New energy grid-connected tie line permanent fault identification method based on variational mode decomposition

Abstract

The invention discloses a new energy grid-connected tie line permanent fault identification method based on variational mode decomposition, and relates to the technical field of high-voltage transmission network fault identification, and the method comprises the steps: obtaining the terminal voltage of a fault phase after a circuit breaker starts a single-phase opening signal, obtaining a judgment result whether the secondary arc in the line is extinguished or not according to the terminal voltage and based on the voltage energy integral ratio; when the secondary arc is extinguished, obtaining a fault phase terminal voltage in a plurality of power frequency periods, and obtaining a plurality of intrinsic mode components corresponding to each fault phase terminal voltage by using a variational mode decomposition algorithm; determining the component with the minimum kurtosis value as a fault feature component; calculating the deviation degree of the fault characteristic component of each fault phase end voltage, and if the deviation degree of each fault characteristic component is constantly zero, obtaining an identification result that the fault in the line is a permanent fault; the permanent fault identification of the power transmission network can be quickly and accurately realized, and the problem of fault property identification during reclosing of the power transmission line under the existing background is solved.

Description

Technical Field

[0001] The invention relates to the technical field of high-voltage transmission network fault identification, and more specifically, to a permanent fault identification method for a new energy grid-connected tie line based on variational mode decomposition. Background Art

[0002] In the power system, the transmission line is the component with the most faults. According to operating experience, on the high-voltage overhead lines of the large ground current system above 110kV, more than 70% of the faults are single-phase ground short circuits, and more than 80% of them are transient faults. Therefore, when a single-phase ground short circuit occurs, only tripping the fault phase and reclosing is one of the important measures to ensure the safe and stable operation of the power system. But it also brings some adverse effects to the power system: the impact on the system caused by reclosing on a permanent fault is even greater than the impact on the system when the short circuit occurs under normal circumstances. If the fault is not removed in time, it may cause equipment damage, electrical fires and reduced grid stability. Therefore, pre-judgment of whether the fault is a permanent or transient fault to decide whether to reclose (reclosing is allowed for transient faults, and not for permanent faults) can reduce the impact on the system and has great practical significance for the power system; At present, after the circuit breakers at both ends of the line trip, the voltage at the line end is weak and the transient characteristics are complex, making it difficult to accurately extract effective fault characteristics, resulting in a low accuracy rate in fault nature judgment. Summary of the invention

[0003] The purpose of the present invention is to provide a permanent fault identification method for a new energy grid-connected interconnection line based on variational modal decomposition. By identifying the time domain characteristics of the fault phase terminal voltage of the transmission network, digital processing and waveform morphology methods are used to judge the nature of the fault. This method can quickly and accurately realize the permanent fault identification of the transmission network, which has important practical significance for maintaining the safe and stable operation of the system, so as to solve the problem of fault nature identification when the transmission line is reclosed under the existing background.

[0004] The above technical objectives of the present invention are achieved through the following technical solutions:

[0005] In a first aspect, the present application provides a method for identifying permanent faults of new energy grid-connected tie lines based on variational mode decomposition, comprising the following specific steps:

[0006] Obtaining the terminal voltage of the fault phase after the circuit breaker initiates the single-phase opening signal, and obtaining a judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and based on the voltage energy integral ratio;

[0007] When the judgment result is that the secondary arc is extinguished, the fault phase terminal voltage within a plurality of consecutive power frequency cycles is obtained, and a plurality of intrinsic mode components corresponding to each fault phase terminal voltage are obtained by using a variational mode decomposition algorithm;

[0008] For each fault phase terminal voltage, the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components is determined as the fault characteristic component;

[0009] The deviation of the fault characteristic component of each fault phase terminal voltage is calculated. If the deviation of each fault characteristic component is constant to zero, the fault in the line is identified as a permanent fault.

[0010] Based on the above technical solution, the present invention can also be improved as follows.

[0011] Furthermore, the above-mentioned judgment result of whether the secondary arc in the line is extinguished is obtained based on the terminal voltage and the voltage energy integral ratio, specifically:

[0012] Calculate the voltage energy value: In the formula, J i Indicates voltage energy value, U i represents the terminal voltage, and N represents the number of samples;

[0013] Calculate the voltage energy integral ratio: When the voltage energy integral ratio is greater than the threshold value, a judgment result of the extinguishing of the secondary arc in the circuit is obtained.

[0014] Furthermore, the variational mode decomposition algorithm is used to obtain multiple intrinsic mode components corresponding to each fault phase terminal voltage, specifically:

[0015] The decomposition model based on the variational mode decomposition algorithm and which is a constrained model is converted into a decomposition model of an unconstrained model by using a quadratic penalty factor and a Lagrange multiplication operator;

[0016] The decomposition model of the unconstrained model is optimized twice using the multiplication operator alternating direction method. Based on the optimized decomposition model of the unconstrained model, multiple corresponding intrinsic mode components are obtained according to the terminal voltage of each fault phase.

[0017] Furthermore, the decomposition model of the above constraint model is specifically as follows:

[0018]

[0019] In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, x represents the original input signal, K represents the total number of eigenmode components of the signal to be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, and t represents time;

[0020] The decomposition model of the unconstrained model is as follows:

[0021]

[0022] In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, α represents the quadratic penalty factor, λ represents the Lagrangian multiplication operator, x(t) represents the original input signal, K represents the total number of eigenmode components into which the signal will be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, t represents time, and L represents the Lagrangian function.

[0023] Furthermore, the above-mentioned eigenmode components are specifically:

[0024]

[0025] In the formula, and Represent x(t), u respectively i (t), λ(t), and Fourier transform, n is the number of iterations, x(t) represents the original input signal, u i (t) represents the i-th eigenmode component, λ(t) represents the Lagrange multiplier, represents the kth modal component of the n+1th iteration, α represents the penalty parameter, ω represents the frequency, and ω k represents the center frequency of the kth mode, and k represents the mode number, which is used to identify the specific mode.

[0026] Furthermore, the kurtosis value of the above eigenmode component is specifically:

[0027]

[0028] Where kur represents the intrinsic mode component IMF ω The kurtosis value, N represents the intrinsic mode component IMF ω Signal length, IMF ω represents the eigenmode component, IMF stands for intrinsic mode component ω The mean of .

[0029] Furthermore, the deviation of the above fault characteristic component is specifically:

[0030]

[0031] Where ske represents the fault characteristic component IMF ω The deviation degree of N represents the fault characteristic component IMF ωSignal length, IMF ω represents the fault characteristic component, IMF represents the fault characteristic component ω The mean of the fault characteristic component IMF ω The standard deviation of .

[0032] In a second aspect, the present application provides a permanent fault identification system for a new energy grid-connected tie line based on variational mode decomposition, which is applied to any one of the permanent fault identification methods for a new energy grid-connected tie line based on variational mode decomposition in the first aspect, including:

[0033] The first module is used to obtain the terminal voltage of the fault phase after the circuit breaker starts the single-phase opening signal, and obtain the judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and the voltage energy integral ratio;

[0034] The second module is used to obtain the fault phase terminal voltage within a plurality of consecutive power frequency cycles when the judgment result is that the secondary arc is extinguished, and obtain a plurality of intrinsic mode components corresponding to each fault phase terminal voltage by using a variational mode decomposition algorithm;

[0035] The third module is used to determine, for each fault phase terminal voltage, the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components as the fault characteristic component;

[0036] The fourth module is used to calculate the deviation of the fault characteristic component of each fault phase terminal voltage. If the deviation of each fault characteristic component is constant to zero, the fault in the line is identified as a permanent fault.

[0037] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the methods in the first aspect when executing the computer program.

[0038] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute any one of the methods in the first aspect.

[0039] Compared with the prior art, the present invention has at least the following beneficial effects:

[0040] In this application, by identifying the time domain characteristics of the fault phase terminal voltage of the transmission network and using digital processing and waveform morphology methods to judge the nature of the fault, the permanent fault identification of the transmission network can be achieved quickly and accurately, which has important practical significance for maintaining the safe and stable operation of the system, and solves the problem of fault nature identification when the transmission line is reclosed under the existing background.

[0041] In this application, signal processing algorithms are used to improve the ability to identify and extract features of weak fault signals. By extracting key fault features from weak signals, a complete line fault nature identification process is formed to solve the problem of difficulty in identifying the nature of single-phase grounding faults, thereby effectively improving the safe and stable operation level of the transmission network. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0043] Figure 1 A flowchart of an identification method according to an embodiment of the present invention;

[0044] Figure 2 A method flow chart of another form of the identification method in an embodiment of the present invention;

[0045] Figure 3 It is a flow chart of secondary arc extinction detection in an embodiment of the present invention;

[0046] Figure 4 is a flow chart of variational mode decomposition in an embodiment of the present invention;

[0047] Figure 5 This is a flow chart of fault property judgment in an embodiment of the present invention;

[0048] Figure 6 This is a fault simulation model diagram in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0050] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0052] In the description of the embodiments of the present invention, "plurality" means at least 2.

[0053] Embodiment 1: In order to solve the problems that after the circuit breakers at both ends of the line trip, the voltage at the line end is weak, the transient characteristics are complex, it is difficult to accurately extract effective fault characteristics, and the accuracy of fault nature judgment is low, this embodiment provides a permanent fault identification method for new energy grid-connected tie lines based on variational mode decomposition, such as Figure 1 and Figure 2 As shown, the specific steps include:

[0054] S1, obtaining the terminal voltage of the fault phase after the circuit breaker initiates the single-phase opening signal, and obtaining a judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and based on the voltage energy integral ratio.

[0055] Among them, when the circuit breaker starts the single-phase opening signal, the terminal voltage of the faulty phase is collected, and according to the collected terminal voltage of the faulty phase, it is judged whether the secondary arc in the line is extinguished based on the voltage energy integral ratio.

[0056] Optionally, the above-mentioned determination result of whether the secondary arc in the circuit is extinguished is obtained based on the terminal voltage and the voltage energy integral ratio, see Figure 3 , Figure 3 This is the secondary arc extinction detection flow chart, specifically:

[0057] First, calculate the voltage energy value: In the formula, J i Indicates voltage energy value, U i represents the terminal voltage, and N represents the number of samples;

[0058] Secondly, calculate the voltage energy integral ratio: When the voltage energy integral ratio is greater than the threshold value, that is, When R set It represents the threshold value, and the judgment result of whether the secondary arc in the circuit is extinguished is obtained.

[0059] S2, when the judgment result is that the secondary arc is extinguished, the fault phase terminal voltage within multiple consecutive power frequency cycles is obtained, and the variational mode decomposition algorithm is used to obtain multiple intrinsic mode components corresponding to each of the fault phase terminal voltages; specifically, the fault phase terminal voltage within 5 consecutive power frequency cycles can be collected.

[0060] Among them, using Figure 4 The variational mode decomposition flow chart shown in the figure decomposes the fault phase recovery voltage, where the variational mode decomposition algorithm decomposes the signal x(t) into a series of eigenmode components u with specific center frequencies and limited bandwidths. k , the decomposition model can be expressed as the minimum sum of the estimated bandwidths of all eigenmode components, as follows:

[0061] Then, the above constraint model is converted into an unconstrained model using the quadratic penalty factor α and the Lagrange multiplication operator λ. The formula is as follows:

[0062]

[0063] Among them, α plays a role in ensuring the accuracy of signal reconstruction, λ enhances the strictness of the constraint and participates in the subsequent iterative process. is the inner product calculation formula, is the square L 2 Norm calculation formula.

[0064] Optionally, the variational mode decomposition algorithm is used to obtain multiple intrinsic mode components corresponding to each fault phase terminal voltage, specifically:

[0065] S21, converting a decomposition model that is a constrained model based on a variational mode decomposition algorithm into a decomposition model of an unconstrained model by using a quadratic penalty factor and a Lagrange multiplication operator.

[0066] The decomposition model of the constraint model is specifically:

[0067]

[0068] In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, x represents the original input signal, K represents the total number of eigenmode components into which the signal will be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, and t represents time.

[0069] Furthermore, the decomposition model of the above unconstrained model is specifically:

[0070]

[0071] In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, α represents the quadratic penalty factor, λ represents the Lagrangian multiplication operator, x(t) represents the original input signal, K represents the total number of eigenmode components into which the signal will be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, t represents time, and L represents the Lagrangian function.

[0072] S22, performing secondary optimization on the decomposition model of the unconstrained model by using a multiplication operator alternating direction method, and obtaining corresponding multiple intrinsic mode components according to each fault phase terminal voltage based on the optimized decomposition model of the unconstrained model.

[0073] Among them, the multiplication operator alternating direction method is used for secondary optimization until the convergence condition is met and the optimal solution is obtained. Figure 4 First, set the number of decomposition modes, which can be set to 3 in this embodiment, set the secondary penalty factor, and initialize various parameters; secondly, calculate ω k n+1 , After iteration, when k = K, given the convergence accuracy, when the convergence condition is met, see Figure 4 , thus obtaining three eigenmode components, and the formula of the eigenmode components calculated at this time is as follows:

[0074] The above-mentioned eigenmode components are specifically:

[0075]

[0076] In the formula, and Represent x(t), u respectively i (t), λ(t), and Fourier transform, n is the number of iterations, x(t) represents the original input signal, u i (t) represents the i-th eigenmode component, λ(t) represents the Lagrange multiplier, represents the kth modal component of the n+1th iteration, α represents the penalty parameter, ω represents the frequency, and ω k represents the center frequency of the kth mode, and k represents the mode number, which is used to identify the specific mode.

[0077] S3, for each of the fault phase terminal voltages, determining the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components as the fault characteristic component.

[0078] Optionally, the kurtosis value of the above-mentioned intrinsic mode component is specifically:

[0079]

[0080] Where kur represents the intrinsic mode component IMF ω The kurtosis value, N represents the intrinsic mode component IMF ω Signal length, IMF ω represents the eigenmode component, IMF stands for intrinsic mode component ω The mean of .

[0081] S4, calculating the deviation of the fault characteristic component of each fault phase terminal voltage, if the deviation of each fault characteristic component is constant to zero, it is obtained that the fault in the line is a permanent fault.

[0082] Optionally, the offset of the fault characteristic component is specifically:

[0083]

[0084] Where ske represents the fault characteristic component IMF ω The deviation degree of N represents the fault characteristic component IMF ω Signal length, IMF ω represents the fault characteristic component, IMF represents the fault characteristic component ω The mean of the fault characteristic component IMF ω The standard deviation of .

[0085] Among them, according to the characteristic components obtained by screening, such as Figure 5 As shown, the skewness of the sampling value in each cycle is calculated within 5 cycles; if the characteristic component signal sampling value ske is always equal to 0 within 5 cycles, the fault is a permanent fault; if the characteristic component signal sampling value ske is always greater than zero, always less than zero, or shows alternating positive and negative characteristics within 5 cycles, the fault is a transient fault.

[0086] Specifically, the following is done by building the following in the electromagnetic transient simulation software PSCAD: Figure 6 The transmission network model shown is further explained:

[0087] Among them, the total length of the line is 342km, the line parameters are r1 = 0.027Ω / km, r0 = 0.1957Ω / km, L1 = 0.9651mH / km, L0 = 2.211mH / km, C1 = 0.0136uF / km, C0 = 0.0092uF / km, and the resistance of the parallel reactor at both ends of the line is X L =2017Ω,X N =550Ω. Different fault locations, fault distances, fault initial phase angles and transition resistances are set to verify the accuracy of the proposed fault property judgment method. The judgment results are shown in Table 1.

[0088] Table 1

[0089]

[0090] According to the fault nature judgment results in Table 1, the fault nature judgment results are analyzed and it is found that this method can correctly judge the fault nature in the line, is not affected by the fault location, fault distance, closing angle and transition resistance, and has a good fault nature judgment ability.

[0091] Embodiment 2: The embodiment of the present application provides a permanent fault identification system for a new energy grid-connected tie line based on variational mode decomposition, which is applied to any one of the permanent fault identification methods for a new energy grid-connected tie line based on variational mode decomposition in Embodiment 1, including:

[0092] The first module is used to obtain the terminal voltage of the fault phase after the circuit breaker initiates the single-phase opening signal, and obtain the judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and based on the voltage energy integral ratio.

[0093] The second module is used to obtain the fault phase terminal voltage within multiple consecutive power frequency cycles when the judgment result is that the secondary arc is extinguished, and use the variational mode decomposition algorithm to obtain multiple intrinsic mode components corresponding to each of the fault phase terminal voltages.

[0094] The third module is used to determine, for each of the fault phase terminal voltages, the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components as the fault characteristic component.

[0095] The fourth module is used to calculate the deviation of the fault characteristic component of each fault phase terminal voltage. If the deviation of each fault characteristic component is constant to zero, the fault in the line is identified as a permanent fault.

[0096] Embodiment 3: The embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method described in any one of Embodiment 1 is implemented.

[0097] Embodiment 4: The embodiment of the present application provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to execute any one of the methods described in Embodiment 1.

[0098] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A permanent fault identification method for renewable energy grid-connected tie lines based on variational mode decomposition, characterized in that: The specific steps include: Obtaining the terminal voltage of the fault phase after the circuit breaker initiates the single-phase opening signal, and obtaining a judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and based on the voltage energy integral ratio; When the judgment result is that the secondary arc is extinguished, the fault phase terminal voltage within a plurality of consecutive power frequency cycles is obtained, and a plurality of intrinsic mode components corresponding to each of the fault phase terminal voltages are obtained by using a variational mode decomposition algorithm; For each of the fault phase terminal voltages, determining the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components as the fault characteristic component; The deviation of the fault characteristic component of each fault phase terminal voltage is calculated. If the deviation of each fault characteristic component is constant to zero, an identification result that the fault in the line is a permanent fault is obtained.

2. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 1 is characterized in that: The judgment result of whether the secondary arc in the circuit is extinguished is obtained according to the terminal voltage and based on the voltage energy integral ratio, specifically: Calculate the voltage energy value: In the formula, J i Indicates voltage energy value, U i represents the terminal voltage, and N represents the number of samples; Calculate the voltage energy integral ratio: When the voltage energy integral ratio is greater than the threshold value, a judgment result of the extinguishing of the secondary arc in the circuit is obtained.

3. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 1 is characterized in that: The variational mode decomposition algorithm is used to obtain multiple intrinsic mode components corresponding to each fault phase terminal voltage, specifically: The decomposition model based on the variational mode decomposition algorithm and which is a constrained model is converted into a decomposition model of an unconstrained model by using a quadratic penalty factor and a Lagrange multiplication operator; The decomposition model of the unconstrained model is optimized twice using the multiplication operator alternating direction method. Based on the optimized decomposition model of the unconstrained model, multiple corresponding intrinsic mode components are obtained according to the terminal voltage of each fault phase.

4. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 3 is characterized in that: The decomposition model of the constraint model is specifically: In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, x represents the original input signal, K represents the total number of eigenmode components of the signal to be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, and t represents time; The decomposition model of the unconstrained model is specifically: In the formula, u k represents the eigenmode components to be determined, ω k represents the center frequency of each eigenmode component, is the partial derivative of the function with respect to time t, α represents the quadratic penalty factor, λ represents the Lagrangian multiplication operator, x(t) represents the original input signal, K represents the total number of eigenmode components into which the signal will be decomposed, k represents the number of each mode, δ(t) represents the Dirac function, j represents the imaginary unit, t represents time, and L represents the Lagrangian function.

5. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 3 is characterized in that: Each of the eigenmode components is specifically: In the formula, and Represent x(t), u respectively i (t), λ(t), and Fourier transform, n is the number of iterations, x(t) represents the original input signal, u i (t) represents the i-th eigenmode component, λ(t) represents the Lagrange multiplier, represents the kth modal component of the n+1th iteration, α represents the penalty parameter, ω represents the frequency, and ω k represents the center frequency of the kth mode, and k represents the mode number, which is used to identify the specific mode.

6. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 1 is characterized in that: The kurtosis value of the eigenmode component is specifically: Where kur represents the intrinsic mode component IMF ω The kurtosis value, N represents the intrinsic mode component IMF ω Signal length, IMF ω represents the eigenmode component, IMF stands for intrinsic mode component ω The mean of .

7. The permanent fault identification method of renewable energy grid-connected tie line based on variational mode decomposition according to claim 1 is characterized in that: The deviation degree of the fault characteristic component is specifically: Where ske represents the fault characteristic component IMF ω The deviation degree of N represents the fault characteristic component IMF ω Signal length, IMF ω represents the fault characteristic component, IMF represents the fault characteristic component ω The mean of the fault characteristic component IMF ω The standard deviation of .

8. A permanent fault identification system for renewable energy grid-connected tie lines based on variational mode decomposition, applied to a permanent fault identification method for renewable energy grid-connected tie lines based on variational mode decomposition according to any one of claims 1 to 7, characterized in that: include: The first module is used to obtain the terminal voltage of the fault phase after the circuit breaker starts the single-phase opening signal, and obtain the judgment result of whether the secondary arc in the line is extinguished according to the terminal voltage and based on the voltage energy integral ratio; The second module is used for obtaining the fault phase terminal voltage within a plurality of consecutive power frequency cycles when the judgment result is that the secondary arc is extinguished, and obtaining a plurality of intrinsic mode components corresponding to each of the fault phase terminal voltages by using a variational mode decomposition algorithm; The third module is used to determine, for each of the fault phase terminal voltages, the one with the smallest kurtosis value among the corresponding multiple intrinsic mode components as the fault characteristic component; The fourth module is used to calculate the deviation of the fault characteristic component of each fault phase terminal voltage. If the deviation of each fault characteristic component is constant to zero, the fault in the line is identified as a permanent fault.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the method according to any one of claims 1 to 7 is implemented when the processor executes the computer program.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which enable a computer to execute the method of any one of claims 1-7.

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