Offshore wind power plant resonance risk assessment method, system and equipment and storage medium

Abstract

The invention discloses an offshore wind plant resonance risk assessment method, system and device and a storage medium. The offshore wind plant resonance risk assessment method comprises the following steps: establishing an s-domain impedance model of each electrical device of an offshore wind plant; constructing an s-domain equivalent circuit of the offshore wind plant, and further obtaining an s-domain node admittance matrix; in an undamped system, for a concerned frequency band, discrete frequency points are taken according to a certain step length, a normalized s-domain node susceptance matrix determinant under the frequency corresponding to the discrete frequency points is calculated, and resonant frequency is estimated according to mutability of determinant symbols of adjacent frequency points; calculating a node voltage vibration mode, and judging an optimal controllable observable node; in a complete system, the damping and resonance frequency of a resonance mode are actuarially calculated at the optimal controllable observable node by using a test signal method; and evaluating the resonance risk of the offshore wind plant according to the damping of the resonance mode. According to the method, the complexity caused by directly solving the zero point of the determinant of the s-domain node admittance matrix can be avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of power transmission and distribution of electric power systems, and in particular relates to a method, system, equipment and storage medium for evaluating resonance risk in an offshore wind farm. Background Art

[0002] Offshore wind power, which has the advantages of high wind energy quality, low noise pollution, less land resource occupation, and close proximity to load centers for easy nearby consumption, will become an important pillar of renewable energy power generation in the future.

[0003] Compared with overhead lines, the positive sequence capacitance of AC cables is 20 to 40 times that of overhead lines of the same length and voltage level, and the series impedance is 50% to 100% of that of overhead lines of the same level. Therefore, the capacitance effect of AC submarine cables is significant. When AC submarine cables are connected to inductive components such as transformers, parallel resonance is very likely to occur. There are a large number of power electronic equipment in offshore wind farms. Their wide bandwidth and fast response characteristics have a great impact on the resonance characteristics of offshore wind farms, and there is a risk of induced resonance. Therefore, the resonance problem that is generally not serious in onshore wind farms may become very serious in offshore wind farms.

[0004] Common methods for system resonance risk assessment include the Nyquist criterion method, the state space method, and the s-domain node admittance matrix method. The Nyquist criterion method divides the entire system into two parts: the device to be connected and the existing system. The resonance risk is assessed by analyzing whether the incremental impedance frequency characteristics of the two parts meet the Nyquist criterion. This method compresses the system into a single-node system and ignores the topological structure and possible resonance modes in the system. Therefore, it cannot be used for resonance risk assessment of large systems. The mathematical model of the state space method is the state space equation. The key to calculating the resonance mode is to solve the eigenvalue of the system matrix. When the system contains distributed parameter elements and frequency-varying parameter elements, the system cannot be described using the standard state space equation of the linear time-invariant system. In addition, the incremental linearized state space equation at a certain working point of the power electronic equipment is difficult to establish. The mathematical model of the s-domain node admittance matrix method is the s-domain node admittance matrix. The key to calculating the resonance mode is to solve the zero point of the determinant of the s-domain node admittance matrix. There is no difficulty in dealing with systems containing distributed parameter elements and frequency-varying parameter elements. Therefore, the s-domain node admittance matrix method is more suitable for resonance risk assessment of large systems. For large systems, the order of the s-domain node admittance matrix is ​​very high. It is difficult to directly solve the zeros of the determinant of the s-domain node admittance matrix, and there is a risk of numerical overflow in the process of calculating the determinant. Summary of the invention

[0005] In order to deal with the problem of resonance that is prone to occur in offshore wind farms, the purpose of the present invention is to provide a method, system, device and storage medium for evaluating the risk of resonance in offshore wind farms, so as to solve the problems of poor comprehensiveness of analysis and difficulty in solving resonance modes in traditional resonance risk assessment methods.

[0006] In a first aspect, the present invention provides a method for evaluating the risk of resonance in an offshore wind farm, comprising the following steps:

[0007] (1) Establish the s-domain impedance model of each electrical equipment in the offshore wind farm, including the s-domain impedance model of the wind turbine, the s-domain impedance model of the transformer, and the s-domain impedance model of the cable;

[0008] (2) According to the topological structure of the offshore wind farm and the s-domain impedance model of each electrical equipment in the offshore wind farm, the s-domain equivalent circuit of the offshore wind farm is constructed, and then the s-domain node admittance matrix of the offshore wind farm is obtained;

[0009] (3) In an undamped system, for a frequency band of interest, discrete frequency points are taken at a certain step size, the normalized s-domain node susceptance matrix determinant at the corresponding frequency of the discrete frequency points is calculated, and the resonant frequency is estimated based on the sudden change in the sign of the s-domain node susceptance matrix determinant at adjacent frequency points;

[0010] (4) Calculating the node voltage vibration mode by estimating the node susceptance matrix at the resonant frequency, and determining the best controllable and observable node, wherein the best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode, so as to facilitate the subsequent injection of the test current into the best controllable and observable node in the damped system to accurately resonate the mode;

[0011] (5) In the complete system, the damping and resonant frequency of the resonant mode are calculated using the test signal method at the best controllable and observable node;

[0012] (6) Evaluate the resonance risk of offshore wind farms at the resonant frequency based on the damping of the resonant mode.

[0013] Unstable resonant modes, that is, resonant modes with resonance risks, will resonate at the resonant frequency. Accurately calculating the resonant frequency facilitates the subsequent design of the suppressor and reduces the resonance risk.

[0014] Furthermore, in step (1), the process of establishing the S-domain impedance model of the wind turbine is specifically as follows: according to the circuit and control parameters of the wind turbine, the transmission of the voltage disturbance component inside the equipment, the quantitative correspondence between the disturbance components and the corresponding current disturbance components are analyzed, the ratio of the voltage disturbance component to the current disturbance component in the frequency domain is determined, and the S-domain impedance model of the power equipment is determined according to the correspondence between the frequency domain and the S-domain.

[0015] Furthermore, in step (1), the transformer s-domain impedance model is:

[0016]

[0017] Where: f0 is the fundamental frequency; X0 is the leakage reactance of the transformer at the fundamental frequency; S N is the rated capacity of the transformer.

[0018] Furthermore, in step (1), the specific steps for establishing the cable s-domain impedance model are as follows: the full-dimensional series impedance matrix and the unit length parallel capacitance are calculated according to the cable specification parameters, the full-dimensional series impedance matrix is ​​transformed into different three-phase series impedance matrices according to different wiring methods, the three-phase series impedance matrix is ​​obtained by sequence transformation to obtain a sequence impedance matrix, only considering the positive sequence impedance, and further converted into a unit length positive sequence resistance and a unit length positive sequence inductance; taking into account the cable length, a π model considering the parameter distribution characteristics is established; if the values ​​of the resistance, inductance and capacitance in the π model are R, L and C respectively, then the corresponding s-domain impedance model is R, sL and 1 / sC.

[0019] Furthermore, in step (3), the undamped system is obtained by setting the resistance in the s-domain impedance model of all electrical devices to zero. At this time, the resonant mode only exhibits the resonant frequency, and the s-domain node admittance matrix is ​​converted into the s-domain node susceptance matrix, that is:

[0020] Y node (s)=Y node (σ+jω)=Y node (jω)=G node (ω)+jB node (ω) = jB node (ω) = jB node (2πf)

[0021] Where: Y node (s) is the admittance matrix of the s-domain nodes; G node (ω) is the s-domain node conductance matrix, G node (ω)=0;B node (ω) is the s-domain node susceptance matrix; σ is the damping coefficient or attenuation coefficient; ω is the angular frequency; f is the frequency;

[0022] The normalization of the s-domain node susceptance matrix is ​​based on the absolute value of the element with the largest absolute value in the s-domain node susceptance matrix, and maps all elements in the s-domain node susceptance matrix to [-1,1], that is:

[0023]

[0024] Where: is the normalized s-domain node susceptance matrix; B ij (ω) is the element in the s domain node susceptance matrix;

[0025] The estimated resonant frequency is determined by the mutation of the sign of the determinant of the s-domain node susceptance matrix of adjacent frequency points to determine whether there is a resonant frequency between adjacent frequency points. If there is, the resonant frequency is estimated by a two-point linear interpolation method, that is:

[0026]

[0027] Where: is to estimate the resonant frequency; f1 and f2 are adjacent frequency points that meet the above conditions.

[0028] Furthermore, the specific steps for calculating the node voltage vibration mode in step (4) are as follows:

[0029] Estimate the node susceptance matrix at the resonant frequency There must be an eigenvalue with a value of 0. The node voltage vibration mode T is the eigenvector of this eigenvalue. Perform QR decomposition to satisfy the following relationship:

[0030]

[0031] Where: Q is an orthogonal matrix; R is an upper triangular matrix;

[0032] T is not unique, so let T n =1, and the other elements in T are obtained by solving the following equations:

[0033]

[0034] Normalize T by dividing each element in T by the absolute value of the element with the largest absolute value.

[0035] Furthermore, the specific steps of the test signal method in step (5) are as follows:

[0036] Inject current into the best controllable and observable node k. Node k has a node l that is directly connected to it. Calculate the branch current between node k and node l. The ratio of branch current to injected current is the shunt ratio, which is calculated as follows:

[0037]

[0038] Where: η shunt (s) is the split ratio; i k (s) is the injected current; i shunt (s) is the branch current; y shunt (s) is the branch admittance; γ is a 1×n-dimensional row vector, the kth element is 1, the lth element is -1, and the rest are 0; β is an n×1-dimensional column vector, the kth element is 1, and the rest are 0; Y nodeThe adjoint matrix of (s);

[0039] η shunt The denominator polynomial of (s) contains det[Y node (s)], when s is in the neighborhood of the corresponding root of the system resonant mode, η shunt (s) is approximately expressed as:

[0040]

[0041] Where: b2, b1, b0, a1 and a0 are the coefficients of the unknown polynomial, all of which are real numbers;

[0042] At the undamped resonant frequency Take multiple calculation frequency points in the neighborhood of and calculate the corresponding η shunt (s) to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0;

[0043] Solve the quadratic polynomial for the denominator of the split ratio to obtain the exact resonant mode σ res ±jω res =σ res ±j2πf res , where σ res is the damping coefficient or attenuation coefficient of the resonant mode; ω res is the resonant angular frequency; f res is the resonant frequency.

[0044] Furthermore, the fitting method is used to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0. Take 11 evenly distributed calculation frequency points within the frequency range and Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf 11 ), using computer fitting tools to shunt The expression of (s) is fitted.

[0045] Furthermore, the real-imaginary decoupling method is used to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0. Take 5 evenly distributed calculation frequency points within the frequency range and Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf5), expressed by η1~η5, forms the equation:

[0046]

[0047] Transform the real part equation and the imaginary part equation:

[0048]

[0049] Where: real(x) means returning the real part of the complex number x; imag(x) means returning the imaginary part of the complex number x; b 2,real 、b 0,real 、a 1,real and a 0,real b is the coefficient of the unknown polynomial solved by the real part equation; 1,imag 、a 1,imag and a 0,imag A is the coefficient of the unknown polynomial solved by the imaginary part equation; real is the coefficient matrix of the real part equation; b real is the vector on the right side of the real part equation; A imag is the coefficient matrix of the imaginary part equation; b imag is the vector on the right side of the imaginary part equation;

[0050] Then construct the real part normal equation and the imaginary part normal equation to solve the unknown polynomial coefficients:

[0051]

[0052] Take b2 = b 2,real , b1=b 1,imag , b0=b 0,real , a1=a 1,imag , a0=a 0,imag .

[0053] In a second aspect, the present invention provides an offshore wind farm resonance risk assessment system, which is used to implement the offshore wind farm resonance risk assessment method, comprising:

[0054] Impedance model building unit: building s-domain impedance models of various electrical equipment in offshore wind farms, including wind turbine s-domain impedance models, transformer s-domain impedance models and cable s-domain impedance models;

[0055] Node admittance matrix acquisition unit: constructs an s-domain equivalent circuit of the offshore wind farm according to the topological structure of the offshore wind farm and the s-domain impedance model of each electrical equipment in the offshore wind farm, and then obtains the s-domain node admittance matrix of the offshore wind farm;

[0056] Resonance frequency estimation module: In an undamped system, for the frequency band of interest, discrete frequency points are taken at a certain step size, the normalized s-domain node susceptance matrix determinant at the corresponding frequency of the discrete frequency points is calculated, and the resonance frequency is estimated according to the sudden change of the sign of the s-domain node susceptance matrix determinant at adjacent frequency points;

[0057] The best controllable and observable node acquisition unit is used to calculate the node voltage vibration mode by estimating the node susceptance matrix at the resonant frequency, and determine the best controllable and observable node, wherein the best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode;

[0058] Resonance mode calculation unit: In the complete system, the damping and resonant frequency of the resonant mode are calculated using the test signal method at the best controllable and observable node;

[0059] Resonance risk assessment unit: Assess the resonance risk of the offshore wind farm at the resonant frequency based on the damping of the resonant mode.

[0060] In a third aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the offshore wind farm resonance risk assessment method when executing the computer program.

[0061] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the offshore wind farm resonance risk assessment method.

[0062] Compared with the existing methods, the present invention has the following beneficial effects: fully considering the topological structure of the offshore wind farm under the interaction of multiple electrical equipment, the resonance risk assessment is more comprehensive; fully considering the weak coupling relationship between the damping and reactance of the resonant mode and between the resonant frequency and the resistance, estimating the resonant frequency in the undamped system, and accurately calculating the resonant mode in the complete system, avoiding the complexity brought by directly solving the zero points of the determinant of the s-domain node admittance matrix; normalizing before calculating the determinant of the s-domain node susceptance matrix, avoiding the high-order s-domain node susceptance matrix determinant from exceeding the numerical range, and improving numerical stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic flow chart of the offshore wind farm resonance risk assessment method of the present invention;

[0064] Figure 2 This is a diagram showing the structure of the offshore wind farm resonance risk assessment system of the present invention;

[0065] Figure 3 A schematic diagram of the structure of an offshore wind farm analyzed for an application example of the present invention;

[0066] Figure 4 This is a schematic diagram of an S-domain equivalent circuit of an offshore wind farm analyzed in an application example of the present invention;

[0067] Figure 5 A schematic diagram of a logical structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to describe the present invention more specifically, the technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0069] Example 1

[0070] like Figure 1 As shown, this embodiment provides a method for evaluating the resonance risk of an offshore wind farm, and the steps are as follows:

[0071] (1) Establish the s-domain impedance model of each electrical equipment in the offshore wind farm, including the s-domain impedance model of the wind turbine, the s-domain impedance model of the transformer, and the s-domain impedance model of the cable.

[0072] The specific process of establishing the S-domain impedance model of the wind turbine is as follows: according to the circuit and control parameters of the wind turbine, the transmission of the voltage disturbance component inside the equipment, the quantitative correspondence between the disturbance components and the corresponding current disturbance components are analyzed, and the ratio of the voltage disturbance component to the current disturbance component in the frequency domain is determined. According to the correspondence between the frequency domain and the S-domain, the S-domain impedance model of the power equipment is determined.

[0073] The transformer s-domain impedance model is:

[0074]

[0075] Where: f0 is the fundamental frequency; X0 is the leakage reactance of the transformer at the fundamental frequency; S N is the rated capacity of the transformer.

[0076] The specific steps for establishing the cable s-domain impedance model are as follows: the full-dimensional series impedance matrix and the unit length shunt capacitance are calculated according to the cable specification parameters. The full-dimensional series impedance matrix is ​​transformed into different three-phase series impedance matrices according to different wiring methods. The three-phase series impedance matrix is ​​transformed into a sequence impedance matrix through sequence transformation, considering only the positive-sequence impedance, which is further converted into the unit length positive-sequence resistance and unit length positive-sequence inductance; taking into account the cable length, a π model considering the parameter distribution characteristics is established; if the values ​​of resistance, inductance and capacitance in the π model are R, L and C respectively, the corresponding s-domain impedance model is R, sL and 1 / sC.

[0077] (2) The s-domain impedance models of all electrical equipment in the offshore wind farm are converted to the basic voltage level. The basic voltage level is generally selected as the voltage level of the submarine cables in the offshore wind farm. The s-domain equivalent circuit of the offshore wind farm is constructed according to the topological structure of the offshore wind farm, and then the s-domain node admittance matrix of the offshore wind farm is obtained.

[0078] s-domain node admittance matrix Y node (s) shall be in the form of:

[0079]

[0080] Among them, N is the number of nodes in the entire offshore wind farm. The main diagonal elements in the above matrix represent the self-admittance values ​​of the corresponding nodes, and the remaining elements represent the mutual admittance values ​​between nodes. The subscripts of each element represent the node number. The method for constructing the frequency domain node admittance matrix of the offshore wind farm is to traverse each element in the offshore wind farm and add it to the corresponding matrix element according to the node to which the element is connected. For example: when an element with an s-domain impedance of Z1 is connected to the i node of the offshore wind farm, its impact on the frequency domain node admittance matrix of the offshore wind farm is to make y ii Add 1 / Z1; when an element with s-domain impedance Z2 is connected between node j and node k of the offshore wind farm, its impact on the frequency-domain node admittance matrix of the offshore wind farm is to make y jj and kk Add 1 / Z2 and make y jk and kj Add (-1 / Z2).

[0081] (3) In an undamped system, for the frequency band of interest, discrete frequency points are taken at a certain step size, and the normalized s-domain node susceptance matrix determinant at this frequency is calculated. The resonant frequency is estimated based on the sudden change in the sign of the determinant at adjacent frequency points, and the number of resonant modes is determined.

[0082] The undamped system is obtained by setting the resistance in the s-domain impedance model of all electrical equipment to zero. At this time, the resonant mode only shows the resonant frequency, and the s-domain node admittance matrix is ​​converted to the s-domain node susceptance matrix, that is:

[0083] Y node (s)=Y node (σ+jω)=Y node (jω)=G node (ω)+jB node (ω) = jB node (ω) = jB node (2πf)

[0084] Where: G node (ω) is the s-domain node conductance matrix, G node (ω)=0;B node (ω) is the s-domain node susceptance matrix; σ is the damping coefficient or attenuation coefficient; ω is the angular frequency; and f is the frequency.

[0085] The normalization of the s-domain node susceptance matrix is ​​based on the absolute value of the element with the largest absolute value in the s-domain node susceptance matrix, and all elements in the s-domain node susceptance matrix are mapped to [-1,1] to improve numerical stability, that is:

[0086]

[0087] Where: is the normalized s-domain node susceptance matrix; B ij (ω) is an element in the s-domain node susceptance matrix.

[0088] The estimated resonant frequency is determined by the mutation of the sign of the determinant of the s-domain node susceptance matrix of adjacent frequency points to determine whether there is a resonant frequency between adjacent frequency points. If there is, the resonant frequency is estimated by a two-point linear interpolation method, that is:

[0089]

[0090] Where: is to estimate the resonant frequency; f1 and f2 are adjacent frequency points that meet the above conditions.

[0091] (4) The node voltage vibration mode is calculated by estimating the node susceptance matrix at the resonant frequency, and the best controllable and observable node is determined. The best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode.

[0092] The specific steps for calculating the node voltage vibration mode are as follows:

[0093] Estimate the node susceptance matrix at the resonant frequency There must be an eigenvalue with a value of 0. The node voltage vibration mode T is the eigenvector of this eigenvalue. Perform QR decomposition to satisfy the following relationship:

[0094]

[0095] Where: Q is an orthogonal matrix; R is an upper triangular matrix;

[0096] T is not unique, so let T n =1, the other elements in T can be obtained by solving the following equations:

[0097]

[0098] T reflects the relative amplitude and relative phase relationship of the voltages at each node in the resonant mode, so T can be normalized, that is, each element in T is divided by the absolute value of the element with the largest absolute value.

[0099] (5) In the complete system, the damping and resonant frequency of the resonant mode are accurately calculated using the test signal method at the best controllable and observable node.

[0100] The specific steps of the test signal method are as follows:

[0101] Inject current into the best controllable and observable node k. Node k has a node l that is directly connected to it. Calculate the branch current between node k and node l. The ratio of branch current to injected current is the shunt ratio, which is calculated as follows:

[0102]

[0103] Where: η shunt (s) is the split ratio; i k (s) is the injected current; i shunt (s) is the branch current; y shunt (s) is the branch admittance; γ is a 1×n-dimensional row vector, the kth element is 1, the lth element is -1, and the rest are 0; β is an n×1-dimensional column vector, the kth element is 1, and the rest are 0; Y *node (s) is Y node The adjoint matrix of (s);

[0104] η shunt The denominator polynomial of (s) contains det[Y node (s)], when s is in the neighborhood of the corresponding root of the system resonant mode, η shunt (s) can be approximately expressed as:

[0105]

[0106] Where: b2, b1, b0, a1, a0 are the coefficients of the unknown polynomial, all of which are real numbers;

[0107] At the undamped resonant frequency Take multiple calculation frequency points in the neighborhood of and calculate the corresponding η shunt (s) to solve the unknown polynomial coefficients b2, b1, b0, a1, a0;

[0108] Solve the quadratic polynomial for the denominator of the split ratio to obtain the exact resonant mode σ res ±jω res =σ res ±j2πf res , where: res is the damping coefficient or attenuation coefficient of the resonant mode; ω res is the resonant angular frequency; f res is the resonant frequency.

[0109] The fitting method can be used to solve the unknown polynomial coefficients b2, b1, b0, a1, and a0. Take 11 evenly distributed calculation frequency points within the frequency range Calculate the corresponding η respectively shunt (j2πf1)~ηshunt (j2πf 11 ), using computer fitting tools to shunt The expression of (s) is fitted.

[0110] The real-imaginary decoupling method can also be used to solve the unknown polynomial coefficients b2, b1, b0, a1, and a0. Take 5 evenly distributed calculation frequency points within the frequency range Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf5), expressed by η1~η5, forms the equation:

[0111]

[0112] Transform the real part equation and the imaginary part equation:

[0113]

[0114] Where: real(x) returns the real part of the complex number x; imag(x) returns the imaginary part of the complex number x; b 2,real 、b 0,real 、a 1,real 、a 0,real b is the coefficient of the unknown polynomial solved by the real part equation; 1,imag 、a 1,imag 、a 0,imag A is the coefficient of the unknown polynomial solved by the imaginary part equation; real is the coefficient matrix of the real part equation; b real is the vector on the right side of the real part equation; A imag is the coefficient matrix of the imaginary part equation; b imag is the vector on the right side of the imaginary part equation;

[0115] Then construct the real part normal equation and the imaginary part normal equation to solve the unknown polynomial coefficients:

[0116]

[0117] Take b2 = b 2,real , b1=b 1,imag , b0=b 0,real , a1=a 1,imag , a0=a 0,imag .

[0118] (6) Evaluate the resonance risk of offshore wind farms based on the damping of the resonant modes. res The sign of σ determines the resonance risk of offshore wind farms. res<0, the offshore wind farm will be res Divergent resonance occurs, if σ res = 0, the offshore wind farm will be res In both cases, the resonance risk of offshore wind farms is high and resonance suppression is required to reduce the resonance risk. res >0, the resonance risk of offshore wind farms is low, and σ res The larger the absolute value of is, the lower the frequency of the offshore wind farm is.

[0119] Example 2

[0120] This embodiment provides an offshore wind farm resonance risk assessment system, which is composed of an impedance model building unit, a node admittance matrix acquisition unit, a resonance frequency estimation unit, an optimal controllable and observable node acquisition unit, a resonance mode actuarial unit and a resonance risk assessment unit. Figure 2 shown.

[0121] Impedance model building unit: Establish the s-domain impedance model of each electrical equipment in the offshore wind farm, including wind turbines, transformers and cables.

[0122] In the impedance model establishment unit, the establishment process of the wind turbine s-domain impedance model is specifically as follows: according to the wind turbine circuit and control parameters, the transmission of the voltage disturbance component inside the equipment, the quantitative correspondence between the disturbance components and the corresponding current disturbance components are analyzed, the ratio of the voltage disturbance component to the current disturbance component in the frequency domain is determined, and the s-domain impedance model of the power equipment is determined according to the correspondence between the frequency domain and the s-domain.

[0123] The transformer s-domain impedance model is:

[0124]

[0125] Where: f0 is the fundamental frequency; X0 is the leakage reactance of the transformer at the fundamental frequency; S N is the rated capacity of the transformer.

[0126] The specific steps for establishing the cable s-domain impedance model are as follows: the full-dimensional series impedance matrix and the unit length shunt capacitance are calculated according to the cable specification parameters. The full-dimensional series impedance matrix is ​​transformed into different three-phase series impedance matrices according to different wiring methods. The three-phase series impedance matrix is ​​transformed into a sequence impedance matrix through sequence transformation, considering only the positive-sequence impedance, which is further converted into the unit length positive-sequence resistance and unit length positive-sequence inductance; taking into account the cable length, a π model considering the parameter distribution characteristics is established; if the values ​​of resistance, inductance and capacitance in the π model are R, L and C respectively, the corresponding s-domain impedance model is R, sL and 1 / sC.

[0127] Node admittance matrix acquisition unit: constructs the s-domain equivalent circuit according to the topological structure of the offshore wind farm, and then obtains its s-domain node admittance matrix. The s-domain impedance model of each electrical equipment in the offshore wind farm is reduced to the basic voltage level, which is generally selected as the voltage level of the submarine cable in the offshore wind farm.

[0128] s-domain node admittance matrix Y node (s) shall be in the form of:

[0129]

[0130] Among them, N is the number of nodes in the entire offshore wind farm. The main diagonal elements in the above matrix represent the self-admittance values ​​of the corresponding nodes, and the remaining elements represent the mutual admittance values ​​between nodes. The subscripts of each element represent the node number. The method for constructing the frequency domain node admittance matrix of the offshore wind farm is to traverse each element in the offshore wind farm and add it to the corresponding matrix element according to the node to which the element is connected. For example: when an element with an s-domain impedance of Z1 is connected to the i node of the offshore wind farm, its impact on the frequency domain node admittance matrix of the offshore wind farm is to make y ii Add 1 / Z1; when an element with s-domain impedance Z2 is connected between node j and node k of the offshore wind farm, its impact on the frequency-domain node admittance matrix of the offshore wind farm is to make y jj and kk Add 1 / Z2 and make y jk and kj Add (-1 / Z2).

[0131] Resonance frequency estimation unit: In an undamped system, for the frequency band of interest, discrete frequency points are taken at a certain step size, and the normalized s-domain node susceptance matrix determinant at the frequency is calculated. The resonant frequency is estimated based on the sudden change in the sign of the determinant of adjacent frequency points to determine the number of resonant modes.

[0132] In the resonant frequency estimation unit, the undamped system is obtained by setting the resistance in the s-domain impedance model of all electrical devices to zero. At this time, the resonant mode only shows the resonant frequency, and the s-domain node admittance matrix is ​​converted into the s-domain node susceptance matrix, that is:

[0133] Y node (s)=Y node (σ+jω)=Y node (jω)=G node (ω)+jB node (ω) = jB node (ω) = jB node (2πf)

[0134] Where: Y node (s) is the admittance matrix of the s-domain nodes; Gnode (ω) is the s-domain node conductance matrix, G node (ω)=0;B node (ω) is the s-domain node susceptance matrix; σ is the damping coefficient or attenuation coefficient; ω is the angular frequency; f is the frequency;

[0135] The normalization of the s-domain node susceptance matrix is ​​based on the absolute value of the element with the largest absolute value in the s-domain node susceptance matrix, and maps all elements in the s-domain node susceptance matrix to [-1,1], that is:

[0136]

[0137] Where: is the normalized s-domain node susceptance matrix; B ij (ω) is the element in the s domain node susceptance matrix;

[0138] The estimated resonant frequency is determined by the mutation of the sign of the determinant of the s-domain node susceptance matrix of adjacent frequency points to determine whether there is a resonant frequency between adjacent frequency points. If there is, the resonant frequency is estimated by a two-point linear interpolation method, that is:

[0139]

[0140] Where: is to estimate the resonant frequency; f1 and f2 are adjacent frequency points that meet the above conditions.

[0141] The best controllable and observable node acquisition unit calculates the node voltage vibration mode by estimating the node susceptance matrix at the resonant frequency, and determines the best controllable and observable node. The best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode.

[0142] In the optimal controllable and observable node acquisition unit, the specific steps of calculating the node voltage vibration mode are as follows:

[0143] Estimate the node susceptance matrix at the resonant frequency There must be an eigenvalue with a value of 0. The node voltage vibration mode T is the eigenvector of this eigenvalue. Perform QR decomposition to satisfy the following relationship:

[0144]

[0145] Where: Q is an orthogonal matrix; R is an upper triangular matrix;

[0146] T is not unique, so let T n =1, and the other elements in T are obtained by solving the following equations:

[0147]

[0148] Normalize T by dividing each element in T by the absolute value of the element with the largest absolute value.

[0149] Resonance mode calculation unit: In the complete system, the damping and resonant frequency of the resonant mode are calculated using the test signal method at the best controllable and observable node.

[0150] In the resonant mode actuating unit, the specific steps of the test signal method are as follows:

[0151] Inject current into the best controllable and observable node k. Node k has a node l that is directly connected to it. Calculate the branch current between node k and node l. The ratio of branch current to injected current is the shunt ratio, which is calculated as follows:

[0152]

[0153] Where: η shunt (s) is the split ratio; i k (s) is the injected current; i shunt (s) is the branch current; y shunt (s) is the branch admittance; γ is a 1×n-dimensional row vector, the kth element is 1, the lth element is -1, and the rest are 0; β is an n×1-dimensional column vector, the kth element is 1, and the rest are 0; Y node The adjoint matrix of (s);

[0154] η shunt The denominator polynomial of (s) contains det[Y node (s)], when s is in the neighborhood of the corresponding root of the system resonant mode, η shunt (s) is approximately expressed as:

[0155]

[0156] Where: b2, b1, b0, a1 and a0 are the coefficients of the unknown polynomial, all of which are real numbers;

[0157] At the undamped resonant frequency Take multiple calculation frequency points in the neighborhood of and calculate the corresponding η shunt (s) to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0;

[0158] Solve the quadratic polynomial for the denominator of the split ratio to obtain the exact resonant mode σ res ±jω res =σ res ±j2πf res , where σ resis the damping coefficient or attenuation coefficient of the resonant mode; ω res is the resonant angular frequency; f res is the resonant frequency.

[0159] The fitting method can be used to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0. Take 11 evenly distributed calculation frequency points within the frequency range and Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf 11 ), using computer fitting tools to shunt The expression of (s) is fitted.

[0160] The real-imaginary decoupling method can also be used to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0. Take 5 evenly distributed calculation frequency points within the frequency range and Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf5), expressed by η1~η5, forms the equation:

[0161]

[0162] Transform the real part equation and the imaginary part equation:

[0163]

[0164] Where: real(x) means returning the real part of the complex number x; imag(x) means returning the imaginary part of the complex number x; b 2,real 、b 0,real 、a 1,real and a 0,real b is the coefficient of the unknown polynomial solved by the real part equation; 1,imag 、a 1,imag and a 0,imag A is the coefficient of the unknown polynomial solved by the imaginary part equation; real is the coefficient matrix of the real part equation; b real is the vector on the right side of the real part equation; A imag is the coefficient matrix of the imaginary part equation; b imag is the vector on the right side of the imaginary part equation;

[0165] Then construct the real part normal equation and the imaginary part normal equation to solve the unknown polynomial coefficients:

[0166]

[0167] Take b2 = b 2,real , b1=b 1,imag , b0=b 0,real , a1=a 1,imag , a0=a 0,imag .

[0168] Resonance risk assessment unit: It assesses the resonance risk of offshore wind farms based on the damping of the resonant modes. res The sign of σ determines the resonance risk of offshore wind farms. res >0, the offshore wind farm will be res If divergent resonance occurs, the resonance risk of offshore wind farms is high and resonance suppression is required to reduce the resonance risk. res <0, the resonance risk of offshore wind farms is low, and σ res The larger the absolute value of is, the lower the frequency of the offshore wind farm is.

[0169] Application Examples

[0170] Take an offshore wind farm as an example, its structural diagram is as follows Figure 3 As shown, the method described in Example 1 is used to evaluate the resonance risk of an offshore wind farm.

[0171] Establish the s-domain impedance model of each electrical equipment in the offshore wind farm, including wind turbines, transformers, cables, etc. Among them, wind turbines specifically include double-fed wind turbines and direct-drive wind turbines. According to the circuit and control parameters, the transmission and coupling process of the disturbance component are analyzed to establish the s-domain impedance model of the wind turbine; the transformer specifically includes the step-up transformer at the outlet of the wind turbine and the offshore step-up transformer at the busbar. The transformer s-domain impedance model is established according to the fundamental frequency parameters; the cable specifically includes three-core cables, single-core submarine cables and single-core onshore cables. Considering the frequency-varying effect of parameters, the series impedance matrix and the parallel admittance matrix are constructed and converted into positive sequence parameters. The s-domain impedance model of the cable is established by integrating the parameter distribution characteristics.

[0172] The s-domain impedance models of all electrical equipment in the offshore wind farm are converted to the basic voltage level. The basic voltage level is generally selected as the voltage level of the submarine cable in the offshore wind farm. The s-domain equivalent circuit is constructed according to the topological structure of the offshore wind farm, as shown in Figure 4 Based on the s-domain equivalent circuit of the offshore wind farm, all nodes are numbered and traversed, and the self-admittance y of the nodes is filled in according to the numbering order. ii and mutual admittance ij , forming the s-domain node admittance matrix Y of the offshore wind farm node (s).

[0173] The undamped system is obtained by setting the resistance in the s-domain impedance model of all electrical equipment to zero from the complete system. The frequency band of interest is 20~2500Hz, and discrete frequency points are taken in steps of 1Hz. The s-domain node susceptance matrix is ​​normalized based on the absolute value of the element with the largest absolute value in the s-domain node susceptance matrix. The determinant of the normalized s-domain node susceptance matrix is ​​calculated at each frequency, and the resonant frequency is estimated by the two-point linear interpolation method based on the sudden change in the sign of the determinant at adjacent frequency points. Determine the number of resonant modes.

[0174] To estimate the resonant frequency The node susceptance matrix is ​​decomposed by QR, the node voltage vibration mode is calculated, and the node with the largest amplitude in the node voltage vibration mode is determined to be the best controllable and observable node.

[0175] In the complete system, the damping and resonant frequency of the resonant mode are calculated accurately using the test signal method at the best controllable and observable node. The fitting method is used to solve the coefficients of the unknown polynomial of the split ratio. Take 11 evenly distributed calculation frequency points within the frequency range At The corresponding optimal controllable observable node injects current and calculates the corresponding η shunt (j2πf1)~η shunt (j2πf 11 ), using computer fitting tools to shunt The real-imaginary decoupling method is used to solve the coefficients of the unknown polynomial of the split ratio. Take 5 evenly distributed calculation frequency points within the frequency range At The corresponding optimal controllable observable node injects current and calculates the corresponding η shunt (j2πf1)~η shunt (j2πf5), solve the real part equation to get b 2,real 、b 0,real 、a 1,real 、a 0,real , solve the imaginary part equation to get b 1,imag 、a 1,imag 、a 0,imag , take b2 = b 2,real , b1=b 1,imag , b0=b 0,real , a1=a 1,imag , a0=a 0,imag Solving the quadratic polynomial for the denominator of the split ratio yields the exact resonant mode σ res ±jω res =σ res ±j2πf res .

[0176] The calculation results of the resonant modes of the offshore wind farm analyzed in the application example of the present invention are shown in Table 1.

[0177] Table 1

[0178]

[0179] The resonance risk of offshore wind farms is assessed based on the damping of the resonant modes. res The sign of σ is used to judge the resonance risk of the offshore wind farm. res <0, so the risk of resonance is low.

[0180] Example 3

[0181] This embodiment provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the electronic device executes the method according to Embodiment 1 of the present invention.

[0182] Example 4

[0183] This embodiment provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute the method according to Embodiment 1 of the present invention.

[0184] refer to Figure 5 , a block diagram of an electronic device 400 that can be used as a server or client of the present invention will now be described, which is an example of a hardware device that can be applied to various aspects of the present invention. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0185] like Figure 5As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0186] A plurality of components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 may be any type of device capable of inputting information to the electronic device 400, and the input unit 406 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 407 may be any type of device capable of presenting information, and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 408 may include, but is not limited to, a disk, an optical disk. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0187] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above. For example, in some embodiments, the aforementioned metal corrosion prediction method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via the ROM 402 and / or the communication unit 409. In some embodiments, the computing unit 401 may be configured to perform the aforementioned metal corrosion prediction method in any other appropriate manner (e.g., by means of firmware).

[0188] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0189] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer 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 of the foregoing.

[0190] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0191] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0192] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0193] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0194] The above description of the implementation cases is to facilitate the understanding and application of the present invention by those skilled in the art. It is obvious that those familiar with the art can easily make various modifications to the above implementation cases and apply the general principles described herein to other cases without creative work. Therefore, the present invention is not limited to the above implementation cases, and improvements and modifications made to the present invention by those skilled in the art based on the disclosure of the present invention should be within the scope of protection of the present invention.

Claims

1. A method for evaluating the risk of resonance in an offshore wind farm, characterized in that: The steps include: Establish the s-domain impedance model of each electrical equipment in the offshore wind farm, including the s-domain impedance model of the wind turbine, the s-domain impedance model of the transformer and the s-domain impedance model of the cable; According to the topological structure of the offshore wind farm and the s-domain impedance model of each electrical equipment in the offshore wind farm, the s-domain equivalent circuit of the offshore wind farm is constructed, and then the s-domain node admittance matrix of the offshore wind farm is obtained; In an undamped system, for a frequency band of interest, discrete frequency points are taken at a certain step size, the normalized s-domain node susceptance matrix determinant at the frequency corresponding to the discrete frequency points is calculated, and the resonant frequency is estimated according to the sudden change in the sign of the s-domain node susceptance matrix determinant at adjacent frequency points; By estimating the node susceptance matrix at the resonant frequency and calculating the node voltage vibration mode, the best controllable and observable node is determined, wherein the best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode; In the complete system, the damping and resonant frequency of the resonant mode are calculated using the test signal method at the best controllable and observable node; The resonance risk of an offshore wind farm at the resonant frequency is assessed based on the damping of the resonant modes.

2. The method according to claim 1, characterized in that The process of establishing the S-domain impedance model of the wind turbine is specifically as follows: according to the circuit and control parameters of the wind turbine, the transmission of the voltage disturbance component inside the equipment, the quantitative correspondence between the disturbance components and the corresponding current disturbance components are analyzed, the ratio of the voltage disturbance component to the current disturbance component in the frequency domain is determined, and the S-domain impedance model of the power equipment is determined according to the correspondence between the frequency domain and the S-domain.

3. The method according to claim 1, characterized in that The specific steps of establishing the cable s-domain impedance model are as follows: according to the cable specification parameters, the full-dimensional series impedance matrix and the unit length parallel capacitance are calculated, the full-dimensional series impedance matrix is ​​transformed into different three-phase series impedance matrices according to different wiring modes, the three-phase series impedance matrix is ​​transformed into a sequence impedance matrix by sequence transformation, only considering the positive sequence impedance, and further converted into a unit length positive sequence resistance and a unit length positive sequence inductance; taking into account the cable length, a π model considering the parameter distribution characteristics is established; if the values ​​of resistance, inductance and capacitance in the π model are R, L and C respectively, then the corresponding s-domain impedance model is R, sL and 1 / sC.

4. The method according to claim 1, characterized in that The undamped system is obtained by setting the resistance in the s-domain impedance model of all electrical devices to zero. At this time, the resonant mode only shows the resonant frequency, and the s-domain node admittance matrix is ​​converted into the s-domain node susceptance matrix, that is: Y node (s)=Y node (σ+jω)=Y node (jω)=G node (ω)+jB node (ω)=jB node (ω)=jB node (2πf) Where: Y node (s) is the admittance matrix of the s-domain nodes; G node (ω) is the s-domain node conductance matrix, G node (ω)=0;B node (ω) is the s-domain node susceptance matrix; σ is the damping coefficient or attenuation coefficient; ω is the angular frequency; f is the frequency; The normalization of the s-domain node susceptance matrix is ​​based on the absolute value of the element with the largest absolute value in the s-domain node susceptance matrix, and maps all elements in the s-domain node susceptance matrix to [-1,1], that is: Where: is the normalized s-domain node susceptance matrix; B ij (ω) is the element in the s domain node susceptance matrix; The estimated resonant frequency is determined by the mutation of the sign of the determinant of the s-domain node susceptance matrix of adjacent frequency points to determine whether there is a resonant frequency between adjacent frequency points. If there is, the resonant frequency is estimated by a two-point linear interpolation method, that is: Where: is to estimate the resonant frequency; f1 and f2 are adjacent frequency points that meet the above conditions.

5. The method according to claim 4, characterized in that The specific steps of calculating the node voltage vibration mode by estimating the node susceptance matrix at the resonant frequency are as follows: Estimate the node susceptance matrix at the resonant frequency There must be an eigenvalue with a value of 0. The node voltage vibration mode T is the eigenvector of this eigenvalue. Perform QR decomposition to satisfy the following relationship: Where: Q is an orthogonal matrix; R is an upper triangular matrix; T is not unique, so let T n =1, and the other elements in T are obtained by solving the following equations: Normalize T by dividing each element in T by the absolute value of the element with the largest absolute value.

6. The method according to claim 4, characterized in that The specific steps of the test signal method are as follows: Inject current into the best controllable and observable node k. Node k has a node l that is directly connected to it. Calculate the branch current between node k and node l. The ratio of branch current to injected current is the shunt ratio, which is calculated as follows: Where: η shunt (s) is the split ratio; i k (s) is the injected current; i shunt (s) is the branch current; y shunt (s) is the branch admittance; γ is a 1×n-dimensional row vector, the kth element is 1, the lth element is -1, and the rest are 0; β is an n×1-dimensional column vector, the kth element is 1, and the rest are 0; Y node The adjoint matrix of (s); η shunt The denominator polynomial of (s) contains det[Y node (s)], when s is in the neighborhood of the corresponding root of the system resonant mode, η shunt (s) is approximately expressed as: Where: b2, b1, b0, a1 and a0 are the coefficients of the unknown polynomial, all of which are real numbers; At the undamped resonant frequency Take multiple calculation frequency points in the neighborhood of and calculate the corresponding η shunt (s) to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0; Solve the quadratic polynomial for the denominator of the split ratio to obtain the exact resonant mode σ res ±jω res =σ res ±j2πf res , where σ res is the damping coefficient or attenuation coefficient of the resonant mode; ω res is the resonant angular frequency; f res is the resonant frequency.

7. The method according to claim 6, characterized in that The real-imaginary decoupling method is used to solve the unknown polynomial coefficients b2, b1, b0, a1 and a0. Take 5 evenly distributed calculation frequency points within the frequency range and Calculate the corresponding η respectively shunt (j2πf1)~η shunt (j2πf5), expressed by η1~η5, forms the equation: Transform the real part equation and the imaginary part equation: Where: real(x) means returning the real part of the complex number x; imag(x) means returning the imaginary part of the complex number x; b 2,real , b 0,real 、a 1,real and a 0,real b is the coefficient of the unknown polynomial solved by the real part equation; 1,imag 、a 1,imag and a 0,imag A is the coefficient of the unknown polynomial solved by the imaginary part equation; real is the coefficient matrix of the real part equation; b real is the vector on the right side of the real part equation; A imag is the coefficient matrix of the imaginary part equation; b imag is the vector on the right side of the imaginary part equation; Then construct the real part normal equation and the imaginary part normal equation to solve the unknown polynomial coefficients: Take b2 = b 2,real , b1 = b 1,imag , b0 = b 0,real , a1 = a 1,imag , a0 = a 0,imag .

8. An offshore wind farm resonance risk assessment system, used to implement the method according to any one of claims 1 to 7, characterized in that: include: Impedance model building unit: building s-domain impedance models of various electrical equipment in offshore wind farms, including wind turbine s-domain impedance models, transformer s-domain impedance models and cable s-domain impedance models; Node admittance matrix acquisition unit: constructs an s-domain equivalent circuit of the offshore wind farm according to the topological structure of the offshore wind farm and the s-domain impedance model of each electrical equipment in the offshore wind farm, and then obtains the s-domain node admittance matrix of the offshore wind farm; Resonance frequency estimation unit: In an undamped system, for a frequency band of interest, discrete frequency points are taken at a certain step length, the normalized s-domain node susceptance matrix determinant at the frequency corresponding to the discrete frequency points is calculated, and the resonance frequency is estimated according to the sudden change in the sign of the s-domain node susceptance matrix determinant at adjacent frequency points; The best controllable and observable node acquisition unit is used to calculate the node voltage vibration mode by estimating the node susceptance matrix at the resonant frequency, and determine the best controllable and observable node, wherein the best controllable and observable node is the node with the largest amplitude in the node voltage vibration mode; Resonance mode calculation unit: In the complete system, the damping and resonant frequency of the resonant mode are calculated using the test signal method at the best controllable and observable node; Resonance risk assessment unit: Assess the resonance risk of the offshore wind farm at the resonant frequency based on the damping of the resonant mode.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. 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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