Power distribution network fault line selection method and system based on modal decomposition and adaptive noise

Abstract

The invention discloses a power distribution network fault line selection method and system based on modal decomposition and adaptive noise. The method comprises the steps that whether a power system breaks down or not is judged according to zero-sequence voltage; if a fault occurs, a transient zero-sequence current signal containing noise on the feeder line is obtained; selecting a main frequency mode component from the intrinsic mode components according to energy, frequency spectrum and time domain correlation of the intrinsic mode components; calculating the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, and the sum of the correlation coefficients of each feeder and other feeders; if the feeder line not only meets the minimum energy difference value, but also meets the condition that the sum of the correlation coefficients is less than zero, the feeder line is a fault feeder line. According to the method, the fault feeder is screened through the energy and the correlation coefficient, and the accuracy of power distribution network fault line selection judgment is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of distribution network fault line selection, and more specifically, relates to a distribution network fault line selection method and system based on fully integrated empirical mode decomposition and adaptive noise. Background Art

[0002] As more and more distributed energy sources are connected to the power grid, how to ensure the power supply reliability of the distribution network has become a research focus for scholars at home and abroad. The probability of a single-phase grounding fault in the power system accounts for more than 80% of all fault conditions. When a single-phase fault occurs, the line voltage of the three-phase system remains balanced, so it can continue to supply power for 1-2 hours. If it is not handled for a long time, it will cause insulation breakdown to develop into a phase-to-phase fault, so it is necessary to locate and remove the faulty section in time. However, due to the compensation effect of the arc suppression coil, the fault current is small, which makes it impossible for the existing research methods to accurately identify it.

[0003] With the development of deep learning, the current fault section location methods can be roughly divided into two types: traditional methods based on fault characteristics and modern methods based on artificial intelligence algorithms. According to the different fault feature quantities used, the traditional methods can be divided into steady-state information-based, matrix method and transient feature quantity-based. The method of fault section location based on steady-state information is easily affected by topological changes, arc suppression coils, etc., and the matrix method is affected by data loss and distortion. The method of fault section location based on transient feature quantities can be further refined into traveling wave method and signal decomposition method. The traveling wave method uses the refraction and reflection characteristics of the traveling wave signal when a fault occurs, and combines the wave speed and transmission time to measure the distance to the fault. According to the difference in the electrical quantity used, the traveling wave method is divided into single-end traveling wave method and double-end traveling wave method. However, the traveling wave method requires special equipment, high cost, and there is a certain difficulty in wave head identification, and it is necessary to further improve the waveform data and improve the waveform fault feature matching technology. Some modern signal processing methods are often used to decompose the measurement data into different frequency band components.

[0004] CN110632462A provides a method for locating a small current grounding fault and its system, computer equipment, and medium, including the following steps: receiving zero-mode current recording data of each monitoring node of the line in real time when a line fault occurs; wherein each line is divided into multiple sections, and multiple monitoring nodes are set in each section; extracting the transient component of the zero-mode current recording data, and determining its transient amplitude and transient resonant frequency according to the transient component; generating the transient characteristic quantity of each monitoring node according to the transient amplitude and transient resonant frequency; determining the section where the fault point is located according to the transient characteristic quantity of each monitoring node. However, the fault location method does not perform signal decomposition on the zero-mode current recording data obtained by the monitoring node, and cannot remove the influence of noise; and does not establish a global transient characteristic quantity index, only considering the amplitude and resonant frequency, and does not consider that the transient zero-mode current waveform of the fault line is opposite to the polarity of the non-fault line. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides a distribution network fault line selection method and system based on fully integrated empirical mode decomposition and adaptive noise.

[0006] The present invention adopts the following technical solution.

[0007] The first aspect of the present invention proposes a distribution network fault line selection method based on modal decomposition and adaptive noise, which is characterized by comprising the following contents: Monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal components are selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Calculate the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, as well as the sum of the correlation coefficients of each feeder and other feeders; if there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder; otherwise, return to monitoring the zero-sequence voltage of the power system and determine whether the power system is faulty based on the zero-sequence voltage.

[0008] Preferably, judging whether the power system is faulty according to the zero-sequence voltage is specifically: Determine whether the zero-sequence voltage exceeds the set multiple of the bus rated voltage. If so, the power system is faulty, otherwise there is no fault; the value range of the set multiple is between 0.05-0.15.

[0009] Preferably, the transient zero-sequence current of the multiple period set after the fault is the transient zero-sequence current of 1 / 4 period.

[0010] The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components, specifically: The transient zero-sequence current signal containing noise is taken as the original signal, and multiple pairs of mutually opposite white noises are sequentially added to the original signal; after each addition, the signal is modally decomposed to obtain its first intrinsic modal component; all the first intrinsic modal components are averaged, which is the first intrinsic modal component of the transient zero-sequence current signal containing noise; Subtract the first intrinsic modal component of the transient zero-sequence current signal containing noise from the original signal to obtain the residual value; Add multiple pairs of adaptive noises to the residual value; perform modal decomposition after each addition to obtain its second intrinsic modal component; average all the second intrinsic modal components, which is the second intrinsic modal component of the transient zero-sequence current signal containing noise; The second intrinsic modal component of the transient zero-sequence current signal containing noise is subtracted from the residual value to obtain the updated residual, and the above process is repeated until the updated residual cannot continue the modal decomposition.

[0011] Preferably, the adding of multiple pairs of adaptive noises is specifically: If the decomposition results in the transient zero-sequence current signal containing noise, k The intrinsic modal components are then added to the original signal to perform modal decomposition on multiple pairs of mutually opposite white noises, and the first k -1 intrinsic modal component; for each pair of white noise k -1 inherent modal component multiplied by the adaptive amplitude corresponds to each pair of adaptive white noise; the adaptive amplitude is the amplitude of multiple pairs of mutually opposite white noises added to the original signal multiplied by the energy of the residual at this time.

[0012] Preferably, the main frequency modal component is selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components, specifically: First, the ratio of the energy of each intrinsic modal component to the energy of all intrinsic modal components is calculated. If the ratio of any intrinsic modal component exceeds the set energy ratio threshold, the intrinsic modal component with the largest energy is selected as the main frequency modal component. Otherwise, the spectrum of each intrinsic modal component is obtained by Fourier transform, and the comprehensive index is calculated. The intrinsic modal component with the largest comprehensive index is taken as the main frequency modal component; Comprehensive indicators The calculation formula is:

[0013] in, , , is the set weight, For the k The energy of the natural mode components, K is the total number of natural mode components, is the maximum value of the energy of the natural mode components, is the standard deviation of the energy of the intrinsic mode components; For the k The peak frequency of the spectrum of the natural mode component; , Respectively k The frequency at which the spectrum of the natural mode component drops by a set dB on both sides; for k The intrinsic modal components; is the corresponding original signal, n is the sampling point; is the time domain correlation; represents the inner product operation; is the norm.

[0014] Preferably, the calculation of the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, and the sum of the correlation coefficients of each feeder with other feeders is specifically as follows: The difference between the energy of each feeder main frequency modal component and the energy of the sum of the main frequency modal components of other feeders , the calculation formula is:

[0015] in, N is the number of sampling points of the original signal, i , j Indicates i , j Feeder, , For the i, j The main frequency modal component of the feeder n The value of the sampling point, J is the total number of feeders; The sum of the correlation coefficients of each feeder with other feeders The calculation formula is:

[0016] in, , For the i, j The original signal of the feeder n The value of the sampling point, , For the i , j The average value of all sampling points of the original signal of the feeder.

[0017] The second aspect of the present invention proposes a distribution network fault line selection system based on modal decomposition and adaptive noise using the method described in the first aspect of the present invention, comprising: a monitoring module, a main frequency modal component acquisition module, and a distribution network fault line selection module, characterized in that: Monitoring module: monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; Main frequency modal component acquisition module: decomposes the transient zero-sequence current signal containing noise through modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal component is selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Distribution network fault line selection module: calculate the difference between the energy of the main frequency modal component of each feeder and the sum of the energy of the main frequency modal components of other feeders, as well as the sum of the correlation coefficients of each feeder and other feeders; if there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder, otherwise it returns to monitor the zero-sequence voltage of the power system and determines whether the power system is faulty based on the zero-sequence voltage.

[0018] The third aspect of the present invention proposes a device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of a distribution network fault line selection method based on modal decomposition and adaptive noise as described in the first aspect of the present invention.

[0019] The fourth aspect of the present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of a distribution network fault line selection method based on modal decomposition and adaptive noise described in the first aspect of the present invention are used.

[0020] The beneficial effect of the present invention is that, compared with the prior art, the present invention is based on a distribution network fault line selection method and system that fully integrates empirical mode decomposition and adaptive noise, performs theoretical analysis on a simplified single-phase grounding fault transient analysis equivalent circuit, detects the zero-sequence current signal of each feeder to obtain a feeder with a transient zero-sequence current signal containing noise, decomposes the transient zero-sequence current signal containing noise through mode decomposition and an adaptive noise algorithm to obtain a plurality of inherent mode components, selects a main frequency mode component from the inherent mode component according to the energy, spectrum and time domain correlation of the inherent mode component, determines the energy and correlation coefficient of the main frequency mode component of each feeder based on the correlation and energy difference theory, thereby obtaining a feeder with the maximum energy and a correlation coefficient less than zero as a fault feeder, thereby improving the accuracy of distribution network fault line selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flow chart of the present invention; Figure 2 This is an equivalent circuit diagram of the simplified circuit of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0023] As attached Figure 1 As shown, embodiment 1 of the present invention discloses a distribution network fault line selection method based on modal decomposition and adaptive noise, comprising the following steps: like Figure 2 As shown, the circuit is simplified according to the actual situation, and the simplified single-phase ground fault transient analysis equivalent circuit is theoretically analyzed. The relationship between the polarity and amplitude of the fault line and the healthy line is analyzed, and it is concluded that the polarity of the fault line is different from that of the healthy line, and the amplitude of the fault line is significantly greater than that of the healthy line. Specifically, at the power frequency Under this condition, it is approximately considered that the inductive reactance of the arc suppression coil is equal to the capacitive reactance of the system to ground, that is:

[0024] In the formula, It is 3 times the arc suppression coil inductance; is the distributed capacitance of the line per unit length to the ground; It is the sum of the lengths of all outgoing lines of the system; It is the sum of the distributed capacitance of all outgoing lines to ground; Since the capacitive reactance of the system to ground decreases with the increase of frequency, and the inductive reactance of the arc suppression coil increases with the increase of frequency, at the transient main resonant frequency Under this condition, the relationship between the system's capacitive reactance to ground and the arc suppression coil's inductive reactance is as follows:

[0025] In the formula, is the ratio of the transient main resonant frequency to the power frequency; it can be seen from the above formula that when When , it can be approximately considered that the inductive reactance of the arc suppression coil is 9 times greater than the capacitive reactance of the ground capacitor. In this way, the effect of the arc suppression coil can be ignored in the process of model simplification, and the simplified single-phase ground fault transient analysis equivalent circuit is obtained, as shown in Figure 2 As shown, a theoretical analysis is performed and the following formula is obtained:

[0026] In the formula, is the voltage across the line, R is the equivalent resistance, is the bus voltage amplitude, For the moment, is the initial phase angle, For the h The zero-sequence current of a healthy line, For the h The capacitance to ground of a healthy line, is the zero-sequence current of the fault line; H The total number of healthy lines set up , put it into the above equation and solve it, we can get:

[0027]

[0028]

[0029]

[0030] In the formula, , for r Two solutions of ; is an imaginary number; is the characteristic root; because When it is greater than 1, it can be concluded that the difference between the energy of the main frequency modal component of the transient zero-sequence current of the fault line and the energy of the sum of the main frequency modal components of other feeders is the smallest, and the transient zero-sequence current waveform of the fault line and the transient zero-sequence current waveforms of other feeders present an upside-down state.

[0031] Monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal components are selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Calculate the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, as well as the sum of the correlation coefficients of each feeder and other feeders; if there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder; otherwise, return to monitoring the zero-sequence voltage of the power system and determine whether the power system is faulty based on the zero-sequence voltage.

[0032] The method of judging whether the power system is faulty according to the zero-sequence voltage is specifically as follows: Determine whether the zero-sequence voltage exceeds the set multiple of the bus rated voltage. If so, the power system is faulty, otherwise there is no fault; the value range of the set multiple is between 0.05-0.15.

[0033] The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components, specifically: The transient zero-sequence current signal containing noise is taken as the original signal, and multiple pairs of mutually opposite white noises are sequentially added to the original signal; after each addition, the signal is modally decomposed to obtain its first intrinsic modal component; all the first intrinsic modal components are averaged, which is the first intrinsic modal component of the transient zero-sequence current signal containing noise; Subtract the first intrinsic modal component of the transient zero-sequence current signal containing noise from the original signal to obtain the residual value; Add multiple pairs of adaptive noises to the residual value; perform modal decomposition after each addition to obtain its second intrinsic modal component; average all the second intrinsic modal components, which is the second intrinsic modal component of the transient zero-sequence current signal containing noise; The second intrinsic modal component of the transient zero-sequence current signal containing noise is subtracted from the residual value to obtain the updated residual, and the above process is repeated until the updated residual cannot continue the modal decomposition.

[0034] The adding of multiple pairs of adaptive noises is specifically as follows: If the decomposition results in the transient zero-sequence current signal containing noise, k The intrinsic modal components are then added to the original signal to perform modal decomposition on multiple pairs of mutually opposite white noises, and the first k -1 intrinsic modal component; for each pair of white noise k -1 inherent modal component multiplied by the adaptive amplitude corresponds to each pair of adaptive white noise; the adaptive amplitude is the amplitude of multiple pairs of mutually opposite white noises added to the original signal multiplied by the energy of the residual at this time.

[0035] According to the energy, spectrum and time domain correlation of the intrinsic modal components, the main frequency modal components are selected from the intrinsic modal components, specifically: First, the ratio of the energy of each intrinsic modal component to the energy of all intrinsic modal components is calculated. If the ratio of any intrinsic modal component exceeds the set energy ratio threshold, the intrinsic modal component with the largest energy is selected as the main frequency modal component. Otherwise, the spectrum of each intrinsic modal component is obtained by Fourier transform, and the comprehensive index is calculated. The intrinsic modal component with the largest comprehensive index is taken as the main frequency modal component; Comprehensive indicators The calculation formula is:

[0036] in, , , is the set weight, For the k The energy of the natural mode components, K is the total number of natural mode components, is the maximum value of the energy of the natural mode components, is the standard deviation of the energy of the intrinsic mode components; For the k The peak frequency of the spectrum of the natural mode component; , Respectively k The frequency at which the spectrum of the natural mode component drops by a set dB on both sides; for k The intrinsic modal components; is the corresponding original signal, n is the sampling point; is the time domain correlation; represents the inner product operation; is the norm.

[0037] The calculation of the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, and the sum of the correlation coefficients of each feeder with other feeders, is specifically: The difference between the energy of each feeder main frequency modal component and the energy of the sum of the main frequency modal components of other feeders , the calculation formula is:

[0038] in, N is the number of sampling points of the original signal, i , j Indicates i , j Feeder, , For the i, j The main frequency modal component of the feeder n The value of the sampling point, J is the total number of feeders; The sum of the correlation coefficients of each feeder with other feeders The calculation formula is:

[0039] in, , For the i , j The original signal of the feeder n The value of the sampling point, , For the i , j The average value of all sampling points of the original signal of the feeder.

[0040] Embodiment 2 of the present invention proposes a distribution network fault line selection system based on modal decomposition and adaptive noise using the method described in Embodiment 1 of the present invention, comprising: a monitoring module, a main frequency modal component acquisition module, and a distribution network fault line selection module, characterized in that: Monitoring module: monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; Main frequency modal component acquisition module: decomposes the transient zero-sequence current signal containing noise through modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal component is selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Distribution network fault line selection module: calculate the difference between the energy of the main frequency modal component of each feeder and the sum of the energy of the main frequency modal components of other feeders, as well as the sum of the correlation coefficients of each feeder and other feeders; if there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder, otherwise it returns to monitor the zero-sequence voltage of the power system and determines whether the power system is faulty based on the zero-sequence voltage.

[0041] Embodiment 3 of the present invention proposes a device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of a distribution network fault line selection method based on modal decomposition and adaptive noise as described in Embodiment 1 of the present invention.

[0042] Embodiment 4 of the present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of a distribution network fault line selection method based on modal decomposition and adaptive noise described in Embodiment 1 of the present invention are used.

[0043] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A distribution network fault line selection method based on modal decomposition and adaptive noise, characterized in that: Includes the following: Monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal components are selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Calculate the difference between the energy of the main frequency modal component of each feeder and the sum of the energy of the main frequency modal components of other feeders, and the sum of the correlation coefficients of each feeder with other feeders; If there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder. Otherwise, the zero-sequence voltage of the power system is monitored and whether the power system is faulty is determined based on the zero-sequence voltage.

2. The method for fault line selection in a distribution network based on modal decomposition and adaptive noise according to claim 1, characterized in that: The method of judging whether the power system is faulty according to the zero-sequence voltage is specifically as follows: Determine whether the zero-sequence voltage exceeds the set multiple of the bus rated voltage. If so, the power system is faulty, otherwise there is no fault; the value range of the set multiple is between 0.05-0.

15.

3. The method for fault line selection in distribution network based on modal decomposition and adaptive noise according to claim 1, characterized in that: The transient zero-sequence current of the multiple period set after the fault is the transient zero-sequence current of 1 / 4 period.

4. The method for fault line selection in distribution network based on modal decomposition and adaptive noise according to claim 1, characterized in that: The transient zero-sequence current signal containing noise is decomposed by modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components, specifically: The transient zero-sequence current signal containing noise is taken as the original signal, and multiple pairs of mutually opposite white noises are sequentially added to the original signal; after each addition, the signal is modally decomposed to obtain its first intrinsic modal component; all the first intrinsic modal components are averaged, which is the first intrinsic modal component of the transient zero-sequence current signal containing noise; Subtract the first intrinsic modal component of the transient zero-sequence current signal containing noise from the original signal to obtain the residual value; Add multiple pairs of adaptive noises to the residual value; perform modal decomposition after each addition to obtain its second intrinsic modal component; average all the second intrinsic modal components, which is the second intrinsic modal component of the transient zero-sequence current signal containing noise; The second intrinsic modal component of the transient zero-sequence current signal containing noise is subtracted from the residual value to obtain the updated residual, and the above process is repeated until the updated residual cannot continue the modal decomposition.

5. The method for fault line selection in distribution network based on modal decomposition and adaptive noise according to claim 4 is characterized in that: The adding of multiple pairs of adaptive noises is specifically as follows: If the decomposition results in the transient zero-sequence current signal containing noise, k The intrinsic modal components are then added to the original signal to perform modal decomposition on multiple pairs of mutually opposite white noises, and the first k -1 natural mode component; For each pair of white noise k -1 inherent modal component multiplied by the adaptive amplitude corresponds to each pair of adaptive white noise; the adaptive amplitude is the amplitude of multiple pairs of mutually opposite white noises added to the original signal multiplied by the energy of the residual at this time.

6. The method for fault line selection in distribution network based on modal decomposition and adaptive noise according to claim 5, characterized in that: According to the energy, spectrum and time domain correlation of the intrinsic modal components, the main frequency modal components are selected from the intrinsic modal components, specifically: First, the ratio of the energy of each intrinsic modal component to the energy of all intrinsic modal components is calculated. If the ratio of any intrinsic modal component exceeds the set energy ratio threshold, the intrinsic modal component with the largest energy is selected as the main frequency modal component. Otherwise, the spectrum of each intrinsic modal component is obtained by Fourier transform, and the comprehensive index is calculated. The intrinsic modal component with the largest comprehensive index is taken as the main frequency modal component; Comprehensive indicators The calculation formula is: in, , , is the set weight, For the k The energy of the natural mode components, K is the total number of natural mode components, is the maximum value of the energy of the natural mode components, is the standard deviation of the energy of the intrinsic mode components; For the k The peak frequency of the spectrum of the natural mode component; , Respectively k The frequency at which the spectrum of the natural mode component drops by a set dB on both sides; for k The intrinsic modal components; is the corresponding original signal, n is the sampling point; is the time domain correlation; represents the inner product operation; is the norm.

7. The method for fault line selection in distribution network based on modal decomposition and adaptive noise according to claim 6, characterized in that: The calculation of the difference between the energy of the main frequency modal component of each feeder and the energy of the sum of the main frequency modal components of other feeders, and the sum of the correlation coefficients of each feeder with other feeders, is specifically: The difference between the energy of each feeder main frequency modal component and the energy of the sum of the main frequency modal components of other feeders , the calculation formula is: in, N is the number of sampling points of the original signal, i , j Indicates i , j Feeder, , For the i, j The main frequency modal component of the feeder n The value of the sampling point, J is the total number of feeders; The sum of the correlation coefficients of each feeder with other feeders The calculation formula is: in, , For the i , j The original signal of the feeder n The value of the sampling point, , For the i , j The average value of all sampling points of the original signal of the feeder.

8. A distribution network fault line selection system based on modal decomposition and adaptive noise using the method according to any one of claims 1 to 7, comprising: The monitoring module, the main frequency modal component acquisition module and the distribution network fault line selection module are characterized by: Monitoring module: monitor the zero-sequence voltage of the power system in real time, and judge whether the power system is faulty according to the zero-sequence voltage; if there is a fault, record and collect the transient zero-sequence current of the set multiple period after the fault to obtain the transient zero-sequence current signal containing noise on the feeder; Main frequency modal component acquisition module: decomposes the transient zero-sequence current signal containing noise through modal decomposition and adaptive noise algorithm to obtain multiple inherent modal components. The main frequency modal component is selected from the inherent modal components according to the energy, spectrum and time domain correlation of the inherent modal components. Distribution network fault line selection module: calculate the difference between the energy of the main frequency modal component of each feeder and the sum of the energy of the main frequency modal components of other feeders, as well as the sum of the correlation coefficients of each feeder and other feeders; if there is a feeder that satisfies both the minimum energy difference and the sum of the correlation coefficients being less than zero, then the feeder is a faulty feeder, otherwise it returns to monitor the zero-sequence voltage of the power system and determines whether the power system is faulty based on the zero-sequence voltage.

9. A device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of a distribution network fault line selection method based on modal decomposition and adaptive noise as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of a method for fault line selection in a distribution network based on modal decomposition and adaptive noise as claimed in any one of claims 1 to 7 are used.

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