Harmonic resonance suppression method and system for net-forming type energy storage converter

Abstract

The embodiment of the invention relates to the technical field of harmonic resonance suppression of an energy storage converter, and provides a harmonic resonance suppression method and system for a network construction type energy storage converter, which abandons the traditional thought of relying on fixed parameters, and perceives the stability of a grid-connected system online in real time through a non-intrusive resonance state observer. The resonance state observer can accurately identify the frequency and the damping ratio of the most unstable resonance mode in the current system to form a real-time diagnosis report, and based on the real-time diagnosis report, a virtual impedance controller with optimal parameters is further dynamically synthesized, so that the real-time diagnosis report is obtained. The center frequency of the virtual impedance can accurately lock the identified resonant frequency, and the damping strength of the virtual impedance is adaptively adjusted according to the severity of resonance (namely the deterioration degree of the damping ratio), so that the problem of invalidation or deterioration of suppression caused by the time-varying of the impedance of the power grid and the drifting of a resonance point in the traditional method is solved; and the stability of the converter in a dynamic change power grid environment is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of harmonic resonance suppression of energy storage converters, and particularly relates to a grid-connected energy storage converter harmonic resonance suppression method and system. BACKGROUND

[0002] With the continuous rise of renewable energy in the global energy structure, power electronic devices represented by energy storage systems play an increasingly important role in maintaining the stable operation of the power grid. Among them, grid-connected energy storage converters are considered as the key technology to support future high-proportion new energy power systems (i.e. weak power grid) because they can simulate the active support characteristics of synchronous generators to provide voltage and frequency reference for the power grid. However, when the grid-connected converter interacts with the power grid, its own output impedance will be coupled with the equivalent impedance of the power grid at a certain harmonic frequency, which can easily cause harmonic resonance. This resonance can cause serious distortion of the grid-connected point voltage and converter output current, threatening the safe and stable operation of the converter itself and the grid-connected system.

[0003] At present, for the suppression of harmonic resonance, the industry generally uses active damping technology based on virtual impedance. By introducing a virtual resistance into the control algorithm of the converter, the output impedance characteristics of the converter are changed, thereby increasing the damping of the system at the resonance frequency point and dissipating resonance energy. However, most existing virtual impedance schemes use fixed parameter design, which has a fundamental flaw in the contradiction between its static nature and the dynamics of the resonance problem. Specifically, the resonance frequency point is determined by the converter-side parameters and the equivalent impedance of the power grid. In the actual power grid, due to factors such as line switching, load start-stop, and other new energy station grid-connected and off-grid, the power grid impedance presents time-varying and uncertainty. When the power grid impedance changes, the resonance frequency point of the system will also shift. A fixed parameter virtual impedance designed for a specific resonance frequency will have a greatly reduced suppression effect after the resonance point shifts. Due to the inherent phase delay of the control loop, it may even exhibit negative damping characteristics at the new resonance frequency point, exacerbating resonance and worsening system stability. SUMMARY

[0004] The present application aims to at least solve one of the problems existing in the prior art, and provides a grid-connected energy storage converter harmonic resonance suppression method and system.

[0005] In one aspect of the present application, a grid-connected energy storage converter harmonic resonance suppression method is provided, which comprises: performing coordinate transformation on the PCC three-phase voltage and the converter output three-phase current to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current; Harmonic separation and online observation of the resonant state of the dq synchronous rotating coordinate system components of the PCC voltage are performed to obtain the estimated resonant frequency and the estimated resonant damping ratio. The virtual impedance controller parameters are obtained by dynamically synthesizing the estimated resonant frequency and the estimated resonant damping ratio using adaptive virtual impedance parameters. Harmonic current extraction and damping voltage generation are performed on the dq synchronous rotating coordinate system components of the converter output current based on the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression. Voltage reference superposition and PWM modulation are performed on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid converter to obtain the three-phase PWM signal driving the power devices of the converter.

[0006] Optionally, harmonic separation and online resonant state observation are performed on the dq synchronous rotating coordinate system components of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio, including: Harmonic components are digitally extracted from the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage. The pure harmonic components of the PCC voltage are input into an adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

[0007] Optionally, the adaptive resonant observer is an extended Kalman filter.

[0008] Optionally, the estimated resonant frequency and estimated resonant damping ratio are used to adaptively synthesize virtual impedance parameters to obtain virtual impedance controller parameters, including: The estimated resonant damping ratio is compared with the preset damping ratio activation threshold. If the estimated resonant damping ratio is less than the preset damping ratio activation threshold, the unlimited target virtual resistance value is calculated using the following formula: ; in, The preset damping ratio activation threshold, To estimate the resonant damping ratio, For virtual resistance proportional gain, The target virtual resistance value is not limited. If the estimated resonant damping ratio is greater than or equal to the preset damping ratio activation threshold, the unlimited target virtual resistance value is set to zero.

[0009] Optionally, the virtual impedance controller parameters are obtained by adaptively synthesizing virtual impedance parameters from the estimated resonant frequency and the estimated resonant damping ratio, and the method further includes: The unlimited target virtual resistance value is safely limited to obtain the limited final virtual resistance value; Based on the final virtual resistance value after limiting, the final SOGI damping coefficient is determined; The estimated resonant frequency is converted into the center angular frequency, and the final SOGI damping coefficient and center angular frequency are used to form the virtual impedance controller parameters.

[0010] Optionally, based on the final virtual resistance value after limiting, the final SOGI damping coefficient is determined, including: Based on the final virtual resistance value after limiting, the final SOGI damping coefficient is determined using the following formula: ; in, This is the final virtual resistance value after limiting. This represents the final SOGI damping coefficient.

[0011] Optionally, the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter are subjected to voltage reference superposition and PWM modulation to obtain a three-phase PWM signal driving the power devices of the converter, including: The final voltage reference signal is obtained by subtracting the damping voltage reference signal used for resonance suppression from the original voltage reference signal of the grid converter. The final voltage reference signal is subjected to inverse Park transform and inverse Clarke transform to obtain the voltage reference in the three-phase stationary coordinate system; The voltage reference in the three-phase stationary coordinate system is input to the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

[0012] Another aspect of the present invention provides a harmonic resonance suppression system for a grid-type energy storage converter, the grid-type energy storage converter harmonic resonance suppression system comprising: The coordinate transformation module is used to perform coordinate transformation on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current. The data estimation module is used to perform harmonic separation and online observation of the resonant state of the dq synchronous rotating coordinate system component of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio. The dynamic synthesis module is used to adaptively synthesize virtual impedance parameters from the estimated resonant frequency and the estimated resonant damping ratio to obtain virtual impedance controller parameters. The reference signal generation module is used to extract harmonic currents and generate damping voltages from the dq synchronous rotating coordinate system components of the converter output current based on the virtual impedance controller parameters, so as to obtain a damping voltage reference signal for resonance suppression. The PWM signal generation module is used to perform voltage reference superposition and PWM modulation on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter to obtain the three-phase PWM signal driving the power devices of the converter.

[0013] Optionally, the data estimation module includes: The digital extraction unit is used to digitally extract the harmonic components of the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage. The parameter estimation unit is used to input the pure harmonic components of the PCC voltage into the adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

[0014] Optionally, the PWM signal generation module includes: The reference signal generation unit is used to subtract the damped voltage reference signal used for resonance suppression from the original voltage reference signal of the grid converter to obtain the final voltage reference signal. The reference voltage generation unit is used to perform inverse Park transform and inverse Clarke transform on the final voltage reference signal to obtain the voltage reference in the three-phase stationary coordinate system. The PWM signal generation unit is used to input the voltage reference of the three-phase stationary coordinate system into the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

[0015] Compared to existing technologies, this invention abandons the traditional approach of relying on fixed parameters. Instead, it uses a non-intrusive resonant state observer to sense the stability of the grid-connected system in real time. This observer can accurately identify the frequency and damping ratio of the most unstable resonant mode in the current system, generating a real-time diagnostic report. Based on this report, a virtual impedance controller with optimal parameters is dynamically synthesized. The center frequency of this virtual impedance can be precisely locked to the identified resonant frequency, and its damping strength is adaptively adjusted according to the severity of the resonance (i.e., the degree of deterioration of the damping ratio). This solves the problem of suppression failure or deterioration caused by time-varying grid impedance and resonant point drift in traditional methods, ensuring the stability of the converter in a dynamically changing grid environment. Attached Figure Description

[0016] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0017] Figure 1 A flowchart illustrating a harmonic resonance suppression method for a grid-type energy storage converter according to an embodiment of the present invention; Figure 2 This is a data flow diagram illustrating a harmonic resonance suppression method for a grid-type energy storage converter, provided in another embodiment of the present invention. Figure 3 The flowchart of a harmonic resonance suppression method for a grid-type energy storage converter provided in another embodiment of the present invention is as follows: the method involves adaptively synthesizing virtual impedance parameters from the estimated resonant frequency and the estimated resonant damping ratio to obtain virtual impedance controller parameters. Figure 4 The flowchart of a harmonic resonance suppression method for a grid-type energy storage converter provided in another embodiment of the present invention is as follows: voltage reference superposition and PWM modulation are performed on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter to obtain the three-phase PWM signal driving the power device of the converter. Figure 5 A block diagram of a harmonic resonance suppression system for a grid-type energy storage converter is provided for another embodiment of the present invention. Detailed Implementation

[0018] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0019] As indicated in the specification and claims of this invention, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0020] While this invention makes various references to certain modules in systems according to embodiments of the invention, any number of different modules can be used and run on user terminals and / or servers. The modules are merely illustrative, and different aspects of the systems and methods may use different modules.

[0021] This invention uses flowcharts to illustrate the operations performed by the system according to embodiments of the invention. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously, as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0022] To address the problems existing in the background technology, the present invention proposes a harmonic resonance suppression scheme for grid-connected energy storage converters. This scheme solves the problem that existing fixed-parameter virtual impedance strategies cannot adapt to the dynamic drift of resonant frequencies caused by changes in grid topology, leading to a decrease in suppression effectiveness or even failure. Specifically, the proposed harmonic resonance suppression scheme for grid-connected energy storage converters first starts from the data source. By real-time acquisition of the voltage signal at the grid connection point (PCC), and performing coordinate transformation and digital filtering, the pure harmonic components are accurately separated. Then, this pure harmonic component is input into an advanced online resonant state observer (such as an extended Kalman filter). This online resonant state observer can estimate the specific frequency of the most unstable resonant mode in the current system and its damping ratio characterizing the stability margin in real time and with high accuracy. Based on this accurate result, adaptive virtual impedance parameters are immediately dynamically synthesized to estimate... The calculated resonant frequency is the center frequency, and based on the difference between the estimated resonant damping ratio and the preset safety threshold, an optimal target virtual resistance value is dynamically calculated. Subsequently, after safety limiting, this target virtual resistance value is used to configure a digital bandpass filter (such as SOGI) in real time. This filter then extracts the corresponding harmonic components in the converter output current and generates a damping voltage signal proportional to it. Finally, this damping voltage signal used for resonance suppression is superimposed with the original voltage reference signal of the converter to form the final modulation command, thereby achieving precise, fast and adaptive targeted suppression of dynamic resonance.

[0023] In the technical solution of this invention, a method for suppressing harmonic resonance in a grid-type energy storage converter is proposed. Figure 1 This is a flowchart of a harmonic resonance suppression method for a grid-type energy storage converter according to an embodiment of the present invention. Figure 2 This is a data flow diagram illustrating a harmonic resonance suppression method for a grid-type energy storage converter according to an embodiment of the present invention. (In conjunction with...) Figure 1 and Figure 2According to an embodiment of the present invention, a harmonic resonance suppression method for a grid-type energy storage converter includes the following steps: S100, performing coordinate transformation on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current; S200, performing harmonic separation and online observation of the resonance state on the dq synchronous rotating coordinate system components of the PCC voltage to obtain the estimated resonance frequency and the estimated resonance damping ratio; S300, performing adaptive virtual impedance parameter dynamic synthesis on the estimated resonance frequency and the estimated resonance damping ratio to obtain virtual impedance controller parameters; S400, performing harmonic current extraction and damping voltage generation on the dq synchronous rotating coordinate system components of the converter output current based on the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression; S500, performing voltage reference superposition and PWM modulation on the damping voltage reference signal for resonance suppression and the original voltage reference signal of the grid-type converter to obtain a three-phase PWM signal driving the power devices of the converter.

[0024] Specifically, in step S100, coordinate transformation is performed on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the converter output current. It should be understood that in the three-phase stationary coordinate system, both the grid voltage and the converter current are time-varying AC sinusoidal quantities. Directly performing harmonic analysis and control design on them would face problems of high computational complexity and difficulty in guaranteeing control accuracy. Therefore, in the technical solution of this invention, coordinate transformation is performed on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the converter output current, thereby transforming the AC control problem into a DC control problem. This decouples the fundamental component into an easily controllable DC component, while simultaneously making each harmonic component appear as an AC component of a specific frequency, laying a crucial data processing foundation for subsequent accurate and efficient harmonic separation and resonant state observation.

[0025] More specifically, in a specific example of the present invention, firstly, the PCC three-phase voltage (…) acquired by the hardware sampling circuit is… , , ) and converter output three-phase current ( , , Perform a Clarke transformation to transfer it from the three-phase stationary coordinate system ( Transform to a two-phase orthogonal stationary coordinate system. ), to obtain the three-phase voltage of PCC Components ( , and converter output current Components ( , Subsequently, a phase-locked loop (PLL) module is used to track the phase angle of the three-phase voltage of the PCC in real time. Finally, based on this phase angle Perform the Park transformation to convert the previously obtained PCC three-phase voltages... Components ( , and converter output current Components ( , The components of the PCC voltage are rotated to the dq coordinate system, which rotates synchronously with the grid voltage, and finally output as the dq-coordinate system component of the PCC voltage. , ) and the dq synchronous rotating coordinate system component of the converter output current ( , ).

[0026] Specifically, in step S200, harmonic separation and online resonant state observation are performed on the dq synchronous rotating coordinate system components of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio. It should be understood that the key challenge in achieving adaptive harmonic suppression lies in the inability to obtain the precise dynamic characteristics of the system's unstable resonant modes in real time, especially since the resonant frequency and resonant damping ratio, which are its core characteristics, are unknown and dynamically change with the power grid operating conditions. Therefore, in the technical solution of this invention, harmonic separation and online resonant state observation are further performed on the dq synchronous rotating coordinate system components of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio, thereby constructing a non-intrusive online diagnostic mechanism. This mechanism first separates the pure harmonic components from the strong fundamental background through digital extraction, and then uses an adaptive resonant observer to perform in-depth analysis of the pure harmonic components, thereby accurately identifying the system's most unstable resonant mode and its key parameters. This provides the most direct and crucial decision-making basis for the subsequent adaptive virtual impedance parameter dynamic synthesis stage, ensuring that the frequency of the suppression strategy can be accurately targeted and the intensity can be adjusted as needed, thereby solving the suppression failure problem caused by the lack of information in traditional fixed parameter methods.

[0027] More specifically, in this embodiment of the invention, harmonic separation and online observation of the resonant state of the dq synchronous rotating coordinate system component of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio include: digitally extracting the harmonic components of the dq synchronous rotating coordinate system component of the PCC voltage to obtain the pure harmonic components of the PCC voltage; and inputting the pure harmonic components of the PCC voltage into an adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

[0028] Specifically, harmonic components are digitally extracted from the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage. It should be understood that in the dq synchronous rotating coordinate system components of the PCC voltage after coordinate transformation, the fundamental component with a large amplitude exhibits DC, while the harmonic resonant component to be observed exhibits a relatively weak AC. If a signal containing both DC and AC is directly fed into the resonant observer, the strong DC component will severely interfere with the dynamic tracking performance of the resonant observer for the weak AC signal, reducing its identification sensitivity and accuracy. Therefore, in the technical solution of this invention, harmonic components are further digitally extracted from the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage, thereby eliminating the interference of the fundamental DC component and separating the resonant signal to be analyzed from the strong background noise. This provides a clean input signal with a high signal-to-noise ratio and no DC bias for the subsequent adaptive resonant observer, thereby improving the accuracy, convergence speed, and precision of the estimation of the resonant frequency and damping ratio.

[0029] More specifically, in a specific example of the present invention, firstly, the dq components of the PCC voltage are synchronously rotated in the coordinate system ( , The signal is input to a first-order digital low-pass filter, which estimates the DC component, i.e., the fundamental component, in real time through iterative calculation. , Then, within the same calculation cycle of the controller, the dq component of the original PCC voltage is synchronously rotated in the coordinate system. , ) and the fundamental component of the filter output ( , The subtraction is performed in the subtractor, and the output of the subtractor is the pure harmonic component of the PCC voltage after removing the fundamental DC frequency. , The pure harmonic component of the PCC voltage is then transmitted to an adaptive resonant observer for processing.

[0030] Specifically, the pure harmonic components of the PCC voltage are input into an adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio. It is worth noting that the adaptive resonant observer is an extended Kalman filter. It should be understood that obtaining only the pure harmonic components is insufficient for adaptive control, as they contain multiple frequency components, and it is impossible to directly determine which harmonic is the dominant, unstable resonant mode, let alone quantify its stability margin. Therefore, in the technical solution of this invention, the pure harmonic components of the PCC voltage are further input into the adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio. This allows the use of the resonant dynamic model established within the observer, through a closed-loop iterative mechanism combining prediction and correction, to track and lock the oscillation component with the fastest amplitude growth or the weakest damping in the pure harmonic components in real time, and to separate its frequency and damping ratio—the two key state variables. In this way, a complex harmonic spectrum analysis problem can be transformed into a real-time, accurate estimation of two key parameters, providing a quantitative and dynamic input for the subsequent parameter synthesis of the adaptive virtual impedance, thereby achieving accurate diagnosis of the resonant state.

[0031] More specifically, in a concrete example of the present invention, firstly, a state-space model describing the dominant resonant component is established, whose state vector includes the dq-axis components of the resonant voltage and the resonant angular frequency to be estimated. Then, an extended Kalman filter performs two steps within one control cycle: prediction and update. In the prediction step, the extended Kalman filter predicts the current state based on the state estimate from the previous time step and the state transition equation, i.e., the position of the resonant voltage vector after rotation and the invariant frequency. In the update step, the extended Kalman filter compares the actual measured value of the pure harmonic component of the PCC voltage with the predicted value, generating a measurement residual; then, using this measurement residual and the calculated Kalman gain, the predicted state is corrected to obtain the optimal posterior state estimate for the current time step. Finally, the resonant angular frequency is directly extracted from the updated state vector as the estimated resonant frequency, and the estimated resonant damping ratio is obtained by calculating the rate of change of the resonant voltage amplitude between two consecutive time steps.

[0032] Specifically, in step S300, the estimated resonant frequency and estimated resonant damping ratio are dynamically synthesized using adaptive virtual impedance parameters to obtain virtual impedance controller parameters. It should be understood that the resonant frequency and damping ratio output by the resonant state observer are physical quantities characterizing the system state and cannot be directly used as execution parameters for the controller. They must be transformed into specific parameters that the controller can recognize and execute, and this transformation process needs to consider the effectiveness, timeliness, and safety of suppression. Therefore, in the technical solution of this invention, the estimated resonant frequency and estimated resonant damping ratio are further dynamically synthesized using adaptive virtual impedance parameters to obtain virtual impedance controller parameters. This establishes a direct mapping relationship from system state diagnosis to control strategy generation. An activation threshold is set to determine whether suppression is initiated, the suppression strength is determined through proportional calculation, and system stability is ensured through safety limiting. Ultimately, the physical suppression requirements are accurately transformed into mathematical controller parameters. In this way, it can be ensured that the suppression effect of the virtual impedance is not only precisely aligned with the resonant point in frequency, but also dynamically matched with the severity of the resonance in intensity. This achieves a fundamental shift from passive, fixed suppression to active, on-demand adaptive suppression, thereby minimizing unnecessary power loss and interference with the dynamic performance of the system while ensuring the suppression effect.

[0033] Figure 3 This document presents a flowchart illustrating the adaptive dynamic synthesis of virtual impedance parameters to obtain virtual impedance controller parameters from the estimated resonant frequency and estimated resonant damping ratio in a harmonic resonance suppression method for a grid-type energy storage converter according to an embodiment of the present invention. (This is combined with...) Figure 3 Step S300 includes: S310, comparing the estimated resonant damping ratio with a preset damping ratio activation threshold; S320, if the estimated resonant damping ratio is less than the preset damping ratio activation threshold, calculating the unlimited target virtual resistance value using the following formula; S330, if the estimated resonant damping ratio is greater than or equal to the preset damping ratio activation threshold, setting the unlimited target virtual resistance value to zero; S340, performing safety limiting on the unlimited target virtual resistance value to obtain a limited final virtual resistance value; S350, determining the final SOGI damping coefficient based on the limited final virtual resistance value; S360, converting the estimated resonant frequency into a center angular frequency, and combining the final SOGI damping coefficient and the center angular frequency to form the virtual impedance controller parameters.

[0034] Specifically, in step S310, the estimated resonant damping ratio is compared with a preset damping ratio activation threshold; in step S320, if the estimated resonant damping ratio is less than the preset damping ratio activation threshold, the unlimited target virtual resistance is calculated using the following formula: ;in, The preset damping ratio activation threshold, To estimate the resonant damping ratio, For virtual resistance proportional gain, The target virtual resistance value is the unlimited value. In step S330, if the estimated resonant damping ratio is greater than or equal to the preset damping ratio activation threshold, the unlimited target virtual resistance value is set to zero.

[0035] It should be understood that during stable system operation, any additional virtual resistance will cause unnecessary power loss and affect the system's dynamic response performance, and damping is only required when the system is at risk of resonance. Therefore, in the technical solution of this invention, the estimated resonance damping ratio is further compared with a preset damping ratio activation threshold; if the estimated resonance damping ratio is less than the preset damping ratio activation threshold, the unlimited target virtual resistance value is calculated using a formula; if the estimated resonance damping ratio is greater than or equal to the preset damping ratio activation threshold, the unlimited target virtual resistance value is set to zero, thereby establishing a precise, event-driven control logic. This control logic can not only determine whether the resonance suppression function needs to be activated, but also calculate the required amount of damping proportionally according to the specific degree of deterioration in the system's stability margin. In this way, damping can be applied on demand, automatically disabling virtual impedance to ensure maximum operating efficiency when the system is stable, and quickly and accurately applying suppression force matching the level of risk when the system shows signs of instability, thereby achieving the best balance between ensuring system safety and improving operational economy.

[0036] Specifically, in step S340, the unlimited target virtual resistance value is subjected to safety limiting to obtain the limited final virtual resistance value. It should be understood that the unlimited target virtual resistance value is dynamically calculated based on real-time estimation. Under system transients or measurement noise interference, it may momentarily become excessively large or exhibit illegal negative values. Directly using this value for control could lead to risks such as PWM overmodulation, current surges, and even control system instability. Therefore, in the technical solution of this invention, the unlimited target virtual resistance value is further subjected to safety limiting to obtain the limited final virtual resistance value. This sets a predefined safety boundary for the range of virtual resistance values, ensuring that it always remains within a reasonable and harmless range for the system. This effectively prevents sudden changes in control commands caused by drastic fluctuations in estimated parameters, thereby ensuring the stability of the control system and the safe operation of the converter hardware, and ensuring the stability and reliability of the entire resonance suppression function.

[0037] More specifically, in one particular example of the invention, firstly, an upper limit value for the virtual resistance is preset in the controller. and lower limit value Among them, the lower limit value It is set to zero to prevent negative damping. Then, in each control cycle, the calculated unlimited target virtual resistance value is... With upper limit and lower limit value Compare them. If the target virtual resistance value Greater than the upper limit The final virtual resistance value after limiting will then be... Forced to be set to the upper limit value If the target virtual resistance value Less than the lower limit value The final virtual resistance value after limiting will then be... Forced to be set to the lower limit value ;like At the upper limit and lower limit value Between these points, the final virtual resistance value after amplitude limiting will be... Set to equal to the target virtual resistance value The final output will be the final virtual resistance value after being limited. This refers to a virtual resistance value that has undergone safety constraints and can be directly used for subsequent calculations.

[0038] Specifically, in step S350, the final SOGI damping coefficient is determined based on the final virtual resistance value after limiting. Step S350 specifically includes: determining the final SOGI damping coefficient based on the final virtual resistance value after limiting using the following formula: ;in, This is the final virtual resistance value after limiting. This represents the final SOGI damping coefficient.

[0039] It should be understood that the final virtual resistance value after limiting is a quantity characterizing the physical damping strength, while the second-order generalized integrator (SOGI), as the core of the digital controller, configures its filtering characteristics through its internal mathematical coefficients (i.e., damping coefficients). There exists a conversion relationship between the two that must be precisely defined. Therefore, in the technical solution of this invention, the final SOGI damping coefficient is further determined based on the final virtual resistance value after limiting, thereby accurately converting the target damping value at the physical level into executable parameters at the digital filter algorithm level. This ensures that the damping effect generated by the subsequently constructed SOGI filter corresponds numerically exactly to the final virtual resistance value after safety constraints, thus accurately applying the adaptively calculated optimal damping to the control loop, providing the final parameter guarantee for achieving effective resonance suppression.

[0040] Specifically, in step S360, the estimated resonant frequency is converted into the center angular frequency, and the final SOGI damping coefficient and center angular frequency are combined to form the virtual impedance controller parameters. It should be understood that SOGI, as a digital filter, defines its transfer function and discretization based on angular frequency. However, the estimated resonant frequency output by the resonant state observer is mismatched in terms of unit system and cannot be directly used to configure SOGI. Therefore, in the technical solution of this invention, the estimated resonant frequency is further converted into the center angular frequency, and the final SOGI damping coefficient and center angular frequency are combined to form the virtual impedance controller parameters. This achieves unit system unification and integrates the two independently calculated parameters—the center angular frequency representing the suppression frequency and the damping coefficient representing the suppression strength—into a complete and executable set of controller parameters. This ensures a complete and unambiguous configuration instruction for the downstream virtual impedance implementation stage, enabling the SOGI filter to be precisely set to apply the correct damping strength at the correct target frequency.

[0041] More specifically, in a particular example of the invention, firstly, the controller inputs the estimated resonant frequency. With constant Performing the multiplication operation yields the center angular frequency required for SOGI. Then, the calculated center angular frequency The final SOGI damping coefficient determined in the previous step These are stored together in a predefined data structure or array. This contains... and The combined data constitutes the final virtual impedance controller parameters, which are then passed to the subsequent harmonic current extraction and damping voltage generation stages as the final output of the adaptive parameter dynamic synthesis stage.

[0042] Specifically, in step S400, harmonic current extraction and damping voltage generation are performed on the dq synchronous rotating coordinate system component of the converter output current based on the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression. It should be understood that the virtual impedance controller parameters generated in the preceding steps are merely a set of configuration instructions; they cannot directly act on the system themselves. An execution mechanism is required to apply the virtual impedance characteristics represented by these parameters to the converter's output behavior. Therefore, in the technical solution of this invention, harmonic current extraction and damping voltage generation are further performed on the dq synchronous rotating coordinate system component of the converter output current based on the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression. This constructs the execution mechanism of the virtual impedance. Through a digital filter configured in real-time by the controller parameters, Ohm's law is accurately simulated at the resonant frequency point, i.e., a voltage signal proportional to the magnitude of the resonant current is generated. In this way, the abstract concept of virtual impedance can be materialized into a concrete voltage reference signal that can be superimposed within the control system, thus providing an execution-level guarantee for the final accurate correction of the converter output voltage.

[0043] More specifically, in a specific example of the invention, firstly, the dq components of the converter output current are synchronously rotated in the coordinate system ( , Perform a digital filtering operation similar to PCC voltage harmonic extraction, that is, obtain its fundamental DC component through a low-pass filter, and then use the dq component of the converter output current to synchronously rotate the coordinate system. , Subtracting the fundamental DC component from the original value of the current yields the pure harmonic current component (which does not contain the fundamental wave). , Then, the pure harmonic current component is input to an SOGI module, whose center angular frequency and damping coefficient have been previously obtained from the virtual impedance controller parameters generated in the preceding steps. , Configured as described above. The SOGI module performs bandpass filtering on the pure harmonic current component of its input, and its output is a damped voltage reference signal containing only the target resonant frequency component with an amplitude proportional to the resonant current. , ).

[0044] Specifically, in step S500, the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter are subjected to voltage reference superposition and PWM modulation to obtain a three-phase PWM signal driving the power devices of the converter. It should be understood that the damping voltage reference signal generated in the preceding steps is only a correction quantity existing within the digital controller; it cannot directly drive the power devices on its own. It must be combined with the original voltage reference signal generated by the main control loop of the converter and ultimately converted into a physical drive signal that can be executed by the power semiconductor switches. Therefore, in the technical solution of this invention, the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter are further subjected to voltage reference superposition and PWM modulation to obtain a three-phase PWM signal driving the power devices of the converter. This allows the calculated virtual impedance effect to be finally applied to the physical output of the converter. By subtracting the voltage signals, an equivalent virtual resistor is inserted in series at the control level. Then, through coordinate inverse transformation and pulse width modulation, the corrected final control command is converted from the digital domain to the physical switch action without distortion. In this way, the final result of the entire adaptive resonance suppression algorithm, namely the dynamically generated damping voltage, can be accurately materialized into a real-time correction of the converter output voltage, thereby completing a complete closed-loop control from resonance diagnosis to physical suppression, ultimately effectively dissipating resonance energy and ensuring the stable operation of the system.

[0045] Figure 4 This is a flowchart illustrating a harmonic resonance suppression method for a grid-type energy storage converter according to an embodiment of the present invention. The method involves voltage reference superposition and PWM modulation of a damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter to obtain a three-phase PWM signal driving the converter power devices. Figure 4 As shown, step S500 includes: S510, subtracting the damping voltage reference signal used for resonance suppression from the original voltage reference signal of the grid-type converter to obtain the final voltage reference signal; S520, performing inverse Park transform and inverse Clarke transform on the final voltage reference signal to obtain the voltage reference in the three-phase stationary coordinate system; S530, inputting the voltage reference in the three-phase stationary coordinate system into the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

[0046] Specifically, in step S510, the damping voltage reference signal used for resonance suppression is subtracted from the original voltage reference signal of the grid-type converter to obtain the final voltage reference signal. It should be understood that in the control system, the original voltage reference signal of the grid-type converter determines its main voltage support function, while the damping voltage reference signal used for resonance suppression is an independent correction quantity. The two must be combined through a clear mathematical operation to form a unified final command that includes all control objectives. Therefore, in the technical solution of this invention, the damping voltage reference signal used for resonance suppression is further subtracted from the original voltage reference signal of the grid-type converter to obtain the final voltage reference signal. This accurately simulates the behavior of a physical series impedance at the control algorithm level, that is, subtracting a voltage drop proportional to the resonant current from the original voltage source reference. In this way, the damping effect of the virtual impedance can be seamlessly embedded into the final output voltage command of the converter, so that the generated PWM waveform can not only maintain the grid voltage but also actively generate a voltage component opposite to the resonant current, thereby achieving direct suppression of resonance.

[0047] More specifically, in a specific example of the invention, firstly, the controller reads the dq component of the original voltage reference signal of the grid converter from the corresponding memory register. , ) and the dq component of the damping voltage reference signal used for resonance suppression ( , Then, perform element-wise subtraction on these two dq components, i.e., according to... Calculate the d-component of the final voltage reference signal and according to Calculate the q-component of the final voltage reference signal Finally, the dq component of the final voltage reference signal is calculated. , This is output as a new data vector to the subsequent inverse coordinate transformation step for processing.

[0048] Specifically, in step S520, the final voltage reference signal undergoes inverse Park transform and inverse Clarke transform to obtain the voltage reference in the three-phase stationary coordinate system. It should be understood that the final voltage reference signal is a DC or low-frequency AC component existing in the dq synchronous rotating coordinate system. This is a mathematical expression that facilitates control calculations, while the space vector pulse width modulation (SVPWM) module that ultimately executes the switching action needs the AC voltage reference in the three-phase stationary coordinate system as its direct input. Therefore, in the technical solution of this invention, the final voltage reference signal is further subjected to inverse Park transform and inverse Clarke transform to obtain the voltage reference in the three-phase stationary coordinate system. This completes the necessary conversion of the control command from the mathematical domain to the physical domain, restoring the abstract dq control quantity to a concrete, time-varying three-phase sinusoidal wave command that can be understood and executed by the modulator. In this way, a set of three-phase voltage reference waveforms with correct instantaneous values ​​that completely contain the main control objective and resonance suppression correction quantity can be generated, providing a direct and accurate input for the final generation of the PWM signal driving the power device.

[0049] More specifically, in a particular example of the invention, firstly, the controller performs an inverse Park transform, converting the dq component of the final voltage reference signal ( , Synchronization phase angle provided by the phase-locked loop Combining these methods, the dq component of the final voltage reference signal is inversely transformed from the dq coordinate system, which rotates synchronously with the grid voltage, to a two-phase orthogonal stationary coordinate system. This yields the final voltage reference signal. Components ( , Following this, the controller processes the final voltage reference signal. Perform an inverse Clarke transformation on the components, transforming them from two orthogonal stationary coordinate systems ( Further transformation to a three-phase stationary coordinate system ( The final output is a voltage reference in the three-phase stationary coordinate system that can directly drive the SVPWM module. , , ).

[0050] Specifically, in step S530, the voltage reference of the three-phase stationary coordinate system is input to the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter. It should be understood that the voltage reference of the three-phase stationary coordinate system is a set of continuously changing ideal voltage commands, while the power devices of the converter are essentially high-speed switches that can only be in two states: on or off. Therefore, the two cannot be directly correlated. Thus, in the technical solution of this invention, the voltage reference of the three-phase stationary coordinate system is further input to the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter. This effectively synthesizes the continuous voltage reference vector into a series of discrete switching state sequences that can be executed by the power devices within each switching cycle, and accurately calculates the duration of each switching state. In this way, the converter can accurately synthesize an output voltage waveform consistent with the three-phase voltage reference command on a macroscopic scale (within one switching cycle), thereby transforming the final command of the entire control algorithm into a physical drive for the power devices, completing the last link of the control closed loop.

[0051] More specifically, in a specific example of the invention, firstly, the SVPWM module, based on the input three-phase stationary coordinate system voltage reference (… , , The system synthesizes a space voltage vector and determines its current sector position. Then, based on the sector information and the amplitude and phase of the space voltage vector, it calculates the duration of action of the two adjacent basic voltage vectors constituting the reference vector (i.e., the space voltage vector) and the zero vector. Finally, according to a preset switching sequence (e.g., seven-segment SVPWM), these durations are distributed into a single switching cycle, generating three complementary pulse width modulation (PWM) waveforms for the upper and lower bridge arms. These three PWM signals are ultimately output to the gate drive circuit of the power devices to directly control the precise on / off switching of the power devices in the three-phase bridge arms of the converter.

[0052] In summary, a harmonic resonance suppression method for a grid-connected energy storage converter according to an embodiment of the present invention has been clarified. Firstly, it abandons the traditional approach relying on fixed parameters and instead uses a non-intrusive resonant state observer to sense the stability of the grid-connected system in real time. This resonant state observer can accurately identify the frequency and damping ratio of the most unstable resonant mode in the current system, generating a real-time diagnostic report. Based on this report, a virtual impedance controller with optimal parameters is dynamically synthesized. The center frequency of this virtual impedance can accurately lock the identified resonant frequency, and its damping strength is adaptively adjusted according to the severity of the resonance (i.e., the degree of deterioration of the damping ratio). This solves the problem of suppression failure or deterioration caused by time-varying grid impedance and resonant point drift in traditional methods, ensuring the stability of the converter in a dynamically changing grid environment.

[0053] This invention also provides a harmonic resonance suppression system for a grid-type energy storage converter.

[0054] Figure 5 This is a block diagram of a grid-type energy storage converter harmonic resonance suppression system according to an embodiment of the present invention. Figure 5 As shown, a harmonic resonance suppression system 500 for a grid-type energy storage converter according to an embodiment of the present invention includes: a coordinate transformation module 510, used to perform coordinate transformation on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current; a data estimation module 520, used to perform harmonic separation and online observation of the resonance state on the dq synchronous rotating coordinate system components of the PCC voltage to obtain the estimated resonance frequency and the estimated resonance damping ratio; and a dynamic synthesis module 530, used to perform harmonic separation and online observation of the resonance state on the estimated resonance frequency. The virtual impedance controller parameters are dynamically synthesized adaptively based on the estimated resonant damping ratio. The reference signal generation module 540 is used to extract harmonic current and generate damping voltage based on the dq synchronous rotating coordinate system component of the converter output current according to the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression. The PWM signal generation module 550 is used to perform voltage reference superposition and PWM modulation on the damping voltage reference signal for resonance suppression and the original voltage reference signal of the grid-type converter to obtain a three-phase PWM signal driving the power devices of the converter.

[0055] Specifically, the data estimation module 520 includes: a digital extraction unit for digitally extracting harmonic components from the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage; and a parameter estimation unit for inputting the pure harmonic components of the PCC voltage into an adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

[0056] Specifically, the PWM signal generation module 550 includes: a reference signal generation unit, used to subtract the damping voltage reference signal used for resonance suppression from the original voltage reference signal of the grid-type converter to obtain the final voltage reference signal; a reference voltage generation unit, used to perform inverse Park transform and inverse Clarke transform on the final voltage reference signal to obtain the voltage reference in the three-phase stationary coordinate system; and a PWM signal generation unit, used to input the voltage reference in the three-phase stationary coordinate system into the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

[0057] The specific implementation method of the harmonic resonance suppression system of the grid-type energy storage converter provided in the embodiments of the present invention can be found in the harmonic resonance suppression method of the grid-type energy storage converter provided in the embodiments of the present invention, and will not be repeated here.

[0058] A harmonic resonance suppression system 500 for a grid-type energy storage converter according to an embodiment of the present invention can be implemented in various wireless terminals, such as servers with a harmonic resonance suppression algorithm for a grid-type energy storage converter. In one possible implementation, the harmonic resonance suppression system 500 for a grid-type energy storage converter according to an embodiment of the present invention can be integrated into a wireless terminal as a software module and / or a hardware module. For example, the harmonic resonance suppression system 500 for a grid-type energy storage converter can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the harmonic resonance suppression system 500 for a grid-type energy storage converter can also be one of many hardware modules of the wireless terminal.

[0059] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for suppressing harmonic resonance in a grid-type energy storage converter, characterized in that, The harmonic resonance suppression method for the grid-type energy storage converter includes: The coordinate transformation is performed on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current. Harmonic separation and online observation of the resonant state of the dq synchronous rotating coordinate system components of the PCC voltage are performed to obtain the estimated resonant frequency and the estimated resonant damping ratio. The virtual impedance controller parameters are obtained by dynamically synthesizing the estimated resonant frequency and the estimated resonant damping ratio using adaptive virtual impedance parameters. Harmonic current extraction and damping voltage generation are performed on the dq synchronous rotating coordinate system components of the converter output current based on the virtual impedance controller parameters to obtain a damping voltage reference signal for resonance suppression. Voltage reference superposition and PWM modulation are performed on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid converter to obtain the three-phase PWM signal driving the power devices of the converter.

2. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 1, characterized in that, Harmonic separation and online resonant state observation of the dq synchronous rotating coordinate system components of the PCC voltage are performed to obtain the estimated resonant frequency and the estimated resonant damping ratio, including: Harmonic components are digitally extracted from the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage. The pure harmonic components of the PCC voltage are input into an adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

3. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 2, characterized in that, The adaptive resonant observer is an extended Kalman filter.

4. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 1, characterized in that, Adaptive virtual impedance parameters are dynamically synthesized from the estimated resonant frequency and estimated resonant damping ratio to obtain virtual impedance controller parameters, including: The estimated resonant damping ratio is compared with the preset damping ratio activation threshold. If the estimated resonant damping ratio is less than the preset damping ratio activation threshold, the unlimited target virtual resistance value is calculated using the following formula: ； in, The preset damping ratio activation threshold, To estimate the resonant damping ratio, For virtual resistance proportional gain, The target virtual resistance value is not limited. If the estimated resonant damping ratio is greater than or equal to the preset damping ratio activation threshold, the unlimited target virtual resistance value is set to zero.

5. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 4, characterized in that, The virtual impedance controller parameters are obtained by adaptively synthesizing virtual impedance parameters from the estimated resonant frequency and the estimated resonant damping ratio, and the process also includes: The unlimited target virtual resistance value is safely limited to obtain the limited final virtual resistance value; Based on the final virtual resistance value after limiting, the final SOGI damping coefficient is determined; The estimated resonant frequency is converted into the center angular frequency, and the final SOGI damping coefficient and center angular frequency are used to form the virtual impedance controller parameters.

6. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 5, characterized in that, Based on the final virtual resistance value after amplitude limiting, the final SOGI damping coefficient is determined, including: Based on the final virtual resistance value after limiting, the final SOGI damping coefficient is determined using the following formula: ； in, This is the final virtual resistance value after limiting. This represents the final SOGI damping coefficient.

7. The harmonic resonance suppression method for a grid-type energy storage converter according to claim 1, characterized in that, Voltage reference superposition and PWM modulation are performed on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid converter to obtain the three-phase PWM signal driving the power devices of the converter, including: The final voltage reference signal is obtained by subtracting the damping voltage reference signal used for resonance suppression from the original voltage reference signal of the grid converter. The final voltage reference signal is subjected to inverse Park transform and inverse Clarke transform to obtain the voltage reference in the three-phase stationary coordinate system; The voltage reference in the three-phase stationary coordinate system is input to the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

8. A harmonic resonance suppression system for a grid-type energy storage converter, characterized in that, The harmonic resonance suppression system for the grid-type energy storage converter includes: The coordinate transformation module is used to perform coordinate transformation on the three-phase voltage of the PCC and the three-phase output current of the converter to obtain the dq synchronous rotating coordinate system components of the PCC voltage and the dq synchronous rotating coordinate system components of the converter output current. The data estimation module is used to perform harmonic separation and online observation of the resonant state of the dq synchronous rotating coordinate system component of the PCC voltage to obtain the estimated resonant frequency and the estimated resonant damping ratio. The dynamic synthesis module is used to adaptively synthesize virtual impedance parameters from the estimated resonant frequency and the estimated resonant damping ratio to obtain virtual impedance controller parameters. The reference signal generation module is used to extract harmonic currents and generate damping voltages from the dq synchronous rotating coordinate system components of the converter output current based on the virtual impedance controller parameters, so as to obtain a damping voltage reference signal for resonance suppression. The PWM signal generation module is used to perform voltage reference superposition and PWM modulation on the damping voltage reference signal used for resonance suppression and the original voltage reference signal of the grid-type converter to obtain the three-phase PWM signal driving the power devices of the converter.

9. The harmonic resonance suppression system for a grid-type energy storage converter according to claim 8, characterized in that, The data estimation module includes: The digital extraction unit is used to digitally extract the harmonic components of the dq synchronous rotating coordinate system components of the PCC voltage to obtain the pure harmonic components of the PCC voltage. The parameter estimation unit is used to input the pure harmonic components of the PCC voltage into the adaptive resonant observer to obtain the estimated resonant frequency and the estimated resonant damping ratio.

10. The harmonic resonance suppression system for a grid-type energy storage converter according to claim 8, characterized in that, The PWM signal generation module includes: The reference signal generation unit is used to subtract the damped voltage reference signal used for resonance suppression from the original voltage reference signal of the grid converter to obtain the final voltage reference signal. The reference voltage generation unit is used to perform inverse Park transform and inverse Clarke transform on the final voltage reference signal to obtain the voltage reference in the three-phase stationary coordinate system. The PWM signal generation unit is used to input the voltage reference of the three-phase stationary coordinate system into the space vector pulse width modulation module to obtain the three-phase PWM signal driving the power devices of the converter.

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