A grid-forming inverter adaptive feed-forward damping enhancement method and system

Abstract

The application provides a network-constructing type inverter adaptive feedforward damping enhancement method and system, and belongs to the technical field of new energy grid-connected inverter control. The method comprises the following steps: obtaining the capacitor voltage of the inverter filter and the grid-connected point current, calculating the active power and the reactive power and respectively subtracting the corresponding reference values; the reactive power difference value generates a voltage amplitude reference signal through a virtual oscillator voltage control dynamic equation, and the active power difference value generates a reference reference angle frequency through a virtual oscillator angle frequency control dynamic equation; an adaptive feedforward damping controller is constructed, the active power reference is sent into the controller to obtain an angle frequency compensation signal, the compensation signal is superimposed with the reference reference angle frequency to obtain an actual control angle frequency; the actual control angle frequency and the voltage amplitude reference are sent into a voltage-current double closed loop control to generate a modulation wave driving signal. The application does not need to identify the grid impedance on line, and effectively suppresses the damping deviation caused by the impedance change through adaptive feedforward compensation.

Description

Technical Field

[0001] This invention belongs to the field of control technology for grid-connected inverters in new energy, and particularly relates to an adaptive feedforward damping enhancement method and system for grid-connected inverters. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the continuous increase in the penetration rate of renewable energy sources such as photovoltaics and wind power, power systems are increasingly exhibiting characteristics such as low inertia, weak support, and weak damping. Grid-connected inverters, which can actively establish voltage and frequency references and provide voltage, frequency, and inertia support for the power system, have become a research hotspot in the field of renewable energy grid connection.

[0004] In existing grid-based control strategies, virtual oscillators based on Andernov-Hopf oscillators have attracted widespread attention due to their fast synchronization speed. However, the damping characteristics of grid-based inverters using virtual oscillators are highly sensitive to grid impedance. In actual power grids, line impedance varies over a wide range due to changes in operating mode, capacity adjustments, line length differences, and load fluctuations, leading to significant fluctuations in the short-circuit ratio and inductance-resistance ratio. Impedance uncertainty alters the equivalent damping ratio and natural frequency of the power loop, causing problems such as increased overshoot, slower response, and even oscillatory instability in the active power response. Meanwhile, in medium- and low-voltage power grids, line impedance cannot be ignored, and the cross-coupling effect between active and reactive power is significantly enhanced, making it difficult for damping controllers designed based on nominal impedance to maintain the expected dynamic performance.

[0005] To address the aforementioned issues, existing damping optimization methods mainly include droop coefficient tuning, series filter damping shaping, additional feedback damping channels, and switching adaptive damping. Among these, droop coefficient tuning easily alters the system's steady-state operating point and struggles to simultaneously consider grid connection standards and dynamic performance; series filter damping shaping typically relies on known line impedance parameters and insufficiently considers power cross-coupling effects; while additional feedback damping can improve damping, it may sacrifice dynamic response speed; and the switching adaptive impedance method suffers from insufficient dynamic smoothness during mode switching, making it difficult to continuously and accurately maintain system damping to the target value. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, the present invention provides an adaptive feedforward damping enhancement method and system for grid-type inverters, aiming to solve the problem of damping offset in grid-type inverters caused by line impedance uncertainty.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: The first aspect of this invention provides an adaptive feedforward damping enhancement method for grid-type inverters; An adaptive feedforward damping enhancement method for grid-type inverters includes: Obtain the inverter's filter capacitor voltage and grid connection point current; The real-time active power and reactive power are calculated based on the capacitor voltage and grid connection point current, and the power difference is obtained by subtracting them from the active power reference and reactive power reference, respectively. After inputting the reactive power difference into the voltage control dynamic equation of the virtual oscillator, the oscillator outputs a voltage amplitude reference signal based on the voltage response dynamics; after inputting the active power difference into the angular frequency control dynamic equation of the virtual oscillator, the oscillator outputs a reference angular frequency based on the angular frequency response dynamics. An adaptive feedforward damping controller is constructed. The active power reference is fed into the adaptive feedforward damping controller, and the angular frequency compensation signal is output. The actual control angular frequency is obtained by superimposing the basic angular frequency and the angular frequency compensation signal. The actual control angular frequency and voltage amplitude reference are fed into the voltage and current dual closed-loop control to generate the inverter modulation wave to drive the power devices.

[0008] As a further technical solution, the virtual oscillator includes a voltage control dynamic equation and an angular frequency control dynamic equation. After substituting the real-time power calculation value and the power reference, reference signals for voltage and angular frequency are generated based on the dynamic response, which serve as inputs for the voltage and current dual closed-loop control. The formulas are as follows:

[0009] in, The output voltage amplitude of the virtual oscillator. This is the output voltage reference value. For convergence speed, , These are the voltage and current amplification factors. For inverter power output, For reactive power reference, To output the phase angle, For the output angular frequency, This is the reference value for angular frequency. The output is the difference in active power after filtering. For the active power output of the inverter, For active power reference, For virtual inertia coefficient, For virtual oscillator capacitors; This is the derivative of the filtered active power difference output; To output the derivative of the phase angle; This is the derivative of the output voltage amplitude of the virtual oscillator.

[0010] As a further technical solution, the transfer function of the adaptive feedforward damping controller is:

[0011] in, For the frequency domain transfer function of the adaptive feedforward controller; For complex variables in the Laplace transform; For fixed control items; For adaptive terms, For time-domain adaptive variables, This is the fixed transfer function in the adaptive term.

[0012] f(s) and q(s) are expressed as:

[0013]

[0014] in, , These are the voltage and current amplification factors; For a complex variable in the Laplace domain; The damping ratio is the desired response. The natural frequency of the desired response; , represents a combination of coefficients, used here for simplified representation; This is the virtual inertia coefficient.

[0015] As a further technical solution, the adaptive feedforward damping controller adopts the form of PD generalized error to ensure the strict positive real condition and accelerate the convergence speed. Its specific implementation is as follows:

[0016]

[0017] Where λ is the generalized error coefficient; The output is the generalized error; The derivative of the actual error; This represents the actual error. The frequency domain representation of the generalized error output; This is a frequency domain function relating the actual error and the error of the parameter to be estimated. It is the error between the parameter to be estimated and the actual value; , is the regression term; It is the frequency domain function between the generalized error and the error of the parameter to be estimated.

[0018] As a further technical solution, the adaptive term employs an adaptive gradient descent controller with e-correction and normalization functions, and its time-domain controller is expressed as follows:

[0019] in, For time-domain controller; This is an adaptive gain used to adjust the convergence speed of the parameters; These are the correction term coefficients, used to suppress parameter drift; For weighting functions; This represents the time-domain form of the regression term; This represents the time-domain form of the generalized error; The parameter to be estimated; The nonlinear weighting function is expressed as:

[0020] in, This is the expression for the weighting function; This is a critical value used to define the range of error effects and to reduce the impact of the correction term on steady-state performance in the small error region.

[0021] As a further technical solution, the active power reference is fed into the adaptive feedforward damping controller, which outputs an angular frequency compensation signal. The actual control angular frequency is obtained by superimposing the fundamental angular frequency and the angular frequency compensation signal, including: The active power reference is fed into the adaptive controller. The active power reference enters the controller in two ways. One way generates the ideal active power through the system expected response model. After comparing it with the actual power reference, it is processed by the generalized error and adaptive law to generate the estimated parameters. Another path is used to substitute the fixed control term and the adaptive control term in the adaptive feedforward controller to construct an adaptive feedforward damping controller and output an angular frequency compensation signal. The actual control angular frequency is obtained by superimposing the fundamental angular frequency and the angular frequency compensation signal.

[0022] As a further technical solution, the actual control angular frequency and voltage amplitude reference are fed into the voltage and current dual closed-loop control to generate the inverter modulation wave to drive the power devices, including: The actual control angular frequency is combined with the voltage amplitude signal output by the virtual oscillator, and the integral of the difference between the actual control angular frequency and the rated frequency is used as the angle of the Park transform. Based on the Park transformation, an abc / dq transformation is performed, with the voltage amplitude as the d-axis voltage reference and 0 as the q-axis voltage reference. After substituting the voltage and current dual closed loop, an inverter modulation wave drive signal is generated to achieve adaptive damping enhancement.

[0023] A second aspect of the present invention provides an adaptive feedforward damping enhancement system for a grid-type inverter.

[0024] An adaptive feedforward damping enhancement system for a grid-type inverter includes: The data acquisition module is configured to acquire the inverter's filter capacitor voltage and grid connection point current. The real-time power calculation module is configured to: calculate the real-time active power and reactive power based on the capacitor voltage and grid connection point current, and obtain the power difference value by subtracting it from the active power reference and reactive power reference respectively; The virtual oscillator reference generation module is configured to: input the reactive power difference into the voltage control dynamic equation of the virtual oscillator, and output a voltage amplitude reference signal based on the voltage response dynamics; input the active power difference into the angular frequency control dynamic equation of the virtual oscillator, and output a reference angular frequency based on the angular frequency response dynamics. The adaptive feedforward damping compensation module is configured to: construct an adaptive feedforward damping controller, send the active power reference into the adaptive feedforward damping controller, output the angular frequency compensation signal, and superimpose the basic angular frequency and the angular frequency compensation signal to obtain the actual control angular frequency. The dual-closed-loop modulation drive module is configured to input the actual control angular frequency and voltage amplitude reference into the voltage and current dual-closed-loop control to generate the inverter modulation wave to drive the power devices.

[0025] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of an adaptive feedforward damping enhancement method for a grid-type inverter as described in the first aspect of the present invention.

[0026] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the adaptive feedforward damping enhancement method for a grid-type inverter as described in the first aspect of the present invention.

[0027] The above one or more technical solutions have the following beneficial effects: (1) This invention decomposes the ideal feedforward damping controller into fixed control terms and adaptive terms. It uses lumped uncertainties to uniformly characterize the combined impact of line impedance changes and power cross-coupling on system damping, and employs a normalized gradient adaptive law with a correction term to update the feedforward damping coefficient online. This method can automatically track impedance changes and adjust the compensation amount in real time without needing to identify the specific value of the grid impedance online, maintaining the system damping ratio near the target value under a wide range of line impedance fluctuations. It achieves adaptive continuous compensation for impedance changes, fundamentally solving the damping offset problem of virtual oscillator grid-type inverters under weak grid and complex line conditions, and significantly broadening the system's stable operating domain.

[0028] (2) This invention employs a PD-type generalized error-driven adaptive parameter update. The PD generalized error can simultaneously sense the amplitude and trend of the tracking error, making the adjustment direction of the adaptive parameters more accurate and the adjustment action more rapid. During transient processes such as step changes in grid impedance or sudden changes in power command, the adaptive feedforward controller can respond quickly and smoothly adjust the compensation output, avoiding secondary impacts on the system caused by sudden changes in compensation. At the same time, the fixed control branch ensures the real-time performance of the basic compensation, while the adaptive branch supplements and corrects the fixed branch on a medium- to long-term time scale. The two work together to ensure that the system achieves a high damping ratio while maintaining a fast dynamic response, realizing the unity of damping enhancement and fast response.

[0029] (3) The adaptive feedforward damping controller of the present invention contains only two parallel channels: a fixed control branch and an adaptive branch. It does not require a complex online identification algorithm for grid impedance, nor does it require an additional high-order observer or state reconstructor. It can be discretized and deployed on a digital signal processor or microcontroller with only a few multiply-accumulate operations, resulting in a light computational burden, small memory footprint, and good real-time performance. At the same time, the present invention conducts a rigorous boundedness analysis of the error system based on Lyapunov stability theory. By constructing an energy function that includes state energy and parameter estimation error, it proves that both state error and parameter estimation error remain bounded under any bounded impedance change condition. The proposed adaptive feedforward damping enhancement method has strict stability guarantees in practical engineering applications.

[0030] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0031] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0032] Figure 1This is a flowchart of the method in the first embodiment.

[0033] Figure 2 The diagram shows the main circuit and control block diagram of the virtual oscillator grid-type inverter in the first embodiment.

[0034] Figure 3 This is the equivalent model of the virtual oscillator grid-type inverter in the first embodiment.

[0035] Figure 4 This is a block diagram of the small-signal model for inverter control in the first embodiment.

[0036] Figure 5 This is a control block diagram of an ideal feedforward controller for the first embodiment.

[0037] Figure 6 This is a schematic diagram of the discrete implementation of the feedforward adaptive damping enhancement method in the first embodiment.

[0038] Figure 7 This is a schematic diagram comparing the effects of the damping optimization method under different impedance conditions in the first embodiment.

[0039] Figure 8 This is a system structure diagram of the second embodiment. Detailed Implementation

[0040] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0041] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0042] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0043] Example 1 This embodiment discloses an adaptive feedforward damping enhancement method for grid-connected inverters. It characterizes the combined impact of grid impedance variations and power cross-coupling on damping through lumped uncertainties. The ideal feedforward damping controller is decomposed into fixed and adaptive control terms, and the control parameters are updated online using a normalized gradient adaptive law, thereby maintaining the target damping without estimating grid impedance. This method has a clear structure, is simple to implement in engineering, and can maintain the expected damping characteristics under different grid impedance conditions.

[0044] like Figure 1 As shown, an adaptive feedforward damping enhancement method for grid-type inverters includes: Step S1: Obtain the inverter's filter capacitor voltage and grid connection point current.

[0045] like Figure 2 As shown, the inverter topology adopts a three-phase grid-connected structure, and the voltage of the inverter's filter capacitor is acquired in real time. Three-phase grid connection point current and grid voltage The nominal grid-connected line impedance used in system model establishment , The inverter's main circuit and control parameters are shown in Table 1.

[0046] Table 1 Inverter main circuit and control parameters

[0047] Step S2: Calculate the real-time active power and reactive power based on the capacitor voltage and grid connection point current, and obtain the power difference value by subtracting it from the active power reference and reactive power reference respectively.

[0048] Specifically, the capacitor voltage obtained in step S1 and grid connection point current The dq-axis components are obtained through the Park transform. , , , The phase angle of the Park transform is obtained by integrating the angular frequency output by the virtual oscillator. The formulas for calculating real-time active power P and reactive power Q are:

[0049]

[0050] in, , These are the d-axis and q-axis components of the capacitor voltage; , These are the d-axis and q-axis components of the grid-connected current.

[0051] The calculated real-time active power P and reactive power Q are filtered out for high-frequency components by a low-pass filter, and then the difference between them and the active power reference and reactive power reference is calculated to obtain the power difference signal, which is used for subsequent virtual oscillator control.

[0052] Step S3: After inputting the reactive power difference into the voltage control dynamic equation of the virtual oscillator, the oscillator outputs a voltage amplitude reference signal based on the voltage response dynamics; after inputting the active power difference into the angular frequency control dynamic equation of the virtual oscillator, the oscillator outputs a reference angular frequency based on the angular frequency response dynamics.

[0053] In this embodiment, the virtual oscillator includes voltage control dynamic equations and angular frequency control dynamic equations. After substituting the real-time power calculation value and the power reference, reference signals for voltage and angular frequency can be generated based on the dynamic response, which serve as inputs for the voltage and current dual closed-loop control. The specific formulas are as follows:

[0054] in, The output voltage amplitude of the virtual oscillator. This is the output voltage reference value. For convergence speed, , These are the voltage and current amplification factors. For inverter power output, For reactive power reference, To output the phase angle, For the output angular frequency, This is the reference value for angular frequency. The output is the difference in active power after filtering. For the active power output of the inverter, For active power reference, For virtual inertia coefficient, For virtual oscillator capacitors; This is the derivative of the filtered active power difference output; To output the derivative of the phase angle; This is the derivative of the output voltage amplitude of the virtual oscillator.

[0055] To further analyze the damping characteristics and design an adaptive damping controller, a small-signal model of the inverter system is established. The small-signal model of the virtual oscillator control can be obtained by applying a small perturbation and linearization near the operating point, performing a Taylor series expansion, and neglecting higher-order terms:

[0056] in, Let be the open-loop transfer function of the active power of the virtual oscillator; For the capacitance parameters of the virtual oscillator; This represents the steady-state value of the output voltage of the virtual oscillator. Let be the open-loop transfer function of the reactive power of the virtual oscillator; This represents the steady-state value of the reactive power output by the inverter.

[0057] To establish a small-signal model of the inverter power flow, the inverter can be simplified to... Figure 3 The voltage source in the middle has a power output that satisfies:

[0058] in, The apparent power output of the inverter; The imaginary unit; For the angle of attack; This represents the magnitude of the grid impedance. The power grid impedance angle; The peak value of the grid-connected voltage e.

[0059] Similarly, by analyzing active and reactive power with respect to voltage... Harmony and angle Performing a Taylor series expansion near the operating point and ignoring higher-order terms, the small-signal model of the inverter power flow is obtained as follows:

[0060] in, This represents the small disturbance value of active power; This represents the small disturbance value of reactive power; This refers to the small-signal coefficient from active power to power angle; This represents the small-signal coefficient from reactive power to power angle; The small-signal coefficient is used to convert active power to voltage. This refers to the small-signal coefficient from reactive power to voltage. The small perturbation value of the work angle; This represents a small disturbance in the voltage. After substituting into the formula and solving, the matrix formula is obtained as follows:

[0061] From the above equation, it can be seen that the small-signal model of inverter power flow is related to the amplitude of grid impedance. and impedance angle Closely related; when the magnitude and impedance angle of the grid impedance change, the coefficients of the inverter's small-signal model... , , , This will result in corresponding nonlinear changes, which in turn will lead to a nonlinear shift in the system's damping performance.

[0062] In addition, through analysis Figure 4 According to the small-signal model of the grid-type inverter, the system damping characteristics are affected not only by path a, but also by the cross-coupling path b. The cross-coupling loop will further change the closed-loop damping characteristics.

[0063] Step S4: Construct an adaptive feedforward damping controller. Input the active power reference into the adaptive feedforward damping controller and output an angular frequency compensation signal. Superimpose the basic angular frequency and the angular frequency compensation signal to obtain the actual control angular frequency. As shown in step S3, the uncertainty in grid impedance will cause a significant shift in the system's damping response. Therefore, the system design objective should shift from damping design based on nominal parameters to maintaining the expected closed-loop damping characteristics under impedance variations. To describe the target dynamics, the desired system response can be equivalently represented by a second-order closed-loop transfer function. :

[0064] in, The natural frequency of the desired response; The damping ratio is the desired response. Under the ideal target damping characteristics, the ideal feedforward controller can be further derived. For example... Figure 5 As shown, the feedforward controller is positioned between the active power reference and the angular frequency channel to compensate for impedance uncertainties and damping offsets caused by power coupling. The adjusted small-signal model... for:

[0065] in, For a complex variable in the Laplace domain; For the open-loop transfer function of active power control of the virtual oscillator; Small disturbance values ​​for active power reference; The transfer function for the additional control channel; These are adaptively estimated parameters.

[0066] By eliminating variables, the closed-loop transfer function from the active power reference to the power output can be obtained. for:

[0067] To maintain the expected characteristics, an equivalent second-order closed-loop transfer function is used. and closed-loop transfer function The transfer function of the ideal feedforward controller with fixed coefficients is:

[0068] in, , which is a combination of coefficients, used here for simplification; each coefficient is determined by the virtual oscillator parameters, the power small-signal model parameters, and the target closed-loop damping parameters.

[0069] Based on the above process, although an ideal feedforward controller can compensate for damping characteristics, its parameters are difficult to maintain accuracy when the actual line impedance changes. Therefore, this embodiment employs adaptive parameter estimation. Replacing the actual uncertain parameters, and decomposing the feedforward controller into a fixed control term and an adaptive term, its transfer function is:

[0070] in, For the frequency domain transfer function of the adaptive feedforward controller; For complex variables in the Laplace transform; For fixed control items; For adaptive terms, For time-domain adaptive variables, The transfer function is fixed in the adaptive term; f(s) and q(s) are expressed as:

[0071]

[0072] in, , These are the voltage and current amplification factors; For complex variables in the Laplace transform; The damping ratio is the desired response. The natural frequency of the desired response; , represents a combination of coefficients, used here for simplified representation; This is the virtual inertia coefficient.

[0073] When estimated parameters are used, the output power of the feedforward controller is related to the expected system response. Tracking error of output power It can be represented as:

[0074] in, These are the parameters to be estimated; The error is the parameter to be estimated. The actual value of the parameter to be estimated.

[0075] The regression term function is It consists of a reference input, a system output, and fixed control terms. To ensure stability and accelerate convergence, a generalized error in PD form is further adopted:

[0076] Where λ is the generalized error gain, used to adjust the error dynamics. In the Laplace domain, the generalized error can be rewritten as:

[0077] in, The output is the generalized error; The derivative of the actual error; This represents the actual error. The frequency domain representation of the generalized error output; This is a frequency domain function relating the actual error and the error of the parameter to be estimated. It is the error between the parameter to be estimated and the actual value; , is the regression term; The error transfer function is the frequency domain function between the generalized error and the error of the parameter to be estimated. By reasonably selecting the parameter λ, the error transfer function can satisfy the strictly positive real characteristic, thus providing a basis for adaptive control law design and Lyapunov stability analysis.

[0078] Based on classical gradient adaptive control theory, the product of the generalized error and the regression term is selected as the adaptive driving term. To avoid excessively rapid updates and suppress parameter shifts under a wide range of parameter variations, a normalized adaptive law with e-correction is adopted:

[0079] in, For time-domain controller; This is an adaptive gain used to adjust the convergence speed of the parameters; These are the correction term coefficients, used to suppress parameter drift; For weighting functions; This represents the time-domain form of the regression term; This represents the time-domain form of the generalized error; These are the parameters to be estimated.

[0080] To avoid degradation of steady-state characteristics, the nonlinear weighting function is expressed as follows:

[0081] in, This is the expression for the weighting function; This is a critical value used to define the range of error effects and to reduce the impact of the correction term on steady-state performance in the small error region.

[0082] In practical engineering applications, its discretization implementation is as follows: Figure 6 As shown. The active power reference... The active power reference is fed into the adaptive controller via two paths: one path is fed into the reference model, i.e., the system's desired response model. Generating ideal active power After comparing with the actual power reference, the estimated parameters are generated through generalized error and adaptive law; another path is substituted into the fixed control term in the adaptive feedforward controller. and adaptive control terms This is used to construct an adaptive feedforward damping controller. After combining the above two items according to the formula of the adaptive feedforward damping controller's transfer function, the adaptive controller outputs an angular frequency compensation signal. The fundamental angular frequency With angular frequency compensation signal The actual control angular frequency is obtained by superposition. .

[0083] Step S5: The actual control angular frequency and voltage amplitude reference are fed into the voltage and current dual closed-loop control to generate the inverter modulation wave to drive the power device.

[0084] After combining this signal with the voltage amplitude signal V output by the virtual oscillator, the actual control angular frequency is... With rated frequency The integral of the difference, i.e., the phase angle of the virtual oscillator output. From the perspective of Park transform, using voltage amplitude V as the d-axis voltage reference and 0 as the q-axis voltage reference, we input... Figure 2 After the voltage and current dual closed loop shown, an inverter modulation wave drive signal is generated to achieve adaptive damping enhancement.

[0085] The parameter adjustment process can be summarized as follows: First, design the target reference model based on the expected damping and natural frequency; second, derive the fixed control term and adaptive term from the transfer function of the adaptive feedforward damping controller and implement them by discretization; then, set the upper and lower limits of the estimated parameters according to the expected damping variation range; finally, tune the adaptive gain and correction term coefficients in combination with the convergence speed, steady-state error and oscillation suppression requirements. The tuned parameters are shown in Table 2.

[0086] Table 2 Adaptive Control Parameters

[0087] Finally, a rigorous boundedness analysis of the error system was conducted based on Lyapunov stability theory.

[0088] The error propagation function can be rewritten as:

[0089] in, Let be the frequency domain function between the generalized error and the error of the parameter to be estimated; This is the transpose of the coefficient c; It is the identity matrix; The coefficients are the minimum realization coefficients of the transfer function.

[0090] Its minimum implementation can be expressed as:

[0091] in, The derivative of the least realized state variable; The input for the minimum implementation; The state variable is the minimum implementation.

[0092] The coefficient can be expressed as:

[0093] in, The coefficients of matrix A; The coefficients of matrix A; The coefficients of the generalized error and the state variables.

[0094] Since the error transfer function satisfies the strictly positive real condition, according to the Kalman-Yakubovich-Popv theorem, there exists Satisfying the following symmetric positive definite matrices:

[0095] Based on this, the boundedness of the proposed adaptive error system is further analyzed, and a Lyapunov function incorporating state energy and parameter estimation error is established:

[0096] in, Let Lyapunov be the function used for analysis.

[0097] By substituting the normalized adaptive law formula with e-correction and the symmetric positive definite matrix, the derivative of the Lyapunov function can be expressed as:

[0098] in, The derivative of the Lyapunov function; is the convergence rate coefficient, which is a positive number greater than zero.

[0099] After applying Young's inequality, the above factors satisfy the following condition:

[0100] in, The coefficient is greater than zero.

[0101] Define the error band as , This serves as an acceptable error range in the analysis. Due to the weighting function... It is non-negative, therefore there exists a boundary value of . .for The following inequalities are satisfied:

[0102] The two inequalities above give the boundaries of the fixed adaptive term and the leakage term. Substituting them into the following equation, we can obtain:

[0103] in, The coefficients of the inequality are greater than zero. This represents the lower limit of the weighting function.

[0104] By selecting parameters appropriately We can construct a fixed number of positive numbers such that the following inequality holds:

[0105] in, The generalized error correlation coefficient; The correlation coefficient for parameter estimation error; It is a fixed coefficient.

[0106] Therefore, the inequality satisfies:

[0107] Both the state error and parameter estimation error remain within bounded ranges, and the proposed adaptive feedforward damping enhancement method exhibits bounded stability in practical applications.

[0108] like Figure 7 As shown, the power step response of the fixed feedforward method, the additional channel method, and the method proposed in this invention are compared under five operating conditions. The method proposed in this invention can maintain the expected closed-loop damping characteristics without the need for line impedance information.

[0109] Example 2 This embodiment discloses an adaptive feedforward damping enhancement system for a grid-type inverter; like Figure 8 As shown, an adaptive feedforward damping enhancement system for a grid-type inverter includes: The data acquisition module is configured to acquire the inverter's filter capacitor voltage and grid connection point current. The real-time power calculation module is configured to: calculate the real-time active power and reactive power based on the capacitor voltage and grid connection point current, and obtain the power difference value by subtracting it from the active power reference and reactive power reference respectively; The virtual oscillator reference generation module is configured to: input the reactive power difference into the voltage control dynamic equation of the virtual oscillator, and output a voltage amplitude reference signal based on the voltage response dynamics; input the active power difference into the angular frequency control dynamic equation of the virtual oscillator, and output a reference angular frequency based on the angular frequency response dynamics. The adaptive feedforward damping compensation module is configured to: construct an adaptive feedforward damping controller, send the active power reference into the adaptive feedforward damping controller, output the angular frequency compensation signal, and superimpose the basic angular frequency and the angular frequency compensation signal to obtain the actual control angular frequency. The dual-closed-loop modulation drive module is configured to input the actual control angular frequency and voltage amplitude reference into the voltage and current dual-closed-loop control to generate the inverter modulation wave to drive the power devices.

[0110] Example 3 The purpose of this embodiment is to provide a computer-readable storage medium.

[0111] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in an adaptive feedforward damping enhancement method for a grid-type inverter as described in Example 1.

[0112] Example 4 The purpose of this embodiment is to provide an electronic device.

[0113] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the adaptive feedforward damping enhancement method for a grid-type inverter as described in Embodiment 1.

[0114] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0115] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0116] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for enhancing adaptive feedforward damping in a grid-type inverter, characterized in that, include: Obtain the inverter's filter capacitor voltage and grid connection point current; The real-time active power and reactive power are calculated based on the capacitor voltage and grid connection point current, and the power difference is obtained by subtracting them from the active power reference and reactive power reference, respectively. After inputting the reactive power difference into the voltage control dynamic equation of the virtual oscillator, the oscillator outputs a voltage amplitude reference signal based on the voltage response dynamics. After inputting the active power difference into the dynamic equation for angular frequency control of the virtual oscillator, the oscillator outputs a reference angular frequency based on the dynamic angular frequency response. An adaptive feedforward damping controller is constructed. The active power reference is fed into the adaptive feedforward damping controller, and the angular frequency compensation signal is output. The actual control angular frequency is obtained by superimposing the basic angular frequency and the angular frequency compensation signal. The actual control angular frequency and voltage amplitude reference are fed into the voltage and current dual closed-loop control to generate the inverter modulation wave to drive the power devices.

2. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The virtual oscillator includes voltage control dynamic equations and angular frequency control dynamic equations. After substituting the real-time power calculation value and the power reference, reference signals for voltage and angular frequency are generated based on the dynamic response, which serve as inputs for voltage and current dual closed-loop control. The formulas are shown below: in, The output voltage amplitude of the virtual oscillator. This is the output voltage reference value. For convergence speed, , These are the voltage and current amplification factors. For inverter power output, For reactive power reference, To output the phase angle, For the output angular frequency, This is the reference value for angular frequency. The output is the difference in active power after filtering. This refers to the active power output of the inverter. For active power reference, For virtual inertia coefficient, For virtual oscillator capacitors; This is the derivative of the filtered active power difference output; To output the derivative of the phase angle; This is the derivative of the output voltage amplitude of the virtual oscillator.

3. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The transfer function of the adaptive feedforward damping controller is: in, For the frequency domain transfer function of the adaptive feedforward controller; For complex variables in the Laplace transform; For fixed control items; For adaptive terms, For time-domain adaptive variables, This is the fixed transfer function in the adaptive term. f(s) and q(s) are expressed as: in, , These are the voltage and current amplification factors; For a complex variable in the Laplace domain; The damping ratio is the desired response. The natural frequency of the desired response; , represents a combination of coefficients, used here for simplified representation; This is the virtual inertia coefficient.

4. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The adaptive feedforward damping controller employs the form of PD generalized error to ensure the strict positive real condition and accelerate the convergence speed. Its specific implementation is as follows: Where λ is the generalized error coefficient; The output is the generalized error; The derivative of the actual error; This represents the actual error. The frequency domain representation of the generalized error output; This is a frequency domain function relating the actual error and the error of the parameter to be estimated. It is the error between the parameter to be estimated and the actual value; , is the regression term; It is the frequency domain function between the generalized error and the error of the parameter to be estimated.

5. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The adaptive term employs an adaptive gradient descent controller with e-correction and normalization capabilities, whose time-domain controller is expressed as: in, For time-domain controller; This is an adaptive gain used to adjust the convergence speed of the parameters; These are the correction term coefficients, used to suppress parameter drift; For weighting functions; This represents the time-domain form of the regression term; This represents the time-domain form of the generalized error; The parameter to be estimated; The nonlinear weighting function is expressed as: in, This is the expression for the weighting function; This is a critical value used to define the range of error effects and to reduce the impact of the correction term on steady-state performance in the small error region.

6. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The active power reference is fed into the adaptive feedforward damping controller, which outputs an angular frequency compensation signal. The actual control angular frequency is obtained by superimposing the fundamental angular frequency ω and the angular frequency compensation signal, including: The active power reference is fed into the adaptive controller. The active power reference enters the controller in two ways. One way generates the ideal active power through the system expected response model. After comparing it with the actual power reference, it is processed by the generalized error and adaptive law to generate the estimated parameters. Another path is used to substitute the fixed control term and the adaptive control term in the adaptive feedforward controller to construct an adaptive feedforward damping controller and output an angular frequency compensation signal. The actual control angular frequency is obtained by superimposing the fundamental angular frequency and the angular frequency compensation signal.

7. The adaptive feedforward damping enhancement method for a grid-type inverter as described in claim 1, characterized in that, The actual control angular frequency and voltage amplitude reference are fed into the voltage and current dual closed-loop control to generate the inverter modulation wave to drive the power devices, including: The actual control angular frequency is combined with the voltage amplitude signal output by the virtual oscillator, and the integral of the difference between the actual control angular frequency and the rated frequency is used as the angle of the Park transform. Based on the Park transformation, an abc / dq transformation is performed, with the voltage amplitude as the d-axis voltage reference and 0 as the q-axis voltage reference. After substituting the voltage and current dual closed loop, an inverter modulation wave drive signal is generated to achieve adaptive damping enhancement.

8. An adaptive feedforward damping enhancement system for a grid-type inverter, characterized in that, include: The data acquisition module is configured to acquire the inverter's filter capacitor voltage and grid connection point current. The real-time power calculation module is configured to: calculate the real-time active power and reactive power based on the capacitor voltage and grid connection point current, and obtain the power difference value by subtracting it from the active power reference and reactive power reference respectively; The virtual oscillator reference generation module is configured to: input the reactive power difference into the voltage control dynamic equation of the virtual oscillator, and then, based on the voltage response dynamics, output a voltage amplitude reference signal from the oscillator. After inputting the active power difference into the dynamic equation for angular frequency control of the virtual oscillator, the oscillator outputs a reference angular frequency based on the dynamic angular frequency response. The adaptive feedforward damping compensation module is configured to: construct an adaptive feedforward damping controller, send the active power reference into the adaptive feedforward damping controller, output the angular frequency compensation signal, and superimpose the basic angular frequency and the angular frequency compensation signal to obtain the actual control angular frequency. The dual-closed-loop modulation drive module is configured to input the actual control angular frequency and voltage amplitude reference into the voltage and current dual-closed-loop control to generate the inverter modulation wave to drive the power devices.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the adaptive feedforward damping enhancement method for a grid-type inverter as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the adaptive feedforward damping enhancement method for a grid-type inverter as described in any one of claims 1-7.

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