Self-adaptive control method and system for virtual synchronous generator

Abstract

The invention relates to a self-adaptive control method and system for a virtual synchronous generator. According to the method, a double-layer self-adaptive inertia regulation and control mechanism is constructed; the double-layer self-adaptive inertia regulation and control mechanism comprises a control priority self-adaptive link and a frequency self-adaptive regulation link; in the control priority self-adaption link, under the condition that a power oscillation value is larger than a frequency oscillation value, namely power adjustment is taken as a main part, the virtual inertia is reduced; on the contrary, the virtual inertia is improved, and the frequency support is strengthened. In the frequency adaptive adjustment link, a response sensitive area and an overshoot stabilizing area are constructed, and the virtual inertia is adjusted based on the response sensitive area and the overshoot stabilizing area. Compared with the prior art, the method has the advantages of being high in robustness, stable in control, short in response time and the like.

Description

Technical Field

[0001] The present invention relates to the field of virtual synchronous generator control, and in particular to an adaptive control method and system for a virtual synchronous generator. Background Art

[0002] As a crucial component of power systems, synchronous generators have achieved remarkable results in both theoretical exploration and control design. In grid-connected power generation, they demonstrate unique advantages far exceeding those of distributed generation systems that rely on power electronics. As a key element in traditional power grids, synchronous generators not only effectively cope with fluctuations in grid voltage and frequency, but also offer unique characteristics such as high output impedance, autonomous synchronization, excellent overload capacity, large moment of inertia, and automatic frequency regulation.

[0003] In response to the shortcomings of existing grid-connected inverters in stability control and the problem of angle oscillation, some scholars were inspired to propose the concept of virtual synchronous generator (VSG).

[0004] However, current research has mostly focused on simulating the inherent characteristics of synchronous generators, with less attention paid to the potential advantages that inverters offer over synchronous generators. With the widespread adoption of VSG technology, the functional deficiencies of traditional VSG methods with fixed inertia constants have become increasingly apparent under complex operating conditions.

[0005] For example, patent publication CN119482747A discloses a method for controlling the secondary control of a virtual synchronous generator within a predetermined timeframe. This method calculates frequency errors and cooperatively controls input signal errors to construct a secondary control equation for the virtual synchronous generator within the predetermined timeframe. This control model is then constructed to ensure that the output frequency of each DG returns to its rated frequency within the predetermined timeframe, and that output power is distributed proportionally to demand. However, this method only considers the time factor and ignores the stability of the control, resulting in poor overall control effectiveness.

[0006] For example, patent publication CN116231679B discloses an adaptive virtual synchronous generator control method based on deep reinforcement learning. This method uses deep reinforcement learning to adaptively control virtual inertia and damping coefficients. However, this deep reinforcement learning method relies on initial data for training, resulting in unsatisfactory initial stability and response time.

[0007] While lower virtual inertia results in faster transient response, the frequency fluctuations are larger, hindering stable operation. Higher virtual inertia reduces the system's stability margin, slowing response and extending recovery times when subjected to external disturbances. This results in traditional fixed-inertia VSG technology experiencing insufficient response and inability to balance loads or external frequency disturbances. Summary of the Invention

[0008] The purpose of the present invention is to provide an adaptive control method and system for a virtual synchronous generator in order to overcome the defects of the prior art.

[0009] The purpose of the present invention can be achieved by the following technical solutions: According to one aspect of the present invention, a method for adaptive control of a virtual synchronous generator is provided. In the method, a two-layer adaptive inertia control mechanism is constructed and used to control the virtual inertia. The two-layer adaptive inertia control mechanism includes a control priority adaptive link and a frequency adaptive adjustment link. During the priority adaptation process, firstly, it is determined whether the current situation is mainly power regulation or frequency regulation, and the virtual inertia is adjusted according to the determination result; During the frequency self-shift process, a response-sensitive region and an overshoot suppression region are constructed, and the virtual inertia is adjusted based on the response-sensitive region and the overshoot suppression region.

[0010] As a preferred technical solution, the method includes the following steps: S1. Design the parameters of the second-order oscillation model to determine the upper and lower limits of the virtual inertia; S2. Constructing a dual-layer adaptive inertia control mechanism, which includes a control priority adaptive link and a frequency adaptive adjustment link; S3, real-time monitoring of the frequency, active power and angular frequency of the virtual synchronous generator, and calculation of the deviation values ​​of the three in adjacent preset unit time; S4. When any deviation value exceeds its corresponding preset deviation value, the current virtual inertia is calculated based on the deviation value of the angular frequency and the preset deviation value within the upper and lower limits of the virtual inertia using the dual-layer adaptive inertia control mechanism; S5. Adjust the active power and frequency of the virtual synchronous generator based on the current virtual inertia control.

[0011] As a preferred technical solution, the second-order oscillation model parameters in S1 include the second-order oscillation model damping coefficient 、 Droop coefficient and damping coefficient; the damping coefficient of the second-order oscillation model satisfies the following formula: ; ; Where, ζ is the damping coefficient; H is the virtual inertia; μ is the damping coefficient; λ is the partial derivative of the active output with respect to the output voltage parameter at the reference active and reactive power points; The reciprocal of the droop coefficient is of the same order of magnitude as the damping coefficient, that is, the droop coefficient and the damping coefficient satisfy the following formula: 1 / D =a· k ; Where, D is the droop coefficient; k is the damping coefficient; a is a constant, which is less than 10 and greater than 1 / 10.

[0012] As a preferred technical solution, the control priority adaptive link is specifically as follows: when the power oscillation value is greater than the frequency oscillation value, that is, when power regulation is mainly used, the virtual inertia is reduced; otherwise, the virtual inertia is increased and the frequency support is strengthened.

[0013] As a preferred technical solution, the frequency adaptive adjustment link is specifically as follows: when the system is subject to external interference and causes the frequency to deviate from its stable operating point, if the deviation amplitude is lower than the preset deviation amplitude, the system enters the response-sensitive area, that is, the virtual inertia is adaptively adjusted with the change of frequency; conversely, if the deviation amplitude is higher than the preset deviation amplitude, the system enters the overshoot suppression area, that is, the virtual inertia does not change with the change of frequency. At this time, the VSG output frequency remains stable and is gradually adjusted until it reaches the response-sensitive area.

[0014] As a preferred technical solution, in S4, the current virtual inertia calculated based on the deviation value of the angular frequency and the preset deviation includes a sensitive area gain term, an offset suppression term, and a reference inertia compensation, thereby realizing the frequency adaptive adjustment link. The specific formula is: ; Where, H is the virtual inertia; A is Adjust the amplitude parameter to control the maximum change amplitude of virtual inertia; C The response bandwidth parameter is used to define the width of the response curve of the virtual inertia. B It is the sensitivity factor of adaptive control, used to adjust the virtual inertia H The rate of response; H 0 is the virtual inertia reference value; ω is the angular frequency at the VSG output; ω ref is the reference angular frequency; when When the deviation is less than the preset value, the virtual inertia is dominated by the sensitive zone gain term, and the sensitivity of the virtual inertia to small frequency deviations is dynamically changed by adjusting the adaptive control sensitivity factor; when When the value is greater than or equal to the preset deviation value, the virtual inertia is controlled by the offset suppression term. At this time, the offset suppression term controls the virtual inertia gain to reduce, avoiding phase lag caused by excessive virtual inertia.

[0015] As a preferred technical solution, in S4, when calculating the current virtual inertia, the sensitivity factor of adaptive control is used B , in order to complete the control priority adaptive link, the sensitivity factor of adaptive control B The specific formula is: ; Among them, the parameters k It is a preset adjustment factor used to measure the importance attached to frequency deviation; k The larger the value of , the more significant the deviation of the current output frequency of the system from the expected value, thus giving priority to frequency control; the numerator reflects the square characteristic of the frequency offset and is used to enhance the sensitivity under large deviation conditions.

[0016] As a preferred technical solution, the preset adjustment factor k according to Change and change; when When the preset adjustment factor gives priority to ensuring the power tracking speed; when When the preset adjustment factor is used to balance power regulation and frequency regulation; when When , the preset adjustment factor is used to force frequency stability to take priority. The specific formula of the preset adjustment factor is: ; ; ; in, is the baseline sensitivity; is the intermediate gain coefficient; is the maximum sensitivity threshold.

[0017] As a preferred technical solution, the specific process of adjusting the active power and frequency of the virtual synchronous generator based on the current virtual inertia control in S5 is: using the current virtual inertia to calculate the virtual rotational inertia, combining it with the rotor motion equation, further calculating the virtual torque required to resist the frequency change, and by controlling the inverter output, adjusting the current electromagnetic torque to the required virtual compensation torque ∆T, adjusting the inverter bridge arm conduction timing through the PWM modulator, so that the output electromagnetic torque tracks ∆T, and then adjusting the output frequency of the virtual synchronous generator to make it close to the rated frequency, thereby suppressing frequency fluctuations.

[0018] According to another aspect of the present invention, an adaptive control system for a virtual synchronous generator is provided, the system comprising a parameter configuration unit, an algorithm core unit, a signal sensing unit, an inertia decision unit, and a power execution unit; The parameter configuration unit is used to store the second-order oscillation model parameters; The algorithm core unit is used to run the double-layer adaptive inertia control mechanism; The signal sensing unit is used to monitor the frequency, active power and angular frequency of the virtual synchronous generator in real time, and calculate the deviation values ​​of the three in adjacent preset unit time respectively; The inertia decision unit is used to calculate the current virtual inertia based on the angular frequency deviation and the preset deviation value within the upper and lower limits of the virtual inertia using a double-layer adaptive inertia control mechanism when any deviation value exceeds its corresponding preset deviation value; The power execution unit is used to convert the virtual inertia into a control signal to control and adjust the active power and frequency of the virtual synchronous generator.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, a two-layer adaptive inertia control mechanism is constructed and utilized to control virtual inertia. The two-layer adaptive inertia control mechanism includes a control priority adaptation link and a frequency adaptive adjustment link. During the priority adaptation process, it is first determined whether the current situation is mainly power regulation or frequency regulation, and the virtual inertia is adjusted based on the determination result. During the frequency self-shifting process, a response-sensitive region and an overshoot suppression region are constructed, and the virtual inertia is adjusted based on the response-sensitive region and the overshoot suppression region. The active power and frequency of the virtual synchronous generator are controlled and adjusted based on the current virtual inertia. This not only achieves dynamic adjustment of the virtual inertia according to the actual operating state, better coping with various complex operating conditions and sudden disturbances, but also balances stability and response speed, so that its stability and response speed can reach the optimal state, providing a strong guarantee for the safe, stable and efficient operation of the power system.

[0020] 2. In the present invention, the second-order oscillation model parameters include the damping coefficient, droop coefficient, and damping coefficient. These three second-order oscillation model parameters are all limited to corresponding ranges. This allows the VSG control system to better simulate the characteristics of synchronous generators, improve the stability and power quality of the power grid, and provide reliable technical support for the large-scale integration of distributed power sources into the grid. Specifically, the range limit for the damping coefficient of the second-order oscillation model helps the system adapt to external changes more quickly and enhances the system's dynamic response capability. The range limits for the damping coefficient and droop coefficient enable the controller to meet regulation requirements under various operating conditions, enhancing the robustness and adaptability of the control.

[0021] 3. In the present invention, a double-layer adaptive inertia control mechanism is utilized to calculate the current virtual inertia based on the deviation value of the angular frequency and the preset deviation value, so that the system can dynamically adapt to frequency changes and dynamically adjust the virtual inertia according to the deviation of the angular frequency. It responds quickly when the frequency deviation is small and adjusts smoothly when the frequency deviation is large, effectively suppressing frequency fluctuations and achieving the best effect in the initial application stage. In addition, by adjusting the amplitude A, width parameter C and sensitivity factor B, the change amplitude and response rate of the virtual inertia can be flexibly controlled, so that the system can achieve optimal dynamic response performance under different working conditions. At the same time, by dynamically adjusting the virtual inertia and angular frequency deviation, a relatively simple control strategy can be implemented, reducing the complexity of the control system and reducing the implementation cost.

[0022] 4. The dual-layer adaptive inertia control mechanism constructed in the present invention includes a control priority adaptive link and a frequency adaptive adjustment link. The control priority adaptive link ensures that when power regulation is the primary focus, a smaller inertia is used to quickly respond to power changes, while when frequency regulation is the primary focus, a larger inertia is used to enhance frequency stability, thereby achieving smooth output of active power. The frequency adaptive adjustment link allows the system to dynamically adjust the virtual inertia according to the amplitude of the frequency deviation, quickly responding to small frequency fluctuations while smoothly adjusting during large frequency deviations, effectively suppressing further frequency changes and allowing the frequency to quickly approach the rated frequency. The dual-layer adaptive inertia control mechanism can adapt to different operating conditions and load characteristics without the need for frequent adjustment of hardware parameters, improving the system's flexibility and adaptability and making it suitable for a variety of complex operating conditions.

[0023] 5. In the present invention, the sensitivity factor B and the preset adjustment factor k The specific settings of the priority are used to realize the priority adaptive process, so that when power regulation is the main focus, the power tracking speed is prioritized. When the frequency deviation is within the medium range, the power and frequency regulation are balanced and overshoot is suppressed. When the frequency deviation is too large, the frequency stability is forced to take priority. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1A schematic diagram of the steps of a virtual synchronous generator adaptive control method in the present invention; Figure 2 2. A topological structure diagram of a grid-type inverter based on a virtual synchronous generator in an embodiment; Figure 3 This is a schematic diagram of the active power-frequency control process in the present invention; Figure 4 This is a structural diagram of a small signal analysis model of a VSG in an embodiment; Figure 5 Schematic diagram of the root locus of the active loop under different J and D in the embodiment; Figure 6 is the adaptive virtual inertia in the embodiment H and ω The relationship curve diagram; Figure 7 It is a system simulation model diagram in the embodiment; Figure 8a Schematic diagram of the change of active power output of the virtual synchronous generator over time in the embodiment; Figure 8b Schematic diagram of the change of reactive power output by the virtual synchronous generator over time in the embodiment; Figure 8c Schematic diagram of power deviation changing with time in the embodiment; Figure 8d Schematic diagram of frequency variation over time in the embodiment; Figure 9 Schematic diagram showing the comparison of changes in the active power output by the VSG in the embodiment; Figure 10 Schematic diagram comparing the changes in VSG output frequency in the embodiment. DETAILED DESCRIPTION

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0026] As a crucial component of the power system, synchronous generators have achieved remarkable results in both theoretical exploration and control design. During grid-connected power generation, they demonstrate unique advantages far exceeding those of distributed generation systems that rely on power electronics. As a key element in traditional power grids, synchronous generators not only effectively cope with fluctuations in grid voltage and frequency, but also feature high output impedance, autonomous synchronization, excellent overload capacity, large moment of inertia, and automatic frequency regulation. Inspired by the shortcomings of existing grid-connected inverters in stability control and their tendency to induce angle oscillations, some researchers have proposed the concept of VSG. This technology incorporates the mechanical rotor equations of the synchronous generator into the inverter to mimic its external operating characteristics, thereby providing virtual inertia support for the inverter system, which is primarily composed of power electronics components, enhancing its control flexibility and improving the stability of grid operation.

[0027] By incorporating a mechanical transient model of synchronous generators into the control loop of grid-connected inverters, VSG technology enables stable grid connection of inverters. Consequently, VSG-based inverters not only distribute power but also regulate frequency and voltage. Their external characteristics are similar to those of traditional synchronous generators, exhibiting the same inertia and damping effects. VSG technology is typically applied to inverter-type distributed power systems. When load fluctuations cause power imbalances, its internal virtual inertia and damping controller effectively mitigate frequency fluctuations. Furthermore, by adjusting the reactive power output deviation, the inverter output voltage can be regulated, thereby enhancing system stability and dynamic response. However, current research has largely focused on simulating the inherent characteristics of synchronous generators, with less attention paid to the potential advantages that inverters offer over synchronous generators. Other researchers have also conducted detailed analyses of the impact of virtual inertia and damping coefficients on system frequency stability control, noting that increasing virtual inertia can reduce frequency overshoot, while increasing the damping coefficient can help accelerate system response to peak value.

[0028] With the widespread application of VSG technology, the functional deficiencies exposed by the traditional VSG method with a fixed inertia constant under complex operating conditions are becoming increasingly prominent. When a lower virtual inertia is used, although the system's transient response is faster, the frequency fluctuation amplitude is large, which is not conducive to stable operation; while choosing a higher virtual inertia will reduce the system's stability margin, resulting in a slower response and longer recovery period when subjected to external disturbances. Therefore, the setting of virtual inertia not only affects the output frequency of the inverter, but also plays an important role in power regulation: fast power regulation requires a smaller inertia, while frequency stability requires a larger inertia. The dual effects of virtual inertia on output power and frequency changes must be comprehensively considered to ensure that the VSG can achieve excellent dynamic response in various operating scenarios and meet diverse operating needs.

[0029] This application proposes a dual adaptive inertia frequency control strategy, significantly improving the dynamic response and steady-state performance of distributed power generation when connected to the grid. When the system encounters sudden load changes or external frequency disturbances, it dynamically adjusts the virtual inertia and damping coefficient using real-time frequency and power data. A control priority mechanism is used to achieve an optimal balance between fast response and steady-state control, effectively reducing frequency overshoot and active power fluctuations.

[0030] Example 1 In this embodiment, a grid-type distributed power adaptive virtual inertia control method based on virtual synchronous generator technology is adopted. The method steps are as follows: Figure 1 As shown, specifically including: S1. Design the parameters of the second-order oscillation model to determine the upper and lower limits of the virtual inertia; S2. Construct a two-layer adaptive inertia control mechanism; S3, real-time monitoring of the frequency, active power and angular frequency of the virtual synchronous generator, and calculation of the deviation values ​​of the three in adjacent preset unit time; S4. When any deviation value exceeds its corresponding preset deviation value, the current virtual inertia is calculated based on the deviation value of the angular frequency and the preset deviation value within the upper and lower limits of the virtual inertia using the dual-layer adaptive inertia control mechanism; S5. Adjust the active power and frequency of the virtual synchronous generator based on the current virtual inertia control.

[0031] This method realizes real-time adjustment of virtual inertia and damping parameters through a dual adaptive control algorithm, solving the problem of insufficient response of traditional fixed inertia VSG technology under load mutation or external frequency disturbance.

[0032] In this embodiment, the topology of the grid-type inverter is first analyzed.

[0033] A typical grid-type inverter topology driven by a virtual synchronous generator is as follows: Figure 2As shown in the figure. The pulse width modulation (PWM) signal required by the inverter is determined by a control unit in conjunction with a reference voltage, and the conduction state of each switching device in the inverter bridge is controlled by a drive circuit. The voltage output by the three-phase bridge leg inverter is used to simulate the internal electromotive force of the synchronous generator. An inductor-capacitor (LC) filter network is connected to the AC output side of the inverter. The filtered output voltage is used to reproduce the terminal voltage characteristics of the synchronous generator, thereby achieving the effect of a virtual synchronous generator. By introducing a transient model of the mechanical rotation of the synchronous motor into the control loop of the grid-connected inverter, the VSG can ensure stable grid connection of the inverter power supply; therefore, its external characteristics exhibit inertia and damping similar to those of a traditional synchronous generator set, which can be used for power distribution and frequency and voltage regulation in the system.

[0034] A speed regulator is used in VSG control to simulate the frequency regulation characteristics of a synchronous generator. The speed regulator is the droop characteristic between active power and frequency, as shown in the following formula: Where, P m represents the mechanical power of the synchronous generator; P ref is the reference active power; k p is the active power-frequency droop coefficient; ω 0 is the rated angular frequency; ω is the angular frequency at the VSG output.

[0035] In this embodiment, in order to provide frequency support, suppress power oscillation, and accelerate the recovery of steady state when the system is disturbed, virtual inertia and damping are further added, that is, the rotor motion equation of the synchronous generator is simulated, as shown in the following equation: Where, J is the virtual moment of inertia in inverter control; T m is the mechanical torque; T e is the electromagnetic torque; ω 0 is the rated angular frequency; P ref is the reference active power; k p is the active power-frequency droop coefficient; D is the virtual damping torque in inverter control; P mIt is the active power output from the inverter port, which is equivalent to the mechanical power of the virtual synchronous generator; ω is the angular frequency at the VSG output; ω s Referenced to the angular frequency at the point of common coupling.

[0036] The active power-frequency control of the VSG controller is as follows Figure 3 As shown in the figure, when VSG is connected to the grid, the frequency regulation item in the droop control is mainly used. k p ( ω - ω s ) tracks the grid frequency and keeps synchronization with it, thereby achieving inverter-side frequency control.

[0037] In the above formula J Indicates the virtual inertia constant of the virtual synchronous generator, and its corresponding inertia time constant reflects the size of the "virtual mechanical inertia" exhibited by the VSG during the adjustment process. H and J Essentially describing the same physical quantity, the two can be converted to each other through mathematical relationships. In traditional synchronous generators, the moment of inertia is determined by factors such as the generator's physical size and mass, and is used to characterize the rotor's response to changes in external torque. In VSG control systems, the inertia constant serves as an adjustable virtual control parameter whose value can be flexibly set according to system requirements, taking the form of a fixed value or a time-varying function. Compared to actual mechanical inertia, this virtual inertia has a wider range of values ​​and better regulation performance, enabling grid-connected inverters to provide effective inertia support.

[0038] In this embodiment, the inertia and damping characteristics of the VSG are analyzed next.

[0039] The moment of inertia of a synchronous generator is an important physical parameter that is closely related to the size of the generator. Its value usually increases with the increase of rated power. In order to compare models of different sizes and power levels, virtual inertia is often used. H As an evaluation index of rotational inertia. H Defined as: Where, H is the virtual inertia; S n is the rated capacity of VSG; J is the virtual moment of inertia in inverter control; ω 0 is the rated angular frequency.

[0040] make ωr = ( ω - ω 0 ) / ω 0 , we can get: Where, ω r is the per-unit angular frequency deviation; ω 0 is the rated angular frequency; ω is the angular frequency at the VSG output.

[0041] Let the rated active power be the rated capacity of VSG, that is S n = P n , and obtain the reference value of VSG torque: Where, T B is the reference value of VSG torque; P n is the rated active power; S n is the rated capacity of VSG; ω 0 is the rated angular frequency.

[0042] From the above two equations and the rotor motion equation of the simulated synchronous generator, we can get: Where, T m * and T e * They are T m and T e The per-unit value of ω r is the per-unit angular frequency deviation; D is the virtual damping torque in inverter control; D p is the normalized damping torque coefficient; ω 0 is the rated angular frequency; S n is the rated capacity of VSG; H is the virtual inertia.

[0043] Since the angle between the voltage at the VSG port after grid connection and the grid connection voltage after passing through the LC filter is very small, it can be considered that sin δ = δ Therefore, the small signal analysis model of VSG can be obtained as Figure 4 shown.

[0044] Figure 4 In the VSG input P m * , output P e * The response characteristics are in line with the typical second-order transfer function, namely: Where, G ( s ) is the transfer function; P e * and P m * are the per-unit values ​​of electromagnetic power and mechanical power respectively; ω 0 is the rated angular frequency; H is the virtual inertia; D p is the normalized damping torque coefficient; S E It is the benchmark capacity related to electromagnetic power.

[0045] In this embodiment, S n It is related to the reference setting of active power and reactive power. When the power setting value is constant, S n is a constant. The damping coefficient and natural oscillation angular frequency of the second-order oscillation model can be obtained from the above formula: Where, ω n is the natural oscillation angular frequency; ξ is the damping coefficient; S E is the reference capacity related to electromagnetic power; H is the virtual inertia; ω 0 is the rated angular frequency; D p is the normalized damping torque coefficient.

[0046] According to the above relationship, the active loop root locus diagram can be made as follows: Figure 5 As shown, Figure 5 In the figure, the green line is the root locus of the first conjugate root of the second-order oscillation model. The blue line is the root locus of the second conjugate root of the second-order oscillation model. As the system gain changes, the closed-loop poles move from the open-loop pole positions along a circular arc toward the imaginary axis, symmetrically distributed on both sides of the positive and negative imaginary axes. This indicates that the system is stable.

[0047] Based on the theory of "optimal second-order oscillation model", including Pontryagin minimum principle, optimal damping ratio, Hamiltonian function method and linear quadratic optimal control theory, in the process of adjusting the damping parameters, the damping ratio of the system is defined as ξ =0.707 can obtain better adjustment performance, that is, the damping parameter can be selected as: Where, D p is the normalized damping torque coefficient; ω 0 is the rated angular frequency; S E is the reference capacity related to electromagnetic power; H is the virtual inertia.

[0048] From the above formula we can get: Where, D is the virtual damping torque in inverter control; S n is the rated capacity of VSG; ω 0 is the rated angular frequency; S E is the electromagnetic related capacity; H is the virtual inertia.

[0049] From the above formula we can get: Where, ω n is the natural oscillation angular frequency; S n is the rated capacity of VSG; ω 0 is the rated angular frequency; S E * is the normalized electromagnetic related capacity; J is the virtual moment of inertia in inverter control.

[0050] When the load changes dramatically, the moment of inertia can slow down the rate of change of the output frequency, allowing the system to gradually approach a new equilibrium state. The larger the moment of inertia, the slower the frequency adjustment, thus extending the time it takes for the system to reach a steady state. At the same time, the damping coefficient D It helps to limit the amplitude of frequency fluctuation and reduce the impact of sudden load change. J Increase, such as Figure 5 As shown in the figure, the real parts of the characteristic roots s1 and s2 of the second-order oscillation model gradually approach zero, which means that the two poles gradually move toward the imaginary axis, thereby reducing the response speed of the system; and the damping value decreases with the increase of J, which leads to a decrease in the dynamic performance and stability of the system.

[0051] In this embodiment, the dual adaptive inertia control strategy optimization is performed next.

[0052] 3.1 Adaptive Inertia Implementation Method In VSG systems, there is an inherent trade-off between active power and frequency regulation capability: when external disturbances cause a sharp change in frequency, it is desirable to increase the active power and frequency regulation capability. H value to reduce the frequency deviation, thereby slowing down the frequency fluctuation; and when the active power reference value changes suddenly, it is necessary to reduce H value to reduce the deviation of active output and make power adjustment more stable. H It is difficult for the value to meet the requirements of different working scenarios at the same time, which requires the design of a control strategy that can adaptively adjust the inertia constant to cope with diverse operating conditions.

[0053] Based on the above considerations, this scheme proposes a two-layer adaptive inertia control mechanism, the basic idea of ​​which can be summarized as follows: (1) When power regulation is the main purpose, use a smaller inertia; (2) When frequency regulation is the main purpose, a larger inertia is selected.

[0054] In addition, the algorithm will make adaptive adjustments based on the amplitude of the frequency fluctuation: when the fluctuation amplitude is small, the control strategy prioritizes fast response to quickly suppress the impact of external disturbances; when the fluctuation amplitude is large, it focuses on balancing overshoot, that is, allowing the response speed to be appropriately reduced to achieve smooth control.

[0055] The main functions of the adaptive inertia control algorithm are: control priority adaptation and frequency offset adaptation. Figure 6 As shown, the adaptive control virtual inertia H and ω The functional relationship can be expressed as: Where, A andC They are the adjustment amplitude and width parameters, which are used to control the maximum change amplitude of the virtual inertia and the width of the response curve; B It is the sensitivity factor of adaptive control, used to adjust the virtual inertia H The rate of response; H 0 is the virtual inertia reference value; ω is the angular frequency at the VSG output; ω ref is the reference angular frequency.

[0056] In order to make the designed VSG algorithm adapt to different operating conditions, the expression of the sensitivity coefficient B in adaptive control is: Among them, the parameters k It is a preset adjustment factor used to measure the importance of frequency deviation. The larger its value is, the more significant the deviation of the current output frequency of the system from the expected value is, and therefore frequency control needs to be prioritized. k It can be used as a basis for dynamically adjusting the control weight. In the case of significant output frequency deviation, the control variable B Increase, making the system control trajectory closer to the frequency regulation curve; on the contrary, when the active power deviates significantly, B The virtual inertia approaches its minimum during the entire regulation process, improving the rapid response of power output, reducing system overshoot, and optimizing dynamic performance. This shows that in actual control strategies, the system can not only adjust the output path horizontally but also dynamically assign control priorities vertically to achieve coordinated management of frequency and power.

[0057] Preset adjustment factor k according to Change and change; when When the preset adjustment factor gives priority to ensuring the power tracking speed; when When the preset adjustment factor is used to balance power regulation and frequency regulation; when When , the preset adjustment factor is used to force frequency stability to take priority. The specific formula of the preset adjustment factor is: ; Among them, 0.5 is the linear gain coefficient, ensuring that under small deviations k Slowly increasing; ; in, is the differential gain, which suppresses overshoot. In this critical case, use tanh function, so that the method can smoothly transition from the case of small frequency deviation to the case of large frequency deviation; ; Among them, 5 is the exponential decay rate, which enhances the steady-state regulation accuracy.

[0058] in, is the baseline sensitivity; is the intermediate gain coefficient; is the maximum sensitivity threshold.

[0059] 1) Adaptive adjustment of offset like Figure 6 As shown in the figure, when the system is disturbed by external factors and the frequency deviates from its stable operating point, if the deviation is small, the system enters the sensitive response area and can respond quickly to suppress the influence of the disturbance; on the contrary, if the deviation is large, the system enters the overshoot suppression area, at which time the VSG output frequency remains relatively stable and gradually adjusts to the sensitive response area to achieve rapid response. Considering the extreme case, when the frequency offset is infinite, the virtual inertia tends to H 0+ A / 2 C , H 0+ A / 2 C is the baseline virtual inertia constant, which represents the adaptive virtual inertia value when the frequency deviation of the overall system is 0; when the VSG output frequency has no deviation, the virtual inertia constant used by the control algorithm is H 0, so A 、 C and H 0 is an important factor in determining the upper and lower limits of the entire adaptive virtual inertia adjustment. In addition, ω When changes occur, the virtual inertia always maintains a positive value, thereby ensuring that the damping of the control system is always positive and making all characteristic roots located on the left side of the imaginary axis, thus ensuring the stability of the system during the adjustment process.

[0060] 3.2 Adaptive inertia range regulations In the VSG algorithm, the constant H As an important parameter of virtual inertia, its numerical range directly determines the system control time domain and has a significant impact on the output performance of the power grid. Next, this section introduces in detail the parameter selection method in the VSG control system. By designing the parameters of the second-order oscillation model (i.e., the damping coefficient ζ , droop coefficient D and damping coefficient k ) Determine the virtual inertia H Upper and lower limits H h and H 0。

[0061] 1) Damping coefficient of the second-order oscillation model ζ From the above analysis, we can see that the VSG control system is a typical second-order oscillation model, and its damping coefficient ζ The expression is: Where, ζ is the damping coefficient; H is the virtual inertia; μ is the damping coefficient; λ It is the partial derivative of the active output with respect to the output voltage parameter at the reference active and reactive power points. After the impact comes, in order to make the transient response of the system quickly reach the expected stable value, the system overshoot should be limited and the adjustment time should be kept short. ζ It should be 0.2-0.8, that is: In this case, due to the low damping of the system, its output response gradually shows the characteristics of oscillation attenuation over time.

[0062] 2) Droop coefficient D Droop coefficient D It reflects the gradient of change between active power and frequency, and reactive power and voltage. Specifically, the active power droop coefficient describes the adjustment amplitude of the inverter output active power for every 1Hz change in frequency; the reactive power droop coefficient indicates the corresponding change in reactive power for every 1kV change in output voltage amplitude. When selecting the droop coefficient, reference should be made to the relevant standards of the power grid. Because it reflects the gradient of change between active power and frequency, and reactive power and voltage, a reasonable range limitation can ensure that the VSG matches the frequency and voltage changes of the power grid when outputting active power and reactive power, thereby improving the compatibility and stability of the VSG and the power grid, and ensuring the reliable operation of the power system.

[0063] The reciprocal of the droop coefficient is of the same order of magnitude as the damping coefficient, that is, the droop coefficient and the damping coefficient satisfy the following formula: 1 / D =a· k Where, D is the droop coefficient; k is the damping coefficient; a is a constant, which is less than 10 and greater than 1 / 10.

[0064] 3) Damping coefficient k When VSG is in grid-connected mode and operates stably, ω ref = ω grid , a frequency modulation term ( ωref - ω grid ) / D is zero, and only the damping term k ( ω - ω grid ) determines the active power control signal. However, in actual operation, when the system is disturbed, the grid frequency and the reference frequency are often inconsistent, so that the primary frequency regulation and the damping term are not zero, and jointly affect the active power control signal. In order to make the controller meet the regulation requirements under various working conditions, the damping coefficient should be selected to ensure that 1 / D and k The magnitudes of the two are similar, so that they play similar roles in generating active power control signals.

[0065] Finally, the active power and frequency of the virtual synchronous generator are adjusted based on the current virtual inertia control. The specific process is as follows: the virtual moment of inertia is calculated using the current virtual inertia. Combined with the rotor motion equation, the virtual torque required to resist frequency changes is further calculated. By controlling the inverter output, the current electromagnetic torque is adjusted to the required virtual torque, and the output frequency of the virtual synchronous generator is adjusted to approach the rated frequency, suppressing frequency fluctuations. This effectively enhances the frequency stability and active power regulation capability of the virtual synchronous generator, improving the system's flexibility, stability, and control accuracy, while reducing hardware loss and failure risks, and improving the overall system performance and reliability.

[0066] Example 2 In this embodiment, an adaptive control system of a virtual synchronous generator is applied. The system operates by applying the adaptive control method of a virtual synchronous generator in Example 1. The system includes a system parameter design module, a control algorithm construction module, a real-time monitoring module, a virtual inertia calculation module, and a control and adjustment module. The parameter design module is used to design the parameters of the second-order oscillation model to determine the upper and lower limits of the virtual inertia; The control algorithm building module is used to build a two-layer adaptive inertia control mechanism; The real-time monitoring module is used to monitor the frequency and active power of the virtual synchronous generator in real time, and the deviation values ​​of frequency, active power and angular frequency within the adjacent preset unit time in real time; The virtual inertia calculation module is used to calculate the current virtual inertia based on the angular frequency deviation and the preset deviation value within the upper and lower limits of the virtual inertia using a double-layer adaptive inertia control mechanism when any deviation value exceeds its corresponding preset deviation value; The control and regulation module is used to control and regulate the active power and frequency of the virtual synchronous generator based on the current virtual inertia.

[0067] In this embodiment, a simulation verification of the example is performed. Specifically, a system is built in the simulation system for simulation verification. Figure 7 As shown in Figure 1, the rotor mechanical equation adopts a double-layer adaptive control strategy. The simulation parameters are shown in Table 1. The upper and lower limits of the double-layer adaptive control inertia are selected as 1 and 0.1. is -9, is 1, is 5.

[0068] Table 1 System parameters In the simulation experiment, the control effect of the VSG system when it encounters a sudden change in the active power reference value and a grid frequency disturbance in the grid-connected operation state is simulated. Specifically, after the system has been running stably for 2 seconds, the grid frequency oscillates by -0.5Hz due to external interference. The disturbance disappears after 0.05 seconds. When the system returns to stability and runs for 4 seconds, the active power reference value output by the VSG jumps from 25kW to 40kW. Figure 8 shows the changes in various output variables under adaptive inertia control; among them, Figure 8a The figure shows the change of active power output of virtual synchronous generator over time. Figure 8b This is a diagram showing how the reactive power output of the virtual synchronous generator changes over time. Figure 8c The power deviation changes with time. Figure 8d It shows the frequency changing with time; Figure 9 The dynamic changes in active power output under the fixed virtual inertia constant control strategy and the adaptive inertia control strategy are compared. The red line shows the dynamic changes in active power output under the fixed virtual inertia constant control strategy, and the blue line shows the dynamic changes in active power output under the adaptive inertia control strategy. Figure 10 The figure shows a comparison of the frequency output under the two control strategies; the red line represents the dynamic change of the frequency output under the fixed virtual inertia constant control strategy, and the blue line represents the dynamic change of the frequency output under the adaptive inertia control strategy.

[0069] From Figure 8, Figure 9 and Figure 10It can be seen that when the frequency and active power reference values ​​undergo sudden changes, the system will oscillate. Due to inertia, the frequency eventually stabilizes and returns to its original state after oscillation, and the output active power quickly adjusts to the new stable value. Compared with the VSG control algorithm using a fixed virtual inertia constant, the adaptive control algorithm reduces frequency overshoot and takes less time to reach a stable state, resulting in a more stable system output. In terms of power variation, although the active output overshoot is slightly larger, it recovers quickly and the increase in overshoot is not significant, thus achieving a more stable output. Furthermore, the VSG using dual-layer adaptive inertia control has a faster response speed, achieving a new stable state in a very short time.

[0070] In summary, under the premise of reasonable selection of the damping coefficient, the double-layer adaptive inertia control strategy can not only take into account the stability of the system output, but also improve the dynamic response speed, and effectively improve the operating performance of the system under different working conditions.

[0071] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. An adaptive control method for a virtual synchronous generator, characterized in that: In this method, a two-layer adaptive inertia control mechanism is used to adaptively control the virtual inertia; The two-layer mechanism includes: a control priority adaptive link and a frequency adaptive adjustment link; In the control priority adaptation link, power regulation priority or frequency regulation priority is determined according to the current dominant regulation mode, and the virtual inertia is dynamically adjusted through the sensitivity factor; In the frequency adaptive adjustment link, the sensitive area gain term, the offset suppression term and the reference inertia compensation are comprehensively used to establish a response sensitive area and an overshoot suppression area, and the virtual inertia is adjusted based on these two areas.

2. The adaptive control method of a virtual synchronous generator according to claim 1, characterized in that: The method comprises the following steps: S1. Design the parameters of the second-order oscillation model to determine the upper and lower limits of the virtual inertia; S2. Constructing a dual-layer adaptive inertia control mechanism, which includes a control priority adaptive link and a frequency adaptive adjustment link; S3, real-time monitoring of the frequency, active power and angular frequency of the virtual synchronous generator, and calculation of the deviation values ​​of the three in adjacent preset unit time; S4. When any deviation value exceeds its corresponding preset deviation value, the current virtual inertia is calculated based on the deviation value of the angular frequency and the preset deviation value within the upper and lower limits of the virtual inertia using the dual-layer adaptive inertia control mechanism; S5. Adjust the active power and frequency of the virtual synchronous generator based on the current virtual inertia control.

3. The adaptive control method of a virtual synchronous generator according to claim 2, characterized in that: The second-order oscillation model parameters in S1 include the second-order oscillation model damping coefficient 、 Droop coefficient and damping coefficient; the damping coefficient of the second-order oscillation model satisfies the following formula: ； ； Where, ζ is the damping coefficient; H is the virtual inertia; μ is the damping coefficient; λ It is the partial derivative of the active output with respect to the output voltage parameter at the reference active and reactive power points.

4. The adaptive control method of a virtual synchronous generator according to claim 3, characterized in that: The reciprocal of the droop coefficient is of the same order of magnitude as the damping coefficient, that is, the droop coefficient and the damping coefficient satisfy the following formula: 1 / D =a· k ； Where, D is the droop coefficient; k is the damping coefficient; a is a constant, which is less than 10 and greater than 1 / 10.

5. The adaptive control method of a virtual synchronous generator according to claim 2, characterized in that: The specific process of the control priority adaptation link is: when the power oscillation value is greater than the frequency oscillation value, that is, when power regulation is mainly used, the virtual inertia is reduced; otherwise, the virtual inertia is increased to strengthen the frequency support.

6. The adaptive control method of a virtual synchronous generator according to claim 5, characterized in that: The specific process of the frequency adaptive adjustment link is as follows: when the system is subjected to external interference and causes the frequency to deviate from its stable operating point, if the deviation amplitude is lower than the preset deviation amplitude, the system enters the response-sensitive area, that is, the virtual inertia is adaptively adjusted with the change of frequency; conversely, if the deviation amplitude is higher than the preset deviation amplitude, the system enters the overshoot suppression area, that is, the virtual inertia does not change with the change of frequency. At this time, the output frequency of the virtual synchronous generator remains stable and is gradually adjusted until it reaches the response-sensitive area.

7. The adaptive control method of a virtual synchronous generator according to claim 6, characterized in that: In the above S4, the current virtual inertia calculated based on the deviation value of the angular frequency and the preset deviation includes the sensitive area gain term, the offset suppression term and the reference inertia compensation, thereby realizing the frequency adaptive adjustment link. The specific formula is: ； Where, H is the virtual inertia; A is Adjust the amplitude parameter to control the maximum change amplitude of virtual inertia; C The response bandwidth parameter is used to define the width of the response curve of the virtual inertia. B It is the sensitivity factor of adaptive control, used to adjust the virtual inertia H The rate of response; H 0 is the virtual inertia reference value; ω is the angular frequency at the VSG output; ω ref is the reference angular frequency; when When the deviation is less than the preset value, the virtual inertia is dominated by the sensitive zone gain term, and the sensitivity of the virtual inertia to small frequency deviations is dynamically changed by adjusting the adaptive control sensitivity factor; when When the value is greater than or equal to the preset deviation value, the virtual inertia is controlled by the offset suppression term. At this time, the offset suppression term controls the virtual inertia gain to reduce, avoiding phase lag caused by excessive virtual inertia.

8. The adaptive control method of a virtual synchronous generator according to claim 7, characterized in that: In the above S4, when calculating the current virtual inertia, the sensitivity factor of the adaptive control is used B , in order to complete the control priority adaptive link, the sensitivity factor of adaptive control B The specific formula is: ； Among them, the parameters k It is a preset adjustment factor used to measure the importance attached to frequency deviation; k The larger the value of , the more significant the deviation of the current output frequency of the system from the expected value, thus giving priority to frequency control; the numerator reflects the square characteristic of the frequency offset and is used to enhance the sensitivity under large deviation conditions.

9. The adaptive control method of a virtual synchronous generator according to claim 8, characterized in that: The preset adjustment factor k according to Change and change; when When the preset adjustment factor gives priority to ensuring the power tracking speed; when When the preset adjustment factor is used to balance power regulation and frequency regulation; when When , the preset adjustment factor is used to force frequency stability to take priority. The specific formula of the preset adjustment factor is: ； ； ； in, is the baseline sensitivity; is the intermediate gain coefficient; is the maximum sensitivity threshold.

10. The adaptive control method of a virtual synchronous generator according to claim 9, characterized in that: The specific process of controlling and adjusting the active power and frequency of the virtual synchronous generator based on the current virtual inertia in S5 is as follows: using the current virtual inertia to calculate the virtual rotational inertia, combining it with the rotor motion equation, further calculating the virtual torque required to resist the frequency change, and controlling the inverter output to adjust the current electromagnetic torque to the required virtual compensation torque ∆T. The PWM modulator adjusts the inverter bridge arm conduction timing so that the output electromagnetic torque tracks ∆T, and then adjusts the output frequency of the virtual synchronous generator to make it close to the rated frequency, thereby suppressing frequency fluctuations.

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