±10% of the rated voltage, mark the data as abnormal data and take corresponding measures, such as re-acquisition or sending an alarm signal. Use the processed and verified three-phase voltage data as the stator voltage input data for subsequent calculation and control operations; Receiving the load torque command: Determine the communication method with the device that provides the load torque command (such as the pre-stage controller or the central dispatching unit). Wired communication methods such as industrial Ethernet, RS-485, etc., or wireless communication methods such as ZigBee, Wi-Fi, etc. can be used and selected according to the requirements of the actual application scenario. Establish the corresponding communication interface on the control device of the energy storage converter and configure communication parameters such as baud rate, data bits, stop bits, etc. to ensure communication matching with the command source device. Receive the load torque command from the external device in real time through the established communication interface. Verify the received load torque command. Methods such as checksum and cyclic redundancy check (CRC) can be used to check whether an error occurs during the transmission of the command. If the verification fails, request the command to be resent. Store the verified load torque command in the local cache for subsequent use in operations such as calculating the stator current vector; S3 Calculate the stator current vector: Calculate the stator current vector of the virtual asynchronous machine based on the mathematical model constructed in step S1 and the input data in step S2. When performing the calculation, an iterative calculation method is adopted. After the initial calculation based on the mathematical model in step S1 and the input data in step S2, substitute the calculation result into the mathematical model for reverse verification; The specific process of the iterative calculation is as follows: First, compare the parameter values obtained from the above initial calculation with the expected values or physical constraint conditions of the actual system. For example, check whether the calculated ωr is within the speed range of normal operation of the virtual asynchronous machine. If it exceeds the range or the relationship with other physical quantities does not meet the expectations (such as the power calculated according to the electromagnetic relationship does not match the power of the power grid actually collected), it indicates that there is a deviation in the initial calculation; According to the situation of the calculation deviation, adjust the assumed value of the stator current vector is. For example, if the calculated ωr is too large, appropriately reduce the assumed value of is; if ωr is too small, appropriately increase the assumed value of is; Take the adjusted stator current vector value as the new assumed value and substitute it into each equation in the mathematical model again, repeating the above calculation process, including recalculating parameters such as ψs, ir, Te, ωr, etc.; Continue the iterative calculation until the parameter values obtained from the calculation meet certain convergence conditions. The convergence conditions can be that the error between the parameter values obtained from the calculation and the expected values of the actual system is less than a pre-set threshold. For example, for the rotational speed ωr, the error between its calculated value and the expected value is less than 1% of the rated speed; for the electromagnetic torque Te, the error between its calculated value and the expected value is less than 5% of the rated torque, etc.; Regarding the reverse verification: After the iterative calculation converges, substitute the finally calculated stator current vector is and other related parameters (such as ψs, ir, Te, ωr, etc.) into each equation in the mathematical model. For example, substitute is into the stator voltage equation to calculate the corresponding us′; substitute is and ir into the flux linkage equation and then into the torque equation to calculate Te′, etc.; Compare the results obtained from the reverse verification calculation (such as us′, ψs′, Te′, etc.) with the data collected in step S2 and the initial assumptions. For example, compare us′ with us obtained by converting the instantaneous values of the three-phase grid voltages collected in step S2. If the error between the two is within an acceptable range (such as the error is less than 5%), it indicates that the calculated stator current vector is is valid; if the error exceeds the acceptable range, it is necessary to recheck the mathematical model, the collected data or the iterative calculation process, and it may be necessary to adjust the convergence conditions or perform the calculation again; S4 Control the working state of the converter: Use the stator current vector calculated in step S3 as the output current command of the energy storage converter, and then control the motor state and regenerative braking state of the converter according to the current command. After the virtual induction machine is connected to the grid, the rotation direction of the three-phase fundamental synthetic magnetic field and the synchronous angular velocity ωs are also connected to the phase sequence and the determined frequency of the grid. At the same time, the inherent mechanical characteristics of the speed and torque of the virtual induction machine are also determined. Finally, by changing the magnitude of the mechanical load torque TL and its direction relative to Te, the rotor speed can be changed, thereby determining the operating point of the system. At the same time, for the energy storage converter TL, the command is given by the pre-stage controller and sent down through the central dispatching unit; The setting method of the synchronous angular velocity ωs is as follows: First, set the direction of ωs to be positive. When Tmax+≥TL>-To, where To is the no-load torque and Tmax+ is the maximum allowable positive torque, the virtual induction machine absorbs active power from the grid to overcome the load torque and do work. The virtual induction machine operates in the motor state, ωr is in the same direction as ωs and ωr<ωs. At this time, the energy storage converter is in the charging state; Secondly, set the direction of ωs to be positive. When TL=-To, where To is the no-load torque, the virtual induction machine operates in synchronization with the grid, ωr is in the same direction as ωs and ωr = ωs. At this time, the energy storage converter is in the no-load state; Finally, set the direction of ωs to be positive. When -Tmax-≤TL<-To, where To is the no-load torque and Tmax- is the maximum allowable negative torque, the virtual induction machine operates in the regenerative braking state, ωr is in the same direction as ωs and ωr>ωs. At this time, the energy storage converter is in the discharging state; Embodiment 2: On the basis of Embodiment 1, when using the stator current vector as the output current command of the energy storage converter to control the working state of the converter, a real-time fault diagnosis mechanism is established synchronously, and fault tolerance measures are preset; Regarding the establishment of the real-time fault diagnosis mechanism: Monitoring the stator current vector \(i_s\): Real-time measurement of parameters such as the amplitude and phase of the stator current vector. The current signal is obtained through a current sensor installed at the output of the energy storage converter, converted into a digital signal and then analyzed. Monitoring the stator voltage vector \(u_s\): Similarly, the amplitude, frequency and phase information of the stator voltage vector are obtained in real time using a voltage sensor. This is very important for judging the connection status between the converter and the power grid and the power transmission situation. Monitoring the load torque \(T_L\): According to the instructions given by the pre-stage controller and sent by the central dispatching unit, as well as the changes in electrical parameters monitored in real time, the load torque is monitored and evaluated; The above parameters are monitored using a trend analysis algorithm. For example, the amplitude of the stator current vector \(i_s\) is continuously sampled, and its change trend over time is observed. If the current amplitude shows a continuous upward or downward trend and exceeds a certain slope threshold (such as \(k_{max}\)), it may indicate that the system is about to fail, such as a short circuit or overload trend in the circuit. Trend analysis is also performed on the frequency of the stator voltage vector \(u_s\). If the frequency fluctuates significantly within a short period of time and the fluctuation frequency exceeds a certain threshold (such as the number of fluctuations per minute exceeds \(n_{max}\)), it indicates that there are unstable factors in the power grid or the converter itself; Fault alarm and recording: When the fault diagnosis algorithm determines that a fault has occurred, the alarm mechanism is immediately triggered. The alarm method can be to emit an audible and visual alarm signal. For example, a fault indicator light is lit on the control panel of the energy storage converter, and a buzzer sound is emitted. At the same time, the fault information is sent to the remote monitoring center through the communication interface so that the operation and maintenance personnel can obtain the fault information in a timely manner. Record the time when the fault occurred, the type of fault (such as current overload, voltage abnormality, power factor abnormality, etc.), and the relevant parameter values at the time of the fault (such as the values of the stator current vector, stator voltage vector, power factor, etc. at the moment of the fault). These records will be stored in the local fault log database for subsequent fault analysis and troubleshooting; Pre-setting of fault tolerance measures: In the design of the energy storage converter, redundant power modules are adopted. For example, multiple power modules are set to work in parallel. Under normal circumstances, they share the load current together. When one of the power modules fails, the other normal power modules can continue to work and bear more load current to ensure that the basic functions of the energy storage converter are not affected. For key sensors, such as the stator current sensor and the stator voltage sensor, redundant designs are adopted. Multiple sensors are installed to measure the same parameter at the same time, and data fusion technology or majority voting mechanism is used to improve the reliability of the measurement. For example, when a current sensor fails and causes abnormal measurement data, the data of other normal current sensors can continue to be used for control and fault diagnosis; Software fault tolerance strategy: When certain faults are detected, adjust the control algorithm to adapt to the fault state. For example, when the magnitude of the stator current vector slightly exceeds the normal range but does not reach the severe fault level, the current loop parameters in the control algorithm, such as the proportional coefficient Kp and the integral coefficient Ki, can be adjusted to try to restore the current to the normal range. If the power factor is abnormal, the reactive power compensation strategy can be adjusted, such as adjusting the output of the reactive power generator inside the converter, to improve the power factor. When it is determined that a certain component (such as a power module or a sensor) fails, perform a fault isolation operation. For example, isolate the faulty power module from the circuit through a relay or other switching elements to prevent the fault from spreading further. After the fault isolation, perform system reconstruction according to the remaining available resources of the system. For example, if a power module is isolated, reallocate the working modes and load sharing ratios of other normal power modules to ensure that the energy storage converter can continue to operate stably in the derated mode.

[0018] This solution provides a solid theoretical basis for the entire control process by constructing the mathematical model framework of the virtual asynchronous machine and establishing the model based on multiple equations, which helps to accurately grasp the operating characteristics of the virtual asynchronous machine. Secondly, in the data acquisition step, the instantaneous values of the three-phase grid voltages and the load torque command are acquired in real time, which can timely obtain the key information of the system operation and ensure that the control process matches the actual grid and load requirements. Then, through the step of calculating the stator current vector, combined with the model constructed previously and the acquired data, the stator current vector can be accurately obtained, providing an accurate instruction basis for controlling the working state of the converter. Finally, using the stator current vector to control the working state of the converter can effectively achieve flexible control of the energy storage converter between the motoring state and the regenerative braking state, which helps to improve the adaptability of the energy storage converter under different working requirements, enhance the energy interaction efficiency and stability between the energy storage system and the grid, and ensure the stable operation of the entire power system.

[0019] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0020] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control method for an energy storage converter based on a virtual asynchronous machine, characterized in that, It includes the following steps: S1 Construct the mathematical model framework of the virtual asynchronous machine: First, establish the mathematical model of the virtual asynchronous machine based on the stator voltage equation, rotor voltage equation, flux linkage equation, torque equation, and motion equation; S3 Collect data: Collect the instantaneous values of the three-phase grid voltage in real time as the stator voltage input data, and receive the load torque command; S3 Calculate the stator current vector: According to the mathematical model constructed in step S1 and the input data in step S2, calculate the stator current vector of the virtual asynchronous machine; S4 Control the working state of the converter: Take the stator current vector calculated in step S3 as the output current command of the energy storage converter, and then control the motor state and feedback braking state of the converter according to the current command.

2. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, wherein: The stator voltage equation in step S1 is: In the above formula, us is the stator voltage vector, is is the stator current vector, ψs is the stator flux linkage vector, ωs is the synchronous electrical angular velocity, and Rs is the stator resistance.

3. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, characterized in that: The rotor voltage equation in step S1 is: In the above formula, Rr is the rotor resistance, ir is the rotor current vector, ψr is the rotor flux linkage vector, and ωr is the rotor electrical angular velocity.

4. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, wherein: The flux linkage equation in step S1 is: In the above formula, Ls is the stator inductance, Lr is the rotor inductance, and Lm is the mutual inductance.

5. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, wherein: The torque equation in step S1 is: In the above formula, p is the number of pole pairs, × represents vector cross product, and Te is the electromagnetic torque vector.

6. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, characterized in that: The motion equation in step S1 is: In the above formula, J is the moment of inertia, TL is the load torque vector, and B is the friction coefficient.

7. A control method for an energy storage converter based on a virtual asynchronous machine according to claim 1, characterized in that: In step S4, when the virtual asynchronous machine is connected to the grid, the rotation direction of the three-phase fundamental synthesized magnetic field and the synchronous angular velocity ωs also follow the phase sequence and determined frequency of the grid connected. At the same time, the inherent mechanical characteristics of the speed and torque of the virtual asynchronous machine are also determined. Finally, by changing the magnitude of the mechanical load torque TL and its direction relative to Te, the rotor speed can be changed, thereby determining the system operating point. At the same time, for the energy storage converter TL, it is given by the pre-stage controller and sent an instruction via the central dispatching unit.

8. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 7, characterized in that: The setting method of the synchronous angular velocity ωs is: First, set the direction of ωs as positive. When Tmax+ ≥ TL > -To, To is the no-load torque, and Tmax+ is the maximum allowable positive torque. The virtual asynchronous machine absorbs active power from the grid to overcome the load torque and do work. The virtual asynchronous machine operates in the motor state, ωr is in the same direction as ωs and ωr < ωs. At this time, the energy storage converter is in the charging state; Secondly, set the direction of ωs as positive. When TL = -To, To is the no-load torque, the virtual asynchronous machine operates in synchronization with the grid, ωr is in the same direction as ωs and ωr = ωs. At this time, the energy storage converter is in the no-load state; Finally, set the direction of ωs as positive. When -Tmax- ≤ TL < -To, To is the no-load torque, and Tmax- is the maximum allowable negative torque. The virtual asynchronous machine operates in the feedback braking state, ωr is in the same direction as ωs and ωr > ωs. At this time, the energy storage converter is in the discharging state.

9. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, characterized in that: In the step S3, an iterative calculation method is adopted during the calculation. After the initial calculation is performed based on the mathematical model in step S1 and the input data in step S2, the calculation result is substituted into the mathematical model for reverse verification.

10. The control method of an energy storage converter based on a virtual asynchronous machine according to claim 1, wherein: In the step S4, when the stator current vector is used as the output current command of the energy storage converter to control the working state of the converter, a real-time fault diagnosis mechanism is synchronously established, and fault tolerance measures are preset.

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