Network resonance mode stability identification method and device and medium

Abstract

The invention discloses a network resonance mode stability identification method and device and a medium. The method comprises the following steps: reading elements and topology of a new energy and power electronic equipment system network to form a complex frequency domain network admittance array; performing numerical calculation on the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve; solving extreme points of the frequency-response curve to obtain an extreme point set; obtaining real part values and imaginary part values of determinant function transfer zero points corresponding to the extreme points in sequence based on the extreme point set; and based on the real part value and the imaginary part value of each determinant transfer function zero point, placing the zero points meeting a preset criterion into the determinant transfer function zero point data set, and based on the real part value and the imaginary part value of the determinant transfer function zero point data set, determining the mode stability of the system network.

Description

Technical Field

[0001] The present invention relates to the technical field of network resonance identification, and more particularly to a method, device and medium for identifying the stability of a network resonance mode. Background Art

[0002] Renewable energy is gradually replacing traditional fossil fuels, and in the future, renewable energy generation will become the primary source of final energy demand. As the proportion of renewable energy generation increases, the power system is evolving toward a high proportion of renewable energy and power electronics. The multiple control links within renewable energy generation and power electronics systems are coupled, forming a complex, multi-timescale, high-order nonlinear system. This interaction with the power grid can easily cause broadband oscillations, a significant issue impacting the safe and stable operation of the power grid.

[0003] When analyzing the stability of grid-connected renewable energy generation and power electronic equipment, the time domain state space method and frequency domain impedance analysis method are usually used [1]-[3]. As the scale of the system increases, the state space model may face the "curse of dimensionality", making the use of the state space method for system analysis cumbersome and complicated. The frequency domain impedance method has a clear physical meaning and does not require the establishment of a detailed internal model of the equipment. When using the impedance method to analyze the stability of a complex system with many renewable energy generation and power electronic equipment connected to the grid, a complex frequency domain network admittance matrix can be established [4], and the numerical solution of the complex frequency domain network admittance matrix determinant can be obtained through numerical calculation. How to judge the stability characteristics of the grid-connected system from the numerical solution curve is of great research value. However, the analysis of the broadband oscillation characteristics of a network with a high proportion of renewable energy and a high proportion of power electronic equipment is complex, and existing theoretical methods are difficult to analyze the stability characteristics of a complex frequency domain network node admittance matrix with high dimensions and matrix elements of high-order transfer functions. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method, device and medium for identifying the stability of a network resonance mode.

[0005] According to one aspect of the present invention, a method for identifying the stability of a network resonance mode is provided, comprising:

[0006] Read in the components and topology of the new energy and power electronic equipment system network to form a complex frequency domain network admittance matrix;

[0007] The determinant transfer function of the complex frequency domain network admittance array is numerically calculated to obtain the frequency-response curve;

[0008] Find the extreme points of the frequency-response curve and obtain a set of extreme points;

[0009] Based on the extreme point set, the real part value and imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point are calculated in turn;

[0010] Based on the real and imaginary values of the zero points of each determinant transfer function, the zero points that meet the preset criteria are placed into the determinant transfer function zero point data set, and based on the real and imaginary values of the determinant transfer function zero point data set, the mode stability of the system network is determined.

[0011] Optionally, based on the extreme point set, the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point are sequentially obtained, including:

[0012] The real part, imaginary part and derivative value of each extreme point in the extreme point set are calculated using numerical interpolation method;

[0013] Based on the real part, imaginary part and derivative value of each extreme point, the real part and imaginary part value of the corresponding determinant transfer function zero point are solved.

[0014] Optionally, based on the real and imaginary values of the zero points of each determinant transfer function, zero points that meet a preset criterion are placed into a zero point data set, including:

[0015] Calculate the zero-point damping ratio of the determinant function at each zero point of the determinant function according to the real and imaginary values of each zero point;

[0016] When the zero-point damping ratio meets the preset criterion, the corresponding determinant transfer function zero point is placed into the zero-point data set.

[0017] Alternatively, the expression for the zero-point damping ratio of the determinant transfer function is:

[0018]

[0019] Where, σ p is the real part value of the zero point, ω p The imaginary value of zero.

[0020] Optionally, the preset criterion is:

[0021] ζ p ≤ζ ref

[0022] Where, ζ ref is the zero-point damping ratio threshold.

[0023] Optionally, determining the mode stability of the system network based on the real part value and the imaginary part value of the determinant transfer function zero point data set includes:

[0024] When there is a zero point of the determinant transfer function in the set of zero points of the determinant transfer function and the real part thereof is positive, the system network is determined to be in an unstable state; otherwise, the system network is determined to be in a stable state.

[0025] According to another aspect of the present invention, a network resonance mode stability identification device is provided, comprising:

[0026] Formation module, used to read the components and topology of the new energy and power electronic equipment system network and form the complex frequency domain network admittance matrix;

[0027] A calculation module is used to perform numerical calculations on the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve;

[0028] A first obtaining module is used to obtain extreme points of the frequency-response curve to obtain an extreme point set;

[0029] The second obtaining module is used to obtain the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point in sequence based on the extreme point set;

[0030] A determination module is used to place the zero points that meet the preset criteria into the determinant transfer function zero point data set based on the real part value and imaginary part value of each determinant transfer function zero point, and determine the mode stability of the system network based on the real part value and imaginary part value of the determinant transfer function zero point data set.

[0031] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method according to any one of the above aspects of the present invention.

[0032] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; and the processor for reading the executable instructions from the memory and executing the instructions to implement the method described in any one of the above aspects of the present invention.

[0033] Therefore, the present invention adopts a continuous numerical calculation method, that is, by gradually calculating the numerical solution of the determinant transfer function corresponding to the node admittance matrix with a set frequency step size; it is theoretically proved that the extreme point frequency of the amplitude-frequency numerical solution is closer to the network resonant mode frequency than the imaginary part zero-crossing frequency, and it is proposed to estimate the frequency of the network resonant mode by the extreme point frequency of the transfer function amplitude-frequency numerical solution curve; further, based on the real and imaginary part morphological characteristics of the numerical solution in the extreme point frequency field, the zero (pole) point approximation corresponding to the network resonant mode is analyzed and calculated, which can quickly determine the stability characteristics of the network broadband oscillation. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0035] Figure 1 1 is a flow chart of a method for identifying network resonance mode stability provided by an exemplary embodiment of the present invention;

[0036] Figure 2is another flow chart of a method for identifying network resonance mode stability provided by an exemplary embodiment of the present invention;

[0037] Figure 3 It is a schematic diagram of the dual relationship between time domain and frequency domain simulation calculation analysis provided by an exemplary embodiment of the present invention;

[0038] Figure 4 is a schematic diagram of a typical RLC series circuit provided by an exemplary embodiment of the present invention;

[0039] Figure 5 1 is a schematic diagram of a curve of the ratio of the pole damping ratio to the maximum admittance amplitude frequency and the pole frequency provided by an exemplary embodiment of the present invention;

[0040] Figure 6 1 is a schematic diagram of a curve showing the ratio of the pole damping ratio to the susceptance zero-crossing frequency and the pole frequency, provided by an exemplary embodiment of the present invention;

[0041] Figure 7a 、 Figure 7b 、 Figure 7c 、 Figure 7d They are respectively a schematic diagram of frequency-amplitude / phase / real part / imaginary part corresponding to a given transfer function provided by an exemplary embodiment of the present invention;

[0042] Figure 8a and Figure 8b An exemplary embodiment of the present invention provides a theoretical and identification diagram of the complex plane distribution of zeros and poles;

[0043] Figure 9 is a schematic diagram of an RLC circuit provided by an exemplary embodiment of the present invention;

[0044] Figure 10a 、 Figure 10b 、 Figure 10c and Figure 10d They are schematic diagrams of the frequency-amplitude / phase / real part / imaginary part corresponding to the impedance transfer function of the N1 port provided by an exemplary embodiment of the present invention;

[0045] Figure 11 1 is a schematic structural diagram of a network resonance mode stability identification device provided by an exemplary embodiment of the present invention;

[0046] Figure 12 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0047] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0048] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0049] Those skilled in the art will understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0050] It should also be understood that, in the embodiments of the present invention, “a plurality of” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0051] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0052] In addition, the term "and / or" in this invention merely describes an association relationship between related objects, indicating that three possible relationships exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " in this invention generally indicates that the related objects are in an "or" relationship.

[0053] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced with each other. For the sake of brevity, they will not be described one by one.

[0054] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0055] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0056] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0057] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0058] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate in conjunction with numerous other general-purpose or specialized computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with terminal devices, computer systems, servers, and other electronic devices include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above.

[0059] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media, including storage devices.

[0060] Exemplary Methods

[0061] Figure 1 FIG. 1 is a flow chart of a method for identifying the stability of a network resonance mode provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the network resonance mode stability identification method 100 includes the following steps:

[0062] Step 101, read in the components and topology of the new energy and power electronic equipment system network to form a complex frequency domain network admittance matrix;

[0063] Step 102, numerically calculating the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve;

[0064] Step 103, finding the extreme points of the frequency-response curve to obtain an extreme point set;

[0065] Step 104, based on the extreme point set, sequentially obtain the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point;

[0066] Step 105, based on the real and imaginary values of the zero points of each determinant transfer function, the zero points that meet the preset criteria are placed into the determinant transfer function zero point data set, and based on the real and imaginary values of the determinant transfer function zero point data set, the mode stability of the system network is determined.

[0067] Specifically, the present invention proposes a method for quickly estimating the characteristic quantity of system stability: using a continuous numerical calculation method, that is, by gradually calculating the numerical solution of the determinant transfer function corresponding to the node admittance matrix with a set frequency step; theoretically proving that the extreme point frequency of the amplitude-frequency numerical solution is closer to the network resonant mode frequency than the imaginary part zero-crossing frequency, it is proposed to estimate the frequency of the network resonant mode by the extreme point frequency of the transfer function amplitude-frequency numerical solution curve; further, based on the real and imaginary part morphological characteristics of the numerical solution in the extreme point frequency field, the zero (pole) point approximation corresponding to the network resonant mode is analyzed and calculated, which can quickly determine the stability characteristics of the network broadband oscillation. The specific implementation is as follows:

[0068] refer to Figure 2 As shown, the network topology and model parameters of the corresponding node connection elements are first read in to form a complex frequency-domain network admittance matrix. The determinant transfer function of the admittance matrix is numerically solved at a specified frequency step size of Δf, or the impedance / admittance transfer function of a specified node port is numerically solved. A numerical method is then used to obtain the set of extreme points of the curve corresponding to the numerical solution. Each extreme point frequency is then extracted in turn. The real and imaginary parts of the curve at the extreme point frequency and the derivatives in the neighborhood of that frequency are numerically interpolated using a two-point or five-point method. Based on the correspondence with the second-order transfer function in the neighborhood of the extreme point, the real and imaginary parts of the corresponding zero (pole) are determined. The damping ratio of the zero (pole) is then calculated. If the damping ratio is less than a set threshold, the complex number is considered a valid zero (pole). The calculation is repeated repeatedly until all elements of the extreme point set are calculated. The real part of the obtained valid zero (pole) set element can be used to determine the stability of the corresponding system, while the imaginary part corresponds to the frequency of the network resonant mode.

[0069] The specific principles are as follows:

[0070] 1. Principles of network complex frequency domain calculation and analysis

[0071] A large number of literatures have studied the incremental impedance / admittance model of renewable energy power generation units. Using comprehensive analysis in the network complex frequency domain, the broadband interaction of numerous power electronic devices in the renewable energy collection network can be taken into account. The network elements adopt the complex frequency domain impedance / admittance form in the three-phase stationary coordinate system, which facilitates the programmatic realization of broadband characteristic analysis of the renewable energy collection system.

[0072] like Figure 3As shown, in a general electromagnetic transient simulation program, the differential algebraic models of network components are converted into differential algebraic equations. The network topology is integrated to form the network node admittance equations, and simulation calculations are performed with a ΔT time step. Complex frequency domain simulation and electromagnetic transient time domain simulation form a dual relationship. In complex frequency domain simulation, the differential algebraic models of network components are converted into complex frequency domain algebraic equations. The network topology is integrated to form a complex frequency domain network node admittance matrix, and numerical calculations are performed with a Δf frequency step. Conventional network components such as RLCs, lines, and transformers have the same positive-sequence and negative-sequence impedances. However, the incremental positive-sequence and negative-sequence impedances of the ports of renewable energy power generation units differ significantly. Therefore, it is possible to separately form positive- and negative-sequence complex frequency domain network node admittance matrices for numerical analysis.

[0073] 2. Relationship between the RLC circuit pole frequency, the amplitude-frequency curve extreme value frequency, and the susceptance zero-crossing frequency

[0074] like Figure 4 As shown, considering the typical RLC series circuit, the relationship between the circuit pole frequency, the extreme value frequency of the port admittance amplitude-frequency curve, and the susceptance zero-crossing frequency is analyzed below.

[0075] The RLC circuit port admittance transfer function is:

[0076]

[0077] Where s is the Laplace operator, R is the resistance, L is the inductance, and C is the capacitance. There is a pair of conjugate poles s in the transfer function 1,2 =σ p ±jω p , poles and damping ratio as follows:

[0078]

[0079] The maximum frequency ω of the port admittance amplitude curve can be derived Y_Max and the circuit pole frequency ω p The ratio function is:

[0080]

[0081] The relationship curve between the frequency ratio function and the circuit pole damping ratio is as follows: Figure 5 shown.

[0082] Depend on Figure 5 It can be obtained that the range of the damping ratio at the extreme point is 0.254≤ζ p ≤0.382, ratio function value 1.02≤f(ζ p )≤1.023, when 0<ζ p <0.254 and 0.382 <ζ p≤0.515, ratio function value 0.98≤f(ζ p )≤1.02, the comprehensive value range of the circuit extreme damping ratio is ζ p ≤0.515, the difference between the maximum frequency of the port admittance amplitude curve and the circuit pole frequency is basically within 2%.

[0083] The zero-crossing frequency ω of the port susceptance curve can also be derived B0 and the circuit pole frequency ω p The ratio function is:

[0084]

[0085] The relationship curve between the ratio function and the extreme damping ratio is as follows: Figure 6 shown.

[0086] Depend on Figure 6 It can be obtained that the damping ratio at the extreme point is in the range of 0<ζ p ≤0.114, ratio function value 0.98≤f(ζ p )≤1.0, in ζ p >0.114, the ratio function value f(ζ p )≤0.98, that is, the damping ratio value range of the circuit pole is ζ p >0.114, the zero-crossing frequency of the port susceptance curve differs from the circuit pole frequency by more than 2%. As the pole damping ratio increases, the difference between the two frequencies increases significantly.

[0087] Therefore, within a wider range of pole damping ratio, the frequency of the extreme point of the amplitude-frequency curve of the circuit port admittance transfer function is closer to the circuit pole frequency than the frequency of the imaginary part zero crossing point. The frequency of the extreme point of the amplitude-frequency curve is more suitable for estimating the circuit pole frequency.

[0088] 3. Stability analysis method based on complex frequency domain response curve

[0089] The determinant of the network's complex frequency domain admittance matrix is D(s) = det(Y(s)), where Y(s) is the network's complex frequency domain admittance matrix and D(s) is the determinant transfer function of Y(s). Assume that the transfer function has a pair of conjugate complex zeros λ in the sub- / supersynchronous frequency band. 1，2 =α WBO ±jω WBO , α WBO is the real part of the conjugate complex zero, ω WBO is the imaginary part of the conjugate complex zero, and D(s) is in ω WBO There are no other conjugate complex zeros and poles in the tiny neighborhood, and D(s) is expressed as follows:

[0090] D(s)=(s-λ1)(s-λ2)G(s) (6)

[0091] In the formula K is the gain, z j is zero point, p j is the number of poles, m is the number of zeros, and n is the number of poles.

[0092] Consider D(s) at ω WBO There are no other poles or zeros in the tiny neighborhood, so it can be considered that the response of G(s) corresponding to s=jω in this neighborhood is approximately G(jω)=a+jb, where a and b are constants. Expand the above formula to:

[0093]

[0094] In ω WBO The derivative of the magnitude of D(s) with respect to ω in the neighborhood is:

[0095]

[0096] Let the above formula be equal to 0, and the minimum frequency of the D(s) amplitude-frequency curve is obtained as:

[0097]

[0098] The ratio of the frequency of this minimum to the frequency of the given conjugate complex zero is:

[0099]

[0100] The network containing new energy and power electronic devices is a physical system, and the damping of the broadband oscillation frequency of interest is weak, that is, |α WBO |<0.1|ω WBO |. Take |α WBO |=0.1|ω WBO |, then ω MIN / ω WBO =0.995, it can be seen that the minimum frequency of the amplitude-frequency curve of the network complex frequency domain admittance determinant transfer function is very close to the network modal frequency, which is consistent with the conclusion in the previous section.

[0101] Substituting the minimum frequency into the real and imaginary part expressions, we can get:

[0102]

[0103] Where: Y R 、Y I They are D(s) at frequency ω MIN Numerical solutions of the real and imaginary parts of .

[0104] From formula (7), we can get WBO The expressions of the real and imaginary derivatives within the neighborhood are as follows:

[0105]

[0106] Where: S R 、S I They are D(s) at frequency ω MIN The numerical solutions of the real and imaginary derivatives can be solved by 2-point or 5-point numerical difference equations.

[0107] By using equations (11) and (12), we can solve α WBO , a, b, where α WBO The expression is as follows:

[0108]

[0109] Based on equations (9) and (13), we can get the zero point λ of D(s) 1，2 =α WBO ±jω WBO Estimated value. WBO The symbol can be used to determine the stability of the network resonance mode, and ω WBO The approximate frequency of the mode can be determined.

[0110] In one embodiment of the present invention, given a closed-loop transfer function expression for the system, its poles can be solved, and then the system stability characteristics can be judged by the sign of the real part of the pole value. Conversely, for complex high-order closed-loop transfer functions, it is difficult to directly solve the zero (pole) point. Is it possible to solve the numerical solution of its frequency response, or to give a numerical solution of the closed-loop transfer function without a transfer function expression, that is, to judge the system stability characteristics by the numerical characteristics of the frequency response numerical curve of the transfer function? This is of great significance to the stability analysis of actual new energy transmission systems. Based on the numerical solution of the given system frequency response, the present invention proposes a fast system stability characteristic judgment method, that is, based on the morphological characteristics of the real and imaginary numerical solutions in the frequency neighborhood of the system extreme point, the pole approximation corresponding to the network resonant mode is analyzed and calculated, and the stability characteristics of the network resonant mode can be directly judged.

[0111] The effectiveness and accuracy of the method of the present invention can be verified theoretically. For example, a typical high-order transfer function is shown in Equation (14). Given the transfer function zeros and poles as shown in Table 1, the transfer function zeros include 9 real zeros and 15 pairs of conjugate complex zeros, and the transfer function poles include 9 real poles and 15 pairs of conjugate complex poles.

[0112]

[0113] Where K D is the transfer function gain coefficient, let K D =1,z j is zero point, p j is the number of poles, M is the number of zeros, and N is the number of poles.

[0114] Table 1 Zeros and poles of given transfer function

[0115]

[0116] The frequency response curve can be directly solved by the analytical expression of the transfer function of the known zero (pole) point, such as Figure 7a to Figure 7d shown.

[0117] in accordance with Figure 7a to Figure 7d The frequency response curve data of the transfer function shown in the figure are obtained by using the method for identifying the zero and pole points of the transfer function of the present invention. The comparison between the identification results and the theoretical values is shown in Table 2 and Table 3. The complex plane distribution of the identified zero and pole points and the theoretical values is shown in Table 3. Figure 8a and Figure 8b shown.

[0118] Table 2 Comparison of identification transfer function zero point and original zero point

[0119]

[0120]

[0121] Table 3 Comparison of identified transfer function poles and original poles

[0122]

[0123] In summary, the pattern recognition method based on transfer function value solution proposed in the present invention has good recognition accuracy, which verifies the effectiveness and accuracy of the method.

[0124] In one embodiment of the present invention, Figure 9 As shown, there are multiple network resonance modes in the circuit composed of RLC elements.

[0125] like Figures 10a to 10d As shown, the frequency response curve can be drawn using the analytical expression of the transfer function.

[0126] First, you can create Figure 9 The impedance theoretical transfer function of the N1 port is obtained, from which the theoretical poles of the circuit can be obtained; secondly, the network broadband modeling method is used to obtain the complex frequency domain network admittance matrix determinant and the N1 port impedance frequency numerical solution. The above-mentioned stability numerical analysis method is used to obtain the identification data of the network mode. The analysis results are shown in Table 4 below.

[0127] Table 4 Comparison of identified circuit poles and theoretical circuit poles

[0128] Serial number Theoretical Model Identification mode 1 -0.25±j120.56×2π -0.30±j120.58×2π 2 -5.28±j168.07×2π -6.34±j168.08×2π 3 -11.35±j265.21×2π -10.00±j265.16×2π 4 -5.59±j304.73×2π -3.83±j304.74×2π 5 -2.35±j1396.18×2π -1.75±j1396.16×2π

[0129] As can be seen from Table 4, the network model obtained by the stability numerical analysis method is basically consistent with the circuit theory model, which further verifies the correctness and accuracy of the method proposed in the present invention.

[0130] Therefore, the present invention adopts a continuous numerical calculation method, that is, by gradually calculating the numerical solution of the determinant transfer function corresponding to the node admittance matrix with a set frequency step size; it is theoretically proved that the extreme point frequency of the amplitude-frequency numerical solution is closer to the network resonant mode frequency than the imaginary part zero-crossing frequency, and it is proposed to estimate the frequency of the network resonant mode by the extreme point frequency of the transfer function amplitude-frequency numerical solution curve; further, based on the real and imaginary part morphological characteristics of the numerical solution in the extreme point frequency field, the zero (pole) point approximation corresponding to the network resonant mode is analyzed and calculated, which can quickly determine the stability characteristics of the network broadband oscillation.

[0131] Exemplary devices

[0132] Figure 11 FIG. 1 is a schematic diagram of a network resonance mode stability identification device provided by an exemplary embodiment of the present invention. Figure 11 As shown, the apparatus 1100 includes:

[0133] The forming module 1110 is used to read the components and topology of the new energy and power electronic equipment system network and form a complex frequency domain network admittance matrix;

[0134] The calculation module 1120 is used to perform numerical calculation on the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve;

[0135] A first obtaining module 1130 is configured to obtain extreme points of the frequency-response curve to obtain an extreme point set;

[0136] The second obtaining module 1140 is used to obtain the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point in sequence based on the extreme point set;

[0137] Determination module 1150 is used to place the zero points that meet the preset criteria into the determinant transfer function zero point data set based on the real part value and imaginary part value of each determinant transfer function zero point, and determine the mode stability of the system network based on the real part value and imaginary part value of the determinant transfer function zero point data set.

[0138] Optionally, the second obtaining module 1140 includes:

[0139] The first calculation submodule is used to calculate the real part, imaginary part and derivative value of each extreme point in the extreme point set by using a numerical interpolation method;

[0140] The solving submodule is used to solve the real part and imaginary part of the corresponding determinant transfer function zero point based on the real part, imaginary part and derivative value of each extreme point.

[0141] Optionally, the determination module 1150 places zero points that meet a preset criterion into a zero point data set based on the real and imaginary values of the zero points of each determinant function, including:

[0142] The second calculation submodule is used to calculate the determinant transfer function zero point damping ratio of each determinant transfer function zero point according to the real part value and the imaginary part value of each zero point;

[0143] The insertion submodule is used to insert the corresponding determinant transfer function zero point into the zero point data set when the zero point damping ratio meets the preset criterion.

[0144] Alternatively, the expression for the zero-point damping ratio of the determinant transfer function is:

[0145]

[0146] Where σ p is the real part value of the zero point, ω p The imaginary value of zero.

[0147] Optionally, the preset criterion is:

[0148] ζ p ≤ζ ref

[0149] Where, ζ ref is the zero-point damping ratio threshold.

[0150] Optionally, determining the mode stability of the system network based on the real part value and the imaginary part value of the determinant transfer function zero point data set in the determination module 1150 includes:

[0151] The determination submodule is used to determine that the system network is in an unstable state when the real part of the determinant transfer function zero point in the determinant transfer function zero point set is positive; otherwise, the system network is in a stable state.

[0152] Exemplary electronic devices

[0153] Figure 12 This is the structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 12 As shown, the electronic device 120 includes one or more processors 121 and a memory 122 .

[0154] The processor 121 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0155] The memory 122 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 121 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may further include: an input device 123 and an output device 124, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0156] In addition, the input device 123 may also include, for example, a keyboard, a mouse, and the like.

[0157] The output device 124 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0158] Of course, to simplify, Figure 12 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0159] Exemplary computer program products and computer-readable storage media

[0160] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to perform the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0161] The computer program product may be written in any combination of one or more programming languages to implement the operations of embodiments of the present invention, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as C or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0162] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0163] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0164] The basic principles of the present invention have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in the present invention are merely illustrative and non-limiting, and should not be construed as necessarily possessed by each embodiment of the present invention. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, and are not intended to be limiting. These details do not necessarily limit the present invention to being implemented using these specific details.

[0165] Each embodiment in this specification is described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. References to the same or similar parts between the various embodiments are sufficient. For system embodiments, since they largely correspond to method embodiments, their description is relatively simple. For relevant parts, references to the description of the method embodiments are sufficient.

[0166] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0167] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above, unless otherwise specified. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers recording media that store programs for executing the method according to the present invention.

[0168] It should also be noted that, in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in this field to make or use the present invention. Various modifications to these aspects will be very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but according to the widest scope consistent with the principles disclosed here and novel features.

[0169] The above description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for identifying the stability of a network resonance mode, characterized in that: include: Read in the components and topology of the new energy and power electronic equipment system network to form a complex frequency domain network admittance matrix; Numerically calculating the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve; Finding extreme points of the frequency-response curve to obtain an extreme point set; Based on the extreme point set, the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point are sequentially calculated; Based on the real and imaginary values of the zero points of each determinant transfer function, the zero points that meet the preset criteria are placed into the determinant transfer function zero point data set, and based on the real and imaginary values of the determinant transfer function zero point data set, the mode stability of the system network is determined.

2. The method according to claim 1, characterized in that Based on the extreme point set, the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point are sequentially obtained, including: Calculating the real part, imaginary part and derivative value of each extreme point in the extreme point set by using a numerical interpolation method; Based on the real part, imaginary part and derivative value of each extreme point, the real part and imaginary part value of the corresponding determinant transfer function zero point are solved.

3. The method according to claim 1, characterized in that Based on the real and imaginary values of the zero points of each determinant function, the zero points that meet the preset criteria are placed into the zero point data set, including: Calculate the zero-point damping ratio of the determinant function at each zero point of the determinant function according to the real and imaginary values of each zero point; In the case where the zero-point damping ratio satisfies the preset criterion, the corresponding determinant transfer function zero point is placed into the zero-point data set.

4. The method according to claim 3, characterized in that The expression of the zero-point damping ratio of the determinant transfer function is: Where, σ p is the real part value of the zero point, ω p The imaginary value of zero.

5. The method according to claim 3, characterized in that The preset criteria are: g p ≤ζ ref Where, ζ ref is the zero-point damping ratio threshold.

6. The method according to claim 1, characterized in that Determining the mode stability of the system network based on the real part value and the imaginary part value of the determinant transfer function zero point data set includes: When there is a determinant transfer function zero point in the determinant transfer function zero point set whose real part is positive, the system network is determined to be in an unstable state; otherwise, the system network is determined to be in a stable state.

7. A network resonance mode stability identification device, characterized in that: include: Formation module, used to read the components and topology of the new energy and power electronic equipment system network and form the complex frequency domain network admittance matrix; A calculation module, configured to perform numerical calculation on the determinant transfer function of the complex frequency domain network admittance array to obtain a frequency-response curve; A first obtaining module is used to obtain extreme points of the frequency-response curve to obtain an extreme point set; A second obtaining module is used to obtain the real part value and the imaginary part value of the zero point of the determinant transfer function corresponding to each extreme point in sequence based on the extreme point set; A determination module is used to place zero points that meet preset criteria into a determinant transfer function zero point data set based on the real and imaginary values of each determinant transfer function zero point, and determine the mode stability of the system network based on the real and imaginary values of the determinant transfer function zero point data set.

8. The device according to claim 7, characterized in that The second obtaining module includes: A first calculation submodule is used to calculate the real part, imaginary part and derivative value of each extreme point in the extreme point set by using a numerical interpolation method; The solving submodule is used to solve the real part and imaginary part of the corresponding determinant transfer function zero point based on the real part, imaginary part and derivative value of each extreme point.

9. The device according to claim 7, characterized in that In the determination module, the real and imaginary values of the zero points of each determinant transfer function are determined, and the zero points that meet the preset criteria are placed into the zero point data set, including: The second calculation submodule is used to calculate the determinant transfer function zero point damping ratio of each determinant transfer function zero point according to the real part value and the imaginary part value of each zero point; The insertion submodule is used to insert the corresponding determinant transfer function zero point into the zero point data set when the zero point damping ratio meets the preset criterion.

10. The device according to claim 9, characterized in that The expression of the zero-point damping ratio of the determinant transfer function is: Where, σ p is the real part value of the zero point, ω p The imaginary value of zero.

11. The device according to claim 9, characterized in that The preset criteria are: g p ≤ζ ref Where, ζ ref is the zero-point damping ratio threshold.

12. The device according to claim 7, characterized in that The determining module determines the mode stability of the system network based on the real part value and the imaginary part value of the zero point data set of the determinant transfer function, including: The determination submodule is configured to determine that the system network is in an unstable state when a real part of a determinant transfer function zero point exists in the determinant transfer function zero point set, and otherwise determine that the system network is in a stable state.

13. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

14. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1 to 7.

Images