Distribution network T-connection line fault positioning method based on SVMD

Abstract

The invention belongs to the technical field of power system power distribution network relay protection, and provides a distribution network T-connection line fault positioning method based on SVMD, which comprises the following steps: step 1, acquiring three-phase voltage by using a traveling wave detection device installed on a distribution network line, and performing phase-mode conversion to obtain a voltage traveling wave alpha-mode component; step 2, decomposing the voltage traveling wave alpha-mode component by using continuous variational mode decomposition (SVMD) to obtain intrinsic mode components of different frequencies; 3, calculating the kurtosis value of each modal component, and selecting the modal component corresponding to the maximum kurtosis value as a characteristic modal; compared with the traditional VMD, the SVMD method using the successive decomposition strategy is different in that the mode number does not need to be preset, and the mode component is extracted by optimizing the spectrum compactness, the residual signal energy minimization and the mode orthogonality principle, so that the method can eliminate the dependence on the prior knowledge, can better adapt to different signals, and can improve the robustness of the signal. The method can avoid the problem of mode aliasing, and has the characteristics of low calculation complexity and strong anti-noise capability.

Description

Technical Field

[0001] The invention belongs to the technical field of relay protection of power system distribution network, in particular to a distribution network T-connection line fault locating method based on SVMD. Background Art

[0002] In the power distribution system, fault location is an important link to ensure power supply reliability and rapid recovery. However, with the development of modern distribution networks, the structure of distribution lines has become increasingly complex, especially the T-connected lines, which have inaccurate fault location due to their branching characteristics. Traditional fault location methods are difficult to effectively extract key features in fault signals, especially when the signal amplitude is weak or the noise interference is severe, and the fault wave head is difficult to be accurately calibrated. Due to the limitations of the fixed number of decomposition layers, the wrong selection of the number of decomposition layers may lead to modal aliasing or information loss, affecting the accuracy of fault feature extraction. In view of the above problems, there is an urgent need for a fault location method that can adapt to the branch structure of T-connected lines, accurately extract fault features in complex backgrounds, and calibrate the wave head moment.

[0003] In recent years, VMD has been widely used due to its signal decomposition capability. In order to further improve the adaptability and resolution of decomposition, SVMD has gradually become a research hotspot; SVMD does not require the pre-setting of the number of modes, has low computational complexity, and can avoid mode aliasing by extracting the intrinsic mode components through successive decomposition, which is particularly suitable for feature extraction of non-stationary signals.

[0004] To this end, those skilled in the art have proposed a distribution network T-connected line fault location method based on SVMD to solve the problems raised in the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a distribution network T-connected line fault location method based on SVMD to solve the problem that the fault location method in the prior art is difficult to effectively extract key features in the fault signal, especially when the signal amplitude is weak or the noise interference is serious, the fault wave head is difficult to be accurately calibrated; due to the limitations of the fixed decomposition layer number, the wrong selection of the decomposition layer number may lead to modal aliasing or information loss, affecting the extraction accuracy of the fault features, and other problems.

[0006] The purpose of the present invention is to provide a distribution network T-connection line fault locating method based on SVMD, which can accurately determine the specific location of the fault.

[0007] The technical solution adopted by the present invention is a distribution network T-connection line fault location method based on SVMD, comprising:

[0008] Step 1: Use the traveling wave detection device installed on the distribution network line to collect the three-phase voltage, and perform phase mode transformation to obtain the α mode component of the voltage traveling wave;

[0009] Step 2: Decompose the α-mode component of the voltage traveling wave using continuous variational mode decomposition (SVMD) to obtain eigenmode components of different frequencies;

[0010] Step 3: Calculate the kurtosis value of each modal component, select the modal component corresponding to the maximum kurtosis value as the characteristic mode, and use the symmetric difference energy operator SDEO to obtain the arrival time of the fault wave head;

[0011] Step 4: Determine the specific fault location based on the arrival time of the fault wave head and the two-terminal distance measurement formula.

[0012] Preferably, the specific process of step 1 is as follows: when a T-connected distribution network line fails, a three-phase voltage traveling wave is obtained by using a traveling wave detection device installed at the head end, the end end and the end end of the branch line of the distribution network main line, and a Karen Bell transformation is performed on the collected three-phase voltage traveling wave to obtain the voltage traveling wave α mode component u αi , i is the number of the traveling wave detection device i = 1, 2, 3;

[0013] Assume that the fault occurs at t, the start time of sampling is (t-0.001) seconds, and the end time of sampling is (t+0.001) seconds, and a traveling wave signal with a data window length of 2ms is obtained.

[0014] Preferably, in step 1, the three-phase voltage is transformed by Karlenberg transformation to obtain the voltage traveling wave α mode component u αi The calculation formula is as follows:

[0015] The calculation formula of the α-mode component of the voltage traveling wave is:

[0016] u αi =(u i_a -u i_b ) / 3

[0017] Among them, u i_a 、u i_b The a-phase and b-phase voltages collected by each traveling wave detection device.

[0018] Preferably, the specific process of step 2 is: perform SVMD decomposition on the α-mode component of the voltage traveling wave, adopt a method of obtaining an approximate value of the modal center frequency and continuously extracting the modal components, adaptively determine the number of decomposition modes K, and obtain the eigenmodal components of different center frequencies:

[0019]

[0020] Among them, SVMD(u αi ) represents the α-mode component u of the voltage traveling wave αi Perform SVMD decomposition, IMFk i(n) is the kth modal component after SVMD decomposition of the α-mode component of the voltage traveling wave of the i-th traveling wave detection device, k=1, 2, ..., K; n is the sampling point.

[0021] Preferably, the specific process of step 3 is: calculate each modal component IMFk i The kurtosis value of (n) is defined, and the modal component corresponding to the maximum kurtosis value is defined as the characteristic mode. The symmetric difference energy operator SDEO is used to obtain the arrival time t of the fault wave head in the characteristic mode. i ;

[0022] Follow the steps below to implement it:

[0023] Step 3.1: Calculate each modal component IMFk i The kurtosis value of (n) Define the modal component corresponding to the maximum kurtosis value as the characteristic mode IMFp i (n), the kurtosis is calculated as follows:

[0024]

[0025] Among them, μ and σ are the intrinsic mode components IMFk i (n) mean and standard deviation, N is the total number of sampling points;

[0026] Step 3.2: Use the symmetric difference energy operator SDEO to obtain the arrival time t of the fault wave head in the characteristic mode i ; SDEO is calculated as follows:

[0027]

[0028] Among them, ψ[IMFp i (n)] is IMFp i The symmetric difference energy operator at time n in (n), and Represents the Teager-Kaiser energy operator at time n-1 and n+1.

[0029] Preferably, the specific process of step 4 is: calculating the distance d1 from the fault point to the head end of the trunk line and the distance d2 to the end of the trunk line according to the two-terminal distance measurement formula:

[0030]

[0031]

[0032] In the formula, l MN is the line length from the beginning of the trunk line to the end of the trunk line, v α is the α modulus wave velocity, L and C are the line inductance and capacitance parameters;

[0033] when When the fault is determined to be located at the branch point T or on the branch line, where l MT is the distance from the beginning of the trunk line to the T branch point, l NT is the distance from the end of the trunk line to the branch point T, δ is the set threshold, δ=0.005; the distance from the fault point to the end of the branch is:

[0034]

[0035] In the formula, l MP It is the line length from the beginning of the main line to the end of the branch line;

[0036] Otherwise, the fault distance is on the main line, and the distance from the head end of the line is d1.

[0037] The distribution network T-connection line fault location system based on SVMD, using the above-mentioned distribution network T-connection line fault location method based on SVMD, includes:

[0038] Traveling wave detection device: installed at the head end, end end and branch end of the distribution network trunk line, used to collect three-phase voltage traveling wave signals;

[0039] Signal processing module: receiving the three-phase voltage traveling wave signal collected by the traveling wave detection device, performing phase mode transformation to obtain the α-mode component of the voltage traveling wave, and then decomposing the α-mode component of the voltage traveling wave using the continuous variational mode decomposition (SVMD) technology to obtain the intrinsic mode components of different frequencies;

[0040] Feature extraction module: calculate the kurtosis value of each modal component, select the modal component corresponding to the maximum kurtosis value as the characteristic mode, and use the symmetric difference energy operator (SDEO) to obtain the arrival time of the fault wave head in the characteristic mode;

[0041] Fault location module: According to the arrival time of the fault wave head and the two-terminal distance measurement formula, the distance from the fault point to the beginning and end of the main line is calculated to determine the specific fault location.

[0042] A processor is configured to execute the above-mentioned SVMD-based distribution network T-connected line fault location method.

[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned SVMD-based distribution network T-connected line fault locating method.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] 1. Fault signal processing: The present invention uses the SVMD method with a successive decomposition strategy. Unlike the traditional VMD, the present invention does not require a preset modal number. The modal components are extracted by optimizing the spectral compactness, minimizing the residual signal energy and the modal orthogonality principle. This enables the method to eliminate the dependence on prior knowledge, better adapt to different signals, avoid the problem of modal aliasing, and has the characteristics of low computational complexity and strong anti-noise ability.

[0046] 2. Fault location: The present invention calculates the fault distance through the information of the three-terminal traveling wave detection device, which can avoid the problem of inaccurate positioning caused by a single erroneous data. At the same time, the fault location method described in the present invention is also adaptable to the single-phase high-resistance grounding condition under the resonant grounding system, which is beneficial to improve the accuracy of fault analysis and operation and maintenance efficiency and shorten the power outage time. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a method for locating a fault in a distribution network T-connected line based on SVMD according to the present invention;

[0048] Figure 2 This is a schematic diagram of a simulation model of a 10kV resonant grounding system according to an embodiment of the present invention;

[0049] Figure 3 This is a decomposition diagram of the line mode voltage SVMD at the M end in an embodiment of the present invention;

[0050] Figure 4 This is a decomposition diagram of the N-terminal line mode voltage SVMD in an embodiment of the present invention;

[0051] Figure 5 It is a decomposition diagram of the P-end line mode voltage SVMD in an embodiment of the present invention;

[0052] Figure 6 The instant when the initial wave head of the IMF with the maximum kurtosis value is calibrated by the TKEO energy operator in the embodiment of the present invention reaches the measurement position; wherein (a) is the TKEO energy operator wave head calibration diagram at the M end; (b) is the TKEO energy operator wave head calibration diagram at the N end; (c) is the TKEO energy operator wave head calibration diagram at the P end;

[0053] Figure 7 This is a framework diagram of the distribution network T-connected line fault location system based on SVMD of the present invention. DETAILED DESCRIPTION

[0054] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0055] Embodiment 1: Figure 1As shown, the present invention provides a distribution network T-connection line fault location method based on SVMD, comprising:

[0056] Step 1: When a fault occurs in the T-connected distribution network line, the three-phase voltage traveling wave is obtained by using the traveling wave detection device installed at the head end, the end end and the end end of the branch line of the distribution network main line. The collected three-phase voltage traveling wave is transformed by Karenberg to obtain the voltage traveling wave α mode component u αi , i is the number of the traveling wave detection device i = 1, 2, 3;

[0057] Assume that the fault occurs at t, the start time of sampling is (t-0.001) seconds, the end time of sampling is (t+0.001) seconds, and the traveling wave signal with a data window length of 2ms is obtained;

[0058] The calculation formula of the α-mode component of the voltage traveling wave is:

[0059] u αi =(u i_a -u i_b ) / 3

[0060] Among them, u i_a 、u i_b The a-phase and b-phase voltages collected by each traveling wave detection device;

[0061] Step 2: Perform SVMD decomposition on the α-mode component of the voltage traveling wave, obtain the approximate value of the modal center frequency and continuously extract the modal components, adaptively determine the number of decomposition modes K, and obtain the eigenmodal components of different center frequencies:

[0062]

[0063] Among them, SVMD(u αi ) represents the α-mode component u of the voltage traveling wave αi Perform SVMD decomposition, IMFk i (n) is the kth modal component after SVMD decomposition of the α-mode component of the voltage traveling wave of the i-th traveling wave detection device, k=1, 2, ..., K; n is a sampling point;

[0064] Step 3: Calculate each modal component IMFk i The kurtosis value of (n) is defined, and the modal component corresponding to the maximum kurtosis value is defined as the characteristic mode. The symmetric difference energy operator SDEO is used to obtain the arrival time t of the fault wave head in the characteristic mode. i ; Specific implementation steps:

[0065] Step 3.1: Calculate each modal component IMFk i The kurtosis value of (n) Define the modal component corresponding to the maximum kurtosis value as the characteristic mode IMFpi (n), the kurtosis is calculated as follows:

[0066]

[0067] Among them, μ and σ are the intrinsic mode components IMFk i (n) mean and standard deviation, N is the total number of sampling points;

[0068] Step 3.2: Use the symmetric difference energy operator SDEO to obtain the arrival time t of the fault wave head in the characteristic mode i ; SDEO is calculated as follows:

[0069]

[0070] Among them, ψ[IMFp i (n)] is IMFp i The symmetric difference energy operator at time n in (n), and represents the Teager-Kaiser energy operator at time n-1 and n+1;

[0071] Step 4: Calculate the distance d1 from the fault point to the beginning of the trunk line and the distance d2 from the fault point to the end of the trunk line according to the two-terminal distance measurement formula:

[0072]

[0073]

[0074] In the formula, l MN is the line length from the beginning of the trunk line to the end of the trunk line, v α is the α modulus wave velocity, L and C are the line inductance and capacitance parameters;

[0075] when When the fault is determined to be located at the branch point T or on the branch line, where l MT is the distance from the beginning of the trunk line to the T branch point, l NT is the distance from the end of the trunk line to the branch point T, δ is the set threshold, δ=0.005; the distance from the fault point to the end of the branch is:

[0076]

[0077] In the formula, l MP It is the line length from the beginning of the main line to the end of the branch line;

[0078] Otherwise, the fault distance is on the main line, and the distance from the head end of the line is d1.

[0079] The working principle of the SVMD-based distribution network T-connected line fault location method of the present invention is:

[0080] 1. Analysis of SVMD decomposition principle:

[0081] Successive Variational Mode Decomposition (SVMD) is a signal decomposition method. It is based on the strategy of extracting modes one by one, and solves the problems of decomposition efficiency and accuracy of traditional variational mode decomposition (VMD) when the number of modes is unknown. SVMD decomposes the signal into a series of narrowband modal components, extracts each mode one by one, finds each mode by optimizing the problem, and reduces the interference of the extracted modes and the influence of the residual signal.

[0082] Assume that the input signal f(t) is decomposed into the Lth modal component u L (t) and the residual signal f r (t), satisfying the following relationship:

[0083] f(t)=u L (t)+f r (t) (1)

[0084] The residual signal is the sum of the previously extracted modes and the untreated part f u (t)Composition:

[0085]

[0086] In each iteration, SVMD optimizes the extracted modes by the following three criteria:

[0087] (1) Spectral concentration: mode u L The spectrum of (t) should be closely centered around the center frequency ω L Expand:

[0088]

[0089] Among them, J1 is the spectrum concentration target, To find the partial derivative with respect to t, δ(t) is the unit impulse function.

[0090] (2) Minimum spectral overlap between the residual signal and the mode: The residual signal f r (t) In mode u L The energy in the frequency range (t) should be minimized:

[0091]

[0092] Among them, J2 spectrum overlap minimization objective, β L (t) is a filter designed to reduce spectral overlap.

[0093] (3) Avoid frequency overlap with previous modes: Mode u L (t) should have less energy around the center frequency of the previous mode:

[0094]

[0095] Among them, J3 is the spectrum overlap minimization target, β i (t) is a filter that avoids overlapping with the previous modal spectrum, i = 1, 2, ..., L-1.

[0096] To ensure complete reconstruction of the signal, the constraints are:

[0097]

[0098] 2. Kurtosis theory

[0099] Kurtosis is a statistical characteristic index that reflects the peak and tail characteristics of signal distribution. Fault signals usually contain short-term impact or abnormal components, which cause the kurtosis value of the signal to increase significantly. The larger the kurtosis, the more significant the fault impact characteristics contained in the mode. The kurtosis index can be used to screen out fault characteristic modes.

[0100] For the intrinsic mode component IMF(n), it is defined as:

[0101]

[0102] Where μ and σ are the mean and standard deviation of the intrinsic mode component IMF(n), respectively, and N is the total number of sampling points.

[0103] 3. Symmetric difference energy operator:

[0104] The symmetric difference energy operator SDEO (Symmetric Difference Energy Operator) introduces a sliding weighted average based on the Teager-Kaiser energy operator TKEO (Teager-Kaise Energy Operator); traditional energy operators are sensitive to noise, especially when the signal amplitude is low or the noise is high, the detection effect is easily affected. SDEO enhances the ability to capture local characteristics of the signal, which helps to accurately extract the true energy characteristics of the signal in complex environments; therefore, SDEO is used to achieve accurate calibration of the wave head.

[0105] For the modal component IMF(n), TKEO is defined as:

[0106] φ[IMF(n)]=IMF 2 (n)-IMF(n+1)IMF(n-1) (8)

[0107] Where n is the sampling point, φ[IMF(n)] represents the energy operator at time n in IMF(n), and IMF(n-1) and represent the signal values ​​corresponding to time n-1 and n+1;

[0108] Then SDEO is defined as:

[0109]

[0110] In the formula, is the symmetric energy difference operator at time n in IMF(n), φ[IMF(n+1)] and φ[IMF(n-1)] represent the energy operators at time n-1 and n+1.

[0111] Embodiment 2: Figure 2 is the 10kV resonant grounding system simulation model described in the embodiment of the present invention; Figure 2 As shown in the figure, the system has 3 feeders, and only the detailed topology of the T-connection line as the main research object is listed, while other lines are simplified. The feeder parameters are shown in Table 1. Traveling wave acquisition devices F1, F2 and F3 are arranged at the M position at the head end of the main line, the N position at the end, and the P position at the end of the branch line. The system adopts overcompensation operation mode, with an overcompensation degree of 10%, an arc coil inductance of 0.646H, and a resistance of 6.09Ω. Constant power loads are used at the ends of each feeder, where P = 1.62MW, Q = 0.99Mvar. The fault time is 0.04s, and the sampling frequency is 10MHz. The wave speed v α is 2.9189×10 5 km / s.

[0112] Table 1

[0113]

[0114] When a single-phase grounding fault f1 with a grounding resistance of 100Ω occurs at the 16km point of the line head end, the fault voltage traveling wave at each measuring point within 39-41ms is analyzed; the line mode voltage at each position is decomposed using the SVMD method. Figure 3 This is the SVMD decomposition diagram of the line mode voltage at the M end. The number of adaptive decomposition modes is 7. Figure 4 It is the N-terminal line mode voltage SVMD decomposition diagram, and the number of decomposition modes is 4; Figure 5 The SVMD decomposition diagram of the line mode voltage at the P end, the number of decomposition modes is 5, and then the IMFk obtained by decomposition is calculated i The kurtosis value is calculated by the line mode voltage u at the M end. α1The IMF71 kurtosis value is the largest, which is 1065; the N-terminal line mode voltage u α2 The IMF42 kurtosis value is the largest, which is 760; the P-end line mode voltage u α3 The IMF53 kurtosis value is the largest, which is 210. The time when the initial wave head of the IMF with the largest kurtosis value reaches each measurement position is calibrated by SDEO, such as Figure 6 As shown, (a) is the SDEO wave head calibration diagram at the M end; (b) is the SDEO wave head calibration diagram at the N end; (c) is the SDEO wave head calibration diagram at the P end.

[0115] from Figure 6 It can be seen that the time when the initial fault wave head reaches the M end, N end and P end is 0.0400548, 0.0400513 and 0.0400274 respectively; according to the double-end traveling wave ranging formula, d1=16.011km, d2=14.989km; |1-d1 / l MT |=0.334>δ,|1-d2 / l NT |=0.211>δ, so the fault is located on the main line 16.011km away from the M end; for Figure 2 For the 10kV resonant grounding system shown in the figure, for different fault conditions, the positioning results are shown in Table 2:

[0116] Table 2

[0117]

[0118] It can be seen from Table 2 that when a single-phase grounding fault occurs in a resonant grounding system, under different fault initial phase angles, fault locations and transition resistances, the SVMD-based distribution network T-connected line fault location method can correctly determine the location of the fault point, with a small positioning error, and is also adaptable to single-phase high-resistance grounding in a resonant grounding system.

[0119] Distribution network T-connected line fault location system based on SVMD, such as Figure 7 As shown, the above-mentioned SVMD-based distribution network T-connected line fault location method includes:

[0120] Traveling wave detection device: installed at the head end, end end and branch end of the distribution network trunk line, used to collect three-phase voltage traveling wave signals;

[0121] Signal processing module: Receives the three-phase voltage traveling wave signal collected by the traveling wave detection device, performs phase mode transformation to obtain the voltage traveling wave α The voltage traveling wave is then decomposed using the continuous variational mode decomposition (SVMD) technique. α The modal components are decomposed to obtain the eigenmodal components of different frequencies;

[0122] Feature extraction module: calculate the kurtosis value of each modal component, select the modal component corresponding to the maximum kurtosis value as the characteristic mode, and use the symmetric difference energy operator (SDEO) to obtain the arrival time of the fault wave head in the characteristic mode;

[0123] Fault location module: According to the arrival time of the fault wave head and the two-terminal distance measurement formula, the distance from the fault point to the beginning and end of the main line is calculated to determine the specific fault location.

[0124] In summary, the present invention has the following beneficial effects:

[0125] 1) The voltage traveling wave signal is processed by continuous variational mode decomposition (SVMD) technology, which improves the extraction accuracy and resolution of fault features and avoids the problems of modal aliasing and information loss.

[0126] 2) The symmetric difference energy operator (SDEO) is used to accurately calibrate the arrival time of the fault wave head, which improves the accuracy and reliability of fault location.

[0127] 3) The present invention is applicable to complex distribution network structures, especially T-connected lines, and can realize rapid positioning of fault points.

[0128] 4) Through fast and accurate fault location, power supply can be restored quickly, reducing the duration and scope of power outages and improving power supply reliability.

[0129] 5) Rapidly locating the fault point helps maintenance personnel quickly find and repair the fault, thereby improving the speed of fault recovery.

[0130] 6) Accurate fault location helps to eliminate faults in a timely manner and prevent the fault from expanding, thereby enhancing the stability of the entire power system.

[0131] 7) Reduce the maintenance cost of the power system by reducing long power outages and repeated repairs caused by faults.

[0132] The embodiment of the present application provides an electronic device, which is applicable to the above-mentioned SVMD-based distribution network T-connection line fault location method, including:

[0133] Memory, used to protect computer programs and data;

[0134] Processor, used to run system programs.

[0135] The embodiment of the present application provides a computer storage medium, which is applicable to the above-mentioned SVMD-based distribution network T-connection line fault location method, and performs hierarchical confidentiality management on the above-mentioned system and data in accordance with confidentiality management requirements.

[0136] Those skilled in the art will appreciate that the embodiments of the present application may be provided as a system or a computer program product. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0137] The present application is described with reference to the flowcharts and / or block diagrams of the devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0138] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0141] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0142] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0143] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, commodity or device including the elements.

[0144] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A distribution network T-connection line fault location method based on SVMD, characterized by: include: Step 1: Use the traveling wave detection device installed on the distribution network line to collect the three-phase voltage, and perform phase mode transformation to obtain the α mode component of the voltage traveling wave; Step 2: Decompose the α-mode component of the voltage traveling wave using continuous variational mode decomposition (SVMD) to obtain eigenmode components of different frequencies; Step 3: Calculate the kurtosis value of each modal component, select the modal component corresponding to the maximum kurtosis value as the characteristic mode, and use the symmetric difference energy operator SDEO to obtain the arrival time of the fault wave head; Step 4: Determine the specific fault location based on the arrival time of the fault wave head and the two-terminal distance measurement formula.

2. The method for locating a distribution network T-connection line fault based on SVMD as claimed in claim 1, characterized in that: The specific process of step 1 is as follows: when a fault occurs in the T-connected distribution network line, the three-phase voltage traveling wave is obtained by using the traveling wave detection device installed at the head end, the end end and the end end of the branch line of the distribution network main line, and the Karenberg transformation is performed on the collected three-phase voltage traveling wave to obtain the voltage traveling wave α mode component u αi , i is the number of the traveling wave detection device i = 1, 2, 3; Assume that the fault occurs at t, the start time of sampling is (t-0.001) seconds, and the end time of sampling is (t+0.001) seconds, and a traveling wave signal with a data window length of 2ms is obtained.

3. The method for locating a distribution network T-connection line fault based on SVMD as claimed in claim 1, characterized in that: In step 1, the three-phase voltage is transformed by Karenberg to obtain the voltage traveling wave α mode component u αi The calculation formula is as follows: The calculation formula of the α-mode component of the voltage traveling wave is: in αi =(in i_a -in i_b ) / 3 Among them, u i_a 、u i_b The a-phase and b-phase voltages collected by each traveling wave detection device.

4. The method for locating a distribution network T-connection line fault based on SVMD as claimed in claim 1, characterized in that: The specific process of step 2 is: perform SVMD decomposition on the α-mode component of the voltage traveling wave, adopt the method of obtaining the approximate value of the modal center frequency and continuously extracting the modal components, adaptively determine the number of decomposition modes K, and obtain the eigenmodal components of different center frequencies: Among them, SVMD(u αi ) represents the α-mode component u of the voltage traveling wave αi Perform SVMD decomposition, IMFk i (n) is the kth modal component after SVMD decomposition of the α-mode component of the voltage traveling wave of the i-th traveling wave detection device, k=1, 2, ..., K; n is the sampling point.

5. The method for locating a distribution network T-connection line fault based on SVMD as claimed in claim 1, characterized in that: The specific process of step 3 is: calculate each modal component IMFk i The kurtosis value of (n) is defined, and the modal component corresponding to the maximum kurtosis value is defined as the characteristic mode. The symmetric difference energy operator SDEO is used to obtain the arrival time t of the fault wave head in the characteristic mode. i .

6. The method for locating a distribution network T-connection line fault based on SVMD as claimed in claim 1, characterized in that: The specific process of step 4 is: calculate the distance d1 from the fault point to the beginning of the main line and the distance d2 from the fault point to the end of the main line according to the two-terminal distance measurement formula: In the formula, l MN is the line length from the beginning of the trunk line to the end of the trunk line, v α is the α modulus wave velocity, L and C are the line inductance and capacitance parameters; when When the fault is determined to be located at the branch point T or on the branch line, where l MT is the distance from the beginning of the trunk line to the T branch point, l NT is the distance from the end of the trunk line to the branch point T, δ is the set threshold, δ=0.005; the distance from the fault point to the end of the branch is: In the formula, l MP It is the line length from the beginning of the main line to the end of the branch line; Otherwise, the fault distance is on the main line, and the distance from the head end of the line is d1.

7. The distribution network T-connection line fault location system based on SVMD is characterized by: The method for locating a distribution network T-connection line fault based on SVMD according to any one of claims 1 to 6 comprises: Traveling wave detection device: installed at the head end, end end and branch end of the distribution network trunk line, used to collect three-phase voltage traveling wave signals; Signal processing module: receiving the three-phase voltage traveling wave signal collected by the traveling wave detection device, performing phase mode transformation to obtain the α-mode component of the voltage traveling wave, and then decomposing the α-mode component of the voltage traveling wave using the continuous variational mode decomposition (SVMD) technology to obtain the intrinsic mode components of different frequencies; Feature extraction module: calculate the kurtosis value of each modal component, select the modal component corresponding to the maximum kurtosis value as the characteristic mode, and use the symmetric difference energy operator (SDEO) to obtain the arrival time of the fault wave head in the characteristic mode; Fault location module: According to the arrival time of the fault wave head and the two-terminal distance measurement formula, the distance from the fault point to the beginning and end of the main line is calculated to determine the specific fault location.

8. A processor, characterized in that: The method is configured to execute the SVMD-based distribution network T-connected line fault location method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the distribution network T-connected line fault location method based on SVMD described in any one of claims 1 to 6 is implemented.

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