Virtual synchronous machine virtual inertia and damping coefficient adaptive control method, system, equipment and medium

Abstract

The invention relates to a virtual synchronous machine virtual inertia and damping coefficient adaptive control method, system and device and a medium. The method comprises the following steps: establishing a VSG typical grid-connected model; based on a VSG typical grid-connected model, the selection principle of the virtual inertia and the damping coefficient is analyzed when the load changes or the new energy output changes; establishing a mathematical relationship between the virtual inertia and the damping coefficient under the optimal damping ratio through a second-order system small signal analysis and parameter setting method, and analyzing to obtain the influence of the virtual inertia and the damping coefficient on the system stability; and according to the determined selection principle of the virtual inertia and the virtual damping, a logarithmic function-based adaptive virtual inertia and damping coefficient control strategy is adopted, and the reference values of the virtual inertia and the damping coefficient are determined according to the optimal damping ratio. The method can be widely applied to the technical field of virtual synchronous generator control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of virtual synchronous generator control, in particular to a virtual inertia and damping coefficient adaptive control method, system, device and medium for virtual synchronous machine. BACKGROUND

[0002] As a clean and renewable energy source, wind power generation system is becoming a key direction of global energy transformation due to its significant resource abundance and development potential. In order to reduce carbon emissions and power generation costs, wind power generation systems are widely connected to offshore oil and gas field power grids, resulting in a state of "high proportion of renewable energy and high proportion of power electronic devices". Large-scale wind power generation system grid connection leads to a decrease in the equivalent inertia and damping level of the offshore oil and gas field power grid, which may cause frequency stability problems. Large-scale wind power access helps to reduce carbon emissions and protect the environment, but its randomness and intermittency in power generation will lead to fluctuations in power grid frequency, which restricts the further development and utilization of wind energy. The virtual synchronous generator (VSG) technology reserves energy based on new energy or installs energy storage, etc. Through improved converter control method, it simulates the operation mechanism of synchronous generator, so that new energy power generation equipment has the ability to establish voltage and frequency independently, and can realize inertia response, primary frequency modulation, fast voltage regulation and other active support functions.

[0003] As shown in Figure 1 , in the prior art, the virtual inertia and damping coefficient configuration scheme in the VSG technology is mostly fixed parameter configuration. For different power systems and different degrees of power and frequency disturbances, the configuration scheme has poor ability to maintain frequency stability, and needs to be further improved. The method of virtual inertia and virtual damping cooperative control proposed by Yang Yun et al. increases the moment of inertia when the rate of change of the rotor angular velocity of the virtual synchronous generator is large, and increases the damping coefficient when the angular velocity deviation is large. The coordinated control of the two variables suppresses the rapid change and large deviation of the frequency, and ensures the stability of the system.

[0004] The shortcomings of the prior art are: 1) Single moment of inertia configuration scheme: only considers increasing the moment of inertia when the frequency deviates from the reference value, and the moment of inertia does not change when the frequency approaches the reference value; 2) Single damping coefficient configuration scheme; the damping coefficient configuration scheme does not change when the frequency deviates from the reference value and when the frequency approaches the reference value, and the influence of damping coefficient change on regulation time is not considered; 3) The starting judgment standards of moment of inertia control and damping coefficient control are not unified, which increases the complexity of the system when implementing the control scheme.

[0005] The prior art has difficulties in solving these problems: The VSG technology provides rotational inertia and damping characteristics for the power grid, but the specific configuration scheme of rotational inertia and damping coefficient is different in the grid-connected operation of different new energy power generation systems. The characteristics of different types of new energy power generation systems need to be analyzed, and the corresponding inertia and damping characteristic scheme needs to be configured. The appropriate inertia and damping for different scenes is conducive to further improving the frequency stability of the power grid system. SUMMARY

[0006] To solve the above problems, the purpose of the present application is to provide a virtual synchronous machine virtual inertia and damping coefficient adaptive control method, system, device and medium, which is suitable for high proportion of offshore wind power grid-connected offshore oil and gas field microgrid, adopts hybrid configuration of virtual inertia and damping coefficient, and improves the stability of system frequency.

[0007] To achieve the above purpose, the present application adopts the following technical solutions: In a first aspect, the present application provides a virtual synchronous machine virtual inertia and damping coefficient adaptive control method, comprising the following steps: Establishing a typical VSG grid-connected model; Based on the typical VSG grid-connected model, analyzing the selection principle of virtual inertia and damping coefficient when the load changes or the new energy output changes; Through the small signal analysis and parameter setting method of the second-order system, the influence of virtual inertia and damping coefficient on system stability is analyzed, and the mathematical relationship between virtual inertia and damping coefficient under the concept of optimal damping ratio is established; According to the determined selection principle of virtual inertia and virtual damping, an adaptive virtual inertia and damping coefficient control strategy based on logarithmic function is adopted, and the reference value of virtual inertia and damping coefficient is determined according to the concept of optimal damping ratio.

[0008] Further, the VSG typical grid-connected model comprises: Electromagnetic torque equation:

[0009] In the formula: is the electromagnetic torque; is the electromagnetic power of the virtual synchronous machine; is the inverter output voltage; is the inverter output current; , , is the inverter output voltage corresponding to the three-phase value; , , is the inverter output current corresponding to the three-phase value; virtual rotor angular velocity of the virtual synchronous machine; electromagnetic equation:

[0010] synchronous inductance of the virtual synchronous machine; synchronous resistance of the synchronous generator; terminal voltage of the synchronous generator; active regulation equation:

[0011] input mechanical power; active power instruction of the virtual synchronous machine, active regulation coefficient; synchronous angular velocity of the power grid; reactive regulation equation:

[0012] port voltage, reference voltage, reactive regulation coefficient; reactive power instruction of the inverter, actual output reactive power of the inverter.

[0013] Further, the VSG-based typical grid-connection model is used to analyze the selection principles of virtual inertia and damping coefficient when the load changes or the new energy output changes, including: the mechanical equation of the synchronous generator is equivalently transformed, and the influence of the changes of virtual inertia and damping coefficient on the frequency and the frequency change is analyzed to determine the change law thereof; the power angle and frequency oscillation curve of the synchronous generator are analyzed, and the selection principles of rotational inertia and damping coefficient when the load changes or the new energy output changes are determined in combination with the determined change law.

[0014] Further, the selection principles of rotational inertia and damping coefficient when the load changes or the new energy output changes include: an oscillation process caused by the load change or the new energy output change is divided into four intervals: ① , ② , ③ , and ④ , wherein, , , , , ​​​corresponding to the moment of disturbance, the moment of maximum positive angular velocity deviation, the moment of returning to rated angular velocity, the moment of maximum negative angular velocity deviation, and the moment of next returning to rated angular velocity, respectively; In interval ①, if > 0, > 0, the virtual inertia and the damping coefficient are increased; In interval ②, if > 0, < 0, the virtual inertia is decreased and the damping coefficient is increased; In interval ③, if < 0, < 0, the virtual inertia and the damping coefficient are increased; In interval ④, if < 0, < 0, the virtual inertia is decreased and the damping coefficient is increased.

[0015] Further, the virtual inertia and the damping coefficient under the optimal damping ratio need to satisfy:

[0016]

[0017]

[0018] wherein, is the damping, is the rated capacity of the synchronous generator, is the synchronous angular velocity of the power grid, is the unit value of the synchronous power; is the inertia time constant.

[0019] Further, the calculation formula for the reference value of the virtual inertia and the damping coefficient is represented as:

[0020]

[0021] wherein: is the initial value of the virtual rotational inertia; , are the virtual rotational inertia adjustment coefficients; is the minimum frequency deviation of the start configuration scheme; is the initial value of the virtual damping; , is a virtual damping coefficient adjustment coefficient.

[0022] In a second aspect, the present application provides a virtual synchronous machine virtual inertia and damping coefficient adaptive control system, comprising: A model establishing module is configured to establish a VSG typical grid-connection model. A selection principle determining module is configured to analyze the selection principle of the virtual inertia and the damping coefficient when the load changes or the new energy output changes based on the VSG typical grid-connection model. A small signal analysis and parameter setting module is configured to establish the mathematical relationship between the virtual inertia and the damping coefficient under the optimal damping ratio by the small signal analysis and parameter setting method of the second-order system, and analyze the influence of the virtual inertia and the damping coefficient on the system stability. A parameter calculation module is configured to determine the reference value of the virtual inertia and the damping coefficient from the optimal damping ratio by using the adaptive virtual inertia and damping coefficient control strategy based on the logarithmic function according to the determined selection principle of the virtual inertia and the virtual damping.

[0023] Further, the selection principle determining module comprises: A change law analysis module is configured to perform equivalent transformation on the mechanical equation of the synchronous generator, analyze the influence of the change of the virtual inertia and the damping coefficient on the frequency and the frequency change, and determine the change law thereof. A principle determining module is configured to analyze the power angle and the frequency oscillation curve of the synchronous generator, and determine the selection principle of the rotational inertia and the damping coefficient when the load changes or the new energy output changes in combination with the determined change law.

[0024] In a third aspect, the present application provides a computer readable storage medium storing one or more programs, the one or more programs comprising instructions which, when executed by a computing device, cause the computing device to perform any of the methods.

[0025] In a fourth aspect, the present application provides a computing device comprising one or more processors and memory storing one or more programs configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods.

[0026] The present application has the following advantages due to the above technical solutions: the present application proposes a dynamic control strategy for the VSG virtual inertia and the damping coefficient, and proposes a parameter adaptive adjustment strategy based on the natural logarithmic function of the frequency change rate. The simulation results show that, compared with the fixed parameter control strategy, the proposed method has smaller frequency overshoot and shorter adjustment time, and effectively improves the frequency stability.

[0027] Therefore, the application is suitable for offshore wind power grid connection scenarios considering output uncertainty, and can be widely applied to the field of virtual synchronous generator control technology. BRIEF DESCRIPTION OF DRAWINGS

[0028] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The detailed description is made with reference to the accompanying drawings. Figure 1 is a virtual synchronous machine control method flowchart in a conventional method; Figure 2 is a virtual synchronous machine virtual inertia and damping coefficient adaptive control method flowchart provided in the embodiment of the application; Figure 3 is a structure topology diagram of a virtual synchronous machine provided in the embodiment of the application; Figure 4 is a virtual governor control principle diagram provided in the embodiment of the application; Figure 5 is a virtual exciter control principle diagram provided in the embodiment of the application; Figure 6 is a synchronous generator power angle and frequency oscillation curve provided in the embodiment of the application; Figure 7 is a small signal analysis model diagram provided in the embodiment of the application; Figure 8 is an active power response comparison under different control strategies provided in the embodiment of the application; Figure 9 is a frequency change comparison under different control strategies provided in the embodiment of the application; Figure 10 is a change condition provided in the embodiment of the application; Figure 11 is a change condition provided in the embodiment of the application. DETAILED DESCRIPTION

[0029] In order to make the objects, technical solutions and advantages of the embodiments of the application clearer, the technical solutions of the embodiments of the application will be described clearly and completely below with reference to the drawings of the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments of the application. Based on the described embodiments of the application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the application.

[0030] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0031] Fluctuations in active power output from offshore wind farms threaten frequency stability. By simulating the characteristics of synchronous generators, virtual synchronous generator (VSG) control provides an effective means of frequency support.

[0032] Based on this, in some embodiments of the present invention, an adaptive control method for virtual inertia and damping coefficient of a virtual synchronous machine is provided. By analyzing the mathematical relationship between rotational inertia and damping coefficient, the starting judgment criteria for a unified configuration scheme of virtual inertia and damping coefficient of the virtual synchronous machine are integrated to achieve a rotational inertia and damping coefficient configuration that meets the frequency stability requirements of the offshore oil and gas field power grid.

[0033] Correspondingly, in other embodiments of the present invention, an adaptive control system, device, and medium for virtual synchronous machine virtual inertia and damping coefficient are provided.

[0034] Example 1 like Figure 2 As shown, this invention provides an adaptive control method for virtual inertia and damping coefficient of a virtual synchronizer, comprising the following steps: 1) Establish a typical VSG grid connection model.

[0035] Specifically, it includes the following steps: 1.1) Based on the typical inverter grid-connected topology, establish a typical VSG grid-connected model.

[0036] like Figure 3 As shown, a typical VSG grid-connected model is constructed based on a typical inverter grid-connected topology. This topology includes an inverter, an LC filter, a load, and an external power grid.

[0037] In a traditional synchronous generator, the mechanical equations of the synchronous generator can be expressed as: (1) In the formula: The moment of inertia of the synchronous generator; The synchronous angular velocity of the power grid; , , These are the mechanical torque, electromagnetic torque, and damping torque of the synchronous generator, respectively. The damping coefficient; The power angle of the synchronous generator; This represents the rotor angular velocity of the synchronous generator.

[0038] Analysis of formula (1) shows that the electromagnetic torque of the synchronous generator The electromagnetic power of the virtual synchronizer can be used to... With virtual rotor angular velocity The calculation yields the following result, which is expressed as: (2) In the formula: , , These are the inverter output voltages. The corresponding three-phase values; , , The inverter output current is respectively The corresponding three-phase values.

[0039] By introducing rotational inertia With damping coefficient This gives the inverter inertia during power and frequency fluctuations, allowing the inverter devices to dampen grid power oscillations during power generation and grid connection, similar to a traditional synchronous generator. This is of great significance for the stability of frequency and power in microgrid operation.

[0040] pass Figure 3 The typical grid-connected VSG model can be further used to derive the electromagnetic equations of the virtual synchronous machine, which are expressed as: (3) In the formula: Synchronization inductor for virtual synchronous machines; The synchronizing resistance of the synchronous generator; This refers to the terminal voltage of the synchronous generator; This refers to the inverter output voltage. This is the inverter output current.

[0041] 1.2) Based on the typical VSG grid connection model, establish the active power regulation equation and reactive power regulation equation of the virtual synchronous machine.

[0042] Traditional synchronous generators can adjust their output active power by changing the input power of the prime mover, i.e., changing the mechanical power, and stabilize the grid frequency through a frequency regulator. Borrowing from this principle, the active power of a grid-connected inverter can be adjusted by changing its mechanical torque.

[0043] Among them, mechanical torque , Given the input mechanical power, the active power regulation equation is: (4) In the formula: The active power command for the virtual synchronizer. This is the active power adjustment coefficient.

[0044] like Figure 5 As shown, substituting equation (4) into equation (1) and performing a Laplace transform yields the active power control relationship: (5) Traditional synchronous generators regulate the reactive power output and terminal voltage by adjusting the excitation current. In inverters, the reactive power and port voltage are regulated by adjusting the virtual electromotive force in the virtual synchronous machine.

[0045] (6) In the formula: Port voltage, The reference voltage is typically... V; This is the reactive power regulation coefficient; This is the reactive power command for the inverter. This represents the actual reactive power output of the inverter.

[0046] like Figure 5 As shown, the potential-voltage control principle diagram of the virtual synchronizer can be obtained. The potential-voltage vector of the virtual synchronizer is: (7) In the formula: This is the phase angle output by the active power regulation equation of the virtual synchronous machine.

[0047] 2) Based on the typical VSG grid connection model, analyze the selection principles of virtual inertia and damping coefficient when the load / new energy output changes.

[0048] Specifically, it includes the following steps: 2.1) Perform equivalent transformations on the mechanical equations of the synchronous generator, analyze the effects of changes in virtual inertia and damping coefficient on frequency and frequency variation, and determine their variation patterns.

[0049] According to the transformation of equation (1), we can obtain: (8) It can be seen from equation (8) that if If it remains constant, then it increases. It can reduce the deviation ;like If it remains unchanged, then it increases. It can reduce the rate of change of angular velocity To ensure frequency stability, the moment of inertia is changed. With damping coefficient It can inhibit and This is similar to how the rotational inertia of a synchronous generator and the damping characteristics caused by damping windings, rotor losses, and physical friction maintain grid stability.

[0050] 2.2) Analyze the power angle and frequency oscillation curves of the synchronous generator, and combine them with the variation law determined in step 2.1) to determine the selection principles of moment of inertia and damping coefficient when the load changes / new energy output changes.

[0051] like Figure 6 The figure shows the oscillation curves of the power angle and frequency of the synchronous generator. Combined with formula (8), the selection principles for the moment of inertia and damping coefficient under different conditions can be determined: The given active power of the synchronous generator is from Rise to During the switching process, both power and frequency changes are damped oscillations, similar to the oscillation process of a virtual synchronous machine. Generally, for ease of analysis, assuming constant moment of inertia and damping coefficient, an oscillation process is divided into four intervals: ① , ② ③ , ④ ,in, , , , , These correspond to the time of disturbance occurrence, the time of maximum positive angular velocity deviation, the time of recovery to rated angular velocity, the time of maximum negative angular velocity deviation, and the time of the next recovery to rated angular velocity.

[0052] Within interval ①, the virtual rotor angular velocity of the virtual synchronous machine is greater than the grid velocity and gradually increases, with the rate of change of angular velocity being... It first suddenly gets bigger and then gradually gets smaller. When it is greater than 0, increase and To suppress and This constrains the increase in rotor angular velocity; in interval ②, the rate of change of the virtual rotor angular velocity of the virtual synchronizer. When the value is less than 0, the deceleration phase begins. It gradually decreases from the maximum value, but > In other words, the virtual rotor angular velocity is still greater than the grid angular velocity. A smaller moment of inertia should be used to speed up the process of the angular velocity recovering to the rated value. At the same time, increasing the damping coefficient can further suppress the deviation of the angular velocity. However, the increase in the damping coefficient should not be too large, otherwise the recovery time will be prolonged. In intervals ③ and ④, the selection of virtual inertia and damping coefficient is similar to that in intervals ① and ②.

[0053] The selection principles for moment of inertia and damping coefficient are shown in Table 1.

[0054] Table 1. Selection principles for moment of inertia and damping coefficient under different conditions.

[0055] In summary, the virtual rotational inertia has been determined in the VSG control strategy. J With virtual damping coefficient D The law of increase and decrease in power angle and frequency oscillation is understood, but the specific setting during the change process is still one of the technologies under research.

[0056] 3) By using the small-signal analysis and parameter tuning method of second-order system, the influence of virtual inertia and damping coefficient on system stability is analyzed, and the mathematical relationship between virtual inertia and damping coefficient under the concept of optimal damping ratio is established.

[0057] Specifically, it includes the following steps: The moment of inertia of a synchronous generator is a physical quantity related to the generator's dimensions, and generally increases with increasing rated power. Typically, the inertial time constant is used... To measure the inertia of generators of different sizes. Defined as: (9) In the formula: This refers to the rated capacity of the synchronous generator.

[0058] (10) In the formula: If the torque reference value is used, then the power reference value is used. If the per-unit value of the rotational speed is 1, then .

[0059] definition , Combined with the inertial time constant and torque reference value Substituting into equation (1) and performing a Laplace transform yields: (11) In the formula, per-unit value of speed deviation per-unit value of rotational speed per-unit value of mechanical torque This is the per-unit value of the electromagnetic torque.

[0060] Combining the foregoing analysis and equation (11), and drawing upon traditional small-signal analysis methods for power systems, a virtual synchronizing machine small-signal analysis model can be obtained, such as... Figure 7 As shown, the input and output power of the virtual synchronous machine is a typical second-order transfer function: (12) In the formula: Output power of virtual synchronous machine in frequency domain This is the reference power for the virtual synchronizer in the frequency domain; The per-unit value of synchronous power is expressed as: (13) In the formula: and It is related to the virtual synchronizer. and The relevant steady-state equilibrium point.

[0061] exist LC The inductor parameters of the filter circuit are known, and the mains voltage is... Under constant conditions, it can be calculated using equation (14): (14) In the formula: This is the impedance of the filter circuit.

[0062] It can be seen that, given the active and reactive commands, If ω is a constant, then the second-order model of the virtual synchronizer and its natural oscillation angular frequency are... and damping coefficient Zeta They are respectively: (15) For traditional synchronous generators, the natural oscillation angular frequency is typically between 0.628 and 15.7 rad / s, under damping... Insufficient damping can cause low-frequency oscillations in the power grid, posing a significant hidden danger to the power system. For virtual synchronous generators, inertia and damping can be considered pre-defined; when damping is sufficiently large, It is an underdamped second-order system, 0 < ζ < 1, and its dynamic response time is: (16) By utilizing the concept of an optimal second-order system, a fast response speed and small overshoot are achieved, and the system's damping ratio is controlled within... ZetaAt =0.707, that is: (17) 4) Based on the determined selection principles of virtual inertia and virtual damping, an adaptive virtual inertia and damping coefficient control strategy based on logarithmic functions is adopted, and the reference values ​​of virtual inertia and damping coefficient are determined by the concept of optimal damping ratio.

[0063] In this embodiment, the logarithmic function ln is used to configure the virtual inertia and damping coefficient, which are expressed as follows: (18) (19) In the formula: This is the initial value of the virtual moment of inertia; , Both are virtual moment of inertia adjustment coefficients; Minimum frequency deviation for starting the configuration scheme; This is the initial value for virtual damping; , This is the virtual damping coefficient adjustment coefficient.

[0064] Example 2 To verify the effectiveness of the theoretical analysis and proposed parameter adaptive control strategy of this invention, this embodiment builds a single-machine virtual synchronous machine model in MATLAB / Simulink software for simulation analysis. The simulation parameters are shown in Table 2. For filtering capacitors; This is the DC bus voltage.

[0065] Table 2 Simulation Parameters

[0066] A single virtual synchronous generator was connected to the power grid. The simulation time was 2 seconds. The active power of the load was 10kW and the reactive power was 0kvar. Initially, the given output active power of the virtual synchronous generator was 10kW. At 0.5s, the active power suddenly increased to 15kW and then suddenly dropped back to 10kW at 1.3s. The reactive power remained constant at 0kvar.

[0067] Figure 8 The step response curves of the active power output of the virtual synchronous generator under different control strategies are shown. When the input power suddenly increases, the active power overshoot of the virtual synchronous generator control with constant parameters, the control with configured moment of inertia, and the control with configured moment of inertia and damping coefficient are 8.6%, 2.67%, and 1.33%, respectively, and the settling times are approximately 0.28s, 0.25s, and 0.2s, respectively. This proves that the proposed method reduces the active power overshoot and settling time, and improves the system response performance.

[0068] Figure 9 This paper compares the output frequencies of virtual synchronous generators under different control strategies. The adaptive change of moment of inertia has a significant impact on the rate of frequency change. When the input power suddenly increases, the output frequency deviation of the virtual synchronous generator with fixed parameters is close to 0.16Hz, and the oscillation duration is about 0.3s. When the moment of inertia control strategy is adopted, the maximum frequency deviation is reduced to 0.125Hz, and the settling time is reduced. When the moment of inertia and damping coefficient control strategy is adopted, the frequency deviation is reduced to 0.1Hz, indicating that the addition of damping coefficient control reduces the frequency deviation range.

[0069] The simulation condition involves the VSG power command increasing from 10kW to 15kW in 0.5 seconds, and then returning to 10kW in 1.3 seconds. Figure 10 and Figure 11 As shown, this is a control strategy configured with rotational inertia and damping coefficient. and The changes.

[0070] Output fluctuations caused by distributed energy sources integrated into microgrids can lead to grid frequency instability and power fluctuations. This invention proposes an adaptive control strategy for configuring the rotational inertia and damping coefficient of a virtual synchronous generator (VSG). First, a virtual synchronous generator model is established, and the correlation between inertia, damping coefficient, and frequency and power deviations under disturbance conditions is derived. Then, a control strategy targeting inertia is proposed. and damping coefficient Cooperative adaptive control strategy: and The invention is achieved by adjusting the logarithmic function. Simulation using MATLAB / Simulink verifies the effectiveness of this invention. , The cooperative adaptive control virtual synchronous generator has better frequency fluctuation suppression performance. It can reduce the rate of change of frequency fluctuation and the frequency offset, ultimately reducing frequency overshoot, shortening recovery time, and improving frequency stability. It also demonstrates the flexibility of virtual synchronous generator in control.

[0071] Example 3 The above-described embodiment 1 provides an adaptive control method for the virtual inertia and damping coefficient of a virtual synchronizer. Correspondingly, this embodiment provides an adaptive control system for the virtual inertia and damping coefficient of a virtual synchronizer. The system provided in this embodiment can implement the adaptive control method for the virtual inertia and damping coefficient of the virtual synchronizer in embodiment 1. This system can be implemented through software, hardware, or a combination of both. For example, the system may include integrated or separate functional modules or units to execute the corresponding steps in the methods of embodiment 1. Since the system in this embodiment is basically similar to the method embodiment, the description process in this embodiment is relatively simple. For relevant details, please refer to the description of embodiment 1. The system embodiment provided in this embodiment is merely illustrative.

[0072] The virtual synchronous machine virtual inertia and damping coefficient adaptive control system provided in this embodiment includes: The model building module is used to establish a typical VSG grid-connected model and determine the active power regulation equation and reactive power regulation equation. The variation law analysis module is used to analyze the variation law of frequency and frequency change rate when the load changes / new energy output changes based on the typical VSG grid connection model, and then obtain the variation law of rotational inertia and damping coefficient. The relationship analysis module is used to determine the mathematical relationship between virtual inertia and damping coefficient through small-signal analysis and parameter tuning methods for second-order systems, and to analyze the impact of virtual inertia and damping coefficient on system stability. The parameter configuration module is used for an adaptive virtual inertia and damping coefficient control strategy based on a logarithmic function. It takes the frequency deviation value and frequency change rate when a disturbance occurs as inputs to obtain the corresponding virtual inertia and damping coefficient values.

[0073] Example 4 This embodiment provides a processing device corresponding to the virtual synchronous machine virtual inertia and damping coefficient adaptive control method provided in Embodiment 1. The processing device can be a client-side processing device, such as a mobile phone, laptop, tablet computer, desktop computer, etc., to execute the method of Embodiment 1.

[0074] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to enable communication between them. The memory stores a computer program that can run on the processor. When the processor runs the computer program, it executes the virtual synchronous machine virtual inertia and damping coefficient adaptive control method provided in Embodiment 1.

[0075] Preferably, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0076] Preferably, the processor can be any type of general-purpose processor such as a central processing unit (CPU) or a digital signal processor (DSP), and there is no limitation herein.

[0077] Example 5 The virtual inertia and damping coefficient adaptive control method of the virtual synchronizer in Embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the virtual inertia and damping coefficient adaptive control method of the virtual synchronizer described in Embodiment 1 are loaded.

[0078] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0079] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A virtual synchronous machine virtual inertia and damping coefficient adaptive control method, characterized in that, The method comprises the following steps: establishing a typical grid-connected model of a VSG; based on the typical grid-connected model of the VSG, analyzing the selection principle of the virtual inertia and the damping coefficient when the load changes or the new energy output changes; through small signal analysis and parameter setting method of a second-order system, analyzing the influence of the virtual inertia and the damping coefficient on system stability, and establishing a mathematical relationship between the virtual inertia and the damping coefficient under the concept of optimal damping ratio; according to the determined selection principle of the virtual inertia and the virtual damping, adopting an adaptive virtual inertia and damping coefficient control strategy based on a logarithmic function, and determining the reference value of the virtual inertia and the damping coefficient according to the concept of optimal damping ratio.

2. The virtual synchronous machine virtual inertia and damping coefficient adaptive control method of claim 1, wherein, The typical grid-connected model of the VSG comprises: an electromagnetic torque equation: wherein: is the electromagnetic torque; is the electromagnetic power of the virtual synchronous machine; is the inverter output voltage; is the inverter output current; , , are the inverter output voltage corresponding three-phase values; , , are the inverter output current corresponding three-phase values; is the virtual rotor angular velocity of the virtual synchronous machine; an electromagnetic equation: In the formulae: is the synchronous inductance of the virtual synchronous machine; is the synchronous resistance of the synchronous generator; is the terminal voltage of the synchronous generator; an active regulation equation: In the formula: is the input mechanical power; is the active power command of the virtual synchronous machine, is the active regulation coefficient; is the synchronous angular speed of the grid; a reactive regulation equation. In the formula: is the port voltage, is the reference voltage, is the reactive power adjustment coefficient; is the reactive power command of the inverter, is the actual output reactive power of the inverter.

3. The virtual synchronous machine virtual inertia and damping coefficient adaptive control method of claim 2, wherein, The selection principle of the virtual inertia and the damping coefficient when the load changes or the new energy output changes based on the typical grid-connected model of the VSG comprises: performing equivalent transformation on a mechanical equation of a synchronous generator, and analyzing the influence of the change of the virtual inertia and the damping coefficient on the frequency and the frequency change, to determine the change law thereof; analyzing an oscillation curve of the power angle and the frequency of the synchronous generator, and combining the determined change law to determine the selection principle of the rotational inertia and the damping coefficient when the load changes or the new energy output changes.

4. The virtual synchronous machine virtual inertia and damping coefficient adaptive control method of claim 3, wherein, The selection principle of the rotational inertia and the damping coefficient when the load changes or the new energy output changes comprises: The oscillation process caused by load change or new energy output change is divided into four intervals: ① , ② , ③ , ④ , wherein , , , , correspond to the moment of disturbance, the moment of maximum positive angular velocity deviation, the moment of recovery to rated angular velocity, the moment of maximum negative angular velocity deviation and the moment of next recovery to rated angular velocity respectively. Within interval ①, if > 0, > 0, then increase virtual inertia and damping coefficient ; In interval ②, if > 0, < 0, then decrease the virtual inertia , increase the damping coefficient ; In interval ③, if <0, <0, then increase virtual inertia and damping coefficient ; In interval (IV), if <0, <0, then the virtual inertia is decreased and the damping coefficient is increased.

5. The virtual synchronous machine virtual inertia and damping coefficient adaptive control method of claim 2, wherein, The virtual inertia and the damping coefficient under the optimal damping ratio need to satisfy: wherein is the damping, is the rated capacity of the synchronous generator, is the synchronous angular velocity of the power grid, is the unit of the synchronous power; is the inertia time constant.

6. The virtual synchronous machine virtual inertia and damping coefficient adaptive control method of claim 2, wherein, The calculation formula of the reference value of the virtual inertia and the damping coefficient is expressed as: wherein: is the virtual moment of inertia initial value; , are virtual moment of inertia adjustment coefficients; is the minimum frequency deviation of the start-up configuration scheme; is the virtual damping initial value; , is the virtual damping coefficient adjustment coefficient.

7. A virtual synchronous machine virtual inertia and damping coefficient adaptive control system, characterized by, comprises: a model establishing module configured to establish a typical grid-connected model of a VSG; a selection principle determining module configured to, based on the typical grid-connected model of the VSG, analyze the selection principle of the virtual inertia and the damping coefficient when the load changes or the new energy output changes; a small signal analysis and parameter setting module configured to, through small signal analysis and parameter setting method of a second-order system, analyze the influence of the virtual inertia and the damping coefficient on system stability, and establish a mathematical relationship between the virtual inertia and the damping coefficient under the concept of optimal damping ratio; a parameter calculation module configured to, according to the determined selection principle of the virtual inertia and the virtual damping, adopt an adaptive virtual inertia and damping coefficient control strategy based on a logarithmic function, and determine the reference value of the virtual inertia and the damping coefficient according to the concept of optimal damping ratio.

8. A virtual synchronous machine virtual inertia and damping coefficient adaptive control system in accordance with claim 7, characterized in that, The selection principle determining module comprises: a change law analyzing module configured to perform equivalent transformation on a mechanical equation of a synchronous generator, and analyze the influence of the change of the virtual inertia and the damping coefficient on the frequency and the frequency change, to determine the change law thereof; a principle determining module configured to analyze an oscillation curve of the power angle and the frequency of the synchronous generator, and combine the determined change law to determine the selection principle of the rotational inertia and the damping coefficient when the load changes or the new energy output changes.

9. A computer-readable storage medium storing one or more programs, the one or more programs comprising instructions that when executed by a computer cause the computer to perform a method of any of claims 1-8. The one or more programs comprise instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1-6.

10. A computing device, comprising: comprises: One or more processors and memory having stored therein one or more programs configured to, working with the one or more processors, cause performance of any of the methods of claims 1-6.

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