Method for inhibiting power interactive oscillation caused by impact load through inertia self-adaption

Abstract

The invention discloses a method for adaptively suppressing power interactive oscillation caused by an impact load through inertia. The method comprises the following steps: S1, establishing a sparse communication network; s2, each VSG control inverter respectively measures the output frequency of the VSG control inverter, a frequency second derivative SDFD and the output frequency difference value of each neighbor node; s3, determining respective virtual rotational inertia control targets; s4, determining the value range of the virtual rotational inertia and the setting rule of the damping coefficient; s5, suppressing power interaction oscillation; the method can be directly applied to a multi-machine parallel VSG control system without modifying or additionally installing power equipment; the SDFD measurement method is adopted to solve the problems that the frequency change of the OCOF is delayed due to system inertia, and the robustness of the system is reduced at the same time; a self-adaptive virtual rotational inertia control strategy based on a multi-agent theory is provided, and active power oscillation is effectively suppressed.

Description

Technical Field

[0001] This invention relates to the field of electrical engineering technology, specifically to a method for adaptively suppressing power oscillations caused by impact loads. Background Technology

[0002] Virtual synchronous generator (VSG) technology simulates the external characteristics of a synchronous generator, enabling inverter-type power electronic devices to possess the inertia and damping of a traditional synchronous generator, thereby significantly improving the system's frequency and voltage regulation capabilities. However, in actual engineering events, due to objective limitations, it is difficult to maintain the internal and external characteristics of VSGs operating in a multi-machine parallel system completely consistent. When subjected to impact loads, the angular acceleration generated by each VSG will be different, resulting in different dynamic response angular velocities. This leads to frequency oscillations in the parallel operation of VSGs, which in turn causes active power oscillations.

[0003] Impact loads are characterized by rapid, large-amplitude, and short-duration power changes, causing a rapid drop in frequency and making the frequency change nonlinear. While there has been considerable research on single-unit VSG oscillations, less attention has been paid to the interactive oscillations and influences between VSGs. In practical engineering, parallel operation of multiple units is more in line with the current demand for large-scale, high-proportion renewable energy grid connection and off-grid deployment, but certain unresolved issues remain.

[0004] First, in power systems with a large proportion of renewable energy connected to the grid, multi-machine parallel VSG control systems are widely used. However, the frequent switching of impact loads can easily cause active power interaction oscillations, which seriously threaten system stability. In existing technologies, some power oscillation suppression schemes require the modification or addition of power equipment, which has poor adaptability to existing multi-machine parallel VSG control systems and is difficult to apply directly. In the complex scenario of new energy power systems, it is difficult to effectively cope with the power oscillation challenges brought by impact loads.

[0005] Secondly, in the inertia control stage of the VSG control system, the dynamic changes of the system frequency are usually sensed by measuring ROCOF. However, due to the existence of system inertia, ROCOF measurement has an inherent delay and is easily affected by noise or small disturbances, which can cause the system measurement tool to misjudge the operating status, reduce the robustness of the system, and thus affect the accuracy of virtual rotational inertia control, making it impossible for inertia adjustment to respond to frequency changes caused by impact loads in a timely and accurate manner.

[0006] Furthermore, for inertia control strategies in multi-machine parallel VSG systems, most existing technologies adopt centralized control architectures or fixed virtual rotational inertia schemes. Centralized control architectures rely on a central controller, and if the central controller fails, the inertia adjustment of the entire system will not be able to proceed normally, resulting in insufficient reliability. In addition, centralized communication architectures have a heavy communication burden in multi-machine scenarios. Fixed virtual rotational inertia is difficult to adaptively adjust according to the dynamic changes of impact loads, and has limited effect on suppressing power interaction oscillations. At the same time, the inertia coordination between multiple machines lacks an efficient distributed mechanism, resulting in poor system scalability and difficulty in adapting to the scale changes and complex operating conditions of multi-machine parallel VSG systems.

[0007] Therefore, it is necessary to design an inertia adaptive method to suppress power interaction oscillations caused by impact loads. Summary of the Invention

[0008] The purpose of this invention is to provide an inertia adaptive method for suppressing power interaction oscillations caused by impact loads, thereby solving the problems of poor adaptability of existing solutions in the background art to multi-machine parallel VSG control systems and difficulty in directly dealing with active power interaction oscillations caused by impact loads; solving the problem of misjudgment and reduced system robustness caused by system inertia delay and susceptibility to noise interference when measuring ROCOF; and simultaneously solving the problems of insufficient reliability of existing inertia control strategies using centralized architecture or difficulty in adaptively adjusting fixed inertia, limited oscillation suppression effect and poor system scalability.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a method for adaptively suppressing power oscillations caused by impact loads, comprising the following steps:

[0010] S1: For the VSG control system of multiple parallel VSGs in an AC microgrid, a sparse communication network is established between each VSG control inverter. The sparse communication network provides a transmission channel for information interaction between each VSG control inverter. The sparse communication network adopts a point-to-point or bus topology structure, which can be flexibly configured according to the scale of the microgrid and the distribution of nodes to ensure the real-time performance and reliability of information transmission and provide timely status feedback for subsequent distributed inertia adaptive control.

[0011] S2: Based on the sparse communication network established in S1, each VSG-controlled inverter acts as an independent node, measuring its own output frequency and second frequency derivative (SDFD). It communicates with neighboring nodes through this sparse communication network to obtain the output frequencies of neighboring nodes and calculates the output frequency difference between itself and each neighboring node. The measurement of the second frequency derivative (SDFD) can be achieved by performing a second differential operation on the output frequency signal, which can effectively identify the rapid frequency change trend when impact loads are applied or removed. When calculating the output frequency difference, a sliding window method or an instantaneous difference method is used to ensure the timeliness of the frequency difference data, providing an accurate dynamic excitation signal for the adaptive adjustment of inertia in S3.

[0012] S3: An improved inertia adaptive control strategy is constructed based on multi-agent theory. Each VSG control inverter calls the output frequency difference between itself and its neighboring nodes and its own frequency second derivative SDFD obtained from S2. Through distributed control logic and virtual rotational inertia control formula, it determines its own virtual rotational inertia control target. The application of multi-agent theory enables each VSG control inverter to act as an agent and autonomously coordinate the inertia adjustment strategy without a central controller. The distributed control logic avoids the single-point failure risk of centralized control through local calculation and neighbor information interaction. The virtual rotational inertia control formula realizes the adaptive change of inertia with the system oscillation state, effectively suppressing the power interaction oscillation caused by impact load.

[0013] S4: Determine the virtual moment of inertia based on the rotor motion equations of VSG control and the virtual moment of inertia control formula in S3. The range of values ​​and damping coefficient The tuning rules; the rotor motion equation of VSG control is the core equation for simulating the rotor motion characteristics of a synchronous generator. Through it, a quantitative relationship between inertia, damping, and system frequency dynamics can be established; the virtual moment of inertia can be determined. The range of values ​​and damping coefficient The tuning rules are based on the stability criteria of linearized systems, ensuring that under impact load disturbances, the dynamic response of the system will not oscillate and diverge due to insufficient inertia, nor will it be slow to respond due to excessive inertia. The tuning of the damping coefficient balances the oscillation decay rate and steady-state error of the system.

[0014] S5: Substitute the virtual moment of inertia control target determined in S3 into the rotor motion equation corresponding to S4, and combine the VSG reactive power control equation and active power regulation equation to solve for the effective voltage value and output frequency; perform dq transformation on the effective voltage value and output frequency to obtain the three-phase AC voltage waveform, modulate the three-phase AC voltage waveform into a three-phase PWM switching control signal, and apply the three-phase PWM switching control signal to each VSG control converter to achieve power interaction oscillation suppression; the dq transformation converts the three-phase AC quantity into DC direct-axis d-axis and quadrature-axis q-axis components, which facilitates the use of mature DC control strategies to achieve precise regulation of voltage and frequency; the generation of the three-phase PWM switching control signal follows the sinusoidal pulse width modulation principle, and by adjusting the switching duty cycle, the VSG control converter outputs a three-phase AC voltage waveform that meets the requirements, thereby converting the inertia adaptive control strategy determined in S3 and S4 into actual power output, and finally achieving power interaction oscillation suppression caused by impact load.

[0015] As a further technical solution of the present invention, in S1, the nodes of the sparse communication network are each VSG control inverter in the multi-machine parallel VSG control system. When a communication connection is established between two nodes, the two nodes are neighbor nodes to each other. The number of neighbor nodes can be set according to the system redundancy and communication bandwidth requirements.

[0016] As a further technical solution of the present invention, in S1, the content of the information interaction includes the output frequency data of each VSG control inverter.

[0017] As a further technical solution of the present invention, in step S2, the calculation method of the output frequency difference is as follows: taking the output frequency of the current node as a reference, the difference is calculated with the output frequency of each neighboring node to obtain multiple one-to-one corresponding frequency difference values; the calculation period of the frequency difference is synchronized with the system sampling period to ensure that the frequency transients caused by the impact load can be captured in time, and to provide a fast excitation input for inertia adjustment.

[0018] As a further technical solution of the present invention, the virtual moment of inertia control formula in S3 is as follows:

[0019]

[0020] in, The virtual inertia of the i-th VSG-controlled inverter in steady state; Let i be the output angular velocity of the i-th VSG control inverter; Let j be the output angular velocity of the VSG-controlled inverter; This is the inertia adjustment coefficient; This represents the neighborhood set of the neighboring nodes of the i-th VSG-controlled inverter; This refers to the communication weighting coefficient. This is the coefficient for the direction of change of the virtual moment of inertia; Let be the first-order frequency derivative of the i-th VSG-controlled inverter; SDFD is the second frequency derivative of the i-th VSG-controlled inverter; in the formula function based on The sign of the inertia determines the direction of inertia adjustment. When the rate of change of frequency and the acceleration of frequency change have the same sign, it indicates that the system oscillation has a tendency to intensify. This tendency can be effectively suppressed by adjusting the inertia. The value of needs to take into account the dynamic response speed and steady-state accuracy of the system. In practical applications, it can be optimized through offline simulation or online adaptive algorithms.

[0021] As a further technical solution of the present invention, in S4, the rotor motion equation controlled by VSG is as follows:

[0022]

[0023] In S5, the VSG reactive power control equation is as follows:

[0024]

[0025] The corresponding VSG active power regulation equation is as follows:

[0026]

[0027] in, This is the active power droop coefficient; This is the reactive power droop coefficient; The mechanical power of the VSG; Q is the given reference power; Q is the output reactive power. Given reactive power; and These are the output angular frequency and rated angular frequency of the VSG, respectively; E and These are the output voltage amplitude and rated voltage amplitude of the VSG, respectively; The active power output of the VSG is J; the virtual moment of inertia is D; and the damping coefficient is D. The grid-side angular frequency is given. The active power regulation equation of the VSG simulates the speed regulation characteristics of a synchronous generator, and the reactive power control equation simulates the excitation regulation characteristics. Together with the rotor motion equation, they constitute the electromechanical transient model of the VSG, providing a physically equivalent control framework for inertia adaptive control. This enables the inverter to have inertia and damping characteristics similar to those of a synchronous generator, thus effectively participating in the suppression of power oscillations in a microgrid.

[0028] As a further technical solution of the present invention, in S4, the virtual moment of inertia The range of values ​​for is determined by the following formula:

[0029]

[0030] Substituting the above formula into the rotor motion equation of claim 6 and linearizing it, we get:

[0031]

[0032] Based on traditional control theory, the damping ratio of a second-order system The calculation formula is:

[0033]

[0034] Set damping ratio The value range is [0.1, 1.414], and Approaching 1, we obtain the upper and lower limits of the virtual moment of inertia:

[0035]

[0036] in, Let be the steady-state phase angle difference between the output voltage of the i-th VSG and the voltage at the point of common coupling; Let i be the output voltage amplitude of the i-th VSG; This refers to the voltage amplitude at the point of common coupling. Let be the equivalent reactance of the i-th VSG; the linearized rotor motion equation is a second-order system with a damping ratio of It is a key indicator for measuring the oscillation damping characteristics of a system, and is achieved through tuning. and By keeping the damping ratio within a reasonable range, the system can be guaranteed to have good dynamic stability under impact loads, which can both quickly dampen oscillations and maintain the stability of frequency and voltage.

[0037] As a further technical solution of the present invention, in S4, the damping coefficient The tuning must meet the following conditions:

[0038]

[0039] in, and These are the maximum and minimum angular frequencies allowed by the system, respectively. The maximum power that the i-th VSG can withstand; The minimum output power of the i-th VSG under the support of the energy storage device; this setting condition is based on the constraints of the system power regulation range and frequency regulation range, ensuring that the frequency fluctuation of the VSG will not exceed the allowable range within the maximum and minimum power output range, while providing sufficient damping support for the power sudden change of the impact load to avoid the continuous expansion of frequency oscillation.

[0040] As a further technical solution of the present invention, in S1, the multi-machine parallel VSG control system includes two types: grid-connected multi-machine parallel VSG control system and islanded multi-machine parallel VSG control system. In the grid-connected multi-machine parallel VSG control system, this strategy can work in conjunction with the inertia characteristics of the power grid to enhance the overall system's resistance to shocks. In the islanded multi-machine parallel VSG control system, this strategy is a key means to maintain system frequency stability and can effectively avoid system collapse caused by power oscillations in islanded scenarios with frequent impact loads.

[0041] As a further technical solution of the present invention, in S5, the dq transformation is to convert the voltage signal in the three-phase stationary coordinate system into the direct-axis and quadrature-axis voltage signals in the two-phase rotating coordinate system; the three-phase PWM switching control signal is generated by sinusoidal pulse width modulation technology and is used to drive the switching devices of the VSG control converter to operate; and the inertia adjustment coefficient in S3 Adjustments are made based on the actual measured second derivative SDFD of the frequency to ensure the virtual moment of inertia. Falling within the scope defined in claim 7 and Between; the rotating coordinate system of the dq transformation is based on the synchronous rotational angular velocity of the VSG output voltage, ensuring the alignment of the d-axis with the voltage vector, which facilitates the decoupling control of active and reactive power; the modulation depth and carrier frequency of the three-phase PWM switching control signal can be set according to the characteristics of the converter's switching devices and filtering requirements, ensuring that the harmonic content of the output voltage waveform meets the power quality requirements of the microgrid.

[0042] Compared with existing technologies, the beneficial effects of this inertia adaptive method for suppressing power interaction oscillations caused by impact loads are:

[0043] This method does not require modification or addition of power equipment and can be directly applied to the multi-machine parallel VSG control system. It can seamlessly adapt to the existing system architecture to address the active power oscillation problem of the multi-machine parallel VSG control system. In large-scale, high-proportion renewable energy grid connection and off-grid scenarios, it can effectively cope with the power interaction oscillation challenge caused by frequent impact loads, which meets the current operation requirements of new energy power systems.

[0044] The SDFD measurement method solves the problems in actual ROCOF measurement, such as the delay caused by system inertia in frequency change, and the fluctuation of ROCOF caused by noise or small disturbances, which can lead to misjudgment by the system measurement tool and reduce the robustness of the system. SDFD can more sensitively and timely capture the characteristics of rapid frequency change under impact load, avoid measurement delay, reduce unnecessary fluctuation interference, ensure the accuracy of system state judgment, provide a reliable basis for adaptive adjustment of virtual rotational inertia, and thus improve the system's response accuracy to impact.

[0045] An adaptive virtual inertia control strategy based on multi-agent theory is proposed, which combines information exchange with a sparse communication network. This allows the virtual inertia of each VSG to be adjusted in a timely manner when subjected to impact loads, effectively suppressing active power oscillations. The multi-agent theory enables autonomous distributed coordination among the VSGs, eliminating the need for a centralized controller and improving the system's reliability and flexibility. The sparse communication network reduces the communication burden and ensures efficient information exchange. At the same time, the architecture has good scalability, adapting to changes in the scale of multi-machine parallel VSG systems, and helping the system maintain stable power output characteristics under impact loads. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0047] Figure 2 This is a schematic diagram of a multi-machine parallel VSG control system;

[0048] Figure 3 for Figure 2 Overall control block diagram of the multi-machine parallel VSG system adopting the improved inertia adaptive control strategy;

[0049] Figure 4 for Figure 3 The active power control equations in each VSG-controlled inverter adopt an improved inertia adaptive control strategy. (Schematic diagram) Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Please see the appendix Figure 1 - Appendix Figure 4 The present invention provides an embodiment of a method for adaptively suppressing power interaction oscillations caused by impact loads, comprising the following steps:

[0052] S1: For multi-unit parallel VSG control systems in AC microgrids, a sparse communication network is established between each VSG-controlled inverter. Multi-unit parallel VSG control systems include two types: grid-connected and islanded. In grid-connected VSG control systems, this strategy can coordinate with the grid's inertia characteristics to enhance the overall system's resilience. In islanded VSG control systems, this strategy is a key means of maintaining system frequency stability. In islanded scenarios with frequent impact loads, it can effectively prevent system collapse caused by power oscillations. The sparse communication network provides communication between each VSG-controlled inverter. The sparse communication network provides a transmission channel for information exchange between VSG control inverters. The content of the information exchange includes the output frequency data of each VSG control inverter. The sparse communication network adopts a point-to-point or bus topology, which can be flexibly configured according to the microgrid scale and node distribution to ensure the real-time and reliability of information transmission and provide timely status feedback for subsequent distributed inertia adaptive control. The nodes of the sparse communication network are each VSG control inverter in the multi-machine parallel VSG control system. When two nodes establish a communication connection, the two nodes are neighbors. The number of neighbor nodes can be set according to the system redundancy and communication bandwidth requirements.

[0053] S2: Based on the sparse communication network established in S1, each VSG-controlled inverter acts as an independent node, measuring its own output frequency and second-order frequency derivative (SDFD). It communicates with neighboring nodes through this sparse communication network to obtain the output frequencies of neighboring nodes and calculates the frequency difference between itself and each neighboring node. Measuring the second-order frequency derivative (SDFD) can be achieved by performing a second-order differential operation on the output frequency signal, effectively identifying the rapid frequency change trend when impact loads are applied or removed. When calculating the output frequency difference, a sliding window method or instantaneous difference method is used to ensure the timeliness of the frequency difference data, providing an accurate dynamic excitation signal for the adaptive adjustment of inertia in S3. The calculation method for the output frequency difference is as follows: using the current node's output frequency as a reference, the difference is calculated with the output frequency of each neighboring node, resulting in multiple one-to-one frequency difference values. The calculation period for the frequency difference is synchronized with the system sampling period, ensuring timely capture of frequency transients caused by impact loads and providing a rapid excitation input for inertia adjustment.

[0054] S3: An improved adaptive inertia control strategy is constructed based on multi-agent theory. Each VSG control inverter uses the output frequency difference between itself and its neighboring nodes, and its own second-order frequency derivative (SDFD) obtained from S2, to determine its own virtual rotational inertia control target through distributed control logic and the virtual rotational inertia control formula. The application of multi-agent theory enables each VSG control inverter to act as an agent, autonomously coordinating the inertia adjustment strategy without a central controller. The distributed control logic avoids the single-point failure risk of centralized control through local calculation and neighbor information interaction. The virtual rotational inertia control formula realizes the adaptive change of inertia with the system oscillation state, effectively suppressing power interaction oscillations caused by impact loads. The virtual rotational inertia control formula is as follows:

[0055]

[0056] in, The virtual inertia of the i-th VSG-controlled inverter in steady state; Let i be the output angular velocity of the i-th VSG control inverter; Let j be the output angular velocity of the VSG-controlled inverter; This is the inertia adjustment coefficient; This represents the neighborhood set of the neighboring nodes of the i-th VSG-controlled inverter; This refers to the communication weighting coefficient. This is the coefficient for the direction of change of the virtual moment of inertia; Let be the first-order frequency derivative of the i-th VSG-controlled inverter; SDFD is the second frequency derivative of the i-th VSG-controlled inverter; in the formula function based on The sign of the inertia determines the direction of inertia adjustment. When the rate of change of frequency and the acceleration of frequency change have the same sign, it indicates that the system oscillation has a tendency to intensify. This tendency can be effectively suppressed by adjusting the inertia. The value of needs to take into account the dynamic response speed and steady-state accuracy of the system. In practical applications, it can be optimized through offline simulation or online adaptive algorithm.

[0057] S4: Determine the virtual moment of inertia based on the rotor motion equations of VSG control and the virtual moment of inertia control formula in S3. The range of values ​​and damping coefficient The tuning rules; the rotor motion equation of VSG control is the core equation for simulating the rotor motion characteristics of a synchronous generator. Through it, a quantitative relationship between inertia, damping, and system frequency dynamics can be established; the virtual moment of inertia can be determined. The range of values ​​and damping coefficient The tuning rules are based on the stability criteria of linearized systems, ensuring that under impact load disturbances, the dynamic response of the system will not oscillate and diverge due to insufficient inertia, nor will it be slow to respond due to excessive inertia. The tuning of the damping coefficient balances the oscillation decay rate and steady-state error of the system.

[0058] Virtual moment of inertia The range of values ​​for is determined by the following formula:

[0059]

[0060] Substituting the above formula into the rotor motion equation of claim 6 and linearizing it, we get:

[0061]

[0062] Based on traditional control theory, the damping ratio of a second-order system The calculation formula is:

[0063]

[0064] Set damping ratio The value range is [0.1, 1.414], and Approaching 1, we obtain the upper and lower limits of the virtual moment of inertia:

[0065]

[0066] in, Let be the steady-state phase angle difference between the output voltage of the i-th VSG and the voltage at the point of common coupling; Let i be the output voltage amplitude of the i-th VSG; This refers to the voltage amplitude at the point of common coupling. Let be the equivalent reactance of the i-th VSG; the linearized rotor motion equation is a second-order system with a damping ratio of It is a key indicator for measuring the oscillation damping characteristics of a system, and is achieved through tuning. and Keeping the damping ratio within a reasonable range ensures that the system has good dynamic stability under impact loads, which can both quickly dampen oscillations and maintain frequency and voltage stability.

[0067] Damping coefficient The tuning must meet the following conditions:

[0068]

[0069] in, and These are the maximum and minimum angular frequencies allowed by the system, respectively. The maximum power that the i-th VSG can withstand; The minimum output power of the i-th VSG under the support of the energy storage device; this setting condition is based on the constraints of the system power regulation range and frequency regulation range, ensuring that the frequency fluctuation of the VSG will not exceed the allowable range within the maximum and minimum power output range, while providing sufficient damping support for the power change of the impact load, and avoiding the continuous expansion of frequency oscillation;

[0070] S5: Substitute the virtual moment of inertia control target determined in S3 into the rotor motion equation corresponding to S4, and combine the VSG reactive power control equation and active power regulation equation to solve for the effective voltage value and output frequency; perform dq transformation on the effective voltage value and output frequency to obtain the three-phase AC voltage waveform, modulate the three-phase AC voltage waveform into a three-phase PWM switching control signal, and apply the three-phase PWM switching control signal to each VSG control converter to achieve power interaction oscillation suppression; the dq transformation converts the three-phase AC quantity into DC direct-axis d-axis and quadrature-axis q-axis components, which facilitates the use of mature DC control strategies to achieve precise regulation of voltage and frequency; the generation of the three-phase PWM switching control signal follows the sinusoidal pulse width modulation principle, and by adjusting the switching duty cycle, the VSG control converter outputs a three-phase AC voltage waveform that meets the requirements, thereby converting the inertia adaptive control strategy determined in S3 and S4 into actual power output, and finally achieving power interaction oscillation suppression caused by impact load;

[0071] The rotor motion equations under VSG control are as follows:

[0072]

[0073] The VSG reactive power control equations are as follows:

[0074]

[0075] The corresponding VSG active power regulation equation is as follows:

[0076]

[0077] in, This is the active power droop coefficient; This is the reactive power droop coefficient; The mechanical power of the VSG; Q is the given reference power; Q is the output reactive power. Given reactive power; and These are the output angular frequency and rated angular frequency of the VSG, respectively; E and These are the output voltage amplitude and rated voltage amplitude of the VSG, respectively; The active power output of the VSG is J; the virtual moment of inertia is D; and the damping coefficient is D. The grid-side angular frequency is given. The active power regulation equation of the VSG simulates the speed regulation characteristics of the synchronous generator, and the reactive power control equation simulates the excitation regulation characteristics. Together with the rotor motion equation, they constitute the electromechanical transient model of the VSG, providing a physically equivalent control framework for inertia adaptive control. This enables the inverter to have inertia and damping characteristics similar to those of a synchronous generator, thus effectively participating in the suppression of power oscillations in the microgrid.

[0078] The dq transformation converts the voltage signals in a three-phase stationary coordinate system into direct-axis and quadrature-axis voltage signals in a two-phase rotating coordinate system. The three-phase PWM switching control signals are generated using sinusoidal pulse width modulation technology and are used to drive the switching devices of the VSG control converter. The inertia adjustment coefficient in S3... Adjustments are made based on the actual measured second derivative SDFD of the frequency to ensure the virtual moment of inertia. Falling within the scope defined in claim 7 and Between; the rotating coordinate system of the dq transformation is based on the synchronous rotational angular velocity of the VSG output voltage, ensuring the alignment of the d-axis with the voltage vector, which facilitates the decoupling control of active and reactive power; the modulation depth and carrier frequency of the three-phase PWM switching control signal can be set according to the characteristics of the converter's switching devices and filtering requirements, ensuring that the harmonic content of the output voltage waveform meets the power quality requirements of the microgrid.

[0079] In summary, this invention does not require modification or addition of power equipment and can be directly applied to a multi-machine parallel VSG control system. It can seamlessly adapt to the existing system architecture to address the active power oscillation problem of the multi-machine parallel VSG control system. In large-scale, high-proportion renewable energy grid connection and off-grid scenarios, it can effectively cope with the power interaction oscillation challenge caused by frequent impact loads, and meets the current operation requirements of new energy power systems.

[0080] The SDFD measurement method solves the problems in actual ROCOF measurement, such as the delay caused by system inertia in frequency change, and the fluctuation of ROCOF caused by noise or small disturbances, which can lead to misjudgment by the system measurement tool and reduce the robustness of the system. SDFD can more sensitively and timely capture the characteristics of rapid frequency change under impact load, avoid measurement delay, reduce unnecessary fluctuation interference, ensure the accuracy of system state judgment, provide a reliable basis for adaptive adjustment of virtual rotational inertia, and thus improve the system's response accuracy to impact.

[0081] An adaptive virtual inertia control strategy based on multi-agent theory is proposed, which combines information exchange with a sparse communication network. This allows the virtual inertia of each VSG to be adjusted in a timely manner when subjected to impact loads, effectively suppressing active power oscillations. The multi-agent theory enables autonomous distributed coordination among the VSGs, eliminating the need for a centralized controller and improving the system's reliability and flexibility. The sparse communication network reduces the communication burden and ensures efficient information exchange. At the same time, the architecture has good scalability, adapting to changes in the scale of multi-machine parallel VSG systems, and helping the system maintain stable power output characteristics under impact loads.

[0082] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for adaptively suppressing power oscillations caused by impact loads, characterized in that: Includes the following steps: S1: For the VSG control system of multiple parallel VSGs in AC microgrids, a sparse communication network is established between each VSG control inverter. The sparse communication network provides a transmission channel for information interaction between each VSG control inverter. S2: Based on the sparse communication network established by S1, each VSG control inverter acts as an independent node, measuring its own output frequency and frequency second derivative SDFD, and communicating with neighboring nodes through the sparse communication network to obtain the output frequency of neighboring nodes, and calculating the output frequency difference between itself and each neighboring node. S3: Based on the multi-agent theory, an improved inertia adaptive control strategy is constructed. Each VSG control inverter calls the output frequency difference between itself and its neighboring nodes and its own frequency second derivative SDFD obtained from S2. Through distributed control logic and virtual rotational inertia control formula, it determines its own virtual rotational inertia control target. S4: Determine the virtual moment of inertia based on the rotor motion equations of VSG control and the virtual moment of inertia control formula in S3. The range of values ​​and damping coefficient The tuning rules; S5: Substitute the virtual moment of inertia control target determined in S3 into the rotor motion equation corresponding to S4, and combine the VSG reactive power control equation and active power regulation equation to solve for the effective voltage value and output frequency; perform dq transformation on the effective voltage value and output frequency to obtain the three-phase AC voltage waveform, modulate the three-phase AC voltage waveform into a three-phase PWM switching control signal, and apply the three-phase PWM switching control signal to each VSG controlled converter to achieve power interaction oscillation suppression.

2. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S1, the nodes of the sparse communication network are each VSG control inverter in the multi-machine parallel VSG control system. When a communication connection is established between two nodes, the two nodes are neighbor nodes.

3. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S1, the information exchange content includes the output frequency data of each VSG control inverter.

4. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In step S2, the output frequency difference is calculated as follows: taking the output frequency of the current node as a reference, the difference is calculated with the output frequency of each neighboring node to obtain multiple one-to-one frequency difference values.

5. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S3, the virtual moment of inertia control formula is as follows: in, The virtual inertia of the i-th VSG-controlled inverter in steady state; Let i be the output angular velocity of the i-th VSG control inverter; Let j be the output angular velocity of the VSG-controlled inverter; This is the inertia adjustment coefficient; This represents the neighborhood set of the neighboring nodes of the i-th VSG-controlled inverter; This refers to the communication weighting coefficient. This is the coefficient for the direction of change of the virtual moment of inertia; Let be the first-order frequency derivative of the i-th VSG-controlled inverter; Let SDFD be the second-order frequency derivative of the i-th VSG-controlled inverter.

6. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S4, the rotor motion equation controlled by VSG is as follows: In S5, the VSG reactive power control equation is as follows: The corresponding VSG active power regulation equation is as follows: in, This is the active power droop coefficient; This is the reactive power droop coefficient; The mechanical power of the VSG; Q is the given reference power; Q is the output reactive power. Given reactive power; and These are the output angular frequency and rated angular frequency of the VSG, respectively; E and These are the output voltage amplitude and rated voltage amplitude of the VSG, respectively; The active power output of the VSG is J; the virtual moment of inertia is D; and the damping coefficient is D. This is the angular frequency on the power grid side.

7. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S4, the virtual moment of inertia The range of values ​​for is determined by the following formula: Substituting the above formula into the rotor motion equation of claim 6 and linearizing it, we get: Based on traditional control theory, the damping ratio of a second-order system The calculation formula is: Set damping ratio The value range is [0.1, 1.414], and Approaching 1, we obtain the upper and lower limits of the virtual moment of inertia: in, Let be the steady-state phase angle difference between the output voltage of the i-th VSG and the voltage at the point of common coupling; Let i be the output voltage amplitude of the i-th VSG; This refers to the voltage amplitude at the point of common coupling. Let be the equivalent reactance of the i-th VSG.

8. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S4, the damping coefficient The tuning must meet the following conditions: in, and These are the maximum and minimum angular frequencies allowed by the system, respectively. The maximum power that the i-th VSG can withstand; Let be the minimum output power of the i-th VSG supported by the energy storage device.

9. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In S1, the multi-machine parallel VSG control system includes two types: grid-connected multi-machine parallel VSG control system and islanded multi-machine parallel VSG control system.

10. The method for adaptively suppressing power oscillations caused by impact loads according to claim 1, characterized in that: In step S5, the dq transformation converts the voltage signal in the three-phase stationary coordinate system into direct-axis and quadrature-axis voltage signals in the two-phase rotating coordinate system. The three-phase PWM switching control signal is generated using sinusoidal pulse width modulation technology and is used to drive the switching devices of the VSG control converter. Furthermore, the inertia adjustment coefficient in step S3... Adjustments are made based on the actual measured second derivative of the frequency (SDFD) to ensure the virtual moment of inertia. Falling within the scope defined in claim 7 and between.

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