Grid-connected system stability margin online estimation method, system, equipment and medium

Abstract

The invention belongs to the technical field of new energy development, and discloses a grid-connected system stability margin online estimation method, system and device and a medium, and the online estimation method comprises the steps: analyzing a transfer function of each control link of a network construction type converter grid-connected system, and obtaining a control mechanism of the network construction type converter grid-connected system; constructing a network construction type station grid-connected system model; the method comprises the following steps: operating a grid-building type station grid-connected system model, and observing an active and / or reactive curve waveform; and performing oscillation mode parameter extraction on the response waveform data sequence by using a high-resolution spectrum estimation algorithm, determining a dominant oscillation mode of the grid-connected system of the network-building type converter, and evaluating the stability margin of the grid-connected system of the network-building type converter by calculating the damping ratio of the grid-connected system of the network-building type converter. According to the method, the stability margin evaluation of the small interference oscillation of the grid-connected system of the network construction type current converter can be effectively realized, so that the stability problem of the grid-connected system of the network construction type current converter can be guided and analyzed.

Description

Technical Field

[0001] The present invention relates to the field of new energy development technology, and in particular to an online estimation method, system, equipment and medium for stability margin of a grid-connected system. Background Art

[0002] In order to cope with global climate challenges, the integration of new energy into the power system has become a new development trend. Its grid connection requires connection to the grid through power electronic converters. However, the internal parameters of the converter involve commercial secrets, and its internal structure cannot be fully understood. It is difficult to obtain accurate internal parameters in actual engineering, which makes stability margin analysis difficult. The commonly used oscillation stability analysis methods are mainly characteristic analysis method and impedance analysis method, but both face some difficulties.

[0003] The characteristic analysis method needs to build a system state space model and judge the system stability according to the characteristics of the system characteristic root. However, the establishment of the state space model requires the internal parameters of the converter, which is difficult to obtain for the "black box" problem of the corresponding structure. The impedance analysis method is based on the established impedance model and performs stability analysis through the generalized Nyquist stability criterion, but its application requires full-band oscillation data. At the same time, the noise in actual engineering will lead to inaccurate stability analysis, and it is more difficult to analyze high-dimensional systems. In actual engineering, it faces the problems of low practicality and difficulty in application.

[0004] Therefore, how to provide a method, system, device and medium for online estimation of the stability margin of a grid-connected system is a problem that needs to be solved urgently. Summary of the invention

[0005] The embodiments of the present invention provide a method, system, device and medium for online estimation of stability margin of a grid-connected system to solve the problems in the prior art.

[0006] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0007] According to a first aspect of an embodiment of the present invention, a method for online estimating stability margin of a grid-connected system is provided.

[0008] In one embodiment, a method for online estimating a grid-connected system stability margin includes:

[0009] Analyze the transfer functions of each control link of the grid-connected converter system to obtain the control mechanism of the grid-connected converter system; and construct a grid-connected station system model based on the control mechanism of the grid-connected converter system;

[0010] The grid-connected system model of the grid-forming station is run in a simulation manner, and a pulse signal is applied at a current reference of the grid-forming station grid-connected system model, and a response waveform data sequence is obtained by observing active and / or reactive curve waveforms;

[0011] A high-resolution spectral estimation algorithm is used to extract the oscillation modal parameters of the response waveform data sequence to determine the dominant oscillation mode of the grid-connected converter system. Based on the dominant oscillation mode of the grid-connected converter system, the stability margin of the grid-connected converter system is evaluated by calculating the damping ratio of the grid-connected converter system.

[0012] In one embodiment, the grid-connected system model of the grid-connected station is run in a simulation manner, and a pulse signal is applied at the current reference of the grid-connected system model of the grid-connected station, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, including:

[0013] By simulating and running the grid-connected system model of the grid-building type station, the active curve waveform and reactive curve waveform of the grid-building type station grid-connected system model when running under the preset time length are recorded; and the maximum frequency of the grid-building type station grid-connected system model is determined;

[0014] Based on Shannon sampling theorem, the sampling frequency of the response waveform data is calculated according to the maximum frequency of the grid-connected system model of the grid-type station;

[0015] The response waveform data is sampled according to the sampling frequency of the response waveform data to obtain a response waveform data sequence.

[0016] In one embodiment, the calculation formula for calculating the sampling frequency of the response waveform data according to the maximum frequency of the grid-connected system model of the grid-connected station is:

[0017] f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )]

[0018] f smin =2πf imax / (π / 2)=4f imax ;

[0019] In the formula, f s represents the sampling frequency, f i represents the frequency of each component constituting the original waveform, Δt represents the sampling interval, and Im represents the sampling time. i Imaginary part value, Re means taking z i Real value, z iRepresents the complex value representing the decaying cosine component in the discrete time model of the sampling point estimate, f smin Indicates the minimum value of the sampling frequency, f imax Indicates the maximum value of the sampling frequency.

[0020] In one embodiment, the method of extracting oscillation mode parameters from the response waveform data sequence using a high-resolution spectrum estimation algorithm, determining the dominant oscillation mode of the grid-connected converter system, and evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system comprises:

[0021] constructing a number of discrete-time sample function models according to the response waveform data sequence, and constructing a sample function matrix according to the number of discrete-time sample function models;

[0022] The effective order is determined by using the total least squares method of singular value decomposition, and the estimated value of the sampling point is obtained by solving the characteristic root;

[0023] Determine the parameter vector according to the estimated value of the sampling point obtained, and calculate the oscillation mode parameter using the oscillation mode parameter calculation formula;

[0024] The parameter group with the smallest absolute value of the attenuation factor in the oscillation mode parameters is selected as the dominant oscillation mode, and the damping ratio of the grid-connected system of the grid-connected converter is calculated by the damping ratio calculation formula;

[0025] The stability margin of the grid-connected system of the grid-connected converter is evaluated according to the damping of the grid-connected system of the grid-connected converter, and an evaluation result is obtained.

[0026] In one embodiment, the oscillation modal parameter calculation formula is:

[0027]

[0028] In the formula, A i represents the amplitude, b i represents the reference vector, θ i represents the phase, α i represents the attenuation factor, f i represents the frequency of each component, Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete-time model of the sample point estimate.

[0029] In one embodiment, the damping ratio calculation formula is:

[0030]

[0031] Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

[0032] In one embodiment, the evaluation of the stability margin of the grid-connected converter system according to the grid-connected converter system damping to obtain the evaluation result includes:

[0033] If the grid-connected system damping of the grid-connected converter is less than zero, it means that the grid-connected system of the grid-connected converter is in an unstable state;

[0034] If the grid-connected system damping of the grid-connected converter is equal to zero, it means that the grid-connected system of the grid-connected converter is in a critical stable state;

[0035] If the grid-connected system damping of the grid-connected converter is greater than zero, it means that the grid-connected converter system is in a critical stable state.

[0036] According to a second aspect of an embodiment of the present invention, a grid-connected system stability margin online estimation system is provided.

[0037] In one embodiment, a grid-connected system stability margin online estimation system includes:

[0038] A model building module analyzes the transfer functions of each control link of the grid-connected converter system to obtain the control mechanism of the grid-connected converter system; and builds a grid-connected station system model based on the control mechanism of the grid-connected converter system;

[0039] The waveform data acquisition module runs the grid-connected system model of the grid-building type station by simulation, applies a pulse signal at the current reference of the grid-building type station grid-connected system model, and obtains a response waveform data sequence by observing the active and / or reactive curve waveforms;

[0040] The stability assessment module uses a high-resolution spectrum estimation algorithm to extract the oscillation modal parameters of the response waveform data sequence, determines the dominant oscillation mode of the grid-connected converter system, and evaluates the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system.

[0041] In one embodiment, the grid-connected system model of the grid-connected station is run in a simulation manner, and a pulse signal is applied at the current reference of the grid-connected system model of the grid-connected station, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, including:

[0042] By simulating and running the grid-connected system model of the grid-building type station, the active curve waveform and reactive curve waveform of the grid-building type station grid-connected system model when running under the preset time length are recorded; and the maximum frequency of the grid-building type station grid-connected system model is determined;

[0043] Based on Shannon sampling theorem, the sampling frequency of the response waveform data is calculated according to the maximum frequency of the grid-connected system model of the grid-type station;

[0044] The response waveform data is sampled according to the sampling frequency of the response waveform data to obtain a response waveform data sequence.

[0045] In one embodiment, the calculation formula for calculating the sampling frequency of the response waveform data according to the maximum frequency of the grid-connected system model of the grid-connected station is:

[0046] f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )]

[0047] f smin =2πf imax / (π / 2)=4f imax ;

[0048] In the formula, f s represents the sampling frequency, f i represents the frequency of each component constituting the original waveform, Δt represents the sampling interval, and Im represents the sampling time. i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete time model of the sampling point estimate, f smin Indicates the minimum value of the sampling frequency, f imax Indicates the maximum value of the sampling frequency.

[0049] In one embodiment, the method of extracting oscillation mode parameters from the response waveform data sequence using a high-resolution spectrum estimation algorithm, determining the dominant oscillation mode of the grid-connected converter system, and evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system comprises:

[0050] constructing a number of discrete-time sample function models according to the response waveform data sequence, and constructing a sample function matrix according to the number of discrete-time sample function models;

[0051] The effective order is determined by using the total least squares method of singular value decomposition, and the estimated value of the sampling point is obtained by solving the characteristic root;

[0052] Determine the parameter vector according to the estimated value of the sampling point obtained, and calculate the oscillation mode parameter using the oscillation mode parameter calculation formula;

[0053] The parameter group with the smallest absolute value of the attenuation factor in the oscillation mode parameters is selected as the dominant oscillation mode, and the damping ratio of the grid-connected system of the grid-connected converter is calculated by the damping ratio calculation formula;

[0054] The stability margin of the grid-connected system of the grid-connected converter is evaluated according to the damping of the grid-connected system of the grid-connected converter, and an evaluation result is obtained.

[0055] In one embodiment, the oscillation modal parameter calculation formula is:

[0056]

[0057] In the formula, A i represents the amplitude, b i represents the reference vector, θ i represents the phase, α i represents the attenuation factor, f i represents the frequency of each component, Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary value, Re represents z i Its actual value, z i Represents the complex value representing the decaying cosine component in the discrete-time model of the sample point estimate.

[0058] In one embodiment, the damping ratio calculation formula is:

[0059]

[0060] Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

[0061] In one embodiment, the evaluation of the stability margin of the grid-connected converter system according to the grid-connected converter system damping to obtain the evaluation result includes:

[0062] If the grid-connected system damping of the grid-connected converter is less than zero, it means that the grid-connected system of the grid-connected converter is in an unstable state;

[0063] If the grid-connected system damping of the grid-connected converter is equal to zero, it means that the grid-connected system of the grid-connected converter is in a critical stable state;

[0064] If the grid-connected system damping of the grid-connected converter is greater than zero, it means that the grid-connected converter system is in a critical stable state.

[0065] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0066] In some embodiments, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0067] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0068] In one embodiment, the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0069] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0070] The present invention ignores the parameter analysis inside the grid-connected converter system, analyzes the system stability through an online estimation method, applies a small disturbance to the reference signal at the control end based on the grid-connected converter system model, records the waveforms of active power and reactive power in the power grid, extracts the dominant eigenvalues ​​of the oscillation through a high-resolution spectrum estimation algorithm, and then calculates the damping ratio for stability margin evaluation. There is no need to pay attention to the internal parameters of the converter, and a method is provided for analyzing the stability problem of the grid-connected converter system. The stability margin evaluation of the small disturbance oscillation of the grid-connected converter system can be effectively realized, thereby guiding the analysis of the stability problem of the grid-connected converter system.

[0071] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0073] Figure 1 is a flow chart showing a method for online estimation of stability margin of a grid-connected system according to an exemplary embodiment;

[0074] Figure 2 is a principle block diagram of an online estimation system for stability margin of a grid-connected system according to an exemplary embodiment;

[0075] Figure 3 is a control structure diagram of a grid-connected system of a grid-connected converter in an online estimation method of a grid-connected system stability margin according to an exemplary embodiment;

[0076] Figure 4 A flowchart of extracting oscillation parameters by expanding the prony algorithm in an online estimation method for a grid-connected system stability margin according to an exemplary embodiment;

[0077] Figure 5 is a flow chart of stability margin evaluation in an online estimation method for stability margin of a grid-connected system according to an exemplary embodiment;

[0078] Figure 6 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0079] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0080] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0081] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0082] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0083] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0084] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0085] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0086] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0087] Figure 1 An embodiment of the grid-connected system stability margin online estimation method of the present invention is shown.

[0088] In this optional embodiment, the grid-connected system stability margin online estimation method includes:

[0089] Step S101, analyzing the transfer functions of each control link of the grid-connected converter system to obtain the control mechanism of the grid-connected converter system; and constructing a grid-connected station system model according to the control mechanism of the grid-connected converter system;

[0090] Step S103, running the grid-connected system model of the grid-forming station in a simulation manner, applying a pulse signal at the current reference of the grid-forming station grid-connected system model, and obtaining a response waveform data sequence by observing the active and / or reactive curve waveforms;

[0091] Step S105, using a high-resolution spectrum estimation algorithm (extended prony algorithm) to extract oscillation modal parameters of the response waveform data sequence, determine the dominant oscillation mode of the grid-connected converter system, and based on the dominant oscillation mode of the grid-connected converter system, evaluate the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system.

[0092] In this optional embodiment, when the grid-connected system model of the grid-connected station is run in a simulation manner, a pulse signal is applied at the current reference of the grid-connected system model of the grid-connected station, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, the grid-connected system model of the grid-connected station can be simulated and run to record the active curve waveform and reactive curve waveform of the grid-connected system model of the grid-connected station under a preset time length; and the maximum frequency of the grid-connected system model of the grid-connected station is determined; based on the Shannon sampling theorem, the sampling frequency of the response waveform data is calculated according to the maximum frequency of the grid-connected system model of the grid-connected station; according to the sampling frequency of the response waveform data, the response waveform data is sampled to obtain a response waveform data sequence.

[0093] In this optional embodiment, when extracting oscillation modal parameters from the response waveform data sequence using a high-resolution spectrum estimation algorithm to determine the dominant oscillation mode of the grid-connected converter system, and based on the dominant oscillation mode of the grid-connected converter system, evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system, a number of discrete-time sample function models can be constructed according to the response waveform data sequence, and a sample function matrix can be constructed according to the number of discrete-time sample function models; the effective order is determined using the singular value decomposition total least squares method, and the estimated value of the sampling point is obtained by solving the characteristic root; the parameter vector is determined according to the obtained estimated value of the sampling point, and the oscillation modal parameter calculation formula is used to calculate the oscillation modal parameter; the parameter group with the smallest absolute value of the attenuation factor in the oscillation modal parameter is selected as the dominant oscillation mode, and the damping ratio of the grid-connected converter system is calculated by the damping ratio calculation formula; the stability margin of the grid-connected converter system is evaluated according to the damping of the grid-connected converter system to obtain an evaluation result.

[0094] In this optional embodiment, the stability margin of the grid-connected converter grid-connected system is evaluated according to the damping of the grid-connected converter grid-connected system, and the evaluation results include: if the damping of the grid-connected converter grid-connected system is less than zero, it means that the grid-connected converter grid-connected system is in an unstable state; if the damping of the grid-connected converter grid-connected system is equal to zero, it means that the grid-connected converter grid-connected system is in a critical stable state; if the damping of the grid-connected converter grid-connected system is greater than zero, it means that the grid-connected converter grid-connected system is in a critical stable state.

[0095] In order to facilitate understanding of the above technical solutions of the present invention, the above technical solutions of the present invention are further described below from the perspective of architecture and principle, as follows:

[0096] Step 1: Build a grid-connected system model;

[0097] At present, common grid-forming control methods include droop control, virtual synchronous machine and virtual oscillator control. Droop control can be regarded as a virtual synchronous machine with a virtual inertia of 0. Without loss of generality, the grid-forming converter model of virtual synchronous control is considered and analyzed. The control structure is as follows: Figure 3 shown.

[0098] Figure 3 In the figure, a, b, and c are the three-phase form of the power system abc, dq represents the value of each parameter after conversion to the dq axis, PWM is pulse width modulation, P is active power, Q is reactive power, U and I are the voltage and current output by the converter, and U g ,I g Subscript g indicates network side parameters, U C Represents the capacitor side voltage, P E , Q E It represents the active and reactive power actually output by the converter, P0 represents the command active power used for regulation, w0 represents the angular frequency, J represents the moment of inertia, D represents the damping coefficient, and ref represents the reference value.

[0099] Among them, the outer loop of GFM is the voltage control loop, and the dynamic equation is as follows:

[0100]

[0101] In the formula, I d ref and I q ref Indicates the current reference value, and Indicates the voltage reference value, U Cd and U Cq represents the capacitor side voltage, ω0 represents the synchronous speed of the AC power grid, C F Represents the machine-side capacitance of the filter, K F Represents the current feed-forward coefficient, I gd and I gq Indicates the injected AC grid current, PI vc (s) represents the transfer function of the PI regulator in the current control loop.

[0102] The inner loop of GFM is the current control loop, and the dynamic equation is as follows:

[0103]

[0104] Where U d and U q Represent the d-axis and q-axis values ​​of the converter output voltage, I d and I q They represent the d-axis and q-axis values ​​of the converter output current, respectively. F Indicates the machine side inductance, PIcc (s) represents the transfer function of the PI regulator in the current control loop, f vf (s) represents the transfer function of the first-order filter used to eliminate high-frequency components in voltage feedforward.

[0105] The dynamic equation of the LCL filter is as follows:

[0106]

[0107] In the formula, represents the converter output voltage, Represents the capacitor side voltage, represents the inverter output current, Indicates the grid side current, Indicates the grid side voltage, L g Indicates the grid-side inductance, L F represents the machine-side inductance, s represents the Laplace operator, ω represents the output angular frequency, and j represents the imaginary unit.

[0108] Specifically, the grid-connected converter achieves grid synchronization through the virtual rotor motion equation, and the dynamic equation is:

[0109]

[0110] In the formula, θ represents the output phase angle, J represents the inertia parameter, s represents the Laplace operator, D represents the damping parameter, P0 represents the steady-state value of the output power, and P E Indicates the active power value of the converter output. In addition, Q E Indicates the reactive power value of the converter output, P E and Q E The calculation formula is as follows:

[0111] P E =U Cd I gd +U Cq I gq

[0112] Q E =U Cq I gd -U Cd I gq ;

[0113] According to the above control equation, the system model is established in Matlab / Simulink. After running, the corresponding P and Q waveforms are recorded, the duration is more than 3 times the oscillation period, and the maximum frequency is preliminarily determined. The waveform data is sampled at equal intervals as the data sequence of the high-resolution spectrum estimation algorithm, recorded as x(0), x(1), ..., x(N-1).

[0114] In order to obtain the small interference oscillation waveform of the grid-connected system of the grid-connected converter, a pulse signal with an amplitude of 0.1pu and a duration of 0.1s is applied at the current reference value at 3s after the grid-connected system runs stably.

[0115] The sampling frequency setting method is as follows:

[0116] The accuracy of the prony algorithm fitting result is closely related to the selection of parameters. Improper parameter selection will lead to insufficient fitting accuracy or erroneous results. The model effective order and sampling frequency are the two most important parameters that play a decisive role in the algorithm fitting result. Since the present invention adopts a high-resolution spectrum estimation algorithm, the model effective order has been automatically determined by the SVD-TLS (singular value decomposition total least squares method), so the main discussion is about the setting of the sampling frequency.

[0117] The sampling frequency should first satisfy Shannon sampling theorem, that is, f s >2f imax , refers to the highest frequency of the signal. At the same time, according to the frequency of each component f i The calculation formula for calculating the sampling frequency is:

[0118] f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )]

[0119] f smin =2πf imax / (π / 2)=4f imax ;

[0120] In the formula, f s represents the sampling frequency, f i Represents the frequency of each component. Combining the two, it can be concluded that the minimum value of the sampling frequency is 4f imax However, as the sampling frequency increases, the fitting characteristics of the oscillation waveform show an overall trend from bad to good and then from good to bad, and the optimal sampling frequency range is often between 4 times and more than ten times the maximum frequency.

[0121] Step 2: After obtaining the waveform data, use the high-resolution spectrum estimation algorithm to extract the oscillation parameters. The original data sequence of the signal to be analyzed after equal-interval sampling is x(0), x(1), ..., x(N-1). The extended prony method estimates the sequence in the form of a combination of a set of p exponential functions with arbitrary amplitude, phase, frequency and attenuation factor. The estimated value is used as the model of the original data sequence. The function form of the discrete time model of the sampling point estimate is:

[0122]

[0123] In the formula, Represents the estimated value of the nth sampling point, A m represents the amplitude, b m represents the reference vector, θ m represents the phase, α m represents the attenuation factor, f m Represents the frequency of each component, Δt represents the sampling interval, m represents the number of each component, n represents the nth sampling point, N represents the total number of sampling points, and j represents the imaginary unit.

[0124] The main work of the prony algorithm is to solve {A m ,θ m ,α m ,f m}, studying the discrete time function form, we can find that it is a homogeneous solution of a linear difference equation with constant coefficients. To solve the linear difference equation, we need to estimate the value This satisfies the recursive difference equation:

[0125]

[0126] In the formula, m represents the number of each component.

[0127] Define the error e(n) as the difference between the actual data x(n) and the estimated value The difference is:

[0128]

[0129] Substituting the difference equation into the difference formula yields:

[0130]

[0131] Where ε(n) represents the equivalent error.

[0132] Attenuation parameters α1, α2, …, α p The least squares estimate of Minimum, and transform it into solving α i Value makes Minimum, let The matrix can be obtained:

[0133]

[0134] To make Minimum, order:

[0135]

[0136] In the formula, the symbol * represents conjugation.

[0137] We can get:

[0138]

[0139] definition:

[0140]

[0141] Where r(i,j) represents the value of the element in the i-th row and j-th column of the corresponding matrix.

[0142] but Can be rewritten as:

[0143]

[0144] Solving the above equation, we can get α1, α2, …, α p and ε p The estimated value of , the characteristic equation is as follows:

[0145]

[0146] Right now:

[0147]

[0148] Φ represents the N×p-dimensional Vandermonde determinant, which is non-singular, so the solution for the parameter vector b is:

[0149]

[0150] In the formula, H represents the conjugate transpose. After obtaining the parameter b, the amplitude A can be obtained by the oscillation modal parameter calculation formula: i , phase θ i , attenuation factor α i , frequency f i The calculation formula of oscillation modal parameters is:

[0151]

[0152] Step 3: Damping ratio calculation and stability margin analysis;

[0153] According to the parameters of each oscillation mode extracted by the high-resolution spectrum estimation algorithm, the smaller the absolute value of the attenuation factor, the slower the corresponding oscillation attenuation, so the set of results with the smallest absolute value of the attenuation factor is taken as the dominant oscillation mode. The damping ratio of the system is calculated based on the corresponding parameters of the dominant oscillation mode to evaluate the stability margin. The damping ratio calculation method is as follows:

[0154]

[0155] Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

[0156] The damping ratio reflects the dynamic response characteristics of the system after being subjected to a small disturbance. When ξ<, the system is in an unstable state; when ξ=0, the system is in a critical stable state; when ξ>0, the system is in a stable state, and the larger the ξ, the stronger the system damping, and the easier it is to recover to a balanced state when dealing with the same small disturbance, and the greater the stability margin of the system. Therefore, the stability margin of the system can be evaluated by the size of the dominant mode damping ratio. The present invention provides an effective method for analyzing the stability of the grid-connected system of the grid-connected converter.

[0157] For example, according to the parameter value settings in Table 1 and the model structure described in the first part, the grid-connected inverter system model is built in Matlab / Simulink software.

[0158] Table 1 Parameter values ​​of some system variables in the implementation example simulation verification

[0159]

[0160] An application example analysis is performed by taking the case of changing the damping parameter D to 20 and 25 respectively. After the model runs stably, a pulse signal with an amplitude of 0.1pu (pu represents per-unit value) and a duration of 0.1s is applied at the current reference value at 3s to obtain the output active and reactive power waveforms. The active power P waveform is taken as an example below. A high-resolution spectrum estimation algorithm is used to extract parameters of the corresponding waveforms, and then the group with the smallest absolute value of the attenuation factor is taken as the dominant mode based on the obtained data, and the corresponding damping ratio is calculated to achieve the estimation of the stability margin. The specific data are shown in Tables 2 and 3. It can be seen that when the damping parameter D decreases, the corresponding dominant mode damping ratio decreases accordingly, and the stability margin decreases. The effectiveness of the present invention is demonstrated through the above application examples.

[0161] Table 2 Oscillation data when D=25

[0162]

[0163] Table 3 Oscillation data when D=20

[0164]

[0165] Figure 2 An embodiment of the grid-connected system stability margin online estimation system of the present invention is shown.

[0166] In this optional embodiment, the grid-connected system stability margin online estimation system includes:

[0167] The model building module 201 analyzes the transfer functions of each control link of the grid-connected converter system to obtain the control mechanism of the grid-connected converter system; and builds a grid-connected station system model according to the control mechanism of the grid-connected converter system;

[0168] The waveform data acquisition module 203 runs the grid-connected system model of the grid-building type station by simulation, applies a pulse signal at the current reference of the grid-building type station grid-connected system model, and obtains a response waveform data sequence by observing the active and / or reactive curve waveforms;

[0169] The stability assessment module 205 uses a high-resolution spectrum estimation algorithm to extract oscillation mode parameters of the response waveform data sequence, determines the dominant oscillation mode of the grid-connected inverter system, and evaluates the stability margin of the grid-connected inverter system by calculating the damping ratio of the grid-connected inverter system based on the dominant oscillation mode of the grid-connected inverter system.

[0170] In this optional embodiment, the grid-connected system model of the grid-connected station is run in a simulation manner, and a pulse signal is applied at the current reference of the grid-connected system model of the grid-connected station, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, including:

[0171] By simulating and running the grid-connected system model of the grid-forming station, the active curve waveform and the reactive curve waveform of the grid-connected system model of the grid-forming station are recorded during the operation of the grid-connected system model of the grid-forming station under a preset time length; and the maximum frequency of the grid-connected system model of the grid-forming station is determined; based on the Shannon sampling theorem, and according to the maximum frequency of the grid-connected system model of the grid-forming station, the sampling frequency of the response waveform data is calculated; according to the sampling frequency of the response waveform data, the response waveform data is sampled to obtain a response waveform data sequence.

[0172] In this optional embodiment, the calculation formula for calculating the sampling frequency of the response waveform data according to the maximum frequency of the grid-connected system model of the grid-forming station is:

[0173] f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )]

[0174] f smin =2πf imax / (π / 2)=4f imax ;

[0175] In the formula, f s represents the sampling frequency, f irepresents the frequency of each component constituting the original waveform (the original waveform can be extracted into a set of attenuated sinusoidal components by the prony algorithm of the present invention, f i That is, it represents the different component frequencies), Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete time model of the sampling point estimate, f smin Indicates the minimum value of the sampling frequency, f imax Indicates the maximum value of the sampling frequency.

[0176] In this optional embodiment, the method of extracting oscillation mode parameters from the response waveform data sequence using a high-resolution spectrum estimation algorithm to determine the dominant oscillation mode of the grid-connected converter system, and evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system includes:

[0177] According to the response waveform data sequence, several discrete-time sample function models are constructed, and according to the several discrete-time sample function models, a sample function matrix is ​​constructed; the effective order is determined by using the singular value decomposition total least squares method, and the estimated value of the sampling point is obtained by solving the characteristic root; the parameter vector is determined according to the obtained estimated value of the sampling point, and the oscillation modal parameter is calculated by using the oscillation modal parameter calculation formula; the parameter group with the smallest absolute value of the attenuation factor in the oscillation modal parameter is selected as the dominant oscillation mode, and the damping ratio of the grid-connected system of the grid-connected converter is calculated by the damping ratio calculation formula; the stability margin of the grid-connected system of the grid-connected converter is evaluated according to the damping of the grid-connected system of the grid-connected converter, and an evaluation result is obtained.

[0178] In this optional embodiment, the oscillation modal parameter calculation formula is:

[0179]

[0180] In the formula, A i represents the amplitude, b i represents the reference vector, θ i represents the phase, α i represents the attenuation factor, f i represents the frequency of each component, Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete-time model of the sample point estimate.

[0181] In this optional embodiment, the damping ratio calculation formula is:

[0182]

[0183] Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

[0184] In this optional embodiment, the stability margin of the grid-connected converter system is evaluated according to the damping of the grid-connected converter system, and the evaluation result obtained includes:

[0185] If the damping of the grid-connected converter system is less than zero, it means that the grid-connected converter system is in an unstable state; if the damping of the grid-connected converter system is equal to zero, it means that the grid-connected converter system is in a critical stable state; if the damping of the grid-connected converter system is greater than zero, it means that the grid-connected converter system is in a critical stable state.

[0186] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0187] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0188] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0189] In addition, the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0190] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0191] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for online estimation of grid-connected system stability margin, characterized in that: include: Analyze the transfer functions of each control link of the grid-connected converter system, and obtain the control mechanism of the grid-connected converter system; And according to the control mechanism of the grid-connected converter system, a grid-connected station system model is constructed; The grid-connected system model of the grid-forming station is run in a simulation manner, and a pulse signal is applied at a current reference of the grid-forming station grid-connected system model, and a response waveform data sequence is obtained by observing active and / or reactive curve waveforms; A high-resolution spectral estimation algorithm is used to extract the oscillation modal parameters of the response waveform data sequence to determine the dominant oscillation mode of the grid-connected converter system. Based on the dominant oscillation mode of the grid-connected converter system, the stability margin of the grid-connected converter system is evaluated by calculating the damping ratio of the grid-connected converter system.

2. The method for online estimation of grid-connected system stability margin according to claim 1, characterized in that: The grid-connected system model of the grid-forming station is run in a simulation manner, and a pulse signal is applied at the current reference of the grid-forming station grid-connected system model, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, including: By simulating and running the grid-connected system model of the grid-building type station, the active curve waveform and reactive curve waveform of the grid-building type station grid-connected system model when running under the preset time length are recorded; and the maximum frequency of the grid-building type station grid-connected system model is determined; Based on Shannon sampling theorem, the sampling frequency of the response waveform data is calculated according to the maximum frequency of the grid-connected system model of the grid-type station; The response waveform data is sampled according to the sampling frequency of the response waveform data to obtain a response waveform data sequence.

3. The method for online estimation of grid-connected system stability margin according to claim 2, characterized in that: The calculation formula for calculating the sampling frequency of the response waveform data according to the maximum frequency of the grid-connected system model of the grid-connected station is: f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )] f smin =2πf imax / (π / 2)=4f imax ; In the formula, f s represents the sampling frequency, f i represents the frequency of each component constituting the original waveform, Δt represents the sampling interval, Im(z i ) means taking z i The imaginary part value, Re(z i ) means taking z i The real part of z i Represents the complex value representing the decaying cosine component in the discrete time model of the sampling point estimate, f smin Indicates the minimum value of the sampling frequency, f imax Indicates the maximum value of the sampling frequency.

4. The method for online estimation of grid-connected system stability margin according to claim 1, characterized in that: The method of extracting oscillation mode parameters from the response waveform data sequence using a high-resolution spectrum estimation algorithm, determining the dominant oscillation mode of the grid-connected converter system, and evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system comprises the following steps: constructing a number of discrete-time sample function models according to the response waveform data sequence, and constructing a sample function matrix according to the number of discrete-time sample function models; The effective order is determined by using the total least squares method of singular value decomposition, and the estimated value of the sampling point is obtained by solving the characteristic root; Determine the parameter vector according to the estimated value of the sampling point obtained, and calculate the oscillation mode parameter using the oscillation mode parameter calculation formula; The parameter group with the smallest absolute value of the attenuation factor in the oscillation mode parameters is selected as the dominant oscillation mode, and the damping ratio of the grid-connected system of the grid-connected converter is calculated by the damping ratio calculation formula; The stability margin of the grid-connected system of the grid-connected converter is evaluated according to the damping of the grid-connected system of the grid-connected converter, and an evaluation result is obtained.

5. The method for online estimation of grid-connected system stability margin according to claim 4, characterized in that: The oscillation modal parameter calculation formula is: In the formula, A i represents the amplitude, b i represents the reference vector, θ i represents the phase, α i represents the attenuation factor, f i represents the frequency of each component, Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary value, Re represents z i Its actual value, z i Represents the complex value representing the decaying cosine component in the discrete-time model of the sample point estimate.

6. The method for online estimation of grid-connected system stability margin according to claim 4, characterized in that: The damping ratio calculation formula is: Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

7. The method for online estimation of grid-connected system stability margin according to claim 4, characterized in that: The stability margin of the grid-connected converter system is evaluated according to the grid-connected converter system damping, and the evaluation results obtained include: If the grid-connected system damping of the grid-connected converter is less than zero, it means that the grid-connected system of the grid-connected converter is in an unstable state; If the grid-connected system damping of the grid-connected converter is equal to zero, it means that the grid-connected system of the grid-connected converter is in a critical stable state; If the grid-connected system damping of the grid-connected converter is greater than zero, it means that the grid-connected converter system is in a critical stable state.

8. An online estimation system for grid-connected system stability margin, characterized in that: include: A model building module analyzes the transfer functions of each control link of the grid-connected converter system to obtain the control mechanism of the grid-connected converter system; and builds a grid-connected station system model based on the control mechanism of the grid-connected converter system; The waveform data acquisition module runs the grid-connected system model of the grid-building type station by simulation, applies a pulse signal at the current reference of the grid-building type station grid-connected system model, and obtains a response waveform data sequence by observing the active and / or reactive curve waveforms; The stability assessment module uses a high-resolution spectrum estimation algorithm to extract the oscillation modal parameters of the response waveform data sequence, determines the dominant oscillation mode of the grid-connected converter system, and evaluates the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system.

9. The grid-connected system stability margin online estimation system according to claim 8, characterized in that: The grid-connected system model of the grid-forming station is run in a simulation manner, and a pulse signal is applied at the current reference of the grid-forming station grid-connected system model, and a response waveform data sequence is obtained by observing the active and / or reactive curve waveforms, including: By simulating and running the grid-connected system model of the grid-building type station, the active curve waveform and reactive curve waveform of the grid-building type station grid-connected system model when running under the preset time length are recorded; and the maximum frequency of the grid-building type station grid-connected system model is determined; Based on Shannon sampling theorem, the sampling frequency of the response waveform data is calculated according to the maximum frequency of the grid-connected system model of the grid-type station; The response waveform data is sampled according to the sampling frequency of the response waveform data to obtain a response waveform data sequence.

10. The grid-connected system stability margin online estimation system according to claim 9, characterized in that: The calculation formula for calculating the sampling frequency of the response waveform data according to the maximum frequency of the grid-connected system model of the grid-connected station is: f s =1 / Δt=2πf i / arctan[Im(z i ) / Re(z i )] f smin =2πf imax / (π / 2)=4f imax ; In the formula, f s represents the sampling frequency, f i represents the frequency of each component constituting the original waveform, Δt represents the sampling interval, and Im represents the sampling time. i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete time model of the sampling point estimate, f smin Indicates the minimum value of the sampling frequency, f imax Indicates the maximum value of the sampling frequency.

11. The grid-connected system stability margin online estimation system according to claim 10, characterized in that: The method of extracting oscillation mode parameters of the response waveform data sequence by using a high-resolution spectrum estimation algorithm, determining the dominant oscillation mode of the grid-connected converter system, and evaluating the stability margin of the grid-connected converter system by calculating the damping ratio of the grid-connected converter system based on the dominant oscillation mode of the grid-connected converter system includes: constructing a number of discrete-time sample function models according to the response waveform data sequence, and constructing a sample function matrix according to the number of discrete-time sample function models; The effective order is determined by using the total least squares method of singular value decomposition, and the estimated value of the sampling point is obtained by solving the characteristic root; Determine the parameter vector according to the estimated value of the sampling point obtained, and calculate the oscillation mode parameter using the oscillation mode parameter calculation formula; The parameter group with the smallest absolute value of the attenuation factor in the oscillation mode parameters is selected as the dominant oscillation mode, and the damping ratio of the grid-connected system of the grid-connected converter is calculated by the damping ratio calculation formula; The stability margin of the grid-connected system of the grid-connected converter is evaluated according to the damping of the grid-connected system of the grid-connected converter, and an evaluation result is obtained.

12. The grid-connected system stability margin online estimation system according to claim 11, characterized in that: The oscillation modal parameter calculation formula is: In the formula, A i represents the amplitude, b i represents the reference vector, θ i represents the phase, α i represents the attenuation factor, f i represents the frequency of each component, Δt represents the sampling interval, and Im represents the sampling interval z i Imaginary part value, Re means taking z i Real value, z i Represents the complex value representing the decaying cosine component in the discrete-time model of the sample point estimate.

13. The grid-connected system stability margin online estimation system according to claim 12, characterized in that: The damping ratio calculation formula is: Where ξ represents the damping ratio, α represents the attenuation factor, and f represents the oscillation frequency.

14. The grid-connected system stability margin online estimation system according to claim 13, characterized in that: The stability margin of the grid-connected converter system is evaluated according to the grid-connected converter system damping, and the evaluation results obtained include: If the grid-connected system damping of the grid-connected converter is less than zero, it means that the grid-connected system of the grid-connected converter is in an unstable state; If the grid-connected system damping of the grid-connected converter is equal to zero, it means that the grid-connected system of the grid-connected converter is in a critical stable state; If the grid-connected system damping of the grid-connected converter is greater than zero, it means that the grid-connected converter system is in a critical stable state.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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