Frequency control method for low-inertia micro-grid system under channel attenuation

Abstract

The invention provides a frequency control method for a low-inertia micro-grid system under channel attenuation and a medium, and relates to the field of micro-grids, and the method comprises the steps: constructing a micro-grid frequency control system in which a virtual generator participates in frequency modulation under the influence of channel attenuation; designing an output feedback controller; under the condition of realizing the stability of the micro-grid frequency control system and # imgabs0 # performance, solving a gain solving result of an output feedback controller; and substituting the gain solving result of the output feedback controller into the micro-grid frequency control system in which the virtual generator participates in frequency modulation, thereby realizing frequency control of the micro-grid frequency control system under the condition of channel attenuation caused by time delay, packet loss and noise. According to the technical scheme, normal operation of the low-inertia micro-grid frequency control system under the influence of random disturbance and channel attenuation is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of microgrids, and in particular to a frequency control method and medium for a low-inertia microgrid system under channel attenuation. Background Art

[0002] Microgrids are interconnected regional distributed loads and low-voltage distributed energy sources. To ensure that the frequency of the microgrid system remains at a predetermined value, frequency control is required to maintain a balance between power generation and consumption. Secondary frequency control achieves this balance through the microgrid central controller. However, in practical applications, measurement signals are often interfered by time delays, packet loss, and various noises during transmission. These interference factors work together to cause the signal to experience channel attenuation during transmission, thereby affecting the integrity and reliability of the signal. Therefore, it is common for the signal received by the microgrid central controller to experience channel attenuation after transmission.

[0003] As the complexity and intelligence level of microgrids continue to increase, the massive amount of communication data increases the communication burden they face. These problems seriously affect the stability of the frequency of microgrid systems. In addition, with the increase in the penetration level of distributed power sources and renewable energy, the inertia and damping of microgrid systems gradually decrease. Microgrid systems are therefore more sensitive to frequency fluctuations caused by load disturbances and channel attenuation. Control strategies and communication networks are important factors affecting the control performance of microgrid frequency control systems.

[0004] Scholars have conducted a lot of research to ensure the stable operation of microgrids, such as references [1] and [2]. In reference [3], a and The synthetic robust control technology is used to control the secondary frequency of the microgrid. This control strategy is proposed based on ideal communication conditions. In actual engineering, open communication networks may cause time-varying delays in control signals. Taking this into account, reference [4] proposed a scheme in which electric vehicles are used as energy storage systems to participate in microgrid frequency control while considering the influence of time delay. Reference [5] further considered the impact of random time-delay network attacks on system stability and designed an adaptive finite-time tracking end sliding mode controller to achieve better control results.

[0005] These studies have made the frequency of the microgrid system more stable and ensured the safe operation of the microgrid. However, their studies have not fully considered the impact of the communication network on frequency control. In fact, it is limited to consider the impact of the control signal in the open communication network only as time delay. Network-induced factors such as time delay, packet loss and noise have a negative impact on the transmission of control signals. The channel attenuation caused by them seriously affects the effect of microgrid frequency control. These problems need to be solved urgently.

[0006] Reference [1]: Fathi A, Shafiee Q, Bevrani H. Robust frequency control of microgrids using an extended virtual synchronous generator[J]. IEEE Transactions on Power Systems, 2018, 33(6): 6289-6297. Reference [2]: Rafiee A, Batmani Y, Ahmadi F, et al. Robust load-frequency control in islanded microgrids: Virtual synchronous generator concept and quantitative feedback theory[J]. IEEE Transactions on Power Systems, 2021, 36(6): 5408-5416. Reference [3]: Bevrani H, Feizi M R, Ataee S. Robust frequency control in an islanded microgrid: and -synthesis approaches[J]. IEEE Transactions on Smart Grid, 2016, 7(2): 706-717. Reference [4]: Khooban M H. Secondary load frequency control of time-delay stand-alone microgrids with electric vehicles[J]. IEEE Transactions on Industrial Electronics, 2018, 65(9): 7416-7422. Literature [5]: Rouhani SH, Abbaszadeh E, Sepestanaki MA, et al. Adaptivefinite-time tracking control of fractional microgrids against time-delayattacks[J]. IEEE Transactions on Industry Applications, 2024, 60(2): 2153-2164. Summary of the invention

[0007] The purpose of the present invention is to provide a frequency control method and medium for a low-inertia microgrid system under channel attenuation in order to solve the problem that the existing microgrid control method does not consider the influence of network induced factors such as time delay, packet loss and noise on the control signal.

[0008] The above-mentioned purpose of the present application is achieved through the following technical solutions: S1: Construct a microgrid frequency control system with virtual generators participating in frequency regulation under the influence of channel attenuation; S2: Design output feedback controller; in order to achieve the stability and Under the condition of performance, solve the gain solution of the output feedback controller; S3: Substitute the gain solution of the output feedback controller into the microgrid frequency control system in which the virtual generator participates in frequency modulation, so as to realize the frequency control of the microgrid frequency control system under the conditions of channel attenuation caused by time delay, packet loss and noise.

[0009] Optionally, step S1 includes: Photovoltaic power generation , Wind power generation and the disturbance caused by the load Set to the external disturbance of the microgrid frequency control system , ; A diesel generator set, a battery energy storage system, a flywheel energy storage system and a fuel cell system are set to participate in the primary frequency modulation process of the microgrid frequency control system; set up , and Represent the time constants of the battery energy storage system, flywheel energy storage system and fuel cell system respectively; , , , , and They represent the generator moment of inertia, diesel generator damping coefficient, steam turbine time constant, governor time constant, fuel cell gain and droop characteristics respectively; , as well as Represent the output power changes of the battery energy storage system, flywheel energy storage system and fuel cell system respectively.

[0010] Optionally, step S1 further includes: The secondary control loop of the microgrid uses the PI controller as the microgrid central controller for frequency regulation; The frequency deviation of the secondary control loop of the microgrid frequency control system is used as the feedback signal. The frequency deviation is added to the primary frequency modulation loop through the microgrid central controller. The control input of the secondary control loop is recorded as .

[0011] Optionally, step S1 further includes: The relationship between the frequency deviation, active power generated and load of the microgrid frequency control system is expressed by the swing equation as follows:

[0012] in, Indicates the change in mechanical power of the generator; Indicates the load power change; represents a complex variable; Indicates the frequency deviation of the system.

[0013] Optionally, step S1 further includes: By constructing a virtual synchronous generator that acts like a synchronous motor, inertial support is provided for the microgrid frequency control system. The control input of the virtual synchronous generator is recorded as ; Determine the power reference of the inverter of the microgrid frequency control system based on the swing equation , expressed as:

[0014] in and The virtual moment of inertia and virtual damping coefficient provided by the virtual generator are considered; Indicates system frequency deviation; The Rice attenuation model is used to represent the channel attenuation phenomenon caused by time delay, packet loss and noise, as follows:

[0015] in, and are respectively a given positive scalar and a real constant matrix of preset dimension; is the receive signal available to the controller; is an independent and identically distributed Gaussian random variable, representing the channel coefficient, whose mean and variance are and ; Indicates interference input; Indicates the partial state of the signal during the attenuation process; Indicates the impact on the signal at the sampling time during the attenuation process; In the Rice attenuation model, the measured signal is considered to be transmitted to the receiving end through different paths, and the intensity of interference on each path is determined by independent coefficients to characterize; Select state variables , external disturbance , control input , measurement output , the controlled output , the state space expression of the microgrid frequency control system with the participation of virtual synchronous generators is as follows:

[0016] in , , , , , , ; represents the time constant of the energy storage system; represents the gain of the virtual droop characteristic; According to the sampling interval of microgrid frequency control in actual projects , discretize equation (3) and rewrite it into the following linear discrete-time system:

[0017] The sampling time of the sensor is expressed as , , , , ; Consider the static event-triggered communication mechanism to determine whether the output signal of the PI controller needs to be transmitted to the actuator; define the event generation function as follows:

[0018] in, is a given positive scalar; set up is the moment of the most recent control signal, and has , when the condition is met , a static event is triggered, and has:

[0019] in, is a sequence of event triggers; Considering the influence of channel attenuation in equation (2), the output feedback control law based on the PI controller is expressed as:

[0020] in, is a scalar quantity representing the length of time; and is the controller gain to be designed; The process of virtual inertia control is described as:

[0021] in, is the controller gain to be designed; Written

[0022] in

[0023] Combining equations (5)-(8), the frequency control system (4) of the microgrid with virtual generators participating in frequency regulation is written as:

[0024] in , , , , , , , represents the Q-dimensional unit matrix; , , , , , , , , represents the identity matrix of appropriate dimension; , , , .

[0025] Optionally, step S2 includes: Design an output feedback controller to ensure that the microgrid frequency control system (9) is exponentially mean square stable and at a given disturbance rejection level Under this condition, the microgrid frequency control system meets Performance constraints:

[0026] The gain of the output feedback controller is , ,and , given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; There exists a positive definite matrix and , so that the linear matrix inequality (11) holds true, then the microgrid frequency control system (9) is exponential mean square stable, and the linear matrix inequality is as follows:

[0027] in , , , , , , , , , , , , , , , .

[0028] Optionally, step S2 further includes: Solve the linear matrix inequality for the controller gains as follows: For a given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; If there is a matrix , , and , and the positive definite matrix and , so that the linear matrix inequality (11) holds, then the microgrid frequency control system (9) is exponentially mean square stable and satisfies under zero initial conditions The performance constraints, linear matrix inequalities, are as follows: (11) in, , is a scalar, and , , , , , , , , , , , , , , , , .

[0029] Optionally, step S2 further includes: By solving the linear matrix inequality (11), the controller gain solution results of the quadratic frequency control and the virtual quadratic frequency control, that is, the gain solution results of the output feedback controller, are obtained as follows: .

[0030] A computer-readable storage medium stores instructions. When the instructions are executed, a frequency control method for a low-inertia microgrid system under channel attenuation is performed.

[0031] The beneficial effects of the technical solution provided by this application are: 1. This invention proposes a method of coordinating secondary frequency control and virtual inertia control for the microgrid frequency control system under channel attenuation. Robust control method. Firstly, a frequency control system model of a microgrid is established with virtual synchronous generators participating in frequency regulation under the influence of channel attenuation. Secondly, the Lyapunov theory is used to analyze the constructed model. Performance analysis; then, the linear matrix inequality for solving the collaborative controller gain is obtained through matrix transformation; finally, the effectiveness of the proposed control strategy is verified through simulation. The new method proposed in this patent can help the microgrid frequency control system better cope with the problems caused by channel attenuation, disturbance and inertia reduction, and ensure the stable operation of the microgrid.

[0032] 2. Considering the channel attenuation caused by time delay, packet loss and noise, a microgrid frequency control model under the influence of channel attenuation was established.

[0033] 3. The appropriate event trigger mechanism is applied to effectively alleviate the time lag problem caused by control signal redundancy due to periodic signal update in microgrid frequency control.

[0034] 4. A robust control strategy of coordinated control of secondary frequency control and virtual inertia control is designed, which provides virtual inertia support without increasing dependence on virtual inertia sources and significantly improves the control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present application will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 is a microgrid frequency control model diagram in an embodiment of the present application; Figure 2 is a random disturbance diagram caused by renewable energy and load in an embodiment of the present application; Figure 3 It is a simulation result diagram in the embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to have a clearer understanding of the technical features, purposes and effects of the present application, the specific implementation methods of the present application are now described in detail with reference to the accompanying drawings.

[0037] An embodiment of the present application provides a frequency control method for a low-inertia microgrid system under channel attenuation.

[0038] Please refer to Figure 1 , Figure 1 It is a microgrid frequency control model diagram of a frequency control method for a low inertia microgrid system under channel attenuation in an embodiment of the present application, including: S1: Construct a microgrid frequency control system with virtual generators participating in frequency regulation under the influence of channel attenuation; S2: Design output feedback controller; in order to achieve the stability and Under the condition of performance, solve the gain solution of the output feedback controller; S3: Substitute the gain solution of the output feedback controller into the microgrid frequency control system in which the virtual generator participates in frequency modulation, so as to realize the frequency control of the microgrid frequency control system under the conditions of channel attenuation caused by time delay, packet loss and noise.

[0039] Step S1 includes: Photovoltaic power generation , Wind power generation and the disturbance caused by the load Set to the external disturbance of the microgrid frequency control system , ; A diesel generator set, a battery energy storage system, a flywheel energy storage system and a fuel cell system are set to participate in the primary frequency modulation process of the microgrid frequency control system; set up , and Represent the time constants of the battery energy storage system, flywheel energy storage system and fuel cell system respectively; , , , , and They represent the generator moment of inertia, diesel generator damping coefficient, steam turbine time constant, governor time constant, fuel cell gain and droop characteristics respectively; , as well as Represent the output power changes of the battery energy storage system, flywheel energy storage system and fuel cell system respectively.

[0040] As an embodiment, a diesel generator set, a battery energy storage system, a flywheel energy storage system and a fuel cell system participate in the primary frequency regulation process of the microgrid. They are not affected by time lag and can quickly adjust smaller frequency errors.

[0041] As an embodiment, since the present application is aimed at the low-frequency behavior of distributed generators and the designed controller has strong robustness, these systems (battery energy storage system, flywheel energy storage system and fuel cell system) are modeled as first-order models.

[0042] Step S1 also includes: The secondary control loop of the microgrid uses the PI controller as the microgrid central controller for frequency regulation; The frequency deviation of the secondary control loop of the microgrid frequency control system is used as the feedback signal. The frequency deviation is added to the primary frequency modulation loop through the microgrid central controller. The control input of the secondary control loop is recorded as .

[0043] Step S1 also includes: The relationship between the frequency deviation, active power generated and load of the microgrid frequency control system is expressed by the swing equation as follows:

[0044] in, Indicates the change in mechanical power of the generator; Indicates the load power change; represents a complex variable; Indicates the frequency deviation of the system.

[0045] Step S1 also includes: By constructing a virtual synchronous generator that acts like a synchronous motor, inertial support is provided for the microgrid frequency control system. The control input of the virtual synchronous generator is recorded as ; Determine the power reference of the inverter of the microgrid frequency control system based on the swing equation , expressed as:

[0046] in and The virtual moment of inertia and virtual damping coefficient provided by the virtual generator are considered; Indicates the system frequency deviation; As an example, according to the swing equation in formula (1), the influence of frequency deviation needs to be compensated by the power of power supply compensation. It is expressed as: By simulating the frequency regulation process of the primary and secondary loops (primary and secondary control loops), the virtual synchronous generator is also modeled as a model including virtual primary control and virtual secondary control, such as Figure 1 As shown in Figure 2. Virtual secondary control takes into account the same time lag as the secondary frequency modulation process. and They represent the virtual droop characteristic and the gain of the virtual quadratic integrator respectively.

[0047] As an example, compared with a large power grid that uses a dedicated communication channel for point-to-point control, due to the introduction of a controller area network in a microgrid, data will inevitably be affected by channel attenuation caused by time delay, packet loss and noise during transmission.

[0048] The Rice attenuation model is used to represent the channel attenuation phenomenon caused by time delay, packet loss and noise, as follows:

[0049] in, and are respectively a given positive scalar and a real constant matrix of preset dimension; is the receive signal available to the controller; is an independent and identically distributed Gaussian random variable, representing the channel coefficient, whose mean and variance are and ; Indicates interference input; Indicates the partial state of the signal during the attenuation process; Indicates the impact on the signal at the sampling time during the attenuation process; In the Rice attenuation model, the measured signal is considered to be transmitted to the receiving end through different paths, and the intensity of interference on each path is determined by independent coefficients to characterize; Select state variables , external disturbance , control input , measurement output , the controlled output , the state space expression of the microgrid frequency control system with the participation of virtual synchronous generators is as follows:

[0050] in , , , , , , ; represents the time constant of the energy storage system; represents the gain of the virtual droop characteristic; According to the sampling interval of microgrid frequency control in actual projects , discretize equation (3) and rewrite it into the following linear discrete-time system:

[0051] The sampling time of the sensor is expressed as , , , , ; Consider the static event-triggered communication mechanism to determine whether the output signal of the PI controller needs to be transmitted to the actuator; define the event generation function as follows:

[0052] in, is a given positive scalar; set up is the moment of the most recent control signal, and has , when the condition is met , a static event is triggered, and has:

[0053] in, is a sequence of event triggers; Considering the influence of channel attenuation in equation (2), the output feedback control law based on the PI controller is expressed as:

[0054] in, is a scalar quantity representing the length of time; and is the controller gain to be designed; The process of virtual inertia control is described as:

[0055] in, is the controller gain to be designed; Written

[0056] in

[0057] Combining equations (5)-(8), the frequency control system (4) of the microgrid with virtual generators participating in frequency regulation is written as:

[0058] in , , , , , , , represents the Q-dimensional unit matrix; , , , , , , , , represents the identity matrix of appropriate dimension; , , , .

[0059] Step S2 includes: Design an output feedback controller to ensure that the microgrid frequency control system (9) is exponentially mean square stable and at a given disturbance rejection level Under this condition, the microgrid frequency control system meets Performance constraints:

[0060] The gain of the output feedback controller is , ,and , given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; There exists a positive definite matrix and , so that the linear matrix inequality (11) holds true, then the microgrid frequency control system (9) is exponential mean square stable, and the linear matrix inequality is as follows:

[0061] in , , , , , , , , , , , , , , , .

[0062] Step S2 also includes: Solve the linear matrix inequality for the controller gains as follows: For a given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; If there is a matrix , , and , and the positive definite matrix and , so that the linear matrix inequality (11) holds, then the microgrid frequency control system (9) is exponentially mean square stable and satisfies under zero initial conditions The performance constraints, linear matrix inequalities, are as follows: (11) in, , is a scalar, and , , , , , , , , , , , , , , , , .

[0063] Step S2 also includes: By solving the linear matrix inequality (11), the controller gain solution results of the quadratic frequency control and the virtual quadratic frequency control, that is, the gain solution results of the output feedback controller, are obtained as follows: .

[0064] In order to verify the effectiveness of the method proposed in the patent, a simulation verification is carried out here to illustrate. First, the system parameters required are given as shown in Table 1 in the appendix.

[0065] Table 1 System parameters

[0066] Given a discrete sampling period , interference suppression level and event trigger thresholds are 7 and 0.5 respectively. Consider the channel attenuation model (2) , , the mathematical expectation of the channel coefficient ,variance According to the method of solving the controller gain in method 2, the controller gain is obtained , , . For the following situations, simulation tests were carried out to further verify the effectiveness and superiority of the proposed control strategy.

[0067] Assume that under the influence of channel attenuation, the microgrid frequency control system is affected by Figure 2 The random perturbation shown, and the inertia constant of the system and the damping coefficient Reduced The simulation results are as follows: Figure 3 As shown. It can be seen that under the influence of channel attenuation, the cooperative control method proposed in this patent can reduce overshoot, help the system recover stability faster, and better deal with problems such as channel attenuation, system inertia reduction, and random disturbances.

[0068] This patent proposes a robust collaborative control strategy for the microgrid frequency control system under the influence of channel attenuation, which can help the microgrid frequency control system effectively deal with the negative impact of random disturbances, channel attenuation and system inertia reduction. First, a microgrid frequency control system model considering the virtual synchronous generator participating in frequency regulation under the influence of channel attenuation is established; secondly, the Lyapunov theory is used to analyze the constructed model. Performance analysis; then, the linear matrix inequality for solving the collaborative controller gain is obtained through matrix transformation; finally, the effectiveness of the proposed control strategy is verified through simulation. The results show that this method can effectively deal with the problems of random disturbance, channel attenuation and system inertia reduction faced by the microgrid frequency control system under the influence of channel attenuation. It can help the microgrid to operate better in actual engineering.

[0069] The present application also discloses a computer-readable storage medium storing a plurality of instructions suitable for loading by a processor to execute the above-mentioned method for frequency control of a low-inertia microgrid system under channel attenuation.

[0070] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure.

[0071] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A frequency control method for a low-inertia microgrid system under channel attenuation, characterized in that: The method comprises the following steps: S1: Construct a microgrid frequency control system with virtual generators participating in frequency regulation under the influence of channel attenuation; S2: Design output feedback controller; in order to achieve the stability and Under the condition of performance, solve the gain solution of the output feedback controller; S3: Substitute the gain solution of the output feedback controller into the microgrid frequency control system in which the virtual generator participates in frequency modulation, so as to realize the frequency control of the microgrid frequency control system under the conditions of channel attenuation caused by time delay, packet loss and noise.

2. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 1, characterized in that: Step S1 includes: Photovoltaic power generation , Wind power generation and the disturbance caused by the load Set to the external disturbance of the microgrid frequency control system , ; A diesel generator set, a battery energy storage system, a flywheel energy storage system and a fuel cell system are set to participate in the primary frequency modulation process of the microgrid frequency control system; set up , and Represent the time constants of the battery energy storage system, flywheel energy storage system and fuel cell system respectively; , , , , and They represent the generator moment of inertia, diesel generator damping coefficient, steam turbine time constant, governor time constant, fuel cell gain and droop characteristics respectively; , as well as Represent the output power changes of the battery energy storage system, flywheel energy storage system and fuel cell system respectively.

3. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 2, characterized in that: Step S1 also includes: The secondary control loop of the microgrid uses the PI controller as the microgrid central controller for frequency regulation; The frequency deviation of the secondary control loop of the microgrid frequency control system is used as the feedback signal. The frequency deviation is added to the primary frequency modulation loop through the microgrid central controller. The control input of the secondary control loop is recorded as .

4. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 3, characterized in that: Step S1 also includes: The relationship between the frequency deviation, active power generated and load of the microgrid frequency control system is expressed by the swing equation as follows: in, Indicates the change in mechanical power of the generator; Indicates the load power change; represents a complex variable; Indicates the frequency deviation of the system.

5. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 4, characterized in that: Step S1 also includes: By constructing a virtual synchronous generator that acts like a synchronous motor, inertial support is provided for the microgrid frequency control system. The control input of the virtual synchronous generator is recorded as ; Determine the power reference of the inverter of the microgrid frequency control system based on the swing equation , expressed as: in and The virtual moment of inertia and virtual damping coefficient provided by the virtual generator are considered; Indicates system frequency deviation; The Rice attenuation model is used to represent the channel attenuation phenomenon caused by time delay, packet loss and noise, as follows: in, and are respectively a given positive scalar and a real constant matrix of preset dimension; is the receive signal available to the controller; is an independent and identically distributed Gaussian random variable, representing the channel coefficient, whose mean and variance are and ; Indicates interference input; Indicates the partial state of the signal during the attenuation process; Indicates the impact on the signal at the sampling time during the attenuation process; In the Rice attenuation model, the measured signal is considered to be transmitted to the receiving end through different paths, and the intensity of interference on each path is determined by independent coefficients to characterize; Select state variables , external disturbance , control input , measurement output , the controlled output , the state space expression of the microgrid frequency control system with the participation of virtual synchronous generators is as follows: in , , , , , , ; represents the time constant of the energy storage system; represents the gain of the virtual droop characteristic; According to the sampling interval of microgrid frequency control in actual projects , discretize equation (3) and rewrite it into the following linear discrete-time system: The sampling time of the sensor is expressed as , , , , ; Consider the static event-triggered communication mechanism to determine whether the output signal of the PI controller needs to be transmitted to the actuator; define the event generation function as follows: in, is a given positive scalar; set up is the moment of the most recent control signal, and has , when the condition is met , a static event is triggered, and has: in, is a sequence of event triggers; Considering the influence of channel attenuation in equation (2), the output feedback control law based on the PI controller is expressed as: in, is a scalar quantity representing the length of time; and is the controller gain to be designed; The process of virtual inertia control is described as: in, is the controller gain to be designed; Written in Combining equations (5)-(8), the frequency control system (4) of the microgrid with virtual generators participating in frequency regulation is written as: in , , , , , , , represents the Q-dimensional unit matrix; , , , , , , , , represents the identity matrix of appropriate dimension; , , , .

6. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 5, characterized in that: Step S2 includes: Design an output feedback controller to ensure that the microgrid frequency control system (9) is exponentially mean square stable and at a given disturbance rejection level Under this condition, the microgrid frequency control system meets Performance constraints: The gain of the output feedback controller is , ,and , given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; There exists a positive definite matrix and , so that the linear matrix inequality (11) holds true, then the microgrid frequency control system (9) is exponential mean square stable, and the linear matrix inequality is as follows: in ， ， ， ， ， ， ， ， ， ， ， ， ， ， ， 。 7. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 6, characterized in that: Step S2 also includes: Solve the linear matrix inequality for the controller gains as follows: For a given Performance Indicators , the integral time length of the PI controller , and event trigger threshold ; If there is a matrix , , and , and the positive definite matrix and , so that the linear matrix inequality (11) holds, then the microgrid frequency control system (9) is exponentially mean square stable and satisfies under zero initial conditions The performance constraints, linear matrix inequalities, are as follows: in, , is a scalar, and , ， ， ， ， ， ， ， ， ， ， ， ， ， ， ， 。 8. A frequency control method for a low inertia microgrid system under channel attenuation as claimed in claim 7, characterized in that: Step S2 also includes: By solving the linear matrix inequality (11), the controller gain solution results of the quadratic frequency control and the virtual quadratic frequency control, that is, the gain solution results of the output feedback controller, are obtained as follows: 。 9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 8 is executed.

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